Welcome to the Data Science Lab at KCGI.
We develop data-driven solutions that integrate advanced analytics, machine learning, and statistical modeling with qualitative inquiry to tackle complex, real-world problems. By combining quantitative and qualitative evidence, we generate deeper insights and actionable tools. Our interdisciplinary team collaborates across domains.
Professor, President of KCGI
Research fields: database, data warehouse, data mining, business intelligence
Research interests:
Email: terashita@kcg.ac.jp
Homepage: https://www.kcg.edu/en/faculty/professor/y-terashita
Associate professor, KCGI
Research fields: data science, data analytics
Research interests: data engineering, data mining, data visualization
Email: t_dinh@kcg.ac.jp, it08duytai@gmail.com
Master student, KCGI
Research fields: data science, data analytics, data visualization, artificial intelligence, machine learning
Research interests: categorical data clustering LLMs, data mining, data engineering, big data and data warehouses, deep learning
Email: htetmyat31799@gmail.com
Master student, KCGI
Research fields: lulc mapping, xAI, remote sensing & geobia, deep learning image segmentation, interpretable machine learning
Research interests: object-based lulc segmentation, xAI, interpretable rule mining, high-resolution geospatial analysis, trustworthy gis-ai, transparent and auditable lulc systems
Email: farhajkalsi@gmail.com
Homepage: www.linkedin.com/in/farhaj-habib
Master student, KCGI
Research fields: data science, artificial intelligence, economics, econometrics, analytics, fintech
Research interests: artificial intelligence, machine learning, predictive analytics, econometrics, trade analytics, risk modeling, blockchain ai solutions, sentiment analysis, data analytic
Master student, KCGI
Research fields: artificial intelligence, machine learning, computer vision, data science, data analytics
Research interests: long-tail distribution learning, insect pest recognition, deep learning, image classification,data mining
Email: vidushineranjani@gmail.com
Master student, KCGI
Research fields: data science, data analytics, educational data analysis, machine learning, data visualization
Research interests: data-driven educational resource analysis, educational data mining, district-level school census analysis, hierarchical clustering, UMAP-based visualization, predictive analytics, and machine learning applications in education.
Email: ushaminimaduthisari98@gmail.com
Homepape: linkedin.com/in/ushamini-madhuthisari
Master student, KCGI
Research fields: business statistics, data science, business analytics, machine learning
Research interests: predictive analytics, statistical modelling, applied machine learning, customer & business data analytics, data visualization
Email: sachinihansika154@gmail.com
Homepape: linkedin.com/in/sachiniperera154
Master student, KCGI
Research fields: data science, data analytics, data visualization, machine learning, image processing, geospatial data science, remote sensing, spatial data analysis, predictive modeling, and applied artificial intelligence.
Research interests: geospatial analytics, satellite image analysis, remote sensing, socioeconomic data analysis, spatial machine learning, predictive analytics, data integration, feature engineering, and ai-driven decision support systems.
Email: Zinnorigne@gmail.com
Homepape: linkedin.com/in/zinnorigne
Master student, KCGI
Research fields: data science, data analytics, data visualization, machine learning, natural language processing, image processing, predictive analytics, social media analytics, artificial intelligence, and business intelligence
Research interests: big data analytics, neural networks, data engineering, predictive modeling, social media trend analysis, audience behavior prediction, content optimization, data-driven decision making
Email: azimpk.4@gmail.com
Homepape: linkedin.com/in/sachiniperera154
Master student, KCGI
Research fields: data science, data mining and knowledge discovery, data analytics, machine learning, data visualization, socioeconomic data analytics, and sustainable development data analysis.
Research interests: pattern mining; interactive data mining frameworks; scalable pattern discovery; machine learning and predictive analytics; data visualization and visual analytics; socioeconomic and SDG data analysis; local-level and geospatial data analysis; time-series data analysis; and data-driven stock market analysis.
Email: subedi.binod.333@gmail.com
Homepape: linkedin.com/in/subedi-binod-bb4734181/
Master student, KCGI
Research fields: data science, biotechnology, artificial intelligence, machine learning, explainable artificial intelligence (XAI), data analytics
Research interests: AI for biotechnology, explainable AI, human-centered AI, health informatics, digital behavior analysis, sleep analytics, machine learning, qualitative and mixed-methods research
Email: mdashraful2526@gmail.com
Master student, KCGI
Research fields: data science, data mining and knowledge discovery, data analytics, machine learning, data visualization, socioeconomic data analytics, and sustainable development data analysis.
