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Generalized hybrid LiFi-WiFi UniPHY learning framework towards intelligent UAV-based indoor networks

International Journal of Intelligent Networks 2024年第1期5卷 255-266页

作者： Ahmad, Rizwana Anwar, Dil Nashin Bany Salameh, Haythem Elgala, Hany Ayyash, Moussa Almajali, Sufyan El-Khazali, Reyad Electronic and Electrical Engineering Department University of Cambridge United Kingdom Electrical and Computer Engineering Department University at Albany-State University of New York United States Artificial Intelligence Research Center Al Ain University Al Ain United Arab Emirates Telecommunications Engineering Department Yarmouk University Irbid Jordan Department of Computing Information and Technology Chicago State University ChicagoIL United States Department of Computer Science Princess Sumaya University for Technology Amman Jordan Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi United Arab Emirates

Advancements in unmanned aerial vehicle (UAV) technology, along with indoor hybrid LiFi-WiFi networks (HLWN), promise the development of cost-effective, energy-efficient, adaptable, reliable, rapid, and on-demand HLWN-capable indoor flying networks (IFNs). To achieve this, a unified physical layer (UniPHY) capable of simultaneous control communication, data transfer, and sensing is crucial. However, traditional block-based decoders, designed independently for LiFi and WiFi, perform poorly in complex and hybrid LiFi-WiFi-enabled UniPHY systems. In this study, we propose an end-to-end learning framework based on convolutional neural networks (CNNs) for UniPHY, which can be trained to serve hybrid LiFi-WiFi transmissions to improve error performance and simplify UAV hardware. In this work, the performance of the proposed framework is assessed and compared with that of the conventional independent block-based communication system. Furthermore, a comprehensive summary of optimal hyper-parameters for efficient training of our learning framework has been provided. It is shown that, with optimal hyper-parameters, the proposed CNN-based framework outperforms the conventional block-based approach by providing a signal-to-noise ratio gain of approximately 7 dB for the LiFi channel and 23 dB for the WiFi channel. In addition, we evaluate the complexity and training convergence for loss and accuracy. © 2024 The Authors

关键词： Data transfer

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A switchable high-sensitivity strain sensor based on piezotronic resonant tunneling junctions

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Nano research 2024年第11期17卷 10242-10255页

作者： Gongwei Hu Li Zeng Fobao Huang Shuaiwei Fan Qiao Chen Wei Huang Hubei Engineering Research Center of Weak Magnetic-field Detection Department of Physics China Three Gorges University Yichang 443002 China School of Microelectronics Northwestern Polytechnical University Xi’an 710072 China Institute of Flexible Electronics Northwestern Polytechnical University Xi’an 710072 China School of Computational Science and Electronics Hunan Institute of Engineering Xiangtan 411104 China

Developing emerging technologies in Internet of Things and artificial intelligence requires high-speed, low-power, high-sensitivity, and switchable-functionality strain sensors capable of sensing subtle mechanical stimuli in complex ambience. Resonant tunneling diodes (RTDs) are the good candidate for such sensing applications due to the ultrafast transport process, lower tunneling current, and negative differential resistance. However, notably enhancing sensing sensitivity remains one of the greatest challenges for RTD-related strain sensors. Here, we use piezotronic effect to improve sensing performance of strain sensors in double-barrier ZnO nanowire RTDs. This strain sensor not only possesses an ultrahigh gauge factor (GF) 390 GPa^(−1), two orders of magnitude higher than these reported RTD-based strain sensors, but also can switch the sensitivity with a GF ratio of 160 by adjusting bias voltage in a small range of 0.2 V. By employing Landauer–Büttiker quantum transport theory, we uncover two primary factors governing piezotronic modulation of resonant tunneling transport, i.e., the strain-mediated polarization field for manipulation of quantized subband levels, and the interfacial polarization charges for adjustment of space charge region. These two mechanisms enable strain to induce the negative differential resistance, amplify the peak-valley current ratio, and diminish the resonant bias voltage. These performances can be engineered by the regulation of bias voltage, temperature, and device architectures. Moreover, a strain sensor capable of electrically switching sensing performance within sensitive and insensitive regimes is proposed. This study not only offers a deep insight into piezotronic modulation of resonant tunneling physics, but also advances the RTD towards highly sensitive and multifunctional sensor applications.

关键词： piezotronic effect resonant tunneling diode negative differential resistance highly sensitive strain sensor ZnO nanowire ratio of gauge factor

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A Systematic Analysis of Machine Learning Algorithms for Cloud DDoS Attack Detection 10

A Systematic Analysis of Machine Learning Algorithms for Clo...

