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Examining Spurious information through Text Categorization Methods

Examining Spurious Information through Text Categorization M...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Watcharin Warinthaksa Worawut Yimyam Mahasak Ketcham Thittaporn Ganokratanaa Thidarat Pinthong Rajamangala University Of Technology Rattanakosin Nakhonprathom Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Dep. of Management Information System King Mongkut’s University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut’s University of Technology Thonburi Bangkok Thailand

ISBN: (数字)9798350370096

ISBN: (纸本)9798350370102

In recent years, deceptive content such as fake news and fake reviews, also known as opinion spams, have increasingly become a dangerous prospect for online users. Fake reviews have affected consumers and stores alike. Furthermore, the problem of fake news has gained attention in 2016, especially in the aftermath of the last U.S. presidential elections. Fake reviews and fake news are a closely related phenomenon as both consist of writing and spreading false information or beliefs. The opinion spam problem was formulated for the first time a few years ago, but it has quickly become a growing research area due to the abundance of user‐generated content. It is now easy for anyone to either write fake reviews or write fake news on the web. The biggest challenge is the lack of an efficient way to tell the difference between a real review and a fake one; even humans are often unable to tell the difference. In this paper, we introduce a new n‐gram model to detect automatically fake contents with a particular focus on fake reviews and fake news.

关键词： Training Technological innovation Social networking (online) Voting Unsolicited e-mail User-generated content Text categorization

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Integrating System Dynamics and Random Forest Algorithm for Sales Forecasting

Integrating System Dynamics and Random Forest Algorithm for ...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Natalia Magdalena Rafu Mamulak Erma Suryani Jerry Dwi Trijoyo Purnomo Doctoral Program in Technology Management Interdisciplinary School of Management and Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Statistics Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350365191

ISBN: (纸本)9798350365207

This study proposes an approach to improve sales forecasting accuracy by integrating System Dynamics (SD) modeling with the Random Forest (RF) algorithm. The combination of these two methods offers a promising way to make sales predictions more reliable, especially in uncertain market conditions. Using SD principles within the RF algorithm helps us simulate expected sales growth, gain insights into market dynamics, and make our forecasting model more understandable to stakeholders. This study using synthetic sales data shows that the integrated approach is offered as an open idea and customizable, particularly in scenarios with dynamic growth patterns and feedback effects.

关键词： Radio frequency System dynamics Heuristic algorithms Predictive models Prediction algorithms Market research Stakeholders Reliability Forecasting Random forests

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ATT&CKViz: Enhancing Cybersecurity Insights by Visual Analytics of Attack Patterns

ATT&CKViz: Enhancing Cybersecurity Insights by Visual Analyt...

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Engineering & Computing Technologies (ICECT), International Conference on

作者： Inbasat Fiza Fizza Khurshid Manahil Fatima Umara Noor Zahid Rashid Department of Software Engineering Faculty of Computing and Information Technology International Islamic University Islamabad Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul South Korea

ISBN: (数字)9798350349719

ISBN: (纸本)9798350349726

The ATT&CK MITRE framework serves as an expansive repository of adversary tactics, techniques, and procedures. Given the sheer volume of these intricate attack patterns, the conventional manual navigation method proves to be time-intensive and less efficient for security analysts. As a remedy, there arises a compelling necessity to present the rich content encapsulated within the ATT&CK MITRE repository through interactive visualizations. In this paper ATT&CKViz an interactive web-based cyber-attack patterns visualization tool is presented that aims to empower security analysts with the ability to effortlessly explore the repository from diverse angles, which facilitates deep insights into cyber threats. The aim is to understand cyber threat efficiently with a timely response. The empirical evaluations depict that effectiveness and user-friendliness of ATT&CKViz.

关键词： Computers Navigation Visual analytics Manuals Cyberattack

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Exploring Regression and Classification in Big Data with Deep Learning

Exploring Regression and Classification in Big Data with Dee...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Ravindra Pandey Aruna Sri Rongali S. Gopinath Nilesh Anute Forda Nama Sachin Pund Department - Management Hult International Business School Doctoral Information Technology/Information Technology Emphasis/Information Technology University of The Cumberlands US Department of Electronics And Communication Engineering Karpagam Institute of Technology Coimbatore Management ASM's Institute of Business Management and Research Pune Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets.

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Usability Evaluation of Communication Tools Used as Remote Support in Machine Service Industry: A Comparison between Microsoft Teams and Skype 23

Usability Evaluation of Communication Tools Used as Remote S...

