• 한국정밀공학회지
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• 제25권6호
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• pp.47-54
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• 2008

Fitting process carried out in the automobile transmission assembly line is classified into three classes; heat fitting, press fitting, and their combined fitting. Heat fitting is a method that heats gear to a suitable range under the tempering temperature and squeezes it toward the outer diameter of shaft. Its stress depends on the yield strength of gear. Press fitting is a method that generally squeezes gear toward that of shaft at room temperature by a press. Another method heats warmly gear and safely squeezes it toward that of shaft. Warm shrink fitting process for the automobile transmission part is now gradually increased, but the parts (shaft/gear) assembled by this process produced dimensional changes in both the outer diameter and profile of the gear. So that it may cause noise and vibration between gears. In order to solve these problems, we need an analysis of warm shrink fitting process, in which design parameters are involved; contact pressure according to fitting interference between outer diameter of shaft and inner diameter of gear, fitting temperature, and profile tolerance of gear. In this study, an closed form equation to predict contact pressure and fitting load was proposed in order to develop an optimization technique of the warm shrink fitting process and verified its reliability through the experimental results measured in the field and FEM, that is, thermal-structural coupled field analysis. Actual loads measured in the field was in good agreements with the results obtained by the theoretical and finite element analysis.

• Structural Engineering and Mechanics
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• 제78권3호
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• pp.305-317
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• 2021

An AMD control system is usually built based on the original model of a target building. As a result, the fact leads a large calculation workload exists. Therefore, the orders of a structural model should be reduced appropriately. Among various model-reduction methods, a suitable reduced-order model is important to high-rise buildings. Meanwhile, a partial structural information is discarded directly in the model-reduction process, which leads to the accuracy reduction of its controller design. In this paper, an optimal technique is selected through comparing several common model-reduction methods. Then, considering the dynamic characteristics of a high-rise building, an improved balanced truncation (BT) method is proposed for establishing its reduced-order model. The abandoned structural information, including natural frequencies, damping ratios and modal information of the original model, is reconsidered. Based on the improved reduced-order model, a new reduced-order controller is designed by a regional pole-placement method. A high-rise building with an AMD system is regarded as an example, in which the energy distribution, the control effects and the control parameters are used as the indexes to analyze the performance of the improved reduced-order controller. To verify its effectiveness, the proposed methodology is also applied to a four-storey experimental frame. The results demonstrate that the new controller has a stable control performance and a relatively short calculation time, which provides good potential for structural vibration control of high-rise buildings.

• 한국컴퓨터정보학회논문지
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• 제26권11호
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• pp.11-19
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• 2021

본 논문은 충전식 배터리의 단점을 보완하여 급속 충전과 방전이 가능하고 높은 전력 효율 및 반영구적인 충·방전 사이클 수명의 특성을 갖는 수퍼커패시터를 보조 전력 저장장치로 사용하여 전력 관리 시스템에 결합한 프로토타입 플랫폼을 제안한다. 본 논문의 플랫폼을 위해 물리적인 환경 변화에 따른 태양광 패널에서의 공급 전력 차단 혹은 재개 상태를 마이크로컨트롤러에 연결된 인터럽트를 통해 감지할 수 있는 기법을 개발하였다. 연속적인 전원 공급이 보장되지 않는 컴퓨팅 환경에서 데이터의 유실을 방지하기 위해 전원 공급이 차단되는 경우 휘발성 메모리에 있는 프로그램 문맥 및 데이터를 비휘발성 메모리로 이전하는 낮은 수준의 시스템 소프트웨어를 마이크로컨트롤러에 구현하였다. 실험을 통해 슈퍼커패시터가 보조 전력 저장장치로서 일시적 전원 공급에 효과적으로 하는지를 검증하였으며 다양한 벤치마크를 통해 전원 상태 감지 및 휘발성 메모리에서 비휘발성 메모리로의 프로그램 문맥 및 데이터의 이전 기법이 낮은 오버헤드를 갖음을 확인하였다.

