• Journal of Agricultural Extension & Community Development
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• v.4 no.1
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• pp.97-120
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• 1997

This study intends to develop a computer software for an efficient swineherd production and management. Current softwares are concerned on the sow management and ignore the actual farm environment. This study focuses on the farm environment in developing the software and covers the production management financial management, marketing management, and business planning for swineherd farm. The FSR(Farming Systems Research) analysis and interview survey aye applied to collect the data for the system planning, farmer's demand and analysis on the system, system design and program development. The systems are designed to meet the needs for the progressive swineherd farmers. Visual FoxPro 5.1 is used to develop the system. The developed system includes pig farm financial records keeping and management, pig farm production management program, pig farm marketing management program, and pig farm business diagnosis and planning program to meet the scope of the study. The weekly maintenance records and financial records are adopted for the input interface since most of farmers use their computer less than 5 hours a week. Pulldown Menu systems are adopted and designed for easy use by structuring to meet the pig farm and system demands. The manu system allocates the input-output screen based on the sectors, scopes, users, frequencies, importances, and the usages of the information. The GUI(Graphic User Interface) method is used to develop input-output screens for easy use. Backward Chaining mechanism fo the Expert System is used in the diagnosis of the pig farm management and the Systems Simulators Approach is used in the pig farm management planning.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.34-49
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• 2012

Recently, the smart grid (SG) has been introduced to solve the serious network issues caused by the increasing electrical demand and the complex nonlinear nature of the electric power distribution network. The SG, regarded as the next generation power grid, can transmit power in more efficient ways by building an automatic and distributed energy delivery network. In this paper, we first assess how various existing networking technologies, such as IEEE 802.11 (WiFi) and IEEE 802.15.4 (ZigBee), meet the requirements of the SG communication protocols. Specifically, we classify the existing network protocols into three categories: WSN-based networking, WiFi-based networking, and wireline-based networking. We then survey the security issues regarding the SG. Finally, we propose an agile SG networking architecture and show the effectiveness of different adopted networking technologies and, as a result, present a candidate solution to implement agile networking in SGs.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.307-314
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• 2022

Recently, researches using deep learning-based models are being actively conducted to replace statistical-based time series forecast techniques to predict electric power demand. The result of analyzing the researches shows that the performance of the LSTM-based prediction model is acceptable, but it is not sufficient for long-term regional-wide power demand prediction. In this paper, we propose a WaveNet deep learning model to predict electric power demand 24-hour-ahead with temperature data in order to achieve the prediction accuracy better than MAPE value of 2% which statistical-based time series forecast techniques can present. First of all, we illustrate a delated causal one-dimensional convolutional neural network architecture of WaveNet and the preprocessing mechanism of the input data of electric power demand and temperature. Second, we present the training process and walk forward validation with the modified WaveNet. The performance comparison results show that the prediction model with temperature data achieves MAPE value of 1.33%, which is better than MAPE Value (2.33%) of the same model without temperature data.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.6
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• pp.221-228
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• 2018

With an increase in demand for the high added value of shipbuilding and marine industry based on the information and communications technology (ICT), software technology has become more important than ever in the industry. In this paper, we present the result of our preliminary investigation on the current software development environment in the shipbuilding and marine industry in order to develop reusable software component, which can enhance the competitiveness of software development. The investigation is performed based on the survey answers from 34 developers who are working in different shipbuilding and marine companies. The questionnaire is composed of items to gather the information of each company such as the number of employees and product domain, and actual software development environment such as operating system, programming languages, deployment format, obstacles for developing components, and the adoption of software development methods and tools. According to the results of the survey, the most important consideration to select their development platform was the number of available utilities and the technical supports, followed by performance, price and security problems. In addition, the requirements of various platforms supporting and the higher reliability, and the limitations of low development cost and manpower made it difficult for them to develop reusable software components. Finally, throughout the survey, we find out that only 15% of developers used software development processes and managed the quality to systematically develop their software products, therefore, shipbuilding and marine companies need more technical and institutional support to improve their ability to develop high qualified software.

