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Tzu-Liang (Bill) Tseng
Department of Industrial, Manufacturing and Systems Engineering, The University of Texas at El Paso, El Paso, TX 79968, USA

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Editorial
Published: 15 March 2021 in Applied Soft Computing
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ACS Style

Ching-Ter Chang; Chun-Che Huang; Tzu-Liang (Bill) Tseng. Preface: Data-driven Decision Making - Theory, Methods, and Applications. Applied Soft Computing 2021, 102, 107261 .

AMA Style

Ching-Ter Chang, Chun-Che Huang, Tzu-Liang (Bill) Tseng. Preface: Data-driven Decision Making - Theory, Methods, and Applications. Applied Soft Computing. 2021; 102 ():107261.

Chicago/Turabian Style

Ching-Ter Chang; Chun-Che Huang; Tzu-Liang (Bill) Tseng. 2021. "Preface: Data-driven Decision Making - Theory, Methods, and Applications." Applied Soft Computing 102, no. : 107261.

Journal article
Published: 29 September 2020 in Sustainability
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More and more people are involved in sustainability-related activities through social network to support/protect their idea or motivation for sustainable development. Understanding the variety of issues of social pulsation is crucial in development of social sustainability. However, issues in social media generally change overtime. Issues not identified in advance may soon become popular topics discussed in society, particularly controversial issues. Previous studies have focused on the detection of hot topics and discussion of controversial issues, rather than the identification of potential controversial issues, which truly require paying attention to social sustainability. Furthermore, previous studies have focused on issue detection and tracking based on historical data. However, not all controversial issues are related to historical data to foster the cases. To avoid the above-mentioned research gap, Artificial Intelligence (AI) plays an essential role in issue detection in the early stage. In this study, an AI-based solution approach is proposed to resolve two practical problems in social media: (1) the impact caused by the number of fan pages from Facebook and (2) awareness of the levels for an issue. The proposed solution approach to detect potential issues is based on the popularity of public opinion in social media using a Web crawler to collect daily posts related to issues in social media under a big data environment. Some analytical findings are carried out via the congregational rules proposed in this research, and the solution approach detects the attentive subjects in the early stages. A comparison of the proposed method to the traditional methods are illustrated in the domain of green energy. The computational results demonstrate that the proposed approach is accurate and effective and therefore it provides significant contribution to upsurge green energy deployment.

ACS Style

Chun-Che Huang; Wen-Yau Liang; Shian-Hua Lin; Tzu-Liang (Bill) Tseng; Yu-Hsien Wang; Kuo-Hsin Wu. Detection of Potential Controversial Issues for Social Sustainability: Case of Green Energy. Sustainability 2020, 12, 8057 .

AMA Style

Chun-Che Huang, Wen-Yau Liang, Shian-Hua Lin, Tzu-Liang (Bill) Tseng, Yu-Hsien Wang, Kuo-Hsin Wu. Detection of Potential Controversial Issues for Social Sustainability: Case of Green Energy. Sustainability. 2020; 12 (19):8057.

Chicago/Turabian Style

Chun-Che Huang; Wen-Yau Liang; Shian-Hua Lin; Tzu-Liang (Bill) Tseng; Yu-Hsien Wang; Kuo-Hsin Wu. 2020. "Detection of Potential Controversial Issues for Social Sustainability: Case of Green Energy." Sustainability 12, no. 19: 8057.

Journal article
Published: 04 March 2019 in Rapid Prototyping Journal
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Purpose Shape memory polymer (SMP) is capable of recovering its original shape from a high degree of deformation by applying an external stimulus such as thermal energy. This research presents an integration of two commercial SMP materials (DiAPLEX and Tecoflex) and a material extrusion (ME) printer to fabricate SMP parts and specimens. The material properties such as Young’s modulus of the specimens was examined as a process output. Furthermore, stress-strain curve, strain recovery, instant shape-fixity ratio, long-term shape-fixity ratio and recovery ratio of SMP specimens during a thermo-mechanical cycle were investigated. Design/methodology/approach The ME fabrication settings for the SMP specimens were defined by implementing a design of experiments with temperature, velocity and layer height as process variables. Findings It was found, according to main effect and iteration plots, that fabrication parameters have an impact on Young’s modulus and exist minimum iteration among variables. In addition, Young’s modulus variation of DiAPLEX and Tecoflex specimens was mostly caused by velocity and layer height parameters, respectively. Moreover, results showed that SMP specimens were able to recover high levels of deformation. Originality/value This paper is a reference for process control and for rheological properties of SMP parts produced by ME fabrication process.

