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Future Technologies Conference

作者： Tseu Kwan Lee Koh Tieng Wei Abdul Azim Abd. Ghani Department of Software Engineering and Information System Faculty of Computer Science and Information Technology Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia

ISBN: (纸本)9781509041725

The development of Web applications has a crucial role as most organizations have their own corporate Web applications to meet the needs of their respective businesses. Different needs create different complexities which represent a new challenge to Web application development. In order to ensure the timely delivery of a project, software providers offering this service choose to use Open Sources (OSS) as an alternative. Since OSS consist of an existing framework that can be implemented directly into the application, how far does this affect the complexity of the effort estimation? A number of research papers have outlined the efforts made to refine the complexity of this field. However, to our best knowledge a systematic overview of the research done on Web application development that involves OSS usage does not appear to exist. Hence, the aim of this paper is to conduct a systematic literature review (SLR) of OSS Web application development. For this purpose, 34 papers from a total of 67 papers were identified and studied. The findings of this study indicate that (a) no research has been carried out on the field mentioned;(b) there is no early effort estimation model for Web projects that involve the usage of OSS. Therefore, this work provides an overview of the field besides identifying future research possibilities.

关键词： Effort estimation Open sources systematic literature review Web application development

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Knowledge of extraction from trained neural network by using decision tree

Knowledge of extraction from trained neural network by using...

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International Conference on Science in Information technology (ICSITech)

作者： Soleh Ardiansyah Mazlina Abdul Majid Jasni Mohamad Zain Department of Information Systems Kalimantan Institute of Technology Balikpapan Indonesia Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Gambang-Kuantan Malaysia

ISBN: (纸本)9781509017225

Inside the sets of data, hidden knowledge can be acquired by using neural network. These knowledge are described within topology, using activation function and connection weight at hidden neurons and output neurons. Is hardly to be understanding since neural networks act as a black box. The black box problem can be solved by extracting knowledge (rule) from trained neural network. Thus, the aim of this paper is to extract valuable information from trained neural networks using decision. Further, the Levenberg Marquardt algorithm was applied to training 30 networks for each datasets, using learning parameters and basis weights differences. As the number of hidden neurons increase, mean squared error and mean absolute percentage error decrease, and more time they need to deal with the dataset, that is result of investigation from neural network architectures. Decision tree induction generally performs better in knowledge extraction result with accuracy and precision level from 84.07 to 93.17 percent. The extracted rule can be used to explaining the process of the neural network systems and also can be applied in other systems like expert systems.

关键词： Biological neural networks Neurons Training Forecasting Predictive models Data mining Decision trees

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An evaluation of Error Level Analysis in image forensics 5

An evaluation of Error Level Analysis in image forensics

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5th IEEE International Conference on system Engineering and technology, ICSET 2015

作者： Warif, Nor Bakiah Abd Idris, Mohd. Yamani Idna Wahab, Ainuddin Wahid Abdul Salleh, Rosli Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781467367134

The advancement in digital image tampering has encouraged studies in the image forensics fields. The image tampering can be found over various image formats such as Joint Photographic Experts Group (JPEG). JPEG is the most common format that supported by devices and applications. Therefore, researchers have been studying the implementation of JPEG algorithm in the image forensics. In this paper, the Error Level Analysis (ELA) technique was evaluated with different types of image tampering, including JPEG compression, image splicing, copy-move and image retouching. From the experiment, the ELA showed reliability with JPEG compression, image splicing and image retouching forgery. © 2015 IEEE.

关键词： Image compression

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Evolutionary ensemble learning of fuzzy randomized neural network for posture recognition

Evolutionary ensemble learning of fuzzy randomized neural ne...

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Proceedings of the Biannual World Automation Congress

作者： Takenori Obo Naoyuki Kubota Chu Kiong Loo Dept. of System Design Tokyo Metropolitan University Tokyo Japan Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

Many works of human posture recognition have been published in the literature. Gesture and posture recognition by using Kinect Sensor is an important technique for many types of application. In this paper, we apply a neuro-fuzzy system for classification of human posture. A recent approach of learning algorithm for Single-layer hidden feedforward neural network (SLFN), known as Randomized Neural Network (RNN), has been attracting attention as a solution of several problems of traditional neural networks. However, the performance of RNN varies depending on the number of hidden neurons. In this paper, ensemble learning methods are therefore developed to deal with the issue, using Fuzzy-RNNs with various sizes of networks. Moreover, we utilize evolutionary algorithm to optimize the structure of ensembles. This paper discusses the effectiveness of the proposed approach, comparing with performance of some ensemble learning methods by using benchmark datasets and real measurement data of human posture.

