افزايش روزافزون كاربرد سيست مهاي مخابراتي و راداري په نباند و حساسيت اين تجهيزات به تداخ لهاي الكترومغناطيسي (EMI) ، نياز مبرمي به توسع هي جاذبهاي موج پيشرفته با قابليت جذب بالا و پهناي باند عملياتي گسترده ايجاد كرده است. جاذبهاي فراماد هاي (Metamaterial Absorbers - MMA) به دليل امكان كنترل بيسابق هي پارامترهاي مؤثر الكتريكي و مغناطيسي از طريق طراحي هندسه، پاسخي ايد هآل براي اين نياز فناورانه هستند. با اين حال، اغلب اين ساختارها ذاتاً باند باريكي دارند . هدف اصلي اين پاياننامه، طراحي، بهين هسازي و تحليل يك جاذب فراماد هاي صفح هاي فوقنازك و په نبان دو قابل تنظيم براي كاربرد در محدود هي فركانسي X/Ku ( ??.?? تا ??.? گيگاهرتز( است. در اين راستا، ابتدا يك ساختار پايه مرور شد و سپس از طريق يكرويه گا مب هگام سيستماتيك، با اعمال تغييرات هدفمند در هندس هي سلول واحد، نظير افزودن حلق ههاي ه ممركز، ايجاد و تنظيم شكا فهاي تشديدي و معرفي مسيرهاي مارپيچ، ساختار اصلي توسعه يافت . مكانيسم عملكرد مبتني بر ايجاد همزمان رزونان سهاي الكتريكي و مغناطيسي و كوپلينگ مؤثر بين آ نها است كه منجر به تطبيق امپدانس بهينه با فضاي آزاد و در نتيجه كاهش چشمگير بازتاب ميشود . براي تحليل عملكرد، از شبي هسازي الكترومغناطيسي تما مموج در نرمافزار CST Studio Suite استفاده شد و پارامترهاي پراكندگي، توزيع ميدان و جريان سطحي به دقت بررسي گرديد. در مرحلهي بعد، اثر آراي هسازي و كوپلينگ متقابل بين سلولها با بررسي دو آرايه با فواصل سلولي متفاوت مورد مطالعه قرار گرفت . دستاوردهاي كليدي اين پژوه شعبارتند از : ? ( دستيابي به يكسلول واحد بهينه با ضخامت تنها ?.??? ميل يمتر معادل تقريبي ? ? در فركانس مركزي كه جذب بالاي ??? را در پهناي باند ?.?? گيگاهرتزي ارائه م يدهد و در نقاط اوج به بازدهي حدود ??? ميرسد. ? ( نشان دادن اين كه كوپلينگ متقابل در آراي ههاي فشرد ه ميتواند به عنوان يك پارامتر طراحي مثبت عمل كرده و منحني پاسخ را هموارتر نمايد . ساختار پيشنهادي به دليل سازگاري با فناوري ساخت PCB و عملكرد پايدار در زواياي تابش مختلف، گزينهاي عملي و اميدبخش برا ي كاربرد در سيستمهاي راداري، مخابراتي نوين و فناور يهاي كاهش سطح مقطع رادار ي (RCS) محسوب ميشود  

 This research investigates and optimizes routing protocols in Internet of Things (IoT) based telecommunication networks. Considering the increasing number of connected devices, resource constraints, and the need for fast and stable data transmission, optimization of routing protocols plays a key role in improving network efficiency, reducing energy consumption, and increasing reliability. In this research, an improved DCUR algorithm with the Whale Optimization algorithm is proposed to select optimal routes and balance load distribution in the IoT network. This method determines the optimal data transmission routes using criteria such as received signal strength (RSS), distance between nodes, energy status, and temperature of nodes. Simulation results show that implementing the optimal protocol reduces data transmission latency, increases network lifetime, reduces

In recent years, intelligent video surveillance systems have played a vital role in enhancing safety and security across various environments. This thesis presents the design and implementation of a comprehensive real-time detection and alerting system capable of identifying specific hazardous objects, including various weapons (pistols, swords, knives), incidents (accidents, fire, smoke), and violence. The proposed method is based on the utilization of two distinct object detection models founded on the YOLO11 (Nano version) architecture. The primary model is used for detecting general objects such as humans and vehicles, while the secondary model—trained on a customized dataset—focuses on the precise identification of hazardous items. This custom dataset was collected, labeled, and integrated using Roboflow tools. The software architecture consists of a processing core based on PyTorch (with CPU or GPU execution capabilities) and OpenCV. To manage concurrent processes, a threading-based system is employed to decouple video processing from the user interface. An advanced Graphical User Interface (GUI) has been developed using the PyQt6 library, allowing for the adjustment of various parameters such as confidence thresholds, input modes (webcam, video/image files), and the display of system logs. A key feature of the system is the multi-frame verification mechanism designed to prevent false alarms. Furthermore, upon threat detection, an immediate audio alert system (including sirens and voice messages) is activated, and the final output video is merged with the original audio and saved. Experimental results demonstrate that the system is capable of identifying hazardous objects in various scenarios with high accuracy and speed, providing a real-time response.   

The growing energy consumption in buildings is one of the major challenges to sustainable development, especially in countries such as Iran with diverse climates and high dependence on fossil fuels. Employing passive solar strategies such as the solar chimney, together with innovative technologies like thermochromic and electrochromic coatings, can play a significant role in reducing heating loads and improving thermal comfort. This study aims to investigate the performance of a hybrid system consisting of a solar chimney integrated with these smart coatings and to compare their effects during January 2022. The research was conducted in two cold Iranian climates: Tehran and Ardabil. The designed system comprised a vertical solar chimney with glazed façade, internal absorber surface, and inlet/outlet vents, simulated in DesignBuilder and EnergyPlus software. Input data included climatic datasets (EPW), building material properties, optical and thermal characteristics of the coatings, and window-to-wall ratios of 30% and 70%. Simulations were carried out for three consecutive days (10–12 January 2022) within the time interval of 09:00–15:00. Five main scenarios were defined: (1) a base model without solar chimney or smart coatings in a test room of 3 × 2.7 × 2.7 m³; (2) addition of a solar chimney with single glazing at 30% and 70% WWR; (3) replacement of single glazing with double glazing at 70% WWR; (4) application of thermochromic coating on the chimney glazing in Scenario 3; and (5) application of electrochromic coating on the glazing in Scenario 3. Results showed that thermochromic coating increased average indoor air temperature by 4.41 °C in Tehran and 6.06 °C in Ardabil, reduced daily heating demand by 22.5% and 24.9%, and improved thermal comfort indices. Overall, findings highlight the efficiency of integrating solar chimneys with smart coatings in cold Iranian climates, providing a basis for future research on combining these technologies with other building energy management systems.   

   Lithium-ion batteries are the powerhouse of the digital electronic revolution in this modern society. However, a critical issue is the thermal management of these devices' batteries to ensure rapid charging or discharging, safe operation, and efficient performance by regulating their temperature within the optimal range. Nevertheless, existing battery thermal management methods, including air and liquid cooling (known as active cooling), not only occupy significant space but also struggle to overcome battery cooling at high temperatures due to their heavy weight and limited energy consumption, leading to reduced vehicle efficiency. In contrast, passive cooling methods, referred to as phase change material (PCM)-based battery thermal management technology, have demonstrated favorable performance by saving weight and energy consumption. However, the low thermal conductivity and leakage of PCMs have limited their application in battery thermal management. In this thesis, the thermal modeling of a battery using a heater was experimentally investigated. Additionally, several battery thermal management systems, including PCMs with three different mass percentage ratios composed of paraffin and beeswax, and carbon-based aerogel/PCM composites, were fabricated. The results showed that using a PCM composed of 75% paraffin and 25% beeswax alone increased thermal performance by up to 56% compared to the other two ratios. Furthermore, using raw aerogel/PCM composed of 25% paraffin and 75% beeswax resulted in a 31% increase in thermal conductivity compared to the PCM alone. However, black aerogel/PCM composites showed acceptable performance across all ratios and resulted in a 46% increase in thermal conductivity. Overall, the use of a black aerogel/PCM composite composed of 25% paraffin and 75% beeswax was considered the optimal thermal management system due to its highest thermal conductivity.