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6th International Conference on Computers in management and Business, ICCMB 2023

作者： Flame, Roland Ross F. Prasetyo, Yogi Tri Nadlifatin, Reny Ayuwati, Irene Dyah Persada, Satria Fadil Chuenyindee, Thanatorn School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Rd. Chung-Li32003 Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia Faculty of Business and Information Technology Institut Teknologi Telkom Surabaya Surabaya Indonesia Entrepreneurship Department Binus Business School Undergraduate Program Bina Nusantara University Indonesia Department of Industrial Engineering and Aviation Management Navaminda Kasatriyadhiraj Royal Air Force Academy Bangkok10220 Thailand

ISBN: (纸本)9781450398046

Due to pandemic Covid-19, there is an increase and rough transition into remote work. Communication tools/platforms are softwares used by industries to facilitate different functionalities like remote technical support and communication. Especially for service industries, coordinators and engineers adapted on using these tools to support internal and external communications. For a certain machine service company, Skype and Microsoft Teams are the main communication tools used. The objective of this study is to determine the usability/user experience of these tools of engineers and coordinators on their daily activities. System Usability Scale were used to evaluate their user experience. As interpreted using the Curved Grading Scale, only the use of Microsoft Teams of Coordinators is graded as D, and the rest are graded as F. Based on the results on the user experience of coordinators and engineers using platforms Microsoft Teams and Skype, the low scores show that they are struggling with the usability of these tools due to drastic change and adaptability and limitation of activities that these tools can only perform. © 2023 ACM.

关键词： Engineers

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The Analysis of Online Order Mobile Application Using User Experience Questionnaire (A Case Study Approach) 7

The Analysis of Online Order Mobile Application Using User E...

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7th International Conference on information management and technology, ICIMTech 2022

作者： Hartono, Sugiarto Shahudin, Faizah Widagdo, Hermawan Honggo Hendrawan, Tommy School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Economics and Management Xiamen University Malaysia Selangor Malaysia Faculty of Science & Technology Information System Study Program Universitas Nasional Karangturi Semarang50227 Indonesia PT. Elgibor Solusi Digital Semarang50167 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

ABC Application is owned by ABC Company which already has branches of more than 100 stores in 7 countries where Indonesia is one of the branches with 79 stores spread across several cities, especially Jabodetabek area. ABC has launched an application that has been operating for more than a year;because the ABC application is new to the food and beverage sector, the application has received several positive and negative responses from its users especially on its user experience. Based on this background, this research will more focus on user experience of ABC Application. ABC Application can find out the assessment of user experience and improve the results of any negative responses in the form of criticism or suggestions from users. The method used in this research is the User Experience Questionnaire (UEQ). From the research results that have been carried out, the novelty scale is the scale with the lowest attachment of all respondents. Therefore, improving and developing the ABC application through this scale is necessary. © 2022 IEEE.

关键词： Surveys

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Intelligent IoT-enabled Ankle Brace: Enhancing Mobility and Safety

Intelligent IoT-enabled Ankle Brace: Enhancing Mobility and ...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Thittaporn Ganokratanaa Patiyuth Pramkeaw Mahasak Ketcham Yanisa Khamphao Putanet Wanthanasak Dept. of Mathematics King Mongkut’s University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut’s University of Technology Thonburi Bangkok Thailand Dept. of Information Technology Management King Mongkut’s University of Technology North Bangkok

ISBN: (数字)9798350370096

ISBN: (纸本)9798350370102

This research focuses on the development of a footworn device to assist individuals with limited mobility in walking. The device aims to reduce the risk of accidents by closely monitoring the wearer's movements and detecting potential hazards. It incorporates sensors, including the MPU6050 gyro sensor and KY-031 vibration sensor, to track the wearer's walking behavior. In case of abnormalities, such as falls, the device triggers an auditory alert and notifies the caregiver via LINE Notify. The system is controlled by the Node MCU ESP8266, enabling seamless integration with the Internet of Things (IoT). The objective of this study is to design an IoT system for medical assistance. The researchers created a prototype of a smart ankle device capable of detecting falls and sending notifications to the user's smartphone. The effectiveness of the notification system was evaluated using the Line Notify application. Results demonstrated a successful detection of falls in 48 out of 50 trials, with two instances of false alarms during normal walking. The overall efficiency of the smart ankle device was 98%. In summary, the proposed smart ankle device demonstrates promising potential for various applications in fall detection and safety alert systems. Further improvements and collaborations with healthcare experts are recommended to enhance its performance and make it commercially viable. The device's connectivity and responsiveness to IoT systems are vital aspects to be considered. Future research should aim to develop additional features in collaboration with physiotherapists and healthcare professionals to meet user requirements. The device holds significant benefits in terms of fall detection and safety alerts, and efforts should be made to enhance its durability, robustness, and commercialization prospects.