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10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Mehta, Ankush Badotra, Sumit Singh, Gurpreet Verma, Amit Lovely Professional University Department of Computer Science and Engineering Punjab Phagwara India Bennett University Computer Science and Engineering Greater Noida India Chandigarh University University Center for Research and Development Department of Computer Science and Engineering Gharuan Mohali India

ISBN: (纸本)9798350382471

Computing in the cloud is a relatively recent innovation that involves sending data processing jobs to third-party service providers through the Internet. Cloud computing comes with several benefits, such as reduced overhead costs, expandable capabilities, and changeable pricing. However, there are several concerns about the cloud's level of security. DDoS assaults, also known as distributed denial-of-service attacks, pose a danger to cloud infrastructure. In order to defend against DDoS assaults in the cloud, a variety of different machine learning algorithms have been developed. However, there is not yet a general agreement on employing machine learning to protect against DDoS assaults in the cloud. In addition, as the number of relevant literature increases, it becomes more challenging to monitor all of it, much alone characterize the current state of the art or identify emerging gaps in study. This project aims to conduct a literature review on DDoS machine learning approaches for the cloud. To that aim, the purpose of this study is to undertake a methodical examination of the existing research that discusses cloud machine learning algorithms for DDoS in an attempt to synthesize the evidence associated with this topic. © 2023 IEEE.

关键词： DDoS DDoS attack prediction Intrusion Detection system Machine learning

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High-Speed Visible Light Communication Using Phenothiazine/Dimesitylborane Derivatives as Color Conversion Materials in Semipolar Micro-LED-Based White-Light Systems

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ACS Photonics 2024年第2期11卷 489-497页

作者： Sadhu, Annada Sankar Chen, Li-Yin Pai, Yi-Hua Hsieh, Chung-An Lin, Hao-Wu Chow, Chi-Wai Kuo, Hao-Chung Department of Photonics Institute of Electro-Optical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan

Visible light communication (VLC) has emerged as a cutting-edge high-speed communication technology, poised to meet the surging capacity demands of 6G networks. Micro-light-emitting diodes (μLEDs) are considered as the light sources for achieving high-speed VLC, distinguished by their remarkable modulation bandwidths. However, achieving broadband white light emission hinges on the utilization of color-conversion materials with wide emission spectra. The transmission speed of the white-light system is inherently constrained by the characteristics of these color-conversion materials. In this work, we demonstrate CC-MP7 and CC-MP8, two derivatives of phenothiazine/dimesitylborane, as color conversion materials in a semipolar (20-21) micro-LED-based white-light system for high-speed VLC. The color conversion layers possess wide emission spectra, enabling them to achieve excellent color rendering performance when combined with blue micro-LEDs. CCMP7 and CC-MP8 demonstrate rapid photoluminescence decay characteristics, thereby enhancing the modulation bandwidth of the color-conversion layer in the white-light system. The resulting bandwidths achieved by CC-MP7 and CC-MP8 are 210 and 240 MHz, respectively, which represents an approximately 45-fold increase compared to ordinary phosphors. By combining semipolar (20-21) micro-LEDs with CC-MP7 and CC-MP8, the resulting white-light systems exhibit correlated color temperatures of 6860 and 7500 K, CIE coordinates of (0.3009, 0.3577) and (0.2958, 0.3129), and color-rendering indexes of 80 and 85, respectively. Furthermore, both systems offer high bandwidths of 1063 and 1084 MHz with the data rates of 1.72 Gbps and 1.74 Gbps using non-return-to-zero on-off keying (NRZ-OOK) format, respectively, indicating the significant potential of CC-MP7 and CC-MP8 for practical applications in VLC. © 2024 The Authors.

