Yazar "Ilyas, Muhammad" seçeneğine göre listele
Listeleniyor 1 - 20 / 64
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe A hybrid control topology for standalone PV systems Co2(American Institute of Physics Inc., 2022) Khazaal, Hasan F.; Hburi, Ismail; Ilyas, Muhammad; Mohsin Al-Lami, Ameer Mohammed QasimSolar energy is the most significant energy resource since it is pollution-free, clean, and inexhaustible. A huge number of approaches have been suggested in recent years for tracking the maximum Power and smoothing the performance of the system. In this manuscript, we submit a hybrid control scheme to ensure enduring power and achieve variable load requests in Battery based standalone photovoltaic systems. More specifically, in the submitted scheme, Model Predictive Control (MPC) is joint with Fuzzy logic to achieve the advantages of these two diverse approaches where a fuzzy approach controller is employed for the battery bidirectional DC line and a joint fuzzy-MPC scheme for the inverter (DC-AC) on the load side of the stand-alone system. The suggested controller could enhance the power reliability performance of the solar scheme. According to obtained results, the proposed topology overcomes the traditional PI model by achieving profits in the context of step-overshoot response enhancement around 0.9 % and the reduction in settling time is around 0.19 msec.Öğe A metamaterial-based compact MIMO antenna array incorporating hilbert fractal design for enhanced 5G wireless communication networks(International Information and Engineering Technology Association, 2023) Ali, Leena; Ilyas, Muhammad; Elwi, Taha A.A novel compact antenna array design, tailored for 5G applications, is introduced in this paper. The proposed antenna operates in the sub-6GHz frequency range, ensuring optimal wave propagation characteristics in local areas. To achieve this, a Hilbert fractal patch-based design is employed. The antenna is developed as a two-element array, catering to Multi-Input Multi-Output (MIMO) communication systems. The overall size of the antenna array is reduced by minimizing the spacing between the antenna elements, which is achieved through the integration of Metamaterial (MTM) Minkowski inclusions as defects on the back panel. The antenna exhibits a gain greater than 4.7dBi within the targeted frequency band, with a maximum coupling of -20dB. Two primary frequency bands, centered around 3.5 GHz and 5.5 GHz, are demonstrated by the antenna array. The proposed design is fabricated and subsequently subjected to experimental testing. The measured results exhibit excellent agreement with their corresponding simulation outcomes, confirming the effectiveness of the proposed antenna design.Öğe A Novel Flip-Filtered Orthagonal Frequency Division Multiplexing-Based Visible Light Communication System: Peak-to-Average-Power Ratio Assessment and System Performance Improvement(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Hujijo, Hayder S. R.; Ilyas, MuhammadFiltered orthogonal frequency division multiplexing (F-OFDM), employed in visible light communication (VLC) systems, has been considered a promising technique for overcoming OFDM’s large out-of-band emissions and thus reducing bandwidth efficiency. However, due to Hermitian symmetry (HS) imposition, a challenge in VLC involves increasing power consumption and doubling inverse fast Fourier transform IFFT/FFT length. This paper introduces the non-Hermitian symmetry (NHS) Flip-F-OFDM technique to enhance bandwidth efficiency, reduce the peak–average-power ratio (PAPR), and lower system complexity. Compared to the traditional HS-based Flip-F-OFDM method, the proposed method achieves around 50% reduced system complexity and prevents the PAPR from increasing. Therefore, the proposed method offers more resource-saving and power efficiency than traditional Flip-F-OFDM. Then, the proposed scheme is assessed with HS-free Flip-OFDM, asymmetrically clipped optical (ACO)-OFDM, and direct-current bias optical (DCO)-OFDM. Concerning bandwidth efficiency, the proposed method shows better spectral efficiency than HS-free Flip-OFDM, ACO-OFDM, and DCO-OFDM.