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Mobile communication companies choose different smart phone platforms, so that game developers must create content designed specifically for each platform or use a conversion process to provide game content to consumers. In this paper, to resolve this problem, the Android-to-Ios smart game converter was designed to automatically convert game contents from the Android platform to the iOS platform for smart phones using a content analyzer, a resource converter, a platform mapping engine and a source translator. The Android platform developed by Google is an optimized platform for mobile devices with a perfect combination of an operating system, middleware, and application programs. The iOS platform developed by Apple is the world’s most advanced mobile operating system, continually redefining what people can do with a mobile device. Through the Android-to-iOS converter, resources such as images and sounds can be converted, APIs can be converted using a platform mapping engine and game sources can be converted using a source translator with compiler writing technology. Experimental results indicate that the graphics, image output, sound output, and other functions of converted iOS games were equivalent to those of the Android games before conversion.

Virtualized Computing Cloud (VCC) is a well-known resource-provisioning and computing environment due to advantages such as maximized resource utilization, isolated performance, and customizable runtimes. Therefore, recently, VCC has been increasingly adopted in a broad spectrum of service domains, including internet-based application services and computational science. However, efficient resource (i.e., virtual machine; VM) allocation techniques are required to deliver higher-quality Internet and/or computing services. In this paper, we propose a novel dynamic, self-adaptive VMs allocation technique considering network resource contention in a Xen virtualization environment. In addition, we provide generic virtualized resources and job management framework to realize our proposed VM allocation technique. Using the virtualized resources and job management framework, we also practically analyze the impact of various system parameters and job characteristics on the performance of our technique. The results show that our approach outperforms others, reducing the average job response (by up to 37%) and execution (by up to 22.3%) times.

Nondestructive Testing (NDT) is appropriate for ceramic materials but the image may contain cracks, spiracles, and other foreign substances to form various defects on the surface. Such subtle defects are often neglected on manual visual inspection and it also causes inspector subjectivity problem thus we need am automated computational method to solve the problem. In this paper, we propose a fuzzy logic based method to detect such various defects from the surface of ceramic material. In our method, we first apply fuzzy stretching to enhance the brightness contrast from the input image. Then the fuzzy binarization and upper/lower level search algorithm finds the interval range of defects' existence. Finally ART2 learning algorithm determines different types of defects. The novelty of this paper is avoiding segmentation-identification paradigm and apply simpler image processing technique with fuzzy logic and neural learning in defect identification. In experiment, the proposed method successfully detects poor fusing and tungsten defects.

Vehicular Ad-hoc Network systems (VANETs) are a dynamic wireless network where the nodes move randomly without any infrastructure. VANETs are an open transmission and communication media without any security mechanism. So, there are a lot of malicious nodes attacks on VANETs. Blackhole attack is one of the security threats in which the traffic isn’t transmitted to the destination node but will redirect it to a node that actually does not exist in the network to drop that traffic. The main target of the paper is to measure the impact of Blackhole attack on the VANET’s reactive and proactive routing protocols i.e., AODV, DSR, OLSR, and TORA. Simulation is carried out by using OPNET modeler 14.5 [1]. Measurements of different parameters with complete analysis and comparison are presented.

Classification of facial expressions is a great challenge in the area of computer vision. Using single feature models, the percentage of recognition is considerably low even in controlled conditions of capturing. To improve the accuracy of the facial emotion recognition and classification, a new method is proposed in this paper based on the fusion of features extracted from different techniques. Local features are extracted using Directional Local Binary Patterns (DLBP) and global features are extracted using Discrete Cosine Transform (DCT) from facial expression images. Principal Components Analysis (PCA) is used to reduce the dimensions of extracted features. Weighted summation and PCA fusion methods are used to fuse the local and global features extracted from facial images. RBF neural network is used as classifier for classification of facial images into six emotions (surprise, fear, sad, joy, anger and disgust). Cohn-Kanade database is used to evaluate the proposed method. The results of proposed algorithm yield better recognition rate of 97% in comparison with existing methods.

