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Über dieses Buch

This book constitutes the proceedings of the 5th International Conference on Context-Aware Systems and Applications, ICCASA 2016, held in Thu Dau Mot, Vietnam, in November 2016.
The 22 revised full papers presented were carefully selected from 35 submissions and cover a wide spectrum in the area of Context-Aware-Systems (CAS). CAS is characterized by its self- facets such as self-organization, self-configuration, self-healing, self-optimization, self-protection, where context awareness used to dynamically control computing and networking functions. The overall goal of CAS is to realize nature-inspired autonomic systems that can manage themselves without direct human interventions.

Inhaltsverzeichnis

Frontmatter

Modelling and Reasoning About Context-Aware Agents over Heterogeneous Knowledge Sources

Abstract
This paper presents a conceptual framework and multi-agent model for context-aware decision support in dynamic smart environments based on heterogeneous knowledge sources. The framework relies on distributed ontologies and allows us to model context-aware agents which reason using rules that are derived from ontologies using the notion of multi-context systems. The use of the proposed framework is illustrated using a simple system developed from ontologies considering three different smart environment domains.
Hafiz Mahfooz Ul Haque, Abdur Rakib, Ijaz Uddin

Context-Based Project Management

Abstract
Context-based computing has become an integral part of the software infrastructure of modern society. Better software are made adaptive to suit the surrounding environment. Context-based applications best fit into environments that undergo constant and frequent changes. Temperature management, Time management, GPS are just few examples where context-awareness becomes inevitable. Project Management is another domain that requires constant monitoring. The current tools of project management handle data gathering, plotting, and organizing, but requires high-level of human intervention to analyze data and integrate it. To the extent of our knowledge there is no efforts to introduce context awareness to project management domain. In this work, we introduce context and formally model project context using FCA. Additionally, we provide the results of the full implementation of our approach on a real-world software project. We show that our approach can formally answer queries that traditional tools could not answer. Also, we introduce a brief comparison between our approach and traditional project management software. Finally, we show that our approach can improve project management tools and minimize the effort spent by project managers.
Ammar Alsaig, Alaa Alsaig, Mubarak Mohammad

Organisational Knowledge Sharing Using Social Networking Sites: Risks, Benefits and Barriers

Abstract
Augmented globalisation and the increased speed of operations in the business world have led to dramatic changes in organisational life; the traditional way of work is no longer competitive. It is assumed that an organisation that knows how to communicate and share knowledge quickly will always have an extra competitive advantage in comparison to others who do not participate in knowledge collaboration. Social Networking Sites (SNS) have created a new method of knowledge exchange and introduced new abilities for an organisation to share knowledge. This research investigates the role of SNS in organisational knowledge sharing through a review of concepts and theories from different disciplines. We explore and investigate how SNS are used to facilitate storage, access and knowledge sharing in organisational contexts. The research will conclude with the discussion on the risks, benefits and barriers to implementing SNS for knowledge sharing.
Valeria Sadovykh, David Sundaram

Context-Adaptive Business Networks

Abstract
Businesses are facing turbulences in an environment that includes social, political, technical and economic challenges. Traditional business networks lack the adaptability to rapidly reconfigure their strategy, people, structure, business processes, and systems to respond to such challenges. In this paper we analyse structures and limitations of traditional business networks (Sect. 2). Based on the literature on adaptive business networks (ABN) which have been discussed for about two decades (Sect. 3) we outline the most important conceptualisations of ABN. In order to emphasise the integrated perspective on the strategic, social, structural, business process, and information systems level - which we consider to be essential for adaptability - we create the term “Context-Adaptive Business Networks (CABN)” (Sect. 4). We discuss the necessary features of context-adaptability in more detail (Sect. 5) and conclude with suggestions how this context-adaptability can be achieved on all five levels (Sect. 6).
Jing Jing He, Elke Wolf, David Sundaram

Context-Aware Hand Pose Classifying Algorithm Based on Combination of Viola-Jones Method, Wavelet Transform, PCA and Neural Networks

