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Modularity detection in protein-protein interaction networks

BMC Research Notes 2011年第1期4卷 1-6页

作者： Narayanan, Tejaswini Gersten, Merril Subramaniam, Shankar Grama, Ananth Department of Electrical and Computer Engineering University of California San Diego United States Graduate Program in Bioinformatics and Systems Biology University of California San Diego United States Department of Bioengineering University of California San Diego United States Department of Computer Science Purdue University West Lafayette IN United States

Background: Many recent studies have investigated modularity in biological networks, and its role in functional and structural characterization of constituent biomolecules. A technique that has shown considerable promise in the domain of modularity detection is the Newman and Girvan (NG) algorithm, which relies on the number of shortest-paths across pairs of vertices in the network traversing a given edge, referred to as the betweenness of that edge. The edge with the highest betweenness is iteratively eliminated from the network, with the betweenness of the remaining edges recalculated in every iteration. This generates a complete dendrogram, from which modules are extracted by applying a quality metric called modularity denoted by Q. This exhaustive computation can be prohibitively expensive for large networks such as Protein-Protein Interaction Networks. In this paper, we present a novel optimization to the modularity detection algorithm, in terms of an efficient termination criterion based on a target edge betweenness value, using which the process of iterative edge removal may be terminated. Results: We validate the robustness of our approach by applying our algorithm on real-world protein-protein interaction networks of Yeast, *** and Drosophila, and demonstrate that our algorithm consistently has significant computational gains in terms of reduced runtime, when compared to the NG algorithm. Furthermore, our algorithm produces modules comparable to those from the NG algorithm, qualitatively and quantitatively. We illustrate this using comparison metrics such as module distribution, module membership cardinality, modularity Q, and Jaccard Similarity Coefficient. Conclusions: We have presented an optimized approach for efficient modularity detection in networks. The intuition driving our approach is the extraction of holistic measures of centrality from graphs, which are representative of inherent modular structure of the underlying network, and the applic

关键词： Biological Network Jaccard Index Input Network High Betweenness Jaccard Similarity Coefficient

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Importance sampling for general hybrid Bayesian networks

Importance sampling for general hybrid Bayesian networks

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11th International Conference on Artificial Intelligence and Statistics, AISTATS 2007

作者： Yuan, Changhe Druzdzel, Marek J. Department of Computer Science and Engineering Mississippi State University Mississippi State MS 39762 United States Decision Systems Laboratory School of Information Sciences and Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States

Some real problems are more naturally modeled by hybrid Bayesian networks that consist of mixtures of continuous and discrete variables with their interactions described by equations and continuous probability distributions. However, inference in such general hybrid models is hard. Therefore, existing approaches either only deal with special instances, such as Conditional Linear Gaussians (CLGs), or approximate a general model with a restricted version and then perform inference on the simpler model. However, results thus obtained highly depend on the quality of the approximations. This paper describes an importance sampling-based algorithm that directly deals with hybrid Bayesian networks constructed in the most general settings and guarantees to converge to the correct answers given enough time.

关键词： Importance sampling

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Experimental measurement of growth patterns on fossil corals:Secular variation in ancient Earth-Sun distances

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Chinese science Bulletin 2010年第35期55卷 4010-4017页

作者： ZHANG WeiJia1,3,4,LI ZhengBin2,3 & LEI Yang1 1 department of Physics,Peking University,Beijing 100871,China 2 department of Electrical engineering and computer science,Peking University,Beijing 100871,China 3 State Key Laboratory of Advanced Optical Communication systems & Networks,Peking University,Beijing 100871,China 4 Committee of Yuanpei Honors program,Peking University,Beijing 100871,China Department of Physics Peking University Beijing 100871 China State Key Laboratory of Advanced Optical Communication Systems & Networks Peking University Beijing 100871 China Committee of Yuanpei Honors Program Peking University Beijing 100871 China Department of Electrical Engineering and Computer Science Peking University Beijing 100871 China

