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期刊論文
1. Tao-Ming Cheng, Hsing-Yu Hou, Sung-Chi Hsu, Dinesh Chandra Agrawal, Rung-Ching Chen, and Mei-Ling Liu, "Improving Students Learning Performance from Learning Engagement and Institutional Resources Planning," Advanced Science Letters (Scopus), 24 (11), 8011–8015, Nov, 2018.
2. Cheng, T.-M., Hou, H.-Y., Agrawal, D. C., and Hsu, S.-C., "The influence of freshmen’s psychological characteristics on learning performance and retention," Journal of Institutional Research South East Asia (Scopus), 16(1), 126-151, Jun, 2018.
Wellness in the workplace has been given importance nowadays by many organizations globally because of the benefit it brings to both the human resources and the institution in general in terms of organizational performance and productivity. Being an administrator entails great responsibility in planning, organizing, leading and managing people to achieve organizational goals. In the process, it is inevitable that administrators may encounter various challenges which could affect their wellness, engagement and eventually their overall work performance. It is in this context that a study focused on wellness and engagement of administrators from La Salle Schools in the Philippines was conducted, with an end goal of crafting recommendations for an empirically-based wellness and engagement program. Likewise, literature shows that no research has been carried out regarding wellness of Lasallian administrators. Results revealed a significant relationship between wellness and engagement of the participants.
3. Lin, D.-J., Yu, W.-D., Wu, C.-M., and Cheng, T.-M., "Correlation between Intellectual Capital and Business Performance of Construction Industry— an Empirical Study in Taiwan," International Journal of Construction Management (EI), 18(3), 232-246, May, 2018.
Researchers have sought to determine the correlation between intellectual capital and business performance to enable corporations to shape policy decisions that benefit business performance in the past two decades. Previous works have focused on information technology (IT) and biotechnology (Biotech) industries rather than on the construction industry. This research aims at developing a construction industry intellectual capital valuation model for managers of construction-related firms to make better decisions in managing intellectual capitals. An empirical study was conducted on the application of the proposed intellectual capital valuation model to four representative firms from the construction industry listed in Taiwan’s stock market. It is found from the results of the empirical study that the business performance of construction industry relies highly on intellectual capital. As a result, the managers of construction related-firms should emphasize more on accumulation of the intellectual assets in order to improve their business performance. Moreover, the empirical results also show that the traditionally conceived “capital- and labor-intensive” construction industry is actually highly intellectually capitalized, with the average values of the MV/BV and Tobin’s q values significantly greater than 1.0 similar to that in the high-tech industries.
4. T.-M. Cheng, H.-Y. Gou, D. C. Agrawal, C.-F. Liaw and R.-C. Chen, "Remedial education for high-risk university freshmen - the case of a university of technology in Taiwan," Asia Pacific Journal of Educatin (SSCI), 38(2), 241-256, May, 2018.
Potential high-risk freshmen for three courses (Basic Math, Calculus, and Computing) in the university were identified based on the "College Students' Adjustment Chenck List (CSACL)" data available with the Student Development Center in the Office of Students' Affairs of the university. The study demonstrates that to ameliorate the problem of unpreparedness of freshmen, to check failure rates, and efficient use of limited resources, an effeitive remedial system could be developed by the combined inputs from the Office of Students' Affairs, Computer Center, Academic Affairs, and the Institutional Research. Our study corroborates the findings of other researches that gender, teacher, department, high school performance, enrollment channel, and loads during remedial course influence the learning outcome. Also, it was found that the use of multi-evaluation approaches in different enrollment channels can attain higher retention rates.
5. Cheng, T.-M., Hou, H.-Y., Chen, R.-C., Agrawal, D. C., and Lin, J.-Y., "Competency-bsed diagnosis for interns-quality accreditation," International Journal of Information Systems and Change Management (EI), 10(1), 55-79, Apr, 2018.
In order to understand how the advantages of internship programs influence the undergraduates, this study evaluated seniors’ experiences with the internship program in marketing and logistics management department at the case university. Through the University Career and Competency Assessment Network (UCAN) system, we used Deming’s ‘plan-do-check-action’ (PDCA) methodology to investigate the relationship between learning outcome, competency assessment, and curriculum improvement. Our study showed that after the internship, students’ professional and common competencies were improved and interns were satisfied with the program. In professional competency, students get opportunities for direct learning and experience of product, price, promotion, and place. Among the eight common competencies, the highest score represents the ‘responsibility and discipline’. The satisfaction surveys showed that it is very important to offer a rich and sufficient
curriculum design. Also, it was found that ‘communication expression’ and ‘job responsibility and discipline’ are best achieved by real-world training. This research fulfils objectives of the PDCA cycle and fits teaching and learning quality improvement.
