检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Modelling, Simulation and Intelligent Computing, MoSICom 2023

作者： Dalal, Riya Randhawa, Simrat Kaur Modi, Shrey Vishwakarma, Rahul Adani Institute of Infrastructure Engineering Department of Information and Communication Technology Ahmedabad India California State University Long Beach Department of Computer Engineering and Computer Science Long Beach United States California State Uni. Long Beach Department of Computer Engineering and Computer Science Long BeachCA United States

ISBN: (纸本)9798350393415

Geolocation refers to the identification of the geographic location of a user or computing device via a variety of data collection mechanisms. The proposed system aims to enable accurate and efficient localization of objects within a given environment. Traditional positioning systems often rely on GPS or other sensor-based technologies, which may face limitations in indoor or highly cluttered environments. To overcome these challenges, our approach leverages the power of CBIR, which involves matching query images with a pre-existing database of reference images. By extracting key features from images and employing Annoy, a fast approximate nearest neighbor library, we achieve efficient retrieval and comparison of images. The extracted features act as robust descriptors, enabling accurate positioning of objects based on visual similarities. This research contributes to the advancement of positioning systems by introducing a novel methodology that combines CBIR, Annoy, and feature extraction techniques, offering a promising solution for accurate object localization in challenging *** dataset that has been is used is gathered by the authors and the dataset plays a crucial role in position mapping, enabling accurate and context-Aware positioning within a given *** results demonstrate the effectiveness of the proposed position system, as it achieves high accuracy and real-Time performance. This research contributes to the advancement of positioning systems by introducing a novel methodology that combines CBIR, Annoy, and feature extraction techniques, offering a promising solution for accurate object localization in challenging environments. © 2023 IEEE.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

Function Scheduling with Data Security in Serverless Computing systems

Function Scheduling with Data Security in Serverless Computi...

引用

International Communication systems and Networks and Workshops, COMSNETS

作者： Srestha Saha Arvind Pandey Sourav Kanti Addya Shubha Brata Nath Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati India Department of Computer Science and Engineering SRM Institute of Science and Technology Tamil Nadu India Department of Computer Science and Engineering National Institute of Technology Karnataka Surathkal India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

In serverless computing, the service provider takes full responsibility for function management. However, serverless computing has many challenges regarding data security and function scheduling. To address these challenges, we have proposed a system to secure the data of an end-user. We also aim to meet the quality of service (QoS) for the end-user requests. This work presents a Simulated Annealing-based optimization algorithm for function placement. Also, we have Hyperledger Fabric, a blockchain framework in the system architecture for securing the data of an end-user. We have conducted experiments in Amazon Elastic Compute Cloud (EC2) taking virtual machine instances. The experiments in Amazon EC2 indicate that the proposed system secures the data and enhances the end-user’s QoS.

关键词： Processor scheduling Distributed ledger Data security Serverless computing systems architecture Quality of service Simulated annealing Virtual machines Fabrics Time factors

来源：评论

学校读者我要写书评

暂无评论

Unveiling Genetic Disorders: Machine Learning and Deep Learning Approaches in Gene Expression Analysis 2

Unveiling Genetic Disorders: Machine Learning and Deep Learn...

引用

2nd International Conference on Intelligent Cyber Physical systems and Internet of Things, ICoICI 2024

作者： Revathi, K. Karthikeyan, V.V. Priyanka, S. Prakash, S. Jaya Sns College of Engineering Department of Information Technology Tamil Nadu Coimbatore India Sns College of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore India Idhaya Engineering College for Women Department of Computer Science and Engineering Tamilnadu Chinnasalem India

ISBN: (纸本)9798331540661

The human body is composed of cells, and each cell has a variety of components. Cancer is one of the most serious illnesses in the world and is a leading cause of India's death rate. Breast cancer is frequently diagnosed in women, and one in twenty-eight Indian women is likely to develop breast cancer during her lifetime. There is a need of early identification and accurate prognosis of breast cancer to improve the recovery rate of patients. Once identified, the stage of cancer is the information which shows the extent of cancer within a patient. A cancer staging system also performs an important role in the identification of most of the cancer subtypes. It interprets a patient's prognosis and the treatment options available. Cancer registries collect medical data related to cancer, such as the number of patients, cancer type, age, sex, recovery rate, mortality rate, etc. In order to conduct an analysis of cancer, cancer registries also require cancer stage information. Earlier, the anatomic stage based on anatomic factors was used to identify the cancer stage of breast cancer patients, but more recently, the prognostic stage has been used to identify the cancer stage of breast cancer patients. Clinical experts refer to the prognostic stage for cancer prognosis and for precise outcome prediction because it is based on anatomic and biologic factors. The results generated by ML algorithms will be made interpretable with the help of Explainable AI technology to identify Cancer Biomarkers from the Genomic data. From the obtained results, Precision Medicine will be recommended to the Cancer patients. The results will be validated in the Cancer hospitals on the actual patients being treated. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

CRISP - DM Process in Smart Building Management 11

CRISP - DM Process in Smart Building Management

引用

11th International Conference on Electrical and Electronics Engineering, ICEEE 2024

作者： Dursun, Mahir Sabyrzhan, Moldir Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey Graduate School of Informatics Gazi University Department of Computer Science Ankara Turkey

ISBN: (纸本)9798350362541

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM). © 2024 IEEE.