• Journal of Power Electronics
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• 제19권4호
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• pp.846-857
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• 2019

Voltage step-down converters are very popular in distributed power systems, voltage regular modules, electric vehicles, etc. However, a high step-down voltage ratio is required in many applications to prevent the traditional buck converter from operating at extreme duty cycles. In this paper, a series capacitor interleaved buck converter with a soft switching technique is proposed. The DC voltage ratio of the proposed converter is half that of the traditional buck converter and the voltage stress across the one main switch and the diodes is reduced. Moreover, by paralleling the series connected auxiliary switch and the auxiliary inductor with the main inductor, zero voltage transition (ZVT) of the main switches can be obtained without increasing the voltage or current stress of the main power switches. In addition, zero current turned-on and zero current switching (ZCS) of the auxiliary switches can be achieved. Furthermore, owing to the presence of the auxiliary inductor, the turned-off rate of the output diodes can be limited and the reverse-recovery switching losses of the diodes can be reduced. Thus, the efficiency of the proposed converter can be improved. The DC voltage gain ratio, soft switching conditions and a design guideline for the critical parameters are given in this paper. A loss analysis of the proposed converter is shown to demonstrate its advantages over traditional converter topologies. Finally, experimental results obtained from a 100V/10V prototype are presented to verify the analysis of the proposed converter.

• 융합정보논문지
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• 제11권3호
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• pp.132-139
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• 2021

고감쇠 차량이 둔턱(bumped barrier)을 넘어갈 때 발생하는 강제 진동의 응답 특성이 연구되었고, 이와 관련하여 특히 강제 진동 차량에서 변위, 속도 및 가속도의 응답 거동을 분석하였다. 또한, 각각의 응답을 얻기 위해 Runge-Kutta-Gill의 수치해석법을 수행하여 시간영역의 분석을 하였다. 강제 진동 모델의 여러 고감쇠 조건으로 응답 특성을 얻을 수 있었고 질량, 감쇠 및 강성을 달리하여 수치 분석 후, 임펄스 충격력으로 차체에 가해지는 모델을 고려하여 강제력에 의한 차량 모델의 응답 특성을 얻었고 실험 결과와 비교하여 그 모델의 타당성을 밝혔다. 진폭 및 차량의 고유진동수도 고려하여 분석하였고 차량 모델의 나이키스트 선도를 구하여 고감쇠의 정도에 따라 특성을 분석할 수 있었다. 상이한 질량, 감쇠 및 강성에 따라 임펄스 충격력에 의한 강제 진동 응답 특성을 분석하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.21-42
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• 2021

Purpose In order for companies to continue to grow, they should properly manage human resources, which are the core of corporate competitiveness. Employee turnover means the loss of talent in the workforce. When an employee voluntarily leaves his or her company, it will lose hiring and training cost and lead to the withdrawal of key personnel and new costs to train a new employee. From an employee's viewpoint, moving to another company is also risky because it can be time consuming and costly. Therefore, in order to reduce the social and economic costs caused by employee turnover, it is necessary to accurately predict employee turnover intention, identify the factors affecting employee turnover, and manage them appropriately in the company. Design/methodology/approach Prior studies have mainly used logistic regression and decision trees, which have explanatory power but poor predictive accuracy. In order to develop a more accurate prediction model, XGBoost is proposed as the classification technique. Then, to compensate for the lack of explainability, SHAP, one of the XAI techniques, is applied. As a result, the prediction accuracy of the proposed model is improved compared to the conventional methods such as LOGIT and Decision Trees. By applying SHAP to the proposed model, the factors affecting the overall employee turnover intention as well as a specific sample's turnover intention are identified. Findings Experimental results show that the prediction accuracy of XGBoost is superior to that of logistic regression and decision trees. Using SHAP, we find that jobseeking, annuity, eng_test, comm_temp, seti_dev, seti_money, equl_ablt, and sati_safe significantly affect overall employee turnover intention. In addition, it is confirmed that the factors affecting an individual's turnover intention are more diverse. Our research findings imply that companies should adopt a personalized approach for each employee in order to effectively prevent his or her turnover.

