检索结果-内蒙古大学图书馆

1st Mohammad Ali Jinnah University International Conference on Computing, MAJICC 2021

作者： Nadeem, Adnan Rizwan, Kashif Mehmood, Amir Qadeer, Nauman Noor, Fazal Alzahrani, Ali Islamic University of Madinah Faculty of Computer and Information System Madinah Saudi Arabia Federal Urdu University of Arts Science and Technology Department of Computer Science Islamabad Pakistan Muhammad Ali Jinnah University Department of Computer Science Karachi Pakistan

ISBN: (纸本)9781665424134

Ensuring the safety of residents and visitors is one of the major priorities of the Kingdom of Saudi Arabia (KSA). There are some residents in Madinah who are vulnerable or prone to getting lost in crowded areas, including children, the elderly, and people with certain diseases and disorders. Besides, the Kingdom receives millions of visiting pilgrims in Madinah and Makkah and thousands of them get lost every year around Masjid-e-Nabavi and Masjid Al Haram. Considering the importance of the safety of residents and visiting pilgrims in Madinah, in this paper, we propose a smart city application design for tracking and locating the missing person using an emerging Internet of Things (IoT) based system. We propose to evaluate the performance of Bluetooth low energy (BLE), low power wide area network (LPWAN), technologies, both individually and as a hybrid solution. We propose an IoT based system with a proactive approach to help security officials in Madinah and the department of lost and found in Masjid e Nabavi in two major safety issues: 1) Tracking the companion of missing person found by a security official and 2) Tracking the missing person using reported location via IoT based system. We present our proposed smart city application design and its implementation scenarios in Madinah. © 2021 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Expectation-Confirmation Model (ECM) to See Satisfaction and Continued Intention of e-Learning (“Cyber”)

Expectation-Confirmation Model (ECM) to See Satisfaction and...

引用

International Conference on information Technology (INCIT)

作者： Fx Hendra Prasetya Bernardinus Harnadi Albertus Dwiyoga Widiantoro Andre Kurniawan Pamudji Department of Information System Faculty Computer Science Soegijapranata Catholic University Semarang Indonesia

The Expectation-Confirmation Model (ECM) has been widely used to test technology adoption by many researchers. This study aims to examine the ECM used for e-learning used at Soegijapranata Catholic University Semarang. The respondents used in this study were Soegijapranata Catholic University students from various study programs, both D3, Sl, S2, and S3. The methodology used in this study is to distribute questionnaires to cyber user respondents at Soegijapranata Catholic University, then test the data with statistical tests using Smar PLS, the expected results are models that are compiled based on hypotheses from literature studies as expected. Based on the hypothesis test, it turns out that all the hypotheses that have been prepared can be accepted because all P Value prices are below 5% or 0.05. The results of this study turned out to be a correlation between cyber user satisfaction on the sustainability of cyber use in the future.

关键词： Electronic learning Correlation Data models Sustainable development information technology

来源：评论

学校读者我要写书评

暂无评论

Opportunities and Conditions in Education on Blockchain Gamification Technology

Opportunities and Conditions in Education on Blockchain Gami...

引用

2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Tjahjono, Budi Soleman, Muhammad Dede Azmi, Aulia Millah, Shofiyul Andriani, Riri Dewi, Elisa Royani Esa Unggul University Computer Science Faculty Tangerang Indonesia University of Raharja Webcenter Sentra Solusindo Ltd. Tangerang Indonesia University of Raharja Department of Science and Technology Tangerang Indonesia University of Raharja Department of Information System Tangerang Indonesia