Abstract
In this paper we propose a novel context-aware algorithm for hand poses classifying. The proposed algorithm based on Viola-Jones method, wavelet transforms, PCA and neural networks. At first, the Viola-Jones method is used to find the location of hand pose in images. Then the features of hand pose are extracted using combination of wavelet transform and PCA. Finally, these extracted features are classified by multi-layer feedforward neural networks. In this proposed algorithm, for each training hand pose we create one neural network, which will determine whether an input hand pose is training hand pose or not. In order to test the proposed algorithm, we use known Cambridge Gesture database and divide it into 5 parts with difference light contrast conditions. The experimental results show that the proposed algorithm effectively classifies the hand pose in difference light contrast conditions and competes with state-of-the-art algorithms.
Ngoc Hoang Phan, Thi Thu Trang Bui

A Load Balancing Game Approach for VM Provision Cloud Computing Based on Ant Colony Optimization

Abstract
The resource management on cloud computing is a major challenge. Resource management in cloud computing environment can be divided into two phases: resource provisioning and resource scheduling. In this paper, we propose VM provision solution ensure to balance the goals of the party stakeholders including service providers and customers based on game theory. The optimal or near optimal solution is approximated by meta-heuristic algorithm – Ant Colony Optimization (ACO) based on Nash equilibrium. In the experiments, the Ant System, Max-Min Ant System, Ant Colony System algorithm are applied to solve the game. The simulation results show how to use the coefficients to achieve load balancing in VM provision. These coefficients depend on objectives of cloud computing service providers.
Khiet Thanh Bui, Tran Vu Pham, Hung Cong Tran

Optimizing the Algorithm Localization Mobile Robot Using Triangulation Map

Abstract
The problem of minimum distance localization in environments that may contain self-similarities is addressed. A mobile robot is placed at an unknown location inside a 2D self-similar polygonal environment P. The robot has a map of P and can compute visibility data through sensing. However, the self-similarities in the environment mean that the same visibility data may correspond to several different locations. The goal, therefore, is to determine the robot’s true initial location while minimizing the distance traveled by the robot. We consider approximation algorithm for the robot localization problem. The algorithm is based on triangulation of a simple polygon representing a map. Based on the basis of the implemented program, we conducted experimental studies of this algorithm. The numerical results and their interpretation are better than others.
Dao Duy Nam, Nguyen Quoc Huy

Enhanced Human Activity Recognition on Smartphone by Using Linear Discrimination Analysis Recursive Feature Elimination Algorithm

Abstract
Human Activity Recognition (HAR) is a challenging research topic in tracking a person’s state of motion and interaction with the surroundings. HAR plays an important role in developing many applications helping improve quality of life. Applications based on HAR could be used in checking the state of health, identifying a mobile phone’s context, keeping track of user’s physical activities, etc. In this research, we applied Recursive Feature Elimination based on Linear Discrimination Analysis (RFELDA) to (http://​topepo.​github.​io/​caret/​rfe.​html#rfe) reduce the dimensionality of dataset before applying classification algorithms to assign subject’s activities. The experiment results on dataset showed that RFELDA improved performance and reduced processor time better than original dataset did.
Loc Tan Nguyen

LCD-Based on Probability in Content Centric Networking

Abstract
Nowadays, Content Centric Networking (CCN) could be the future Internet architecture for its advance feature: In-network caching due to cheaper to cache than to transmit contents nowadays. Besides, the popularity of content in CCN gives much challenge to researchers, but there are a few solutions for that, such as LCD (Leave Copy Down). LCD policy is known as simple and effective caching mechanism so far. This work presents a new way of cooperation between CCN nodes in caching mechanism. Our caching mechanism is an optimization of LCD that some CCN nodes can help the others for their work on caching decision policy. This cooperation method doesn’t require both additional signaling packet and much computation resource to work. Experiments show that this optimization in terms of cache hit can achieve better than convention LCD does. In additional, our solution is simple and very low overhead.
Dang Tran Phuong, Tuan-Anh Le, Le Phong Du, Tuyet Anh Thi Nguyen, Phuong Luu Vo

