检索结果-内蒙古大学图书馆

5th International Conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Raj, Saurabh Sakhare, Nitin N. Sharma, Yogesh Soni, Monika Bhange, Anup Deshmukh, Pradeep Kundlik Pune India Department of Computer Engineering BRACT'S Vishwakarma Institute of Information Technology Maharashtra Pune India VIIT Pune India Auricle Global Society of Education and Research Sudarshan Nagar Rajasthan Bikaner India Department of Computer Science & Engineering KDK College of Engineering Maharashtra Nagpur India Department of Computer Science and Engineering School of Computational Sciences COEP Technological University Pune India

ISBN: (纸本)9798400709418

Detecting emotions helps create more intuitive and responsive technology interfaces between humans and machines. This study introduces deep learning-based emotion detection using EEG signals. Our research uses Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, and a proposed hybrid of CNN and LSTM (ConvLSTM) along with Particle Swarm Optimization (PSO) for hyperparameter optimization. The presented study aims to improve EEG-based emotion detection, which will help create more unified and emotionally intelligent human-machine interfaces. Recent deep learning advances have advanced emotion detection. These advances have allowed systems to understand and respond to human emotions. Electroencephalography (EEG) signals can capture neural patterns linked to different emotions, giving a unique view of the brain's emotional state. However, extracting meaningful emotional information from these complex signals is difficult. EEG spatial patterns are captured using CNN and LSTM networks model data temporal dependencies. A hybrid ConvLSTM model integrates spatial and temporal information for a complete EEG analysis. The study presents a method that helps to detect emotions from EEG signals with accuracy of 99.63%. This study's high accuracy is a significant advancement in the field and has great potential for improving human-machine interaction systems. Due to the use of deep learning-based emotion detection, these systems are able to intuitively respond to the feelings of their users. They allow for deeper and more genuine connections to be made between humans and machines. The presented methodology achieves remarkable precision and lays the groundwork for emotionally intelligent technologies that can impact virtual assistants, healthcare, and entertainment. This research advances emotionally intelligent human-machine interfaces, paving the way for technology to understand and respond to human emotions with precision and sensitivity. © 2023 ACM.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Cross-Layer Hidden Markov Analysis for Intrusion Detection

引用

computers, Materials & Continua 2022年第2期70卷 3685-3700页

作者： K.Venkatachalam P.Prabu B.Saravana Balaji Byeong-Gwon Kang Yunyoung Nam Mohamed Abouhawwash Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Department of Computer Science CHRIST(Deemed to be University)Bangalore560029India Department of Information Technology Lebanese French UniversityErbil44001KRIraq Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast Lansing48824MIUSA

Ad hoc mobile cloud computing networks are affected by various issues,like delay,energy consumption,flexibility,infrastructure,network lifetime,security,stability,data transition,and link *** the issues above,route failure is prevalent in ad hoc mobile cloud computing networks,which increases energy consumption and delay and reduces *** issues may affect several interconnected nodes in an ad hoc mobile cloud computing *** address these weaknesses,which raise many concerns about privacy and security,this study formulated clustering-based storage and search optimization approaches using cross-layer *** proposed approaches were formed by cross-layer analysis based on intrusion detection ***,the clustering process based on storage and search optimization was formulated for clustering and route maintenance in ad hoc mobile cloud computing ***,delay,energy consumption,network lifetime,and link accomplishment are highly addressed by the proposed *** hidden Markov model is used to maintain the data transition and distributions in the *** data communication network,like ad hoc mobile cloud computing,faces security and confidentiality ***,the main security issues in this article are addressed using the storage and search optimization ***,the new algorithm developed helps detect intruders through intelligent cross layer analysis with theMarkov *** proposed model was simulated in Network Simulator 3,and the outcomes were compared with those of prevailing methods for evaluating parameters,like accuracy,end-to-end delay,energy consumption,network lifetime,packet delivery ratio,and throughput.

关键词： Data transition end-to-end delay energy consumption flexibility hidden Markov model intrusion detection link optimization packet delivery ratio privacy security searching throughput

来源：评论

学校读者我要写书评

暂无评论

MatrikalinDiabetes: User-Centered Design of a mHealth App for Gestational Diabetes Mellitus Management and Education Among Bangladeshi Women 26th

MatrikalinDiabetes: User-Centered Design of a mHealth App ...

