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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Bharanidharan, N. Abhinav, Kalluri Karthikeyagopala Lathvik, Cherukuri Krishna Chethan, Muppavarapu Reddy, Metta Manikanta Karthikeya Deepak, K. Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9798331504403

Oral cancer diagnosis at earlier stage is very crucial to decide the treatment procedure and to avoid mortality due to this malignant disease. Histopathological imaging is one among modalities widely used by the clinicians to identify the oral cancer. This research focuses on utilizing the hybridized version of transfer learning to extract the deep features from the histopathological oral images for oral cancer detection. Three transfer learning approaches namely VGG16, MobileNetV2, and ResNet50 are used to extract the features individually and then variance based filter technique is used to choose the appropriate features. The experiment is done using 439 oral cancer images and 89 normal images which are obtained from an online repository. The suggested approach offers 97% accuracy while the accuracy attained by stand-alone transfer learning models are less than 90%. © 2024 IEEE.

关键词： Lung cancer

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Operando chemo-mechanical evolution in LiNi0.8Co0.1Mn0.1O2 cathodes

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National science Review 2024年第9期11卷 253-263页

作者： Yi Zhang Shuaipeng Hao Fei Pei Xiangpeng Xiao Chang Lu Xing Lin Zhe Li Haijin Ji Yue Shen Lixia Yuan Zhen Li Yunhui Huang State Key Laboratory of Material Processing and Die & Mould Technology School of Materials Science and EngineeringHuazhong University of Science and Technology School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access SystemWuhan National Laboratory for OptoelectronicsHuazhong University of Science and Technology Gatan Inc.& EDAX LLC. AMETEK Commercial Enterprise (Shanghai)Co. Ltd.Pilot Free Trade Zone Department of Physics The Chinese University of Hong Kong

Ni-rich LiNixCoyMnzO2（NCMxyz,x+y+z=1,x≥0.8） layered oxide materials are considered the main cathode materials for high-energy-density Li-ion ***,the endless cracking of polycrystalline NCM materials caused by stress accelerates the loss of active materials and electrolyte decomposition,limiting the cycle ***,understanding the chemo-mechanical evolution during（de）lithiation of NCM materials is crucial to performance *** this work,an optical fiber with με resolution is designed to in operando detect the stress evolution of a polycrystalline LiNi0.8Co0.1Mn0.1O2（P-NCM811） cathode during *** integrating the sensor inside the cathode,the stress variation of P-NCM811 is completely transferred to the optical *** find that the anisotropy of primary particles leads to the appearance of structural stress,inducing the formation of microcracks in polycrystalline particles,which is the main reason for capacity *** isotropy of primary particles reduces the structural stress of polycrystalline particles,eliminating the generation of ***,the P-NCM811 with an ordered arrangement structure delivered high electrochemical performance with capacity retention of 82% over 500 *** work provides a brand-new perspective with regard to understanding the operando chemo-mechanical evolution of NCM materials during battery operation,and guides the design of electrode materials for rechargeable batteries.

关键词： Ni-rich layered oxide cathode in operando stress monitoring polycrystalline chemo-mechanical evolution

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Predicting Genetic Disorders: A Link Mining Approach 2

Predicting Genetic Disorders: A Link Mining Approach

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Sen, Madhura Rajasekaran, Rajkumar Jayaram Reddy, A. Govinda, K. Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350306415

Genetic diseases are conditions caused by a spontaneous alteration or mutation in an individual's DNA. People can inherit genetic disorders from parents, which means they are born with them, even if they are not initially noticeable. On the other hand, some illnesses are not inherited and arise due to disease-causing mutations occurring during cell division. In link mining, link prediction is a crucial task. Based on attribute information and observed existing link information, link prediction predicts if there will be a link between two nodes. Link prediction is applicable not just in the sphere of social networks but also in other fields. This project primarily aims to forecast a person's probability of being diagnosed with a genetic condition. To accomplish this, elements such as the person's family history, the environment in which they live, and a variety of others will be considered. The likelihood of a person being diagnosed with a specific genetic condition can be predicted using the Firefly algorithm. If a person is genetically connected to someone having a given ailment, they are more likely to be diagnosed. Pollution, radioactive radiation, and other environmental factors may also affect the disease's incidence. Considering these factors, we suggest a method for determining the likelihood of a person being diagnosed via link prediction. © 2024 IEEE.

