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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Gafsi, Saddam Dos Santos, Estevao Marques Kravchenko, Ivan Ryckman, Judson D. Holcombe Department of Electrical and Computer Engineering Clemson University ClemsonSC29634 United States Center for Nanophase Materials Science Oak Ridge National Laboratory Oak RidgeTN37831 United States

We introduce the design, fabrication, and experimental investigation of subwavelength Fano resonant porous silicon metasurfaces functioning on the principle of guided mode resonance. These metasurfaces exhibit promise... 详细信息

关键词： Porous materials

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Data Mining Techniques In Bioinformatics Enhanced by HPC and AI Convergence 13

Data Mining Techniques In Bioinformatics Enhanced by HPC and...

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13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024

作者： Kannagi, A. Patil, Shashikant Jain, Sandeep Kumar Department of Computer Science and Information Technology Bangalore India Atlas SkillTech University Department of UGDX Maharashtra Mumbai India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350305463

High-Performance Computing (HPC) and Artificial Intelligence (AI) have come together to usher in a new age of data mining in the field of bioinformatics. Using high-performance computing (HPC) and artificial intelligence (AI), this research presents a suggested strategy for improving data mining techniques and then evaluates it alongside six more conventional approaches. Discovering latent patterns in high-dimensional biological data is the goal of the proposed technique, which combines Principal Component Analysis (PCA), Convolutional Neural Networks (CNN), and Random Forest (RF). The suggested technique consistently outperforms the state-of-the-art methods in our comparisons, including in terms of accuracy, precision, recall, and F1 score. These performance criteria are essential for effective data mining in bioinformatics, and the system's shown equilibrium between them is rather impressive. The suggested strategy also drastically decreases execution time, which is a crucial aspect in effectively managing large-scale biological information. Our findings highlight the need for AI-driven data mining methods in the field of bioinformatics. The application of PCA offers dimensionality reduction, assisting in feature selection and boosting model performance. When it comes to classifying and ranking the value of features, RF provides ensemble learning capabilities, whereas CNNs excel at extracting complicated patterns from pictures and sequences. The suggested technique is holistic in nature, drawing on the advantages of several algorithms to improve data mining and provide a complete service to the field of biological research. Our results show that the suggested approach has considerable potential to further bioinformatics studies and applications. It helps scientists speed up drug development, improve the accuracy of diagnostics, and unearth new biological insights. In addition, the faster execution time suggests better use of computer resources, which is useful for

关键词： Genome

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A Multi-Sequence Prophet Inequality Under Observation Constraints

A Multi-Sequence Prophet Inequality Under Observation Constr...

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IEEE International Symposium on Information Theory

作者： Aristomenis Tsopelakos Olgica Milenkovic Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois at Urbana-Champaign

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In our problem, we are given access to a number of sequences of nonnegative i.i.d. random variables, whose realizations are observed sequentially. All sequences are of the same finite length. The goal is to pick one element from each sequence in order to maximize a reward equal to the expected value of the sum of the selections from all sequences. The decision on which element to pick is irrevocable, i.e., rejected observations cannot be revisited. Furthermore, the procedure terminates upon having a single selection from each sequence. Our observation constraint is that we cannot observe the current realization of all sequences at each time instant. Instead, we can observe only a smaller, yet arbitrary, subset of them. Thus, together with a stopping rule that determines whether we choose or reject the sample, the solution requires a sampling rule that determines which sequence to observe at each instant. The problem can be solved via dynamic programming, but with an exponential complexity in the length of the sequences. In order to make the solution computationally tractable, we introduce a decoupling approach and determine each stopping time using either a single-sequence dynamic programming, or a Prophet Inequality inspired threshold method, with polynomial complexity in the length of the sequences. We prove that the decoupling approach guarantees at least 0.745 of the optimal expected reward of the joint problem. In addition, we describe how to efficiently compute the optimal number of samples for each sequence, and its' dependence on the variances.

关键词： Polynomials Finite element analysis Dynamic programming Complexity theory Random variables Information theory

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Modified TRFI Channel Estimation Scheme in OFDM-IM for 802.11p 23

Modified TRFI Channel Estimation Scheme in OFDM-IM for 802.1...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Zhang, Si-Yu Dong, Qing-Shang Zheng, Hui Zhang, Yue-Xia Shahrrava, Behnam School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China University of Windsor Department of Electrical and Computer Engineering ON Canada

ISBN: (纸本)9798350325959

IEEE 802.11p is developed to support cooperative intelligent transport systems. In such systems, channel estimation is a challenging problem due to the channel's double dispersive nature. In this paper, a modified time domain reliable test frequency domain interpolation (M-TRFI) scheme for 802.11p orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems is proposed. Unlike OFDM, OFDM-IM can achieve better performance in vehicular communication environments. However, due to the in-active subcarriers, channel estimation for OFDM-IM is more difficult than OFDM. Inspired by the OFDM TRFI and the structure of OFDM-IM, the proposed M-TRFI utilizes preambles and least square (LS) methods to fill in the missing channel information on in-active subcarriers, reducing the serious performance degradation caused by the conventional TRFI used in OFDM-IM. Simulation results show that the proposed M-TRFI achieves a similar estimation performance as that of the OFDM TRFI. Moreover, the proposed M-TRFI significantly outperforms the existing channel estimation performance designed for OFDM-IM systems. © 2023 IEEE.