ACS Style

Carlos Alejandro Garcia Rosales; Hoejin Kim; Mario F. Garcia Duarte; Luis Chavez; Mariana Castañeda; Tzu-Liang Bill Tseng; Yirong Lin. Characterization of shape memory polymer parts fabricated using material extrusion 3D printing technique. Rapid Prototyping Journal 2019, 25, 322 -331.

AMA Style

Carlos Alejandro Garcia Rosales, Hoejin Kim, Mario F. Garcia Duarte, Luis Chavez, Mariana Castañeda, Tzu-Liang Bill Tseng, Yirong Lin. Characterization of shape memory polymer parts fabricated using material extrusion 3D printing technique. Rapid Prototyping Journal. 2019; 25 (2):322-331.

Chicago/Turabian Style

Carlos Alejandro Garcia Rosales; Hoejin Kim; Mario F. Garcia Duarte; Luis Chavez; Mariana Castañeda; Tzu-Liang Bill Tseng; Yirong Lin. 2019. "Characterization of shape memory polymer parts fabricated using material extrusion 3D printing technique." Rapid Prototyping Journal 25, no. 2: 322-331.

Journal article
Published: 07 January 2019 in Rapid Prototyping Journal
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Purpose Shape memory polymers (SMPs) are classified as smart materials owing to their inherent stimulus-induced response. SMPs are capable of recovering partially or totally to its original shape after a high degree of deformation by external stimulus. The most used stimuli are thermal, light, magnetic field and electricity. This research aims to characterize the toughness property of thermo-responsive SMP specimens fabricated by the material extrusion (ME) process and to investigate the impact of ME parameters on specimen maximum load and load-displacement curves. Moreover, to investigate the recovery efficiency based on the initial and post toughness generated by the compact tension test. Design/methodology/approach A design of experiments with three parameters (temperature, velocity and layer height) defined the ME settings to fabricate the specimens. The ME raster orientation factor was also evaluated separately. In addition, one more specimen group assisted by a clamp during the recovery process was compared with a specimen control group. After fabrication, specimens were submitted to a thermo-mechanical cycle that encompasses a compact tension test and a thermo-recovery process. Comparison studies of load-displacement, toughness and recovery efficiency of the specimens were carried out to determine the optimized fabrication parameters. Findings It was found that ME parameters and raster orientation impacted the test results. Samples with the clamp support during recovery returned a higher toughness than samples without support. Finally, results showed that the shape memory effect can contribute with up to 43 per cent recovery efficiency in a first recovery and up to 23 per cent in a second recovery of damaged specimens. Originality/value This paper is a reference for toughness and recovery properties of SMP parts produced by the ME fabrication process.

ACS Style

Carlos Alejandro Garcia Rosales; Hoejin Kim; Mario F. Garcia Duarte; Luis Chavez; Tzu-Liang Bill Tseng; Yirong Lin. Toughness-based recovery efficiency of shape memory parts fabricated using material extrusion 3D printing technique. Rapid Prototyping Journal 2019, 25, 30 -37.

AMA Style

Carlos Alejandro Garcia Rosales, Hoejin Kim, Mario F. Garcia Duarte, Luis Chavez, Tzu-Liang Bill Tseng, Yirong Lin. Toughness-based recovery efficiency of shape memory parts fabricated using material extrusion 3D printing technique. Rapid Prototyping Journal. 2019; 25 (1):30-37.

Chicago/Turabian Style

Carlos Alejandro Garcia Rosales; Hoejin Kim; Mario F. Garcia Duarte; Luis Chavez; Tzu-Liang Bill Tseng; Yirong Lin. 2019. "Toughness-based recovery efficiency of shape memory parts fabricated using material extrusion 3D printing technique." Rapid Prototyping Journal 25, no. 1: 30-37.