关键词： firefly algorithm genetic disorders healthcare link prediction social network analysis

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An Intelligent Intrusion Detection using Rule-based CNN with PSO Optimizer 3

An Intelligent Intrusion Detection using Rule-based CNN with...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Karpurasundharapondian, P. Selvi, M. Thangaramya, K. Santhosh Kumar, S.V.N. Kannan, A. Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350372120

Security and secure routing are important design issues in the design of Wireless Sensor Networks (WSNs). Intrusion Detection systems (IDSs) are useful for securing the communication in WSNs. An IDS can be developed by using machine learning based approach. On the other hand, it can be developed using a deep learning classification algorithm. Optimization techniques including Particle Swarm Optimization (PSO) are useful for choosing optimal features from given dataset. This paper proposes an extended CNN algorithm by extending the existing CNN classifier with rules, SVM and PSO named Rule Extended CNN with SVM (RE-SVM-CNN) for developing this IDS which reduces the false alarm rate by enhanced detection accuracy. © 2024 IEEE.

关键词： Wireless sensor networks

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DevSched: an efficient bug-triaging model for allocating and balancing developer tasks

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Iran Journal of Computer science 2024年第1期7卷 1-11页

作者： Uddin, K. M. Aslam Satu, Md. Shahriare Riyad, Md. Mahmudul Hasan Sakib, Kazi Institute of Information Technology University of Dhaka Dhaka Bangladesh Department of Information and Communication Engineering Noakhali Science and Technology University Noakhali Bangladesh Department of Management Information Systems Noakhali Science and Technology University Noakhali Bangladesh Department of Applied Mathematics Noakhali Science and Technology University Noakhali Bangladesh

Bug triage is a critical aspect of software development that involves classifying and prioritizing reported bugs. Effective bug triage ensures that resources are allocated and bug patterns are efficiently identified to address underlying issues. However, inappropriate bug distributions among different types of developers cause delays, errors, incapability, and lower job satisfaction. Many works were proposed to recommend developers for fixing bugs. However, previous works did not consider the proper workload distributions among developers. The objective of the work is to introduce a task allocation and load-balancing model called Developer Scheduler (DevSched) that properly distributes unassigned bugs among different types of developers more efficiently. DevSched creates multiple developer profiles from existing bug reports. Different new bug reports are converted bug into vectors, and developer profiles are transformed into a corpus of words. Then, different bugs are assigned into developers by comparing the highest cosine similarity between vectors of bugs and developers’ corpus. DevSched dynamically updates the developer’s workload, and their ratings are adjusted based on the performance. In this work, Eclipse, Mozilla, and NetBeans bug reports are utilized to investigate individual developers’ performance in bug-triaging process. DevSched assigns and balances bugs among different kinds of developers more efficiently. After applying the proposed load-balancing model, the standard deviations are rapidly decreased than normal bug distributions for different datasets. This process is repeated for each bug to ensure the efficient allocation of resources and the resolution of critical issues. Therefore, the lowest standard deviation is found to be 0.48 for the Eclipse dataset. By assigning bugs based on defined thresholds, skills, and workloads, DevSched improves its efficiency, reduces delays, and enhances job satisfaction among developers. © The Author(s), under exc

关键词： Developer DevSched Load balancing Standard deviation

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Data Secure Storage Mechanism for IIoT Based on Blockchain

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Computers, Materials & Continua 2024年第3期78卷 4029-4048页

作者： Jin Wang Guoshu Huang R.Simon Sherratt Ding Huang Jia Ni School of Computer Science and Mathematics Fujian University of TechnologyFuzhou350118China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410004China School of Systems Engineering The University of ReadingReadingRG66AYUK School of Computer Nanjing University of Information Science and TechnologyNanjing210044China

