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Über dieses Buch

This book constitutes the refereed post-conference proceedings of the International Conferences ICCASA and ICTCC 2018, held in November 2018 in Viet Tri City, Vietnam. The 20 revised full papers presented were carefully selected from 30 submissions. The papers of ICCASA cover a wide spectrum in the area of context-aware-systems. CAS is characterized by its self- facets such as self-organization, self-configuration, self-healing, self-optimization, self-protection used to dynamically control computing and networking functions. The papers of ICTCC cover formal methods for self-adaptive systems and discuss natural approaches and techniques for computation and communication.

Inhaltsverzeichnis

Frontmatter

ICCASA 2018

Frontmatter

Formal Context Representation and Calculus for Context-Aware Computing

Abstract
Context is a rich concept that is mostly understood and used with different representations and interpretations in many different fields. This variety of usage adds both richness and vagueness, thus creating more complexity to comprehension, interpretation, and reasoning with contexts. As pervasive computing technology becomes more and more intrusive there is a need to construct formally verifiable context-aware computing environment, in which human dignity is preserved through safety, security, and privacy. These features cannot be ensured unless context notion is formalized, both in representation and reasoning. Motivated by this concern this paper introduces a formal context representation and a context calculus which can be used to build context models for many applications.
Ammar Alsaig, Vangalur Alagar, Nematollaah Shiri

Transmission Reordering in Self-organizing Network Coordination Framework

Abstract
By virtue of the rapid progress of IoT technology, communication devices are increasing drastically. Along with the increase, collision of transmission often happens, resulting in restricted throughput. This restriction is mainly caused by a hidden node problem. To resolve that difficulty, a promising methodology is Time Division Multiple Access (TDMA) based on a Pulse Coupled Oscillator (PCO) model. Among them, Self-organizing Network Coordination Framework (SoNCF) presents various benefits. However, in some network topologies, the performance of SoNCF is degraded because the order of random initial phases of nodes is unchanged. As described in this paper, we analyze the effect of transmission ordering on SoNCF using graph theory concepts. We also consider its extension to resolve it through reordering. Its effectiveness was confirmed through simulation.
Kohji Tomita, Akiya Kamimura

Context-Aware Parking Systems in Urban Areas: A Survey and Early Experiments

Abstract
Parking spaces have been considered as vital resources in urban areas. Finding parking spaces in jam-packed areas are often challenging, stressful and uncertain for the drivers that cause traffic congestion with a consequent of wastage of time, fuel and increase of pollution. These problems can be addressed using smart parking systems if drivers reserve parking slots in advance. With the proliferation of smart devices in a pervasive computing environment, real-time monitoring of the traffic situation and parking areas is often trivial using context-awareness. Context-awareness has the capability to occupy parking slots dynamically at any time and in any place. However, it is often challenging in busy parking areas because vehicles occupy and leave parking slots very frequently. This paper presents a brief survey on context-aware smart parking systems theoretically as well as practically. We propose a context-aware parking application to assist drivers in finding parking slots dynamically while moving and/or arriving at the destination.
Hafiz Mahfooz Ul Haque, Haidar Zulfiqar, Sajid Ullah Khan, Muneeb Ul Haque

Stream Pseudo-probabilistic Ciphers

Abstract
The paper considers methods and algorithms for stream pseudo-probabilistic encryption and introduces a novel design of such ciphers. In the known algorithms of such type two independent messages (fake and secret ones) are encrypted simultaneously (with using two different keys, fake and secret) and the produced ciphertext is computationally indistinguishable from the ciphertext produced by process of the probabilistic encryption of the fake message using the fake key. However in the known stream pseudo-probabilistic encryption schemes the algorithms for decrypting the fake and secret messages do not coincide completely. Therefore a potential attacker can use the last fact to distinguish the pseudo-probabilistic encryption from the probabilistic one. To provide resistance to such potential attacks in the paper there are proposed stream pseudo-probabilistic ciphers satisfying criterion of the sameness of the algorithms for decrypting the fake and secret messages. The introduced ciphers are sufficiently fast and represent interest for practical application to provide confidentiality of the communication protocols performed using public channels. The randomized pseudo-probabilistic stream ciphers have been also designed.
Nikolay Andreevich Moldovyan, Dmitriy Nikolaevich Moldovyan, Quang Minh Le, Long Giang Nguyen, Sy Tan Ho, Hieu Minh Nguyen

jFAT: An Automation Framework for Web Application Testing

Abstract
Web technologies have developed rapidly because web application is currently leading the trends of software development. A web-based application is a program that is accessed over a network connection, rather than existing within a device’s memory, hence detecting its failures is different from other software systems. Many approaches and tools have been proposed for web testing, however, introducing new frameworks is still an emerging topic in this field. This paper proposes an automation framework running in Java platform for web testing, called jFAT, which integrates with Selenium and TestNG. The paper also illustrates the use of framework with the Bank application case study.
Hanh Phuc Nguyen, Hong Anh Le, Ninh Thuan Truong

