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A Hybrid Multi-Objective Optimization Algorithm for Scheduling Heterogeneous Workloads in Cloud 2nd

A Hybrid Multi-Objective Optimization Algorithm for Scheduli...

Emergent Converging Technologies and Biomedical Systems Select Proceedings of the 2nd International Conference, ETBS 2022

作者： Dar, Iqbal Gani Shrivastava, Vivek Department of Computer Science International Institute of Professional Studies DAVV Indore452001 India

ISBN: (纸本)9789819922703

Cloud computing provides a platform for hosting and providing services to users in an on-demand manner over the Internet. Numerous challenges are faced due to the dynamic nature of the cloud environment. One such key challenge involves the scheduling of tasks submitted by various users at the same time on virtual machines (VMs). Task scheduling involves the optimized resource allocation to various tasks while considering several performance metrics such as the turnaround time and the throughput. To improve these performance measures, a variety of single-criteria and multi-criteria decision-making (MCDM) methods have been suggested. In this study, we have proposed a hybrid algorithm BWM_ELECTRE (Best Worst Method EliminationEt Choice Translating REeality). The performance of this algorithm has been analyzed and evaluated in terms of the turnaround time and the throughput performance measures. The efficiency of BWM_ELECTRE has been compared with the best-known MCDM method BWM_TOPSIS (Best Worst Method Technique for Order Preference by Similarity to Ideal Solution). A dataset of 2400 cloudlets has been considered to compare the performance of these algorithms. Experiments have been carried out in an open-source simulation tool CloudSim 3.0.1. The results validate that BWM_ELECTRE outperforms the BWM_TOPSIS algorithm by 1.27%, and 2.08% in terms of the average turnaround time and the throughput, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing

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Robust Domain Generalization for Multi-modal Object Recognition 5

Robust Domain Generalization for Multi-modal Object Recognit...

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5th International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2024

作者： Qiao, Yuxin Li, Keqin Lin, Junhong Wei, Rong Jiang, Chufeng Luo, Yang Yang, Haoyu Northern Arizona University Department of Computer Information Technology FlagstaffAZ United States Ama University Department of Computer Science Quezon Philippines Massachusetts Institute of Technology Electrical Engineering & Computer Science Department CambridgeMA United States Peking University Academy for Advanced Interdisciplinary Studies Beijing China The University of Texas at Austin Department of Computer Science AustinTX United States University of Southern California Department of Computer Science Los AngelesCA United States Georgia Institute of Technology College of Computing AtlantaGA United States

ISBN: (纸本)9798350366174

In multi-label classification, machine learning encounters the challenge of domain generalization when handling tasks with distributions differing from the training data. Existing approaches primarily focus on vision object recognition and neglect the integration of natural language. Recent advancements in vision-language pre-training leverages supervision from extensive visual-language pairs. This allows learning across diverse domains and enhances recognition in multi-modal scenarios, showcasing superior transfer learning capabilities in methods like CLIPood. However, CLIPood has several limitations: differences in the utilized loss, loss of generality in evaluating only a single backbone, and neglect of class-aware visual *** address these, we propose this paper that infers the actual loss based on the implementation, broadens evaluations to larger vision-language backbones, and introduces Mixup-CLIPood with a novel mix-up loss for enhanced class-aware visual fusion. © 2024 IEEE.

关键词： Visual languages

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Room-temperature waveguide-integrated photodetector using bolometric effect for mid-infrared spectroscopy applications

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光：科学与应用（英文版） 2025年第5期14卷 1300-1311页

作者： Joonsup Shim Jinha Lim Inki Kim Jaeyong Jeong Bong Ho Kim Seong Kwang Kim Dae-Myeong Geum SangHyeon Kim School of Electrical Engineering Korea Advanced Institute of Science and Technology(KAIST)291 Daehak-RoYuseong-GuDaejeon 34141Republic of Korea Department of Electrical & Computer Engineering Inha University100Inha-roMichuhol-guIncheon 22212Republic of Korea

