Bulletin of Electrical Engineering and Informatics
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    2885 research outputs found

    Performance analysis of different methods for optimal sliding mode control of DC/DC buck converter

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    Performance is always need to be considered in designing DC/DC buck converter. Despite the drastic use of DC/DC buck converter in industry, limitations due to unregulated voltage and current still persist. The dynamic performance of three methods of sliding mode control (SMC) were investigated. The comparative assessment of integral sliding mode control (ISMC) method, showed that the ISMC has an outstanding performance over the other tested methods of two variables with conventional SMC. The excellent performance of ISMC, under diverse operating conditions that include varying input voltage and load resistance, is achievable and it can provide a considerable edge over other control techniques in various field of industries, include electrical vehicle. The ISMC is highly preferable to overcome the problem of varying switching frequency, as well as optimizing power on transient response. The performance characteristic of ISMC shows fast dynamic response of various applications. Detailed simulations of the three SMC methods were carried out to validate the control algorithms using MATLAB/Simulink software

    Customizing the minimum number of replicas for achieving fault tolerance in a cloud/grid environment

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    Networks consist of numerous resources; it is crucial not to overlook fault tolerance and consider it during planning. This is because errors during implementation can result in wasted time and effort, thereby squandering these resources. One solution to address this issue effectively is to implement the task on multiple resources to minimize the occurrence of failed tasks. However, employing an unspecified or fixed number of resources can lead to the depletion of network resources and the overall failure of the network. Replication plays a pivotal role in enhancing data availability in distributed systems. By storing data in multiple locations, users can still access it even if some copies are unavailable due to site failure. Many replication-based algorithms utilize a predetermined number of iterations per function, which may consume excessive network resources, even if the ongoing task does not require such abundant resources. This paper proposes task replication as a viable mechanism for an efficient and fault-tolerant scheduling system. We introduce an algorithm that dynamically selects the optimal and minimal number of replicas based on the network's failure history. This approach aims to minimize the failure rate during task execution

    Energy management in hybrid complexes based on wind generation and hydrogen storage

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    This work is devoted to the analysis of scientific articles in the field of hybrid energy complexes based on hydrogen technologies and renewable energy sources. A special attention is given to wind generation. The review of the topics of scientific publications indexed in the Scopus database in the field of research is carried out, the most frequently encountered topics and the rarest ones are highlighted. Brief statistics about publications selected for detailed analysis are given. The most interesting direction for studying is development of control systems for hybrid energy complexes. Several traditional approaches, which are commonly used in research on this topic and methods are highlighted. The existing shortcomings and inaccuracies in the overviewed works are identified. Conclusions are drawn about the need to transform existing methods and specific proposals are made to improve management systems to increase the efficiency of decision-making and achieve greater economic benefits. Promising areas of research that also require special attention are formulated

    Systematic review of mobile applications in learning features to support learners living with epilepsy disorders

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    We systematically review mobile health applications in supporting learners living with epilepsy disorders. There are two objectives of this study i.e., assessing the existing epilepsy-related apps and providing information about some features provided by the apps. In total, 18 of 47 mobile apps that meet the final criteria were reviewed using the Mobile Application Rating Scale (MARS). We found that more than half of the apps had below-average quality and most offered only a few distinct functionalities. Six of them were deemed high quality since they met all standard criteria. In terms of self-management features, we identified several important features such as the provision of a seizure calendar (14/18, 78%), report generation (5/18, 28%), adding individual seizure occurrence and causes (9/18, 50%), and emergency alert (6/18, 34%). The majority of the apps included medication tracker (12/18, 67%), expert consultation (6/18, 34%), and educational features (10/18, 56%). Moreover, 40% of included apps have considered self-efficacy features by providing analytical support for seizure frequency, duration, occurrence distribution, and analysis. This research can make in-person support more feasible for epilepsy learners so that it helps families, caregivers, and educators to easily manage the risk and perform continuous aid. This research can also be the basis for developing more patient-centered software for epilepsy management

    Secure map-based crypto-stego technique based on mac address

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    Steganography and cryptography are spy craft cousins, working differently to achieve the same target. Cryptography is perceptible and observable without understanding the real content, while steganography hides the content so that it is not perceptible or observable and without producing noticeable changes to the carrier image. The challenge is finding the right balance between security and retrievability of embedded data from embedding locations without increasing the required embedded information. This paper proposes a secure map-based steganography technique to enhance the message security level based on the sender and recipient mac addresses. The proposed technique uses rivest-shamir-adleman (RSA) to encrypt the message, then embeds the cipher message in the host image based on the sender and recipient media access control addresses (mac addresses) exclusive or operation "XOR" results without increasing the required embedded information for the embedding location map. The proposed technique is evaluated on various metrics, including peak signal-to-noise ratio (PSNR) and embedding capacity, and the results show that it provides a high level of security and robustness against attacks without an extra location map. The proposed technique can embed more data up to 196.608 KB in the same image with a PSNR higher than 50.58 dB

