Vol. 14, No. 3, Jun. 2018
Youssef Fahim, Hamza Rahhali, Mohamed Hanine, El-Habib Benlahmar, El-Houssine Labriji, Mostafa Hanoune, Ahmed Eddaoui
Vol. 14, No. 3, pp. 569-589, Jun. 2018
Keywords: Bat-Algorithm, Cloud Computing, Load Balancing, Pre-scheduling, Virtual Machines
Show / Hide AbstractCloud computing, also known as country as you go”, is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders’ number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software’s profitability. Our axis of research is the load balancing between a data center’s virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels (‘odd levels’ or ‘even levels’) in ascending order based on the meta-heuristic “Bat-algorithm”. The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.
Jianwei Zhang, Tao Jiang, Yuhui Zheng, Jin Wang, Jiacen Xie
Vol. 14, No. 3, pp. 590-599, Jun. 2018
Keywords: Expected Patch Log Likelihood, Image Denoising, Patch Priors, Structure Information
Show / Hide AbstractMultivariate finite mixture model is becoming more and more popular in image processing. Performing image denoising from image patches to the whole image has been widely studied and applied. However, there remains a problem that the structure information is always ignored when transforming the patch into the vector form. In this paper, we study the operator which extracts patches from image and then transforms them to the vector form. Then, we find that some pixels which should be continuous in the image patches are discontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose a new operator which may keep more information when extracting image patches. We compare the new operator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method, and we obtain better results in both visual effect and the value of PSNR.
Xiaoli Wang, Shilin Wang, Baochen Jiang
Vol. 14, No. 3, pp. 600-606, Jun. 2018
Keywords: Code Wheel Instrument, Image Identification, IoT, Smart City, Template Matching
Show / Hide AbstractSmart city is currently the main direction of development. The automatic management of instrumentation is one task of the smart city. Because there are a lot of old instrumentation in the city that cannot be replaced promptly, how to makes low-cost transformation with Internet of Thing (IoT) becomes a problem. This article gives a low-cost method that can identify code wheel instrument information. This method can effectively identify the information of image as the digital information. Because this method does not require a lot of memory or complicated calculation, it can be deployed on a cheap microcontroller unit (MCU) with low readonly memory (ROM). At the end of this article, test result is given. Using this method to modify the old instrumentation can achieve the automatic management of instrumentation and can help build a smart city.
Vol. 14, No. 3, pp. 607-620, Jun. 2018
Keywords: Automobile Control Software, Risk-based Test, Software Testing Process, Test Design, Test Planning, Test Policy and Strategy, TMMi Assessment
Show / Hide AbstractThe problem surrounding methods of implementing the software testing process has come under the spotlight in recent times. However, as compliance with the software testing process does not necessarily bring with it immediate economic benefits, IT companies need to pursue more aggressive efforts to improve the process, and the software industry needs to makes every effort to improve the software testing process by evaluating the Test Maturity Model integration (TMMi). Furthermore, as the software test process is only at the initial level, high-quality software cannot be guaranteed. This paper applies TMMi model to Automobile control software testing process, including test policy and strategy, test planning, test monitoring and control, test design and execution, and test environment goal. The results suggest improvement of the automobile control software testing process based on Test maturity model. As a result, this study suggest IT organization’s test process improve method.
Muhammad Zahid Tunio, Haiyong Luo, Cong Wang, Fang Zhao, Abdul Rehman Gilal, Wenhua Shao
Vol. 14, No. 3, pp. 621-630, Jun. 2018
Keywords: Crowdsourced, Human Factor, Personality Type, Software Development, Task Assignment
Show / Hide AbstractSelection of a suitable task from the extensively available large set of tasks is an intricate job for the developers in crowdsourcing software development (CSD). Besides, it is also a tiring and a time-consuming job for the platform to evaluate thousands of tasks submitted by developers. Previous studies stated that managerial and technical aspects have prime importance in bringing success for software development projects, however, these two aspects can be more effective and conducive if combined with human aspects. The main purpose of this paper is to present a conceptual framework for task assignment model for future research on the basis of personality types, that will provide a basic structure for CSD workers to find suitable tasks and also a platform to assign the task directly. This will also match their personality and task. Because personality is an internal force which whittles the behavior of developers. Consequently, this research presented a Task Assignment Model (TAM) from a developers point of view, moreover, it will also provide an opportunity to the platform to assign a task to CSD workers according to their personality types directly.