This study investigates ways to improve the performance of rice productivity prediction model by employing the infrequent data binning method. Binning in this study is a technique to reassign infrequent data outside a specific scope, back in to the boundary value of the scope. The main findings of this study include: first, the binning method based on reassigning infrequent data contributes to improving the prediction performance of the model in question. Second, the effects of improvement differ depending on the length of the tail of a distribution. Third, there are no interaction effects due to combination of binned variables involving in different distribution categories with different length of long-tail

For recent mobile platform-based applications associated with festivals, searching for information on festivals disadvantageously results in cookie-cutter information, such as festival information per region, date and theme, and real-time ranking. This paper developed an individual customized algorithm for retrieving festivals with the aim of compensating these disadvantages and thereby enabling application users to efficiently search festivals suitable for individual situations. Based on the developed algorithm, a festival search system under a mobile environment was designed and implemented.

We propose a local search based approach to generate automatically test cases for programs having floating point statements. The proposed approach, called MLFP (for Multi-precision arithmetic and Local search for Floating Point constraints), adopts a local search approach to solve constraints on floating point numbers. Compared to the classical integer domain, floating point numbers F have two particular properties: they have a huge cardinality (e.g., 252 numbers in the interval [0.5, 1.0] with the "double" format), huge values (e.g. 10300), and also tiny values (e.g. 10-300). This huge combinatorial nature of the search space motivates using a local search approach. In order to find test cases containing huge or tiny numbers, such as overflow or underflow exception errors, MLFP uses the multiple precision MPFR library. Our local search approach proceeds in two steps. The first step exploits a line search algorithm to converge quickly to an approximate solution on real numbers. The second step adopts a dedicated local search algorithm on floating point numbers in order to find an exact solution, by using specific neighborhood and evaluation functions. We have implemented the MLFP approach, and we have shown its usefulness on various non trivial programs having floating point statements.

The objective of writing this thesis is to measure the impact of Capability Maturity Model Integration (CMMI) for application development process improvement in Telkomsigma. The method used is by comparing samples of application development projects before Telkomsigma implemented CMMI and after implemented CMMI. In gathering projects information, author observed documentations related to sample projects, organization policies and procedures and discussions with related parties.The data that has been received, is analysed with CMMI practice to measure its maturity levels. The result of the measurement is comparison of CMMI practice goals achievement before and after Telkomsigma’s CMMI implementation from measured samples projects.The conclusion that the author can get is, CMMI implementation can improve Telkomsigma’s application development process.

Computer Science Education (CSE) is one discipline that uses the growing and demanding e-learning environment to deliver the computation and technology knowledge to the learners. CSE needs practical sessions as the main part of its education process. Many Learning Management Systems (LMS) have limited resources towards virtual labs. This hinders the free and direct utilization of the software tools that are needed for CSE. As a consequence, researchers attempted to support the LMSs and develop these resources as built-in components in the LMS itself. In this direction, this paper proposes the usage of the Service-Oriented Architecture (SOA) to overcome the limitations of the LMSs towards the practical sessions of CSE. The software developer uses SOA to develop the needed resources as services and then integrates them in the LMS environment. In this paper, all experimental works are carried out on the Moodle environment since it is an open source and used at the Sultan Qaboos University (SQU) in Oman.

In this paper, we proposed roles and responsibilities of cyber intelligence in cyber operations. In particular, we focused on the roles and responsibilities of cyber intelligence on each phase of cyber operations. Cyber operations are activities related to defense, assurance, and attack to achieve objectives in or through cyberspace. While cyber operation is conducting, cyber intelligence must properly support cyber commander and units for ensuring cyberspace intelligence superiority. Cyber intelligence is a cyber-discipline that exploits a number of information collection and analysis approaches to provide direction and decision to cyber commander and cyber operation units. This is a key role in both cyber-attack and cyber defense. We know that the branch of information and communications conducts cyber operations in cyberspace. But we don’t know well that the cyber intelligence is more in charge of the policy, strategic, and tactics in cyber operations. It is collected information requested from cyber command and units, and is disseminated information to department related to cyber operations. The cyber intelligence is a key factor in cyber operation cycle.