Journal article
Published: 06 June 2018 in Ultrasonics
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The operating principle of the piezoelectric traveling wave rotary ultrasonic motor is based on two energy conversion processes: the generation of the stator traveling wave and the rectification of the stator movement through the stator-rotor contact mechanism. This paper presents a methodology to model in detail the stator-rotor contact interface of these motors. A contact algorithm that couples a model of the stator which is discretized with the finite volume method and an analytical model of the rotor is presented. The outputs of the proposed model are the normal and tangential force distribution produced at the stator-rotor contact interface, contact length, height and shape of the stator traveling wave and rotor speed. The torque-speed characteristic of the USR60 is calculated with the proposed model, and the results of the model are compared versus the real torque-speed of the motor. A good agreement between the proposed model results and the torque-speed characteristic of the USR60 was observed.

ACS Style

I.A. Renteria-Marquez; B. T. L. Tseng. A novel contact model of piezoelectric traveling wave rotary ultrasonic motors with the finite volume method. Ultrasonics 2018, 90, 5 -17.

AMA Style

I.A. Renteria-Marquez, B. T. L. Tseng. A novel contact model of piezoelectric traveling wave rotary ultrasonic motors with the finite volume method. Ultrasonics. 2018; 90 ():5-17.

Chicago/Turabian Style

I.A. Renteria-Marquez; B. T. L. Tseng. 2018. "A novel contact model of piezoelectric traveling wave rotary ultrasonic motors with the finite volume method." Ultrasonics 90, no. : 5-17.

Journal article
Published: 13 July 2017 in Smart Materials and Structures
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This paper presents a novel process to fabricate piezoelectric films from polyvinylidene fluoride (PVDF) polymer using integrated fused deposition modeling (FDM) 3D printing and corona poling technique. Corona poling is one of many effective poling processes that has received attention to activate PVDF as a piezoelectric responsive material. The corona poling process occurs when a PVDF polymer is exposed to a high electric field created and controlled through an electrically charged needle and a grid electrode under heating environment. FDM 3D printing has seen extensive progress in fabricating thermoplastic materials and structures, including PVDF. However, post processing techniques such as poling is needed to align the dipoles in order to gain piezoelectric properties. To further simplify the piezoelectric sensors and structures fabrication process, this paper proposes an integrated 3D printing process with corona poling to fabricate piezoelectric PVDF sensors without post poling process. This proposed process, named 'Integrated 3D Printing and Corona poling process' (IPC), uses the 3D printer's nozzle and heating bed as anode and cathode, respectively, to create poling electric fields in a controlled heating environment. The nozzle travels along the programmed path with fixed distance between nozzle tip and sample's top surface. Simultaneously, the electric field between the nozzle and bottom heating pad promotes the alignment of dipole moment of PVDF molecular chains. The crystalline phase transformation and output current generated by printed samples under different electric fields in this process were characterized by a Fourier transform infrared spectroscopy and through fatigue load frame. It is demonstrated that piezoelectric PVDF films with enhanced β-phase percentage can be fabricated using the IPC process. In addition, mechanical properties of printed PVDF was investigated by tensile testing. It is expected to expand the use of additive manufacturing to fabricate piezoelectric PVDF-based devices for applications such as sensing and energy harvesting.

ACS Style

Hoejin Kim; Fernando Torres; Yanyu Wu; Dino Villagran; Yirong Lin; Tzu-Liang(Bill) Tseng. Integrated 3D printing and corona poling process of PVDF piezoelectric films for pressure sensor application. Smart Materials and Structures 2017, 26, 085027 .

AMA Style

Hoejin Kim, Fernando Torres, Yanyu Wu, Dino Villagran, Yirong Lin, Tzu-Liang(Bill) Tseng. Integrated 3D printing and corona poling process of PVDF piezoelectric films for pressure sensor application. Smart Materials and Structures. 2017; 26 (8):085027.

Chicago/Turabian Style

Hoejin Kim; Fernando Torres; Yanyu Wu; Dino Villagran; Yirong Lin; Tzu-Liang(Bill) Tseng. 2017. "Integrated 3D printing and corona poling process of PVDF piezoelectric films for pressure sensor application." Smart Materials and Structures 26, no. 8: 085027.

