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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Rao, Ashutosh Kumar Nagwanshi, Kapil Kumar Shukla, Manoj Kumar Aswal, Shobha Computer Science & Engineering Amity School of Engineering & Technology Amity University Rajasthan India Computer Science & Engineering Guru Ghasidas Viswavidalaya Raipur India Computer Science & Engineering Amity University Uttar Pradesh India School of Computing Graphic Era Hill University Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350398496

Wireless sensor networks (WSNs) were initially developed for research and development purposes, and are now widely employed in a variety of domains such as communication, weather prediction, agriculture, industries, smart physical condition monitoring, and surveillance. In the agriculture sector, in order to increase yields, the IoT-enabled WSN is extensively used to monitor the environment and climatic conditions by employing a variety of sensors to sense data. These types of sensors are fully deployed in the required agricultural environment to improve production yield through intelligent farming and decision making, to find better and necessary information about plants, such as temperature, humidity, and irrigation patterns. In India, Agriculture gives employment to almost 70% of the population and generates 27 % of the GDP (Gross domestic production). This makes agriculture an important area for research and development. This research study is completely based on the surveying of different methods, which are completely based on Internet of Things (IoT) for leveraging betterresults. © 2023 IEEE.

关键词： Energy efficiency

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An Effective Power Optimization Approach Based on Whale Optimization Algorithm with Two-Populations and Mutation Strategies

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Chinese Journal of Electronics 2024年第2期33卷 423-435页

作者： Juncai HE Zhenxue HE Jia LIU Yan ZHANG Fan ZHANG Fangfang LIANG Tao WANG Limin XIAO Xiang WANG Hebei Agricultural University Beijing Information Science and Technology University School of Computer Science and Engineering Beihang University School of Electronic and Information Engineering Beihang University

Power is an issue that must be considered in the design of logic circuits. Power optimization is a combinatorial optimization problem, since it is necessary to search for a logical expression that consumes the least amount of power from a large number of Reed-Muller(RM) logical expressions. The existing approach for optimizing the power of multi-output mixed polarity RM(MPRM) logic circuits suffer from poor optimization results. To solve this problem, a whale optimization algorithm with two-populations strategy and mutation strategy(TMWOA) is proposed in this paper. The two-populations strategy speeds up the convergence of the algorithm by exchanging information about the two-populations. The mutation strategy enhances the ability of the algorithm to jump out of the local optimal solutions by using the information of the current optimal solution. Based on the TMWOA, we propose a multi-output MPRM logic circuits power optimization approach(TMMPOA). Experiments based on the benchmark circuits of the Microelectronics Center of North Carolina(MCNC) validate the effectiveness and superiority of the proposed TMMPOA.

关键词： Multi-output mixed polarity Reed-Muller Power optimization Combinatorial optimization problem Whale optimization algorithm Two-populations strategy Mutation strategy

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Cloud Resource Management: Monitoring 5

Cloud Resource Management: Monitoring

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5th International Conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Rawat, Anshika Singh, Shubham Singh, Pawan Department of Computer Science and Engineering Amity School of Engineering and Technology Lucknow Amity University Uttar Pradesh India Department of computer science and engineering GLA University Mathura Uttar Pradesh India

ISBN: (纸本)9798400709418

The management and use of computer resources within enterprises has changed as a result of the emergence of cloud computing as a paradigm shift. With its diverse and comprehensive portfolio of cloud services, including AWS CloudWatch for monitoring, Amazon Web Services (AWS) is at the vanguard of this revolution. In order to fully utilize the capabilities of these platforms and achieve cost- effectiveness, scalability, and optimal performance, proper cloud resource management is essential. This, study offers a thorough investigation of AWS's cloud resource management, with a focus on Particle Swarm Optimization (PSO) integration as a cutting-edge optimization technique. The dynamic and ever-changing workloads seen in cloud computing systems present a special set of issues for resource allocation and optimization. However, finding the ideal compromise between performance and cost-efficiency is still a challenging task. This study examines the changing environment of cloud resource management with an eye toward the future. In order to enable even more intelligent resource allocation decisions, we take into account the possible integration of machine learning and predictive analytics into our PSO framework. We also look at the broader implications of PSO-driven resource management. © 2023 ACM.