Research interests: sentiment analysis, text mining, qualitative data analysis, exploratory data analysis, data visualization, cloud computing, web development
Email: kaveeshakwalalawela@gmail.com
Homepape: linkedin.com/in/kaveeshawalalawela
Master student, KCGI
Research fields: data Science, data mining, data visualization
Research interests: data-driven analysis and visualization for supporting sustainable environmental practices and informed decision-making.
Email: Yupeshkandel92@gmail.com
Master student, KCGI
Research fields: data science, data analytics, machine learning, natural language processing, data mining and knowledge discovery, large language models, text analytics, and data visualization.
Research interests: sentiment analysis, text mining, large language models, qualitative and quantitative data analysis, exploratory data analysis, natural language processing, data visualization, machine learning, and AI-driven data analytics.
Email: anupshrestha150@gmail.com
Master student, KCGI
Research fields: data science, data mining, data analytics, data visualization, machine learning, business data analysis, and financial data analysis.
Research interests: pattern mining; machine learning and predictive analytics; data visualization and visual analytics; time-series data analysis; statistical data analysis and data-driven business data analysis based on financial reports.
Email: madhavbh1998@gmail.com
Homepape: www.linkedin.com/in/madhab-bhattarai-94937b278
Master student, KCGI
Research fields: data science & artificial intelligence, statistical machine learning, data mining & information systems.
Research interests: supervised and unsupervised machine learning algorithms, high-utility data mining and association rule discovery, end-to-end machine learning pipelines and scalable data architectures, predictive analytics in environmental and urban systems
Former master student, KCGI
Research fields: data science, data analytics, data visualization, machine learning, NLP, image processing
Research interests: NLP, deep learning, data clustering, machine learning
Email: partho.21partho@gmail.com
Former master student, KCGI
Research fields: data science, machine learning, data analytics
Research interests: big data, neural networks, data engineering
Email: roohulamin935@gmail.com
Former master student, KCGI
Research fields: tourism data analytics, machine learning applications
Research interests: tourism demand forecasting, hybrid prediction models, cultural tourism insights, sustainable tourism development
Email: hkgtskariyawasam@gmail.com
Former master student, KCGI
Research fields: data mining, data analysis and visualization
Research interests: data mining, data science
Email: yelungarsenal1@gmail.com
Former master student, KCGI
Research fields: data science, pattern mining, machine learning applications, predictive analytics
Research interests: High-utility sequential pattern mining, interactive frameworks for pattern discovery, algorithm optimization for large datasets, predictive modeling and data-driven decision systems, applications of pattern mining in agriculture, tourism, and education
Former master student, KCGI
Research fields: data analytics, data visualization, image processing, micro-grid analysis.
Research interests: data science, artificial intelligence, business analytics, data clustering, social network analysis ,machine learning, image processing
Email: salehinhaque41@gmail.com
Former master student, KCGI
Research fields: data science, data mining and knowledge discovery
Research interests: Frequent and periodic pattern mining, closed and maximal itemset mining, interactive data mining frameworks, temporal data analysis, scalable pattern discovery algorithms, and applications of data mining techniques to physics data and complex systems
Email: nareshshresthapathari@gmail.com
Former master student, KCGI
Research fields: data science, microeconomics, macroeconomics, social statistics, econometrics, data analytics
Research interests: artificial intelligence, machine learning, econometrics, predictive analytics, trade analytics, sentiment analysis
Email: sachinimadhushani1997@gmail.com
Former master student, KCGI
Research fields: data science, machine learning, data mining
Research interests: data science, data analytics, machine learning, clustering, categorical data, data mining
Email: shresthaseelu7@gmail.com
Former master student, KCGI
Research fields: biotechnology, data science, business analysis, product analysis, UX Research Research interests: data-driven decision making, human-centered research, product strategy, biostatistics
Email: daud55495@gmail.com
Former master student, KCGI
Research fields: data science, data analytics
Research interests: data science, data analytics, data visualization, machine learning
Email: thosaka0510@gmail.com
Former master student, KCGI
Research fields: data science, AI, finance, economics, and accounting
Research interests: sentiment analysis, NLP, quantitative finance, anomaly detection, prediction-based reasoning, data mining
Email: shehan4101@gmail.com
Former master student, KCGI
Research fields: data science and machine learning, embedded systems, IoT, automation, and control systems
Research interests: sentiment analysis, predictive maintenance using sensor data, smart automation and robotics, real-time data processing on microcontrollers, deep learning on edge devices, signal processing and sensor fusion, computer vision for automated systems
Former master student, KCGI
Research fields: data science, data analytics, business analytics
Research interests: sentiment analysis, quantitative finance, consumer behavior, prediction-based reasoning.