关键词： information management

来源：评论

学校读者我要写书评

暂无评论

CampusSight—College Management Automation Using Full Stack and RPA 12th

CampusSight—College Management Automation Using Full Stack ...

引用

12th International Conference on Recent Trends in Computing, ICRTC 2024

作者： Manohar, Eashaan Duraimurugan, N. Vijay, K. Narayana, K.E. Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India Department of Information Technology Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9789819789450

The college management diaspora encapsulates various stakeholders such as students, faculty members, administrative personnel, and other staff. Unfortunately, most of the management workflows are undertaken manually, leading to silos, long paper work and admin overhauls. The pivotal aim of this research project is to digitalize the college management by bringing the entire setup into an intelligent application, leveraging key technologies like Automation, data analytics, full stack development. This application ultimately streamlines cumbersome tasks and enhance working across the college environment, promoting transparency and facilitating seamless interfaces for the entire user base. Swapping the monotonous manual workings with state-of-art digital platform will elevate the overall student experience by bringing down the high latency issue with the manual undertakings. Prime features of the application features management in terms of attendance, absences, on-duty requests, result disbursement, course registration, and facilitation of placement processes. Also, the system will promote enhanced organizing of events related to campus, industrial visits, increasing the net student engagement within the college and opening new opportunities. The system prioritizes core functionalities such as maintaining clean design and nimble experience, aligning with the increasing trend of digital transformation, granting greater college management autonomy. The application not only brings down the complexities prevailing in the existing college administration but also helps the higher education and placement processes alike, by leveraging key concepts like Data Analysis, Machine Learning and Artificial Intelligence from the data and insights stored, thereby adopting agile college management practices and emphasizing rapid digital growth, contributing to the entire education community. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

An On-Call Shift for Anaesthetist Rostering Problem (ARP): A Mathematical Model 5

An On-Call Shift for Anaesthetist Rostering Problem (ARP): A...

引用

5th IEEE International Conference on Artificial Intelligence in Engineering and technology, IICAIET 2023

作者： Abdullah, Norizal Ayob, Masri Sabar, Nasser R. Lam, Meng Chun Yong, Liu Chian Data Mining and Optimisation Lab Faculty of Information Science and Technology Ukm Bangi Selangor 43600 Malaysia La Trobe University Department of Computer Science and Information Technology Melbourne Australia Faculty of Information Science Ukm Bangi Selangor 43600 Malaysia Ukm Medical Centre Department of Anaesthesiology & Intensive Care Jalan Yaacob Latiff Bandar Tun Razak Cheras Kuala Lumpur56000 Malaysia

ISBN: (纸本)9798350304152

This work dealt with a real-world Anaesthetist Rostering Problem (ARP) for an on-call shift. An on-call shift for an anaesthetist had already been resolved under the physician's rostering problem. However, in their work, each individual can be assigned to only one place throughout the daily on-call shift. In addition, no consecutive days are rostered for the on-call shift, and each level of preference for the on-call shift is excluded from the study. This scenario is irrelevant to the real-world ARP of an on-call shift at Hospital Canselor Tuanku Muhriz (HCTM) in Malaysia, as an anaesthetist is rostered for multiple places of the on-call shifts daily. Also, they can be rostered on consecutive days for on-call shifts, and each anaesthetist will be rostered depending on their preference level for the on-call shift. Therefore, this work proposes a new mathematical formulation with constraints, parameters, and an evaluation function. We utilise Mixed-integer programming to formulate and solve the model with IBM ILOG CPLEX Optimization Studio. The quality of the solution generated by our model is measured using our proposed evaluation function to minimise the violation of constraints. A case study of real-world data from the HCTM was run and tested to validate the model. The result shows that a new model can produce a better optimal solution, whilst the current solution methodology at HCTM is unable to do. © 2023 IEEE.

关键词： Integer programming

来源：评论

学校读者我要写书评

暂无评论

Uncertainty-Aware Gait-Based Age Estimation and its Applications

IEEE Transactions on Biometrics, Behavior, and Identity Scie...