   Common signals recorded from neural activity in the brain, such as EEG or MEG, are non-stationary signals. Therefore, time-frequency analysis tools are well suited to analyze such signals. Over the years, time-frequency analysis has found numerous applications in computational neuroscience, from diagnosing diseases such as schizophrenia in adults to understanding autism spectrum disorders in children and identifying seizures in infants. With advances in computational resources and various types of imaging tools, time-frequency analysis is on the verge of becoming one of the most important mainstream tools in the field of computational neuroscience. We want to examine the methods of examining the properties of brain networks using time-frequency representation tools. In this thesis, time-frequency based phase synchronization methods are introduced and analyzed. Time-frequency distribution includes WVD, Rihaczek, spectrogram, EMBD, ... methods, which are briefly reviewed. Using time-frequency representations, we can access the time-varying properties of brain networks. The results presented in this thesis show that time-frequency-based phase synchrony is a good measure for examining the effective connections of brain networks, which allows us to use powerful analytical tools to investigate and better understand brain networks and their dynamic behavior over time. The results of this evaluation show that phase synchronization methods based on time-frequency representation can have applications in analyzing brain networks, including studying brain signals of infants and adults, diagnosing diseases such as epilepsy, and studying and helping to diagnose diseases such as Parkinson's and autism, which can lead to better and more effective treatment  

 Breast cancer is one of the most common types of cancer among women, which is caused by the abnormal growth of breast cells. Determining the boundaries and analyzing the shape of tumors in ultrasound images are considered to be key aspects of medical diagnosis of breast cancer. Accurate identification of tumor edges and accurate diagnosis of cancer have always created challenges for doctors due to image noise or tumor characteristics. Therefore, in this thesis, an intelligent and automatic method for identifying the border of breast masses and classifying breast cancer using advanced techniques of deep learning and machine learning based on ultrasound images is presented. The data used includes 647 ultrasound images of women between 25 and 75 years of age with benign and malignant masses collected at Bahia Hospital. In the pre-processing stage, the images were removed from unnecessary noise and resized to the standard size of 256,256 pixels. Then, using Deep Lab method 3, the images were accurately segmented and the boundaries of the masses were determined. Next, textural and statistical features were extracted from the masses and using different machine learning models, including support vector machine (SVM), nearest neighbor (KNN) and decision tree, the masses were classified into benign and malignant categories. The results show that the decision tree model with an average accuracy of 89.92%, sensitivity of 73.96%, detectability of 97.72% and a score of 19.3% has performed best in breast cancer classification. This research is considered as an important step towards improving the quality of health and treatment services in breast cancer diagnosis and can help to improve the process of diagnosis and treatment of this disease.

In this research, desulfurization through an adsorption method using activated carbon derived from oak seed husk was investigated for a model fuel consisting of n-hexane solvent and the sulfur compound dibenzothiophene. The activation process utilized chemical activation with phosphoric acid. The adsorption process was conducted in a batch system, and the nitrogen adsorption-desorption isotherm for the synthesized sample was >  

Classifying non-stationary signals, such as electroencephalogram (EEG) signals, is a major challenge in signal processing. Non-stationary signals are signals whose statistical properties, such as mean and variance, change over time, making them more difficult to analyze compared to stationary signals, where these properties remain constant. EEG signals, commonly used to study brain activity, are non-stationary, meaning their patterns change over time. Detecting abnormal brain activity, like epilepsy, which shows different patterns from normal activity, requires advanced techniques to classify these signals accurately. In this study, we explore how well a combination of Continuous Wavelet Transform (CWT) and pre-trained Convolutional Neural Networks (C  ) can classify non-stationary signals. As a case study, we use multi-channel neonatal EEG data, where each segment of the signal is labeled as either healthy or showing a seizure. A novel approach was developed in this research, where continuous wavelet transform representations from all EEG channels were combined into a single RGB image by stacking the continuous wavelet transform representations into the red, green, and blue channels. This creates a multivariable image that captures important time-frequency information from all EEG channels. These images were then classified using two advanced convolutional neural network models, ResNet and MobileNet, which were pre-trained on large datasets. Both models achieved high classification accuracy, with results above 80%, as well as high area under receiver operating characteristic curve scores, also above 80%. The findings show that combining continuous wavelet transform with convolutional neural networks is effective for recognizing patterns and classifying non-stationary signals. This work highlights the potential of this method, especially for medical applications like detecting seizures in newborns.

The design and construction of water wells are unfamiliar to many engineers. Due to this unfamiliarity, their design is often done inappropriately or completely ignored. In the mechanical design of ground source heat pump systems, we should be familiar with the terminology of water wells and key issues related to their construction. In wells, the still water level and the pumping level are two different states, and in case of low water or no water, sensors and automatic cut-offs can remove the float from the circuit. In this research, we have designed a circuit that differs from existing circuits in that the circuit we have designed can be adjusted at any water level.   

In this thesis, the investigation and management of interference for device-to-device (D2D) communication in fifth generation (5G) networks has been discussed. Due to the ever-increasing number of devices connected to the network and the need for more transmission with high speed and low latency, interference management in D2D communication has become a fundamental challenge. As one of the key technologies in 5G networks, D2D communications allow devices to communicate directly with a connection without the need for a base station. This increases efficiency and at the same time reduces, but can increase interference in the network. To solve this issue, two optimization methods using meta-heuristic algorithms are compared: Genetic Algorithm (GA) and Wall Optimization Algorithm (WOA). Genetic algorithm is mainly used in optimization problems due to its high search power and ability to adapt to complex problems. This algorithm searches for optimal solutions using selection, intersection and mutation operations. On the other hand, Wall's optimization algorithm is a new method i  ired by predator behavior that searches for optimal solutions by bubble and circular search. To evaluate the performance of these two algorithms, MATLAB software is used for simulation. Evaluation criteria included efficiency, execution time, and performance volume increase (CDF). The results of the simulations show that the Wall Algorithm (WOA) has performed significantly better than the Genetic Algorithm (GA) in reducing the interference and improving the efficiencies. Also, WOA algorithm has shown shorter execution time and better performance compared to GA. These results show that the optimization algorithm can be used as a treatment solution to manage interference in D2D communication in 5G networks. These findings can help improve the performance of future wireless networks and translate into increased quality of service (QoS) for end users.  

Sleep is a state of reduced mental and physical activity and is vital for part of daily activities. When sleep is insufficient, several problems such as learning disorders and increased risk of stress diseases such as mood disorders and cardiovascular diseases appear. The older population, adults over 60, have more problems with sleep and sleep disorders. They are more prone to sleep disorders, such as insomnia. These problems together can lead to an increased risk of other diseases. A common condition among the elderly is dementia. Lack of sleep and bad sleeping habits are risk factors for dementia, however, sleep is not the only risk factor for dementia. Education, age and gender of people are other factors that play a role in the risk level of a given person. Since data is available on the older population, we can make inferences about different aspects of their lives. Machine learning is a program that uses experience to learn and make predictions based on its experiences. These programs can find the patterns in the data or explain the relationship between them. We use ML to study the relationship between sleep and dementia. We also use other features such as methodological approaches and other aspects of sleep such as REM sleep, so using machine learning with different features is useful in other aspects of sleep. The current thesis evaluates different methods to investigate sleep disorders on dementia using five machine learning algorithms (gradient boosting, logistic regression, Gaussian smoothing, random forest and support vector machine). Data on the older population (60+) in Sweden from the Swedish National Study on Aging and Care - Blacking = 4175 (number of samples) Algorithm from 10-fold stratified cross-validation to obtain results, including Brier score to check accuracy And feature importance is used to investigate factors affecting dementia. Algorithms use 16 features that are based on personal factors and sleep disorders.  

 Detecting brain tumors from the levels of MRI images is one of the biggest challenges in the world of artificial intelligence and engineering sciences Medicine goes to the number. Brain tumors, which can lead to the death of people with their growth, need to be staged Identify, identify. There are two main categories of tumors, which include benign and malignant tumors. made An intelligent medical diagnosis system in the field of brain tumor diagnosis from the levels of MRI images is one of the important parts In medical engineering science, it is numbered, which can help doctors in the early detection and identification of tumors and then diagnosis. Care and maintenance of people until full recovery is helpful. Glioma is the most common malignant brain tumor with grades It is different, which greatly determines the survival rate of patients.Tumor segmentation and grading using contrast-enhanced imaging Magnetic resonance imaging (MRI) is essential for diagnosis and treatment planning. To achieve this clinical need, a feature Part of Convolutional Neural Networks (CNN) based on UNet network for tumor segmentation and transmission Then, based on the pre-trained convolution of the Vgg16 base and a perfection classifier for tumor grading, it is developed. Segmentation and gradation models from the same pipeline T1 - Coping, weak liquid damping inversion recovery (FLAIR) and post-contrast T1 MRI images of 110 low-grade glioma patients (LGG) for teaching and evaluating the use of do Dice similarity coefficient (DSC) and tumor detection accuracy obtained by the segmentation model are 0.84 and 0.92, respectively.Model Grading LGG with accuracy, sensitivity and specificity of 89.0, 87.0 and 92.0 respectively at the level of MRI images and 95.0, 97.0 and 98.0 classifies patients as benign and malignant. This work has the potential to use deep learning MRI images to provide a non-invasive tool for simultaneous and automated tumor segmentation, diagnosis and tumor grading shows for clinical applications.