Email: jahidhasan0704@gmail.com
Former master student, KCGI
Research fields: data science, data analytics, data visualization
Research interests: data science, AI, data visualization, sentiment analysis, data analytics
Email: panchama.amani97@gmail.com
Former master student, KCGI
Research fields: food science, human nutrition, dietetics, data mining, data analysis
Research interests: noncommunicable diseases, public health, epidemiology, biostatistics
Email: madushawijesinghe434@gmail.com
Homepage: https://www.linkedin.com/in/madusha-wijesinghe-03159554/
Former master student, KCGI
Research fields: data science, data analytics, environment
Research interests: data science and analytics, energy science and engineering
Email: maplewonghauchi@gmail.com
Former master student, KCGI
Research fields: data science, data analytics, business analytics, marketing
Research interests: data clustering, customer segmentation, consumer behaviour.
Email: khans7980@gmail.com
Homepage: http://www.linkedin.com/in/rameesh-khan-
Former master student, KCGI
Research fields: data science, data analytics
Research interests: artificial intelligence, machine learning
Email: joshilalit9654@gmail.com
Former master student, KCGI
Research fields: database, data analytics
Research interests:
Email: knsanjaya@gmail.com
Former master student, KCGI
Research fields: data science, data analytics, IoT, computer science
Research interests: data science and analytics, big data, cloud computing and cloud native, AI, IoT, software development and testing
Email: cm19981025@gmail.com
Former master student, KCGI
Research fields: data science, machine learning, artificial intelligence
Research interests: predictive modeling, natural language processing, deep learning applications in various domains
Email: hannouda.amal@gmail.com
Former master student, KCGI
Research fields: machine learning and data mining, recommendation systems, data visualization, and visual analytics
Research interests: social network analysis,privacy-preserving data mining, causal inference, and counterfactual analysis
Email: gyjoshua123@gmail.com
[40] Roka Dil Bahadur, Tai Dinh, Yue Wuyi. “Large-Scale Multi-Source Benchmarking of Clustering Validation Metrics”. The 21st International Conference on Ubiquitous Information Management and Communication (IMCOM 2027), 4–6 January 2027, Taipei, Taiwan, IEEE.
[39] Ashik Kazi, Tai Dinh, and Wuyi Yue. “Spark-AHUS: An Adaptive Pure-Array Parallel Framework for High-Utility Sequential Pattern Mining”. The 4th International Conference on Sustainable Computing and Data Communication Systems (ICSCDS 2026), 15–17 December 2026, Gobichettipalayam, Erode, Tamil Nadu, India, IEEE.
[38] Tai Dinh. “From Welfare Estimation to Socioeconomic Typologies: A Machine Learning Approach Using Household Survey Data”. The 4th International Conference on Sustainable Computing and Data Communication Systems (ICSCDS 2026), 15–17 December 2026, Gobichettipalayam, Erode, Tamil Nadu, India, IEEE.
[37] Hewa Pathiranage Kaveesha Deshan, Tai Dinh, Michal Koren, and Wuyi Yue. “Sentiment Analysis of Higher-Education Online Reviews in Kansai, Japan”. The 9th International Conference on Pattern Analysis, Understanding and Learning (PAUL 2026), 3–5 December 2026, Poornima University, Jaipur, India, Springer CCIS.