Vol. 14, No. 3, pp. 631-644, Jun. 2018
Keywords: flash memory, Page Replacement Algorithm, SSD
Show / Hide AbstractMany studies on flash memory-based buffer replacement algorithms that consider the characteristics of flash memory have recently been developed. Conventional flash memory-based buffer replacement algorithms have the disadvantage that the operation speed slows down, because only the reference is checked when selecting a replacement target page and either the reference count is not considered, or when the reference time is considered, the elapsed time is considered. Therefore, this paper seeks to solve the problem of conventional flash memory-based buffer replacement algorithm by dividing pages into groups and considering the reference frequency and reference time when selecting the replacement target page. In addition, because flash memory has a limited lifespan, candidates for replacement pages are selected based on the number of deletions.
Jin Hua, Zahid Latif, Shen Tiyan, Zulfiqar Hussain Pathan, Muhammad Zahid Tunio, Shafaq Salam, Liu Ximei
Vol. 14, No. 3, pp. 645-654, Jun. 2018
Keywords: Digital Power, European Union (EU), Game Changer, Information and Communication Technology (ICT), One Belt, One Road
Show / Hide AbstractInformation and communication technology (ICT) is increasingly recognized as an important driver of economic growth, innovation, employment and productivity and is widely accepted as a main feature of development. During the last couple of decades, ICT sector became the most innovative service sector that affected the living standards of human beings all over the world. In the beginning of the 21st century, some of the Asian countries made reforms in the ICT sector and spent an enormous amount for the progress of this sector. On the other hand, developed countries in the European Union (EU) faced different crises which badly affected the dissemination of this sector. Consequently, EU countries lost their hegemony in the field of information technology and resultantly, some of the emerging Asian countries like China, India, and South Korea got supremacy over the EU in this field. Currently, these countries have a strong IT infrastructure, R&D sector, IT research centers working for the development of ICT. Moreover, this paper investigates reasons for the shifting of the balance of digital power from Europe to Asia.
Bens Pardamean, James W. Baurley, Anzaludin S. Perbangsa, Dwinita Utami, Habib Rijzaani, Dani Satyawan
Vol. 14, No. 3, pp. 655-665, Jun. 2018
Keywords: Agriculture Biotechnology, Big Data, Genotyping, Infrastructure, IT
Show / Hide AbstractIn efforts to increase its agricultural productivity, the Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development has conducted a variety of genomic studies using highthroughput DNA genotyping and sequencing. The large quantity of data (big data) produced by these biotechnologies require high performance data management system to store, backup, and secure data. Additionally, these genetic studies are computationally demanding, requiring high performance processors and memory for data processing and analysis. Reliable network connectivity with large bandwidth to transfer data is essential as well as database applications and statistical tools that include cleaning, quality control, querying based on specific criteria, and exporting to various formats that are important for generating high yield varieties of crops and improving future agricultural strategies. This manuscript presents a reliable, secure, and scalable information technology infrastructure tailored to Indonesian agriculture genotyping studies.
Chengyou Wang, Heng Zhang, Xiao Zhou
Vol. 14, No. 3, pp. 666-679, Jun. 2018
Keywords: Discrete wavelet transform (DWT), Fragile Watermarking, Image Authentication, Local Binary Pattern (LBP), Semi-blind Detection
Show / Hide AbstractThe discrete wavelet transform (DWT) has good multi-resolution decomposition characteristic and its low frequency component contains the basic information of an image. Based on this, a fragile watermarking using the local binary pattern (LBP) and DWT is proposed for image authentication. In this method, the LBP pattern of low frequency wavelet coefficients is adopted as a feature watermark, and it is inserted into the least significant bit (LSB) of the maximum pixel value in each block of host image. To guarantee the safety of the proposed algorithm, the logistic map is applied to encrypt the watermark. In addition, the locations of the maximum pixel values are stored in advance, which will be used to extract watermark on the receiving side. Due to the use of DWT, the watermarked image generated by the proposed scheme has high visual quality. Compared with other state-of-the-art watermarking methods, experimental results manifest that the proposed algorithm not only has lower watermark payloads, but also achieves good performance in tamper identification and localization for various attacks.