Research article
Published: 24 April 2017 in Journal of Composite Materials
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This paper presents a fabrication process to enhance homogeneous dispersion of BaTiO3 nanoparticles in polyvinylidene fluoride matrix nanocomposites using fused deposition modeling (FDM) 3D printing technique. The nanocomposites integrate the functional property (piezoelectric, pyroelectric, and dielectric) of BaTiO3 with the flexibility and lightweight of polyvinylidene fluoride. Traditionally, the simple yet effective way to fabricate the nanocomposites includes solvent-casting, spin-coating, and hot-embossing. However, these methods have disadvantages such as heterogeneous dispersion of BaTiO3 nanoparticles in polyvinylidene fluoride matrix due to the higher density of BaTiO3 compared with polyvinylidene fluoride and agglomeration during fabrication process. This heterogeneous dispersion could weaken functional and mechanical properties. Herein, fused deposition modeling 3D printing technique was utilized for homogeneous dispersion to alleviate the agglomeration of BaTiO3 in polyvinylidene fluoride through two processes: filament extrusion and 3D printing. In addition, thermal poling was applied to further enhance piezoelectric response of the BaTiO3/polyvinylidene fluoride nanocomposites. It is found that 3D printed BaTiO3/polyvinylidene fluoride nanocomposites exhibit three times higher piezoelectric response than solvent-casted nanocomposites.

ACS Style

Hoejin Kim; Torres Fernando; Mingyue Li; Yirong Lin; Tzu-Liang Bill Tseng. Fabrication and characterization of 3D printed BaTiO3/PVDF nanocomposites. Journal of Composite Materials 2017, 52, 197 -206.

AMA Style

Hoejin Kim, Torres Fernando, Mingyue Li, Yirong Lin, Tzu-Liang Bill Tseng. Fabrication and characterization of 3D printed BaTiO3/PVDF nanocomposites. Journal of Composite Materials. 2017; 52 (2):197-206.

Chicago/Turabian Style

Hoejin Kim; Torres Fernando; Mingyue Li; Yirong Lin; Tzu-Liang Bill Tseng. 2017. "Fabrication and characterization of 3D printed BaTiO3/PVDF nanocomposites." Journal of Composite Materials 52, no. 2: 197-206.

Journal article
Published: 10 November 2016 in International Journal of Computational Intelligence Systems
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Chun-Che Huang; Tzu-Liang (Bill) Tseng; Kun-Cheng Chen. Novel Approach to Tourism Analysis with Multiple Outcome Capability Using Rough Set Theory. International Journal of Computational Intelligence Systems 2016, 9, 1118 -1132.

AMA Style

Chun-Che Huang, Tzu-Liang (Bill) Tseng, Kun-Cheng Chen. Novel Approach to Tourism Analysis with Multiple Outcome Capability Using Rough Set Theory. International Journal of Computational Intelligence Systems. 2016; 9 (6):1118-1132.

Chicago/Turabian Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Kun-Cheng Chen. 2016. "Novel Approach to Tourism Analysis with Multiple Outcome Capability Using Rough Set Theory." International Journal of Computational Intelligence Systems 9, no. 6: 1118-1132.

Journal article
Published: 01 April 2016 in Computer Methods and Programs in Biomedicine
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This paper presents a new heuristic algorithm for reduct selection based on credible index in the rough set theory (RST) applications. This algorithm is efficient and effective in selecting the decision rules particularly the problem to be solved in a large scale. This algorithm is capable to derive the rules with multi-outcomes and identify the most significant features simultaneously, which is unique and useful in solving predictive medical problems. The end results of the proposed approach are a set of decision rules that illustrates the causes for solitary pulmonary nodule and results of the long term treatment.

ACS Style

Tzu-Liang (Bill) Tseng; Chun-Che Huang; Kym Fraser; Hsien-Wei Ting. Rough set based rule induction in decision making using credible classification and preference from medical application perspective. Computer Methods and Programs in Biomedicine 2016, 127, 273 -289.

AMA Style

Tzu-Liang (Bill) Tseng, Chun-Che Huang, Kym Fraser, Hsien-Wei Ting. Rough set based rule induction in decision making using credible classification and preference from medical application perspective. Computer Methods and Programs in Biomedicine. 2016; 127 ():273-289.