Waveguide-integrated mid-infrared(MIR)photodetectors are pivotal components for the development of molecular spectroscopy applications,leveraging mature photonic integrated circuit(PIC)*** various strategies,critical challenges still remain in achieving broadband photoresponse,cooling-free operation,and large-scale complementary-metal-oxide-semiconductor(CMOS)-compatible *** leap beyond these limitations,the bolometric effect-a thermal detection mechanism-is introduced into the waveguide *** importantly,we pursue a free-carrier absorption(FCA)process in germanium(Ge)to create an efficient light-absorbing medium,providing a pragmatic solution for full coverage of the MIR spectrum without incorporating exotic materials into ***,we present an uncooled waveguide-integrated photodetector based on a Ge-on-insulator(Ge-OI)PIC architecture,which exploits the bolometric effect combined with ***,our device exhibits a broadband responsivity of 28.35％/mW across 4030-4360 nm(and potentially beyond),challenging the state of the art,while achieving a noise-equivalent power of 4.03×10-7W/Hz0.5 at 4180 *** further demonstrate label-free sensing of gaseous carbon dioxide(CO2)using our integrated photodetector and sensing waveguide on a single *** approach to room-temperature waveguide-integrated MIR photodetection,harnessing bolometry with FCA in Ge,not only facilitates the realization of fully integrated lab-on-a-chip systems with wavelength flexibility but also provides a blueprint for MIR PICs with CMOS-foundry-compatibility.

关键词： applications temperature integrated room bolometric effect mid-infrared photodetector spectroscopy using

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A Review of Blockchain Technology in Smart Applications: Research Issues and Open Challenges

A Review of Blockchain Technology in Smart Applications: Res...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Samuel, B. Kasturi, K. VISTAS Vels Institute of Science Technology & Advanced Studies School of Computing Sciences Dept.of Computer Science Pallavaram Chennai India

ISBN: (纸本)9798350348217

The increasing urbanization of the worldwide people has a significant impact on societal attitudes, particularly life expectancy, as a consequence of a variety of macroeconomic, sociological, and environmental changes. The idea of a 'smart city' creates opportunities for addressing important urban problems. Smart cities strive to provide exceptional services to the populace, more efficiently use public funds, and advance general welfare. Technology tools are essential to the development of ubiquitous computing. Trustlessness, traceability, anonymity, democracy, automation, decentralization, and confidentiality are just a few advantages of blockchain *** development of IoT technology and the upgrading of intelligent devices are both facilitated by these cryptocurrency capabilities. In this post, we will provide a thorough assessment of published literature on decentralized blockchain systems in wide variety of applications. We start with talking about the core ideas behind distributed ledger technology before moving on to the various fields it has been used in, like the Internet of Things, agribusiness, financial, as well as other businesses. Finally, we examined several security issues facing the healthcare sector and thoroughly examined blockchain technology's trustworthiness. © 2023 IEEE.

关键词： Blockchain

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Comparative study of DNN Models for Skin Cancer Detection 4

Comparative study of DNN Models for Skin Cancer Detection

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4th International Conference on Smart Systems and Inventive Technology, ICSSIT 2022

作者： Kavitha, P. Jayalakshmi, V. Department of Computer Science Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Pallavaram Chennai India Department of Computer Applications Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Pallavaram Chennai India

