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International Conference on Business and Industrial Research (ICBIR)

作者： Narongchai Visitpanya Taweesak Samanchuen Technology of Information System Management Division Faculty of Engineering Mahidol University Nakorn Pathom Thailand

The protection of sensitive tax data poses a challenge for data processors seeking to use it freely, particularly in the realm of financial and tax data. Detecting suspicious behavior related to tax evasion in this area requires sophisticated techniques. This paper presents a study on detecting tax evasion behavior using publicly available financial data. The data was obtained from a public source, and machine learning was applied to identify suspicious behavior based on criteria derived from a literature review. Our study yielded a precision of over 97 % using selected supervised models. Future work involves exploring behavior using unsupervised methods, increasing the number of instances using data synthesis techniques, and comparing results with enterprises that are not registered in a stock market as long as the data is legally available. This research provides valuable insights into identifying suspicious tax evasion behavior and can inform the development of improved tax evasion detection systems in the future.

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Optimal Deep Canonically Correlated Autoencoder-Enabled Prediction Model for Customer Churn Prediction

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Computers, Materials & Continua 2022年第11期73卷 3757-3769页

作者： Olfat M.Mirza GJose Moses R.Rajender E.Laxmi Lydia Seifedine Kadry Cheadchai Me-Ead Orawit Thinnukool Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science Engineering Malla Reddy Engineering College500100India Department of Computer Science Engineering Lendi Institute of Engineering&TechnologyDenkada535005India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeNorway Program in Statistics and Information Management Faculty of ScienceMaejo UniversityChiang Mai50290Thailand Department of Modern Management and Information Technology College of Arts Media and TechnologyChiang Mai UniversityChiang Mai50200Thailand

Presently,customer retention is essential for reducing customer churn in telecommunication *** churn prediction(CCP)is important to predict the possibility of customer retention in the quality of *** risks of customer churn also get essential,the rise of machine learning(ML)models can be employed to investigate the characteristics of customer ***,deep learning(DL)models help in prediction of the customer behavior based characteristic *** the DL models necessitate hyperparameter modelling and effort,the process is difficult for research communities and business *** this view,this study designs an optimal deep canonically correlated autoencoder based prediction(ODCCAEP)model for competitive customer dependent application *** addition,the O-DCCAEP method purposes for determining the churning nature of the *** O-DCCAEP technique encompasses preprocessing,classification,and hyperparameter ***,the DCCAE model is employed to classify the churners or ***,the hyperparameter optimization of the DCCAE technique occurs utilizing the deer hunting optimization algorithm(DHOA).The experimental evaluation of the O-DCCAEP technique is carried out against an own dataset and the outcomes highlighted the betterment of the presented O-DCCAEP approach on existing approaches.

关键词： Churn prediction customer retention deep learning machine learning archimedes optimization algorithm

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Towards Trustworthy Aircraft Safety: Explainable AI for Accurate Incident and Accident Predictions 20th

Towards Trustworthy Aircraft Safety: Explainable AI for Accu...

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20th International Conference on the Economics of Grids, Clouds, systems, and Services, GECON 2024

作者： Amin, Maryam Noor, Umara Fatima, Manahil Rashid, Zahid Altmann, Jörn Department of Software Engineering Faculty of Computing and Information Technology International Islamic University Islamabad44000 Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul Korea Republic of College of Engineering Seoul National University Seoul Korea Republic of Integrated Major in Smart City Global Convergence Seoul National University Seoul Korea Republic of

ISBN: (纸本)9783031812255

Despite technological advancements, ensuring aircraft safety remains a challenge, however, Machine learning (ML)-based approaches for predicting future incidents play a crucial role in addressing flight safety. As ML models increase in complexity, their decision-making process becomes less transparent, posing significant challenges to trustworthiness. While simpler models demonstrate lower accuracy, more intricate models such as deep neural networks achieve higher accuracy but sacrifice interpretability. In this study, we enhance trustworthiness in aircraft safety prediction by leveraging a dataset of past accidents and incidents to prevent similar accidents from occurring in the future. To achieve this, we apply Random Forest and Extreme Gradient Boosting models to classify different categories of aircraft incidents. Additionally, we apply two powerful explainable artificial intelligence (XAI) techniques: Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP) to provide insights into both local and global predictions made by the models. Notably, our results reveal high accuracy in these predictions while maintaining trustworthiness. This research contributes to the advancement of XAI and offers valuable insights for safety-critical applications and decision support systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Aircraft accidents

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Improved Chest X-Ray Image Quality Using Median and Gaussian Filter Methods 4

Improved Chest X-Ray Image Quality Using Median and Gaussian...