[36] Bahing Rai Yelung and Tai Dinh. “A Data-Driven Framework for Survey-Aware and Geographically Robust Household Poverty Prediction in Nepal”. The 5th International Conference on Intelligent Computing, Information and Control Systems (ICOIICS 2026), 22–24 October 2026, Lalitpur, Nepal, IEEE.
[35] Tai Dinh. “XSPM: Structure-Constrained Sequential Pattern Mining for Real-World XML Collections”. The 5th International Conference on Intelligent Computing, Information and Control Systems (ICOIICS 2026), 22–24 October 2026, Lalitpur, Nepal, IEEE.
[34] Tai Dinh. “A Data-Driven Framework for Frequent Co-occurrence Mining in Heterogeneous Economic Data”. The 5th International Conference on Intelligent Computing, Information and Control Systems (ICOIICS 2026), 22–24 October 2026, Lalitpur, Nepal, IEEE.
[33] Madhab Bhattarai and Tai Dinh. “Mining Periodic Closed High-Utility Sequential Patterns”. 2026 Third International Conference on Innovations in Cybersecurity and Data Science (ICICDS 2026), IEEE, 2026, pp. 1658–1665.
[32] M. D. Madhuhansani, Tai Dinh, and Wuyi Yue. “A Data-Driven Machine Learning Framework for Short-Term Solar Irradiance Forecasting in Colombo, Sri Lanka Using NASA POWER Data”. 2026 Third International Conference on Innovations in Cybersecurity and Data Science (ICICDS 2026), IEEE, 2026.
[31] Ediribandanage Sachini Hansika Perera and Tai Dinh. “A Data-Driven Framework for Spatial Inequality Analysis of Household Living Conditions in Sri Lanka Using Grama Niladhari-Level Census Data”. 2026 Third International Conference on Innovations in Cybersecurity and Data Science (ICICDS 2026), IEEE, 2026, pp. 1577–1584.
[30] Shrestha Sheelu, Tai Dinh, Huiyi Xia, Wuyi Yue, and Van-Nam Huynh. “An Upper-Bound-Guided Silhouette Framework for Estimating the Optimal Number of Clusters in Categorical Data Clustering”. International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2026), Springer, 2026, pp. 117–132.
[29] Tharuka Herath, Nafisa Pratiwi, Tai Dinh, Deri Siswara, Arielle Ariane Nacar, Nayomi Vandergert, Indahwati, Anwar Fitrianto, and Wuyi Yue. “A Data Science Framework for Assessing Village Development and Sustainable Development Goals: A Case Study from West Java, Indonesia”. International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2026), Springer, 2026, pp. 133–148.
[28] Michal Koren, Tai Dinh, and Or Peretz. “Hub-Pruned Estimation for Quantum Markov Chains in Hub-Dominated Networks”. The International Conference on Quantum Computing Infrastructure & Technologies (QUANCOM 2026), 1–4 September 2026, University of Trento, Trento, Italy, Springer.
[27] Tai Dinh, Mia Ashraful, Partho Mahmudul Islam, and Ding Zou. “Bedtime Smartphone Use, Sleep Quality, and Daytime Concentration Among Graduate Students: A Qualitative Study”. Sleep Europe 2026: The 28th Congress of the European Sleep Research Society (ESRS), 20–23 October 2026, Maastricht, the Netherlands, Wiley (Abstract paper, Accepted).
[26] Tai Dinh. “A Data-Driven Framework for Classification and Retrieval of Inorganic Materials Synthesis Recipes”. The Second International Conference on Modern Sustainable Systems (CMSS 2026), 12–14 August 2026, Universiti Teknologi MARA, Malaysia, IEEE.
[25] Tai Dinh. “Stability-Guided Consensus Clustering of Superconducting Materials from Elemental Composition”. The Second International Conference on Modern Sustainable Systems (CMSS 2026), 12–14 August 2026, Universiti Teknologi MARA, Malaysia, IEEE.
[24] Tai Dinh. “Pattern Mining in Superconducting Materials Using Frequent, Closed, and Maximal Itemset Analysis”. The Second International Conference on Modern Sustainable Systems (CMSS 2026), 12–14 August 2026, Universiti Teknologi MARA, Malaysia, IEEE.
