• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4706-4724
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• 2020

With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

• Advances in Computational Design
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• v.6 no.1
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• pp.15-30
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• 2021

With improvement in innovative manufacturing technologies, it became possible to fabricate any complex shaped structural design for practical applications. This allows for the fabrication of curvilinearly stiffened pressure vessels and pipes. Compared to straight stiffeners, curvilinear stiffeners have shown to have better structural performance and weight savings under certain loading conditions. In this paper, an optimization framework for designing curvilinearly stiffened composite pressure vessels and pipes is presented. NURBS are utilized to define curvilinear stiffeners over the surface of the pipe. An integrated tool using Python, Rhinoceros 3D, MSC.PATRAN and MSC.NASTRAN is implemented for performing the optimization. Rhinoceros 3D is used for creating the geometry, which later is exported to MSC.PATRAN for finite element model generation. Finally, MSC.NASTRAN is used for structural analysis. A Bi-Level Programming (BLP) optimization technique, consisting of Particle Swarm Optimization (PSO) and Gradient-Based Optimization (GBO), is used to find optimal locations of stiffeners, geometric dimensions for stiffener cross-sections and layer thickness for the composite skin. A cylindrical pipe stiffened by orthogonal and curvilinear stiffeners under torsional and bending load cases is studied. It is seen that curvilinear stiffeners can lead to a potential 10.8% weight saving in the structure as compared to the case of using straight stiffeners.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1744-1760
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• 2021

Since correlation filter appeared in the field of object tracking, it plays an increasingly vital role due to its excellent performance. Although many sophisticated trackers have been successfully applied to track the object accurately, very few of them attaches importance to the scale and rotation estimation. In order to address the above limitation, we propose a novel method combined with Fourier-Mellin transform and confidence evaluation strategy for robust object tracking. In the first place, we construct a correlation filter to locate the target object precisely. Then, a log-polar technique is used in the Fourier-Mellin transform to cope with the rotation and scale changes. In order to achieve subpixel accuracy, we come up with an efficient surface fitting mechanism to obtain the optimal calculation result. In addition, we introduce a confidence evaluation strategy modeled on the output response, which can decrease the impact of image noise and perform as a criterion to evaluate the target model stability. Experimental experiments on OTB100 demonstrate that the proposed algorithm achieves superior capability in success plots and precision plots of OPE, which is 10.8% points and 8.6% points than those of KCF. Besides, our method performs favorably against the others in terms of SRE and TRE validation schemes, which shows the superiority of our proposed algorithm in scale and rotation evaluation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.36-42
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• 2021

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.578-595
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• 2020

Submarine pressure hulls must withstand high hydraulic pressure and be free of defects. To improve the precision of defect detection, we herein examined different probes for optimal defect assessment by applying the Phased Array Ultrasonic Testing (PAUT) method. Two sets of probe design parameters were selected by considering pressure hull characteristics and analyzed through modeling. PAUT probes were applied, and defect assessment results were compared based on ultrasonic signals of various simulated defects in specimens designed to be the same as actual pressure hulls. The final selected design parameters for the submarine probe, which were designed to minimize the grating lobe of wave interference effect and improve the ultrasonic resolution of pressure hull welds, were identified through the experiment. The improvement in the probe's ability to detect defects in a pressure hull was verified. Furthermore, the accuracy of defect length measurement was improved, enhancing the applicability of the technique.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.76-83
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• 2020

Postal logistics organizations are characterized as having high labor intensity and short response times. These characteristics, along with rapid change in mail volume, make load scheduling a fundamental concern. Load analysis of major postal infrastructures such as post offices, sorting centers, exchange centers, and delivery stations is required for optimal postal logistics operation. In particular, the performance of mail traffic forecasting is essential for optimizing the resource operation by accurate load analysis. This paper addresses a traffic forecast problem of postal parcel that arises at delivery stations of Korea Post. The main purpose of this paper is to describe a method for predicting short-term traffic of postal parcel based on self-similarity analysis and to introduce an application of the traffic prediction model to postal logistics system. The proposed scheme develops multiple regression models by the clusters resulted from feature engineering and individual models for delivery stations to reinforce prediction accuracy. The experiment with data supplied by main postal delivery stations shows the advantage in terms of prediction performance. Comparing with other technique, experimental results show that the proposed method improves the accuracy up to 45.8%.

