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AI IoT Congress (AIIoT), World

作者： Sheikh Rahmatulla Sakib Kamarun Nahar Sara Md. Tahmid Hossain Rasel Md. Masudul Islam Asif Md. Aynul Hasan Nahid Md. Saifur Rahman M. F. Mridha Ashraful Islam Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science American International University-Bangladesh Dhaka Bangladesh Center for Computational and Data Sciences Independent University Bangladesh Dhaka Bangladesh

In Dhaka, the capital city of Bangladesh, various sources including vehicle emissions, industrial activities, brick kilns, building sites, and open rubbish burning contribute to the air pollution problem. To assess the air quality, the Air Quality Index (AQI) is utilized, which categorizes air quality based on pollutant concentration. In this study, we have built ARIMA, Auto-ARIMA, SARIMAX, and VAR models to predict the air quality of Dhaka. Unlike previous studies, we have utilized hourly air pollutants factors such as PM 2.5 , PM 10 , SO 2 , CO, NO 2 , and O 3 to forecast air quality. Our novel approach enables us to predict the monthly and weekly air quality of Dhaka city. Our analysis reveals that the SARIMAX model, which takes into account seasonal patterns, trends, and external factors, is the most accurate in predicting Dhaka city’s air quality. The model’s prediction performance is assessed using statistical indicators such as mean absolute percentage error and root mean square error. The study highlights that the SARIMAX model could aid policymakers in evaluating the efficacy of air pollution control measures.

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Invertibility of Discrete-Time Linear Systems with Sparse Inputs

arXiv

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arXiv 2024年

作者： Poe, Kyle Mallada, Enrique Vidal, René Applied Mathematics and Computational Science Group University of Pennsylvania PA19104 United States Department of Electrical and Computer Engineering Johns Hopkins University MD21218 United States Departments of Electrical and Systems Engineering Radiology Computer and Information Science Statistics and Data Science University of Pennsylvania PA19104 United States

One of the fundamental problems of interest for discrete-time linear systems is whether its input sequence may be recovered given its output sequence, a.k.a. the left inversion problem. Many conditions on the state space geometry, dynamics, and spectral structure of a system have been used to characterize the well-posedness of this problem, without assumptions on the inputs. However, certain structural assumptions, such as input sparsity, have been shown to translate to practical gains in the performance of inversion algorithms, surpassing classical guarantees. Establishing necessary and sufficient conditions for left invertibility of systems with sparse inputs is therefore a crucial step toward understanding the performance limits of system inversion under structured input assumptions. In this work, we provide the first necessary and sufficient characterizations of left invertibility for linear systems with sparse inputs, echoing classic characterizations for standard linear systems. The key insight in deriving these results is in establishing the existence of two novel geometric invariants unique to the sparse-input setting, the weakly unobservable and strongly reachable subspace arrangements. By means of a concrete example, we demonstrate the utility of these characterizations. We conclude by discussing extensions and applications of this framework to several related problems in sparse control. © 2024, CC BY.

关键词： Linear systems

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Overview of Speaker Modeling and Its Applications: From the Lens of Deep Speaker Representation Learning

arXiv

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arXiv 2024年

作者： Wang, Shuai Chen, Zhengyang Lee, Kong Aik Qian, Yanmin Li, Haizhou Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Guangdong Shenzhen518172 China Auditory Cognition and Computational Acoustics Lab The Department of Computer Science and Engineering The MoE Key Laboratory of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong

Speaker individuality information is among the most critical elements within speech signals. By thoroughly and accurately modeling this information, it can be utilized in various intelligent speech applications, such as speaker recognition, speaker diarization, speech synthesis, and target speaker extraction. In this overview, we present a comprehensive review of neural approaches to speaker representation learning from both theoretical and practical perspectives. Theoretically, we discuss speaker encoders ranging from supervised to self-supervised learning algorithms, standalone models to large pretrained models, pure speaker embedding learning to joint optimization with downstream tasks, and efforts toward interpretability. Practically, we systematically examine approaches for robustness and effectiveness, introduce and compare various open-source toolkits in the field. Through the systematic and comprehensive review of the relevant literature, research activities, and resources, we provide a clear reference for researchers in the speaker characterization and modeling field, as well as for those who wish to apply speaker modeling techniques to specific downstream tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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An AI-Enabled Side Channel Power Analysis Based Hardware Trojan Detection Method for Securing the Integrated Circuits in Cyber-Physical Systems

arXiv

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arXiv 2024年

作者： Puspa, Sefatun-Noor Enan, Abyad Majumdar, Reek Salek, M. Sabbir Comert, Gurcan Chowdhury, Mashrur Glenn Department of Civil Engineering Clemson University ClemsonSC29634 United States Adjunct Faculty Glenn Department of Civil Engineering Clemson University ClemsonSC29634 United States Computational Data Science and Engineering Department North Carolina A&T State University GreensboroNC27411 United States

Cyber-physical systems rely on sensors, communication, and computing, all powered by integrated circuits (ICs). ICs are largely susceptible to various hardware attacks with malicious intents. One of the stealthiest threats is the insertion of a hardware trojan into the IC, causing the circuit to malfunction or leak sensitive information. Due to supply chain vulnerabilities, ICs face risks of trojan insertion during various design and fabrication stages. These trojans typically remain inactive until triggered. Once triggered, trojans can severely compromise system safety and security. This paper presents a non-invasive method for hardware trojan detection based on side-channel power analysis. We utilize the dynamic power measurements for twelve hardware trojans from IEEE dataPort. Our approach applies to signal processing techniques to extract crucial time-domain and frequency-domain features from the power traces, which are then used for trojan detection leveraging Artificial Intelligence (AI) models. Comparison with a baseline detection approach indicates that our approach achieves higher detection accuracy than the baseline models used on the same side-channel power dataset. © 2024, CC BY-NC-SA.

关键词： Network security

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Measurement of the ^(232)Th(n,f)cross section in the 1-200 MeV range at the CSNS Back-n

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Nuclear science and Techniques 2023年第8期34卷 142-153页

作者： Zhi-Zhou Ren Yi-Wei Yang Yong-Hao Chen Rong Liu Bang-Jiao Ye Jie Wen Hai-Rui Guo Zi-Jie Han Qi-Ping Chen Zhong-Wei Wen Wei-Li Sun Han Yi Xing-Yan Liu Tao Ye Jiang-Bo Bai Qi An Jie Bao Yu Bao Ping Cao Hao-Lei Chen Zhen Chen Zeng-Qi Cui Rui-Rui Fan Chang-Qing Feng Ke-Qing Gao Xiao-Long Gao Min-Hao Gu Chang-Cai Han Guo-Zhu He Yong-Cheng He Yang Hong Yi-Wei Hu Han-Xiong Huang Xi-Ru Huang Hao-Yu Jiang Wei Jiang Zhi-Jie Jiang Han-Tao Jing Ling Kang Bo Li Chao Li Jia-Wen Li Qiang Li Xiao Li Yang Li Jie Liu Shu-Bin Liu Ze Long Guang-Yuan Luan Chang-Jun Ning Meng-Chen Niu Bin-Bin Qi Jie Ren Xi-Chao Ruan Zhao-Hui Song Kang Sun Zhi-Jia Sun Zhi-Xin Tan Jing-Yu Tang Xin-Yi Tang Bin-Bin Tian Li-Jiao Wang Peng-Cheng Wang Zhao-Hui Wang Xiao-Guang Wu Xuan Wu Li-Kun Xie Xiao-Yun Yang Li Yu Tao Yu Yong-Ji Yu Guo-Hui Zhang Lin-Hao Zhang Qi-Wei Zhang Xian-Peng Zhang Yu-Liang Zhang Zhi-Yong Zhang Lu-Ping Zhou Zhi-Hao Zhou Ke-Jun Zhu Department of Modern Physics University of Science and Technology of ChinaHefei 230026China Institute of Nuclear Physics and Chemistry China Academy of Engineering PhysicsMianyang 621900China Institute of High Energy Physics Chinese Academy of Sciences(CAS)Beijing 100049China Spallation Neutron Source Science Center Dongguan 523803China Institute of Applied Physics and Computational Mathematics Beijing 100088China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230027China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230027China State Key Laboratory of Nuclear Physics and Technology School of PhysicsPeking UniversityBeijing 100871China State Key Laboratory of Particle Detection and Electronics Institute of High Energy PhysicsChinese Academy of SciencesBeijingChina Northwest Institute of Nuclear Technology Xi’an 710024China University of Chinese Academy of Sciences Beijing 100049China Department of Engineering and Applied Physics University of Science and Technology of ChinaHefei 230026China