[23] Subedi Binod, Tai Dinh, and Wuyi Yue. “A Data-Driven Framework for Local-Level SDG Deprivation Profiling in Nepal Using Census-Based Household Indicators”. The 11th International Conference on Micro-Electronics, Electromagnetics and Telecommunications (ICMEET-2026), 13–15 October 2026, Sheraton Bali Kuta Resort, Bali, Indonesia, Springer.
[22] Roohul Amin and Tai Dinh. “Large Language Models for Missing Data Imputation: A Survey”. The 11th International Conference on Micro-Electronics, Electromagnetics and Telecommunications (ICMEET-2026), 13–15 October 2026, Sheraton Bali Kuta Resort, Bali, Indonesia, Springer.
[21] Dambura Hewage Ushamini Madhuthisari, Tai Dinh, and Wuyi Yue. “A Data-Driven Framework for Educational Resource Analysis Using Sri Lankan School Census Data”. The 11th International Conference on Micro-Electronics, Electromagnetics and Telecommunications (ICMEET-2026), 13–15 October 2026, Sheraton Bali Kuta Resort, Bali, Indonesia, Springer.
[20] Ashraful Mia and Tai Dinh. “Understanding Pre-Bedtime Smartphone Use and Sleep: A Qualitative Analysis Approach”. The 11th International Conference on Micro-Electronics, Electromagnetics and Telecommunications (ICMEET-2026), 13–15 October 2026, Sheraton Bali Kuta Resort, Bali, Indonesia, Springer.
[19] Tai Dinh. “A Mixed-Methods Framework for Analyzing Travel Reviews with LLMs and MAXQDA: A Case Study in Shiga, Japan”. The 11th International Conference on Micro-Electronics, Electromagnetics and Telecommunications (ICMEET-2026), 13–15 October 2026, Sheraton Bali Kuta Resort, Bali, Indonesia, Springer.
[18] Zinnorigne Hossain Mohammad, Tai Dinh, and Wuyi Yue. “Data-Driven Socio-Digital Sustainability Analysis Across Bangladesh Districts: Evidence from the 2022 Population Census”. The 10th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), 16–18 September 2026, Tribhuvan University Purwanchal Campus, Dharan, Nepal, IEEE.
[17] Kandel Yupesh and Tai Dinh. “Ten Years of Air Quality Monitoring in Nepal: A Data-Driven Analysis and Prediction”. The 10th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), 16–18 September 2026, Tribhuvan University Purwanchal Campus, Dharan, Nepal, IEEE.
[16] Keyash Azim Uddin and Tai Dinh. “A Data-Driven Framework for Educational Resource Profiling Across Bangladesh Using BANBEIS 2024 Institution Records”. The 10th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), 16–18 September 2026, Tribhuvan University Purwanchal Campus, Dharan, Nepal, IEEE.
[15] Walalawela Kaveesha Kavindi, Tai Dinh, and Wuyi Yue. “A Mixed-Methods Analysis of Online Reviews of Pediatric Care: A Case Study in Kyoto, Japan”. The 15th International Conference on Model and Data Engineering (MEDI 2026), 23–25 September 2026, Paphos, Cyprus, Springer.
[14] Htet Myat Aung, Tai Dinh, and Wuyi Yue. “Categorical Data Clustering with LLM-Derived Embeddings”. The 8th International Conference on Intelligent and Fuzzy Systems (INFUS 2026), 7–9 July 2026, Ankara, Turkey, Springer.
[13] Anuradha Jayawardana, Tai Dinh, and Wuyi Yue. “A Data-Driven Analysis of Trade Dependency, Value-Added Integration, and Economic Growth”. The 14th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2026), 8–9 June 2026, London, United Kingdom, Springer.
[12] Habib Farhaj, Tai Dinh, Rameesh Khan, Huynh Van Hong, and Wuyi Yue. “Interpretable Mining of Land-Use and Land-Cover Change Pathways from Multi-Temporal Categorical Maps”. The 14th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2026), 8–9 June 2026, London, United Kingdom, Springer.
[11] Tai Dinh, Bahing Rai Yelung, Sandesh Pathak, Chowdhury Salehin Haque, Pradhan Shrestha Naresh, Alif Ahetasamul Haque, and Philippe Fournier-Viger. “Pypatternminer: An Open-Source Python Library for Pattern Mining”. The 32nd International Conference on Information and Software Technologies (ICIST 2026), 15–16 October 2026, Kaunas, Lithuania, Springer.