Jung Hyun Ryu, Nam Yong Kim, Byoung Wook Kwon, Sang Ki Suk, Jin Ho Park, Jong Hyuk Park
Vol. 14, No. 3, pp. 680-693, Jun. 2018
Keywords: Digital Investigation, Mobile, Forensics, Third-Party Applications
Show / Hide AbstractNowadays, third-party applications form an important part of the mobile environment, and social networking applications in particular can leave a variety of user footprints compared to other applications. Digital forensics of mobile third-party applications can provide important evidence to forensics investigators. However, most mobile operating systems are now updated on a frequent basis, and developers are constantly releasing new versions of them. For these reasons, forensic investigators experience difficulties in finding the locations and meanings of data during digital investigations. Therefore, this paper presents scenario-based methods of forensic analysis for a specific third-party social networking service application on a specific mobile device. When applied to certain third-party applications, digital forensics can provide forensic investigators with useful data for the investigation process. The main purpose of the forensic analysis proposed in the present paper is to determine whether the general use of third-party applications leaves data in the mobile internal storage of mobile devices and whether such data are meaningful for forensic purposes.
Chanchan Zhao, Feng Liu, Xiaowei Hai
Vol. 14, No. 3, pp. 694-708, Jun. 2018
Keywords: Hierarchical Dividing, K-means, Passenger Nodes, Passenger Dedicated line, Self-Organizing Map
Show / Hide AbstractChina possesses a passenger dedicated line system of large scale, passenger flow intensity with uneven distribution, and passenger nodes with complicated relations. Consequently, the significance of passenger nodes shall be considered and the dissimilarity of passenger nodes shall be analyzed in compiling passenger train operation and conducting transportation allocation. For this purpose, the passenger nodes need to be hierarchically divided. Targeting at problems such as hierarchical dividing process vulnerable to subjective factors and local optimum in the current research, we propose a clustering approach based on self-organizing map (SOM) and k-means, and then, harnessing the new approach, hierarchical dividing of passenger dedicated line passenger nodes is effectuated. Specifically, objective passenger nodes parameters are selected and SOM is used to give a preliminary passenger nodes clustering firstly; secondly, Davies–Bouldin index is used to determine the number of clusters of the passenger nodes; and thirdly, k-means is used to conduct accurate clustering, thus getting the hierarchical dividing of passenger nodes. Through example analysis, the feasibility and rationality of the algorithm was proved.
Salim Miloudi, Sid Ahmed Rahal, Salim Khiat
Vol. 14, No. 3, pp. 709-726, Jun. 2018
Keywords: Connected Components, Database Classification, Graph-Based Algorithm, Multi-Database Mining
Show / Hide AbstractDatabase classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to (n2–n)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.
Shi Dong, Xingang Zhang, Ya Li
Vol. 14, No. 3, pp. 727-739, Jun. 2018
Keywords: Machine Learning, RDM, Sentiment Analysis, Spectral Cluster
Show / Hide AbstractThis study evaluates the viewpoints of user focus incidents using microblog sentiment analysis, which has been actively researched in academia. Most existing works have adopted traditional supervised machine learning methods to analyze emotions in microblogs; however, these approaches may not be suitable in Chinese due to linguistic differences. This paper proposes a new microblog sentiment analysis method that mines associated microblog emotions based on a popular microblog through user-building combined with spectral clustering to analyze microblog content. Experimental results for a public microblog benchmark corpus show that the proposed method can improve identification accuracy and save manually labeled time compared to existing methods.
Sarang Na, Taeeun Kim, Hwankuk Kim
Vol. 14, No. 3, pp. 740-750, Jun. 2018
Keywords: Common Platform Enumeration (CPE), Common Vulnerabilities and Exposures (CVE), OS Fingerprinting, Security Vulnerability Analysis, Service Identification
Show / Hide AbstractThere are a great number of Internet-connected devices and their information can be acquired through an Internet-wide scanning tool. By associating device information with publicly known security vulnerabilities, security experts are able to determine whether a particular device is vulnerable. Currently, the identification of the device information and its related vulnerabilities is manually carried out. It is necessary to automate the process to identify a huge number of Internet-connected devices in order to analyze more than one hundred thousand security vulnerabilities. In this paper, we propose a method of automatically generating device information in the Common Platform Enumeration (CPE) format from banner text to discover potentially weak devices having the Common Vulnerabilities Exposures (CVE) vulnerability. We demonstrated that our proposed method can distinguish as much adequate CPE information as possible in the service banner.