6. Hou, H.-Y., Cheng, T.-M., and Chen, R.-C., "Integrating Education Resources Planning and Practice Information System to Alarm and Redeem Learners’ Performance," International Journal of Information Systems and Change Management (EI), 8(4), 271-283, Oct, 2016.
Good learning quality is not at the end of semester, but middle-term alarming system plays a very important role. It is fortunate that setting the independent Institutional Research Office and the data could be explored in one jointed access. The jointed access can be called “Education Resources Planning” system which links Alarming and Consulting System to do data mining and analyses. From ANOVA analysis, we found that the learning confusion ranked first for freshmen. The researchers followed the trail in the integrated Learning Management System and suggested the policy of eLearning for academic alarming students. Besides, the tutors and the teachers can remind the learners to redeem in the earlier period. The system can shorten the alarm time by sending note to those who are under the safe control limit. And students who need academic higher care can choose when and where to learn flexibly then to improve their performance.
7. Lin, C.-T., Hsie, M., Hsiao, W.-T., Wu, H.-T., and Cheng, T.-M., "Optimizing the schedule of dispatching earthmoving trucks through genetic algorithms and simulation," Journal of Performance of Constructed Facilities, ASCE, 26(2). (SCI), Apr, 2012.
Most construction projects involve earthmoving operations. Careful management of trucks to perform these operations is considered crucial by earthwork contractors in Taiwan. This paper presents a mechanism to optimize the management of the truck fleets of earthwork contractors. The proposed model integrates a discrete event simulation technique and genetic algorithms (GAs) to minimize the duration of earthmoving operations. The discrete simulation model is applied to simulate earthmoving operations and generate schedules for dispatching various trucks, and the GAs are used as a filter to screen out schedules that require long trips. Examples prove that the proposed model can determine near‐optimal solutions efficiently. In addition, a user‐friendly computer program is developed so that earthwork contractors can plan the dispatch schedule of earthmoving trucks easily and effectively.
8. Hsie, M., Hsiao, W.-T., Cheng, T.-M., and Chen, H.-C., "A model used in creating a work-rest schedule for laborers," Automation in Construction, 18(6), 762-769. (SCI, EI), Oct, 2009.
This paper presents a theoretical model that can be used to create work-rest schedules for construction
workers. Two objectives are proposed in the optimization processes when such schedules are created. These objectives include minimizing the time for completing jobs and minimizing any extra energy expended by laborers due to inappropriate work assignments that force them to work longer than the maximum acceptable work duration. A GA-based mechanism was developed to search the Pareto front, which is one of the effective ways for solving multiobjective optimization problems. Such a mechanism was implemented by computer programming using a numerical software tool called MATLAB. Theoretical examples demonstrated that the proposed model efficiently created work-rest schedules.
9. Horng, H.-C., Hu, C.-C., and Cheng, T.-M., "Evaluating the effectiveness of FDM in identifying important factors in a dynamic flowshop," Robotics and Computer-Integrated Manufacturing, 25(6), 894-900. (SCI), Aug, 2009.
Dynamiceventssuchasmachinebreakdownandhotjobsmayinduceproblemsontheproduction systemsuchasorderdelay,increasingmachineload,andchanginginventorylevel.Paststudiesof dynamiceventsoftenusetraditionaldesignofexperiments(DOE)toanalyzetheeffectsofdynamic events onsystem’sperformance.Theshortcomingofthisapproachisthatthenumberofexperimental runs conductedwouldbecomeexponentiallyincreasedasthenumberoffactorsincreased.Thisstudy tries tousefrequencydomainmethodology(FDM)insteadsoastodetectthehigherordereffectsand rank importantfactorsinafewexperimentalruns.Spectrumanalysisisusedtocomprehendtheeffects of differentlocationofmachinebreakdownanddifferentsizeofhotjobsonthesystem’sperformance of flowshopswithdifferenttraffic(utilization)andstability(oscillation).Thisstudyfindsthatthe importantfactorsidentifiedbytheFDManalysisarethesameasthatofDOE.However,onlyinsome cases cantherankingsofimportantfactorsbethesameforbothapproaches.Thedissimilaritybetween rankings of important factors found by these two methods is further rmeasured using Kendalltau distance.
10. Cheng, T.-M., Yen, R.-C., "Integrating MGA and simulation to optimize the resource utilization," Computer-Aided Civil and Infrastructure Engineering, 24(6), 401-415. (SCI), May, 2009.
