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Proposal to Improve Exercise Using the Fogg Behavior Model

Proposal to Improve Exercise Using the Fogg Behavior Model

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Yuasa, Tomoya Harada, Fumiko Shimakawa, Hiromitsu Graduate School of Information Science and Engineering Ritsumeikan University Shiga Japan Ritsumeikan University Research Organization of Science and Technology Shiga Japan

ISBN: (纸本)9781665453059

This paper proposes an exercise improvement method utilizing the Fogg Behavior Model (FBM). FBM asserts that three elements, motivation, ability, and triggers, must be satisfied in order to persuade persons to do something. Existing works mainly value motivation. Many methods have been studied to increase user motivation utilizing behavioral economics, such as sending text messages to recipients. On the other hand, few studies have focused on ability and trigger. This method utilizes FBM to realize exercise improvement, taking all three factors into account. The proposed method examines the time-series data of the number of steps the target user takes, which represents the user's physical activity. It regards the user's ability high in the time period when the user's physical activity is high. At the timing, its triggers are given according to the user's Motivation. This enables us to promote exercises to users, having arranged an environment to facilitate users to make exercises. This paper explains a challenge that estimates a user's motivation for exercise from data acquired from a wearable device. © 2022 ieee.

关键词： Motivation

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Interpretable machine learning-based terrorist attack success rate prediction

Interpretable machine learning-based terrorist attack succes...

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Luo, Lanjun Li, Boxiao Wang, Xueyan Cui, Lei Liu, Gang School of Management North Sichuan Medical College Nanehong China School of Management Huazhong University of Science and Technology Wuhan China Information Centre Affiliated Hospital of North Sichuan Medical College Nanchong China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781665453059

The success of terrorist attacks reflects the capability of terrorists and the vulnerability of the security defense, explainable prediction of the average attack success rate at the country-annual level is crucial for governments. In this study, terrorist attack data from 146 countries between 2002 to 2020 was obtained from the global terrorism database (GTD), and a two-stage prediction task was conducted. First, multiple machine learning models, including XGBoost and Random Forest (RF), are used to predict the average success rate of terrorist attacks in the next year, considering terrorism root factors and statistical results from the previous year. The results show that the RF model performs the best. Second, the prediction outputs of the RF model are explained using interpretable methods, including Accumulate Local Effect (ALE) and SHapley Additive exPlanation (SHAP), to provide counterterrorism insights applicable to countries around the world. © 2022 ieee.

关键词： Terrorism

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Messages for Improvement of walking amount based on a stage of change

Messages for Improvement of walking amount based on a stage ...

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Kataoka, Rintaro Shimakawa, Hiromitsu Harada, Fumiko Graduate School of Information Science and Engineering Ritsumeikan University Shiga Japan College of Information Science and Engineering Ritsumeikan University Shiga Japan Ritsumeikan University Research Organization of Science and Technology Shiga Japan

ISBN: (纸本)9781665453059

Based on the transtheoretical model of how be-havior change occurs, this study proposes a support to in-crease the amount of walking through messages. In recent years, lifestyle-related diseases have been threatening people's life expectancy. Regular exercise can prevent lifestyle-related dis-eases. However, currently one in four adults does not get enough exercise. It is not easy to improve the habit of inactivity, and some kind of intervention is required to promote behavioral change. In the transsexual model, which is a model of behavior change, effective interventions differ depending on the stage of change, the transformation stage. In this study, the stage of change is estimated based on the data of the number of steps taken after the intervention with messages. We examine step count data with and without intervention, and with different types of intervention. Seasonal and exogenous components of the step count data were eliminated by the SARIMAX model. In a 6-week experiment with 14 university students and adults, we found that the intervention of e-mail messages could increase the subjects' motivation to exercise. However, it was not possible to identify the types of effective messages for each stage of change. © 2022 ieee.

关键词： Behavioral research

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OkkhorNet: A Deep Convolutional Neural Network to Classify Bengali Handwritten Characters

OkkhorNet: A Deep Convolutional Neural Network to Classify B...