One of the biggest problems of mobile phone operators is mobile network coverage in densely populated urban areas; In mobile networks, communication signals are transmitted between mobile phones and transceiver base stations. These stations include telecommunication equipment such as antenna, radio, processing equipment and other electronic components, which enable the sending and receiving of wireless signals. Factors such as the location of urbanization do not allow the correct transmission of signals from the operator to the subscriber. Artificial obstacles such as buildings block the passage of mobile waves so that the waves reach the subscriber in a weakened form; In dense urban areas, the number of mobile phone users is very high, and synchronizing a large number of users with the limited space of network servers is facing problems. There are a large number of telecommunication equipment and wireless networks in these areas, which cause interference in the radio space. This interference reduces the efficiency and coverage of the network. The subject investigated in this thesis is the improvement of mobile network coverage using the transfer and control of changeable parameters in the transceiver base station in the urban environment. Blind spots in the mobile network are areas where the direct signal from the transceiver base station does not reach them and the quality of communication decreases there. Reducing blind spots is very important. In this thesis, a new software model is presented to improve the coverage of city area  

آنتن‌هاي آرايه‌اي 1 از چندين آنتن مستقل تشكيل شده‌اند كه به صورت هم‌محور يا غير هم‌محور در كنار يكديگر قرار مي‌گيرند. اين آنتن‌ها كاربردهاي فراواني در حوزه‌هاي مختلف مانند ارتباطات بي‌سيم، رادار، سنجش از دور و غيره دارند. يكي از چالش‌هاي مهم در طراحي آنتن‌هاي آرايه‌اي، اثر تزويج متقابل 2 بين المان‌هاي آنتن است. اين اثر باعث مي‌شود كه انرژي سيگنال ارسالي از يك المان، به المان‌هاي ديگر نيز منتقل شود. اين امر مي‌تواند باعث كاهش بازده آنتن، تغيير الگوي تابش و ساير مشكلات شود. در اين پژوهش، از دو روش ساختار DGS و عنصرها پارازيتي براي كاهش اثر تزويج متقابل استفاده شده است. ساختار DGS يك تكنيك مؤثر براي بهبود خصوصيات آنتن‌هاي ريزنوار است. اين ساختار با ايجاد تغييراتي در ساختار زمين آنتن، تأثيرات قابل توجهي در عملكرد آنتن دارد. عنصرها پارازيتي نيز هر المان غير از خود آنتن‌هاي فعال كه در ميدان نزديك آنتن‌هاي آرايه‌اي قرار مي‌گيرد، به عنوان عنصر پارازيتي تعريف مي‌شود. نتايج اين پژوهش نشان مي‌دهد كه استفاده از ساختار DGS و عنصرها پارازيتي 3 ، مي‌تواند اثر تزويج متقابل را به ميزان قابل توجهي كاهش دهد. اين امر باعث بهبود بازده، الگوي تابش و ساير مشخصات آنتن مي‌شود. نتايج اين پژوهش مي‌تواند به طراحان و محققان در زمينه آنتن‌ها كمك كند تا طراحي‌هاي بهتر و با عملكرد بهتري را ارائه دهند. اين نتايج همچنين مي‌تواند در دستيابي به  

در سالهاي اخير پژوهش و مطالعه بر روي سيگنالهاي الكترومايوگرافي به دليل سادگي ثبت اين سيگنالها و نمود خوبي كه از فعاليت بدني افراد دارد توسط محققان حوزه مهندسي پزشكي مورد توجه ويژه اي قرار گرفته شده است. يكي از راه هاي بررسي عملكرد، جداسازي موقعيت وجهت حركت عضلات وتعيين نيروي آنها، ثبت و پردازش سيگنال EMG (الكترومايوگرافي) مي باشد. در پژوهش هاي پيشين به دليل وابستگي موقعيت عضلات به عوامل متعدد، محدوديت¬هايي در ارايه¬ي يك روش به منظورپيش بيني موقعيت عضلات ايجاد شده است. به علت اهميت اين رابطه در مسايل مختلف اسكلت عضلاني و در زمينه¬ي آناليزحركت، ارايه¬ي راهكارهايي براي تخمين تئوري نيروي عضلاني امري ضروري است كه در اين پژوهش به آن پرداخته شده است. هر چند در مطالعات مختلف،روابط گوناگوني براي اين منظور مطرح شده است، اما پيچيدگي ارتباط ميان موقعيت و جهت حركت ايجاد شده در عضله و عوامل مؤثر در آن، باعث شده است تا تلاش براي ارايه¬ي يك روش با بازده محاسباتي بالا با مشكلات زياد روبه روشود. در اين پايان نامه روش تخمين موفعيت و جهت عضلات از روي مدل هاي پارامتري سيگنال الكترومايوگرافي به كمك كلاسيفاير مبتني بر شبكه عصبي عميق و با كمك سه دسته از آنتروپي¬هاي شناخته شده و پركاربرد از قبيل آنتروپي شانون ريني و تساليس مورد بررسي قرار گرفته است. نتايج به دست آمده از شبيه سازي¬ها و دستيابي به دقت 93 درصد حاكي از اين بوده كه استفاده از اين فرايند براي تخمين جهت و موقعيت عضله دست عملكرد مطلوبي را در بر داشته است. 

  Abstract: In this project, firstly, a 2-port cut rectangular microstrip patch antenna (port A: frequency 1.756 and port B: 2.47 GHz) with a fractal structure engraved in the patch, for use in the RFEH system in the LTE band in order to improve the performance in harvesting the energy of electromagnetic waves. The original patch antenna (1) without fractal geometry is designed as the proposed antenna (1). The antenna is made on FR4 substrate with relative transmittance of 4.4, loss tangent of 0.02 and dimensions of 48 x 48 mm2. Also with new changes. In the structure and dimensions of the primary antenna (1) without fractals, with the aim of further reducing the size of the antenna, a new two-port right-angled triangular microstrip patch antenna with a resonant frequency of 2.4 GHz in each port is obtained as the primary antenna (2), which is obtained by applying changes In the right-angled triangular patch antenna, the gain efficiency of the antenna is improved compared to the previous state of the proposed antenna (2). In the first chapter: definitions, introduction, purpose, history and background of the research are introduced. In the second chapter: the structure, challenges and components of the RFEH system (antenna, impedance matching network and rectifier circuit) are presented, in the third chapter: first, the theory and technique of the proposed antenna design (1) and (2) are discussed. Then, the theory and technique of designing a horn transmitter antenna (RF transmitter) and a broadband rectifier including a voltage doubler rectifier circuit to reduce losses, the role of the Schottky diode HSMS2852 used in this part is very effective, also for a good match between The antenna and the rectifier circuit use an innovative matching network that is a combination of microstrip transmission lines and compact modules. The rectifier is made on the FR4 substrate with relative transmittance of 4.4, loss tangent of 0.02 and dimensions of 48 x 48 mm2. The use of fractal structure in the proposed antenna (1) makes effective use of space, reduces the size of the antenna, increases the effective length of the antenna and improves the reflection coefficient. And the change in the structure of the primary antenna patch (2) is from a rectangle to a right-angled triangle in order to reduce the size of the antenna. Also, the purpose of having 2 ports of antennas is to compress the volume of the antenna and increase the energy harvesting of electromagnetic waves. In the fourth chapter: at the beginning, a simple microstrip patch antenna without fractal structure is simulated as the primary antenna (1). And as a result, it led to the shift of resonance frequencies to the desired frequency in the LTE band and the improvement of the S11 coefficient and efficiency compared to the primary antenna (1). In the next step, the two-port microstrip patch antenna in the form of a simple right-angled triangle (initial antenna 2) is simulated with new dimensions for use at 2.4 GHz frequency (in both ports) and finally by applying special changes to the initial triangular patch antenna ( 2) We see the optimal gain efficiency and realization of the proposed antenna (2). By simulating the trumpet antenna (as a transmitter of RF signal to the receiving antennas) and the matching network and the desired rectifier circuit, and in the final stage, by connecting each of the antennas in the role to the matching network and the rectifier circuit, Rectna is formed. And then the simulated output voltage obtained from the proposed antenna (1) is compared with the original antenna (1) and the proposed antenna (2) with the right triangle antenna (primary antenna 2) and finally the result obtained is due to the better performance of the proposed antenna (1) and (2) in harvesting energy and subsequently producing more voltage compared to the primary antennas.

Analysis of Four Electromagnetic Launcher and Calculated the Mutual Gradient Inductance using 2D-FEM

   Smart antenna is one of the latest technologies that has a higher capacity in wireless networks by effectively reducing multi-path and co-channel interference. Smart antennas use a set of radiating elements arranged in an array. In a smart antenna system, the arrays are not smart by themselves, it is the digital signal processing that makes them smart. The method of combining signals and then focusing radiation in a specific direction is often referred to as digital. Beamforming will be widely used in the term. In this thesis, it consists of a presentation of 8 elements. Each element or antenna is a T-shaped dipole designed on an FR4 substrate with a relative electrical conductivity of 4.4 and a thickness of 1.60 mm. Each element is fed using 50-ohm microstrip lines. For each row, four elements of one ground are considered, in other words, four arrays facing each other have separate ground. The operating frequency is equal to 3.5 GHz and the arrangement of the array elements is designed in two rows of four facing each other. The obtained frequency bandwidth is 3.3-3.7 GHz and the radiation efficiency for each antenna is about 97% and the overall efficiency is about 85%.