Chicago/Turabian Style

Tzu-Liang (Bill) Tseng; Chun-Che Huang; Kym Fraser; Hsien-Wei Ting. 2016. "Rough set based rule induction in decision making using credible classification and preference from medical application perspective." Computer Methods and Programs in Biomedicine 127, no. : 273-289.

Journal article
Published: 01 January 2016 in Computers & Industrial Engineering
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In service industry application, there is vague and qualitative information required to be processed properly, for example, to identify customer preferences in order to provide adequate services. From literature, Rough Set Theory (RST) has been indicated to be one of promising approaches to cope with vagueness in a large scale database. Basically, the rough set approach integrates learning-from-example techniques, extracts rules from a data set of interest, and discovers data regularities. Most of the existing RS based approaches are able to implement rule induction but it is very time consuming from computation perspective particularly from a large database. To date, there is a demand to generate and analyze business decision rules based on dynamical data sets and conclude such rules on the daily basis in the service industry. Therefore, in this study, an Incremental Weight Incorporated Rule Identification (IWIRI) algorithm is proposed to fulfill such demand. The proposed approach is proficient to efficiently process in-coming data (objetcs) and generate updated decision rules without re-computation efforts in the database. Identification of features based on the customer’s preference and implementation of the proposed algorithm are summarized in the case study. This paper forms the basis for solving many other similar problems that occur in service industries.

ACS Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Chia-Ying Tang. Feature extraction using rough set theory in service sector application from incremental perspective. Computers & Industrial Engineering 2016, 91, 30 -41.

AMA Style

Chun-Che Huang, Tzu-Liang (Bill) Tseng, Chia-Ying Tang. Feature extraction using rough set theory in service sector application from incremental perspective. Computers & Industrial Engineering. 2016; 91 ():30-41.

Chicago/Turabian Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Chia-Ying Tang. 2016. "Feature extraction using rough set theory in service sector application from incremental perspective." Computers & Industrial Engineering 91, no. : 30-41.

Journal article
Published: 05 March 2015 in Journal of Computational Design and Engineering
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In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions. Highlights A new methodology in predicting a CNC machining output has been investigated. A data mining technique and a hybrid type II fuzzy system are applied. Two different types of membership functions were created to generate a hybrid system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The results showed that the hybrid system generated a far better accuracy.

ACS Style

Tzu-Liang (Bill) Tseng; Fuhua Jiang; Yongjin (James) Kwon. Hybrid Type II fuzzy system & data mining approach for surface finish. Journal of Computational Design and Engineering 2015, 2, 137 -147.

AMA Style

Tzu-Liang (Bill) Tseng, Fuhua Jiang, Yongjin (James) Kwon. Hybrid Type II fuzzy system & data mining approach for surface finish. Journal of Computational Design and Engineering. 2015; 2 (3):137-147.

Chicago/Turabian Style

Tzu-Liang (Bill) Tseng; Fuhua Jiang; Yongjin (James) Kwon. 2015. "Hybrid Type II fuzzy system & data mining approach for surface finish." Journal of Computational Design and Engineering 2, no. 3: 137-147.

Book chapter
Published: 01 January 2015 in Encyclopedia of Information Science and Technology, Third Edition
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ACS Style

Tzu-Liang (Bill) Tseng; Chun-Che Huang; Yu-Neng Fan; Chia-Hsun Lee; Tzu- Liang. Quality Control Using Agent Based Framework. Encyclopedia of Information Science and Technology, Third Edition 2015, 5211 -5223.

AMA Style

Tzu-Liang (Bill) Tseng, Chun-Che Huang, Yu-Neng Fan, Chia-Hsun Lee, Tzu- Liang. Quality Control Using Agent Based Framework. Encyclopedia of Information Science and Technology, Third Edition. 2015; ():5211-5223.

Chicago/Turabian Style

Tzu-Liang (Bill) Tseng; Chun-Che Huang; Yu-Neng Fan; Chia-Hsun Lee; Tzu- Liang. 2015. "Quality Control Using Agent Based Framework." Encyclopedia of Information Science and Technology, Third Edition , no. : 5211-5223.