关键词： Legged locomotion Vibrations Collaboration Prototypes Medical services Robustness Internet of Things

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Integrating FMCW Radar and RGBD Sensor for Vital Sign Detection

Integrating FMCW Radar and RGBD Sensor for Vital Sign Detect...

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IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)

作者： Sheng-Hsien Hsieh Yuh-Jiuan Tsay Yu-Wei Chen Ya-Yun Huang Yu-Xuan Yu Program of Artificial Intelligence and Mechatronics National Pingtung University of Science and Technology Pingtung Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Pingtung Taiwan

The purpose of this study is to address the issue of a shortage of caregivers for the elderly in an aging society. Elderly individuals living alone at home may experience various sudden health issues such as falls and emergencies. However, healthcare professionals may not have access to the individuals at that moment. Having access to real-time data can assist medical professionals in making more informed decisions about the patient's conditions. Thus, using FMCW millimeter-wave radar, we track the vital signs of individuals through a non-contact method in point clouds. Additionally, RGB cameras and the human pose estimation tool, OpenPose, are used to monitor and analyze motions and activities in public spaces, detecting special events such as falls and fainting and issuing alerts for immediate rescue to minimize further harm. This approach facilitates the exchange of information between medical professionals and patients, thereby reducing the likelihood of unfortunate incidents and improving patient outcomes.

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification 19

Deep Learning in Smart Healthcare: A GAN-based Approach for ...

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19th International Conference on Future Networks and Communications, FNC 2024 / 21st International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2024 / 14th International Conference on Sustainable Energy information technology, SEIT 2024

作者： Tufail, Hina Ahad, Abdul Puspitasari, Ira Shayea, Ibraheem Coelho, Paulo Jorge Pires, Ivan Miguel Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga Indonesia School of Software Northwestern Polytechnical University Shaanxi Xian China Turkey Polytechnic University of Leiria Leiria Portugal Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which affects patients' lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD. © 2024 The Authors. Published by Elsevier B.V.

关键词： Generative adversarial networks

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A Social Analysis of Thailand's 2023 Election Through Twitter Feeds

A Social Analysis of Thailand's 2023 Election Through Twitte...

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International Conference on information technology and Electrical Engineering (ICITEE)

作者： Wanaporn Sarapugdi Songphon Namkhun Program in Management of Digital Innovation Faculty of Information Technology Rajabhat Mahasarakham University Maha Sarakham Thailand Program in Computer Engineering Faculty of Engineering Rajabhat Mahasarakham University Maha Sarakham Thailand

Nowadays, it cannot be denied that social media has been in many parts of people's lives, especially in entertainment, business and education. Public figures including politicians frequently use social platforms to connect with their audience, for example Facebook, Instagram, Tiktok and etc. One of the most commonly used is a platform called Twitter or also known as X. It is a platform that people can share their opinions in short messages. Since there is an alphabet limitation, people can deliver and receive message rapidly. It is a perfect platform that we could use to update the real-time situations for example election, emergency alert, natural disasters and etc. According to its characteristic, it can be used as a data source for social media analytics, which involves collecting and analyzing data to perform business decisions. The social media analytics has become commonplace because the number of people using social media tends to increase every second. Specifically, Twitter sentiment analysis offers a quick and inexpensive tool for monitoring and predictions. In this work, Twitter is used as a data source to monitor and predict Thailand Election in 2023 because this election highly attracts attention from Thais and international. Moreover, Twitter is a significant platform that is used to debate about political events in Thailand. The result of this election potentially indicates Thailand's future, including economics, public health, environment, international relations and etc. Our work performs sentiment analysis to categorize the data and mainly focuses on extracting sentiment from text without considering semantic word relations and co-occurrences because it is appropriate and functional for Thai sentence analysis. Based on the result, it can be seen that Twitter plays a significant role in politics, with politicians wielding considerable influence over public perception. Comparing of the actual election result and the predicted result, this analysis dem

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