The ^(232)Th(n,f)cross section is very important in basic nuclear physics and applications based on the Th/U fuel *** the time-of-flight method and a multi-cell fast-fission ionization chamber,a novel measurement of the^(232)Th(n,f)cross sec-tion relative to^(235)U in the 1–200 MeV range was performed at the China Spallation Neutron Source Back-n white neutron source(Back-n).The fission event-neutron energy spectra of^(232)Th and^(235)U fission cells were measured in the single-bunch *** 232Th/235U fission cross-sectional ratios were obtained,and the measurement uncertainties were 2.5–3.7%for energies in the 2–20 MeV range and 3.6–6.2%for energies in the 20–200 MeV ***^(232)Th(n,f)cross section was obtained by introducing the standard cross section of^(235)U(n,f).The results were compared with those of previous theoreti-cal calculations,measurements,and *** measured 232Th fission cross section agreed with the main evaluation results in terms of the experimental uncertainty,and 232Th fission resonances were observed in the 1–3 MeV *** present results provide^(232)Th(n,f)cross-sectional data for the evaluation and design of Th/U cycle nuclear systems.

关键词： 232Th(n f)cross section Fast-fission ionization chamber Back-n white neutron source

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Flow-TSVAD: Target-Speaker Voice Activity Detection via Latent Flow Matching for Speaker Diarization

Flow-TSVAD: Target-Speaker Voice Activity Detection via Late...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhengyang Chen Bing Han Shuai Wang Yidi Jiang Yanmin Qian Department of Computer Science and Engineering Auditory Cognition and Computational Acoustics Lab MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Shenzhen Research Institute of Big Data Shenzhen China School of Data Science The Chinese University of Hong Kong Shenzhen China National University of Singapore Singapore

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Speaker diarization is typically considered as a discriminative task, using discriminative approaches to produce fixed diarization results. In this paper, we explore for the first time the use of neural network-based generative methods for speaker diarization. We implement a Flow-Matching (FM) based generative algorithm within the sequenceto-sequence target speaker voice activity detection (Seq2Seq-TSVAD) diarization system. Our experiments reveal that applying the generative method directly to the original binary label sequence space of the TS-VAD output is ineffective. To address this issue, we propose mapping the binary label sequence into a dense latent space before applying the generative algorithm, and our proposed Flow-TSVAD method can significantly outperform the traditional Seq2Seq-TSVAD system. Additionally, we observe that the FM algorithm converges rapidly during the inference stage, only requiring two inference steps to achieve promising results. Moreover, as a generative model, Flow-TSVAD allows for sampling different diarization results by running the model multiple times, so the ensemble system combining the results from various sampling instances can further boost the diarization performance.

