• Title/Summary/Keyword: power assist system

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A Study on Information Strategy Development Using Configuration Management in Large-scale Construction Project (형상관리기법을 활용한 대형 프로젝트 정보화 전략개발)

  • Won, Seo Kyung
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2018.05a
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    • pp.66-67
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    • 2018
  • Large-scale construction projects require various license and technologies for the manufacturing and handling processes. Also, the whole life cycle business process management determines the success of the project. Then, the efficiency of the business conducted by stakeholders and their possessed technology should be enhanced in order to strengthen their competitive power. For this reason, many experts pointed out to focus on the improvement of the life cycle process and efficient management. Since it is very important to keep up-to-date data and utilize it for work during the long-term project to reflect changes in the large-scale project, the most important part of the project management in project is information change management. Therefore, the objective of this study is applying configuration management(CM) technique in order to managing change data generated for planning in early phase. The result of this research will certainly assist the large-scale project managers in the development of information change management system.

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Fuzzy Partitioning of Photovoltaic Solar Power Patterns

  • Munshi, Amr
    • International Journal of Computer Science & Network Security
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    • v.22 no.5
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    • pp.5-10
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    • 2022
  • Photovoltaic systems provide a reliable green energy solution. The sustainability and low-maintenance of Photovoltaic systems motivate the integration of Photovoltaic systems into the electrical grid and further contribute to a greener environment, as the system does not cause any pollution or emissions. Developing methodologies based on machine learning techniques to assist in reducing the burden of studies related to integrating Photovoltaic systems into the electric grid are of interest. This research aims to develop a methodology based on a unsupervised machine learning algorithm that can reduce the burden of extensive studies and simulations related to the integration of Photovoltaic systems into the electrical grid.

Biocompatibility Evaluation of Bent-Type Left Ventricular Assist Device During Long-Term Animal Experiment and Emergent Situation (장기 동물 실험 및 응급상황에서의 곡관형 좌심실보조장치의 생체적합성 평가)

  • Kang, Seong Min;Her, Keun;Choi, Seong Wok
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.38 no.9
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    • pp.739-745
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    • 2014
  • Although medication is given to heart disease patients, conventional medication alone is not sufficient to treat heart disease. However, it has been reported that left ventricular assist device (LVAD) transplantation is an effective bridge to heart transplantation by assisting cardiac function. This study used long-term animal testing and emergency situations with a bovine model (Holstein) and canine model (Labrador-retriever) to evaluate the biocompatibility of LibraHeart-I (LH-1), which is a bent-tube type of LVAD that was developed in a previous study. In the long-term animal testing with the bovine model, the subjects survived for 49 days with no irregularities observed in their complete blood cell counts or the vital sign tests that were carried out during the test period. In short-term animal testing with the canine model, it was observed that blood did not remain inside the LH-I even without power support from an external drive source. In this study, the biocompatibility of the LH-I that was developed in a previous study was verified by the ejection performance during long-term animal testing and emergency situations.

3-D Hetero-Integration Technologies for Multifunctional Convergence Systems

  • Lee, Kang-Wook
    • Journal of the Microelectronics and Packaging Society
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    • v.22 no.2
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    • pp.11-19
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    • 2015
  • Since CMOS device scaling has stalled, three-dimensional (3-D) integration allows extending Moore's law to ever high density, higher functionality, higher performance, and more diversed materials and devices to be integrated with lower cost. 3-D integration has many benefits such as increased multi-functionality, increased performance, increased data bandwidth, reduced power, small form factor, reduced packaging volume, because it vertically stacks multiple materials, technologies, and functional components such as processor, memory, sensors, logic, analog, and power ICs into one stacked chip. Anticipated applications start with memory, handheld devices, and high-performance computers and especially extend to multifunctional convengence systems such as cloud networking for internet of things, exascale computing for big data server, electrical vehicle system for future automotive, radioactivity safety system, energy harvesting system and, wireless implantable medical system by flexible heterogeneous integrations involving CMOS, MEMS, sensors and photonic circuits. However, heterogeneous integration of different functional devices has many technical challenges owing to various types of size, thickness, and substrate of different functional devices, because they were fabricated by different technologies. This paper describes new 3-D heterogeneous integration technologies of chip self-assembling stacking and 3-D heterogeneous opto-electronics integration, backside TSV fabrication developed by Tohoku University for multifunctional convergence systems. The paper introduce a high speed sensing, highly parallel processing image sensor system comprising a 3-D stacked image sensor with extremely fast signal sensing and processing speed and a 3-D stacked microprocessor with a self-test and self-repair function for autonomous driving assist fabricated by 3-D heterogeneous integration technologies.

A study on the influence of process parameters during laser welding of sheet steels (강판의 레이저 용접시 공정변수의 영향에 관한 연구)

  • Park, Young-Soo;Lee, Yoon-Sik;Kim, Hyung-Sik;Kim, Chan
    • Laser Solutions
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    • v.2 no.3
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    • pp.11-18
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    • 1999
  • This paper describes the weldability of carbon steel and stainless steel using 5㎾ $CO_2$ laser system with nearly multi-mode beam and a parabolic focusing mirror. In the laser welding of steels, major welding parameters are focal point, travel speed, beam power, shield gas and gap tolerance, etc.. Two kinds of gases(Ar, He) were used as a assist gas and supplied through the external nozzle. It is very important for optimum condition to remove plasma plume which absorbs laser beam and to obtain deep penetration and sound weld bead. Bead-on-plate welding tests were carried out for the experiments. Penetration data were obtained with various welding parameters and the effects of welding parameters were discussed. Butt welding tests were performed with various conditions. Only the optimum laser parameters assured good weld quality As a result of this study, We achieve the fundamental weldabilities using a high power $CO_2$ laser for carbon steel and stainless steel.