• Biomedical Science Letters
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• v.26 no.4
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• pp.302-309
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• 2020

Human Coxsackievirus B5 (HuCoxV-B5) infection has been associated with various diseases such as myocarditis, aseptic meningitis, hand-foot-and mouth-disease, and insulin-dependent diabetes. HuCoxV-B5 is a virus transmitted through the fecal-oral route and is detected in clinics, aquatic environments, food, shellfish, etc. and is one of the more important viruses in public health because of its incidence rate reported worldwide. In this study, a combination of SYBR Green-based real-time PCR primers for molecular diagnosis including monitoring of HuCoxV-B5 was selected and the optimal reaction conditions were established. Compared with the previously reported TaqMan probe-based real-time PCR method, assessments including a sample applicability test were performed. Results showed that the real-time PCR method developed in this study was suitable for a molecular diagnostic technique for detecting HuCoxV-B5. This study is expected to contribute to efforts in responding to safety accidents in public health because the proposed method facilitates rapid diagnosis of clinical patients. It can also be used as a specific monitoring tool of HuCoxV-B5 in non-clinical areas such as aquatic environments among others.

• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.100-105
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• 2021

This paper proposes the polydimethylsiloxane (PDMS) blade coating method for fabrication of paper-based analytical device (PAD) that is able to monitor the disease diagnosis and progress without special analytical equipment. The mold that has PAD design is easily modified by using laser cutting technique. And the fabricated mold is used for hydrophobic barrier formation by blade coating. We have optimized the stable formation of PDMS hydrophobic barrier as blade coating condition, which is established by analyzing the structure of the PDMS hydrophobic barrier and change of hydrophilic channel size as thickness of the ink and contact time with the chromatography paper. Based on optimal condition, we demonstrate that PAD as biosensor can apply to detect protein, glucose, and metal ion without special analysis equipment.

• Journal of Yeungnam Medical Science
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• v.38 no.1
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• pp.19-26
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• 2021

Adhesive capsulitis of the shoulder joint is a common disease characterized by pain at the insertional area of the deltoid muscle and decreased range of motion. The pathophysiological process involves fibrous inflammation of the capsule and intraarticular adhesion of synovial folds leading to capsular thickening and contracture. Regarding the multidirectional limitation of motion, a limitation in external rotation is especially prominent, which is related to not only global fibrosis but also to a localized tightness of the anterior capsule. Ultrasound and magnetic resonance imaging studies can be applied to rule out other structural lesions in the diagnosis of adhesive capsulitis. Hydraulic distension of the shoulder joint capsule provides pain relief and an immediate improvement in range of motion by directly expanding the capsule along with the infusion of steroids. However, the optimal technique for hydraulic distension is still a matter of controversy, with regards to the infusion volume and rupture of the capsule. By monitoring the real-time pressure-volume profile during hydraulic distension, the largest possible fluid volume can be infused without rupturing the capsule. The improvement in clinical outcomes is shown to be greater in capsule-preserved hydraulic distension than in capsule-ruptured distension. Moreover, repeated distension is possible, which provides additional clinical improvement. Capsule-preserved hydraulic distension with maximal volume is suggested to be an efficacious treatment option for persistent adhesive capsulitis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.170-175
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• 2022

Reactive failure management techniques are required to mitigate the impact of errors in high performance computing. Checkpoint is the standard recovery technique for coping with errors. An application employing checkpoints periodically saves its state, so that when an error occurs while some task is executing, the application is rolled back to its last checkpointed task and resumes execution from that task onward. In this paper, assuming the time-to-errors are independent each other and generally distributed, we analyze the checkpointing model with instantaneous error detection. The conventional assumption that two or more errors do not take place between two consecutive checkpoints is removed. Given the checkpointing time, down-time, and recovery time, we derive the reliability of the checkpointing model. When the time-to-error follows an exponential distribution, we obtain the optimal checkpointing interval to achieve the maximum reliability.