This paper designs a cluster-based electric vehicle relocation scheme for carsharing systems, aiming at generating a relocation schedule within a reasonable time bound by decomposing a large problem into several smaller ones. In order to develop a genetic algorithm for clustering, a feasible plan is encoded to an integer-valued vector in which intermediary stations locate at fixed positions and negative numbers separate clusters. The vehicles in overflow clusters are moved to underflow clusters through the intermediary stations first and then finally to underflow stations. The fitness function calculates the distance of all inter-station pairs in each cluster and selects the largest of them. Genetic operators continuously reduce the cost generation by generation. The performance measurement result, obtained by a prototype implementation, shows that the proposed clustering scheme linearly increases the cost according to the addition of a station, even if it is expected to increase exponentially. Moreover, the clustering plan converges to a stable cost in the early stages of the genetic evolution. These results indicate that we can overcome the stock imbalance problem and improve the service ratio.

The main purpose of the research was to develop an Automatic Weather Station (AWS) data logger using microcontroller Netduino. It will be useful to each sector which affected by weather. This research implement a telemetry system on Netduino logger in purpose to place it on remote area application, beside the study was developed a switching channel method to expand the number of I/O analog pin on Netduino. A correction factor resulted by data analysis during calibration and validation using linear regression method was “0.8594x + 4.7486” with R2 = 0.9367. This research conclude that processing analog signal on Netduino has an alteration between its real value even not significantly, some treatment has implemented to reduce the error of data output, with using good power resource and moving averaging on each data reads (FAH).

People can watch Internet TV anywhere in the world as long as they are connected to Internet. The number of smartphone users has increased so rapidly that almost everybody carries one all the time. Considering availability of Internet TV and popularity of smartphones, we believe that streaming out videos that introduce local culture on an Internet TV is one of the most efficient ways of publicizing Korean culture and attracting tourists. Therefore, we have built Gyeongju Smart Broadcasting (GSB) system that is an Internet TV System. This paper introduces our Android application for the system. This application provides nVoD (near video on demand: Movies are streamed with multicast upon a schedule), VOD and primitive location-based services.

This study aims to increase our understanding about information seeking behavior via a field study, mediating user-and system-centered approach. In the user-centered view, we investigate if the information type and value offering channels vary according to information seeking purpose. In addition, we examine which channel the users select for the purpose of information use under the system-centered approach, and what differences occur depending on variables such as researchers’ affiliation and research capabilities. We try to identify characteristics of users in Korea and how they are differentiated with others. A survey was made online over 4 weeks and 921 usable responses were left and used. We suggested five hypotheses in research framework and examine these statistically. In conclusion, we derived some insights for national S&T information service strategies from three perspectives - information service, information brokerage and negotiator perspective against worldwide publishing companies

This paper proposes a new Text Encryption (N-TEA) Algorithm that compresses and encrypts input text before transmitting it to the receiver. The N-TEA algorithm uses a predefined static dictionary providing codewords of only 12 bits as maximum length, and occupying less than 16 Kbytes. The predefined dictionary stores characters, symbols, and few frequently used words. The dictionary is hashed, generating encrypted dictionary of large number of possibilities that is almost impossible to be discovered or broken without knowing the right hashing function. Several hashing functions could be applied for exchanging text data between parties. Although dictionary based text coding is not new, the proposed work is novel, very simple, and generic, having three main advantages over those in the literature. First, the used dictionary is for characters and symbols, instead of the complete dictionary of words and encryption is for the dictionary itself, instead of the original text. Second, no private/public keys are transmitted through communication channels, providing secured data exchange. Third, transmitted data is reduced by at least 25% of its original size at the same time the text is encrypted, transmitting compressed and encrypted data. Thus, the proposed N-TEA algorithm is adequate for real-time applications, resisting many kinds of attacks such as the Brute Force, Meet-in-the-Middle, and Birthday attacks.

The present study analyzes policies on cloud computing (CC) in five countries (USA, UK, Japan, Australia, and Singapore) and deduces their implications. It also suggests and analyzes a list of 15 guidelines, 20 check lists, and a service analysis model to implement a public service based on cloud computing (PSBCC). The outline of the necessary procedure for the implementation of a PSBCC is proposed. The analysis model of the service to be implemented is proposed to select the PSBCC that is to be implement according to the promoted policies. The checklist to determine the PSBCC implementation is proposed, which can also be used as data to examine the validity of the implementation. These suggestions provide a systematic method to establish high-quality PSBCC, and the established PSBCC is expected to reduce Information Communication Technology (ICT) operation costs and promote service innovation from the business perspective.