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

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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Robot Tele-Operation / Teaching System using VR Device

Robot Tele-Operation / Teaching System using VR Device

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IEEE Conference on Cybernetics and Intelligent systems

作者： Minami Ohsato Yasumichi Aiyama Master’s Program in Systems and Information Engineering University of Tsukuba (Alumna) Tsukuba Japan Inst. of Systemsand Information Engineering University of Tsukuba Tsukuba Japan

This paper proposes a "robot tele-teaching system using a VR device" as a new robot teaching method to replace the conventional robot teaching method. Currently we still need teach-pendant to teach industrial robots. It is very inconvenient method. Our novel method consists of two robots and a VR device. One robot is on site instead of the operator. A stereo camera is attached to its end of the robot, which realizes a 3D positionand posture obtained from HMD. The operator can then view the images through the HMD as if he/she are on site. The other manipulating robot is equipped with a gripper and can follow the position and orientation of the gripper-like input device held by the operator. This system is equipped with a correction and auto-teaching function that uses the geometric characteristics of the work object. This significantly reduces the time required for operation. In addition, the teaching points obtained by this system have been successfully used for playback in a real environment.

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Classification of Multivariate Time Series Signals Using Self-Supervised Representation Learning for Condition Monitoring

Classification of Multivariate Time Series Signals Using Sel...

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Joint e-Manufacturing and Design Collaboration Symposium (eMDC) & International Symposium on Semiconductor Manufacturing (ISSM)

作者： Koichi Sumiya Sumika Arima Doctoral Program in Policy and Planning Sciences University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (数字)9798331510589

ISBN: (纸本)9798331510596

In the analysis of real-world data, two significant challenges often arise: high-dimensional signals and their temporal interactions. To address these issues and identify transitions in process conditions through end-to-end learning, we propose a self-supervised representation learning framework that conceptualizes signals as images. This straightforward approach classifies imaged signals as time-specific conditions by maximizing mutual information within a domain-specific feature space. We applied this methodology to two labeled open datasets and one unlabeled real-world process dataset, yielding promising results.

关键词： Representation learning Furnaces Time series analysis Self-supervised learning Glass Medical services Semiconductor device manufacture Turning Wool Mutual information

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Rice Variety Identification Using Edge Feature Extraction and Texture-Based Segmentation

Rice Variety Identification Using Edge Feature Extraction an...

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2023 International Seminar on Application for Technology of information and Communication, iSemantic 2023

作者： Setiawan, Aji Adi, Kusworo Widodo, Catur Edi Diponegoro University Doctoral Program of Information Systems School of Postgraduate Studies Semarang Indonesia Faculty of Engineering Darma Persada University Department of Information Technology Jakarta Indonesia Diponegoro University School of Postgraduate Studies Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia

ISBN: (纸本)9798350339215

This research proposes a methodology for identifying the optimal feature combination using Support Vector Machine (SVM) based on edge and texture features. Canny, Sobel, and Prewitt for edge detection and GLCM, Gabor, and LBP for texture analysis are popular feature extraction techniques widely employed in various cases. The approach combines edge and texture features with SVM to classify rice types into five categories: Ipsala, Jasmine, Karacadag, Arborio, and Basmati. Experimental results demonstrate that SVM using Canny, Sobel, and Prewitt combined Gabor texture features outperforms the comparative methods. A comparative analysis based on accuracy scores using confusion matrices is conducted. Combining all feature edge methods, Canny, Sobel, and Prewitt with Gabor on SVM classification is the best model for rice object classification, achieving an accuracy of 96%. © 2023 IEEE.

关键词： Support vector machines

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Improving LED-Based Photoacoustic Image Quality Using an Optimized Deconvolution Technique

Improving LED-Based Photoacoustic Image Quality Using an Opt...