• ETRI Journal
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• v.40 no.2
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• pp.227-236
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• 2018

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

• Nuclear Engineering and Technology
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• v.49 no.8
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• pp.1629-1635
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• 2017

Reliable prediction of nuclear fuel rod behavior of nuclear power reactors constitutes a basic demand for steady-state calculations, design purposes, and fuel performance assessment. Perfect design of fuel rods as the first barrier against fission product release is very important. Simulation of fuel rod performance with a code or software is one of the fuel rod design steps. In this study, a software program called MARCODE is developed in MATLAB environment that can analyze the temperature distribution, gap conductance value, and fuel and clad displacement in both solid and annular fuel rods. With a comparison of the maximum fuel temperature, fuel average temperature, fuel surface temperature, and gap conductance in solid and annular fuel, the effects of a central hole on the fuel temperature distribution are investigated.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.69-77
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• 2021

The widely used low-cost design methodology for IoT devices is very popular. In such a networked device, memory is composed of flash memory, SRAM, DRAM, etc., and because it processes a large amount of data, memory design is an important factor for system performance. Therefore, each device selects optimized design factors such as function, performance and cost according to market demand. The design of a memory architecture available for low-cost IoT devices is very limited with the configuration of SRAM, flash memory, and DRAM. In order to process as much data as possible in the same space, an architecture that supports parallel processing units is usually provided. Such parallel architecture is a design method that provides high performance at low cost. However, it needs precise software techniques for instruction and data mapping on the parallel architecture. This paper proposes an instruction/data mapping method to support optimized parallel processing performance. The proposed method optimizes system performance by actively using hardware and software parallelism.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.857-859
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• 2022

본 연구는 인공지능 기반의 전력 수요 데이터 예측 모델을 구축하고 이를 최종적으로 웹의 형태로 구현하는 것을 목표로 하였다. 기상청 데이터의 기후 요소를 매개변수로 삼아 전력 수요를 예측하고, 그 결과를 가시적으로 시각화하는 것까지의 전 과정을 최대한 간결하게 진행하였다. 추후 한층 더 발전된 모델을 구축할 수 있다면, 전력시장의 효율성과 경제성을 향상시켜 불필요한 에너지 낭비를 미연에 방지할 수 있을 것이라고 기대한다. 나아가 시스템 상용화를 위해 계속 연구 활동에 정진할 수 있을 것이다.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.102-118
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• 2022

With the development of digital content software production technology and the technological progress of related hardware, the social status quo in the post-epidemic era, the popularization and application of 5G networks, the market and consumers' increasing demand for digital content products, artificial intelligence, virtual digital human, virtual Idols, virtual live, self-media content and metaverse-related content industries are all developing rapidly. Virtual idols, virtual digital human, etc. are not only accelerating innovation in production technology. The economic cost, technical difficulty and time requirements of production are also greatly reduced. With the arrival and development of the Metaverse, the author believes that the content industry with virtual digital humans as the core will continue to develop in the direction of refinement, specialization, facilitation and customization. In this article, we will analyze and study the production of virtual digital human based on Photoscan technology and Unreal Engine 5 Metahuman software, and discuss the application status and future development of related content.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.163-171
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• 2012

Demand Responsive Transit (DRT) services are becoming necessary as part of not only alternative transportation means for elderly and mobility impaired passengers, but also sustainable and flexible transportation options in urban area due to the development of communication technologies and Location Based Services (LBS). It is difficult to investigate the system performance regarding vehicle operational schemes and vehicle routing algorithms due to the lack of commercial software to support door-to-door vehicle simulation for larger area. This study proposes a simulation framework to evaluate innovative and flexible transit systems focusing on various vehicle routing algorithms, which describes data-type requirements for simulating door-to-door service on demand. A simulation framework is applied to compare two vehicle dispatch algorithms, Nearest Vehicle Dispatch (NVD) and Insertion Heuristic (IH) for real-time shared-taxi service in Seoul. System productivity and efficiency of the shared-taxi service are investigated, comparing to the conventional taxi system.