[10] Shrestha Anup, Tai Dinh, Wong Hauchi, Roohul Amin, Ananta Dhungana, Dilshara Amarathunga, Daniil Lisik, and Ounnaci Iddir. “Large Language Models: A Review”. The Second International Conference on Applied Artificial Intelligence (2AI), 17–19 June 2026, Ganderbal, India, Springer.
[9] Tharaka Sathsarani Kariyawasam and Tai Dinh. “Tourism Demand Forecasting in Sri Lanka Using Statistical and Learning-Based Time-Series Models: Evidence from 2018–2026 Monthly Data”. The Second International Conference on Applied Artificial Intelligence (2AI), 17–19 June 2026, Ganderbal, India, Springer.
[8] Tai Dinh, Shehan Liyanaarachchi, Sameera Abeysinghe, Panchama Amani, Md. Jahid Hasan, Md Tanvir Chowdhury, Rameesh Khan, Roohul Amin, Ananta Dhungana, Md Anisuzzaman Khan, Kalungallge Rosha Ranpiyadi, Dipa Lamichhane, Rajbanshi Dipesh, Senaka Bandara, Ahmed Md Azaz, Tawhid Ahmed, Pratap Gurung, Sunar Suresh, Dilshara Amarathunga, and Kavindu Ravishan. “A Large-Scale Human-Annotated Travel Review Dataset for the Kansai Region of Japan”. The 8th International Conference on Smart Computing and Informatics (SCI-2026), 24–25 April 2026, Ha Noi, Viet Nam, Springer.
[7] Roohul Amin, Tai Dinh, and Wuyi Yue. “A Comparative Analysis of Large Language Model-Based Imputation for Categorical Data with Missing Values”. The 8th International Conference on Smart Computing and Informatics (SCI-2026), 24–25 April 2026, Ha Noi, Viet Nam, Springer.
[6] Sachini Madhushani, Rameesh Khan, Tai Dinh, Wuyi Yue, Ananta Dhungana, Van-Hong Huynh, and Zdena Dobesova. “A Deep Learning Framework for Land Use and Land Cover Change Detection”. The 8th International Conference on Smart Computing and Informatics (SCI-2026), 24–25 April 2026, Ha Noi, Viet Nam, Springer.
[5] Iresha Chathurani, Tai Dinh, Shehan Liyanaarachchi, and Wuyi Yue. “LLM-Based Sentiment Analysis of Travel Reviews: A Case Study of Kobe, Japan”. The 8th International Conference on Smart Computing and Informatics (SCI-2026), 24–25 April 2026, Ha Noi, Viet Nam, Springer.
[4] Mahmudul Islam Partho, Tai Dinh, Ramesh Khan, Huynh Van Hong, and Wuyi Yue. “On the Impact of Distance Metrics on Land Use and Land Cover Image Clustering”. The 8th International Conference on Smart Computing and Informatics (SCI-2026), 24–25 April 2026, Ha Noi, Viet Nam, Springer.
[3] Daud Santoso, Tai Dinh, Shehan Liyanaarachchi, and Wuyi Yue. “A Mixed-Methods Framework for Analyzing Travel Reviews with LLMs and MAXQDA: A Case Study in Osaka”. The 14th International Conference on Model and Data Engineering (MEDI 2025), 3–4 November 2025, Cairo, Egypt, Springer (to appear).
[2] Shehan Liyanaarachchi, Tai Dinh, Wuyi Yue, Trung Vo, and Le-Minh Nguyen. “Sentiment Analysis of Travel Reviews in Kyoto Using LLMs”. The 21st International Conference on Advanced Data Mining and Applications (ADMA 2025), 22–24 October 2025, Kyoto, Japan, Springer, 2025, pp. 244–256.
[1] Rameesh Khan, Zdena Dobesova, Yu Yang, and Tai Dinh. “Enhanced Feature-Based Clustering for Urban Land Use Pattern Detection”. The 16th International Conference on Knowledge and Systems Engineering (KSE 2024), 5–7 November 2024, Kuala Lumpur, Malaysia, IEEE, pp. 78–83.