关键词： Voice activity detection Frequency modulation computational modeling Signal processing algorithms Signal processing Inference algorithms Acoustics computational efficiency

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Medical Personal Protective Equipment Detection Using YOLOV7

Medical Personal Protective Equipment Detection Using YOLOV7

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Md. Anas Ali Mahmudul Haque Saadia Binte Alam Rashedur Rahman Mashraful Amin Syoji Kobashi Graduate School of Engineering University of Hyogo Himeji Hyogo Japan Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Center for Computational & Data Sciences Independent University Bangladesh Dhaka Bangladesh

In recent years, healthcare and safety have been a major focus of deep learning research. This paper focuses on the detection of Medical Personal Protective Equipment (MPPE) in the health-care sector using YOLOv7. Improper use of personal protective equipment (PPE) can result in the contamination and cross-contamination of infectious diseases, so it is crucial for healthcare professionals to use it correctly. The CPPE-5 dataset was used to train the model, which contains 1029 high-quality images divided into five categories: coveralls, face shield, gloves, masks, and goggles. The objective of this research is to create an accurate model for future applications and development using a suitable medical PPE dataset. The proposed model outperforms previous studies, with an optimal mAP of 90.93 %, indicating that it is a promising method for detecting MPPE in the healthcare sector.

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Improved Imperialist Competitive Algorithm Based Energy Efficient Peak to Average Power Ratio (Papr) in Cooperative Mimo-Af Systems 12

Improved Imperialist Competitive Algorithm Based Energy Effi...

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12th International Conference on Computer Communication and Informatics, ICCCI 2022

作者： Kanithan, S. Ananthanarayanan, Arun Vignesh, N. Arun Kannapiran, Thirunavukkarasu Srinivasarao, N. Kumareshan, N. Madhusudhanan, S. Mvj College of Engineering Department of Ece Bengaluru560067 India Gokaraju Rangaraju Institute of Engineering and Technology Department of Ece Hyderabad500090 India Head of Data Science Unitedworld School of Computational Intelligence Karnavati University Gandhinagar382422 India Bvrit Hyderabad College of Engineering for Women Department of Ece Hyderabad500090 India Sri Shakthi Institute of Engineering and Technology Department of Ece Coimbatore641062 India Koneru Lakshmaiah Education Foundation Department of CSE Guntur522502 India

ISBN: (纸本)9781665480352

To enhance the performance of communication system, there are many cooperative techniques are available. The multi-input multi-output (MIMO) system has been analysed in this paper and its peak to average power is analysed with optimal available techniques. Such techniques are focused on various parameters and in this paper we have considered energy efficiency (EE). Practical implementations of realizing MIMO amplify and forward technique has some difficulties. In recent times, an algorithm such as Firefly fuzzy hybrid algorithm is being used. But in realizing the amplification and forward system, the performance may not be enhanced if the energy is not considered. The energy of the non linear system is associated with the average power and power efficiency. An improved imperialist competitive algorithm is proposed in this paper. The focus is mainly kept on energy efficiency. Algorithms such as EE HFFA (Energy efficient Hybrid Fuzzy Firefly Algorithm), amplify and forward system (AF) are analysed to bring out an algorithm called Improved Imperialist Competitive algorithm (IICA). It has been analysed in this paper that the simulation results of energy efficient IICA induces peak average power ratio (PAPR) which showed significant improvement in energy efficiency. © 2022 IEEE.

关键词： Energy efficiency

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Prediction of Length-of-stay at Intensive Care Unit (ICU) Using Machine Learning based on MIMIC-III database

Prediction of Length-of-stay at Intensive Care Unit (ICU) Us...