ISBN: (纸本)9781665401180

Malignant melanoma, the most dangerous form of skin cancer, has become more common in recent years. The persistent global increase in this cancer, as well as the high medical costs and death rate, have made early detection of this malignancy a priority. Melanoma survival and cure are directly proportional to its thickness;if it can be found early, the survival rate will be enhanced. Despite the fact that significant progress has been achieved in the identification of skin malignancies, there are still significant issues. In comparison to the naked eye, computer-based detection systems can enhance the diagnosis rate of melanoma by 5-30 percent. Because visual perception frequently contains flaws, the need for a second viewpoint with greater precision and consistency is underlined. On the other side, it minimizes the tasks and responsibilities that physicians are responsible for. Many studies have been conducted in the area of automated melanoma detection. The potential benefits of such investigations are enormous and unquantifiable. Furthermore, the challenges are numerous, and fresh contributions in this field are greatly valued. However, it is widely known that more reliable and consistent detection methods necessitate a higher level of accuracy. The goal of this paper is to provide a skin cancer diagnosis system that can automatically identify lesions as malignant or benign. Preprocessing, segmentation, feature extraction and selection, and classification are some of the methods used in an automated skin cancer diagnosis. © 2022 IEEE

关键词： Deep neural networks

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A Simulation Study of n-ZnO/Perovskite/p-Cu2SnS3 Based Self-Powered Photodetector: Design and optimisation

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Materials Research Innovations 2023年第7期27卷 503-510页

作者： Yadav, Sanjeev Mani Pandey, Amritanshu Department of Electronics and Computer Science National Institute of Advanced Manufacturing Technology Jharkhand Ranchi India Centre for Research in Microelectronics Department of Electronics Engineering IIT-BHU Varanasi India

Perovskite has been widely used in the field of optoelectronics owing to its superb optoelectronic properties. The simplest fabrication along with low-temperature handling of perovskite-based planner structures (p-i-n or n-i-p) has drawn their potential impact in organic–inorganic lead halide optoelectronic devices. The poor conductivity, stability, and high processing cost of absorber materials hinder the optical performance of the device. The sandwiching of the perovskite as absorber materials between two inorganic materials working as electron transport layer (ETL) and hole transport layer (HTL) may be a possible solution. An active absorber perovskite (CH3NH3PbI3) assisted by two n-ZnO and p-CTS materials working as an ETL and HTL, respectively, has been used to maximize the overall performance of the proposed device. The resultant optimized device shows the maximum responsivity of ∼0.35 (A/W) for a broad visible spectrum (300–900 nm), while the EQE (%) reported in the range of 25–80%. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Photodetectors

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Connective Reconstruction-Based Novelty Detection 31

Connective Reconstruction-Based Novelty Detection

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31st International Conference on Electrical Engineering, ICEE 2023

作者： Hashemi, Seyyed Morteza Aliniya, Parvaneh Razzaghi, Parvin Institute for Advanced Studies in Basic Sciences Dept. Computer Science and Information Technology Zanjan Iran University of Nevada Dept. Computer Science RenoNV United States

ISBN: (纸本)9798350312560

Detection of out-of-distribution samples is one of the critical tasks for real-world applications of computer vision. The advancement of deep learning has enabled us to analyze real-world data which contain unexplained samples, accentuating the need to detect out-of-distribution instances more than before. GAN-based approaches have been widely used to address this problem due to their ability to perform distribution fitting;however, they are accompanied by training instability and mode collapse. We propose a simple yet efficient reconstruction-based method that avoids adding complexities to compensate for the limitations of GAN models while outperforming them. Unlike previous reconstruction-based works that only utilize reconstruction error or generated samples, our proposed method simultaneously incorporates both of them in the detection task. Our model, which we call 'Connective Novelty Detection' has two subnetworks, an autoencoder, and a binary classifier. The autoencoder learns the representation of the positive class by reconstructing them. Then, the model creates negative and connected positive examples using real and generated samples. Negative instances are generated by manipulating the real data, so their distribution is close to the positive class to achieve a more accurate boundary for the classifier. To boost the robustness of the detection of reconstruction error, connected positive samples are created by combining the real and generated samples. Finally, the binary classifier is trained using connected positive and negative examples. We demonstrate a considerable improvement in novelty detection over state-of-the-art methods on MNIST and Caltech-256 datasets. © 2023 IEEE.

