The primary suspension system of a railway vehicle restrains the wheelset and the bogie, which greatly affects the dynamic characteristics of the vehicle depending on the stiffness in each direction. In order to improve the dynamic characteristics, different stiffness in each direction is required. However, designing different stiffness in each direction is difficult in the case of a general suspension device. To address this, in this paper, an optimization technique is applied to design different stiffness in each direction by using a conical rubber spring. The optimization is performed by using target and analysis RMS values. Lastly, the final model is proposed by complementing the shape of the weak part of the model. An actual model is developed and the reliability of the optimization model is proved on the basis of a deviation average of about 7.7% compared to the target stiffness through a static load test. In addition, the stiffness value is applied to a multibody dynamics model to analyze the stability and curve performance. The critical speed of the improved model was 190km/h, which was faster than the maximum speed of 110km/h. In addition, the steering performance is improved by 34% compared with the conventional model.
KIPS Transactions on Computer and Communication Systems
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v.8
no.6
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pp.127-138
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2019
The data response speed is a critical issue of cloud services because it directly related to the user experience. As such, the in-memory database is widely adopted in many cloud-based applications for achieving fast data response. However, the current implementation of the in-memory database is mostly based on the linked list-based hash table which cannot guarantee the constant data response time. Thus, cuckoo hashing was introduced as an alternative solution, however, there is a disadvantage that only half of the allocated memory can be used for storing data. Subsequently, bucketized cuckoo hashing (BCH) improved the performance of cuckoo hashing in terms of memory efficiency but still cannot overcome the limitation that the insert overhead. In this paper, we propose a data management solution called Wall Cuckoo which aims to improve not only the insert performance but also lookup performance of BCH. The key idea of Wall Cuckoo is that separates the data among a bucket according to the different hash function be used. By doing so, the searching range among the bucket is narrowed down, thereby the amount of slot accesses required for the data lookup can be reduced. At the same time, the insert performance will be improved because the insert is following up the operation of the lookup. According to analysis, the expected value of slot access required for our Wall Cuckoo is less than that of BCH. We conducted experiments to show that Wall Cuckoo outperforms the BCH and Sorting Cuckoo in terms of the amount of slot access in lookup and insert operations and in different load factor (i.e., 10%-95%).
This study deals with the case of student-centered discrete mathematics class with cyber lab. First, we provided lecture notes and cyber labs we developed. In particular, discrete mathematics is a course that covers the principles of algorithms. The purpose of this study is to provide students with basic mathematics, aiming to actively participate in the learning process, to improve their abilities and to reach the ultimate goal of student success with confidence. Second, based on interactions, students were able to prepare for the lectures, review, question, answer, and discussion through an usual learning management system of the school. Third, all the students generated materials through one semester, which were reported, submitted, presented and evaluated. It was possible to improve the learning effectiveness through the discussions and implementation of using some easy open source programming language and codes. Our discrete math laboratory could be practiced without any special knowledge of coding. These lecture models allow students to develop critical thinking skills while describing and presenting their learning and problem-solving processes. We share our experience and our materials including lecture note and cyber lab as well as a possible model of student-centered mathematics class that does not give too much of work load for instructors. This study shares a model that demonstrates that any professor will be able to have an individualized, customized, and creative discrete education without spending much of extra time and assistant, unlike previous research.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.1
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pp.391-400
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2019
In the case of fire, a structure loses its original stiffness due to the temperature rise, and the load bearing capacity decreases. The loss of structural strength increases with increasing fire time of the structure. To prevent the collapse of buildings, it is very important to understand whether or not the members are damaged. On the other hand, there is insufficient data to be a guideline for diagnosing and evaluating the residual strength of the members in Korea. Therefore, this study examined the resistance performance by Finite-Element-Analysis of composite beams, which are composite structures among structural members. Composite beam modeling was carried out based on the model used in the Electrical Penetration Room (EPR) in cooperation with KEPCO. The heat transfer analysis and structural analysis of the critical phase were performed using ANSYS, a finite element analysis program. ANSYS was used to perform heat transfer analysis and structural analysis at the static analysis. To analyze the residual performance, the temperature distribution of the composite beam and the maximum displacement result of the heat-affected structure analysis were derived and the experimental data and the structural analysis result data were compared and analyzed.