ISBN: (纸本)9781665468763

In this disruptive 4.0 era, many generations are competing in creating a new innovation, it makes technological growth increase sharply, one of which is blockchain technology. This technology has ledgers that are simultaneously decentralized and distributed. There is a node that functions to record all transaction histories on the Blockchain with all different networks. Blockchain This is certainly a very practical and safe technology for the world of education, one of which is Gamification. Gamification itself means a concept that has layers of features like a game that is connected or integrated with the blockchain. Gamification provides opportunities for the world of education by creating game elements that focus on the orientation of creating new educational spaces. This study uses the analisis Gamifikasi method and SWOT analysis to determine the overall use of the system starting from the strategies, opportunities, strengths and weaknesses. With this research, it is hoped that gamification in the blockchain system can run optimally in improving the implementation of Blockchain technology in the world of education. The novelty of this research is to apply a concept that has a feature layer such as a game that is connected or integrated with a block chain. © 2022 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Decentralized Electronic Vote Based on Blockchain P2P 9

Decentralized Electronic Vote Based on Blockchain P2P

引用

9th International Conference on Cyber and IT Service Management, CITSM 2021

作者： Widayanti, Riya Aini, Qurotul Haryani, Hendriyati Lutfiani, Ninda Apriliasari, Dwi University of Esa Unggul Computer Science Faculty Department Indonesia University of Raharja Information System Department Indonesia University of Raharja Accounting Department Indonesia University of Raharja Department of Information System Indonesia

ISBN: (纸本)9781665435482

Voting has become one of the methods used by humans to determine decisions in a matter. As technology has developed, conventional Voting has also followed the transformation in the adaptation of today's digital age. There is an electronic version of this Voting, often referred to as e-voting (electronic Voting). Of course, the application of technology in Voting will lead to public opinion about concerns about maintaining network privacy and security in e-voting. Security problems can be overcome with technology that is currently being maximally utilized in various fields of life, namely blockchain technology. In improving the security of e-voting, Blockchain is used in P2P networks. Implementing the blockchain system in e-voting will result in a secure e-voting system to reduce the percentage of vote forgery in the e-voting system. Implementing a blockchain-based e-voting system will involve cryptography, software engineering theory, and voting theory. In realizing blockchain-based e-voting, several stages are required. (1) Counterfeit votes avoid adjusting the voting record model based on ledger technology, (2) in terms of authentication. The technology complemented by designing a user model based on Elliptic Curve Cryptography (ECC), (3) providing a model designed for voters to change their votes before the time limit specified. The implementation of Blockchain in this e-voting system is transparent with the existence of a blockchain system that provides notifications to all nodes to approve an incoming vote data. With this transparency, it can reduce fraud and the election of leaders according to people's choices. © 2021 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

The Role of the Internet of Things in Monitoring Air Pollution-A Survey

The Role of the Internet of Things in Monitoring Air Polluti...

引用

International Conference on information Technology (ICIT)

作者： Ahmad Abusukhon Bareeq Alghannam Computer Science Dep. Faculty of Science and Information Technology Al-Zaytoonah University of Jordan Amman Jordan Department of Computer Science and Information System College of Business Studies The Public Authority for Applied Education and Training Kuwait City Kuwait

Air pollution is one of the most common problems that the world is facing today. In fact, there are numerous causes of air pollution, including the large number of industries and automobiles that emit carbon dioxide (CO2) and carbon monoxide. Pollution is increasing on a daily basis, making air quality monitoring and management a major challenge for governments in both developed and developing countries. Air pollution affects human health as well as the atmosphere, causing climate change. One of the techniques used for monitoring air pollution is the Internet of Things (IoT). In this paper, we demonstrate various techniques for monitoring air quality using IoT and make a comparison based on various factors elicited from the previous work.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Weighted Mask Recurrent-Convolutional Neural Network based Plant Disease Detection using Leaf Images 7

Weighted Mask Recurrent-Convolutional Neural Network based P...