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Artificial Intelligence (CAI), IEEE Conference on

作者： Md Nahid Hasan Sammi Hamdan Samir Poudel Jorge Vargas Khem Poudel Department of Computational and Data Science Middle Tennessee State University Murfreesboro TN USA Department of Computer Science Middle Tennessee State University Murfreesboro TN USA Department of Engineering Technology Middle Tennessee State University Murfreesboro TN USA

The length-of-stay (LOS) is critical for patient care and accommodation in the intensive care unit (ICU). In this work, we developed a framework to predict the LOS using the Medical Information Mart for Intensive Care (MIMIC-III) database. We extracted six features from individual patients and submitted them to the regressors model and examined how well these features could predict LOS. We considered four prediction regimes; extreme gradient boosting (XGBoost), support vector regressor, random forest, and voting regressor. Our analysis reveals that XGBoost yields the best result among other regressors with R 2 0.86 and root mean square error (RMSE) 1.2. Remarkably, our results show that ICD9 (9 th International classification of diseases code), saline intake per hour, and drug rates are the top three critical features for predicting the LOS.

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Cortical transcriptome analysis after spinal cord injury reveals the regenerative mechanism of central nervous system in CRMP2 knock-in mice

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Neural Regeneration Research 2021年第7期16卷 1258-1265页

作者： Ayaka Sugeno Wenhui Piao Miki Yamazaki Kiyofumi Takahashi Koji Arikawa Hiroko Matsunaga Masahito Hosokawa Daisuke Tominaga Yoshio Goshima Haruko Takeyama Toshio Ohshima Laboratory for Molecular Brain Science Department of Life Science and Medical BioscienceGraduate School of Advanced Science and EngineeringWaseda UniversityTokyoJapan Biomolecular Engineering Laboratory Department of Life Science and Medical BioscienceGraduate School of Advanced Science and EngineeringWaseda UniversityTokyoJapan Computational Bio Big-Data Open Innovation Laboratory(CBBD-OIL) National Institute of Advanced Industrial Science and Technology(AIST)TokyoJapan Research Organization for Nano and Life Innovation Waseda UniversityTokyoJapan Institute for Advanced Research of Biosystem Dynamics Waseda Research Institute for Science and EngineeringGraduate School of Advanced Science and EngineeringWaseda UniversityTokyoJapan Cellular and Molecular Biotechnology Research Institute National Institute of Advanced Industrial Science and Technology(AIST)TsukubaJapan Department of Molecular Pharmacology and Neurobiology Graduate School of MedicineYokohama City UniversityYokohamaJapan

Recent studies have shown that mutation at Ser522 causes inhibition of collapsin response mediator protein 2(CRMP2) phosphorylation and induces axon elongation and partial recovery of the lost sensorimotor function after spinal cord injury(SCI).We aimed to reveal the intracellular mechanism in axotomized neurons in the CRMP2 knock-in(CRMP2KI) mouse model by performing transcriptome analysis in mouse sensorimotor cortex using micro-dissection punching *** to that, we analyzed the structural pathophysiology in axotomized or neighboring neurons after SCI and found that somatic atrophy and dendritic spine reduction in sensorimotor cortex were suppressed in CRMP2KI *** analysis of the transcriptome has aided in the identification of four hemoglobin genes Hba-a1, Hba-a2, Hbb-bs, and Hbb-bt that are significantly upregulated in wild-type mice with concomitant upregulation of genes involved in the oxidative phosphorylation and ribosomal pathways after ***, we observed substantial upregulation in channel activity genes and downregulation of genes regulating vesicles, synaptic function, glial cell differentiation in CRMP2KI ***, the transcriptome profile of CRMP2KI mice has been discussed wherein energy metabolism and neuronal pathways were found to be differentially *** results showed that CRMP2KI mice displayed improved SCI pathophysiology not only via microtubule stabilization in neurons, but also possibly via the whole metabolic system in the central nervous system, response changes in glial cells, and *** together, we reveal new insights on SCI pathophysiology and the regenerative mechanism of central nervous system by the inhibition of CRMP2 phosphorylation at *** these experiments were performed in accordance with the guidelines of the Institutional Animal Care and Use Committee at Waseda University, Japan(2017-A027 approved on March 21, 2017;2018-A003 approved on March 25, 2018;2019-A026 approved on March

关键词： CNS regeneration cortex CRMP2 hemoglobin metabolic pathway spinal cord injury spine transcriptome

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