A Genetic Algorithm for Directed Graph-based Supply Network Planning in Memory Module Industry

Li-Chih Wang,Chen-Yang Cheng,Li-Pin Huang 대한산업공학회 2010 Industrial Engineeering & Management Systems Vol.9 No.3

A memory module industry"s supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network"s structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.

A Genetic Algorithm for Directed Graph-based Supply Network Planning in Memory Module Industry

Wang, Li-Chih,Cheng, Chen-Yang,Huang, Li-Pin Korean Institute of Industrial Engineers 2010 Industrial Engineeering & Management Systems Vol.9 No.3

A memory module industry's supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network's structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.

Flow and Learning Emotions in Computer Education

Chih-Chien Wang,Kai-Li Wang,Chien-Chang Chen,Yann-Jy Yang 한국데이타베이스학회 2014 Journal of information technology applications & m Vol.21 No.3

It is important to keep learners’ feeling positive during learning to enhance learning performance. According to flow theory,challenge-skill balance is a precondition for flow experience: Learnersfeel anxietywhen the challenge of learning is higher than their ability, feel boredom when the challenge of learning is lower than learners’ ability, and engage in flow status when the challenge of learning matches the learners’ ability. However, the current empirical study reveals that emotions related to enjoyment may appear when the learners’ skill is equal to or higher than the learning challenge. Nevertheless, boredom emotion may appear when learners perceive the courses are difficult but unimportant. These empirical survey results revealed the necessary of rethinking the appearance of boredom and enjoyment emotions in computer education.

Flow and Learning Emotions in Computer Education: An Empirical Survey

Wang, Chih-Chien,Wang, Kai-Li,Chen, Chien-Chang,Yang, Yann-Jy Korea Data Strategy Society 2014 Journal of information technology applications & m Vol.21 No.3

It is important to keep learners' feeling positive during learning to enhance learning performance. According to flow theory,challenge-skill balance is a precondition for flow experience: Learners feel anxiety when the challenge of learning is higher than their ability, feel boredom when the challenge of learning is lower than learners' ability, and engage in flow status when the challenge of learning matches the learners' ability. However, the current empirical study reveals that emotions related to enjoyment may appear when the learners' skill is equal to or higher than the learning challenge. Nevertheless, boredom emotion may appear when learners perceive the courses are difficult but unimportant. These empirical survey results revealed the necessary of rethinking the appearance of boredom and enjoyment emotions in computer education.

Feline mammary carcinoma-derived extracellular vesicle promotes liver metastasis via sphingosine kinase-1-mediated premetastatic niche formation

Yi-Chih Chang,Hao-Ping Liu,Hsiao-Li Chuang,Jiunn-Wang Liao,Pei-Ling Kao,Hsun-Lung Chan,Ter-Hsin Chen,Yu-Chih Wang 한국실험동물학회 2023 Laboratory Animal Research Vol.39 No.4

Background: Feline mammary carcinoma (FMC) is one of the most prevalent malignancies of female cats. FMC is highly metastatic and thus leads to poor disease outcomes. Among all metastases, liver metastasis occurs in about 25% of FMC patients. However, the mechanism underlying hepatic metastasis of FMC remains largely uncharacterized. Results: Herein, we demonstrate that FMC-derived extracellular vesicles (FMC-EVs) promotes the liver metastasis of FMC by activating hepatic stellate cells (HSCs) to prime a hepatic premetastatic niche (PMN). Moreover, we provide evidence that sphingosine kinase 1 (SK1) delivered by FMC-EV was pivotal for the activation of HSC and the formation of hepatic PMN. Depletion of SK1 impaired cargo sorting in FMC-EV and the EV-potentiated HSC activation, and abolished hepatic colonization of FMC cells. Conclusions: Taken together, our findings uncover a previously uncharacterized mechanism underlying liver-metastasis of FMC and provide new insights into prognosis and treatment of this feline malignancy.

Building Information Model and Optimization Algorithms for Supporting Campus Facility Maintenance Management: A Case Study of Maintaining Water Dispensers

Li-Hsi Yang,Liuya Xu,Wei-Chih Wang,Shih-Hsu Wang 대한토목학회 2021 KSCE Journal of Civil Engineering Vol.25 No.1

Effective management for the maintenance of water dispensers dispersed throughout an academic campus is essential for ensuring the quality of drinking water. Conventionally, water dispenser maintenance is conducted approximately bimonthly or when a passive fault notice is obtained. This maintenance frequency usually results in ineffective allocation of maintenance staff and poor maintenance quality. This study proposes a new model for campus facility maintenance management that enables maintenance staff to maintain water dispensers at the optimal time and select the shortest maintenance path. The proposed model was developed using the maintenance information of the Construction Operations Building Information Exchange obtained from building information models of multiple buildings, water dispenser operation data from a water dispenser monitoring module, and an optimization algorithm developed by integrating Dijkstra’s algorithm, simulated annealing, and a genetic algorithm to identify the shortest maintenance path. The proposed model was tested on a campus in Northern Taiwan. The application results revealed that maintenance strategies could be systematically established to determine the optimal time to dispatch maintenance staff based on the lowest unit cost criterion; this approach was also used to identify the shortest maintenance path through multiple buildings.