Ruchika Malhotra, Anjali Sharma
Vol. 14, No. 3, pp. 751-770, Jun. 2018
Keywords: Empirical Validation, Fault Prediction, Machine Learning, Object-Oriented Metrics, Web Application Quality
Show / Hide AbstractWeb applications are indispensable in the software industry and continuously evolve either meeting a newer criteria and/or including new functionalities. However, despite assuring quality via testing, what hinders a straightforward development is the presence of defects. Several factors contribute to defects and are often minimized at high expense in terms of man-hours. Thus, detection of fault proneness in early phases of software development is important. Therefore, a fault prediction model for identifying fault-prone classes in a web application is highly desired. In this work, we compare 14 machine learning techniques to analyse the relationship between object oriented metrics and fault prediction in web applications. The study is carried out using various releases of Apache Click and Apache Rave datasets. En-route to the predictive analysis, the input basis set for each release is first optimized using filter based correlation feature selection (CFS) method. It is found that the LCOM3, WMC, NPM and DAM metrics are the most significant predictors. The statistical analysis of these metrics also finds good conformity with the CFS evaluation and affirms the role of these metrics in the defect prediction of web applications. The overall predictive ability of different fault prediction models is first ranked using Friedman technique and then statistically compared using Nemenyi post-hoc analysis. The results not only upholds the predictive capability of machine learning models for faulty classes using web applications, but also finds that ensemble algorithms are most appropriate for defect prediction in Apache datasets. Further, we also derive a consensus between the metrics selected by the CFS technique and the statistical analysis of the datasets.
Maximizing Network Utilization in IEEE 802.21 Assisted Vertical Handover over Wireless Heterogeneous NetworksDinesh P, ey, Beom Hun Kim, Hui-Seon Gang, Goo-Rak Kwon, Jae-Young Pyun
Vol. 14, No. 3, pp. 771-789, Jun. 2018
Keywords: Handover Decision, IEEE 802.21, Occupied Bandwidth, SINR, Vertical Handover
Show / Hide AbstractIn heterogeneous wireless networks supporting multi-access services, selecting the best network from among the possible heterogeneous connections and providing seamless service during handover for a higher Quality of Services (QoSs) is a big challenge. Thus, we need an intelligent vertical handover (VHO) decision using suitable network parameters. In the conventional VHOs, various network parameters (i.e., signal strength, bandwidth, dropping probability, monetary cost of service, and power consumption) have been used to measure network status and select the preferred network. Because of various parameter features defined in each wireless/mobile network, the parameter conversion between different networks is required for a handover decision. Therefore, the handover process is highly complex and the selection of parameters is always an issue. In this paper, we present how to maximize network utilization as more than one target network exists during VHO. Also, we show how network parameters can be imbedded into IEEE 802.21- based signaling procedures to provide seamless connectivity during a handover. The network simulation showed that QoS-effective target network selection could be achieved by choosing the suitable parameters from Layers 1 and 2 in each candidate network.
Vol. 14, No. 3, pp. 790-800, Jun. 2018
Keywords: Multi-Criteria Decision-Making, Pattern Recognition, Similarity Measure, Simplified Neutrosophic Sets
Show / Hide AbstractThe simplified neutrosophic set (SNS) is a generalization of fuzzy set that is designed for some practical situations in which each element has truth membership function, indeterminacy membership function and falsity membership function. In this paper, we propose a new method to construct similarity measures of single valued neutrosophic sets (SVNSs) and interval valued neutrosophic sets (IVNSs), respectively. Then we prove that the proposed formulas satisfy the axiomatic definition of the similarity measure. At last, we apply them to pattern recognition under the single valued neutrosophic environment and multi-criteria decisionmaking problems under the interval valued neutrosophic environment. The results show that our methods are effective and reasonable.