引用

7th International Conference on Intelligent Computing and Control systems, ICICCS 2023

作者： Sharmila, R. Kamalitta, R. Moorthy Singh, Devesh Pratap Chauhan, Amit Acharjee, Purnendu Bikash Dhanalakshmi Srinivasan Engineering College Department of MCA Tamilnadu Perambalur India Information Technology K.Ramakrishnan College of Engineering Tamilnadu Trichy India Electronics Engineer Production Dhaksha Unmanned System Pvt Ltd Tamilnadu Chennai India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttrakhand Dehradun India Department of Life Sciences Karnataka Bengaluru India CHRIST University Faculty Member Computer Science Maharashtra Pune India

ISBN: (纸本)9798350397253

Large losses in output, money, and quality/quantity of agricultural goods are incurred due to plant diseases. Seventy percent of India's GDP is tied to the agricultural sector, thus protecting plants from diseases is crucial. For this reason, it is important to keep an eye on plants from the moment they sprout. The usual approach for this omission is naked eye inspection, which is more time-consuming, costly, and requires significant skill. Thus, automating the method for detecting diseases is necessary to speed up this process. It is imperative that image processing methods be used in the creation of the illness detection system. Disease detection involves a number of processes, including Weighted Mask R-CNN, GLCM feature extraction, Multi-thresholding image pre-processing, and K means image segmentation classification. The weighted Mask R-CNN outperforms the standard RNN, the Mask R-CNN, and the CNN in terms of accuracy and recall in analytical trials by a significant margin. © 2023 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Streamflow Prediction in the Mekong River Basin Using Deep Neural Networks

引用

IEEE Access 2023年 11卷 97930-97943页

作者： Nguyen, Thi-Thu-Ha Vu, Duc-Quang Mai, Son T. Dang, Thanh Duc National Taiwan University Department of Bioenvironmental Systems Engineering Taipei10617 Taiwan National Central University Department of Computer Science and Information System Taoyuan320317 Taiwan Thai Nguyen University of Education Thai Nguyen250000 Viet Nam Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Institute for Computational Science and Artificial Intelligence Van Lang University Laboratory of Environmental Sciences and Climate Change Ho Chi Minh City70000 Viet Nam Van Lang University Faculty of Environment Ho Chi Minh City70000 Viet Nam

In recent years, the Mekong River Basin (MRB), one of the largest river basins in Southeast Asia, has experienced severe impacts from extreme droughts and floods. Streamflow forecasting has become crucial for effective risk management strategies in the region. However, this task presents significant challenges due to rapid climate changes and the presence of numerous newly constructed upstream dams, which disrupt the natural flow. In this paper, we develop multiple deep learning models (incl. Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long short-term Memory (LSTM), and Transformer) to predict streamflow with different lead time forecasts based on observed meteorological variables and climatic indices (i.e., discharge, water level, precipitation, and temperature) from 1979 to 2019. The results indicate that LSTM obtains high performance for streamflow prediction in both dry and wet seasons while Transformer is not recommended for long-term prediction, especially in the dry season. The proposed deep learning models capture well the fluctuation of river flow in the MRB during the period of high-dam development, especially LSTM (NSE ≥ 0.8). The models' performances are enhanced with the adding of temperature for short-term prediction while precipitation was the most sensitive variable for long-term one. Such proposed models are essential for government agencies to plan mitigation and adaptation strategies at different periods, which can range from days to years. © 2013 IEEE.

关键词： Floods

来源：评论

学校读者我要写书评

暂无评论

Two-Layer SVM, Towards Deep Statistical Learning 1

Two-Layer SVM, Towards Deep Statistical Learning

引用

1st International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2022

作者： Kazemi, Alireza Boostani, Reza Odeh, Mahmoud Al-Mousa, Mohammad Rasmi Shiraz University Shiraz Faculty of Science Mathematics Department Fars Iran Electrical and Computer Engineering School Shiraz University Shiraz CSEandIT Dept. Fars Iran Zarqa University Department of Management Information System Jordan Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan

ISBN: (纸本)9798350332742

Support Vector Machine (SVM) is originally a binary large-margin classifier emerged from the concept of structural risk minimization. Multiple solutions such as one-versus-one and one-versus-all have been proposed for creating multi-class SVM using elementary binary SVMs. Also multiple solutions have been proposed for SVM model selection, adjusting margin-parameter C and the Gaussian kernel variance. Here, an improved classifier named SVM-SVM is proposed for multi-class problems which increases accuracy and decreases dependency to margin-parameter selection. SVM-SVM adopts two K-class one-vs-one SVMs in a cascaded two-layer structure. In the first layer, input features are fed to one-vs-one SVM with non-linear kernels. We introduce this layer as a large-margin non-linear feature transform that maps input feature space to a discriminative K(K-1)/2 dimensional space. To assess our hierarchical classifier, some datasets from the UCI repository are evaluated. Standard one-vs-one SVM and one-vs-one fuzzy SVM are used as reference classifiers in experiments. Results show significant improvements of our proposed method in terms of test accuracy and robustness to the model (margin and kernel) parameters in comparison with the reference classifiers. Our observations suggest that a multi-layer (deep) SVM structures can gain the same benefits as is seen in the deep neural nets (DNNs). © 2022 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Implementing a Model-Based Approach for Digital Health Adoption Model Development

Implementing a Model-Based Approach for Digital Health Adopt...

引用

International Conference on Informatics, multimedia, Cyber and information system (ICIMCIS)

作者： Puji Rahayu Saruni Dwiasnati Normala Rahim Ipung Dwi Ari Saputra Farhan Ranadhan Information System Department Faculty of Computer Science Universitas Mercu Buana Jakarta Indonesia Informatic Department Faculty of Computer Science Universitas Mercu Buana Jakarta Indonesia Fakulti Informatik Dan Komputeran Universiti Sultan Zainal Abidin Malaysia

The purpose of this study is to create a digital health adoption model based on parameters that have been found in previous studies, using the Model Development Engineering (MDE) method. This method is used to overcome the challenges of the Covid-19 pandemic in validating the model design to be implemented. One of the main advantages of the Model Development Engineering (MDE) approach is that all models produced are formal extensions of the Unified Modeling Language (UML). MDE is a system used to build a framework for organizing, planning, and controlling the information systems development process. In the verification stage of the Digital Health model, the presentation stage is adopted which involves two approaches, namely the design approach and the system approach. The design approach adopts Model Driven Engineering (MDE), which is used in the development of system architecture. The results of this study are the model designs used to adjust validation in developing digital health models using the Model Development Engineering technique.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MELex: The Construction of Malay-English Sentiment Lexicon

引用

computers, Materials & Continua 2022年第4期71卷 1789-1805页

作者： Nurul Husna Mahadzir Mohd Faizal Omar Mohd Nasrun Mohd Nawi Anas ASalameh Kasmaruddin Che Hussin Abid Sohail Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA(UiTM)Kedah08400MerbokKedahMalaysia Department of Decision Sciences School of Quantitative SciencesUniversiti Utara Malaysia06010KedahMalaysia Disaster Management of Institute School of Technology Management and LogisticUniversiti Utara Malaysia06010KedahMalaysia Department of Management Information System College of Business AdministrationPrince Sattam Bin Abdulaziz University165Al-KharjSaudi Arabia Faculty of Entrepreneurship and Business Universiti Malaysia KelantanMalaysia Department of Computer Science COMSATS University IslamabadLahorePakistan

Currently,the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment ***,this issue is addressed in this paper in order to enhance the accuracy of sentiment *** this study,a new lexicon for sentiment analysis is constructed.A detailed review of existing approaches has been conducted,and a new bilingual sentiment lexicon known as MELex(Malay-English Lexicon)has been *** MELex involves three activities:seed words selection,polarity assignment,and synonym *** approach differs from previous works in that MELex can analyze text for the two most widely used languages in Malaysia,Malay,and English,with the accuracy achieved,is 90%.It is evaluated based on the experimentation and case study approaches where the affordable housing projects in Malaysia are selected as case *** finding has given an implication on the ability of MELex to analyze public sentiments in the Malaysian *** novel aspects of this paper are ***,it introduces the new technique in assigning the polarity score,and second,it improves the performance over the classification of mixed language content.

关键词： Machine learning data sciences artificial intelligence opinion mining sentiment analysis sentiment lexicon lexicon-based bilingual lexicon

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：