با توجه به شيوع گسترده بيماري هاي واگيردار در جهان مدل‌هاي رياضي مي‌توانند به پيش‌بيني و كنترل اين پاندمي كمك كنند. پاندمي بيماري نشان داده كه كشورها عليرغم توسعه يافتگي و دسترسي به منابع و تجهيزات در مقابل يك بيماري جديد ناشناخته بايستي زير ساخت‌هاي فيزيكي اعم از بيمارستان‌ها، مراكز بهداشتي درماني و نيروي انساني را در برابر بحران آماده نمايند. اپيدمي ها ممكن است ظرفيت بيمارستاني ارائه خدمات بهداشتي درماني را در هم بشكنند و منابع مادي و انساني، از جمله فضاي بيمارستان، تجهيزات و داروها براي برآوردن تقاضا كافي نباشند، مخصوصاً در مورد اپيدمي كه چندين هفته يا چندين ماه طول بكشد و به ويژه اگر بحران‌هاي همزمان اتفاق افتد، بيمارستان جهت كمك به اقدامات انجام شده در كنترل اپيدمي، بايد بسياري از كاركردها و منابعش را مهار كرده و به طور هماهنگ شده مورد استفاده قرار دهدكه برآوردن اين الزامات مي‌تواند چالش برانگيز باشد. يك اپيدمي نياز به مركز بهداشتي درماني دارد تا اولويت‌هايش را تغيير داده و با روش‌هاي كاري منطبق باشد تا پاسخي سيستميك و هماهنگ به يك موقعيت با   سرعت در حال تغيير بدهد.   بر اساس پيش‌بيني و صحت نتايج مربوطه، آماده‌سازي مراكز درماني در مقابل بحران از جنبه‌هاي مختلف مديريتي، ارتباطات، منابع انساني، تامين تجهيزات، دارو و ساير خدمات تشخيصي، درماني و پشتيباني مورد نياز بيماران، همراهان و كاركنان بهداشت و درمان مهم‌ترين هدف اين تحقيق مي‌باشد كه با مدل‌سازي همه‌گيري بيماري در شرايط مختلف محقق مي‌شود. شبيه سازي با در نظر گرفتن مواردي مانند: تاثيرات اندازه جمعيت، دوره نهفتگي بيماري، دوره بيماري، نرخ آلودگي، مكان‌هاي آلوده بر گسترش بيماري، واكسيناسيون عمومي و ... اجرا و تحليل خواهدشد.

  On March 11, 2020, the World Health Organization (WHO) declared thecoronavirus (covid-19) as a pandemic due to its widespread seriousnessthroughout the world. The new corona virus caused by the SARS-COV2 virusoriginated in the city of Wuhan, China and has spread worldwide. Covid-19 is arespiratory disease that has infected so many people around the world that theWorld Health Organization (WHO) declared this disease as a pandemic due to itshigh mortality among people with poor medical history. has done.The corona virus (covid-19) pandemic has had a negative impact on thehealth of people worldwide. To reduce the impact of this widespread epidemic,it is essential to identify covid-19 cases as quickly as possible. Earlydetection of the virus is very important in the complete recovery of thepatient, but if it is detected at a later stage, it can be fatal. Since thesymptoms of the corona virus are similar to the flu, it is difficult to detectit, so we are looking for a method that will detect the corona virus in theshortest time and with the highest accuracy.Currently, CT scans (computed tomography) and X-rays are the most commonand effective methods used by hospitals to evaluate lung images for covid-19.Since there is a problem with RT-PCR kits being stained and also these kitshave a sensitivity of less than 60%-70%, researchers are trying to find thebest and fastest methods for identifying Covid-19.Chest X-ray images combined with emerging artificial intelligence (AI)methods, especially deep learning (DL) algorithms, have become a suitableoption for initial screening of Covid-19.  Keywords: Covid-19, X-ray, deep learning, artificial intelligence, CT,RT-PCR.

Abstract: In this thesis, a four-element Adcock directional antenna is designed and the angle of the input (received) signal is calculated. Considering that one of the sources of error is the interaction effect, we have gone to design an EBG to reduce the interaction effect. First, we have designed an EBG between two dipole antennas for the 750 MHz frequency band. Then we have designed a four-element Adcock array and checked its error. Then, for this Adcock array, we have designed an EBG and checked its error and compared it with the case without EBG. We observed that the error in this case has decreased by about 3 degrees (more than half).   

In order to diagnose epilepsy, a series of features must be extracted from the EEG signal of the patients, in order to extract the features, the entropy criterion has been used. In this research, permutation entropy, which is the most suitable for the analysis of biomedical signals, is investigated. The purpose of this thesis is to implement one-variable and multi-variable entropy and use it for the analysis of biomedical signals. The experimental results show the highest >  

The design of a reconfigurable antenna that is able to change its radiation pattern characteristics at a certain frequency in an organized and reversible manner using control switches such as (semiconductor switches, microelectromechanical switches and varactor switches), and application in the fifth generation of wireless communication networks have The present research method is descriptive-analytical and practical in terms of applying the results. Collecting the required data and information is also done by reading articles, books, using the knowledge of professors and observing the microstrip antennas that have been designed and built in the past, and to analyze and analyze the obtained data and simulate the desired models, high frequency circuit simulation software is used. CST has been used. In the research, a microstrip antenna (printed circuit patch antenna) has been designed to achieve reconfiguration of the radiation pattern. Two capacitors work simultaneously to achieve the radiation pattern reconfiguration operation. This microstrip antenna is i  ired by the design of a circular loop. The basic structure of the loop is changed and the capacitors are integrated into the patch. By changing the capacity of the capacitors in the range of (0.01-10) picofarad, the radiation pattern of the antenna can be changed to six different modes. An electromagnetic model of the proposed antenna is simulated in CST software for numerical analysis and observation of different radiation patterns. The proposed antenna structure has been implemented and built using a material (FR4) substrate with relative transmittance (4.4) and loss tangent (0.02) and thickness (1.6) mm. Antennas have been used since 1886 to send and receive information. They have special characteristics, this divides antennas into two categories, the first category is antennas with fixed characteristics and the second category is tunable antennas, tunable antennas are divided into several categories, the main ones are tunable antennas (frequency, polarization, bandwidth and radiation pattern), these types of antennas are very useful in the technology of the fifth generation of wireless communication systems. One of the achievements of this research is the design and simulation of a microstrip antenna that can reset the radiation pattern by using capacitors as control switches in order to change the surface current and as a result change the radiation pattern of the antenna.   

  Metal pipes have been widely used in engineering structures for a long time. For example, pipes are used in the transfer of fluids such as oil and water or in the construction of bridges, masts, car chassis, airplanes, military industries, etc. Pipes are also used for torque transmission in cars, industrial equipment and deep well drilling rigs, etc. Therefore, due to the constant presence of metal pipes in various industries, it is sometimes necessary to change the geometrical dimensions of the cross-section of the pipe to suit the work duty by creating local deformations. In this thesis, the process of local lateral compression of thick-walled pipes has been investigated by two experimental methods and numerical simulation. In this process, the pipe is placed horizontally between the upper and lower molds. The molds are cylindrical and the axes of the molds and the tube are perpendicular to each other. To investigate the behavior of plastic deformation, two types of aluminum tubes with the same outer diameter and different inner diameter were selected and three similar samples were made from each type. The real stress behavior in terms of the real strain of the aluminum material was extracted from the simple tensile test. The tubes are placed horizontally on the lower fixed mold and plastically deformed by the upper mold which is connected to the moving part of the press machine. Then, the geometric dimensions of the deformed area of the tubes have been measured for different press courses. The geometric shape of the deformation zone and the experimental data of the deformation forces have been compared with the process simulation results in Abaqus software. Examining and comparing the results of two experimental and simulation methods revealed that the dimensions of the deformed area in both methods have a good match. The forming forces calculated by Abaqus software show slightly higher values than the experimental values, which can be considered a good validity for the data considering the conditions of the problem.

  Heavy metal pollution is one of the concerns that has become a global concern, and cadmium is one of the types of metals that are very dangerous and carcinogenic. Bioremediation is one of the environmentally friendly methods that is a suitable alternative to chemical methods. Biomineralization is one of its subcategories, which is a process during which microorganisms make mineral from the biological mineral environment and eliminate its risk.The aim of this research is to work on the biological mineralization process and test this process in the bacterial culture environment.The microorganism used is Bacillus persicus and the desired metal is cadmium, which by preparing the required solid and liquid culture medium, the defined process for three operational parameters: pH (6.5-8.5), temperature (25-35°C) and the concentration is 1500-200 ppm.The findings indicate that the highest removal rate is 57.17%. In relation to pH, the process of removal increased gradually with the increase of pH from 6.5 to 8.5 and we reached the maximum amount of removal at 8.5. In relation to the temperature, with the increase in temperature from 25 to 35 degrees, the removal status is increasing, and then from 35 to 45 degrees, we have seen a decrease in the amount of removal, and at 45 degrees, we have had the minimum amount of removal. Also, in relation to the concentration, we have seen an increase in the removal rate by increasing the concentration from 200 to about 1240, and after that, a slight decrease has occurred up to the concentration of 1500.The simultaneous state of pH and concentration had the greatest effect on the amount of removal, followed by temperature, concentration and pH respectively.

In this project, a microstrip antenna is presented for use in the RFEH system. In the first chapter, different EH methods are introduced. In the second and third chapters, the structure and components of the RFEH system (antenna, impedance matching circuit, and rectifier are introduced) in the fourth chapter, theory. And the final antenna design technique is discussed, which includes the introduction of the Koch curve, which is used to increase the effective length of the slot. In chapter five, at first, a microstrip antenna with a rectangular patch with a full plate is considered as the initial antenna.