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4th International Conference on Informatics, Multimedia, Cyber and information system, ICIMCIS 2022

作者： Kesuma, Lucky Indra Ermatita, Ermatita Erwin, Erwin Sari, Purwita Purabaya, Rudhy Ho Universitas Sriwijaya Doctoral Program in Engineering Faculty of Engineering Palembang Indonesia Universitas Sjakhyakirti India Universitas Sriwijaya Information System Faculty of Computer Science Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Departement of Computer System Palembang Indonesia Universitas Sriwijaya Informatic Management Faculty of Computer Science Palembang Indonesia Universitas Pembangunan Nasional Veteran Jakarta Information System Faculty of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665473279

The lungs are one of the organs of the body that are responsible for the human respiratory process and are very susceptible to dangerous diseases. For this reason, early detection and diagnosis of lung organs is needed, one of which is through examination of Chest X-Ray (CXR) images. Examination of the results of CXR images is still done manually by doctors and radiologists, this requires time and high accuracy. To facilitate the examination, it is necessary to image quality enhancement in order to get better image quality results so as to produce an accurate diagnosis. The initial stage in this research is to apply the contour improvement technique to the image using Morphology Opening, and followed by noise reduction using Median Filter and Gaussian filter. The results of the two methods of noise reduction are compared with the results of image quality in order to find out the best method that can be applied. The implementation of image quality enhancement results was measured quantitatively using Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index Metrics (SSIM). In the Morphology Opening and Median Filter methods, the values obtained are 39.187, 22.252, and 0.952, respectively. Meanwhile, the Morphology Opening and Gaussian Filter methods obtained values of 38.717, 23.917 and 0.956. Based on these results, it can be concluded that both methods are able to improve image quality well. © 2022 IEEE.

关键词： Image quality

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Automated User Experience (UX) Testing for Mobile Application: Strengths and Limitations

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2022年第4期16卷 30-45页

作者： Abuaddous, Hayfa. Y. Saleh, Ashraf Mousa Enaizan, Odai Ghabban, Fahad Al-Badareen, Anas Bassam Faculty of Computer Sciences and Informatics Amman Arab University Amman Jordan Department of Management Information System University of Tabuk Tabuk Saudi Arabia College of Computer Science and Engineering Taibah University Medina Saudi Arabia Department of Software Engineering Aqaba University of Technology Aqaba Jordan

User Experience (UX) evaluation has a significant importance for any interactive application. Mobile device applications have additional limitations to convey good user experiences (UX) due to the usage and features of mobile devices in ubiquitous computing contexts. There are a lot of automated tools available for evaluating, such applications particularly developed for Android and iOS. Automated UX evaluation provides a number of strengths which are able to overcome the limitations of non-automated (moderated) counterparts. Automated UX evaluation is regarded as unexplored field, especially when it is adopted for the UX evaluation of complex mobile application. Despite these, automated UX evaluation tools are unexplored and should only be used in coupling with traditional UX evaluation techniques. Hence, this study aims to discuss the literature in automated UX evaluation and to highlight the UX measurements that merit further investigation. This paper presents the most fre-quently used automated UX evaluation tools for mobile applications. Therefore, the study analyzes existing automated UX tools and frameworks and identifies which UX attributes and measurements of automated UX evaluation are likely to be of use in future research. Moreover, we discuss the strengths and limitations of automated UX evaluation methods for mobile applications. Finally, the paper provides an overview of automated UX evaluation techniques and tools. It also presents the strengths and limitations for comparing various evaluation methods. © 2022,International Journal of Interactive Mobile Technologies. All Rights Reserved.

关键词： Automation

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An Integration of Personal Health Device and HL7 FHIR Using CoAP 4

An Integration of Personal Health Device and HL7 FHIR Using ...

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4th International Conference on Circuits, systems and Simulation, ICCSS 2021

作者： Leksrisawat, Chollada Samanchuen, Taweesak Mahidol University Technology of Information System Management Division Faculty of Engineering Nakorn Pathom Thailand

ISBN: (纸本)9781728167527

In the field of health care, various electronic instruments are applied. These devices have different types of data formats depending on the service provider. For this work, the integration of IoT technology and electronic health record system is proposed where HL7 FHIR standard and CoAP protocol are selected to overcome this problem. The communication protocols for IoT including CoAP and MQTT were compared in terms of data transfer package size and Round Trip Time (RTT). The experimental result shows that RTT of CoAP smaller than RTT of MQTT while the packages of CoAP are smaller than MQTT as expected. We can see that the proposed system with HL7 FHIR can create a system interconnect between personal health devices and databases seamlessly. The proposed system can apply to various applications of the health care domain. © 2021 IEEE.

关键词： Internet of things

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An Improvement of Network Routing Protocol with K-Means Clustering for Reactive Wireless Sensor Networks 4

An Improvement of Network Routing Protocol with K-Means Clus...

