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6th International Conference on computer science and Computational Mathematics, ICCSCM 2017

作者： Amidi, A. Jabar, M. Jusoh, Y.Y. Abdullah, R. Department of Software Engineering and Information System Faculty of Computer Science and Information Technology University Putra Malaysia UPM Serdang43400 Malaysia

With the rising popularity of social media in the past few years, several researches ratiocinate that this type of interactive and collaborative technology could be a beneficial tool for the sharing of tacit knowledge. Nevertheless, very few literatures have tackled the subject of how social media could facilitate tacit knowledge sharing among medical practitioners, and what are its contributions in the area. Thus, the factors that drive individuals to share tacit knowledge need to be investigated further and included in literature. Through a systematic literature review, this study proposes seven enabling conditions which could potentially facilitate the sharing of tacit knowledge. TAM was applied as a novelty in this study in investigating the factors influencing knowledge sharing via social media, whilst taking into account the mediation effects of Attitude in social media usage. This study uncovered an important correlation between virtual settings and the conversion of tacit knowledge, which affects organizational members who are not co-located physically but have a crucial need for sharing information. © Published under licence by IOP Publishing Ltd.

关键词： Social networking (online)

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A Novel Mutual Information based Ant Colony Classifier 5

A Novel Mutual Information based Ant Colony Classifier

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2017 International Conference on Progress in Informatics and Computing(PIC)

作者： Hang Yu Xiaoxiao Qian Yang Yu Jiujun Cheng Ying Yu Shangce Gao College of Computer Science and Technology Taizhou University Faculty of Engineering University of Toyama Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

ISBN: (纸本)9781538619797;9781538619780

By constructing a list of IF-THEN rules, the traditional ant colony optimization(ACO) has been successfully applied on data classification with not only a promising accuracy but also a user comprehensibility. However, as the collected data to be classified usually contain large volumes and redundant features, it is challenging to further improve the classification accuracy and meanwhile reduce the computational time for *** paper proposes a novel hybrid mutual information based ant colony algorithm(mrAM+) for classification. First, a maximum relevance minimum redundancy feature selection method is used to select the most informative and discriminative attributes in a dataset. Then, we use the enhanced ACO classifier(i.e., AM+)to perform the classification. Experimental results show that the proposed mrAM+ outperforms other seven state-of-art related classification algorithms in terms of accuracy and the size of model.

关键词： ant colony optimization mutual information classification data mining feature selection

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A Comparison of Forecasting Building Material Inventory between Backpropagation Neural Network And Arima

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IOP Conference Series: Materials science and engineering 2019年第1期528卷

作者： I A Soenandi C Hayat Department of Industrial Engineering Faculty of Engineering & Computer Science Krida Wacana Christian University Tanjung Duren Raya No. 4 Jakarta 11470 Indonesia Department of Information System Faculty of Engineering & Computer Science Krida Wacana Christian University Tanjung Duren Raya No. 4 Jakarta 11470 Indonesia

The demand for forecasting task is very important to determine the number of stocks efficiently. This process should accommodate the demand for a company's product or service and control the inventory level. Especially for products such as building materials that needed capitals to buy and wide space to keep it safe. This research has objective to minimize the excessive amount of product in inventory and minimize loss in sales. This study was compared between a method named Back Propagation Neural Network (BPNN) that known as one of the most accurate and widely used forecasting model and ARIMA as a time series model to find the most accurate in forecasting of inventory. In this case, the model of BPNN used 6 input neurons as a monthly period of sale, the price of the product, amount of historical selling, an approximation of project renovation, an approximation of new project building and number of a competitor. And for Arima method we have three trials of tentative models. To compare the accuracy between them, we used the performance criteria such as MAD, MAE, RMSE, RRSE and RAE. In this research, we obtained that forecasting with BPNN is more accurate than ARIMA with error prediction of 19.6, 19.6, 30.4, 0.6, 0.5 for those performance criteria consecutively.

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Lemma functions for frama-C: C programs as proofs

arXiv

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arXiv 2018年

作者： Volkov, Grigoriy Mandrykin, Mikhail Efremov, Denis Faculty of Computer Science National Research University Higher School of Economics Moscow Russia Software Engineering Department Ivannikov Institute for System Programming Russian Academy of Sciences Moscow Russia

This paper describes the development of an auto-active verification technique in the Frama-C framework. We outline the lemma functions method and present the corresponding ACSL extension, its implementation in Frama-C, and evaluation on a set of string-manipulating functions from the Linux kernel. We illustrate the benefits our approach can bring concerning the effort required to prove lemmas, compared to the approach based on interactive provers such as Coq. Current limitations of the method and its implementation are discussed. Copyright © 2018, The Authors. All rights reserved.