   An epileptic seizure is recognized as a neurological disorder caused by transient and unex- pected disturbance resulting from the excessive synchronous activity of the neurons in the brain. Analy- sis of epileptic seizures derived from long-term recordings of electroencephalogram (EEG) is cumbersome and time consuming for a neurologist. Therefore, introducing an automated detection system surrogate the neurologist involvement all time and speed up the treatment procedure. Methods: This study introduces a matrix determinant of EEG as a significant feature for recognition of epileptic seizures. Initially, artifact-free filtered EEG time series was arranged sequentially to form a square matrix of order, namely 13, 16, 23, and 32 and determinant was estimated. Assumed that the total elements in the square matrix represent a typical segmentation length. The experiment was conducted using EEG database obtained from the University of Bonn and Ramaiah Medical College and Hospital (RMCH). In total, eleven classification problems among non-epileptic group and epileptic EEG were com- posed to examine temporal dynamics of brain activity in different states of the epileptic activity. Next, the extracted feature was classified using support vector machine (SVM), K-nearest neighbor (K-NN), multi- layer perceptron (MLP) classifiers with 10-fold cross-validation. Results: Experimental results revealed the highest classification accuracy of 99.45% (using University of Bonn) and 97.56% (using RMCH). Between normal and epileptic EEG. In addition, other classification prob- lems and matrix orders showed better results using all the classifiers. Further, descriptive analysis, his- togram plot in polar coordinates and the bivariate histogram analysis was performed. In conclusion, ma- trix determinant found to be a potential biomarker for the real-time detection of epileptic seizure with minimal computational complexity

  The purpose of thisthesis is to investigate different deep learning techniques that can be used toimplement a system that learns how to detect breast cancer cases inmammography. Today, breast cancer has become one of the deadliest diseases.Mammography is the gold standard for detecting early signs of breast cancer,which can help treat the disease in its early stages. However, mammographymisdiagnosis is common and may harm patients through unnecessary treatments andprocedures (or lack of treatment). Therefore, systems that can learn to detectbreast cancer on their own can help reduce the number of misinterpretations andmissed cases.Convolutional NeuralNetworks (C  ) are used as part of the deep learning process, initially ontheir own. To analyze the effects on performance and efficiency, various deeplearning techniques such as different architectures (VGG16), dropout, dataaugmentation, changing network layers, fine-tuning, etc. are used.Finally, the accuracy of88.69% in the CBIS-DDSM dataset with the pre-trained model with VGG16architecture in two-class classification for the detection of mass andcalcification, as well as the accuracy of 61.31% in the four-classclassification for the simultaneous detection of mass and Calcification andtheir benign and malignant nature are obtained in mammography images. Othertested techniques such as data augmentation, dropout, and fine-tuning alsoincrease accuracy. Finally, these results have been compared with otherarticles using the CBIS-DDSM dataset.

   Currently, fMRIis the most widely used brain function technique. fMRI provides an oppurtunity to observe the neural activity in the brain. In fMRI tests, a blood oxygen level dependent (BOLD) signal is measured. Dynamic causal modeling is a Bayesian framework for inferring latent neural states from measured brain activity. DCM is increasingly used in the analysis of a wide range of neuro imaging and electrophysiological data. One of the methods of functinal magnetic resonance imaging is functional magnetic resonance imaging at rest. The idea that cerebral blood flow can reflect neural activity is the basis of all imaging techniques today. rs-fMRI imaging is used to describe areas of the brain that are correlated with time signals. Spectral Dynamic causal modelling (sp DCM) is introduced to estimate the intrinsic effective connectivity of rs-fMRI data. spDCM estimate the effective connectivity that results in a functional connectivity. spDCM reliably estimates the intrinsic efffective connectivity in the absence of an external stimulus. Spectral DCM models a range of endogenous activities that reproduce the observed functional connectivity fMRI at rest. The aim of this thesis is to investigate both DCM methods for inferring latent neural states from measured brain activity and spDCM methods for estimating the intrinsic effective connectivity of rs-fMRI data. Currently, fMRIis the most widely used brain function technique. fMRI provides an oppurtunity to observe the neural activity in the brain. In fMRI tests, a blood oxygen level dependent (BOLD) signal is measured. Dynamic causal modeling is a Bayesian framework for inferring latent neural states from measured brain activity. DCM is increasingly used in the analysis of a wide range of neuro imaging and electrophysiological data. One of the methods of functinal magnetic resonance imaging is functional magnetic resonance imaging at rest. The idea that cerebral blood flow can reflect neural activity is the basis of all imaging techniques today. rs-fMRI imaging is used to describe areas of the brain that are correlated with time signals. Spectral Dynamic causal modelling (sp DCM) is introduced to estimate the intrinsic effective connectivity of rs-fMRI data. spDCM estimate the effective connectivity that results in a functional connectivity. spDCM reliably estimates the intrinsic efffective connectivity in the absence of an external stimulus. Spectral DCM models a range of endogenous activities that reproduce the observed functional connectivity fMRI at rest. The aim of this thesis is to investigate both DCM methods for inferring latent neural states from measured brain activity and spDCM methods for estimating the intrinsic effective connectivity of rs-fMRI data.

  In this dissertation, the designs of antennas with two bands and two polarizations have been studied. In this study, three different and new designs in the field of multiple antennas are presented. The simulations for all three antennas were examined in ansys hfss software and the antennas were evaluated and compared with each other.The structure of the designed antennas consists of an FR4 substrate and two or four 50 ohm power lines and an improved DGS (incomplete ground plate). The first proposed structure is a square antenna with dual patch. In Figure 4-10, this antenna is made using FR4 substrate with a thickness of less than 1 mm and a dielectric constant of 4.4 and a loss tangent of 0.022, and the overall dimensions of the substrate are 32 × 32 mm2. This structure is powered by a 50 ohm microstrip power line. According to the theory, patch antennas are located at the bottom of the substrate, the defective ground plate or DGS, and at the top of the substrate, the radiation patch and the microstrip power line. Where the measured bandwidth was 4.2 GHz equal to 2.86 GHz (3.59-6.53 GHz). And the measured bandwidth is 9 GHz equal to 3.08 GHz (7.05 - 10.13 GHz).For the second simulation, by creating a circular patch with a thickness of 10 mm, a suitable and practical bandwidth can be obtained from the antenna. At 3.5 GHz, the impedance bandwidth is approximately equal to 2.7 GHz, and at 10 GHz, the impedance bandwidth is equal to 4 GHz, which is It is considered a desirable band.To design the third design in the final antenna structure shown in Figure (32-4), the structure has an impedance bandwidth of 5.076 (3.5030 - 8.5790) GHz and 4.935 (11.587 - 16.522) GHz. The proposed antenna configuration creates a circular polarization with a phase difference of 90 degrees, which has many applications in the industry.

A wireless sensor network consists of sensor nodes located in geographic areas whose job is to monitorPhenomena such as humidity, temperature, vibration, etc. Since wireless sensor networks are networks that are used to monitor and control the environment, data transfer in these networks is based on data. Is done and routing protocols in these networks must be data based.

  Abstract Getting the body by robot fingers despite the constraints of the topics studied by many researchers. In studies conducted so far, investigations of disturbance with the aim of bringing the body to a new stable condition have been considered. In this research, we study the garsping model in three dimensional space, as well as the related topics, first, the kinematic and dynamic modeling of the fingers and the object and the integration of these equations using the adaptive control method. In addition to the usual kinematic and dynamical studies, this paper examines the speed and position of the robot's motion in order to maintain the desired position of the arms and body under its control. The simulation results by MATLAB software have shown that the model reference adaptive control method with disturbance is capable of creating stability for the speed and displacement of the robot arm fingers

   Abstract   The global prevalence of lung cancer in recent years has affected many countries around the world and has had devastating effects on the international community. Due to the very important features of this type of cancer, including its lack of recognition in the early stages of the disease, the similarity of lung nodules with blood vessels, etc., and as a result, misdiagnosis of them instead of each other and high mortality rate has led to The most important and best way to control and control lung cancer, based on the consensus of doctors and global health organizations, early detection and termination of its transmission to other organs of the body with the rapid start of effective treatments for people with this type Be cancer. Therefore, accurate, fast and accessible diagnosis is the best tool to achieve this important. In this regard, in the present dissertation, an intelligent machine for diagnosing lung cancer has been presented and implemented using CT scan images and deep learning. Also, in order to evaluate the proposed smart machine, MATLAB software has been used and the necessary results have been extracted, and the obtained results show the very high accuracy of the proposed smart machine. The use of transfer learning theory, especially the Resnet18 network, in the diagnosis of lung cancer has not yet been used and is an innovative aspect of this design. key words: Lung cancer, lung nodules, lung scans, image processing, deep learning, transfer learning, Convolutional neural network.