关键词： computer vision

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Unmanned Aerial Vehicles and Low-Flying Drones: A Review of Classification 2

Unmanned Aerial Vehicles and Low-Flying Drones: A Review of ...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Pagrut, Shrijeet Jawandhiya, Pradip Shri Sant Gajanan Maharaj College of Engineering Department of Computer Science and Engineering Maharashtra Shegaon India Pankaj Laddhad Institute of Technology and Management Studies Department of Computer Science and Engineering Maharashtra Buldhana India

ISBN: (纸本)9798331528713

Nowadays Research and Development of Novel and Efficient drones becomes the core part of strategic practices of every nation. There is a growing need of using a variety of Unmanned Aerial Vehicles with significant capabilities in Civilian, Military and Commercial Applications. UAVs flight patterns such as Vertical Takeoff Landing and Horizontal Takeoff Landing, its maximum altitude capacity, range are discussed. Designing of Low Flying drones are classified into Small, Micro and Nano-Pico-SmartDust(NPSD) categories. Use and Impact of different materials like Titanium alloy in design is provided. Additionally, current activities in the market related to small drones and future research direction in the field of utility and applications drones are discussed. © 2024 IEEE.

关键词： Drones

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Nanoimprint lithography-assisted block copolymer self-assembly for hyperfine fabrication of magnetic patterns based on L10-FePt nanoparticles

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science China Chemistry 2025年第5期68卷 2027-2034页

作者： Jie Zhang Yi Chen Guijun Li Zelin Sun Zhengong Meng Wai-Yeung Wong Department of Applied Biology and Chemical Technology and Research Institute for Smart Energy The Hong Kong Polytechnic University The Hong Kong Polytechnic University Shenzhen Research Institute Division of Integrative Systems and Design and Department of Electronic and Computer EngineeringThe Hong Kong University of Science and Technology School of Flexible Electronics (Future Technology) and Institute of Advanced Materials (IAM) Nanjing Tech University

L10-FePt-type bit-patterned media has provided a promising alternative for ultrahigh-density magnetic recording systems in the current digital era, but rapid fabrication of magnetic patterns with hyperfine bit islands is still challenging, especially with the target for miniaturization and scalable production simultaneously. Herein, Fe,Pt-containing block copolymers were utilized as single-source precursors for solution-processable patterning and subsequent generation of the demanding magnetic FePt dots by in situ pyrolysis. High-throughput nanoimprint lithography was initially employed to fabricate the predefined bit cells precisely,and then the intrinsic self-assembly of phase-separated block copolymers further drove the formation of accurate bit *** from the synergistic effect of top-down lithographic approach and bottom-up self-assembly, the customizable patterns could be achieved for large-scale mass production in targeted areas, but high-density isolated dots could also be accurately aligned along the patterned features after subsequent self-assembly. This reliable strategy would provide a good avenue to precisely construct ultrahigh-density magnetic data storage devices.

关键词： organometallic precursor magnetic nanoparticles block copolymer self-assembly nanoimprint lithography

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Predictive Analysis in Academic: An Insight to Challenges and Techniques 6

Predictive Analysis in Academic: An Insight to Challenges an...

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6th International Conference on Computing Methodologies and Communication, ICCMC 2022

作者： Bhagya, A. Sripriya, P. Vels Institute of Science Technology Advanced Studies Department of Computer Applications Tamilnadu Chennai India

ISBN: (纸本)9781665410281

The educational sector generates a large amount of data on a daily basis because of the rapid growth of data generation an educational system is facing difficulties in predicting students' performance which is an essential for education institutions and existing methods or not satisfactory for predicting students' performance because of large data sets. As educational institutions looking for an efficient and advanced technology which predicts student's performance, big data and predictive learning analysis is an emerging trend in educational system to improve students' academic learning and growth of the institution in today's competitive world. This paper focus on a literature review on an associated benefits and challenges by implementing predictive learning analytics and brief information about different predictive analytics techniques which can be implemented in education system to gain meaningful insights into available data and to assist the education system to improve their growth by monitoring the students closely based on the predicted data. © 2022 IEEE.

关键词： Predictive analytics

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