Öğe A survey on state of the inter body radio communication channel: performance and solutions(John Wiley and Sons Inc., 2022) Mezher, Mohanad; Alabbas, Amjed Razzaq; Ilyas, MuhammadThe development of in-vivo communications and networking systems has the potential for improving the healthcare delivery while also enabling the creation of new services and applications. In-vivo communications provide wireless networked cyber-physical systems of the embedded devices that enable accurate, quick, and cost-effective responses under a variety of circumstances. Also, it is focused upon modeling and characterizing in-vivo wireless channel, as well as contrasting it to other well-known channels. In this paper, channel coding is also mentioned because it improves data rates and performance gain. This work also discusses present problems and potential research topics for in-vivo communications. This article aims to show the researchers how the orthogonal frequency multiple access (OFDMA) technique improved the performance of in-vivo channel and how it is outperformed compared to the other techniques (TDM, TDMA, CDMA and OFDM) also how the OFDMA outperformed equalizers and channel coding in terms of bit error rate with giving a significant improvement of data transmitting and avoiding inter symbol interference. However, when it comes to the in-vivo communications, the modeling of in-vivo wireless channel is vital. Understanding the features of the in-vivo channel is critical for achieving optimal processing and designing successful procedures that allow WBANs to be arranged inside the human body.Öğe Advanced frameworks human-type communication over wireless sensor network(Institute of Electrical and Electronics Engineers Inc., 2022) Mohammed, Sura Qutaiba; Ilyas, MuhammadThis study intends to construct sophisticated Wireless Sensor Network topologies for real-time group collaboration. WSNs use dispersed sensors to safeguard data privacy and convey data for analysis. Medical services, postal delivery, energy companies, and industries use WSNs to monitor machines and discover faults. Weakly Connected Networks (WSNs) collect optimal application estimates and transfer them to a door so clients can understand and execute them. WSNs are crucial to human communication because they can be programmed to spot pauses and persistent attacks in ViWi: A framework for deep learning data sets for vision-assisted wireless communications. WSN direction standards describe paths between starting and ending nodes. How can these guiding principles divide the organization into more manageable segments and stimulate contact between them and their neighbors before sending information further afield? The testing industry continues to develop new libraries, methodologies, test findings, and customization possibilities. Python reduces grammatical complexity, increases efficiency compared to prearranging languages, and ensures memory safety. This cutting-edge research recognizes that memory health is an issue for modern human communication systems and has begun porting portions of their convention disentangling logic to achieve a 98.74% accuracy rate for distinguishing all interruptions within the WSN that use a parser age structure to achieve safe convention parsing.Öğe Analyzing optical fibre communication networks for intrusion detection using FBG sensors(Institute of Electrical and Electronics Engineers Inc., 2022) Ali, Elaf Alabed; Ilyas, MuhammadDue to its many advantages, fibre optic sensors have quickly become a widely used sensing technology in many different fields. Something that can be fibered Light of a certain wavelength is reflected while the rest of the spectrum passes through an optical fibre with a Bragg grating built into it. Optical fibre with a Fiber Bragg Grating is often utilised for strain and temperature sensing applications. The output is more accurate and may be used in more situations when the system is immune to the effects of electromagnetic interference. The term 'Fiber Bragg Grating' refers to the periodic change in index of refraction that may be achieved in optical fibres. It functions on the basis of changes in wavelength caused by modification of the light source due to temperature increases above the reference point. In this work, we detail the deployment and testing of an intrusion detection system based on Fiber Bragg Grating (FBG) sensors in the real world. Simulations are performed to examine the performance of 1551nm Fiber Bragg Gratings as strain sensors and the resultant dynamic strain and wavelength changes are analysed. This examination of performance is very helpful for intrusion detection systems operating in hostile situations. For remote sensing purposes, this sensor is data-communication-system-compatible.Öğe Automatic detection of vehicle congestion by using roadside unit(2021) Abbood, Zainab Ali; Ilyas, Muhammad; Aydın, Çağatay; Mahmoud, Mahmoud Shuker; Abdulredha, NidaThe presence of Roadside Units (RSUs) helps network loads to be expanded to the other nodes that have already been far away from frequent node exposure. We proposed in this work utilizing the mobile node to operate as a roadside unit and operate data packet routing such as roadside units does. The main problem of utilizing the huge number of roadside units is the spending of huge time for data provision by a reduction in performance. Also, in this paper, we attempt using the various number of mobile nodes such as roadside units that are different from traditional roadside units