Book chapter
Published: 01 January 2015 in Advances in Intelligent Systems and Computing
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Providing sustainable service and energy has been becoming a trend due to environmental concerns. One of the academic challenges in sustainable service and energy is identified: In the complex service sector, those data (e.g., from questionnaires) may be complicated, qualitative and in large scale. Numerous attributes which are non-regular in nature and have the impact on service performance are involved. One of the promised solution approaches is the Rough Set (RS) based approach that can deal with qualitative information and provide an individual object model based approach. However, traditional RS approaches have a few disadvantages: (i) The decision attribute in one level only that can reflects the concept hierarchy, (ii) using two stages to generate reducts and induct decision rules. This paper, an extended RS based rule induction approach is proposed while decision tables are not in traditional format. This study contributes development of the solution models to sustainable service and energy.

ACS Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Yu-Sheng Liu; Jun-Wei Chu; Po-An Chen. Agile Rough Set Based Rule Induction to Sustainable Service and Energy Provision. Advances in Intelligent Systems and Computing 2015, 330, 761 -764.

AMA Style

Chun-Che Huang, Tzu-Liang (Bill) Tseng, Yu-Sheng Liu, Jun-Wei Chu, Po-An Chen. Agile Rough Set Based Rule Induction to Sustainable Service and Energy Provision. Advances in Intelligent Systems and Computing. 2015; 330 ():761-764.

Chicago/Turabian Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Yu-Sheng Liu; Jun-Wei Chu; Po-An Chen. 2015. "Agile Rough Set Based Rule Induction to Sustainable Service and Energy Provision." Advances in Intelligent Systems and Computing 330, no. : 761-764.

Journal article
Published: 01 January 2014 in Journal of Biomedical Science
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Tissue and organ regeneration via transplantation of cell bodies in-situ has become an interesting strategy in regenerative medicine. Developments of cell carriers to systematically deliver cell bodies in the damage site have fall shorten on effectively meet this purpose due to inappropriate release control. Thus, there is still need of novel substrate to achieve targeted cell delivery with appropriate vehicles. In the present study, silicon based photovoltaic (PV) devices are used as a cell culturing substrate for the expansion of myoblast mouse cell (C2C12 cells) that offers an atmosphere for regular cell growth in vitro. The adherence, viability and proliferation of the cells on the silicon surface were examined by direct cell counting and fluorescence microscopy.

ACS Style

Mohammod K Bhuyan; Jorge I Rodriguez-Devora; Kym Fraser; Tzu-Liang Bill Tseng. Silicon substrate as a novel cell culture device for myoblast cells. Journal of Biomedical Science 2014, 21, 47 -47.

AMA Style

Mohammod K Bhuyan, Jorge I Rodriguez-Devora, Kym Fraser, Tzu-Liang Bill Tseng. Silicon substrate as a novel cell culture device for myoblast cells. Journal of Biomedical Science. 2014; 21 (1):47-47.

Chicago/Turabian Style

Mohammod K Bhuyan; Jorge I Rodriguez-Devora; Kym Fraser; Tzu-Liang Bill Tseng. 2014. "Silicon substrate as a novel cell culture device for myoblast cells." Journal of Biomedical Science 21, no. 1: 47-47.

Journal article
Published: 12 April 2013 in Annals of Operations Research
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Rough set theory is a new data mining approach to manage vagueness. It is capable to discover important facts hidden in the data. Literature indicate the current rough set based approaches can’t guarantee that classification of a decision table is credible and it is not able to generate robust decision rules when new attributes are incrementally added in. In this study, an incremental attribute oriented rule-extraction algorithm is proposed to solve this deficiency commonly observed in the literature related to decision rule induction. The proposed approach considers incremental attributes based on the alternative rule extraction algorithm (AREA), which was presented for discovering preference-based rules according to the reducts with the maximum of strength index (SI), specifically the case that the desired reducts are not necessarily unique since several reducts could include the same value of SI. Using the AREA, an alternative rule can be defined as the rule which holds identical preference to the original decision rule and may be more attractive to a decision-maker than the original one. Through implementing the proposed approach, it can be effectively operating with new attributes to be added in the database/information systems. It is not required to re-compute the updated data set similar to the first step at the initial stage. The proposed algorithm also excludes these repetitive rules during the solution search stage since most of the rule induction approaches generate the repetitive rules. The proposed approach is capable to efficiently and effectively generate the complete, robust and non-repetitive decision rules. The rules derived from the data set provide an indication of how to effectively study this problem in further investigations.