关键词： IEEE 802.11p standard index modulation (IM) least square (LS) Orthogonal frequency division multiplexing (OFDM) time domain reliable test frequency domain interpolation (TRFI) vehicular channels

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IoT for Sustainable Hospitality: A Systematic Review of Opportunities and Challenges for the Hospitality Industry Revolution 19

IoT for Sustainable Hospitality: A Systematic Review of Oppo...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Poullas, Marios S. Kakoulli, Elena Neapolis University Pafos Intelligent Systems Laboratory Department of Computer Science Pafos Cyprus Cell and Developmental Biology University College London London United Kingdom Cyprus University of Technology Electrical Engineering and Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798350346497

Technology has influenced the hospitality industry, and the Internet of Things (IoT) has become a focus for sustainability, revenue growth, and problem-solving. This systematic review examined the opportunities and challenges of implementing IoT technology for a sustainable hospitality. Through a thorough analysis of 28 studies, we found that IoT technology has great potential to address sustainability issues in the hospitality industry. However, there are still significant challenges that need to be addressed for the successful implementation of IoT technology in the hospitality industry. Overall, this study highlights the potential of IoT technology to revolutionize the hospitality industry and make it more sustainable. Further research is needed to address the challenges of IoT implementation in the hospitality industry and to evaluate the effectiveness of IoT technology in achieving sustainability goals. © 2023 IEEE.

关键词： Energy efficiency

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Solar and Wind Energy-Based Charging Station Designing for EV with Hybrid Storage Systems Having Power Flow Optimization Using F_MS_GA Algorithm

Solar and Wind Energy-Based Charging Station Designing for E...

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International Conference on Computational Intelligence and Smart Technologies in electrical engineering, CISTEE 2023

作者： Tiwari, Prakash Narayan Tiwari, Kaushal Prasad Dixit, Anshu Bohre, Aashish Kumar Gupta, Sanjeev Kumar Pal, Sitaram Department of Electrical and Electronics Engineering Rabindranath Tagore University Bhopal India Department of Computer Science and Engineering Rabindranath Tagore University Bhopal India Department of Electrical and Electronics Engineering NIT Durgapur West Bengal Durgapur India Department of Electronics Communication Engineering Rabindranath Tagore University Bhopal India

ISBN: (纸本)9789819799152

Renewable energies like solar, wind, etc. have gained a lot of importance in the recent years as they are clean sources that can be brought to use to supply power to charging stations (CS). The growing demand for electric vehicles (EVs) has led to an increasing need for efficient and sustainable charging infrastructure. To optimize the utilization of solar and wind resources, advanced energy management systems are employed in this work. The solar energy system of 25 KW has been integrated with the charging station and its power output and flow across the system has been analyzed that achieves charging of EV clusters. The variable input conditions are studied and power flow management is achieved across the storage systems, grid, and EVs. Wind energy system is further integrated of 11 KW which is operated at its fuel efficiency and then at reduced efficiency to study the impact on the power flow. The control algorithm has been designed with fuzzy interfaced multistage genetic algorithm (F_MS_GA) to achieve efficient energy distribution across the various loading points. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Charging stations

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Inflate Agriculture Crop Yield Prophesy through Deep Neural Network Schemes

Inflate Agriculture Crop Yield Prophesy through Deep Neural ...

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2023 International Conference on Data science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Kumar, Thangiah Sathish Roy, Dharmendra Kumar Partheeban, Pachaivannan Ponnusamy, R. Hemamalini, Renganathan Rani Ettappan, M. Department of Computer Science and Engineering India Chennai Institute of Technology Department of Civil Engineering Chennai Kundrathur India Chennai Institute of Technology Department of Computer Science and Engineering Chennai Kundrathur India St. Peters Institute of Higher Education and Research Department of Electrical and Electronics Engineering Chennai Avadi India Chennai Institute of Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350348910

Recent advancements in DL (Deep Learning) have unlocked the potential for more accurate predictions in various fields, including agricultural crop yield forecasting. This paper presents the NeuroDendritic Networks (NDN) methodology, a biologically inspired approach that emulates the dynamic growth and retraction of dendrites in neurons. This novel method hinges on the NeuroDendritic Units (NDUs) and their ability to grow and prune dendritic branches adaptively based on data stimuli, ensuring optimal processing and information storage. As a result, NDN offers dynamic model adaptation, intrinsic regularization through dendritic retraction, and enhanced focus on pertinent data patterns. Preliminary tests have shown an expected improvement of up to 40% in prediction accuracy compared to traditional methods. This dynamic adaptation ensures the model remains attuned to the most influential factors affecting yield, leading to more informed and timely interventions. The versatility and adaptability of the NDN method not only redefine the standards in agricultural predictive modeling but also hint at its expansive potential across various domains, heralding a promising direction for future research. © 2023 IEEE.

