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Maximizing Harvested Energy in Natural Energy Powered RF WPT with Nonlinear EH Model

IEEE Transactions on Wireless Communications 2025年

作者： Zhang, Xiang Xiong, Ke Chen, Wei Fan, Pingyi Gao, Bo Letaief, Khaled Ben Collaborative Innovation Center of Railway Traffic Safety School of Computer Science and Technology Engineering Research Center of Network Management Technology for High Speed Railway Ministry of Education China Beijing Jiaotong University National Engineering Research Center of Advanced Network Technologies Beijing100044 China Department of Electronic Engineering China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China Department of Electrical and Computer Engineering Hong Kong Hong Kong

In the typical radio frequency (RF)-based wireless power transfer (WPT) system, the wireless power station (WPS) connected to the grid transmits energy to charge low-power sensors via radio signals. Such a system may not be green and also difficult to deploy in some special areas including deserts and mountainous areas, because it depends on the grid. To achieve a green RF WPT system design, this paper considers that the WPS is powered by natural energy sources rather than the grid. To explore the maximal total amount of the energy that can be harvested by the sensors, we focus on the offline setting, so similar to many existing works on offline optimization, we assume that the WPS knows prior knowledge about energy arrivals and channel changes, and then formulate an optimization problem to maximize the total harvested energy via optimizing the WPS's time-domain transmit power subject to multiple constraints, including the finite battery capacity at the WPS, the causal relationship between the natural energy harvesting and the WPT, and the transmit power budget of the WPS, where for practicality, the nonlinear energy harvesting (EH) model is also taken into account. To solve this non-convex problem, we first equivalently transform it by using the epigraph reformulation and the variable substitution, and then use the first-order Taylor expansion to get an approximate convex version. Then, we present a successive convex approximation (SCA)-based algorithm to improve the accuracy of the obtained solution for approaching the optimal one. For the special case with a single sensor, we further propose a branch and bound (BB)-based algorithm that is able to get a more accurate solution with lower complexity than the SCA-based one. Numerical results demonstrate that the proposed algorithms are able to achieve the near-global optimal solution. As the average recharge rate increases, compared with the other two baselines, i.e., the greedy power (GP) policy and the constant pow

关键词： Budget control

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Enhanced QoS Optimization of Opportunistic Networks using Decision Tree

Enhanced QoS Optimization of Opportunistic Networks using De...

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Communication, computer sciences and Engineering (IC3SE), International Conference on

作者： Mansi Mathur Ritu Sawanni Anuj Kumar Ayushi Jain Atul Kumar Pal Manika Manwal Department of Information Technology Management Education and Research Institute (MERI) (Affiliated to GGSIP University) New Delhi India Department of Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Department of Computer Science and Engineering Rajkiya Engineering College (Affiliated to Dr. APJ AKTU) Kannauj Lucknow India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Opportunistic networks are a type of dynamic wireless network that lack a fixed infrastructure and rely on intermittent connections between nodes to facilitate communication. Quality of Service (QoS) is an essential factor for the efficient operation of opportunistic networks, as it ensures that data is delivered in a timely and reliable manner. This paper proposes an enhanced QoS optimization approach for opportunistic networks using a Decision Tree algorithm. The algorithm considers various network parameters such as node mobility, data transmission rate, and available storage capacity to predict the optimal routing path for data transmission. The Decision Tree algorithm uses a classification technique to build a model based on historical data to identify the most suitable routing path for each data transmission. This approach allows for dynamic adaptation to changing network conditions, improving the overall performance and QoS of the opportunistic network. By incorporating the Decision Tree algorithm into the routing decisions of the opportunistic network, we can achieve better QoS optimization than traditional routing protocols. Our experimental results show that the proposed approach outperforms existing routing protocols regarding data delivery ratio, end-to-end delay, and energy consumption, making it a promising solution for enhancing QoS in opportunistic networks.