关键词： Resource allocation

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Viability of Viola-Jones Algorithm for Drowsiness Detection in Drivers 9

Viability of Viola-Jones Algorithm for Drowsiness Detection ...

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9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Joshi, Kireet Jain, Paras Dhiman, Gamini Gupta, Vishan Kumar Singh, Harvinder Sharma, Ujjwal Graphic Era Deemed To Be University Department of Computer Science & Engineering Dehradun India Vit Bhopal University School of Computing Science And Engineering Madhya Pradesh Sehore India Amity University Punjab Amity School of Engineering & Technology Mohali India

ISBN: (纸本)9798350394474

This research paper investigates the viability ofusing the Viola-Jones algorithm for drowsiness detection in drivers. The algorithm is designed to detect the presence of a face, locate the eyes within the face region, and then calculate the Eye Aspect Ratio (EAR) to determine if the eyes are open or closed. The study uses a dataset of images of the driver's face and tests the algorithm's performance under various lighting, pose, and expression variations. The results show that the Viola-Jones algorithm is a robust and effective method for detecting drowsiness in drivers, achieving high accuracy rates even in challenging conditions. The paper concludes by discussing the potential applications of this technology in real-world settings, such as in the development of driver assistance systems for improving road safety. © 2024 IEEE.

关键词： computer vision

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Demonstration of high-performance STO-based WORM devices controlled by oxygen-vacancies and metal filament growth

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Journal of Materials Chemistry C 2024年第23期12卷 8418-8425页

作者： Hsu, Chih-Chieh Wen, Xiu-Ming Xiao, Kai-Zer Jhang, Wun-Ciang Joodaki, Mojtaba Department of Electronic Engineering National Yunlin University of Science and Technology Douliu64002 Taiwan Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Douliu64002 Taiwan School of Computer Science and Engineering Constructor University Bremen28759 Germany

Herein, we propose high-performance Ti/STO/n+-Si and Ag/STO/n+-Si write-once-read-many-times devices, where the resistance transition mechanisms are controlled by oxygen vacancies in the STO layer and metal atoms from the electrochemically active Ag electrode, respectively. The as-deposited STO films have a low oxygen-vacancy content of 12.2%. When the Ti electrode is deposited, the formation of a thin TiOx interfacial layer at the Ti/STO interface is achieved, which leads to an increase of oxygen vacancy content in the STO layer to 28.6%. The relatively higher oxygen vacancy density means that the Ti/STO/n+-Si device can provide a voltage-polarity-independent memory function. In contrast, the resistance transition of the Ag/STO/n+-Si device can be limited in the positive voltage region because Ag cations can only be driven into the STO layer using a positive bias. Both devices show high ILRS/IHRS ratios, superior data retention capability, and fast transition speeds. © 2024 The Royal Society of Chemistry.

关键词： Oxygen vacancies

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New insights into residual triiodide ion removal from iodinated water using magnetic CoFe2O4 nanoparticles: exploring adsorption behavior and mechanisms

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Environmental science and Pollution Research 2024年第58期31卷 66302-66317页

作者： Naagar, Manish Chalia, Sonia Wan, Fayu Thakur, Preeti Sharma, Pritam Babu Thakur, Atul Department of Aerospace Engineering Amity University Haryana Haryana Gurugram122413 India School of Electronics and Information Engineering Nanjing University of Information Science and Technology Nanjing210044 China Amity Institute of Nanotechnology Amity University Haryana Haryana Gurugram122413 India