The yaw and interference effects of blades affect aerodynamic performance of large wind turbine system significantly, thus influencing wind-induced response and stability performance of the tower-blade system. In this study, the 5MW wind turbine which was developed by Nanjing University of Aeronautics and Astronautics (NUAA) was chosen as the research object. Large eddy simulation on flow field and aerodynamics of its wind turbine system with different yaw angles($0^{\circ}$, $5^{\circ}$, $10^{\circ}$, $20^{\circ}$, $30^{\circ}$ and $45^{\circ}$) under the most unfavorable blade position was carried out. Results were compared with codes and measurement results at home and abroad, which verified validity of large eddy simulation. On this basis, effects of yaw angle on average wind pressure, fluctuating wind pressure, lift coefficient, resistance coefficient,streaming and wake characteristics on different interference zone of tower of wind turbine were analyzed. Next, the blade-cabin-tower-foundation integrated coupling model of the large wind turbine was constructed based on finite element method. Dynamic characteristics, wind-induced response and stability performance of the wind turbine structural system under different yaw angle were analyzed systematically. Research results demonstrate that with the increase of yaw angle, the maximum negative pressure and extreme negative pressure of the significant interference zone of the tower present a V-shaped variation trend, whereas the layer resistance coefficient increases gradually. By contrast, the maximum negative pressure, extreme negative pressure and layer resistance coefficient of the non-interference zone remain basically same. Effects of streaming and wake weaken gradually. When the yaw angle increases to $45^{\circ}$, aerodynamic force of the tower is close with that when there's no blade yaw and interference. As the height of significant interference zone increases, layer resistance coefficient decreases firstly and then increases under different yaw angles. Maximum means and mean square error (MSE) of radial displacement under different yaw angles all occur at circumferential $0^{\circ}$ and $180^{\circ}$ of the tower. The maximum bending moment at tower bottom is at circumferential $20^{\circ}$. When the yaw angle is $0^{\circ}$, the maximum downwind displacement responses of different blades are higher than 2.7 m. With the increase of yaw angle, MSEs of radial displacement at tower top, downwind displacement of blades, internal force at blade roots all decrease gradually, while the critical wind speed decreases firstly and then increases and finally decreases. The comprehensive analysis shows that the worst aerodynamic performance and wind-induced response of the wind turbine system are achieved when the yaw angle is $0^{\circ}$, whereas the worst stability performance and ultimate bearing capacity are achieved when the yaw angle is $45^{\circ}$.
Kim, Seon-Jin;Park, Jin-Won;Kim, Sung-Gon;Kang, Tae-Woo;Shin, Cheol-Ho
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.5
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pp.468-476
/
2019
This paper presents the means of improving the strength of LTV's FRP structure for resolve and prevent quality problems. LTV secures enough kerb weight by applying FRP materials at hood and rear van assembly. However, because of FRP's inherent limitations, many initial quality problems such as crack at connections have occurred. Moreover, hood assy' is concerned about fall of endurance, because hood assy' have operated in abnormal condition. Therefore, this study executes lamination structure optimizations of FRP structure for improving bending strength. As a results, hood and rear van's bending strength at connections is improved 8.1 times and 1.5 times, respectively. Also hood assy's plate secures endurance life and improve 1.7 times of critical load about abnormal operating conditions through 1.4 times improvement of bending strength.
In a biological aerated filter (BAF) packed with ceramic media (void fraction of BAF=0.32), nitrite accumulation was studied with the variation of hydraulic retention time (HRT) and superficial air velocity. Synthetic ammonium wastewater and petrochemical wastewater were fed at a constant load of $1.6kgNH_4^+-N/m^3{\cdot}d$. Ammonium removal rate was mainly affected by the superficial air velocity in BAF, but nitrite ratio($NO_2-N/NO_x-N$) in the effluent was dependent on both HRT and superficial air velocity. For a fixed HRT of 0.23 hr (corresponding to the empty bed contact time of 0.7 hr) ammonium removal rate was 73/90/92% and nitrite ratio was 0.92/0.82/0.48 at the superficial air velocity of 0.23/0.45/0.56 cm/s, respectively. When HRT is increased to 0.9 hr with superficial air velocity ranging from 0.34 to 0.45 cm/s, the ammonium removal rate was 89% on average. However nitrite ratio decreased significantly down to 0.13. When HRT was further increased to 1.4 hr, ammonium removal rate decreased, thereby resulting in the free ammonia ($NH_3-N$, FA) build-up and nitrite ratio gradually increased (>0.95). Although aeration rate and FA concentration at HRT of 0.23 hr were unfavorable for nitrite accumulation compared with those at HRT of 0.9 hr, nitrite ratio at HRT of 0.23 hr was higher. Taken together, HRT and nitrogen load were found to be critical, in addition to FA concentration and aeration condition, for nitrite accumulation in the BAF tested in the present study.