关键词： Energy consumption Quality of service Routing Prediction algorithms Routing protocols Delays Classification algorithms

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Integration of AI with the Cybersecurity: A detailed Systematic review with the practical issues and challenges 5

Integration of AI with the Cybersecurity: A detailed Systema...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Lourens, Melanie Dabral, Amar Prakash Gangodkar, Durgaprasad Rathour, Navjot Tida, Nagabhushanam Chadha, Anupama Durban University of Technology Faculty of Management Sciences South Africa Graphic Era Deemed to Be University Department of Hospitality Management Uttarakhand Dehradun India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Hill University Department of Computer Science & Engineering Uttarakhand Dehradun India Uttaranchal Institute of Technology Uttaranchal University Uttarakhand Dehradun India Koneru Lakshmaiah Education Foundation. Department of Law Andhra Pradesh Guntur India Computer Applications MRIIRS Faridabad India

ISBN: (纸本)9798350398267

Not only have there been a lot more cyberattacks in recent years, but they have also gotten much more advanced. Therefore, developing a cyber-resilient strategy is of utmost significance. In the event of a cyberattack, traditional security measures are insufficient to prevent data leaks. Cybercriminals have mastered the use of cutting-edge methods and powerful tools for data intrusion, hacking, and assault. Fortunately, the use of artificial intelligence (AI) technologies has the creation of intelligent models for securing systems against attackers. AI technologies can quickly advance to meet complicated problems, making them useful as fundamental cybersecurity tools. AI-based solutions can provide effective and robust cyber defense capabilities to identify malware attacks, network intrusions, phishing and spam emails, data breaches, and alert security incidents when they occur. This paper provides a summary of existing research regarding the advantages of AI in cybersecurity and a review of the impact that AI has had on cybersecurity. © 2022 IEEE.

关键词： Cybersecurity

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Implementation of Cyber Security for Enabling Data Protection Analysis and Data Protection using Robot Key Homomorphic Encryption 6

Implementation of Cyber Security for Enabling Data Protectio...

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6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022

作者： Biswas, Ankur Karan, Ashish Nigam, Nidhi Doreswamy, Hema Sadykanova, Serikkhan Rauliyevna, Mangazina Zhanel Adamas University Dept. of Comp. Sc. & Engg. Kolkata India Computer Science Independent Researcher and Government Officer Delhi India Computer Science and Information Technology Rajiv Gandhi Proudyogiki Vishwavidyalaya' India Welingkar Institute of Management India International Education Corporation Department of Linguistics Almaty Kazakhstan

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

Cloud computing plays major role in the development of accessing clouduser's document and sensitive information stored. It has variety of content and representation. Cyber security and attacks in the cloud is a challenging aspect. Information security attains a vital part in Cyber Security management. It involves actions intended to reduce the adverse impacts of such incidents. To access the documents stored in cloud safely and securely, access control will be introduced based on cloud users to access the user's document in the cloud. To achieve this, it is highly required to combine security components (e.g., Access Control, Usage Control) in the security document to get automatic information. This research work has proposed a Role Key Homomorphic Encryption Algorithm (RKHEA) to monitor the cloud users, who access the services continuously. This method provides access creation of session-based key to store the singularized encryption to reduce the key size from random methods to occupy memory space. It has some terms and conditions to be followed by the cloud users and also has encryption method to secure the document content. Hence the documents are encrypted with the RKHEA algorithm based on Service Key Access (SKA). Then, the encrypted key will be created based on access control conditions. The proposed analytics result shows an enhanced control over the documents in cloud and improved security performance. © 2022 IEEE.

关键词： Cryptography

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Fog Restoration in Hazy Images using Deep Transfer Learning

Fog Restoration in Hazy Images using Deep Transfer Learning

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Smart Devices (ICSD), International Conference on

作者： Navin Kumar Agrawal Viboo Sharma Pranita Singh Savya Sachi Arpit Jain Md Mohtab Alam Department of Computer Engineering and Applications GLA University Mathura U.P. India Department of IT Hindustan College of Science and Technology Mathura U.P. India Department of Computer Science and Engineering Roorkee Institute of Technology Roorkee U.K. India Department of Information Technology L N Mishra College of Business Management Muzaffarpur Bihar India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Computer Science & Engineering Eklavya University Damoh M.P. India

ISBN: (数字)9798350394412

ISBN: (纸本)9798350394429

Issues like low vision and the distortion of spectral and spatial information in photographs can be brought on by unfavorable atmospheric circumstances including smog, rain, overcast sky, fog, and smoke. This piece looks at images taken in a hazy environment. While de-smogging requires veil and transmission map data, optical imaging systems are limited to capturing smoggy images. To restore blurry photographs, effective optical information prediction is necessary. Research has shown that optical information anticipated by the dark channel prior technique frequently produces subpar images in photographs with areas of higher brightness, noticeable pollution gradients, or textured information. In order to estimate optical information, this study makes use of Deep Transfer Learning (DTL) and Optimized Gradient Prior Prediction (OGPP).We gathered benchmark images of both smoggy and smog-free environments in order to train the DTL model. The OGPP technique uses the smog gradient, which the DTL model is taught to anticipate, to recover pictures free of pollution. A comparison analysis shows that when it comes to recovering hazy photos, the OGPP restoration model performs better than other approaches.