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Approach to diagnosing multiple abnormal events with single-event training data

  • Ji Hyeon Shin;Seung Gyu Cho;Seo Ryong Koo;Seung Jun Lee
    • Nuclear Engineering and Technology
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    • v.56 no.2
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    • pp.558-567
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    • 2024
  • Diagnostic support systems are being researched to assist operators in identifying and responding to abnormal events in a nuclear power plant. Most studies to date have considered single abnormal events only, for which it is relatively straightforward to obtain data to train the deep learning model of the diagnostic support system. However, cases in which multiple abnormal events occur must also be considered, for which obtaining training data becomes difficult due to the large number of combinations of possible abnormal events. This study proposes an approach to maintain diagnostic performance for multiple abnormal events by training a deep learning model with data on single abnormal events only. The proposed approach is applied to an existing algorithm that can perform feature selection and multi-label classification. We choose an extremely randomized trees classifier to select dedicated monitoring parameters for target abnormal events. In diagnosing each event occurrence independently, two-channel convolutional neural networks are employed as sub-models. The algorithm was tested in a case study with various scenarios, including single and multiple abnormal events. Results demonstrated that the proposed approach maintained diagnostic performance for 15 single abnormal events and significantly improved performance for 105 multiple abnormal events compared to the base model.

The Design of a Biomedical Signal Measure System Based on Sensor Networks (센서 네트워크 기반의 생체 신호 측정 시스템 설계)

  • Lee, Jin-Kwan;Lee, Dae-Hyung;Jung, Kyu-Cheol;Jang, Hae-Suk;Lee, Jong-Chan;Park, Ki-Hong
    • Convergence Security Journal
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    • v.7 no.1
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    • pp.35-43
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    • 2007
  • The object of this paper is to design a biomedical signal measure systems based on sensor networks for the patient, integrated with computing technology. Using a combination of zigbee RF, embedded hardware and software technologies, as it allows the healthcare center to receive the information on emergency situations and the ordinary state of the patients individually or simultaneously, the healthcare center can copy with quickly a state of emergency and assist the normal life of the patient. In order to meet the low power and other requirements for the proposed system, we introduce a zigbee based RP which is the most suitable solution for improving the performance of our beeper system.

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Load Balancing Approach to Enhance the Performance in Cloud Computing

  • Rassan, Iehab AL;Alarif, Noof
    • International Journal of Computer Science & Network Security
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    • v.21 no.2
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    • pp.158-170
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    • 2021
  • Virtualization technologies are being adopted and broadly utilized in many fields and at different levels. In cloud computing, achieving load balancing across large distributed virtual machines is considered a complex optimization problem with an essential importance in cloud computing systems and data centers as the overloading or underloading of tasks on VMs may cause multiple issues in the cloud system like longer execution time, machine failure, high power consumption, etc. Therefore, load balancing mechanism is an important aspect in cloud computing that assist in overcoming different performance issues. In this research, we propose a new approach that combines the advantages of different task allocation algorithms like Round robin algorithm, and Random allocation with different threshold techniques like the VM utilization and the number of allocation counts using least connection mechanism. We performed extensive simulations and experiments that augment different scheduling policies to overcome the resource utilization problem without compromising other performance measures like makespan and execution time of the tasks. The proposed system provided better results compared to the original round robin as it takes into consideration the dynamic state of the system.

An Efficient Artificial Intelligence Hybrid Approach for Energy Management in Intelligent Buildings

  • Wahid, Fazli;Ismail, Lokman Hakim;Ghazali, Rozaida;Aamir, Muhammad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.12
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    • pp.5904-5927
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    • 2019
  • Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

Distribution Remote Management System Design and Program Development Based on ADWHM(Advanced Digital Watt-Hour Meter) (차세대 디지털 적산전력계에 기반한 배전원격관리시스템 설계 및 프로그램 개발)

  • Ha Bok-Nam;Ko Yun-Seok
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.54 no.4
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    • pp.185-192
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    • 2005
  • This paper proposes a DRMS(Distribution Remote Management System) which can enhance highly the economics of automatic metering system and the power quality supplied to the electric customer improving the efficiency of the meter reading, voltage management and load management work by realizing the remote meter reading, the remote voltage management and the remote load management based on the ADWHM(Advanced Digital Watt Hour Meter). The DRMS is designed so that the voltage management and load management work in remote site can be processed by collecting the voltage pattern and current pattern as well as watt hour data from all ADWHMs one time every month regularly or from special ADWHMS several time irregularly, A new on-line voltage and load management strategy based on the ADWHM is designed by analyzing the existing voltage management and load management process. Also, DRMS is designed so that watt-hour data, voltage pattern data, load pattern data and power factor data can be collected selectively according to the selection of user to assist effectively the methodology. Remote management program and database of the DRMS are implemented based on Visual C++, MFC and database library of MS. Also, DRMS is designed so as to communicate with the ADWHM using RS232C-TCP/IP converter and ADSL. The effectiveness of the remote metering function is proven by collecting and analyzing the data after ADWHMs installed in any site. The developed strategy and program also is verified through the simulation of voltage management and load management.