The CY can be said to function in various respect as a buffer zone between the maritime and overland inflow-outflow of container. The amount of storage area needed requires a very critical appraisal at pre-operational stage. A container terminal should be designed to handle and store containers in the most efficient and economic way possible. In order to achieve this aim it is necessary to figure out or forecast numbers and types of containers to be handled, CY area required, and internal handling systems to be adopted. This paper aims to calculate the CY area required for each container handling system in Mokpo New Port. The CY area required are directly dependent on the equipment being used and the storage demand. And also the CY area required depends on the dwell time. Furthermore, containers need to be segregated by destination, weight, class, FCL(full container load), LCL(less than container load), direction of travel, and sometimes by type and often by shipping line or service. Thus the full use of a storage area is not always possible as major unbalances and fluctuations in these flow occuring all the time. The calculating CY area must therefore be taken into account in terms of these operational factors. For solving such problem, all these factors have been applied to estimation of CY area in Mokpo New Port. The CY area required in Mokpo New Port was summarized in the conclusion section.
To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.
Ouda, SM;Khairy, AM;Sorour, Ashraf E;Mikhail, Mikhail Nasr
Asian Pacific Journal of Cancer Prevention
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v.16
no.17
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pp.7825-7829
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2015
Background: Egypt has the highest prevalence of HCV infection in the world (~14.7%). Around 10-15% of HCV-infected persons will advance to cirrhosis within the first 20 years. The incidence of HCC is expected to grow in the next two decades, largely due to HCV related cirrhosis, and detection of HCC at an early stage is critical for a favorable clinical outcome. No simple reliable non-invasive marker has been available till now. B2M, a non-glycosylated polypeptide composed of 99 amino acids, is one of the components of HLA class I molecules on the surfaces of all nucleated cells. It has been reported that the level of serum B2M is elevated in patients with chronic hepatitis C and HCV-related HCC when compared to HCV-negative patients or healthy donors. Determining the clinical utility of serum B2M as a marker for disease progression in Egyptian patients with HCV related chronic hepatitis, cirrhosis and hepatocellular carcinoma was the aim of the present study. Materials and Methods: In this analytical cross sectional study 92 participants were included in 4 equal groups: Group (1) non cirrhotic chronic HCV; Group (2) HCV related liver cirrhosis; Group (3) HCC on top of HCV,; and Group (4) healthy controls. History taking, clinical examination, routine labs and abdominal ultrasound were conducted for all patients, PCR and Metavir scores for group (1) patients, and triphasic CT abdomen and AFP for Group (3) patients. B2M levels were measured in serum with a fully-automated IMX system. Results: The mean serum B2M level of Group (1) was $4.25{\pm}1.48{\mu}g/ml$., Group (2) was $7.48{\pm}3.04$, Group (3) was $6.62{\pm}2.49$ and Group (4) was $1.62{\pm}0.63$. Serum B2M levels were significantly higher in diseased than control group (p<0.01) being significantly higher in cirrhosis ($7.48{\pm}3.04$) and HCC groups ($6.62{\pm}2.49$) than the HCV group ($4.25{\pm}1.48$) (p<0.01). There was a significant correlation between B2M Level and ALK, total and direct bilirubin and INR (p<0.05), and a significant inverse correlation between B2M level and albumin, total proteins, HB andWBCS values (p<0.05). There was no significant correlation between B2M level and viral load or Metavir score, largest tumour size or AFP (p>0.05). The best B2M cut-off for HCV diagnosis was 2.6 with a sensitivity of 100%, a specificity of 92%, a positive predictive value (PPV) of 97% and a negative predictive value (NPV) of 100%. The best B2M cut-off for HCC diagnosis was 4.55 which yielded sensitivity, specificity, positive predictive value, negative predictive values of 74%, 62%, 39.5, 87.8% respectively (p-value <0.01) while best cut-off for cirrhosis was 4.9, with sensitivity 74 % and specificity 74%.The sensitivity for HCC diagnosis increased upon B2M and AFP combined estimation to 91%, specificity to 79%, NPV to 95% and accuracy to 83%. Conclusions: Serum B2M level is elevated in HCV related chronic liver diseases and may be used as a marker for HCV disease progression towards cirrhosis and carcinoma.
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