such as the past is fixed and the second is active as a movement previous. The proposed method was executing by utilizing ad hoc on demand distance vector (AODV) routing is a path protocol for mobile ad-hoc networks (MANETs) and other wireless ad-hoc networks, this protocol designed for usage of ad-hoc mobile networks. Also, it's an active protocol, the routes are made only when they are needed, common routing tables, one entry single destination, and supplement numbers in conformity with determine whether routing information is up- to-date and to forestall routing loops. In this paper, mobile vehicles move randomly on highways, so in the event of a collision is too high, it is assumed that the vehicle will stop, and the collision site will be subject to accommodate more than one vehicle. Where vehicles are driven at high speed. Due to the driver's ignorance of the accident area, they can enter it, and thus the problem is magnified. The results achieved shows that numerous mobile nodes as a roadside unit may enhance the communication according to the computation of the average time delay and the link duration of the connection and reconnecting each node. Therefore, the results may reduce the delay time and maintain the connection for a longer period, as shown in the fourth simulation model.Öğe Bit error rate performance of in-vivo radio channel using maximum likelihood sequence estimation(Institute of Electrical and Electronics Engineers Inc., 2020) Mezher, Mohad; Ilyas, Muhammad; Bayat, Oğuz; Abbasi, Qammer H.In this paper we present the Bit Error Rate (BER) performance of equalizers using in-vivo channel response measured using Vector Network Analyzer (VNA). Including the use of a Bandwidth (BW) of 50 MHz in the simulations, the results are compared with multiple equalizers and it is shown that Maximum Likelihood Sequence Estimation (MLSE) equalizer outperformed the rest of the equalizers including linear equalizers Least Mean Square (LMS) and Recursive least sequence (RLS) and non-linear equalizer Decision Feedback Equalizer (DFE). The BER performance using MLSE showed significant improvement by improving the BER and outperforming the linear equalizer from 10-2 to 10-6 and DFE from 10-4 to 10-6 at text{Eb}/ text{No}= 14 dB for in vivo radio communication channel at ultra wideband (UWB) frequencies. Furthermore, the un-equalized and equalized channel frequency response spectrum is also part of this article which presents the overall improvement between the two spectrums. © 2020 IEEE.Öğe Blockchain-enhanced privacy and security in medicare data sharing: identifying gaps and solutions in current practices(Springer Science and Business Media Deutschland GmbH, 2024) Rehman, Abdullah; Ilyas, MuhammadSecuring Medicare data sharing is of paramount importance. Our current centralized approach to data management falls short of preserving privacy and ensuring safe data sharing. Blockchain technology is explored as a viable solution designed to reinforce security in shared data. We conducted a focused survey to uncover the deficiencies and challenges in existing protocols, which provide valuable insights for the future application of blockchain in patient data exchange. The healthcare sector necessitates immediate data access and entry, yet the risk of data breaches looms large. Our study emphasizes blockchain’s potential to enhance data security, granting patients greater control over their shared data. This study is a stepping stone towards a new epoch of data sharing strategies centered on privacy.Öğe Certain investigation of filtered-OFDM in visible light communications system(Institute of Electrical and Electronics Engineers Inc., 2023) Rashid Hujijo, Hayder S.; Ilyas, Muhammad; Qasim, Abdullah Ali; Ullah, UbaidFiltered-OFDM scheme recently considers a promising element for Visible Light Communication (VLC) systems. Converting the F-OFDM bipolar signal to a nonnegative signal and being compatible with the Intensity Modulation and Direct Detection (IM/DD) is a crucial issue for researchers. To achieve a unipolar signal, many techniques have been proposed. In this paper, a Direct Current-bias (DC-bias) technique is employed to acquire a signal unipolarity and evaluate the efficiency of the F-OFDM system. The simulation findings offer that when the DC bias increased, the peak-to-average-power ratio (PAPR) increased even when using different modulation orders. In contrast, comparing different modulation orders, F-OFDM shows better bit error rate (BER) performance, especially in low-order modulation schemes.