引用

26th International Conference on Human-computer Interaction, HCII 2024

作者： Ratul, Mohammad Arshad Hossain Yanoor Bristy, Tunisha Sayeed, Noorjahan Islam, Ashraful Chaudhry, Beenish Moalla Center for Computational and Data Sciences Independent University Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh School of Computing and Informatics University of Louisiana at Lafayette Louisiana United States

ISBN: (纸本)9783031768088

This study employs the User-Centered Design (UCD) methodology to develop a mobile health (mHealth) application (app) specifically tailored for Bangladeshi women with Gestational Diabetes Mellitus (GDM). GDM affects approximately 10% of pregnant women globally and around 35% within Bangladesh, as reported by the World Health Organization (WHO). Despite its high prevalence, there is a significant lack of awareness and education about GDM in Bangladesh, compounded by language barriers that make existing digital solutions less accessible. The MatrikalinDiabetes mHealth app aims to overcome these barriers by providing comprehensive management and educational resources for GDM in the Bangla language, addressing both pre-pregnancy and post-pregnancy needs. To ensure the app meets the actual needs of potential users, personas were created based on a literature review, and a survey was conducted. This process informed the development of both a low-fidelity, paper-based prototype and a high-fidelity digital prototype. Key features of the MatrikalinDiabetes app include tracking of food and water intake, physical activity monitoring, reminders, GDM education, chat forums for community support, blood glucose level (BGL) monitoring, an SOS button for emergency contacts, and quizzes for user engagement. Preliminary feedback indicated that 53.8% of participants favored the integrated features and expressed willingness to use and recommend the app. The survey of the high-fidelity prototype yielded positive responses, with 57.9% of participants strongly agreeing and 42.1% agreeing that the features were beneficial. The user-friendly design of the high-fidelity prototype ensures intuitive interaction, aiding in health management, enhancing GDM understanding, and promoting a healthier lifestyle among pregnant women in Bangladesh. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Obstetrics

来源：评论

学校读者我要写书评

暂无评论

Secure Data Reduplication System with Efficient and Reliable Multi-Key Management in Cloud Storage 3

Secure Data Reduplication System with Efficient and Reliable...

引用

3rd International Conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Jayaram, B. Suguna, T. Fairooz, Shaik Arul Selvam, P. Vimal, S. Rmk Engineering College Department of Computer Science and Business Systems Tamil Nadu Kavaraipettai India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Malla Reddy Engineering College Department of Cse -AIML Telangana Secunderabad India Hindusthan College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore India School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Tamil Nadu Kattankulathur India

ISBN: (纸本)9798350336238

Malicious hackers may compromise hundreds or millions of machines with little effort, allowing them to shut down networks, steal sensitive data, and compromise critical infrastructure. Data is stolen and used for malicious purposes by hackers who exploit security flaws in the network. And the sophisticated technology they use, like the bucks they do, are continually feeding them the information they needed, not just once. Moreover, even if Internet firewalls have improved, cybercrime has been on the rise. Then, we have a long way to go before we approach the limit, what with all the different kinds of cloud server devices that can connect to the internet nowadays. It's certain that in the future, little devices, no matter how helpful they are really in our everyday lives, will become the preferred tool of villains. In this research, we offer a novel security technique for protecting sensitive data on cloud servers. This intelligent cloud server was protected from any hacking with the aid of this algorithm. The system's output was measured against those of pre-existing algorithms. More than 96% of inputs are authenticated by the proposed technique, while password cracking operations are reduced by about 3%. The source code security management is improved to 99% and the updating issues for various devices entries is reduced 0.02%, and further the privacy breach is reduced up to 0.32%. Hence the proposed method was more secured from cyber security issues. © 2023 IEEE.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Effect on Public Health Due to Environment Condition- Role of IoT 14

Effect on Public Health Due to Environment Condition- Role o...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Joshi, Kapil Rastogi, Ritesh Singh, Anupam Kaushik, Vishal Anandaram, Harishchander Kumar, Anil Uttaranchal University Uttaranchal Institute of Technology Department of Cse Dehradun India Niet Department of Computer Science & Engineering Greater Noida India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India Upes School of Computer Science Dehradun India Amrita Vishwa Vidyapeetham Centre for Computational Engineering and Networking Tamil Nadu Coimbatore India Dit University School of Computing Dehradun India

ISBN: (纸本)9798350335095

The biggest environmental issues are poor air quality, polluted water, contaminated food, polluted transportation, and radiation contamination. In order to ensure sustainable growth and preserve a stable social structure, adequate monitoring is required. With the development of contemporary sensors and advancements in the internet of things (IoT), environmental surveillance has evolved into a smart environment monitoring (SEM) platform in recent decades. The emergence and widespread use of Internet of Things (IoT) devices and its supporting technologies are the driving forces behind the growth of ubiquitous systems, as shown in this study. This study analysisIoT has great promise in the environment, health, & safety (EHS) industries that involve high risk. The social health can be improved with the use of technology that manages and organises information about individuals. IoT may actually serve as the foundation for a society that is health. In this study, we discussed how the Internet of Things (IoT) may benefit individuals and how it can be used for public health. and also highlight IoT-related problems and a suggested remedy. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Gaussian Support Vector Machine Algorithm Based Air Pollution Prediction