Abstract Congenital heart disease can cause heart failure or even mortality in 1 out of 125 newborns and infants, each year.   This cardiac failure severity can vary from mild to serious. It has been well-known that the early diagnosis of cardiac disease in the embryonic period may avert the cardiac failures and reduce the chance of mortality in newborns, accordingly. Therefore, it is of great importance to diagnose the condition and treat it, early.    Congenital heart defects can appear in the early stages of pregnancy, when the foetus’s heart is being formed and can affect the heart or its function. Generally, the heart failures may be caused due to genetic syndrome, inherited disorders, or environmental factors such as infection or consumables.    To examine the foetus’s heart condition, the heart’s electrical activities are commonly recorded by electrocardiogram (ECG) and examined by the cardiologist. An ECG is a non-invasive diagnostic method that records the variations in the heart electrical potentials. The non-invasive extraction of fetal ECG (fECG) from maternal abdominal is a demanding difficult task,   as the signal-to-noise ratio (SNR)   is very low and fECG signals are often blended with other signals such as; maternal heart activity,   the respiration, the uterine contractions, and also instrumental noise in the surroundings.    Previous research has already investigated the non-invasive extraction of fECG in the past four decades, but their performances are not yet satisfactory.   esides, there is   till a need for fECG extraction from multi-channel recordings. The main aim is to distinguish the fECG morphology with the highest possible accuracy.    This thesis is a review dissertation on previous research conducted, their outcomes, advantages, disadvantages, using adaptive filtering and discrete wavelet transform based methods, which have been less utilized in the context.    Keywords: Fetal electrocardiogram, Maternal electrocardiogram, Adaptive filter, Discrete wavelet transform. Abstract Congenital heart disease can cause heart failure or even mortality in 1 out of 125 newborns and infants, each year.   This cardiac failure severity can vary from mild to serious. It has been well-known that the early diagnosis of cardiac disease in the embryonic period may avert the cardiac failures and reduce the chance of mortality in newborns, accordingly. Therefore, it is of great importance to diagnose the condition and treat it, early.    Congenital heart defects can appear in the early stages of pregnancy, when the foetus’s heart is being formed and can affect the heart or its function. Generally, the heart failures may be caused due to genetic syndrome, inherited disorders, or environmental factors such as infection or consumables.    To examine the foetus’s heart condition, the heart’s electrical activities are commonly recorded by electrocardiogram (ECG) and examined by the cardiologist. An ECG is a non-invasive diagnostic method that records the variations in the heart electrical potentials. The non-invasive extraction of fetal ECG (fECG) from maternal abdominal is a demanding difficult task,   as the signal-to-noise ratio (SNR)   is very low and fECG signals are often blended with other signals such as; maternal heart activity,   the respiration, the uterine contractions, and also instrumental noise in the surroundings.   

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RFID 

Solution to increase and decrease the radiation of radio signals in buildings

and tried to improve the error  

Abstract With the advancement of radar technology due to electronic warfare, radar systems are capable of measuring high-precision targets over long ranges as they are increasingly being used. Radar protection is more important than radar itself. In radar design, the transmitter and receiver position the transmitter and receiver in one place, but they separate the sender and receiver to protect the accuracy of accuracy. Passive radar is a kind of radar used to detect and detect targets using an unknown antenna. Passive radar can be combined with array antennas to preserve more radar security. In this project, a phase array antenna is used to design passive radar. When a number of antennas are located at a distance from each other, they have the potential to continue to operate in the system alone, in other words, some of the antenna may disappear or have a problem, but the rest of the antenna can continue to function with less efficiency. Many parameters have a role in the design of passive radar using phase array antennas. Depending on this radar, this radar has a stationary or mobile location and is used in different applications such as: military, aerial, imagery, photography. The most important part of this thesis is the number of elements in the array. In this design, all-directional antennas (omni-directional) are or can be used with better performance and more complex antennas. All antennas must be synchronous (synchronous), one of the major challenges in this design. At the same time the antenna is complex in a geographic area. To synchronize the antennas using global positioning systems (GPS). To achieve the desired phase, a source antenna with zero phase is used for proper shape shaping elements that have a suitable pattern in one direction according to the desired phase. Keywords:  oscillators,  eam  haping,  antenna  array,  avigation,  assive  radar   

  :Abstract Every communication network is assumed as a set of interference channels. Therefore, interference channels can be considered as the most important part of the wireless communication system. Each interference channel has included some transceivers, in which all transmitters send signals to their corresponding receivers. In order to maximize the transmission data rate, one common way is to increase the transmitter's power but this fails to be functional in interference channels because it increases the interference power at the receivers as well. Recently alongside all applicable methods to reduce the interference effect at the receivers, such as (TDMA),(FDMA),(SDMA),(CDMA), a method known as Interference Alignment (IA) has been developed. In IA method it is assumed that received signal su  aces in each receiver is projected into two independent linear su  aces with equal dimensions. By this way interference signals from interfering devices are grouped (normally half-size) and desirable signals from each transmitter are placed in an independent linear interference su  ace. Requardless of many advanteges of this method, it is not very functional because it is drastically dependent on the channel state informations (CSI). For this reason this method needs to be improved to a desirable function level. Thus, In this thesis a reconfigurable antenna, which enhances interference alignment with no access to CSI in transmitters, is introduced. It has made the IA to an applicable method. In this way, the need to use the MIMO antenna's and joint processing decreases

  اندازه گيري بار شناختي مغز با استفاده از روش هاي اندازه گيري همزماني فاز سيگنال EEG

Neonates and infants are the most likely group to present with congestive cardiac failule, one of the most cause of mortality in newborns, so that, one out of 125 are born ech year with some form of heart failure. This cardiac failure ranges from mild to severe in terms of severity.In has been well established that the early diagnosis of cardiac disease in the embryyonic period may prevent the cardiac failures after birth and consequently decrease the rate of mortality in newborns.Recording heart electrical activity by electrocardiogram is commonly used to detect abnormal arrythmias. How ever the non-invasive extraction of fetal ECG   from maternal abdominal is challenging, since the fECG signals are aften corrupted by electrical noise from other sources such as maternal heart activity, uterine contractions and respiration, in addition to instrumental noise.Many approaches has been presented to non-invasively extract fECG, However their performance are not entirely satisfactory. Among all exising methods Blind Sourse Seperation have been of great interest to researchers for many applications. In this thesis, we use the method of time-frequency based blind source separation method for the separation of Convolutive Mixtures. We also use the Compressive sensing and the fast independent component analysis method to reduce the complexity of the signal.We apply our proposed method to the database in the 2013 Physionet Challenge and compare the results with existing methods using Compressive Sensing and Independent Component Analysis, which yielded a Mean squar Error of 171.65 and a time of 7.85 minutesKeywords: Fetel Electrocardiogram signal, Blind Source Seperation, Time-frequency analysis, Convolutive Mixtures, fast independent component analysis, Compressive sensing, Discet Wavelet Transform

  AbstractWith attention to the development of new sciences, in particular electronic science and telecommunication, radio waves (radio communications), the size and physical size of high-capacity components will be smaller and smaller in integrated circuits, and these changes also affect the unwanted (noise) signals in the structure. As a result, we need high-performance filters to eliminate these unwanted waves. There are many errors in the integrated circuits due to the high frequencies, and also have unusual dimensions and size. Using the microstrip technique is very suitable for using a substrate (dielectric) substrate. For use in microwave integrated circuit circuits. In this dissertation, a low-pass microprocessor filter with very small size, a wide bandwidth and good return loss are presented.After designing and using the ADS (Advanced Design System) software and comparing the simulated and measured results, the values are acceptable.

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طراحي مدارات ديجيتالي ممريستوري براي محاسبات درون حافظه اي

  The database used in this study is a 10000 sample medical database from a cohort study conducted in ravansar city, IRAN. This database consist variables like biochemical tests, CBC tests, anthropometric data and lifestyle variables. The main reason of creating this database was to have a baseline source for storing ravansar city residents’ information to follow up in a 15 year prospective cohort study. Therefore in this study the effort was to extract interesting relationships between these variables and chronic diseases using genetic programming. In contrast to majority of data mining researches that take performance and creating a novel model as the main purpose, this study has chosen knowledge extraction. At first by using the feature selection ability of genetic programming we have tried to reveal the most related variable for each disease. Rule mining is done by association rule mining algorithm. An evaluation process of the GP results is conducted by the extracted rules to check the correctness of GP’s results. Features selection and rule generation are done separately for biochemical test and CBC tests based on their different definition. From the diseases we have chosen diabetes and hypertension as the goal diseases because of the quality of the data they have. For diabetes ALP, TR, GGT, BU are considered as the most related variables while for hypertension FBS, ALP, LDL, TR are the most important ones. Results considering CBC variables were not mentionable.

Abstract  In recent yerars, new structures have emerged in the field of electromagnetism and microwave, which are known as Metamaterial. These structures are not present in nature and these are artificially created, and have interesting properties such as negative electrical and magnetic permeability coefficients, resulting in a negative or near-zero refractive index. However, the Metamaterial have high losses, difficulty building and bulky structures. Therefore, a different category of these two-dimensional materials, which are known to be Metasurface, are noticed more. As an example of the use of these artificial structures, it is possible to improve the radiation characteristics of antennas in the presence of a Metasurface Given the refractive index of the material with the electrical and magnetic parameters, we know that if one of the electrical or magnetic coefficients is zero at a specified frequency, it will result in zero refractive index of material and, therefore, will result in the direction of the emission waves from the material , Is closer to the normal vector of the surface, which is used to improve the efficiency and antenna gain. in addition, the proper design of the Metasurface can increase the bandwidth or minimize the antenna. In this thesis, the design and simulation of the optimal Metasurfase to increase the gain and directivity of the antenna in the microwave and terahertz band are discussed.