Öğe Cloud assisted approach for determining WiFi problems in field deployed mesh APs - A case study for quality problems(Institute of Electrical and Electronics Engineers Inc., 2020) Demirtaş, Oğuz; Ilyas, MuhammadThe analysis of the WiFi problems, in terms of quality, of home users causes very high costs to manufacturers and service providers. The detection of problems is very difficult due to the variety of devices and protocols. Although cloud computing can be considered a good solution to these problems, collecting and analyzing such data is quite challenging. In this study, the field problems are investigated in a controllable test environment and pro-active solutions are proposed via a cloudbased approach in this manner. © 2020 IEEE.Öğe Comparative analysis of convolutional neural network architectures for classification of plant leaf diseases(IEEE, 2022) Al Heeti, Fatimah; Ilyas, MuhammadPlants play an essential role in the life of any living organism, human or animal, so protecting this organism from disease is an urgent necessity for the survival of living organisms. The development of science has reduced the time required to discover a disease, allowing us to detect and treat diseases early using artificial intelligence. In this scientific paper, we compared the performance of (Vgg-16, MobileNet, and ConvNext) through time and accuracy among these models. We trained these models by using transfer learning models of convolutional neural networks (CNN) to classify plant diseases (potatoes, tomatoes, and peppers). We used a dataset containing 20,639 images divided into 15 classes of different diseases, we also used the same number of parameter and the same number of layers in vgg16 and mobilenet but in convnext 24 layers.The dataset from the Kaggle site and the work environment on google colab using Python language. The results are shown vgg-16 is a high accuracy of 0.97 during the training process from convnext and mobilenet,but MobilNet is faster in the time 62s.Öğe Creating one time virtual encrypted identification number at the ATM(Institute of Electrical and Electronics Engineers Inc., 2022) Aldoghje, Fatma; Jinah, Abdullah; Ilyas, MuhammadThe discovery of ATMs is an important step in the development of banking transactions, the attacks increased on the ATM, And increased attempts to find out the pin code, to reduce the risk of these attacks on the ATM, We suggest a two-factor authentication method to increase the security of the bank accounts from repeated attacks, This method depends on entering a customer's bank card, Without the need to write the pin code for the card, It is based on a database stored in the automated teller machine This method relies on performing a simple arithmetic operation that anyone can perform, regardless of their level of learning, To increase security and reduce the risk of attacks, we suggested that the input be encrypted, And by using seven segments led digital encryption, we will reduce the chances of hackers knowing the secret number of a customer It is considered a successful encryption method because more than one number has the same code, and this will give strength to the code. The degree of security in this method is high and at the same time, It does not require great capabilities and is not expensive at the same time.Öğe Data transmission enhancement using optimal coding technique over ın vivo channel for ınterbody communication(2022) Mezher, Mohanad Ahmed; Din, Sadia; Ilyas, Muhammad; Bayat, Oğuz; Abbasi, Qammer Hussain; Ashraf, ImranWireless in vivo actuators and sensors are examples of sophisticated technologies. Another breakthrough is the use of in vivo wireless medical devices, which provide scalable and cost-effective solutions for wearable device integration. In vivo wireless body area networks devices reduce surgery invasiveness and provide continuous health monitoring. Also, patient data may be collected over a long period of time. Given the large fading in in vivo channels due to the signal path going through flesh, bones, skins, and blood, channel coding is considered a solution for increasing the efficiency and overcoming inter-symbol interference in wireless communications. Simulations are performed by using 50 MHz bandwidth at Ultra-Wideband frequencies (3.10–10.60 GHz). Optimal channel coding (Turbo codes, Convolutional codes, with the help of polar codes) improves data transmission performance over the in vivo channel in this research. Moreover, the results reveal that turbo codes outperform polar and convolutional codes in terms of bit error rate. Other approaches perform similarly when the information block length is increased. The simulation in this work indicates that the in vivo channel shows less performance than the Rayleigh channel due to the dense structure of the human body (flesh, skins, blood, bones, muscles, and fat).