引用

computers, Materials & Continua 2022年第4期71卷 683-695页

作者： K.S.Bhuvaneshwari J.Uma K.Venkatachalam Mehedi Masud Mohamed Abouhawwash T.Logeswaran Department of Computer Sceince and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Electrical and Electronics Engineering M.Kumarasamy College of EngineeringKarur639113India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Electrical and Electronics Engineering Kongu Engineering CollegeErode638060India

Air pollution is one of the major concerns considering detriments to human *** type of pollution leads to several health problems for humans,such as asthma,heart issues,skin diseases,bronchitis,lung cancer,and throat and eye *** pollution also poses serious issues to the *** from the vehicle industry is the cause of greenhouse effect and CO2 ***,real-time monitoring of air pollution in these areas will help local authorities to analyze the current situation of the city and take necessary *** monitoring process has become efficient and dynamic with the advancement of the Internet of things and wireless sensor *** is the main issue in WSNs;if the sensor node location is unknown,then coverage and power and routing are not *** study concentrates on localization-based air pollution prediction systems for real-time monitoring of smart *** systems comprise two phases considering the prediction as heavy or light traffic area using the Gaussian support vector machine algorithm based on the air pollutants,such as PM2.5 particulate matter,PM10,nitrogen dioxide(NO2),carbon monoxide(CO),ozone(O3),and sulfur dioxide(SO2).The sensor nodes are localized on the basis of the predicted area using the meta-heuristic algorithms called fast correlation-based elephant herding *** dataset is divided into training and testing parts based on 10 *** evaluation on predicting the air pollutant for localization is performed with the training *** error prediction in localizing nodes is 9.83 which is lesser than existing solutions and accuracy is 95%.

关键词： Air pollution monitoring air pollutant SVM Gaussian EHO fast correlation WSN localization

来源：评论

学校读者我要写书评

暂无评论

Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations

引用

Research 2024年第2期2023卷 473-489页

作者： Zhe Liu Wei Qian Wenxiang Cai Weichen Song Weidi Wang Dhruba Tara Maharjan Wenhong Cheng Jue Chen Han Wang Dong Xu Guan Ning Lin Shanghai Mental Health Center Shanghai Jiao Tong University School of MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina Shanghai Key Laboratory of Psychotic Disorders ShanghaiChina School of Information Science and Technology Institute of Computational BiologyNortheast Normal UniversityChangchunChina Department of Electrical Engineering and Computer Science University of MissouriColumbiaMO 65211USA Christopher S.Bond Life Sciences Center University of MissouriColumbiaMO 65211USA

Identifying pathogenetic variants and inferring their impact on protein-protein interactions sheds light on their functional consequences on *** by the availability of experimental data on the consequences of protein interaction,most existing methods focus on building models to predict changes in protein binding ***,we introduced MIPPI,an end-to-end,interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from *** was specifically trained to determine the types of variant impact(increasing,decreasing,disrupting,and no effect)on protein-protein *** demonstrate the accuracy of MIPPI and provide interpretation through the analysis of learned attention weights,which exhibit correlations with the amino acids interacting with the ***,we showed the practicality of MIPPI in prioritizing de novo mutations associated with complex neurodevelopmental disorders and the potential to determine the pathogenic and driving ***,we experimentally validated the functional impact of several variants identified in patients with such ***,MIPPI emerges as a versatile,robust,and interpretable model,capable of effectively predicting mutation impacts on protein-protein interactions and facilitating the discovery of clinically actionable variants.

关键词： consequences weights versatile

来源：评论

学校读者我要写书评

暂无评论

Analysis of Smart Healthcare Application in 5G Using Manet 2

Analysis of Smart Healthcare Application in 5G Using Manet

引用

2nd International Conference for Innovation in Technology, INOCON 2023

作者： Sahaaya Arul Mary, S.A. Rajput, Akshay Kumar, S.Jerald Nirmal Kandasamy, Manivel Lakhan, Ram VIT Vellore Department of SCOPE Tamilnadu India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Sharda University Department of Computer Science and Engineering Delhi NCR India Karnavati University Unitedworld School of Computational Intelligence Gujarat India Galgotias University Greater Department of CSE Noida India

ISBN: (纸本)9798350320923

The 5G technology has been highly anticipated by everyone lately. The activation of a whole new type of network is required to connect everything together, from machines and items to other gadgets and electronics. High peak data speeds through several GPS satellites, minimal latency, dependability is just a few of the advantages of 5G technology. Improved performance can result in a better user experience as well as the formation of new business relationships. Using OFDM, which is a technique for converting digital signals across several channels, interference is reduced to the absolute minimum. 5G technology makes use of the 5G NR Air interface, which is based on OFDM principles. In this paper, a smart health care application model was proposed based on the Mobile Ad-Hoc Network (MANET) in 5G communication. This smart application will help the doctors to identify the patient's health issues and provide the treatment to them over the high band coverage of network. The proposed method achieves good accuracy (90%), excellent precision (91%), outstanding recall rate (92%) fine Fl-score (91%) and very low computation time while compared with the existing methods. © 2023 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Efficient Optimal Control of Open Quantum Systems 19