ACS Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Fuhua Jiang; Yu-Neng Fan; Chih-Hua Hsu. Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes. Annals of Operations Research 2013, 216, 163 -189.

AMA Style

Chun-Che Huang, Tzu-Liang (Bill) Tseng, Fuhua Jiang, Yu-Neng Fan, Chih-Hua Hsu. Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes. Annals of Operations Research. 2013; 216 (1):163-189.

Chicago/Turabian Style

Chun-Che Huang; Tzu-Liang (Bill) Tseng; Fuhua Jiang; Yu-Neng Fan; Chih-Hua Hsu. 2013. "Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes." Annals of Operations Research 216, no. 1: 163-189.

Chapter
Published: 24 May 2011 in Encyclopedia of Data Warehousing and Mining, Second Edition
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The Information Technology and Internet techniques are rapidly developing. Interaction between enterprises and customers has dramatically changed. It becomes critical that enterprises are able to perform rapid diagnosis and quickly respond to market change. How to apply business intelligence (BI), manage, and diffuse discovered knowledge efficiently and effectively has attracted much attention (Turban et al., 2007). In this chapter, an “analytical knowledge warehousing” approach is proposed to apply business intelligence, and solve the knowledge management and diffusion issues for decision-making. Analytical knowledge is referred to a set of discovered knowledge, i.e., core of BI, which is extricated from databases, knowledge bases, and other data storage systems through aggregating data analysis techniques and domain experts from business perspective. The solution approach includes conceptual framework of analytical knowledge, analytical knowledge externalization, design and implementation of analytical knowledge warehouse. The methodology has integrated with multi-dimensional analytical techniques to efficiently search analytical knowledge documents. The techniques include static and dynamic domains and solve problems from the technical and management standpoints. The use of analytical knowledge warehouse and multidimensional analysis techniques shows the promising future to apply BI and support decision-making in business.

ACS Style

Chun-Che Huang; Tzu-Liang ("bill") Tseng. Analytical Knowledge Warehousing for Business Intelligence. Encyclopedia of Data Warehousing and Mining, Second Edition 2011, 31 -38.

AMA Style

Chun-Che Huang, Tzu-Liang ("bill") Tseng. Analytical Knowledge Warehousing for Business Intelligence. Encyclopedia of Data Warehousing and Mining, Second Edition. 2011; ():31-38.

Chicago/Turabian Style

Chun-Che Huang; Tzu-Liang ("bill") Tseng. 2011. "Analytical Knowledge Warehousing for Business Intelligence." Encyclopedia of Data Warehousing and Mining, Second Edition , no. : 31-38.

Journal article
Published: 31 January 2011 in Expert Systems with Applications
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Distributor’s selection is an important issue in Supply chain management, particularly in the current competitive environment. The current research works provide only conceptual, descriptive, and simulation results, focusing mainly on firm resources and general marketing factors. The selection and evaluation of distributors generally incorporate qualitative information; however, analyzing qualitative information is difficult by standard statistical techniques. Consequently, a more suitable approach is desired. In this paper, a method based on Rough set theory, which has been recognized as a powerful tool in dealing with qualitative data in the literature, is introduced and modified for preferred distributor selection. We derived certain decision rules which are able to facilitate distributor selection and identified several significant features based on an empirical study conducted in China.

ACS Style

Zhonghai Zou; Tzu-Liang (Bill) Tseng; Hansuk Sohn; Guofang Song; Rafael Gutierrez. A rough set based approach to distributor selection in supply chain management. Expert Systems with Applications 2011, 38, 106 -115.

AMA Style

Zhonghai Zou, Tzu-Liang (Bill) Tseng, Hansuk Sohn, Guofang Song, Rafael Gutierrez. A rough set based approach to distributor selection in supply chain management. Expert Systems with Applications. 2011; 38 (1):106-115.

Chicago/Turabian Style

Zhonghai Zou; Tzu-Liang (Bill) Tseng; Hansuk Sohn; Guofang Song; Rafael Gutierrez. 2011. "A rough set based approach to distributor selection in supply chain management." Expert Systems with Applications 38, no. 1: 106-115.