关键词： Formal verification

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Collective intelligent information and database systems

Collective intelligent information and database systems

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作者： Nguyen, Ngoc-Thanh Núñez, Manuel Trawiski, Bogdan Division of Knowledge and System Engineering for ICT Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Computer Science Complutense University of Madrid Spain Faculty of Computer Science and Management Wroclaw University of Science and Technology Poland

Collective intelligence is most often understood as group intelligence which arises on the basis of intelligences of the group members. This paper presents an overview of application of collective intelligence methods in knowledge engineering and in processing collective data. It also introduces papers included in this issue. © 2017 - IOS Press and the authors. All rights reserved.

关键词： Intelligent systems

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Analysis of performance comparison between Software-Based iSCSI SAN and Hardware-Based iSCSI SAN

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Journal of Physics: Conference Series 2019年第1期1351卷

作者： Dwi Ely Kurniawan Imam Ahmad Muhammat Rasid Ridho Fendi Hidayat Ahmad Anggra Js Department of Informatics Engineering Politeknik Negeri Batam Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Department of Information System Universitas Putera Batam Department of Information System Universitas Batam Department of Multimedia and Network Engineering Politeknik Negeri Batam

Nowadays computer data grows rapidly and make a lot of institutions and companies looking for storage solutions that are safe, reliable and trustworthy. One of the solutions is to implement a Storage Area Network (SAN). In this study, the authors chose the iSCSI protocol as an object for analyzing the performance of the SAN server based on software and hardware. The RAID type used are RAID 5 and RAID 10, while the parameters used are Input Output per Second (IOPS), throughput and average latency with workloads 4 KB, 8 KB, and 256 KB. The tests performed on the network running Link Aggregation (LAG) or network without LAG. From the test results, it is seen that a SAN network running LAG have increased throughput by 89.57 MBps. The best IOPS performance was achieved by Software-Based iSCSI SAN with a value of 26729.48 IOPS. The best throughput performance is achieved by Hardware-Based iSCSI SAN with a value of 118.55MBps. The best latency performance achieved by Software-Based iSCSI SAN with a value of 2.01ms.

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A Direct Proof of Improved Biased Random Walk with Gastric Cancer Dataset

A Direct Proof of Improved Biased Random Walk with Gastric C...

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International Conference on Applied Mathematics & computer science

作者： Choon Sen Seah Shahreen Kasim Mohd Farhan Md Fudzee Mohd Saberi Mohamad Rd Rohmat Saedudin Deden Witarsyah Rohayanti Hassan Mohd Arfian Ismail Rodziah Atan Soft Computing and Data Mining Centre Faculty of Computer Sciences and Information Technology Universiti Tun Hussein Onn Malaysia Faculty of Creative Technology and Heritage Universiti Malaysia Kelantan School of Industrial Engineering Telkom University Laboratory of Biodiversity and Bioinformatics Universiti Teknologi Malaysia Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Department of Software Engineering & Information System Faculty of Computer Science and Information Technology University Putra Malaysia (UPM)

ISBN: (数字)9781728132587

ISBN: (纸本)9781728132594

The relationship between the weight of a single genes and the connection between the genes had been studied. Chemistry and physical sciences have proved the attraction between molecules. Molecules are attracted to each other by bond. This paper is presented to disclose the relationship between weight and connectivity of nodes with biased random walk. An equation of biased random walk which named as significant directed random walk is formed to enhance the connectivity of nodes in directed graph via weigh. To be completely biased to the random walk, references data is implement as directed graph. Weight of genes will be used as one of the parameter in the formula. While the adjacency matrix is further enhanced by Warshall's algorithm to increases the accessibility of nodes via vector. The evolution of random walk is disclosed in this paper as well. Significant directed random walk will be used to prove the importance of weight in this paper. Comparison of the result between biased random walk is presented to prove the enhancement of random walk.