关键词： Dynamic models

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Analysis of a Comparator for Low Delay, High Speed and Compact Area for Portable Device Application

Analysis of a Comparator for Low Delay, High Speed and Compa...

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2023 International Conference on Digital Applications, Transformation and Economy, ICDATE 2023

作者： Basak, Dona Miraz, Mahadi Hasan Jin, Hwang Ha Jibon, Ferdaus Anam Biswas, Satyendra Nath Sivakumar, Saaveethya Mahmud, Hasib Ahsanullah University of Science and Technology Eee Department Dhaka Bangladesh Curtin University Department of Management Digital Marketing Malaysia Sunway University Business Analytics Malaysia University of Information Technology & Sciences Computer Science Bangladesh Ahsanullah University of Science and Technology Computer Science Bangladesh Engineering Curtin University Department of Electrical & Computer Malaysia University of Barishal Department of Geology and Mining Bangladesh

ISBN: (纸本)9798350310689

This paper presents a low delay, high speed CMOS comparator in a lowest possible chip area for portable device application. The proposed comparator is designed using 90nm technology with a supply voltage of 0.8V and clock frequency of 6GHz. Delay, power consumption/conversion and offset voltage are analyzed. Transistor count is also reduced compared to several comparators mentioned in literature in order to make the chip area as compact as possible. Simulation is done using Spectre Circuit Simulator tool-Cadence. Some graphical analysis is made to characterize the proposed comparator behavior and also they are compared with other 90nm comparators for performance analysis. Power consumption is found to be 33.5 μw and delay is 54.32ps for 60% duty cycle of clock pulse. Standard deviation of offset voltage is 6.3mv from Monte Carlo method and the chip area is found to be (8.83∗8.61) m2. Also it has low parasitic effect and low noise than those conventional approaches. © 2023 IEEE.

关键词： Monte Carlo methods

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Research Challenges and Future Facet of Cellular Computing 2

Research Challenges and Future Facet of Cellular Computing

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Alnawayseh, Saif E. A. Khan, Tahir Abbas Farooq, Umer Zulfiqar, Sidra Khan, Shan Al-Kassem, Amer Hani Mutah Univesity Faculty of Engineering Electrical Engineering Department Jordan NCBA&E School of Computer Science Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan LGU Department of Computer Science Lahore Pakistan College of Business Management Sharjah United Arab Emirates

ISBN: (纸本)9798350335644

cellular computing is promising and exciting domain. As the field continues to evolve, several future facets are expected to emerge. One potential facet is the development of more sophisticated and efficient cellular-based computing systems that can perform complex calculations and data processing tasks. This could lead to the creation of new tools and technologies in various fields, including medicine, biotechnology, and environmental monitoring. Moreover, technology has changed the way of communication, sharing and exchanging data. Mobile computing has grown to be very vital as the number of cellular devices have elevated fairly in the preceding years. In this paper, we have mentioned cellular computing, aspects of cell computing, working of cell computing. Also, we have discussed that what challenges are most common in the development of cellular computing. In last we discussed merits, demerits, application, and its future. © 2023 IEEE.

关键词： Mobile computing

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Scale‐wise interaction fusion and knowledge distillation network for aerial scene recognition

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1178-1190页

作者： Hailong Ning Tao Lei Mengyuan An Hao Sun Zhanxuan Hu Asoke K.Nandi School of Computer Science and Technology Xi'an University of Posts and TelecommunicationsShaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXi'anChina Xi'an Key Laboratory of Big Data and Intelligent Computing Xi'anChina School of Electronic Information and Artificial Intelligence Shaanxi University of Science and TechnologyXi'anChina School of Computer Central China Normal UniversityWuhanChina Department of Electronic and Electrical Engineering Brunel University LondonLondonUK Xi'an Jiaotong University Xi'anChina

Aerial scene recognition(ASR)has attracted great attention due to its increasingly essential *** of the ASR methods adopt the multi‐scale architecture because both global and local features play great roles in ***,the existing multi‐scale methods neglect the effective interactions among different scales and various spatial locations when fusing global and local features,leading to a limited ability to deal with challenges of large‐scale variation and complex background in aerial scene *** addition,existing methods may suffer from poor generalisations due to millions of to‐belearnt parameters and inconsistent predictions between global and local *** tackle these problems,this study proposes a scale‐wise interaction fusion and knowledge distillation(SIF‐KD)network for learning robust and discriminative features with scaleinvariance and background‐independent *** main highlights of this study include two *** the one hand,a global‐local features collaborative learning scheme is devised for extracting scale‐invariance features so as to tackle the large‐scale variation problem in aerial scene ***,a plug‐and‐play multi‐scale context attention fusion module is proposed for collaboratively fusing the context information between global and local *** the other hand,a scale‐wise knowledge distillation scheme is proposed to produce more consistent predictions by distilling the predictive distribution between different scales during *** experimental results show the proposed SIF‐KD network achieves the best overall accuracy with 99.68%,98.74%and 95.47%on the UCM,AID and NWPU‐RESISC45 datasets,respectively,compared with state of the arts.

关键词： deep learning image analysis image classification information fusion

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