In recent years,much attention has been given to the increase in the Earth-Sun distance,with the modern rate reported as 5-15 m/cy on the basis of astronomical ***,traditional methods cannot measure the ancient leaving rates,so a myriad of research attempting to provide explanations were met with unmatched *** this paper we consider that the growth patterns on fossils could reflect the ancient Earth-Sun *** mechanical analysis of both the Earth-Sun and Earth-Moon systems,these patterns confirmed an increase in the Earth-Sun *** a large number of well-preserved specimens and new technology available,both the modern and ancient leaving rates could be measured with high precision,and it was found that the Earth has been leaving the Sun over the past 0.53 billion *** Earth's semi-major axis was 146 million kilometers at the beginning of the Phanerozoic Eon,equating to 97.6% of its current *** modern leaving rates are 5-14 m/cy,whereas the ancient rates were much *** results indicate a special expansion with an average expansion coefficient of 0.57H0 and deceleration in the form of Hubble *** the basis of experimental results,the Earth's semi-major axis could be represented by a simple formula that matches fossil measurements.

关键词：地球太阳古代距离生长模式实验石珊瑚量化

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Gastritis Diagnosis Expert System Using Android-Based Certainty Factor Method

Gastritis Diagnosis Expert System Using Android-Based Certai...

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International Seminar on Research of Information Technology and Intelligent systems (ISRITI)

作者： R. Rizal Isnanto Purwanto Yudi Eko Windarto Annas Setiawan Information Systems Doctoral Program Diponegoro University Semarang Indonesia Computer Engineering Department Diponegoro University Semarang Indonesia

In the modern era, an increasing number of diseases are emerging because of human lifestyle choices and bacterial transmission. Gastritis, characterized by inflammation in the stomach lining leading to frequent abdominal pain, is one such ailment. Recognizing the significance of addressing these health issues, there is a need for an expert system application specifically designed for diagnosing gastritis. The primary objective is to disseminate information to the public regarding the early symptoms of gastritis, promoting awareness from a young age. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The diagnostic process employs the Certainty Factor (CF) method to ensure accurate results. By utilizing symptom CF values chosen by the user, the Certainty Factor approach facilitates a diagnosis based on calculations established by medical specialists. The research culminates in the development of an expert system application capable of accurately diagnosing the disease Android based. The accuracy rates for the first, second, and third test cases are reported as 98.848%, 99.8464%, and 99.99115264%, respectively. System testing, conducted through black-box testing, validates the application's functionality, demonstrating a 100% success rate for each component.

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RJSSim: A reconfigurable job scheduling simulator for parallel processing learning 33

RJSSim: A reconfigurable job scheduling simulator for parall...

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33rd Annual Frontiers in Education, FIE 2003

作者： Góes, Luís F.W. Martins, Carlos A.P.S. Pontifical Catholic University of Minas Gerais Post-Graduation Program in Electrical Engineering Computational and Digital Systems Laboratory Belo HorizonteMG Brazil Pontifical Catholic University of Minas Gerais Computer Science Department Post-Graduation Program in Electrical Engineering Computational and Digital Systems Laboratory Belo HorizonteMG Brazil

ISBN: (纸本)0780379616

In this work, we present and analyze the use of a reconfigurable job scheduling simulator called RJSSim as an aid tool for parallel processing learning. This software is a functional and performance Java-based simulator of job scheduling policies. Our objectives are: to present RJSSim;to show the use of RJSSim and reconfigurability concepts for parallel processing learning. First, we present a prototype of RJSSim and the reconfigurability concept. Then we describe two case studies remarking the main parallel processing concepts and skills students can learn. In the first case study, we analyze two parallel algorithm models. In the second, we do some performance tests among parallel (reconfigurable) scheduling policies and architectures. Then, we analyze the performance through some metrics like response time, idle time etc. Finally we discuss and analyze the use of RJSSim for parallel processing learning. Our main contribution is: an implementation of RJSSim for parallel processing learning. © 2003 IEEE.