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Photons Plus Ultrasound: Imaging and Sensing 2025

作者： Ogawa, Ryuhei Sato, Naoto Saito, Atsushi Singh, Mithun Kuniyil Ajith Kawamoto, Hiroaki Sankai, Yoshiyuki Master’s Program in Intelligent and Mechanical Interaction Systems University of Tsukuba Tsukuba Japan Research & Development Division Cyberdyne Inc. Tsukuba Japan Research & Business Development Division Cyberdyne Inc. Rotterdam Netherlands Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781510683860

LED-based photoacoustic imaging (PAI) with linear array ultrasound probes has gained attention due to its cost-effectiveness, safety, and potential for portable applications. However, its low signal-to-noise ratio (SNR) and limited visibility of blood vessel lumens remain challenges. To address these issues, we propose an innovative deconvolution approach that leverages the differential of the LED light pulse to enhance photoacoustic image quality. Our optimized reconstruction algorithm improves blood vessel visualization by applying deconvolution of the PA signals with the differential of the LED pulse, leading to improved lumen visibility and enhanced imaging of peripheral blood vessels in both 2D and potentially 3D. Our method precisely measures the LED pulse profile using the LED arrays integrated into our AcousticX system. The second differential of this pulse is then utilized as the point spread function (PSF) in the deconvolution process. This technique effectively enhances PA signals by emphasizing the leading and trailing edges of the pulse, thereby improving blood vessel visibility and overall image quality. To validate our approach, we conducted experiments using tissue-mimicking phantoms and human volunteers with the AcousticX system. The algorithm was tested offline in MATLAB and in real-time on the AcousticX platform. Results demonstrate substantial artifact suppression, improved SNR, and enhanced image contrast, ultimately enabling clearer visualization of the blood vessels. This advancement improves the competitiveness of LED-based PAI systems compared to laser-based alternatives and broadens their potential for clinical applications, accelerating their translation into medical practice. © 2025 SPIE.

关键词： Ultrasonic imaging

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High Resolution of City-Level Climate Simulation by GPU with Multi-physical Phenomena 18th

High Resolution of City-Level Climate Simulation by GPU with...

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18th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2021

作者： Watanabe, Koei Kikuchi, Kohei Boku, Taisuke Sato, Takuto Kusaka, Hiroyuki Master’s Program in Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukubashi Japan Center for Computational Sciences University of Tsukuba Tsukubashi Tennodi Japan

ISBN: (纸本)9783030935702

In this paper, we describe the Graphics Processing Unit (GPU) implementation of our City-LES code on detailed large eddy simulations, including the multi-physical phenomena on fluid dynamics, heat absorption and reflection by surface and building materials, cloud effects, and even sunlight effect. Because a detailed simulation involving these phenomena is required for analyses at the street level and several meters of resolution, the computation amount is enormous, and ordinary CPU computation cannot provide sufficient performance. Therefore, we implemented the entire code on GPU clusters with large-scale computing. We applied OpenACC coding to incrementally implement relatively easy programming and eliminate data transfers between the CPU and GPU memories. Based on this research, we determined that the elimination of data transfers is effective, even in the case where a part of the code execution on the GPU is slower than the CPU, owing to the absence of spatial parallelism. The objective of this study is to perform a complete climate simulation on a few square-kilometers field around the Tokyo Station, considering the finest resolution of the original highlighted area of the Marathon race in the Olympic Games Tokyo 2020. We successfully transferred the entire code to the GPU to provide approximately eight times the performance of CPU-only computation on multi-GPU per node with a large scale cluster. © 2022, IFIP International Federation for information Processing.

关键词： Graphics processing unit

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Application of the K-Medoids Clustering Model and Borda Decision Group in Viewing Flood Area Groupings in North Aceh Regency

Application of the K-Medoids Clustering Model and Borda Deci...

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Artificial Intelligence and Image Processing (IWAIIP), International Workshop on

作者： Wahyu Fuadi Ilham Sahputra Dedi Fariadi Agustinar Informatics Engineering Study Program Faculty of Engineering Universitas Malikussaleh Lhokseumawe Indonesia Information Systems Study Program Faculty of Engineering Universitas Malikussaleh Lhokseumawe Indonesia Electrical Engineering Study Program Faculty of Engineering Universitas Malikussaleh Lhokseumawe Indonesia

The importance of the K-Medoid model in viewing disaster-prone areas in each sub-district in North Aceh. The advantage of the k-medoid model results is that it has better cluster centers than other models. The novelty of this research is the cluster results are assessed by each decision maker using the Borda group model in providing flood disaster assistance or areas that are a priority for handling, which are included in the flood-prone cluster. Therefore, this research is important because it can be used to identify areas most severely affected by flooding. This research aims to analyze and identify the impact of flood hazards based on grouping and decision-making using the Borda group model in each sub-district in North Aceh. The results of the k-medoids model show 3 clusters that can see potential areas for flood disasters, namely very vulnerable. There are six sub-districts. For the k-medoids results, ten sub-districts are vulnerable. Lastly, the safe zones are 11 sub-districts. This research’s k-medoid model analysis is more precise in seeing clusters of places that are potentially affected by flooding based on spatial maps of their nearest neighboring areas. The percentage of each cluster is as follows: Cluster 1 is 4%, Cluster 2 is 55%, and Cluster 3 is 41%. The k-medoid model provided this result after three iterations, with a closeness difference of 1.594510537. The results of the Borda model group research can be used as a recommendation for the areas that receive the highest priority in disaster management.