On the Compliance of Access Control Policies in Web Applications

Abstract
Model-View-Controller (MVC) architecture has commonly used in the implementation of web applications. These systems often incorporate security policies to ensure their reliability. Role-based access control (RBAC) is one of the effective solutions for reducing resources access violations of a system. This paper introduces an approach to check the compliance of a web application under MVC architecture with its RBAC specification. By investigating the system architecture and source code analysis, our approach conducts with extracting a list of resources access permissions, constructing a resources exploitation graph and organizing an access control matrix according to roles of a web application. The approach aims at checking two violation cases of web applications: (i) the presence of unspecified access rules and (ii) the absence of specified access rules. We illustrate the proposed approach by a case study of web based medical records management system.
Thanh-Nhan Luong, Dinh-Hieu Vo, Van-Khanh To, Ninh-Thuan Truong

Two-Stage Approach to Classifying Multidimensional Cubes for Visualization of Multivariate Data

Abstract
Visualization of multivariate data is a big challenge to problems of visual analytics. A system of data visualization is composed of visual mapping stage and visual display stage. The stage of visual mapping converts data to graph and the stage of visual display shows the graph on screen in accordance with human’s retinal perception which is specified by visual features and Gestalt’s laws. Based on data characteristics, multidimensional cubes representing multivariate data are classified as non-spatial multidimensional cube for non-spatial data, spatial multidimensional cube for spatio-temporal data, spatio-temporal multidimensional cube for movement data, and 3D-spatio-temporal multidimensional cube for flight data. For a visualization system responding human’s retinal perception, multidimensional cubes have to enable analysts to answer elementary questions concerning individual values, variation questions concerning part of data or overall data, and relation questions resulting in the correlation among attributes.
Hong Thi Nguyen, Thuan My Thi Pham, Tuyet Anh Thi Nguyen, Anh Van Thi Tran, Phuoc Vinh Tran, Dang Van Pham

Proposing Storage Structures and Interpolation Algorithms of 3D Spatial Data

Abstract
The rapidly growth urbanization and using high-intensity land in urban areas recently are hot topics interested in researchers of 2-3-4D GIS (2-dimensional, 3-dimensional, and 4-dimensional geographic information system) more and more by the shapes of high-rise buildings (buildings) of diversity and abundance located on limited land funds. This problem is a big challenge for researchers of 2-3-4D GIS, how they can visually represent it into the 2D computer screen. This paper proposes to build space-data storage structures and to develop 3D space data interpolation algorithms (IA and NCA) for visual representation of buildings located on limited land funds in 3D geographical scientific space. This paper also presents experiments by these 3D bodies to represent visualization of buildings. Through these experimental results show able to support the authorities apply for management stages of urban techniques infrastructures in the near future.
Dang Van Pham, Vinh Cong Phan

Visually Analyzing Evolution of Geographic Objects at Different Levels of Details Over Time

Abstract
Evolutionary history of geographic objects (EHGOS) in three-dimensional (3D) space at different levels of details (DLODS) over time is due to natural law or imposed by humans and always goes on every day. To represent visualization this evolutionary history, this paper proposes visual analysis of EHGOS at DLODS over time, results of visual analysis are a model of representation of visualization of GOS at DLODS over time, this model is called TLODS. Time is the class that records the time of formation and loss of GOS. Time in this paper is divided into three main categories and integrate into the TLODs model, namely legal time (LTS), event time (ETS), and database time (DTS). When manipulating queries can be either point of time or period of time in three types of time. This paper presents the experimental setup of the TLODS model in Oracle 11G and incorporating in C# to represent typical forms. Experimental results show that it can be applied to the management of urban technical infrastructure in practice.
Dang Van Pham, Phuoc Vinh Tran

A Conceptual Model of Consumers’ Purchase Intention on Different Online Shopping Platforms