Programming by Demonstration in Augmented Reality for the Motion Planning of a Three-Axis CNC Dispenser

Chih-Hsing Chu,Yu-Wang Liu,Pai-Chia Li,Liao-Chuan Huang,Yuan-Ping Luh 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.7 No.5

This study presents a programming by demonstration (PbD) interface in augmented reality for motion planning in a three-axis CNC glue dispenser. The interface assists a human planner to effectively determine dispenser motion in a planning task. An augmented reality application prompts the planner with instructive information in a video of real environment while guiding the machine in 3D space to dispense glue on a work part. The purpose involves facilitating the generation of the dispenser’s motion commands by enhancing individual spatial reasoning between the dispenser’s tip and the work part. CAD models are not required prior to the planning task, thus eliminating the use of motion planning software. Test results demonstrate the effectiveness of the proposed interface with respect to accelerating the process of the dispenser PbD. The study shows the practical value of augmented reality as a cost-effective interfacing technology for human–machine collaborations in smart manufacturing.

Hydroxydibenzoylmethane induces apoptosis through repressing ornithine decarboxylase in human promyelocytic leukemia HL-60 cells

Wang, Ming-Fu,Liao, Ya-Fan,Hung, Ying-Cheng,Lin, Chih-Li,Hour, Tzyh-Chyuan,Lue, Ko-Huang,Hung, Hui-Chih,Liu, Guang-Yaw Korean Society for Biochemistry and Molecular Bion 2011 Experimental and molecular medicine Vol.43 No.4

Ornithine decarboxylase (ODC) is the rate-limiting enzyme in polyamine biosynthesis and a target for chemoprevention. Hydroxydibenzoylmethane (HDB), a derivative of dibenzoylmethane of licorice, is a promising chemopreventive agent. In this paper, we investigated whether HDB would inhibit the ODC pathway to enhance apoptosis in human promyelocytic leukemia HL-60 cells. We found ODC enzyme activity was reduced during HDB treatment. Overexpression of ODC in HL-60 parental cells could reduce HDB-induced apoptosis, which leads to loss of mitochondrial membrane potential (${\Delta}{\psi}_m$), through lessening intracellular ROS. Furthermore, ODC overexpression protected cytochrome c release and the activation of caspase-3 following HDB treatment. The results demonstrated HDB-induced apoptosis was through a mechanism of down-regulation of ODC and occurred along a ROS-dependent mitochondria-mediated pathway.

The role of the genomic mutation signature and tumor mutation burden on relapse risk prediction in head and neck squamous cell carcinoma after concurrent chemoradiotherapy

Wang Hui-Ching,Moi Sin-Hua,Chan Leong-Perng,Wu Chun-Chieh,Du Jeng-Shiun,Liu Pei-Lin,Chou Meng-Chun,Wu Che-Wei,Huang Chih-Jen,Hsiao Hui-Hua,Pan Mei-Ren,Chen Li-Tzong 생화학분자생물학회 2023 Experimental and molecular medicine Vol.55 No.-

Personalized genetic profiling has focused on improving treatment efficacy and predicting risk stratification by identifying mutated genes and selecting targeted agents according to genetic testing. Therefore, we evaluated the role of genetic profiling and tumor mutation burden (TMB) using next-generation sequencing in patients with head and neck squamous cell carcinoma (HNSC). The relapse mutation signature (RMS) and chromatin remodeling mutation signature (CRMS) were explored to predict the risk of relapse in patients with HNSC treated with concurrent chemoradiotherapy (CCRT) with platinum-based chemotherapy. Patients in the high RMS and CRMS groups showed significantly shorter relapse-free survival than those in the low RMS and CRMS groups, respectively (p < 0.001 and p = 0.006). Multivariate Cox regression analysis showed that extranodal extension, CCRT response, and three somatic mutation profiles (TMB, RMS, and CRMS) were independent risk predictors for HNSC relapse. The predictive nomogram showed satisfactory performance in predicting relapse-free survival in patients with HNSC treated with CCRT.

An Experimental Study to Improve Due-date Performance

Wang, Mei-Ting,Li, Rong-Kwei,Chen, Ching-Piao,Chen, Hsien-Ching,Tsai, Chih-Hung The Korean Society for Quality Management 2009 The Asian Journal on Quality Vol.10 No.3

Due-date performance (DDP) is a very important performance indicator for the companies. Thus, companies with a high hit rate would have greater competitive advantage; on the contrary, companies that delay customers' orders frequently would lose sales opportunities and reputations. Therefore, there were many academic studies and practical efforts to improve DDP in the past, but the problem of low hit rate still exists. In order to increase the hit rate, some companies have focused on reducing the variation, while others focus on production management, but is the real problem affecting the low rate variability or production management? This is indeed difficult to be validated through practice. Therefore, this study designed three scenarios, tested each scenario for 30 times, each test involved seven subjects. The tests were to provide counter-evidence in the Job Shop environment without variation. If the variation is the main factor of affecting hit rate, the rate at this time should be good; otherwise, the assumption that variation is the main cause is rebutted. The results demonstrated that production management planning is the main cause, and the method of enhancing the hit rate is obtained during the test.