• Journal of Forest and Environmental Science
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• 제38권3호
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• pp.141-151
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• 2022

Soil seed banks as natural storage of plant seeds play an important role in the maintenance and regeneration of watershed. Natural regeneration potential of the soil seed bank of Land use types (LUTs) in Ogun River watershed (ORW) was investigated. ORW was stratified using proportionate sampling technique into Guinea Savannah (GS), Rainforest (RF) and Swamp Forest (SF) Ecological Zones (EZs). Three LUTs: Natural Forest (NF), Disturbed Forest (DF) and Farmland (FL) were purposively selected in GS: GSNF, GSDF, GSFL; RF: RFNF, RFDF, RFFL and SF: SFNF, SFDF, SFFL, respectively. Systematic line transects was used in the laying of the sample plots. Sample plots of 25 m×25 m were established in alternate positions. Ten 1 m×1 m quadrats were randomly laid for soil core sampling from previously randomly selected ten plots. The core samples (10) were pooled per plot in each LUT and placed in individual trays. Ten trays with sterilized soil were used as control. The trays were watered regularly and checked for seedlings emergence fortnightly for 18 months. The experimental design used was 3×3 factorial experiments. ANOVA, Diversity index (H') and Similarity index (SI) were used to analyze the data. There was significant difference in seedling emergence among ecological zones and land use types (p<0.05). A total of 4,400 seedlings emerged from the soil samples. All species were distributed among 32 families. FL in the RF had the highest number of germinated seeds (705±37.33 seedlings) followed by DF in the RF (701±49.6 seedlings). The lowest emergence was in NF of the SF (199±28.41 seedlings). DF in the RF had highest number of species (34) distributed among 22 families. Emergence from soil seed bank of NF in ORW was generally with more of tree species than herbs that were predominant in FL and DF.

• 대한물리의학회지
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• 제16권2호
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• pp.9-21
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• 2021

PURPOSE: This study examined the effects of an eight weeks twenty meters walk on the cardiorespiratory fitness and strength of the shoulder extensor, hip extensor, and dorsiflexor of stroke survivor outpatients in two tertiary hospitals in Osogbo, Nigeria. METHODS: A purposive sampling technique was used to select 21 registered right or left outpatient hemiplegic stroke survivors in a pre- and post-test experimental research design. The research questions were presented using the descriptive statistics of frequency, percentage, mean, and standard deviation. The differences between the mean of the cardio-respiratory indices and the muscle strength were tested by repeated measures analysis of variance followed by Bonferroni post-hoc test for multiple comparisons. RESULTS: No significant differences in heart rate were observed at week 0 compared to week 4. A significant decrease was recorded in the parameter at week 8, compared to week 4. Moreover, there were significant decreases in blood pressure and respiratory rate in week 0, compared to week 4, and in the respiratory rate, compared to week 8. In contrast, significant elevations in VO2 max were observed in week 0, compared to week 4, and in the week 4, compared to week 8. Furthermore, significant elevations in muscular strength were documented when comparisons were made at weeks 0, 4, and 8. CONCLUSION: Eight weeks of twenty meters walk aerobic exercise improve the cardio-respiratory fitness and muscular strength of stroke survivor outpatients.

• Steel and Composite Structures
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• 제43권4호
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• pp.447-456
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• 2022

Recent experimental studies showed that deep steel I-shaped profiles classified as high ductility class sections in seismic design international codes exhibit low deformation capacity when subjected to cyclic loading. This paper presents an innovative retrofit solution to increase the rotation capacity of beams using bonded carbon fiber reinforced polymers (CFRP) patches validated with advanced finite element analysis. This investigation focuses on the flexural cyclic behaviour of I-shaped hot rolled steel deep section used as beams in moment-resisting frames (MRF) retrofitted with CFRP patches on the web. The main goal of this CFRP reinforcement is to increase the rotation capacity of the member without increasing the overstrength in order to avoid compromising the strong column-weak beam condition in MRF. A finite element model that simulates the cyclic plasticity behavior of the steel and the damage in the adhesive layer is developed. The damage is modelled using the cohesive zone modelling (CZM) technique that is able to capture the crack initiation and propagation. Details on the modelling techniques including the mesh sensitivity near the fracture zone are presented. The effectiveness of the retrofit solution depends strongly on the selection of the appropriate adhesive. Different adhesive types are investigated where the CZM parameters are calibrated from high fidelity fracture mechanics tests that are thoroughly validated in the literature. This includes a rigid adhesive commonly found in the construction industry and two tough adhesives used in the automotive industry. The results revealed that the CFRP patch can increase the rotation capacity of a steel member considerably when using tough adhesives.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.