• Journal of Information Processing Systems
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• v.18 no.4
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• pp.549-561
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• 2022

In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.363-384
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• 2011

As the complexity of software is increasing, generating an effective test data has become a necessity. This necessity has increased the demand for techniques that can generate test data effectively. This paper proposes a test data generation technique based on adequacy based testing criteria. Adequacy based testing criteria uses the concept of mutation analysis to check the adequacy of test data. In general, mutation analysis is applied after the test data is generated. But, in this work, we propose a technique that applies mutation analysis at the time of test data generation only, rather than applying it after the test data has been generated. This saves significant amount of time (required to generate adequate test cases) as compared to the latter case as the total time in the latter case is the sum of the time to generate test data and the time to apply mutation analysis to the generated test data. We also use genetic algorithms that explore the complete domain of the program to provide near-global optimum solution. In this paper, we first define and explain the proposed technique. Then we validate the proposed technique using ten real time programs. The proposed technique is compared with path testing technique (that use reliability based testing criteria) for these ten programs. The results show that the adequacy based proposed technique is better than the reliability based path testing technique and there is a significant reduce in number of generated test cases and time taken to generate test cases.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1035-1043
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• 2021

An Internet of Things (IOT) sensor network is an effective solution for monitoring environmental conditions. However, IOT sensor networks generate massive data such that the abilities of massive data storage, processing, and query become technical challenges. To solve the problem, a Hadoop cloud platform is proposed. Using the time and workload genetic algorithm (TWLGA), the data processing platform enables the work of one node to be shared with other nodes, which not only raises efficiency of one single node but also provides the compatibility support to reduce the possible risk of software and hardware. In this experiment, a Hadoop cluster platform with TWLGA scheduling algorithm is developed, and the performance of the platform is tested. The results show that the Hadoop cloud platform is suitable for big data processing requirements of IOT sensor networks.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2403-2413
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• 1999

There is a strong need to develop a software cost estimation model on economic value perspective. The objective of this research is to improve current software cost estimation method on economic value perspective. We reviewed domestic and foreign researches and practices on software cost estimation with function point method, and derived promising alternative models. Pilot simulation was performed with real project data, and the probable best model was chosen. We collected data from 39 Korean companies, and assesed statistical significance of the model with those data. Empirical data shows that more practical model has better prediction accuracy. That is, the number of input and output modules, the number of tables, and the number of algorithms are chosen to be best set of functions. There exists strong correlation between the calculated function points and project effort. And, the revised set of technical complexity factors and evaluation guidelines show practical usefulness. We suggest that the above result be incorporated in a new improved guideline for software cost estimation. By adopting the results of this research to the guideline, we expect that technology innovation will be expedited, and that overall productivity of software industry will be increased.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.313-318
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• 2016

To utilize sensory data, it is necessary to design architecture for processing and handling data generated from sensors in an IoT environment. Especially in the IoT environment, a thing connects to the Internet and efficiently enables to communicate a device with diverse sensors. But Hadoop and Twister based on MapReduce are good at handling data in a batch processing. It has a limitation for processing stream data from a sensor in a motion. Traditional streaming data processing has been mainly applied a MoM based message queuing system. It has maintainability and scalability problems because a programmer should consider details related with complex messaging flow. In this paper architecture is designed to handle sensory data aggregated The designed software architecture is used to operate an application on the open source framework Storm. The application is conceptually used to transform streaming data which aggregated via sensor gateway by pipe-filter style.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.17-21
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• 1989

6-DOE simulator system is designed to real-time processing for motion control, data acquisition, image generation and image processing etc.. In this paper, we introduce hardware and software design technologies for distributed processing, event-trapping, system monitoring and time scheduling procedure in 6-DOF simulator system design.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

• Journal of Software Engineering Society
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• v.24 no.2
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• pp.47-54
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• 2011

Recently, smart phones are widely used and as the phone sensors are evolved, we can get more various kinds of data from them. Using the data, many researchers take an effort to aware user's situation and the context-awareness for smart phones are actively applied to the real-world applications. However, to make an advanced information from sensing data need complex processing and analyzing information. Some of these computing processes are fully handled on smart phone or some data are processed by transferring to server. In this paper, we proposed a method for reducing user's context data generated on smart phone and designed a context generator. As a result, we can reduce a transmission data size and save a communication cost.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.215-217
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• 2016

With the popularity of smart device, mobile applications are playing more and more important role in people's daily life, these applications stores various information which greatly facilitate the user's daily life. However due to the frequent transmission of data in the network also increases the risk of data leakage, more and more developers began to focus on how to protect user data. Current mainstream development models include Native development, Web development and Hybrid development. Hybrid development is based on JavaScript and HTML5, it has a cross platform advantages similar to Web Apps and a good user experience similar to Native Apps. In this paper according to the features of Hybrid applications, we proposed a security scheme in Hybrid development model implements message-level data encryption to protect user information. And through the performance evaluation we found that in some scenario the proposed security scheme has a better performance.

• Proceedings of the Safety Management and Science Conference
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• 2002.05a
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• pp.31-36
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• 2002

In this paper, we developed a working adaptation evaluation system using finger force measurement which interact between material and biological system. The system consists of a finger force transducer, a signal conditioner, an A/D converter, a computer, and a software system for data processing. The finger force transducer is made by a load cell and a special mechanism. The data processing software controls the A/D converter, data monitoring, and data analysis for group classification. The developed system were tested by 4 different materials in left hand and the finger forte transducer in the other hand's thumb and index finger with 16 persons. As the results of experiments, the developed system could measure the finger force quantitatively and classify the measured values into four groups.