Efficient Optimal Control of Open Quantum Systems

引用

19th Conference on the Theory of Quantum Computation, Communication and Cryptography, TQC 2024

作者： He, Wenhao Li, Tongyang Li, Xiantao Li, Zecheng Wang, Chunhao Wang, Ke Center for Computational Science and Engineering MIT CambridgeMA United States School of Physics Peking University Beijing China Center on Frontiers of Computing Studies School of Computer Science Peking University Beijing China Department of Mathematics Pennsylvania State University University ParkPA United States Department of Computer Science and Engineering Pennsylvania State University University ParkPA United States

ISBN: (纸本)9783959773287

The optimal control problem for open quantum systems can be formulated as a time-dependent Lindbladian that is parameterized by a number of time-dependent control variables. Given an observable and an initial state, the goal is to tune the control variables so that the expected value of some observable with respect to the final state is maximized. In this paper, we present algorithms for solving this optimal control problem efficiently, i.e., having a poly-logarithmic dependency on the system dimension, which is exponentially faster than best-known classical algorithms. Our algorithms are hybrid, consisting of both quantum and classical components. The quantum procedure simulates time-dependent Lindblad evolution that drives the initial state to the final state, and it also provides access to the gradients of the objective function via quantum gradient estimation. The classical procedure uses the gradient information to update the control variables. At the technical level, we provide the first (to the best of our knowledge) simulation algorithm for time-dependent Lindbladians with an 1-norm dependence. As an alternative, we also present a simulation algorithm in the interaction picture to improve the algorithm for the cases where the time-independent component of a Lindbladian dominates the time-dependent part. On the classical side, we heavily adapt the state-of-the-art classical optimization analysis to interface with the quantum part of our algorithms. Both the quantum simulation techniques and the classical optimization analyses might be of independent interest. © Wenhao He, Tongyang Li, Xiantao Li, Zecheng Li, Chunhao Wang, and Ke Wang.

关键词： Optimal control systems

来源：评论

学校读者我要写书评

暂无评论

Evolving Safety Protocols: Deep Learning-Enabled Detection of Personal Protective Equipment 1

引用

4th International Conference on computer Vision, High-Performance Computing, Smart Devices, and Networks, CHSN 2023

作者： Alahmid, Mustafa Bhimani, Kishankumar Saradva, Khushbu Ghildiyal, Sushil Saeedi, Sayed Aryan Ali, Saraa Yan, Han Filippov, Evgeny Faculty of Computer Science and Technology Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia Laboratory on AI for Computational Biology Faculty of Computer Science HSE University Moscow Russia Department of Computer Science and Engineering Indian Institute of Technology Ropar Punjab India Laboratory of Methods for Big Data Analysis Faculty of Computer Science HSE University Moscow Russia Deggendorf Institute of Technology Bavaria Germany

ISBN: (数字)9789819777945

ISBN: (纸本)9789819777938

To give shift in safety protocols, we have employed advanced deep learning algorithms and frameworks (Shrestha and Mahmood in IEEE Access 7:53,040–53,065, 2019 [25]) to construct an innovative AI model. The designed model detects the usage of personal protective equipment (PPE) (Personal protective equipment. Geneva: World Health Organization, 2020 [18]) by workers in high-risk industries such as construction and manufacturing. We have used Google’s TensorFlow object detection API (Sai and Sasikala in Object detection and count of objects in image using tensor flow object detection API, pp 542–546, 2019 [22]) to modify and train a model for dual purposes: PPE detection and face recognition. The state-of-the-art of this research is to substantially enhance safety compliance by addressing the prevalent issue of PPE non-compliance. To emphasis this, we have developed a pioneering software prototype that synergizes PPE detection with a face recognition-based clock-in system. This prototype demonstrates impressive object detection metrics with a mean average precision (mAP) of 0.9 for vests and 0.85 for helmets. Moreover, it exhibited efficient face recognition with a successful threshold range of 17–20%. The implementation of AI in our system promises significant enhancements to worker safety, while concurrently reducing the financial burden associated with big hazards and accidents. Beyond the development and performance of the system, this paper provides a thorough exploration of the encountered challenges, potential real-world applications (particularly in employee monitoring and clock-in systems), and the future implications of this study on research and practical applications in the field of AI-integrated safety compliance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Software prototyping

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：