This study evaluates the adsorption performance of cobalt ferrite (CoFe2O4)–based magnetic nanoadsorbents (CF-MagNa) for the removal of triiodide ions (I3-) from iodinated water. The crystalline structure and phase purity of the synthesized material were confirmed via X-ray diffraction (XRD), which determined a crystallite size of 42 nm and a specific surface area of 26.98 m2/g. Field emission scanning electron microscopy (FESEM) revealed a porous morphology conducive to enhanced adsorption. The ferromagnetic properties of CF-MagNa were characterized using vibrating sample magnetometry (VSM), which demonstrated a saturation magnetization (σs) of 74.98 emu/g, a remanent magnetization (σr) of 29.82 emu/g, and a coercivity (Hc) of 1304 Oe, significant magnetic separation potential. Batch adsorption experiments revealed a 61.6% reduction in I3- concentration at a CF-MagNa dosage of 2 mg/mL. Adsorption isotherms were analyzed, with the Langmuir model yielding a maximum adsorption capacity (Qmax) of 13.641 mg/g and a Langmuir constant (KL) of 0.00996 L/mg. The Freundlich model provided a capacity factor (KF) of 1.892 mg/g and a heterogeneity factor (nF) of 1.805 L/mg, while the Temkin model yielded a heat of adsorption (B) of 3.404 J/mol and a Temkin constant (KT) of 0.743 L/g. The Dubinin-Radushkevich (D-R) isotherm demonstrated the highest correlation (R2 = 0.97), with a maximum adsorption capacity of 8.28 mg/g. These results highlight CF-MagNa’s efficacy as a potential adsorbent for water treatment, with promising applications in environmental remediation and sustainable water purification technologies. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Saturation magnetization

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Multi-UAV path planning for multiple emergency payloads delivery in natural disaster scenarios

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Journal of Electronic science and technology 2025年第2期23卷 1-18页

作者： Zarina Kutpanova Mustafa Kadhim Xu Zheng Nurkhat Zhakiyev Department of Computer Engineering Astana IT UniversityAstana010000Kazakhstan School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu610054China Department of Computational and Data Science Astana IT UniversityAstana010000Kazakhstan

Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network *** natural disasters,timely delivery of first aid supplies is *** UAVs face risks such as crashing into birds or unexpected *** systems with parachutes risk dispersing payloads away from target *** objective here is to use multiple UAVs to distribute payloads cooperatively to assigned *** civil defense department must balance coverage,accurate landing,and flight safety while considering battery power and *** Q-network(DQN)models are commonly used in multi-UAV path planning to effectively represent the surroundings and action *** strategies focused on advanced DQNs for UAV path planning in different configurations,but rarely addressed non-cooperative scenarios and disaster *** paper introduces a new DQN framework to tackle challenges in disaster *** considers unforeseen structures and birds that could cause UAV crashes and assumes urgent landing zones and winch-based airdrop systems for precise delivery and return.A new DQN model is developed,which incorporates the battery life,safe flying distance between UAVs,and remaining delivery points to encode surrounding hazards into the state space and ***,a unique reward system is created to improve UAV action sequences for better delivery coverage and safe *** experimental results demonstrate that multi-UAV first aid delivery in disaster environments can achieve advanced performance.

关键词： Deep Q-network First aid delivery Multi-UAV path planning Reinforcement learning Unmanned aerial vehicle(UAV)

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Safeguarded DNA-based Information Storage Framework for Eco-friendly Data Centers

Safeguarded DNA-based Information Storage Framework for Eco-...

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2023 Workshop on Advances in Computational Intelligence, ACI 2023

作者： Bhattacharya, Pronaya Chatterjee, Sudip Singh, Anupam Department of Computer Science and Engineering Amity School of Engineering and Technology Research and Innovation Cell Amity University Kolkata700135 India Department of Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun India Department of Computer Science and Engineering Graphic Era Deemed to be University Uttarakhand Dehradun India

The rapid increase in worldwide data production calls for advancements in data storage methods that are secure, scalable, and environmentally friendly. This paper introduces a cutting-edge DNA-based data storage framework. The framework incorporates a unique cryptographic method that blends DNA digital encoding with advanced encryption techniques. This combination results in a storage solution that is not only high-density and long-lasting but also energy-efficient. Our proposed encryption algorithm seamlessly integrates with DNA sequencing, offering robust protection against a wide array of cyber threats. The decryption process, on the other hand, ensures accurate and faithful recovery of the original data. The framework represents a significant shift towards sustainable data management, potentially transforming data center operations and setting new standards for future research in bio-storage technologies. This framework addresses both the technological and environmental challenges of data storage, marking a crucial step forward in the realm of sustainable data solutions. © 2024 Copyright for this paper by its authors.