关键词： Integrated optics Performance evaluation Pollution Rain Transfer learning Optical distortion Predictive models Optical imaging Image restoration Smart devices

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Impact of COVID-19 on Predicting 2020 US Presidential Elections on Social Media 16th

Impact of COVID-19 on Predicting 2020 US Presidential Electi...

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16th International Conference on Information Technology and Applications, ICITA 2022

作者： Khan, Asif Zhang, Huaping Boudjellal, Nada Hayat, Bashir Dai, Lin Ahmad, Arshad Al-Hamed, Ahmed School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China The Faculty of New Information and Communication Technologies University Abdelhamid Mehri Constantine 2 Constantine25000 Algeria Institute of Management Sciences Peshawar Peshawar Pakistan Institute of Software Systems Engineering Johannes Kepler University Linz4040 Austria Department of IT and Computer Science Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology Mang Khanpur Road Haripur22620 Pakistan

ISBN: (纸本)9789811993305

By the beginning of 2020, the world woke up to a global pandemic that changed people’s everyday lives and restrained their physical contact. During those times Social Media Platforms (SMPs) were almost the only mean of individual-to-individual and government-to-individuals communications. Therefore, people’s opinions were more expressed on SM. On the other hand, election candidates used SM to promote themselves and engage with voters. In this study, we investigate how COVID-19 affected voters’ opinions through the months of the US presidential campaign and eventually predict the 2020 US Presidential Election results using Twitter’s data. Mainly two types of experiments were conducted and compared;(i) transformer-based, and (ii) rule-based sentiment analysis (SA). In addition, vote shares for the presidential candidates using both approaches were predicted. The results show that the rule-based approach nearly predicts the right winner, Joe Biden with MAE 2.1, outperforming the predicted results from CNBC, Economist/YouGov, and transformer-based (BERTweet) approach, except for RCP (MAE 1.55). © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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Stunting Classification in Toddlers: Implementation and Evaluation of the Decision Tree Algorithm

Stunting Classification in Toddlers: Implementation and Eval...

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2024 International Conference on Information Technology and Computing, ICITCOM 2024

作者： Alita, Debby Ahmad, Imam Jafar Rumandan, Rhaishudin Erkamim, Moh Widyasmoro Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Institut Agama Islam Negeri Ambon Islamic Education Management Study Program Ambon Indonesia Universitas Tunas Pembangunan Smart City Information Systems Study Program Surakarta Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350379839

Stunting in toddlers is a chronic nutritional issue that affects the physical and cognitive development of children, with serious long-term consequences such as reduced cognitive function and an increased risk of chronic diseases in adulthood. Therefore, early identification and prevention efforts for stunting are crucial. Classifying toddlers into categories of at-risk for stunting or not is essential to provide timely and appropriate interventions. This study employs data mining techniques using the decision tree algorithm to expedite the stunting detection process and improve the accuracy of nutritional status classification in children. The results indicate that the constructed decision tree model can classify children's nutritional status with an accuracy of 83.26%. The decision tree achieves high accuracy in classifying stunting in toddlers due to its ability to handle complex data and identify significant patterns within the data. © 2024 IEEE.

关键词： Classification Data Mining Decision Tree Stunting

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Using Millimeter-Wave Wireless Networks for Opportunistic Wiretapping and Jamming 2

Using Millimeter-Wave Wireless Networks for Opportunistic Wi...

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2nd IEEE Global Conference on Communications and Information technologies, GCCIT 2024

作者： Jayasree, S. Asha, S. Vats, Satvik Wasatkar, N.N. Yuvaraj, K. Taneja, Madhur Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India School of Management - UG Management Karnataka Bangalore India Graphic Era Hill University Uttarakhand Dehradun248002 India Graphic Era Deemed to be University Uttarakhand Dehradun248002 India Vishwakarma Institute of Technology Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India