Abstract
The first objective of this paper is to provide a more comprehensive conceptual model which can be utilized in the examination of the effects of stimuli on online consumers’ behavior and their decision making processes when they are contemplating a particular purchasing action or environment on various online shopping platforms. The proposed conceptual model was constructed by exploiting one of the theoretical framework of consumer behavior, the Stimulus-Organism-Response Model (S-O-R Model), as a base model and incorporating various related literature in the context of online shopping platforms into the base model and then develop into a conceptual framework. The second objective is to present the proposed conceptual model which can be utilized to study the differences of online consumers’ behaviors on different online shopping platforms. The variables that were incorporated with the S-O-R Model include website interactivity (active control and reciprocal communication), perceived risk, social identity, website involvement (affective involvement and cognitive involvement), flow (perceived enjoyment, concentration, and curiosity), and purchase intention.
Attasit Patanasiri, Donyaprueth Krairit

MVMO with Opposite Gradient Initialization for Single Objective Problems

Abstract
The objective of this paper is to describe an opposite gradient initialization concept with mean-variance mapping optimization (OGI-MVMO). OGI-MVMO is an optimization based on the actual manifold of objective function whereas original MVMO based stochastic optimization. Generating the new candidate solution to speed up the solution finding and accuracy of solution are important purposes. The OGI-MVMO algorithm consist of 2 steps: the primary step is generating new solution by OGI and also the second step is mutation between every of selected candidate solution supported the mean and variance of the population. The results showed that OGI-MVMO algorithm has better performance than other algorithm include the original MVMO for 15 real-parameter single objective functions.
Thirachit Saenphon

Context Based Algorithm for Social Influence Measurement on Twitter

Abstract
The social media became one of the most effective method for marketing and for information propagation. Therefore, measuring users influence is important for organizations to know which user to target to successfully spread a piece of information. Twitter is one of the social media tools that is used for information propagation. The current methods for measuring influence of Twitters users, use ranking algorithms that focus on specific criteria such as number of followers or tweets. However, different cases creates different needs in measuring influence. Each need could include different elements with different priority. One of these cases is local businesses which need to propagate information within a specific context such as location. That is, the most influential user for such a business is the one that has the highest number of followers that are located within the required location. Therefore, in this paper, we use the X algorithm for measuring users influence on Twitter by ranking users based on followers context that is represented by number of elements. Each element is given a weight to prioritize elements based on client demand.
Alaa Alsaig, Ammar Alsaig, Marwah Alsadun, Soudabeh Barghi

Context-Aware Recommendation with Objective Interestingness Measures

Abstract
Context-aware recommender systems researches now concentrate on adjusting recommendation results for situations specific context of the users. These studies suggest many ways to integrate user contextual information into the recommendation process such as using topic hierarchies with matrix factorization techniques to improve context-aware recommender systems, measuring frequency-based similarity for context-aware recommender systems, collecting data from social networking to support context-aware recommender systems, and so on. However, these studies mainly focus on the development of context-aware recommendation algorithms to propose items to users in a particular situation and do not care about the extent of contextual involvement in the recommendation process to make recommendation results. In this article, we propose a new approach for context-aware recommender systems based on objective interestingness measures to consider the contextual relationship of the users in the recommendation process. Based on the experimental results on two standard datasets, the proposed model is more accurate than the traditional models.
Nghi Mong Pham, Nghia Quoc Phan, Dang Van Dang, Hiep Xuan Huynh

Development of a Peer-Interaction Programming Learning System

Abstract
Computer programming is basic knowledge in the digital age and becoming an critical subject during recent years. However, learning to programme is not an easy topic as supported by many researchers. During the development of information technology, many online learning systems have been developed and proven their positive effect on students learning. However, few studies have geared toward supporting its use in programming courses with peer-interaction. Therefore, this study aimed to develop an online learning system named Peer-Interaction Programming Learning System. The system was developed and being used by many programming classes both in Vietnam and Taiwan. In this paper, we reported on the design of the system and its user interface, discussed our motivation and underlying teaching philosophy.
Pham-Duc Tho, Nguyen-Hung Cuong, Hoang-Cong Kien, Chih-Hung Lai

Dynamic Measurement for Detecting the Road of an Autonomous Vehicle Using the Proximity Sensor