关键词： Satellites Ionosphere Prediction algorithms Hidden Markov models

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An application program of fingerprint detection using wavelet transform for authentication 3

An application program of fingerprint detection using wavele...

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3rd Management and Innovation technology International Conference, MITiCON 2016

作者： Kwaochai, Aunchisa Pongyupinpanich, Surapong Areekul, Pratya San-Um, Wimol Intelligent Electronic System Research Laboratory Faculty of Engineering Thai-Nichi Institute of Technology Pattanakarn 37 Saunlaung Bangkok10250 Thailand Master Program of Forensic Informatics Ramkhamhang University Bangkapi Bangkok10240 Thailand Department of Mathematics Computer Science Chulachomklao Royal Military Academy Province Nakornnayok26001 Thailand

ISBN: (纸本)9781509041053

This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper proposes a fingerprint recognition technique based on wavelet-based texture pattern recognition method. By collecting incomplete fingerprints of 2 people with 6 images each. The original seven of uncompleted fingerprint images were undetected and only one was detected. After enhancing image quality using wavelet transform method, it was found that those of seven images were completed. The comparison method was a matching technique. This work focuses on the ability of the program and knowledge of image processing by studying algorithms of image processing. In design algorithm process, different technique enhancements were employed as well as the study of different of filters and algorithms based on existing research results from literature. © 2016 IEEE.

关键词： Wavelet transforms

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Genetic Optimized Fuzzy Extreme Learning Machine Ensembles for Affect Classification

Genetic Optimized Fuzzy Extreme Learning Machine Ensembles f...

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International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Wei Shiung Liew Chu Kiong Loo Takenori Obo Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Graduate School of System Design Tokyo Metropolitan University Hino Tokyo Japan

ISBN: (纸本)9781509026791

This paper presents a method for generating an optimized ensemble of fuzzy extreme learning machines (FELM) using a combination of genetic algorithms with a Bayesian Information Criterion (GA-BIC) fitness function. The operation of the FELM is equivalent to that of a fuzzy inference system, and is used for learning and classifying a given data set. The relative simplicity of the FELM structure enables a large number of FELMs to be generated in a short time. GA-BIC is used to select the minimum number of FELMs while maximizing the effectiveness of the classifier ensemble.

关键词： Artificial neural networks Genetic algorithms Training Neurons Sociology Statistics Genetics

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Home energy management by handling life event: Can residents manage energy by knowing their life events?

Home energy management by handling life event: Can residents...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Noriyuki Kushiro Takahiro Kondo Yuki Ogawa Toshiyasu Higuma Faculty of Computer Science and System Engineering Kyushu Institute of Technology Fukuoka Japan Living Environment Systems Laboratory Mitsubishi Electric Corp. Kamakura Kanagawa Japan

This paper describes an attempt for establishing an intelligent home energy management algorithm, which can response to residents' life pattern. A long-term data collection system has been constructed to confirm feasibility of the algorithm. Capability of energy demand prediction on the life events and feasibility of energy management by handling life events are discussed on the field data.

关键词： Energy management Power demand Prediction algorithms Data collection Power measurement Energy consumption Cleaning

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting system (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Computing lumen diameter of coronary arteries using segmented vessel's geometry and line tracking

Computing lumen diameter of coronary arteries using segmente...

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International Conference on Information Science (ICIS)

作者： K.A.S.H. Kulathilake L. Ranathunga G.R. Constantine N.A. Abdullah Department of Information Technology University of Moratuwa Moratuwa Sri Lanka Department of Clinical Medicine Faculty of Medicine University of Colombo Sri Lanka Department of Computer System and Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9781509019885

Coronary cine-angiography is an invasive medical image modality which is widely used in Interventional Cardiology for the detection of luminal obstructions in Coronary Arteries (CA). Angiography based stenosis diagnosis is done as a subjective process and results in overestimations or underestimations of detected stenosis. Therefore, this diagnosis results consequence to the patients' quality of life imperfectly. This study elaborates a novel method for calculating the lumen diameter of CA recorded in the coronary angiograms to overcome the negative effects in subjective coronary analysis. The proposed method is based on the segmented vessels' geometry and vessel path tracking and consists of four major implementation phases namely; preprocessing, segmentation, vessel path tracking and diameter calculation. The result of the proposed method has clearly emphasized its' ability to detect vessel diameter along the vessel skeleton and it assists clinicians to objectively detect and analyze the stenosis in main CA. Moreover, this proposed method can be used to further enhance the coronary cine angiography to assess the stenosis based on the functional significance of the CA.

关键词： Skeleton Arteries Visualization Image segmentation Catheters Geometry Angiography

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