Design and Simulation of Microstrip Patch Antenna Array for Wireless Power Transmissio  

Mutual Coupling Reduction in Microstrip Patch Antenna Array  

Displacment Sensor using Microstrip patch Antenna with Split Ring Resonator  

     In this study, MoO3 metal oxide was loaded by mechanical and wet impregnation methods on nano structure g-C3N and SBA-15 supports, respectively. After finding the optimum amounts of metal oxide loading, 10%MoO3/g-C3N4 and 5%MoO3/SBA-15 nano catalysts were used in the oxidative desulfurization (ODS) process. For investigation the performance of the synthesized nano catalysts in the ODS process, Dibenzothiophene (DBT), H2O2, and acetonitrile were selected respectively   as the target compound in 1000ppm model oil, oxidant, and solvent. In order to optimize the operating conditions including temperature, amount of catalyst, H2O2/DBT molar ratio and time reaction, Response surface methodology based on Box-Behnken Design of Expert (DOE) software was applied for each nano catalyst. Among the various models, DOE proposed the Quadratic equation model because of good accordance with experimental data for each catalysts (R-Squared=0.9831%, Adj R-Squared=0.9707 for 5%MoO3/SBA-15 and R-Squared=0.9569%, Adj R-Squared=0.9240 for 10%MoO3/g-C3N4, respectively). The results of optimization for 5%MoO3/SBA-15 nano catalyst were T=55 ?C, 0.02g amount of catalyst, H2O2/DBT=9 and 49 min reaction time and for 10%MoO3/g-C3N4 nano catalyst optimum condition were T=70 ?C, 0.04g amount of catalyst, H2O2/DBT=8.44 within 55min reaction time. The efficiency of the 5% MoO3/SBA-15 and 10% MoO3/g-C3N4 nano catalysts were predicted to be 100% and 97.7% in optimal operating conditions, respectively.     To evaluate the performance of the synthesized nano catalysts in the removal of other sulfur compounds in the optimal conditions expressed by DOE, two other model oils, 1000ppm Benzothiophene (BT) and Thiophene (Th), were applied in the ODS process, and the   removal efficiency of sulfur compounds was in order of   DBT > BT > Th. Also, the regeneration of the nano catalysts was evaluated four times, showing yield decreases of 5% and 6% for 5%MoO3/SBA-15 and 10% MoO3/g-C3N4, respectively. Finally, the performance of the   ano catalysts in the removal of sulfur compounds of gasoline and gas oil from the Kermanshah Oil Refining & Distribution Company was investigated, and the obtained efficiencies of sulfur removal were 69.73% and 49% for 5%MoO3/SBA-15   and 58.35% and 41% for 10%MoO3/g-C3N4 respectively.

Abstract The Wilkinson power dividers are one of the most ubiquitous passive circuit elements in RF/Microwave applications. They are widely used in antenna arrays, balanced amplifiers, mixers, frequency multipliers etc. in this thesis, a compact microstrip four-way filtering power divider is presented. The structure of the proposed device includes an inline filter has generalized Chebyshev response, where frequency dependent coupling method is used to generate transmission zeros at finite frequencies. A detailed design procedure is shown to determine the initial parameters of all the characteristic impedance and electrical length. Therefore, by the outspread inline filter, the configuration of four-way filtering power divider is achieved. Three isolation resistors are used to satisfy both transmission and isolation property. A porotype is designed and fabricated on a substrate with the relative dielectric constant =3.38, the thickness of h=0.7874mm and the dielectric loss tangent of tan ?=0.0022. after the full wave simulations and optimization by using AWR environment, the dimensions of the prototype is obtained and the overall size is about   55.5×40 .The measured result show 5% bandwidth centered at 2.5 GH with low in-band return loss, high-frequency selectivity, good matching and good isolation between outputs.

Design Of Ultra Wideband Low Noise Amplifier (LNA) With Current Reuse And Noise Cancelling Technique

طراحي تقويت كننده كم نويز در باند فركانسي فوق وسيع با استفاده از تكنيك استفاده مجدد جريان مكمل اصلاح شده

در اين پژوهش طراحي كوپلرهاي جهتي با پهناي باند زياد و ابعاد كوچك و در حوضه شبكه هاي بي‌سيمي به عنوان هدف قرار داده شده. در اين پژوهش نخست تحقيقات گسترده اي در زمينه المانهاي مايكرواستريپ و پاسخ فركانسي آنها صورت گرفت تا به اطلاعات كافي براي كاربرد اين آلمانها در طراحي يك كوپلر پهن باند دست يابيم. سپس به كمك اطلاعات به دست آمده در اين مرحله خطوط تزويج شده مايكرواستريپ براي ارائه طرح اوليه در يك بازه فركانسي نسبتا وسيع بكار برده شد. در مرحله بعد تلفات بازگشتي و ضريب ايزولاسيون كوپلر با استفاده از خطوط شاخه اي خميده شده و استاب هاي تكرار پذير متقارن بهينه سازي شد. ضمن رسيدن به پاسخ فركانسي مناسب و بهينه، حفظ سادگي ساختار نيز در بهينه سازي مورد توجه قرار گرفته است. در پايان چند طرح مناسب براي كوپلر جهتي رسيديم.

در اين پايان نامه به كمك رزوناتورهايTشكل ونيمدايره اي يك فيلتر پايين گذر طراحي، شبيه سازي و ساخته شده است. اين فيلتر داراي فركانس قطع GHz34/1است و همچنين تيزي آن از سطح dB3 تا dB40 برابر GHz41/0 است. همچنين باند قطع اين ساختار از فركانس GHz68/1 تا GHz20 مي­باشد كه نشان مي­دهد فيلتري با پهناي باند قطع عريض طراحي شده است و سطح حذف هارمونيك در باند قطع اين فيلتر برابر dB20 است. اندازه اين فيلتر برابر 9mm2/15 ×3/9مي­باشد كه با اين خصوصيات، اين فيلتر از ضريب شايستگي67954 بهره مي­برد. لازم به ذكر مي باشد كه در اين پايان نامه، فيلتر پايين گذر طراحي شده به چند رزوناتور   تقسيم شده و اين فيلتر ساخته شده است كه مشاهده مي شود پاسخ ساخت و شبيه سازي تطبيق خيلي مناسبي مي­باشند.  كلمات كليدي:رزوناتور،­فيلتر پايين گذر، اندازه كوچك، فركانس قطع.

  Recently, solving under determined systems is interested problem in the researchers of several science , especially that is too hard solving problem in general for reaching sparsete solution. In special term , a linear equation system can be converted to an equal convex optimization problem that has just one solution. This improvement is start for many searches and caused sparse solutions.In this thesis, we Propose a novel algorithm for sparse infiniti impulse response (IIR) filter designe. If a filter be sparse the addres and moltiplieres of zero coefficient will be deleted at last cost and complexity of implementation will redused.In recently years a lot of algorithms for sparsing signal introduced. This algorithms 0in 0in 10pt" >In this thesis we propose a novel algorithm for sparse infinitive impulse response (IIR) filter designs. The objective of the sparse digital filter design problem is to reduce the number of nonzero-valued filter coefficient.The proposed design method is i  ired by   particle swarm optimization(PSO) algorithm.This algorithm is included into two stages ,a preliminary optimization stage is introduced to determine the positions of filter coefficients to be zero then is reduced the error with determined the zero in first step. At last designed Butterworth IIR filter be sparse with six, zero coefficients with pass band edge .3791 , cut of frequency .531   and attenuation -45dB the   implemented on virtex6 Field Programmable Gate Array(FPGA).

Cross Field Antennas (CFA) are a new generation of the antennas that have the major advantages of conventional antennas. Therefore, awareness raising and knowing enough of the performance these antennas can have a significant effect on the advancement and development of telecommunications applications. One of the important reasons to use CFA antennas is very small-size of these antennas,  which can easily be installed on the roof of the buildings. In this thesis, cross-field antennas have analyzed using the quasi-static method. First, in order to reduce the error of calculations in the use of this method, different symmetric conductors were considered. It was observed that the elements to equal dimensions or with the dimensions ratio of one have the minimum probability of error. The using this method and considering the elements with the equal dimensions, the charge density was investigated in asymmetric conductors. It was also shown that too many elements do not have much effect on the results, while the time of the calculation increased and the speed of the process reduced. Then, CFA antenna was analyzed in two static and dynamic states to assume the elements with the dimensions ratio of one using the quasi-static method. The results showed to achieve the ratio of the electric to magnetic fields equal to 337 ohms and efficient radiation; it is necessary that the E-plate excitation amplitudes are twice the D-plate excitation amplitudes in this antenna. The D-plate irradiation phase is about 90 degrees phase-lag to the E-plate irradiation phase, also. Finally, the effect of change each of the physical parameters of the antenna was investigated on the ratio amount of electric to magnetic fields. Finally, the effect of changes each of the physical parameters of the antenna was investigated on the ratio of electric to magnetic fields and was indicated that each parameters a significant impact on this ratio. Whereas, the relationship between the magnitude and the phase of sources must again be determined.