With the development of Industry 4.0 and big data technology,the Industrial Internet of Things(IIoT)is hampered by inherent issues such as privacy,security,and fault tolerance,which pose certain challenges to the rapid development of *** technology has immutability,decentralization,and autonomy,which can greatly improve the inherent defects of the *** the traditional blockchain,data is stored in a Merkle *** data continues to grow,the scale of proofs used to validate it grows,threatening the efficiency,security,and reliability of blockchain-based ***,this paper first analyzes the inefficiency of the traditional blockchain structure in verifying the integrity and correctness of *** solve this problem,a new Vector Commitment(VC)structure,Partition Vector Commitment(PVC),is proposed by improving the traditional VC ***,this paper uses PVC instead of the Merkle tree to store big data generated by *** can improve the efficiency of traditional VC in the process of commitment and ***,this paper uses PVC to build a blockchain-based IIoT data security storage mechanism and carries out a comparative analysis of *** mechanism can greatly reduce communication loss and maximize the rational use of storage space,which is of great significance for maintaining the security and stability of blockchain-based IIoT.

关键词： Blockchain IIoT data storage cryptographic commitment

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Discovering Frequency Bursting Patterns in Temporal Graphs 39

Discovering Frequency Bursting Patterns in Temporal Graphs

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39th IEEE International Conference on Data engineering, ICDE 2023

作者： Zhang, Qianzhen Guo, Deke Zhao, Xiang Yuan, Long Luo, Lailong National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory China National University of Defense Technology Laboratory for Big Data and Decision China Nanjing University of Science and Technology China

ISBN: (纸本)9798350322279

A frequency bursting pattern (FBP) in temporal graphs represents some interaction behavior that accumulates its frequency at the fastest rate. Mining FBPs is essential to early warning of emergencies. However, existing studies on frequency-based pattern mining in graphs do not consider the temporal information and bursting features of a subgraph pattern. As a result, they may not provide effective and efficient mining algorithms for FBP discovery. In this paper, we study the problem of discovering top-k FBPs in temporal graphs. We present a novel model, referred to as maximal (m, θ)-bursting pattern, to describe FBPs in a temporal graph, which is a subgraph with a size larger than m that accumulates its frequency at the fastest rate during a time interval of length no less than θ. A naive solution for top-k FBPs discovery is to use the best-first search algorithm, where the burstiness threshold changes as more patterns are mined. However, this method will result in huge search space since we need to check every possible time interval for a candidate pattern in the temporal graph. To tackle this problem, we devise an online top-k framework in which k candidate results are maintained from the initial timestamp to the end in the temporal graph. Under the new framework, we further conceive two optimization strategies by exploiting incremental subgraph matching and Evolutionary Game Theory to boost the performance. Extensive experiment results on five real temporal graphs show that our algorithm has higher efficiency, effectiveness and scalability. © 2023 IEEE.

关键词： Game theory

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Spatiotemporal influence of driving factors on water conservation in underdeveloped plateau regions: a case in the Yellow River Basin of Sichuan, China

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Journal of Mountain science 2025年第4期22卷 1289-1305页

作者： WANG Xuan MA Lei LU Heng LIU Chao NIE Ruihua LI Naiwen TAN Xiao YANG Zhengli Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural ResourcesSchool of Geography and Ocean ScienceNanjing UniversityNanjing 210023China State Key Laboratory of Hydraulics and Mountain River Engineering College of Hydraulic and Hydroelectric EngineeringSichuan UniversityChengdu 610065China