Multivariate Cube for Representing Multivariable Data in Visual Analytics

Abstract
The data visualization enables users to contribute their knowledge and experience to the analysis of data stored in storages or resulted from collecting systems in real time. Visual techniques displaying data table as 2D or 3D charts, pies, lines, and so on, do not completely enable to explore multivariable data. Multivariate cube is modified from parallel coordinates by rotating the reference axis to the direction perpendicular to parallel coordinates plane. Multivariate cube represents multivariable data to enable users to answer elementary tasks in visual analytics by associating a point with its references on axes of 3-dimensional coordinates. Multivariate cube represents visually multivariable data to enable users to answer synoptic tasks in visual analytics by viewing the variation of data along the reference axis for each variable, or viewing the correlation between variables on the plane being perpendicular to and moving along the reference axis. Multivariate cube is illustrated in this paper with two case studies for visual analytics, the evaluation of learning outcomes of a program of higher education and the happenings of a disease.
Hong Thi Nguyen, Anh Van Thi Tran, Tuyet Anh Thi Nguyen, Luc Tan Vo, Phuoc Vinh Tran

An Approach to Analyzing Execution Preservation in Java Program Refactoring

Abstract
Code refactoring is a technique that improves the existing code in order to make software easier to understand and more extensible without changing the external behavior. Software design patterns, programming language independent reusable solutions to comment problems, are well-known in Java communities. On one hand, the refactoring using design patterns brings many benefits such as cost saving, flexibilities, and maintainability. On the other hand, it potentially causes bugs or changes execution behavior of Java programs. This paper proposes a new approach to checking behavior preservation properties of Java programs after applying design patterns. We present new definitions to compute pre/post conditions of program behavior. In the next step, the paper makes use of Java Modeling Language (JML) to represent and check if the refactored program neglects to preserve the external behavior. A motivating example of Adaptive Road Traffic Control (ARTC) is given to illustrate the approach in detail.
Thi-Huong Dao, Hong Anh Le, Ninh Thuan Truong

A New Method to Analyze Graphical User Interfaces of Android Applications

Abstract
In recent years, the number of Android smartphones increase dramatically and new applications are added numerously in Google store. Android developers usually have to deal with the difficulties such as limited capacity battery, screen design, and limited resources. Among them, specifying graphical user interfaces (GUI) of an application is one of the most important issues. This paper presents a new method to analyze GUI specifications of an Android application. We employ Event-B formal method and its refinement mechanism to formalize the specifications and to check if the constraints are satisfied. A running example of a Note application is given to illustrate the proposed method in detail.
Hong Anh Le, Ninh Thuan Truong

An Efficient Method for Time Series Join on Subsequence Correlation Using Longest Common Substring Algorithm

Abstract
Joining two time series on subsequence correlation provides useful information about the synchronization of the time series. However, finding the exact subsequence which are most correlated is an expensive computational task. Although the current efficient exact method, JOCOR, requires O(n 2 lgn), where n is the length of the time series, it is still very time-consuming even for time series datasets with medium length. In this paper, we propose an approximate method, LCS-JOCOR, in order to reduce the runtime of JOCOR. Our proposed method consists of three steps. First, two original time series are transformed into two corresponding strings by PAA transformation and SAX discretization. Second, we apply an algorithm to efficiently find the longest common substrings (LCS) of two strings. Finally, the resulting LCSs are mapped back to the original time series to find the most correlated subsequence by JOCOR method. In comparison to JOCOR, our proposed method performs much faster while high accuracy is guaranteed.
Vo Duc Vinh, Nguyen Phuc Chau, Duong Tuan Anh

An ORM Based Context Model for Context-Aware Computing

Abstract
Context-aware applications are the future of modern smartphones. Now we have mobile devices with enough sensing and processing capabilities but combining them and developing a context-aware application for mobile devices is still a challenging task for developers. Context-aware middleware support is a solution to reduce the complexity in developing context-aware applications. Context modeling is one of the key requirement for a successful context-aware middleware for context representation and reasoning. This paper presents a new Object-Role Modeling (ORM) based context model which uses the advantage of modern graph databases and overcomes the problems associated with previous context models including their lack of context reasoning ability and poor spatial and temporal context modeling support.
Annet Nishantha Anton Yogarajah, Shiluka Raveen Dharmasena, Gobinath Loganathan, Srinath Perera, Vishnuvathsasarma Balachandrasarma, Malaka Walpola