关键词： Bandwidth

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A low-fabrication-temperature, high-gain chip-scale waveguide amplifier

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science China(Information sciences) 2022年第6期65卷 247-255页

作者： Bo WANG Peiqi ZHOU Xingjun WANG Yandong HE State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer Science Peking University Institute of Microelectronics School of Electronics Engineering and Computer Science Peking University Frontier Science Center for Nano-optoelectronics Peking University Peking University Yangtze Delta Institute of Optoelectronics Peng Cheng Laboratory

The increasing prevalence of integrated on-chip optoelectronic devices has identified serious issues regarding inter-device transmission and coupling losses, highlighting an urgent need for on-chip waveguide amplifiers to compensate for these losses. Compared with other Er-based optical materials, erbium silicate is ideally suited to high-efficiency on-chip amplifiers and lasers because of its extremely high Er3+concentration(1022cm-3). Nevertheless, erbium silicate must be annealed above 1000℃ to crystallize and activate the Er3+, which damages other on-chip optoelectronic components and is not conducive to device ***, we report a low-fabrication-temperature, high-luminescence-efficiency gain material by adding Bi2O3to an erbium-ytterbium silicate mixed film. Our experiments demonstrate that the proposed film crystallizes at 600℃ while the activation of Er3+is also achieved, which is the lowest activation temperature of on-chip waveguide amplifier to our knowledge. This material forms the basis for a new chip-scale waveguide amplifier design, with a theoretical multi-energy-level model of Bi-Er-Yb in the mixed thin films used to analyze its signal enhancement properties. We achieve a peak on-chip gain of 23 dB in a 3.3-mm-long waveguide under the pump and signal powers of 300 mW and 1 μW, respectively. These results highlight the potential of the proposed material for realizing on-chip amplifiers and lasers for large-scale nanophotonic integrated circuits.

关键词： photonic circuit integration low fabrication temperature high gain rare earth material waveguide amplifier

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Improve Harris Hawkes optimizer algorithm via Laplace crossover

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Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2057-2072页

作者： Nasab, Seyed Taha Mousavi Abualigah, Laith Department of Applied Mathematics Iran University of Science and Technology Tehran Iran Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

Nowadays, the speed of solving optimization problems by increasing various issues and the number of variables is critical. The Harris Hawk optimization method is a brand-new, intelligent system that resolves optimization issues by mathematically simulating the natural behavior of hawks. In this study, the Harris Hawks optimization method and the Laplace crossover operator are merged, and a new enhanced Harris Hawks algorithm (LX-HHO) based on the Laplace optimization algorithm is suggested. The purpose of improving this algorithm is to increase the convergence speed while maintaining good accuracy in achieving the optimal solution. The results of the proposed method on the test functions demonstrate that the algorithm has achieved faster convergence than the original version of the Harris Hawks algorithm and other meta-heuristic algorithms. This is due to the algorithm's accuracy in obtaining the best answer in these functions and to a reduction in the evaluation of the optimization function. Also, comparing and evaluating the proposed algorithm with other algorithms by Friedman and MAE test shows the superiority of the LX-HHO algorithm. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Optimization

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NCU-IISR: Enhancing Biomedical Question Answering with GPT-4 and Retrieval Augmented Generation in BioASQ 12b Phase B 25

NCU-IISR: Enhancing Biomedical Question Answering with GPT-4...

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25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Chih, Bing-Chen Han, Jen-Chieh Tsai, Richard Tzong-Han Department of Computer Science and Information Engineering National Central University Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taiwan

In this paper, we introduce our system and submissions in BioASQ 12b phase b [1], highlighting a significant improvement with GPT-4 and the integration of Retrieval Augmented Generation (RAG) techniques. We describe our prompt engineering methods and the experimental procedures followed. Because GPT-4 has proven effectiveness in generating answers and its ability in the biological domain, our system utilizes GPT-4 to address biomedical question-answering (QA). Leveraging OpenAI's ChatCompletions API, we refined previous prompt engineering approaches [2] for BioASQ 11b phase b. This year, the addition of RAG techniques significantly improved the information retrieval capabilities of our system. Consequently, our latest submission employed what we experimented to be the most effective prompts and techniques, achieving excellent performance across multiple metrics in the fourth batch. © 2024 Copyright for this paper by its authors.

关键词： Question answering

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Solving Fuel-Based Unit Commitment Problem Using Improved Binary Bald Eagle Search

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Journal of Bionic engineering 2024年第6期21卷 3098-3122页

作者： Sharaz Ali Mohammed Azmi Al-Betar Mohamed Nasor Mohammed A.Awadallah Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityP.O.Box 346AjmanUnited Arab Emirates Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial Intelligence Research Center(AIRC) Ajman UniversityP.O.Box 346AjmanUnited Arab Emirates