引用

IEEE Transactions on Biometrics, Behavior, and Identity science 2021年第4期3卷 479-494页

作者： Xu, Chi Sakata, Atsuya Makihara, Yasushi Takemura, Noriko Muramatsu, Daigo Yagi, Yasushi Lu, Jianfeng Institute of Scientific and Industrial Research Osaka University Ibaraki Japan Department of Computer and Information Science Faculty of Science and Technology Seikei University Musashino Japan School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

Gait-based age estimation is a key technique for many applications. It is well known that age estimation uncertainty is highly dependent on age (i.e., small for children and large for adults), and it is important to know the uncertainty for the above-mentioned applications. Therefore, we propose a method for uncertainty-aware gait-based age estimation by introducing a label distribution learning framework. Specifically, we design a network that takes an appearance-based gait feature as input and outputs discrete label distributions in the integer age domain. We then train the network to minimize a loss function, which is defined as the dissimilarity between the estimated age distribution and the ground-truth age distribution, in addition to the conventional mean absolute error for the estimated age. Additionally, we demonstrate that uncertainty-aware gait-based age estimation is beneficial for two applications: person search by age query and people counting by age group. Experiments on the world's largest gait database, OULP-Age, demonstrated that the proposed method can successfully represent age estimation uncertainty, and outperforms or is comparable with state-of-the-art methods in terms of age estimation accuracy. Moreover, we demonstrated the effectiveness of the uncertainty-aware framework in applications to person search and people counting through experiments on the database. © 2019 IEEE.

关键词： Query processing

来源：评论

学校读者我要写书评

暂无评论

Online searching trend on Covid-19 using Google trend: infodemiological study in Malaysia

引用

International Journal of information technology (Singapore) 2022年第2期14卷 675-680页

作者： Izhar, Tengku Adil Tengku Torabi, Torab Faculty of Information Management Universiti Teknologi MARA (UiTM) UiTM Selangor Shah Alam Malaysia Department of Computer Science and Information Technology La Trobe University Melbourne Australia

Since January 2020, the emergence of Covid-19 has sparked a worldwide search for information about Covid-19. People frequently use the internet to search the information on the virus. However, the pandemic have triggered the information-seeking trends among public. As a result, large amount of information could lead to infodemic. It will create public concerned such as panic and paranoid because this information spread rapidly. The aim of this study is to analyze information about Covid-19 that has been searched in Malaysia. We investigated online search behavior related to the Covid-19 outbreak among public by using Google Trends to understand public searching behavior on Covid-19. The findings from this study can be used as a tool to monitor public searching activities on Covid-19, which could predict future action regarding the outbreak. © 2021, Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Covid-19 Google trend Infodemic Infodemiological Searching behavior

来源：评论

学校读者我要写书评

暂无评论

Energy efficient indoor localisation for narrowband internet of things

引用

CAAI Transactions on Intelligence technology 2023年第4期8卷 1150-1163页

作者： Ismail Keshta Mukesh Soni Mohammed Wasim Bhatt Azeem Irshad Ali Rizwan Shakir Khan Renato RMaaliw III Arsalan Muhammad Soomar Mohammad Shabaz Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia Department of CSE University Centre for Research and Development Chandigarh UniversityMohaliPunjabIndia Department of Computer Science and Engineering National Institute of TechnologySrinagarIndia Asghar Mall College Rawalpindi Higher Education Department(HED)Govt.of the PunjabRawalpindiPakistan Department of Industrial Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)RiyadhSaudi Arabia College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Automation Electronics and Electrical EngineeringGdansk University of TechnologyGdańskPoland Arba Minch University Arba MinchEthiopia

There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these *** maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a *** on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot *** a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is *** investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT *** current work primarily considers the NOMA Narrow Band IoT network under a single EH ***,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance *** simulation,the proposed approach is successfully *** improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%.

关键词： artificial inteligence detection of moving objects internet of things

来源：评论

学校读者我要写书评

暂无评论

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

引用

computer systems science & Engineering 2023年第5期45卷 1129-1143页

作者： Anwer Mustafa Hilal Eatedal Alabdulkreem Jaber S.Alzahrani Majdy M.Eltahir Mohamed I.Eldesouki Ishfaq Yaseen Abdelwahed Motwakel Radwa Marzouk Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Mathematics Faculty of ScienceCairo UniversityGiza12613Egypt

Biomedical image processing is widely utilized for disease detection and classification of biomedical *** color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and *** removing the qualitative aspect,tongue images are quantitatively inspected,proposing a novel disease classification model in an automated way is *** article introduces a novel political optimizer with deep learning enabled tongue color image analysis(PODL-TCIA)*** presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the *** attain this,the PODL-TCIA model initially performs image pre-processing to enhance medical image *** by,Inception with ResNet-v2 model is employed for feature ***,political optimizer(PO)with twin support vector machine(TSVM)model is exploited for image classification process,shows the novelty of the *** design of PO algorithm assists in the optimal parameter selection of the TSVM *** ensuring the enhanced outcomes of the PODL-TCIA model,a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.

关键词： Tongue color image analysis political optimizer twin support vector machine inception model deep learning

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：