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Sikder, Shihab Uddin Muslebeen, Md. Shafiul Karim, Dewan Ziaul Saha, Ramkrishna Bushra, Tasfia Anika Brac University Computer Science and Engineering Dhaka Bangladesh Daffodil International University Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665453059

Handwritten letter classification of any given language has the potential to be used in various fields such as literature, educational institutions, digitization of government records etc. Bengali language with its complex sets of mixed characters, poses significant complexities in terms of automatic recognition of characters. In the Bengali character set, there are over 360 distinct characters among which a lot of similarities are present between different characters. Thus, the classification of these characters gets harder as the recognition system incorporates all these distinct characters. In recent years, a lot of research has been done to solve this problem on isolated datasets with significant results. Continuing the advancement in image processing, In this paper, we have proposed a custom CNN model which has been trained on Bangla Lekha Isolated dataset containing 1,66,106 images belong to 84 distinct classes with the capability to detect individual handwritten Bengali letters including digits, vowels, consonants and compound characters. Our proposed model was able to achieve 94.73% accuracy while using less number of parameters compared to existing popular models © 2022 ieee.

关键词： Convolutional neural networks

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BanglaSarc: A dataset for Sarcasm Detection

BanglaSarc: A Dataset for Sarcasm Detection

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Apon, Tasnim Sakib Anan, Ramisa Modhu, Elizabeth Antora Suter, Arjun Sneha, Ifrit Jamal Alam, Md. Golam Rabiul Brac University Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665453059

Being one of the most widely spoken language in the world, the use of Bangla has been increasing in the world of social media as well. Sarcasm is a positive statement or remark with an underlying negative motivation that is extensively employed in today's social media platforms. There has been a significant improvement in sarcasm detection in English over the previous many years, however the situation regarding Bangla sarcasm detection remains unchanged. As a result, it is still difficult to identify sarcasm in bangla, and a lack of high-quality data is a major contributing factor. This article proposes BanglaSarc, a dataset constructed specifically for bangla textual data sarcasm detection. This dataset contains of 5112 comments/status and contents collected from various online social platforms such as Facebook, YouTube, along with a few online blogs. Due to the limited amount of data collection of categorized comments in Bengali, this dataset will aid in the of study identifying sarcasm, recognizing people's emotion, detecting various types of Bengali expressions, and other domains. The dataset is publicly available at https://***/datasets/sakibapon/banglasarc. © 2022 ieee.

关键词： Social networking (online)

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Deep Learning for Real Estate Trading

Deep Learning for Real Estate Trading

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Zhao, Yun Chetty, Girija Tran, Dat University of Canberra Faculty of Science and Technology Australia

ISBN: (纸本)9781665453059

Artificial intelligence (AI) and Machine Learning techniques have been making impact on the real estate industry recently. Increasingly, several real estate companies have started to use a variety of AI techniques to optimize their property business. Ma-chine learning (ML) technology for providing support on real es-tate investment decisions, allows investigation of historical property sales data by computer algorithms to automatically predict house prices. Real estate professionals can leverage sophisticate ML techniques to analyse sales data as benchmarks and make appraisals for their home selling clients and customers. ML technologies not only make predictions or classifications, but also can assistant real estate professionals for investment purposes by providing a trading strategy. In this paper, we propose a novel machine learning model, based on a standard deep reinforcement learning (DRL) model, enhanced with a combination of two popular time series algorithms, the Gramian Angular Field (GAF) and long short-term memory (LSTM) algorithms for providing decision support on real estate trading strategy. Our goal is to explore if the proposed enhanced DRL model can make profitable trading strategy for a long-time investment, such as the real estate markets. © 2022 ieee.

关键词： Sales

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Clustering Algorithms based Noise Identification from Air Pollution Monitoring data

Clustering Algorithms based Noise Identification from Air Po...

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Fang, Xinyi Chong, Chak Fong Yang, Xu Wang, Yapeng Macao Polytechnic University Faculty of Applied Sciences Macao China

ISBN: (纸本)9781665453059

The development of data science has brought about many discussions of noise detection, and so far, there is no universal best method. In this paper, we propose a clustering-algorithm-based solution to identify and remove noise from air pollution data collected with mobile portable sensors. The test dataset is the air pollution data collected by the portable sensors throughout three seasons at the campus in Macao. We have applied and compared six clustering algorithms to identify the most appropriate clustering algorithm to achieve this goal: Simple K-means, Hierarchical Clustering, Cascading K-means, X-means, Expectation Maximization, and Self-Organizing Map. The performance is evaluated by their accuracy and the best number of clusters calculated by the Silhouette Coefficient. Additionally, a classification algorithm J48 tree can extract the key attributes and identify the noise cluster for future unlabeled data that may contain noise. The experiment results indicate that the Expectation Maximization and Cascading Simple K-Means perform the best. Moreover, temperature and carbon dioxide are vital attributes in identifying the noise cluster. © 2022 ieee.