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4th International Conference on Circuits, systems and Simulation, ICCSS 2021

作者： Arjinwat, Thanaphat Samanchuen, Taweesak Mahidol University Technology of Information System Management Division Faculty of Engineering Nakorn Pathom Thailand

ISBN: (纸本)9781728167527

Wireless sensor networks (WSNs) are currently used in many areas for monitoring environmental parameters. It is usually deployed in hard-to-access areas and batteries cannot be replaced. WSN components must be designed for energy efficiency for both hardware and software. A routing protocol is needed to manage the network and help extend network lifetime. This work addresses the WSN protocol for reactive networks by aiming to develop a clustering method, which is a huge impact on energy consumption in the routing protocol. K-Means algorithm is deployed for efficiency sensor nodes clustering. The cluster head selection is done based on the maximum remaining energy node in each cluster. Simulation is performed to demonstrate the performance of the proposed scheme. The simulation results show that the proposed scheme has better performance than ordinary protocols and able to extend network lifetime. The characteristics of the proposed scheme are verified by using different sample datasets as well. © 2021 IEEE.

关键词： Routing protocols

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Design and simulation of outbound functions in warehouse operations with queueing theory 18

Design and simulation of outbound functions in warehouse ope...

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18th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and information technology, ECTI-CON 2021

作者： Han-Klup, Worawut Samanchuen, Taweesak Mahidol University Technology of Information System Management Division Faculty of Engineering Nakorn Pathom Thailand

ISBN: (纸本)9780738111278

In modern e-commerce, warehouse management is very crucial for overall service quality. Moreover, the cost of order picking in outbound logistics is estimated to be more than half of the total operating cost in warehouse activity. This work studies the factors of the order processing on average customer order throughput time where the picking, packing, and sorting functions are executed separately by either a single operator or multiple parallel operators. The proposed staff management by using the queuing theory is demonstrated. The data comprise a complete operational history of an e-commerce company, order by order, over 3 months in the year 2020. The queuing theory and statistic model are used to study this activity of the warehouse. To evaluate the efficiency of these operations, the simulation method is utilized. The result shows that the simulation is adequate in approximating the optimal number of pickers and packers. This work is explained generally to be practical for business leading to future research opportunities and giving more solutions from the existing technology supporting and solving the problems. © 2021 IEEE.

关键词： Warehouses

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Classification of pomelo leaf diseases using convolution neural network 18

Classification of pomelo leaf diseases using convolution neu...

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18th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and information technology, ECTI-CON 2021

作者： Laosim, Sirirat Samanchuen, Taweesak Mahidol University Technology of Information System Management Division Faculty of Engineering Nakhon Pathom Thailand

ISBN: (纸本)9780738111278

Pomelo is an important export fruit of Thailand. However, it is a plant that is susceptible to many diseases. The objective of this work is to identify diseases using the convolution neural network, which most of the diseases of Pomelo indicate on its leaves. Three types of pomelo leaves images including healthy leaves, greening disease, and citrus leafminer are addressed in this work. Transfer Learning techniques based on GoogLeNet, AlexNet, and Squeeznet are utilized for building the proper machine learning model for classifying Pomelo diseases. Image process techniques are also applied to enhance the performance of the model such as edging, grayscale, and rotation. Experimental results show that all three models give a similar performance where GoogLeNet has a bit better performance than that of AlexNet and Squeeznet. © 2021 IEEE.

关键词： Image enhancement

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Decision Support system in Determining the Achievement of Widyaiswara Value Using WASPAS and TOPSIS Algorithm 1

Decision Support System in Determining the Achievement of Wi...

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1st International Conference on technology Innovation and Its Applications, ICTIIA 2022

作者： Pratama, Yudhistira Adhitya Iswara, Bagus Ajie Nababan, Adli Abdillah Information System Studies Program Pelita Harapan University Medan Campus Faculty Of Computer Science Medan Indonesia Master's Study Program Informatics Engineering Universitas Sumatera Utara Faculty Of Computer Science And Information Technology Medan Indonesia Digital Business Study Program Stmik Pelita Nusantara Medan Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material by the BPSDM PROVSU. However, the assessment process that occurs is still not precise and time-consuming. Therefore, to minimize this, a decision support system is needed that can minimize time errors and data processing in decision-making so that the assessment runs well and accurately. This system was built by applying the WASPAS method and the TOPSIS method. Based on the results of tests carried out five times, the results of the WASPAS method processing time resulted in an average processing time of 0.00029791 ms and an average memory usage value of 2.836.44 kb, while the results of the TOPSIS method processing time test resulted in an average processing time - an average of 0.000296428 ms and an average memory usage value of 2.862.34 kb. © 2022 IEEE.

关键词： Decision support systems

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