The Yellow River Basin in Sichuan Province(YRS)is undergoing severe soil erosion and exacerbated ecological vulnerability,which collectively pose formidable challenges for regional water conservation(WC)and sustainable *** effectively enhancing WC necessitates a comprehensive understanding of its driving factors and corresponding intervention strategies,existing studies have largely neglected the spatiotemporal heterogeneity of both natural and socio-economic ***,this study explored the spatiotemporal heterogeneity of WC drivers in YRS using multi-scale geographically weighted regression(MGWR)and geographically and temporally weighted regression(GTWR)models from an eco-hydrological *** discovered that downstream regions,which are more developed,achieved significantly better WC than upstream *** results also demonstrated that the influence of temperature and wind speed is consistently dominant and temporally stable due to climate stability,while the influence of vegetation shifted from negative to positive around 2010,likely indicating greater benefits from understory *** growth positively impacted WC in upstream regions but had a negative effect in the more developed downstream *** findings highlight the importance of targeted water conservation strategies,including locally appropriate revegetation,optimization of agricultural and economic structures,and the establishment of eco-compensation mechanisms for ecological conservation and sustainable development.

关键词： Water conservation Multi-scale Geographically Weighted Regression Geographically and Temporally Weighted Regression The Yellow River Basin in Sichuan Province Spatiotemporal variation

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Synergistically enhanced dielectric, insulating and thermally conductive performances of sandwich PMMA based dielectric films

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Progress in Natural science:Materials International 2024年第3期34卷 591-597页

作者： Dongmei Zhang Yufan Li Yuchao Li Zhonggui Sun Hanxue Zhu Lujia Yang Yanhu Zhan Yankai Li Shi Wang Jun-Wei Zha School of Mathematical Sciences Liaocheng University School of Materials Science and Engineering Liaocheng University State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications School of Chemistry and Biological Engineering University of Science and Technology Beijing

A tri-layered(B-G-B) dielectric films were simply prepared by alternatively spin-coating boron nitride/polymethylmethacrylate(BN/PMMA, B) and graphene nanosheets(GNS/PMMA, G) compound solutions. The structure, morphology, thermal conductivity, and particularly the dielectric and relaxation behaviors were systematically studied. Results showed that a good exfoliation and dispersion of BN and GNS can be simply achieved through intensive mechanical compounding with PMMA in the internal mixer. The dielectric constant and breakdown strength of the obtained 1-3-1(B-G-B) sandwich composite film reached 4.3(@1 kHz) and 458.6kV/mm, being 119 % and 113 % higher than that of pure PMMA, respectively. Furthermore, the overall thermal conductivity of sandwich 1-3-1 composite increased by 112 % due to the addition of thermally conductive BN and GNS. The sandwich design strategy provided an effective way of achieving good permittivity, high insulation, and improved thermal conductivity simultaneously, showing potential applications in the miniaturization and integration of electronic devices.

关键词： Sandwich structure Breakdown strength Thermal conductivity Dielectric constant Composites

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Polarization‑entangled photon‑pair source with van der Waals 3R‑WS_(2) crystal

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eLight 2024年第1期4卷 99-106页

作者： Jiangang Feng Yun‑Kun Wu Ruihuan Duan Jun Wang Weijin Chen Jiazhang Qin Zheng Liu Guang‑Can Guo Xi‑Feng Ren Cheng‑Wei Qiu Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Optical Science and Engineering and Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433China

Ultracompact entangled photon sources are pivotal to miniaturized quantum photonic *** der Waals(vdW)nonlinear crystals promise efficient photon-pair generation and on-chip monolithic integration with nanophotonic ***,it remains challenging to generate maximally entangled Bell states of photon pairs with high purity,generation rate,and fidelity required for practical ***,we realize a polarization-entangled photon-pair source based on spontaneous parametric down conversion in an ultrathin rhombohedral tungsten disulfide(3R-WS2)*** vdW entangled photonic source exhibits a high photon-pair purity with a coincidenceto-accidental ratio of above 800,a generation rate of 31 Hz,and two maximally polarization-entangled Bell states with fidelities exceeding 0.93 and entanglement degree over *** results stem from scalable optical nonlinearity,enhanced second-order susceptibility by electronic transitions,and a well-defined symmetry-enabled selection rule inherent in *** polarization entangled photon source can be integrated with photonic structures for generating more complex entangled states,thus paving an avenue for advanced quantum photonic systems toward computation and metrology.

关键词： purity maximal Polarization

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