关键词： Air pollution

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A Mathematical Analysis of Discrete Waveform Relaxation Algorithms for Transmission Line Type Circuits

A Mathematical Analysis of Discrete Waveform Relaxation Algo...

引用

8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Al-Khaleel, Mohammad Wu, Shu-Lin Khalifa Univ Sci & Tech Abu Dhabi U Arab Emirates Yarmouk Univ Irbid Jordan Sichuan Univ Sci & Engn Zigong Sichuan Peoples R China

ISBN: (纸本)9781665495523

Convergence rate is greatly improved by using the new waveform relaxation (WR) methods, known as optimized waveform relaxation (OWR) algorithms, over the classical ones due to the new transmission conditions that exchange more information between subsystems when solving in parallel using multi processors. The new transmission conditions include a free parameter whose value should be chosen in an appropriate way in order to get the best convergence result. In all previous work on OWR for transmission line type circuits, the analysis for finding such value of the free parameter was performed at the continuous level in which any impact of the temporal discretization is neglected. However, it is more realistic to perform the analysis at the discrete level for real computations in a computer when solving time dependant problems. Therefore, choosing transmission line type circuits as our model problem, we perform in this paper the analysis for finding the value of the free parameter appears in the transmission conditions at the discrete level and we study the resulting convergence behavior of the discrete OWR algorithm. We focus on revealing the influence of the time discretization parameter Delta t on the convergence rate of the OWR algorithm.

关键词： computer science Analytical models Power transmission lines Program processors conferences Mathematical analysis data engineering

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Implementation of an Automated Result Management System in a Developing Country

Implementation of an Automated Result Management System in a...

引用

2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Nair, Sonam Shivani Sharma, Neeraj Anand School of Science and Technology The University of Fiji Department of Computer Science and Mathematics Lautoka Fiji

ISBN: (纸本)9781665453059

Errors and omissions in the manual process of compiling student results in secondary schools in pacific Countries were examined in this research. To do that, preliminary research on the existing manual record-keeping system in Fiji was examined in a few chosen secondary schools. A new software application was designed to automate the processing of such results. This solved the issues with manual result processing. C# programming language as well as SQL-Server were used to create a software package. The system's anticipated outcomes demonstrate that educators are not required to record student tests, examinations, and calculation results because the system takes care of almost everything, relieving teachers of the stress of having to prepare students' results. Similarly, it is less expensive to print individual student results on A4-sized paper or imprinted cardboard material that resembles a certificate and has a more attractive appearance than it would be to create result booklets. By reducing the time and energy needed for result preparation, this program will reduce the stress associated with the teacher's work and free up a lot of time for teaching as well as other instructional concerns. The record-keeping and evaluation process capabilities of such a new system can be adjusted to fit the needs of both higher secondary schools whether private or public. © 2022 ieee.

关键词： Students

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Performance Analysis of Verifiable data Registry Solutions for Decentralized Identifiers

Performance Analysis of Verifiable Data Registry Solutions f...

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2022 ieee asia-pacific conference on computer science and data engineering, csde 2022

作者： Alizadeh, Morteza Andersson, Karl Schelen, Olov Electrical and Space Engineering Luleå University of Technology Department of Computer Science Skellefteå Sweden

ISBN: (纸本)9781665453059

User identification in decentralized systems is a demanding task. Identification systems should work resiliently and have efficient performance. Moreover, identification systems should protect the data that they must store against hackers and saboteurs. Keeping a system with decentralized identification without any intervention in the middle has attracted attention to improve earlier centralized identification systems. Decentralized Identifiers (DIDs) constitute a solution for identification divided into different modules. The verifiable data registry is one of the main parts of this technology, which is distributed storage of identity properties. We analyze the decentralized identification data registry and compare the performance of verifiable data registry based on blockchain and the Distributed Hash Table (DHT) on different scales of systems. Our evaluation results show that DHT has better performance. Furthermore, a model based on DHT shows that in addition to immutable storage and faster query time, it makes systems handle or search in data storage with lower searching time compared to Ethereum Blockchain as another immutable secure technology. Finally, our results show that DHT is a better solution than other models in different scenarios. Although blockchain has promising results on a small scale, it still has problems with storage and query time in large-scale systems. © 2022 ieee.

关键词： Blockchain

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