Öğe Delay root cause analysis and 3D modeling of LTE control communication using machine learning(Institute of Electrical and Electronics Engineers Inc., 2022) Mohammed, Sameer Qutaiba; Ilyas, MuhammadThis study investigates and evaluates delay root cause analysis and 3D modeling of LTE control communication utilizing sophisticated machine learning for network testing. The research studied LTE protocols for 5th-generation mobile telephony and provided guidelines for controlling LTE frequency for background knowledge, although it used an independent technique that did not employ LTE standards. 512 elements of input-output MIMO were employed for 100-GHz and 128 elements for mid-band sub-6-GHz. LOS is always 0.5. This paper is about LTE, not 3D modeling of LTE control path loss type communication using machine learning. This work's route loss depends on cross-pol beam LTE polarization (±45o). The receiver (Rx) operations and transmitter (Tx) activities in the estimated distance of 0.5 km at an approximate altitude of 15.25 m. Distance, handover authentication, rain, atmosphere, and sub-6GHz vs 100GHz weather conditions affect path loss. The methodology has enhanced the spatial variety by boosting transmitting power and transmitting efficiency. Authorizing and sanctioning ANN-based LTE frequency for both mid-band sub-6-GHz and 100-GHz is possible due to its planning and development using open-source material and strategy with high transmission power and rate under doubtful handover confirmation using MIMO input/yield receiving wires. This theory examines LTE innovation dimensioning as unbiased for various handover verification and allows input boundary alterations for various organization arrangement setups for LTE recurrent data transmission from 6 GHz to 100 GHz for three climate sorts. This cycle should be seen as an undeniable level way to examine LTE networks under various air conditions. Using signal handling tool compartment and explicit AI-based ANN calculation from AI toolkit in MATLAB R2019a, it is possible to create a result answer for three climate types in a dataset with an LTE communication level of exactness of downpour assimilation and abundance foliage miss fort.Öğe Design a tracing system for a seed supply chain based on blockchain(Institute of Electrical and Electronics Engineers Inc., 2020) Abdulhussein, Ayat B.; Hadi, Ameer K.; Ilyas, MuhammadBlockchain technology performs a process of storing inside a record, and this ledger is raised on a large number of parties (computers, servers). Records are encrypted and cannot be tampered with, as happens in centralized systems. In order to solve the problem of manipulating or modifying information and knowledge of the origin of the product and increasing the consumer's transparency of the product coming from a series of the supply chain, this research suggests building a system to tracing the product. All product information is stored in serial blockchain through an algorithm that organizes the work of each part of the supply chain and the information it stores. Also, an algorithm to retrieve product information by searching for Blockchain. The results are expected to be important in terms of increased food security and increased competition between distributors. The entire purpose behind supply chain the management and coordination are to give customers the level and nature of administration that they require and to do as such at less expense to the complete supply chain. Traceability is a big necessity in supply chain ventures, particularly for the agri-food industry. Building a product tracking system in a supply chain to enable the consumer and government agencies to track and know the source and origin of the product in an easy, safe and reliable way from tampering and provide the fixed system the just manager can approve accepted users that be trusted people because will add data that all world will see it for that in the system, we build an algorithm to generate the activation key for adding a client. © 2020 IEEE.Öğe Design of a smart microgrid for predictive energy generation(Institute of Electrical and Electronics Engineers Inc., 2023) Enad, Karam Hameed; Ilyas, MuhammadThe exploration of artificial neural networks (ANNs) in the realm of renewable energy-based smart grids is the primary focus of this study. The difficulties associated with the integration of renewable energy sources into the electrical grid, primarily due to their inherent variability and intermittency, are identified as the main problem. The smart grid technologies development is recognized as a solution to enhance the grid's efficiency and reliability. It is suggested that ANNs could significantly contribute to the smart grid system performance improvement. An examination of renewable energy-based smart grid key features, integration-related challenges, and potential benefits of incorporating ANNs are presented. Research on ANNs' application in various smart grid systems components, such as energy demand forecasting, energy generation and storage optimization, and grid stability management, are reviewed. Data division for this study was accomplished through random subsampling, with 80% of the data forming the training set and the remaining 20% comprising the testing set. A comparison between these two groups was subsequently performed. Following the computations to determine the Mean Squared Errors (MSEs) for a percentage range between 60% and 90%, the study concludes by highlighting areas requiring additional research to fully exploit the potential of ANNs in renewable energy-based smart grids. In this study, the main objective is to understand the role of ANNs in optimizing the performance of renewable energy-based smart grids and identify areas for future research.