关键词： Biased random walk Cancer classification Gene expression dataset Random walk cancer classification Biased Ganglia one-parameter Mentoring Physical science

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Energy optimization of sustainable Internet of Things (IoT) systems using an energy harvesting medium access protocol

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IOP Conference Series: Earth and Environmental science 2019年第1期268卷

作者： Shaik Shabana Anjum Rafidah Md Noor Ismail Ahmedy Mohammad Hossein Anisi Department of Computer System and Technology Faculty of Computer Science and Information technology University of Malaya 50603 Malaysia. Centre for Mobile Cloud Computing Research (C4MCCR) Faculty of Computer Science and Information technology University of Malaya 50603 Malaysia. School of Computer Science and Electronic Engineering University of Essex Colchester UK

The process of modelling the energy expenditure for IoT systems is distinct when compared to Wireless Sensor Networks (WSN), due to a number of factors and metrics. Few of such factors to mention are the IoT layers being different from the Open system Interconnection (OSI) with communication protocols like IPv6 Low power Wireless Personal Area Networks (6LoWPAN), Routing for Low Power and Lossy networks (RPL) and Constrained Application Protocol (CoAP). This leads to the demand for designing efficient Medium Access Control (MAC) protocols to serve the purpose of balance between the performance of the system and minimum energy consumption. The challenge of compatibility of MAC protocols for IoT deployment needs to be addressed. The proposed work is aimed at developing energy efficient framework for optimal balance between energy consumed by connected devices (sensor networks) in a complex and time-critical IoT system through performance monitoring of underlying communication technologies. It also focuses to address the trade-off between energy expenditure and performance of the network for the communicating nodes. An Energy Harvesting MAC protocol is designed and developed after modelling of the nodes using Reinforcement Learning (RL) for time critical IoT systems. The results have shown that the energy expenditure of the IoT devices is considerably minimized and the performance is increased by nearly 80% when compared to the state-of-art energy harvesting solutions for sustainable IoT systems. This research also plays a significant role in matching the energy predictions and the experimentations that validate the IoT systems in a real-world scenario.

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IMAP-CampUS: Developing an intelligent mobile augmented reality program on campus as a ubiquitous system 17

IMAP-CampUS: Developing an intelligent mobile augmented real...

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9th International Conference on computer and Automation engineering, ICCAE 2017

作者： Alqahtani, Hamed Kavakli, Manolya Department of Information System Faculty of Computer Science King Khalid University Aseer Abha62529 Saudi Arabia Department of Computing Faculty of Science and Engineering Macquarie University SydneyNSW2109 Australia

ISBN: (纸本)9781450348096

Augmented Reality (AR) offers a combination of physical and virtual objects, drawing on the strengths of each. Therefore, it is different from virtual reality since it permits users to sight the real world enhanced with virtual objects. Thus, AR technology holds potential to support users with valuable information about the surrounding area. In this paper, we demonstrate the development of an AR app that provides the students with rich information about the buildings nearby. The application, which we name "iMAP-CampUS", is designed to assist students at Macquarie University in locating places of interest close to them by moving the camera of the device in all probable directions to overlay information of places around them. The iMAP-CampUS has been developed for both iOS and Android platforms and run on smartphones and tablets with different screen sizes. © 2017 ACM.

关键词： Augmented reality

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An influence analysis of the number of members on the quality of knowledge in a collective

An influence analysis of the number of members on the qualit...

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作者： Nguyen, Ngoc Thanh Nguyen, Van Du Hwang, Dosam Division of Knowledge and System Engineering for ICT Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Computer Science and Management Wroclaw University of Science and Technology Poland Department of Computer Engineering Yeungnam University Korea Republic of

Collective knowledge is understood as the common knowledge state of a collective consisting of autonomous units. The knowledge states referred from these autonomous units to some degree reflect the real knowledge state of a subject in the real world, but it is not known to what degree because of incompleteness and uncertainty. Although collective knowledge determination is an important task because these knowledge states can be different from each other, there exists another important issue with its quality. The quality of collective knowledge is based on the difference between the real knowledge state and the collective knowledge. In this study, we investigate the influence of the number of collective members on the quality of collective knowledge. Through experimental analysis, the larger collective we use, the better the quality of collective knowledge will be. In other words, the large number of collective members positively affects the quality of collective knowledge. Besides, some theorems about the relationship between the collective knowledge and the knowledge states in a collective, the influence of adding or removing members on the quality of collective knowledge are also proved. © 2017 - IOS Press and the authors. All rights reserved.

关键词： Quality control

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