关键词： DNA

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Diabetes Estimation Through Data Mining Using Optimization, Clustering, and Secure Cloud Storage Strategies

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SN computer science 2024年第6期5卷 1-9页

作者： Gupta, Shyam S. Pandey, Tushar Kumar Raju, Vadali Pitchi Shrivastava, Rajeev Pandey, Rajeev Nigam, Ankita Roy, Vandana Department of Computer Science and Engineering Amity School of Engineering and Technology (ASET) Amity University College of Community Science Central Agricultural University Indur Institute of Engineering & amp Technology Princeton Institute of Engineering & amp Technology for Women Hyderabad DoCSE UIT-RGPV Department of CSE Princeton Institute of Engineering and Technology for Women Hyderabad Department of EC Gyan Ganga Institute of Technology and Sciences

Asian Indians face a unique risk for type 2 diabetes, with earlier onset and diagnosis at lower BMIs than other populations. Their susceptibility to diabetes-related health risks is higher compared to white populations. India struggles with low public awareness, a shortage of healthcare professionals, and limited treatment accessibility. Innovative strategies using available technological resources could significantly improve diabetes management in India. These challenges, common in developing countries, suggest that insights from India’s experience could benefit global diabetes management. This study aims to develop a hybrid model for predicting type 2 diabetes mellitus (T2-DM) to enhance awareness and preventive strategies. Using the Pima Indian Diabetes Dataset, the model’s effectiveness is validated through various performance metrics. The Fuzzy C-Means (FCM) clustering method is introduced, outperforming traditional models by creating more cohesive clusters with fewer variables. To enhance FCM's effectiveness, the Particle Swarm Optimization (PSO) technique is integrated, preserving FCM's strengths while improving efficiency. The hybrid model's sensitivity is 5.85% higher than K-Means + C4.5, and specificity is 2.79% higher. The proposed model achieves greater accuracy (96.58%) than previous methods. This approach aims to improve diabetes care in India and offers a model adaptable worldwide, addressing a critical global health challenge. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： BMI Data mining Diabetic retinopathy FCM PSO T1-DM T2DM

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Recognition of American sign language using modified deep residual CNN with modified canny edge segmentation

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Multimedia Tools and Applications 2025年 1-28页

作者： Hariharan, U. Devarajan, Devikanniga Kumar, P. Santhosh Rajkumar, K. Meena, M. Akilan, T. Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab Mohali140413 India Department of Computer Science and Engineering GITAM University Karnataka Bengaluru561203 India Department of Information Technology Faculty of Engineering and technology SRM Institute of Science and Technology Ramapuram Tamil Nadu Chennai600089 India Department of Data Science and Business Systems School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai603203 India Department of Computer Science and Engineering Sri Sairam Engineering College Tamil Nadu Tambaram602109 India Research Coordinator Dept. of IQAC Amity University Kolkata West Bengal 700135 India

American Sign Language (ASL) recognition aims to recognize hand gestures, and it is a crucial solution to communicating between the deaf community and hearing people. However, existing sign language recognition algorithms still have some drawbacks, such as difficulty recognizing hand movements and low recognition accuracy for most sign language recognition. A Modified Convolutional Neural Network (MCNN) deep residual 101 classifier-based American Sign Language identification system has been developed to address this problem. There are three main parts presents in the method. The first part is pre-processing the images to remove the noise, enhance the contrast of the picture, adjust the contrast level and smoothen the picture using various filters. The second part is the segmentation, and it’s used to partition the image using a modified canny edge detection method by removing all weak edges present in the image. Finally, classification will be done using the Modified CNN deep residual 101 classifiers. By classifying the image, the American Sign Language is accurately identified. This process is conducted through images. The outcome shows that the suggested approach has a 0.97% accuracy and a 0.05% False Positive Rate. Other CNN architectures such as resNet 50 and resNet 18 reached 0.90% and 0.80% accuracy, respectively, which is lower than our proposed method. In addition, the resNet 101 classifier effectively recognizes the difficult hand gestures through the image data. It obtains high recognition accuracy for 36 signs is 0 to 9 numbers and a to z alphabets from American Sign Language. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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