关键词： Parallel algorithms

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Developing an Expert System for Mobile-based Gastroenteritis Detection Using ESDLC and Best First Search Methods

Developing an Expert System for Mobile-based Gastroenteritis...

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International Conference on Informatics and Computing (ICIC)

作者： R. Rizal Isnanto Catur Edi Widodo Ike Pertiwi Windasari Misik Puspajati Saputri Information Systems Doctoral Program Diponegoro University Semarang Indonesia Computer Engineering Department Diponegoro University Semarang Indonesia

Gastroenteritis is a common gastrointestinal disorder with varying degrees of severity, including cases without dehydration, mild dehydration, moderate dehydration, and severe dehydration. This research focuses on the development of a mobile-based expert system for detecting gastroenteritis, capable of distinguishing between these different dehydration levels. The methodology employed integrates the Extreme Structure Development Life Cycle (ESDLC) and the Best First Search algorithm. The expert system is designed to provide swift and accurate responses to users inputting symptoms, categorizing gastroenteritis cases based on the severity of dehydration. The application of ESDLC ensures a structured and organized development process, while the Best First Search method enhances the efficiency of the diagnostic process, facilitating timely and precise recommendations. Accessible through mobile platforms, the system allows users to input symptoms conveniently and receive rapid recommendations. Rigorous testing and evaluation affirm the system's high accuracy in discerning dehydration levels in gastroenteritis patients. In conclusion, the developed mobile-based expert system exhibits promising potential for advancing diagnostic services, particularly in the categorization of dehydration levels in gastroenteritis cases. The successful implementation of ESDLC and Best First Search paves the way for similar solutions in other healthcare domains, contributing positively to early and accurate disease management efforts. This innovation marks a significant stride towards improving healthcare technology for enhanced decision support in gastroenteritis diagnosis.

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Expert System for Diagnosis of Diphtheria Disease Using Fuzzy Logic

Expert System for Diagnosis of Diphtheria Disease Using Fuzz...

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International Seminar on Research of Information Technology and Intelligent systems (ISRITI)

作者： R.Rizal Isnanto Mustafid Agung Budi Prasetijo Safira Isna Fitria Ali Information Systems Doctoral Program Diponegoro University Semarang Indonesia Computer Engineering Department Diponegoro University Semarang Indonesia

Diphtheria is an infectious disease that affects the upper respiratory system and throat, arising suddenly and caused by Corynebacterium diphtheriae. The symptoms of diphtheria such as fever, swollen neck and slimy nose are often interpreted as influenza or laryngitis. Diphtheria is a contagious and deadly disease that requires specialized and rapid treatment and care. In today's technological era, it can be overcome with a system that can diagnose diphtheria like a doctor's diagnosis ability commonly called an expert system. This study describes the application of an expert system to diagnose diphtheria disease. The research method used is the web-based Expert System Development Life Cycle (ESDLC). The method used to process input values is Forward Chaining. Fuzzy Tsukamoto to calculate the input value from the user. The research has been tested with Blackbox testing showing the results that the expert system works well and accuracy testing with 92% results. The results show effectiveness with a satisfactory level of accuracy in detecting diphtheria disease. This research contributes to the development of expert systems in the health sector with a focus on diagnosing diphtheria disease using a fuzzy logic approach.

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Trends, Opportunities, and Challenges in Detecting Depressive Disorders Through Mobile Devices: A Review 2

Trends, Opportunities, and Challenges in Detecting Depressiv...