Abstract
The majority of sensors have played a vital role in the autonomous vehicle area. In this research, a dynamic model for measuring a characteristic of the analog sensor is developed, the shape of the output signal is a critical factor in road identification of autonomous vehicles. By hand-made testing system is built successfully, a number of alloys and non-magnetic metals (Aluminium and Copper) are considered in every aspect of them. In addition, the comparison experimental outcomes between various dynamic models prove that, with the same metal size (50 × 20), and sensing distance (6 mm), the shape of the output signal of measuring is similar. These results are distinguished clearly with alloys. Signal interference will also be minimized due to the control of the movement speed of the sensor. This is an integral element for approaching road of mobile devices with different obstacles.
Thang Hoang, Hoai Nguyen, Thanh Le Chau Nguyen, Khoa Xuan Le, Tung Minh Phung

ICTCC 2018

Frontmatter

Post-quantum Cryptoschemes: New Finite Non-commutative Algebras for Defining Hidden Logarithm Problem

Abstract
In the article we present some properties of non-commutative finite algebras of four-dimension vectors with parameterized multiplication operation characterized in that different modifications of the multiplication operation are mutually associative. One of the introduced finite algebras represents ring. Other algebra contains no global unit element, its elements are invertible locally, and is characterized in that the multiplication operation possess compression property. Regarding the investigated ring, the detailed attention is paid to properties of the set of non-invertible elements of the ring. Formulas for zero-divisors and unit elements of different types are derived. The introduced finite algebras represent interest to define over them the hidden discrete logarithm problem that is a promising cryptographic primitive for post-quantum cryptography.
Hieu Minh Nguyen, Nikolay Andreevich Moldovyan, Alexandr Andreevich Moldovyan, Nam Hai Nguyen, Cong Manh Tran, Ngoc Han Phieu

Simulating the Irrigation Operations with Cellular Automata

Abstract
In this paper, we propose a new simulation approach based on a cellular automata to predict the closing or opening of irrigation culvert. To solve this problem, water quality parameters such as salinity, temperature, pH, dissolved oxygen, etc. were measured at culverts. Then, opening or closing the culverts depending on the quality of the water there is considered. However, due to the large number of culverts, it is very time consuming to carry out manual measurements of all culverts. It is important to have a measure to help predict the water quality at culverts so as to reduce the amount of effort and time spent by farmers, meanwhile it helps farmers to feel secure to do the production (The simulations are based on data on water quality collected at culverts in subregion X - South Ca Mau, Ca Mau province, Vietnam).
Hiep Xuan Huynh, Nha Thanh Huynh, Toan Phung Huynh, Son Van Tran, Linh Thuy Thi Nguyen

Modeling with Words Based on Hedge Algebra

Abstract
In this paper, we introduce a method for modeling with words based on hedge algebra using fuzzy cognitive map. Our model, called linguistic cognitive map, consists of set of vertices and edges with value to be linguistic variables. We figure out relationship between the length of linguistic variables for fuzzifying data and a number of partition from unit interval. We also prove finite properties of state space, generating from linguistic cognitive map.
Nguyen Van Han, Phan Cong Vinh

A Variable Neighborhood Search Algorithm for Solving the Steiner Minimal Tree Problem

Abstract
Steiner Minimal Tree (SMT) is a complex optimization problem that has many important applications in science and technology; This is a NP-hard problem. Much research has been carried out to solve the SMT problem using approximate algorithms. This paper presents a variable neighborhood search (VNS) algorithm for solving the SMT problem; The proposed algorithm has been tested on sparse graphs in a standardized experimental data system, and it yields better results than some other heuristic algorithms.
Tran Viet Chuong, Ha Hai Nam

Handling Missing Values for the CN2 Algorithm

Abstract
Missing values are existed in several practical data sets. Machine Learning algorithms, such as CN2, require missing values in a data set be pre-processed. The estimated values of a missing value can be provided by Data Imputation methods. However, the data imputation can introduce unexpected information to the data set so that it can reduce the accuracy of Rule Induction algorithms. If missing values can be directly processed in Rule Induction algorithms, the overall performance can be improved. The paper studied the CN2 algorithm to propose a modified version, CN2MV, which is able to directly process missing values without preprocessing. Testing on 17 benchmarking data sets from the UCI Machine Learning Repository, CN2MV outperforms the original algorithm using data imputations.
Cuong Duc Nguyen, Phuong-Tuan Tran, Thi-Thanh-Thao Thai

Backmatter

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