ISBN: (纸本)9798350388916

This study presents a novel model for opportunistic wiretapping with jamming (OWJ) attacks in millimeter-wave (mmWave) wireless networks, despite the fact that mmWave communication is resistant to traditional wiretapping attacks owing to its narrow transmission range and directivity. By taking advantage of the opportunity costs associated with wiretapping and jamming, an eavesdropper may use OWJ to launch a more dangerous assault. Additionally, we provide three OWJ assault realizations, with the distance-, path-, and received-power-related cost models serving as the primary determinants. First, we provide new approximation methods to describe the uneven distributions of wiretappers, jammers, and interferers under three OWJ conclusions. This will help us understand how the new assault affects the security of mmWave networks. We illustrate the network's security effectiveness under OWJ by deriving analytical formulas for the secrecy capacity of transmission using the findings of the node distributions. Last but not least, we provide comprehensive numerical findings to show how OWJ works and how this novel attack might worsen network security performance compared to pure wiretapping or jammer attacks. © 2024 IEEE.

关键词： Jamming

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Efficient Task Scheduling in Cloud Environment Based On Dynamic Priority and Optimized Technique

Efficient Task Scheduling in Cloud Environment Based On Dyna...

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2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Karthik, G.M. Gupta, Ankur Rajeshgupta, Sh. Jha, Amaresh Sivasangari, A. Mishra, B.P. Vellore Institute of Technology School of Computer Science and Engineering Vellore India RIMT University Department of Cse Godindgarh Mandi India Sanskriti University Department of Management Uttar Pradesh Mathura India University of Petroleum and Energy Studies School of Modern Media India Ut Sathyabama Institute of Science and Technology India Electronics Jss Academy of Technical Education Noida India

ISBN: (纸本)9798350322309

Cloud computing emerging filed process large task to handle the resources. From an application perspective, the study of task scheduling mechanisms for data transfer in large cloud computing environments is performed *** scheduling leads to traffic load, loss of energy and hardware controls failure. In addition, resident's devices are not considered to reduce power consumption delay. So, the Internet of things (IoT) rules the current trends of the Internet. The huge number of things (objects), which are associated with the Internet, produces a large amount of information that needs a ton of exertion and tasks preparation to make it valuable. To resolve this problem, we propose a dynamic multi-level task scheduling (DMLTS) based in cascade shrink priority (CSP) to allocate task to optimize the scheduling. With intent a TacticalLoad Balancer (TLB) and The Preemptive Flow Manager (PFM) is responsible for the application of load balancing strategy based on the mixed load balancing algorithm improves the task allocation better to balance load to improve the response time. Experimental results have been demonstrated with respect to better load balancing, lower power rate, and time consumption rate in both phase and random uniform propagation. Simulated results performance of this process can reduce data processing time and achieve load neutralization. © 2023 IEEE.

关键词： Cloud computing

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Identification and Characterization of Spammers from Lists of Recipients 2

Identification and Characterization of Spammers from Lists o...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Shinde, Sharmila Chitre, Vidya Patil, Seema Jitendra Meganathan, R. Kaliappan, Seeniappan Dhyani, Bijesh Jayawantrao Sawant College of Engineering Department of Computer Engineering Maharashtra Pune411038 India Vidyalankar Institute of Technology Department of Information Technology Maharashtra Mumbai400037 India Dr. Vishwanath Karad Mit World Peace University School of Computer Engineering and Technology Maharashtra Pune411038 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522302 India Velammal Institute of Technology Department of Mechanical Engineering Tamil Nadu Chennai601204 India Graphic Era Deemed to Be University Department of Management Studies Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350315905

For millions of users and their friends, online social networks (OSNs) are popular platforms for communication and cooperation. Regrettably, they may be efficient instruments for running spam campaigns and dispersing malware when in the wrong hands. Social spam is more effective than traditional email because users are logically more inclined to reply to messages from friends on Facebook than from complete strangers. In fact, evidence already in existence indicates that hostile actors are seeking to steal OSN account credentials in order to fund these "high-return"spam campaigns. All the more definitively, we see spam crusades that are coordinated and begun on KETTO, a sizable publicly supporting stage situated in India, and we follow the group laborers to their spamming exercises on Quora, the country's greatest local area based Q & A (QA) stage. We can recognize the total biological system that upholds publicly supported spam attacks by associating the spam crusades, laborers, spammer accounts, and spamming ways of behaving. We give a careful and scientific assessment of the biological system from a few points, including the size and degree of spam assaults, Sybil records and spammers' conniving strategies, work costs and monetary motivations, quality looks at conveyed by spam crusades, and so forth. © 2023 IEEE.

关键词： Biological systems

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