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2nd International Conference on computer System, Information Technology, and Electrical engineering, COSITE 2023

作者： Elwirehardja, Gregorius Natanael Isnan, Mahmud Perbangsa, Anzaludin Samsinga Muchtar, Kahlil Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mahmud Isnan Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350343069

Depressive Disorders (DD) is one of the most prevalent mental disorders in the world that may lead to suicide cases. To prevent the latter, ubiquitous early detection systems may be effective. Recent studies have since researched the development of such systems by exploiting several forms of data, including video, audio, Ecological Momentary Assessments (EMA), and passive sensing data using sensors embedded in mobile devices. To summarize the trends, opportunities, and existing challenges in this field, this study reviewed 15 papers to answer four research questions. EMA was the most popular data to be used in this task, but other approaches, such as using video, audio, and typing behaviors, may be considered due to the subjectivity of EMA. These data were typically recorded using smartphones and analyzed using Machine Learning (ML). However, most of the developed systems had yet to be implemented. Overall, it was concluded that further studies may need to explore usages of more objective data in multimodal approaches as well as consider using Mobile Cloud Computing (MCC) to deploy these systems to provide more effective and efficient diagnoses. Future studies must also take into account the existing challenges of the data and infrastructures, such as the weaknesses of several data types, limitations of mobile devices, as well as the challenges of diagnosis approaches. © 2023 IEEE.

关键词： Machine learning

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Improvement of Spatial Ambiguity in Multi-Channel Speech Separation Using Channel Attention

Improvement of Spatial Ambiguity in Multi-Channel Speech Sep...

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2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021

作者： Hong, Qian-Bei Wu, Chung-Hsien Nguyen, Thanh Binh Wang, Hsin-Min National Cheng Kung University and Academia Sinica Graduate Program of Multimedia Systems and Intelligent Computing Tainan Taiwan National Cheng Kung University Department of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9789881476890

Multi-channel speech separation has been successfully applied in a complex real-world environment such as the far-field condition. The common solution to deal with the far-field condition is using a multi-channel signal captured by a structured microphone array and leveraging the inner difference between channels to enhance the speech separation performance. The spatial feature has been widely used in recent speech separation research. This feature appears to be insufficient when the location information becomes ambiguous. This is known as the spatial ambiguity problem. In order to deal with the spatial ambiguity problem, this study proposes an attention mechanism for the Temporal-Spatial Neural Filter (TSNF), in which the channel attention on merged features and the feature map of 1D convolution block in the temporal convolution network is proposed. The proposed method is evaluated on the multi-channel reverberant dataset which is built based on the WSJ0-2mix dataset. The dataset is simulated in the real-environment room by using the Room Impulse Response generator. In the experimental results, the proposed methods produced the SI -SNR improvement of about 1.2dB in close speakers' case, while a small decrease of 0.1dB in other cases. © 2021 APSIPA.

关键词： Convolution

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Awareness and comprehension in software/systems engineering practice and education: Trends and research directions

Awareness and comprehension in software/systems engineering ...

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26th Brazilian Symposium on Software engineering, SBES 2012

作者： Schots, Marcelo Werner, Cláudia Mendonça, Manoel Systems Engineering and Computing Program COPPE/UFRJ Federal University of Rio de Janeiro Rio de Janeiro Brazil Computer Science Department Federal University of Bahia Rio de Janeiro Brazil

ISBN: (纸本)9780769548685

The creation of tools, techniques and methodologies to support the manipulation of large data sets has been receiving special attention of both scientific and industrial communities, in order to discover new ways of dealing with the underlying information, including learning purposes, identification of patterns, decision making support, amongst others. However, making use of computing resources to enhance awareness and understanding of software information and the software itself is still a challenge in software/systems engineering, since it involves the identification of suitable mechanisms, adequate abstractions, and studies on stimulation of the human perceptive and cognitive abilities. This paper presents some of the challenges in this context, based on current trends of software development lifecycle, program comprehension, and software engineering education. At the end, a special focus is given on ongoing research on using and improving current mechanisms for supporting software reuse practices and software comprehension in general. © 2012 IEEE.

关键词： computer software reusability

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