Öğe Detecting myocardial infraction in ECG waveforms using YOLOv8(Institute of Electrical and Electronics Engineers Inc., 2024) Albasrawi, Roaa; Ilyas, MuhammadThe detection of myocardial infarction (MI) using advanced imaging and analysis techniques is a pivotal advance- ment in medical diagnostics. This study employs YOLOv8, a sophisticated deep learning algorithm, for the identification of MI from the electrocardiogram (ECG) images, focusing specifically on the critical ST elevation segment associated with MI. Unlike traditional methods that rely on manual interpretation, our approach automates the detection process, significantly reducing the time and potential for human error. By fine-tuning YOLOv8 on a curated dataset and employing a loss-modified model, we achieved an average accuracy of 96% and a mean Average Precision (mAP) of 0.99 at a 50% confidence threshold, with a Recall of 97.7%. To make this technology accessible to medical staff and patients without technical expertise, we developed a user-friendly GUI that simplifies the detection process by clicking a button. This research not only highlights the potential of applying deep learning in cardiology but also emphasizes the importance of user-centered design in medical technology, promising significant improvements in clinical diagnosis and patient care.Öğe Effect of PE file header features on accuracy(Institute of Electrical and Electronics Engineers Inc., 2020) Al-Khshali, Hasan H.; Ilyas, Muhammad; Uçan, Osman NuriMalware programmers look for ways to attack computers and networks. They try to find entry points that bypass security and enable them to slip into the system. One of these ways is through Portable Executable (PE) files. On the other hand, methods are devised to discover this danger and take action against it. Artificial Intelligence (AI) can play an important role in the process of discovering malwares inside PE files. Using AI as a tool, this work aims to study the features of PE file headers as a means of detecting malware and assess the effect of these features on the level of accuracy. The study uses various numbers of PE features. Two different algorithms are used, each with two options, in order to discover their relative effectiveness. Tests are carried out using a specified control data set so that relative performance can be assessed. The criterion used is the level of accuracy obtained with a large number and variation of groups of studies. Each study starts with a collection of features, then features are progressively added to study the impact of these features on accuracy. This was important in showing that not all the features have a positive impact on accuracy. Also, there were some indications that using a large number of features will not always improve the accuracy. Using graphs, it was shown that accuracy will be enhanced after adding a certain number of features. Graphs also show that, along the way of adding the features, accuracy sometimes improves and, in some other times, it goes down, so not all added features are useful. More than 100 runs were made, using a total of 29 features. The highest accuracy obtained with Decision Tree was 0.987, and 0.979 in Neural Networks-Multi-layer Perceptron (NN-MLPC). © 2020 IEEE.Öğe Efficient WSN routing using bootstapped PSO clustering(Institute of Electrical and Electronics Engineers Inc., 2022) Obad, Ahmed Thaer; Ilyas, MuhammadThe increasing convergence of microprocessors, wireless communication, and micro electro-mechanical systems (MEMS) has led to the development of Wireless Sensor Networks (WSNs). Optimization problems for WSN are usually versions of classic problems in the operational research area, such as routing and clustering, which are NP- Difficult. Thus, it is natural to use meta-heuristics to solve these problems. The main objective of this work is to apply the Bootstrapped PSO metaheuristic to form WSN clusters. bootstrapped PSO was chosen because it is a meta-heuristic that proved to be efficient in solving similar problems, such as P-medians, and because it is a method not yet used to solve the problem addressed in this work.