    Mobile application: awareness of the population on the environmental impact

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    Nowadays, pollution keeps increasing due to social, political, economic, cultural, and environmental factors. Environmental awareness is close to zero because people prioritize personal activities. In that sense, the objective of this investigation is to raise environmental awareness in the population regarding the impact of pollution and support this through a mobile application (APP) that helps reduce pollution. The methodology used was the cascade, and through its phases, it was developed the prototype design of the mobile APP. The results obtained from this hybrid research were through a survey using ATLAS.ti 22; it concluded that environmental awareness begins at home and is taught by the parents, also it should be promoted from elementary school to high school and even in college. Moreover, in a survey, the users stated by 89% that the use of this mobile APP can help reduce the environmental impact. Also, in the validation through expert judgment, all the attributes were accepted with an average of 81%, that of functionality was the lowest, and the highest was that of consistency and integration with 83%. Finally, environmental education should be a priority policy in any country, as this will benefit its population

    Reliability evaluation of non-isolated high gain interleaved DC-DC converter

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    A high gain DC-DC converter is the crucial part in renewable energy systems (RES) and in electric vehicular systems. The reliability of those high-gain converters needs to be assessed for the long-term operation of renewable energy systems. This article presents the reliability analysis of non-isolated high gain interleaved DC-DC converter. The analysis primarily relies on calculating the mean time between failures (MTBF). Based on military handbook (MIL-HDBK-217) criteria, the reliability calculation is performed. Stress factors and predicted failure rate for each component of presented converter is evaluated and tabulated. Reliability evaluation is performed for 1.5 kW hardware prototype. Based on reliability evaluation results, a reliable converter with better operating life time has been introduced

    YOLO-based object detection performance evaluation for automatic target aimbot in first-person shooter games

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    First-person shooter (FPS) focuses on first-person perspective action gameplay, with gunfights usually giving the player a choice of weapons, significantly impacting how the player approaches or strategies. General military-themed FPS games have realistic models with actual weaponsÒ€ℒ shapes and characteristics. This type of game requires high aiming accuracy while using a mouse on a PC. However, not all players have a fast response time in knowing the surrounding situation. New players may need aid when targeting enemies in the FPS world. One popular yet underhanded method is injecting a program code using a dynamic-link library (DLL) to manipulate memory and asset data from the game. Instead of DLL, we promote a novel approach using the playerÒ€ℒs real-time game screen, detecting the person without injecting program code into the game. The you only look once (YOLO) algorithm is used as an object detector model since it can process images in real time for up to 45 frames per second. The proposed object detection has an outstanding performance with 65% accuracy, 98% precision, and 61% recall of 51 tests for each game. YOLOÒ€ℒs fastest detection speed produces an average of 35 FPS on the YOLO tiny variant using a mixed precision (half) graphics processing unit (GPU)

    XSSer: hybrid deep learning for enhanced cross-site scripting detection

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    The importance of an effective cross-site scripting (XSS) detection system cannot be overstated in web security. XSS attacks continue to be a prevalent and severe threat to web applications, making the need for robust detection systems more crucial than ever. This paper introduced a hybrid model that leverages deep learning algorithms, combining recurrent neural network (RNN) and convolutional neural network (CNN) architectures. Our hybrid RNN-CNN model emerged as the top performer in our evaluation, demonstrating outstanding performance across key metrics. It achieved an impressive accuracy of 96.74%, excelling inaccurate predictions. Notably, the precision score reached an impressive 97.78%, highlighting its precision in identifying positive instances while minimizing false positives. Furthermore, the model's recall score of 95.65% showcased its ability to capture a substantial portion of true positive instances. This resulted in an exceptional F1-Score of 96.70, underlining the model's remarkable balance between precision and recall. Compared to other models in the evaluation, our proposed model unequivocally demonstrated its leadership, emphasizing its excellence in detecting potential XSS vulnerabilities within web content

    Energy efficiency based RPL protocol using grasshopper optimization algorithm

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    The routing protocol for low-power and lossy networks (RPL) is necessary for the internet of things (IoT) because it offers scalable, reliable, and energy-efficient routing capabilities. The trickling algorithm generates a destination-oriented directed acyclic graph (DODAG) with the broadcasting of suppression. However, broadcast suppression is insufficient when addressing network coverage and optimization problems based on uneven node distribution. Network congestion develops in large-scale IoT implementations where many devices are interconnected and congestion causes data transmission delays, decreased overall reliability, and higher latency. In this paper, the grasshopper optimization algorithm with the DODAG (GOA-DODAG) is proposed to determine optimization problems and energy-efficient reliable routing paths which include coverage-based dynamic trickling technique to construct DODAG energy-efficient without affecting the coverage of network and data routing reliability. The GOA-DODAG achieves a 98% packet delivery ratio (PDR) while consuming 0.48 mJ, which is more preferable in comparison to the existing methods like efficient-routing protocol for low-power and lossy networks (E-RPL), reliable and energy-efficient RPL (REFER), elaborated cross-layer RPL objective function to achieve energy efficiency (ELITE)

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