Chapter
Published: 18 January 2011 in Encyclopedia of Data Warehousing and Mining, Second Edition
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ACS Style

Chun-Che Huang; Tzu-Liang ("bill") Tseng. Analytical Knowledge Warehousing for Business Intelligence. Encyclopedia of Data Warehousing and Mining, Second Edition 2011, 31 -38.

AMA Style

Chun-Che Huang, Tzu-Liang ("bill") Tseng. Analytical Knowledge Warehousing for Business Intelligence. Encyclopedia of Data Warehousing and Mining, Second Edition. 2011; ():31-38.

Chicago/Turabian Style

Chun-Che Huang; Tzu-Liang ("bill") Tseng. 2011. "Analytical Knowledge Warehousing for Business Intelligence." Encyclopedia of Data Warehousing and Mining, Second Edition , no. : 31-38.

Journal article
Published: 31 December 2010 in Expert Systems with Applications
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This paper presents a new hybrid algorithm for a classical capacitated plant location problem. Benders’ decomposition algorithm has been successfully applied in many areas. A major difficulty with this decomposition lies in the solution of master problem, which is a “hard” problem, costly to compute. Our proposed algorithm, instead of using a costly branch-and-bound method, incorporates a genetic algorithm to obtain “good” suboptimal solutions to the master problem at a tremendous saving in the computational effort. The performance of the proposed algorithm is tested on randomly generated data and also well-known existing data. The computational results indicate that the proposed algorithm is effective and efficient for the capacitated plant location problem and competitive with the Benders’ decomposition algorithm.

ACS Style

Ming-Che Lai; Han-Suk Sohn; Tzu-Liang (Bill) Tseng; Chunkuan Chiang. A hybrid algorithm for capacitated plant location problem. Expert Systems with Applications 2010, 37, 8599 -8605.

AMA Style

Ming-Che Lai, Han-Suk Sohn, Tzu-Liang (Bill) Tseng, Chunkuan Chiang. A hybrid algorithm for capacitated plant location problem. Expert Systems with Applications. 2010; 37 (12):8599-8605.

Chicago/Turabian Style

Ming-Che Lai; Han-Suk Sohn; Tzu-Liang (Bill) Tseng; Chunkuan Chiang. 2010. "A hybrid algorithm for capacitated plant location problem." Expert Systems with Applications 37, no. 12: 8599-8605.

Journal article
Published: 07 October 2010 in Expert Systems with Applications
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In this paper, application of the rough set theory (RST) to feature selection in customer relationship management (CRM) is introduced. Compared to other methods, the RST approach has the advantage of combining both qualitative and quantitative information in the decision analysis, which is extremely important for CRM. Automated decision support for CRM has been proposed in recent years. However, little work has been devoted to the development of computer-based systems to support CRM in rule induction. This paper presents a novel rough set based algorithm for automated decision support for CRM. Particularly, the approach is capable to handle real numbers instead of integer numbers through introduction of converted numbers involving tolerances. Being unique and useful in solving CRM problems, an alternative rule extraction algorithm (AREA) is presented for discovering preference-based rules according to the reducts which contain the maximum of strength index (SI) in the same case, where the data with tolerance. The empirical data set associated with CRM has proven the validity and reliability of these approaches. This research thus contributes to developing and validating a useful approach to automated decision support for CRM. This paper forms the basis for solving many other similar problems that occur in the service industry.

ACS Style

Tzu-Liang (Bill) Tseng; Chun-Che Huang; Yu-Neng Fan. Autonomous rule induction from data with tolerances in customer relationship management. Expert Systems with Applications 2010, 38, 4889 -4900.

AMA Style

Tzu-Liang (Bill) Tseng, Chun-Che Huang, Yu-Neng Fan. Autonomous rule induction from data with tolerances in customer relationship management. Expert Systems with Applications. 2010; 38 (5):4889-4900.

Chicago/Turabian Style

Tzu-Liang (Bill) Tseng; Chun-Che Huang; Yu-Neng Fan. 2010. "Autonomous rule induction from data with tolerances in customer relationship management." Expert Systems with Applications 38, no. 5: 4889-4900.