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Mining the Sentiment of Online Gaming from Social-Media: A Consumer Insight 7

Mining the Sentiment of Online Gaming from Social-Media: A C...

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7th information systems International Conference, ISICO 2023

作者： Nadlifatin, Reny Persada, Satria Fadil Gunawan, Gilbert Aldrich Prasetyo, Yogi Tri Young, Michael Nayat Perwira Redi, Anak Agung Ngurah Lukiyanto, Kukuh Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia School of Industrial Engineering and Engineering & Management Mapua University 658 Muralla St. Intramuros Manila1102 Philippines Industrial Engineering Department Faculty of Engineering and Technology Sampoerna University Jakarta12780 Indonesia

The gaming industry has changed since advanced technologies and hardware specifications were able to create the possibility of gaming with connective network or known as online gaming. Some communities are accepting positively, and others are contradicted. Thus, there is an urgency to know the insight from their sentiment. The present research extracts 10 thousand sentiments at social media with sentiment text analysis. The text is interpreted into six based emotions namely anger, disgust, fear, joy, sadness, and surprise. The mining analysis by lexicon valance aware dictionary and sentiment reasoner (VADER) projects the Joy emotions as the domination result with 94.74%. Positive joy expression on online gaming is revealed by extracting the sentiment analysis. In total, ten thousand data were collected from the corpus, which resulted in the happy sentiments that were experienced. © 2023 The Authors. Published by Elsevier B.V.

关键词： Sentiment analysis

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Study on Wearable Gaze-Based Communication System for Patients with Amyotrophic Lateral Sclerosis (ALS)

Study on Wearable Gaze-Based Communication System for Patien...

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IEEE/SICE International Symposium on System Integration

作者： Sawada Nonoka Akira Uehara Hiroaki Kawamoto Yoshiyuki Sankai Master's Program in Intelligent and Mechanical Interaction Systems University of Tsukuba Ibaraki Japan Institute of Systems and Information Engineering Center for Cybernics Research University of Tsukuba Tsukuba Ibaraki Japan

This study centers its attention on communication among ALS patients with severe symptoms, which is essential to daily life and the part that remains a difficulty. Also, communication is important to promote social participation and ability of independence. To promote social participation and improve the ability of independence without the restrictions for patients, the purpose of this study is to develop a wearable interface that enables communication based on the patient's voluntary intent, without temporal, spatial, or physical restrictions, and to confirm the feasibility of intention transmission using a new text entry algorithm. The developed interface utilized a see-through type head-mounted display (HMD) with a gaze estimation sensor to enable patients themselves to transition between cyberspace and physical space and to communicate by the system without restrictions of posture or usage environment during daily life activities. The letter selection is triggered by a change in the direction of the gaze trajectory. This method of letter selection reduces the burden on the user by avoiding the effects of dwell time and other factors associated with gazing input. The key layout for text input UI considers the characteristics of human eye movements, to minimize key selection errors and allows for quick viewpoint movement. To confirm the feasibility of the basic performance, we conducted the experiment with three able-bodied participants using the developed system and a conventional system as a comparison system, respectively. As a result, the developed system was able to input sentences in the same amount of time as the conventional system. The results show that the developed system has the basic performance of a communication interface with a new character input method based on eye movement functions. Therefore, we confirmed the feasibility of transmitting intention using a new text entry algorithm to enable communication without the restrictions.

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Preliminary Plan for Data Collection on Stakeholder information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones 23

Preliminary Plan for Data Collection on Stakeholder Informat...

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23rd International Symposium on Communications and information Technologies, ISCIT 2024

作者： Arayachookiat, Penpitcha Saengtabtim, Kumpol Kodaka, Akira Leelawat, Natt Tang, Jing Watanabe, Kenji Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan International School of Engineering Chulalongkorn University Faculty of Engineering Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (纸本)9798350353952

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. © 2024 IEEE.

关键词： Area-Business Continuity Management Flood Index of Item-Objective Congruence information Interdependence

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