تعيين نقاط بحراني در شبكه هاي هايبريدي و توسعه مسيرهاي اضافي در شبكه جهت بهبود عملكرد و افزايش ظرفيت و پايداري با ملاحظه به توانايي گره ها

desing of high gain LNA for bluetooth Application

فيلتر ميان نگذر جذبي و انواع آن

جداسازي سيگنال قلب جنين با استفاده از جداسازي كور منابع بر اساس آناليزهاي زمان فركانس

Design of an ultra-wideband low noise amplifier with desirable linearity

  Wilkinson Power Divider using Low Pass Filter with compact size and Harmonics Suppression

  تبديل سيگنال هاي اي اي جي چند كاناله به صدا به منظور تشخيص الگوهاي غير طبيعي

<  gt;توليد كامپوزيت زمينه آلومينيومي تقويت شده با شبكه سيمي فولادي</P>

شبيه سازي لوله هاي مخروطي پر شده از فوم تحت بار ضربه اي محوري در نرم افزار آباكوس

  Global warming and excessive greenhouse gas of concern for todays world has become a dangerous consequences such as drought, diseases, fire and leads. One of these gases is carbon dioxide, which for the separation there of the different ways. One of these methods is using photocatalyst, especially MOFs as a new class. In this study, Prvfyryn- based on metal-organic framework (Co / PMOF) is Using Tetrakis ((4- carboxy phenyl Prvfyryn (TCPP)is built as a ligand, And is analysis by spectrum FESEM and EDX. Photocatalytic experiments around (Co / PMOF) as a photocatalyst is done in the presence of water as a sacrificial electron donor under irradiation with visible / UV.   Results from the reaction shows that mol10 . 96µmol methane is produced in about 4 hours response, which indicates is the high level of production. In addition to measuring the UV-vis and FTIR spectra show that there is no sign of change in the structure of photocatalyst. As well as the reaction mechanism has been studied.

Abstract:  The pipelines that are used in the petroleum industry tra  ort gas and oil with content of sulfidric gas that intensifies the adsorption of hydrogen in the metallic surface provoking the absorption of hydrogen in the wall of the pipe, what can flow in a embrittlement processThe welding process and the manufacturing process can also facilitate entry of hydrogen into the steel.The work done by other researchers suggest several parameters in the hydrogen losses had an impact. For example, have shown that the microstructures ferritic microstructure of ferrite needle more resistant to damage by hydrogen. Also tempered martensite microstructure bainite structures to very fine particles, perlite and martensite shows better behavior. Impurities and inclusions as trapping hydrogen in steels resources to act. Manganese sulfide is known as a harmful impurities.In this project, API 5L X60 pipes used in oil refineries Ntg Bijar area Kermanshah related to oil and gas companies have been defeated West under analysis. It was found that impurities MnS significant role in the formation of cracks were HIC. So that all EDS analysis show the presence of these impurities left in the region. Studies also show that the microstructure of the steel microstructure ferrite - pearlite with a hardness of 210 Vickers is that in some parts of needle ferrite and ferrite Weidman Ashtatn was observed in some areas.

gain scheduling control design of switch reluctance motor via lmi approach

gain scheduling control design of permanent magnet synchronous motor via lmi approach 

Biodiesel is a clean and renewable energy, that using as a substitute for diesel fuel is growing worldwide. In this study, safflower seed as a convenient and cheap raw material for the direct production of biodiesel using contraction processes of extraction and transesterification in the presence of lime was chosen as a natural catalyst. For this purpose on a stage in process conditions similar to extract the maximum amount of oil from safflower seeds at different temperatures and times were investigated. Then, again given the choice of a suitable solvent, time and temperature optimum, biodiesel production was carried out with the catalyst of lime. In order to select a suitable solvent, at first the extraction by solvents such as methanol, hexane and acetone were evaluated and the results showed that the mixture of methanol - hexane (volume ratio 2:1) was the highest extraction efficiency. Then, for investigation of simultaneous transesterification, lime was used as a natural and economical catalyst for the transesterification process synthesis. During the experiment, the volume of solvent 300 ml and 60gr safflower seeds comminuted with 1.6% moisture selected also process time 8 hours and constant temperature 65°C and agitation 750 rpm was considered.  

Predictive control is known as a wide class of controllers that have found recent application in the control of power converters. The main characteristic of model predictive control (MPC) is the use of the system for prediction of the future behavior of the controlled variables over a prediction horizon. This information is used by the MPC control strategy to provide the control actions for the system by optimizing a predefined. This thesis presents a current control strategy using Finite Control Set Model Predictive Control (FCS-MPC) that applied to a three phase four leg voltage source inverter. This control scheme predicts the future load currents behavior for each valid switching state of the inverter. The control method chooses a switching state that minimizes the error between the output currents and their references. Also, in the following, a new method is proposed to reduce the amount of calculation. Finally, simulation results in Simulink/Matlab are demonstrated.  

  AbstractDue to the significant load carrying capacity of masonry wall, they were comprised the main construction materials in the past year. First, this materials were obtained by the hardening of mud on side of the grill and cooking ovens. Todays bricks were built based on this issue. At that time, it was used only because of its strength and availability, but with the passage of time and observing the behavior and performance of these materials in earthquakes and wind, the need to understand the exact behavior of these materials were felt more than ever.,Wood has been used since the beginning of history and due to its good tensile strength and economical and easy process there in its manufacturing and also help to protect the environment because of carbon dioxide that its stored in, is taken into consideration. Another advantage of wood are cheap cost and availability in the Cities and villages are underdeveloped.Masonry structure with timber framed is a structural system with high diversity and complexity. Limited analytical and experimental research has been done to detect seismic response on this structure. From the Bronze Age, this system was common in seismic areas. According to the behavior of masonry structures, the fundamental weakness of them against the earthquake, not lack of strength, But it is the lack of stiffness or plasticity. This weakness can be alleviated by reinforcement. Despite of the high shear strength of masonry structures, due to brittle behavior of materials, the improvement of performance of these structures for increasing in capacity and ductility is very important and the use of reinforcement elements such a member in order to eliminate disadvantages of these structures had historically been considered.

  Due to the development of appropriate methods for seismic retrofit and rehabilitation of buildings against seismic loads due to the vulnerability of masonry buildings that include a large number of buildings in the country is an important. One of the methods of retrofit and rehabilitation for unreinforced wall is use of steel bars with concrete coverage in one or both sides of wall. This steel gride is connected to the wall with steel nails. Implementing of such method increases the lateral loading capacity of wall, but also caused more cohesion of wall in integrity manner. In recent years, engineers implemented this method as an efficient and economical way for the most rehabilitation plans of the countries present masonry buildings. But since the lack of experimental information over these walls seismic performance and actions, which their designing generally based on the standards of concrete instructions or engineering judgment. According to the studies that have not been performed about the effect of steel nails in the reinforced wall. In this thsis first a pull-out test was carried out to place the steel rebar embedded in brick-mortar sample under tensile load. As the result of this test, bond strength, maximum tolerable tensile and displacement corresponding to the tensile load and load-displacement curve are obtained. Then, the experimental model was numerically simulated to obtain sliding, displacement, plastic strain, and the stress of the steel rebar and the brick-mortar sample. Second by using ANSYS17 software is investigated the effect arrengement of this steel nail on seismic performance of masonry walls with 10cm, 20cm, 30cm thickness in full-scale and small scale. The load – displacement diagram to one side wall on both sides of reinforced concrete with an experimental model has compared then the load – displacement diagram, displacement contour, and plastic strain for two side and one side reinforced wall in two forms with steel nails and without steel nails has compared. Finally, the steel nails force diagram is shown.

  AbstractIn recent years, many researchers to increase the technical capacity and economic systems of the DG as well as the appropriate response to the need for high reliability and power quality have tried. The results of these efforts led to the emergence of the concept of the microgrid been entitled. A microgrid is a member of the power system, distribution system usually consists of one or more units is DG which can load one or more local and nonlocal independent of the national grid feed. DG connect to the network and, in fact, the microgrid, the inverter is required. Microgrid inverter control requires sufficient knowledge of the microgrid and having the exact parameters in order to design suitable inverter. In practice, the nature of these parameters are unknown and may change. If microgrid controller, inverter, according to several parameters that are not fully understood its nature, be designed for different parameters of the controller parameters, obtained a negative answer.To deal with this phenomenon at the Thesis of Bumpless Control will be used. Here are a few control parameters will be used to cover all the changes. This means that, if there are two variable parameters in the microgrid can be controlled with 4 covered the whole atmosphere changes in these parameters And for each area of a controller that simplifies If other parameters to control the operation area , With a switch controller and the controller fit into the current of the circuit outside the circuit. To prevent injury when switching between controllers, a controller output gain for maintaining current control circuit that is supposed to be used.In this thesis, the first chapter discusses the challenges and aim of the thesis was described. Then in the second chapter explores a variety of control techniques were discussed. According to the debates that took place, it was observed that any identifiable control techniques to investigate the functional limitations of their own. In the third quarter as the proposed method has been studied and the results were presented in the fourth quarter. The simulation was done in two ways droop and the proposed method and comparing the results show a significant improvement in the results of the proposed method is compared to droop.