The Unit Commitment Problem(UCP)corresponds to the planning of power generation *** objective of the fuel-based unit commitment problem is to determine the optimal schedule of power generators needed to meet the power demand,which also minimizes the total operating cost while adhering to different constraints such as power generation limits,unit startup,and shutdown *** this paper,four different binary variants of the Bald Eagle Search(BES)algorithm,were introduced,which used two variants using S-shape,U-shape,and V-shape transfer *** addition,the best-performing variant(using an S-shape transfer function)was selected and improved further by incorporating two binary operators:swap-window and *** variation is labeled Improved Binary Bald Eagle Search(IBBESS2).All five variants of the proposed algorithm were successfully adopted to solve the fuel-based unit commitment problem using seven test cases of 4-,10-,20-,40-,60-,80-,and *** comparative evaluation,34 comparative methods from existing literature were compared,in which IBBESS2 achieved competitive scores against other optimization *** other words,the proposed IBBESS2 performs better than all other competitors by achieving the best average scores in 20-,40-,60-,80-,and 100-unit ***,IBBESS2 demonstrated quicker convergence to an optimal solution than other algorithms,especially in large-scale unit commitment *** Friedman statistical test further validates the results,where the proposed IBBESS2 is ranked the *** conclusion,the proposed IBBESS2 can be considered a powerful method for solving large-scale UCP and other related problems.

关键词： Swarm intelligence Bald eagle search Unit commitment problem Optimization

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TIGQA: An Expert-Annotated Question-Answering Dataset in Tigrinya 30

TIGQA: An Expert-Annotated Question-Answering Dataset in Tig...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Teklehaymanot, Hailay Kidu Fazlija, Dren Ganguly, Niloy Patro, Gourab K. Nejdl, Wolfgang L3S Research Center Leibniz University Hannover Germany Department of Computer Science and Engineering IIT Kharagpur India

ISBN: (纸本)9782493814104

The absence of explicitly tailored, accessible annotated datasets for educational purposes presents a notable obstacle for NLP tasks in languages with limited resources. This study initially explores the feasibility of using machine translation (MT) to convert an existing dataset into a Tigrinya dataset in SQuAD format. As a result, we present TIGQA, an expert-annotated dataset containing 2,685 question-answer pairs covering 122 diverse topics such as climate, water, and traffic. These pairs are from 537 context paragraphs in publicly accessible Tigrinya and Biology books. Through comprehensive analyses, we demonstrate that the TIGQA dataset requires skills beyond simple word matching, requiring both single-sentence and multiple-sentence inference abilities. We conduct experiments using state-of-the-art MRC methods, marking the first exploration of such models on TIGQA. Additionally, we estimate human performance on the dataset and juxtapose it with the results obtained from pre-trained models. The notable disparities between human performance and the best model performance underscore the potential for future enhancements to TIGQA through continued research. Our dataset is freely accessible via the provided link to encourage the research community to address the challenges in the Tigrinya MRC. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： domain specific QA Low resource QA dataset Tigrinya QA dataset

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Wearable pressure sensors based on antibacterial and porous chitosan hydrogels for full-range human motion detection

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science China(Technological sciences) 2024年第8期67卷 2475-2484页

作者： ZHANG YingXin LIU HanGuang JIN ShunYu LI YaJuan ZHANG Wan ZHOU Hang NIE ZanXiang HUANG Yuan School of Microelectronics Science and Technology Sun Yat-sen UniversityGuangzhou 510275China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 230022China Department of Clinical Laboratory the First Affiliated Hospital of Anhui Medical UniversityHefei 230022China School of Electronic and Computer Engineering Peking University Shenzhen Graduate SchoolShenzhen 518055China Zinergy Shenzhen Ltd. Shenzhen 518109China

Wearable pressure sensors made from conductive hydrogels hold significant potential in health ***,limited pressure range(Pa to hundreds of kPa)and inadequate antibacterial properties restrict their practical applications in diagnostic and health ***,a wearable high-performance pressure sensor was assembled using a facilely prepared porous chitosan-based hydrogel,which was constructed from commercial phenolphthalein particles as a sacrificial *** relationship between the porosity of hydrogels and sensing performance of sensors was systematically ***,the wearable pressure sensor,featuring an optimized porosity of hydrogels,exhibits an ultrawide sensing capacity from 4.83 Pa to 250 k Pa(range-to-limit ratio of 51,760)and high sensitivity throughout high pressure ranges(0.7 kPa~(-1),120–250 kPa).The presence of chitosan endows these hydrogels with outstanding antibacterial performance against *** and ***,making them ideal candidates for use in wearable *** features allow for a practical approach to monitor full-range human motion using a single device with a simple structure.

关键词： porous hydrogels antibacterial performances wearable pressure sensors full-range human motion chitosan

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