A Conceptual Framework for IS Project Success

Abstract
The global IT development is becoming ever more dominant. Notwithstanding, most of the projects of IS are not satisfied – the IS projects are still experiencing failure. This research reviews the IS project success with the multi-dimensional and multi-level approaches. Various works in academic journals and conferences from 1992 to 2016 were elaborated. The findings indicate that empirical studies are crucial. Interestingly, a mutual relationship between three themes of works (project success, IS success, and acceptance and use of technology) has been identified. Consequently, a conceptual framework provides the comprehensive explanation for IS project success is shown, which could be a promising avenue of IS research.
Thanh D. Nguyen, Tuan M. Nguyen, Thi H. Cao

Notes on Recognizing Echinocyte by the Top-Hat Transform

Abstract
In diagnostic of hematology, one of a most important informations is to infer about echinocyte presence. The top-hat transform and its application on echinocyte detection were briefly introducted in [2]. This paper suggests a new improvement based on random method to reduce number of computation for above purpose. We explain the relation between an upper bound of number of the blood cells to perform top-hat transform and number of echinocyte in image.
Hoang Manh Ha

Personalized Email User Action Prediction Based on SpamAssassin

Abstract
Email overload, even after spam filtering, causes waste of time and reduction of work efficiency to email users. Email prioritization is the general solution for the problem. The idea is to sort incoming emails in a decreasing order of importance so that the most important messages are read and processed first and less significant ones later, if there is enough time. This paper proposed a method to predict the action that a user would take on an email. The method is based on SpamAssassin, a famous spam filter framework. Instead of classifying emails as spam and ham (non-spam message), this method is used to predict amongst the three most common actions: reply, read and delete. Experiments are conducted to measure the effectiveness of the new method on a dataset built by the authors.
Ha-Nguyen Thanh, Quan-Dang Dinh, Quang Anh-Tran

Deadlock Avoidance for Resource Allocation Model V VM-out-of-N PM

Abstract
This paper, presents an deadlock avoidance for model V VM-out-of-N PM. Algorithm used to reschedule the policies of resource supply for resource allocation on heterogeneous distributed platform. In the current scenario, deadlock avoidance for model V VM-out-of-N PM algorithm using Two - Way search method has created the problem of taking higher time complexity of O(m*(n − 1)/2 + 2e) where e is the number of edges, for m processes at n sites. This paper proposes the algorithms for allocating multiple resources to competing services running in virtual machines on a heterogeneous distributed platform. We have implemented and performed our algorithm proposed by using CloudSim simulator. The experiments results show that our algorithm can quickly avoid deadlock and then resolve the situation of approximately orders of magnitude in practical cases.
Ha Huy Cuong Nguyen, Hoang Dung Tran, Van Thang Doan, Vu Thi Phuong Anh

Enhance Performance of Action Evaluation Functions with Stochastic Optimization Algorithms

Abstract
In this paper, we describe how to optimize the weights of board cells from data set of game records, the weights of board cells are applied in the action evaluation function which usually uses to enhance Monte Carlo Tree Search programs. The general optimization process is introduced and discussed, and one specific method is implemented. We use Othello as a testing environment, and experiment results is better if the action evaluation function is better.
Nguyen Quoc Huy, Dao Duy Nam, Dang Cong Quoc

A Method for Mobility Management in Cellular Networks Using Data Mining

Abstract
The Mobility prediction is one of the important issues in mobile computing systems. The moving logs of mobile users in mobile computing environment are stored in the Home Location Registry (HLR). The generated moving logs are used for mining mobility patterns. The discovered location patterns can be used to provide various location based services to the mobile user by the application server in mobile computing environment. Currently, some papers have written about mobility data mining methods of mobile users in cellular communications networks. In this paper, we propose a method which decrease time to compute the mobility patterns.
Giang Minh Duc, Le Manh, Do Hong Tuan

Backmatter

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