This article presents a mechanism for integrating messy genetic algorithms (MGAs) and a discrete
event simulation technique to facilitate the simulation of optimal resource utilization to enhance system
performance, such as in relation to the production rate or unit cost. Various resource distribution modeling scenarios were tested in simulation to determine their system performances. MGA operations were then applied in the selection of the best resource utilization schemes based on those performances. A case study showed that this new modeling mechanism, along with the implemented
computer program, could not only ease the process of developing optimal resource utilization, but could
also improve the system performance of the simulation model.
11. Cheng, C.-C., Cheng, T.-M., and Chiang, C.-H., "Defect detection of concrete structures using both infrared thermography and elastic waves," Automation in Construction, 18(1), 87-92. (SCI, EI), Jan, 2008.
There are many nondestructive testing techniques that can be applied to assess the condition of existing
concrete structures with little expenditure of human labor. The objective of the current research is to pilotstudy
how one can combine active infrared thermography (IRT) with elastic wave techniques. In such a
manner, the fast scanning of a large structure is followed by elastic wave probing at a given small area.
Concrete slabs with embedded defects are heated by means of lamps prior to acquisition of thermal images.
The thermal images recorded show clear indication of hidden defects of various depths and areas. At present,
the results of IRT provide only limited quantitative information regarding the depth of hidden defects in
concrete. Depth of defects is readily deduced based on spectral analyses of received elastic wave signals. The
fusion of information gathered from IRT and elastic waves provides effective and efficient means for
inspection of the building exterior.
12. 5. Cheng, T.-M., Chen, Y.-L., "A GA mechanism for optimizing the design of attribute-double-sampling-plan," Automation in Construction, 16(3), 345-353. (SCI, EI), May, 2007.
An attribute double sampling plan (ADSP) can be performed when the acceptance parameters are known. These include first sample size, second sample size, first acceptance number, first rejectable number, and second acceptance number. The acceptance parameters must match the predefined probability 1-α of accepting a lot if the lot proportion defective is at the acceptable quality level (AQL) and β of accepting a lot if the lot proportion defective is at the rejectable quality level (RQL). In addition, the parameters must be all nonnegative integers and thus the system can not be solved as a closed-form solution. As a result, the trial-and-error method is usually used to seek the solutions. This paper presents a genetic algorithms-based mechanism for facilitating the ADSP design process. Objectives of minimizing both the deviations of fitting AQL-α and RQL-β and the total sample sizes are traded off in the optimization process. Case studies show that the new mechanism can effectively locate the
acceptance parameters and therefore facilitate the task of ADSP design. In addition, a computer program is developed for facilitating the task of performing the design of an ADSP.
13. Cheng, T.-M., Chen, Y.-L., "Performing time-cost trade-off anakysis via GA-simulation mechanism," Tamkang Journal of Science and Engineering, 10(4), 307-316. (EI), Jan, 2007.
This paper presents a mechanism integrating genetic algorithms with discrete event simulation
technique to solve construction time-cost trade-off (TCT) problem. Discrete event simulation technique
is used to model construction methods, operation processes, and together with the associated resources
used in the operations. Then, the genetic algorithm (GA) is applied to screen out those alternatives with
both higher cost and longer duration for a project. Case study shows that the proposed GA-simulation
mechanism can efficiently locate the solutions for TCT analysis. Additionally, this new mechanism is
computerized for facilitating the task of TCT analysis.
14. Cheng, T.-M., Feng, C.-W., and Hsu, M.-Y., "An integrated modeling mechanism for optimizing the simulation model of the construction operation," Automation in Construction, 15(3), 327-340. (SCI, EI), May, 2006.
A planner may use the discrete-event simulation to analyze and design the construction operation process that optimizes the overall
performance of a construction system. Normally, the basic elements used in construction operation process simulation system, such as
CYCLONE (CYCLic Operation NEtworks), are ‘‘activity’’ and ‘‘queue.’’ Activity is used to model the task which consumes resources and
takes time to perform. Queue acts as a storage location for resources entering an idle state. In the simulation system, queues have to be created
according to the ways of assigning resources to activities. Conventionally, planner defines queues according to his/her judgment by
determining which and what amount of resources should be allocated to which activity. Consequently, various modeling schemes have to be
examined to obtain the best simulation model. However, such a process of creating queues and activities is time consuming and requires
iterations. This paper introduces a Genetic Algorithms (GA)-based modeling mechanism to automate the process of selecting the optimal
modeling scheme. Case study shows that this new modeling mechanism along with the implemented computer program not only can ease the
process of developing the optimal resource combination but also improve the system performance of the simulation model.
15. Cheng, T.-M., Feng, C.-W., and Chen, Y.-L., "A hybrid mechanism for optimizing construction simulation models," Automation in Construction, 14(1), 85-98. (SCI, EI), Jan, 2005.
Simulation is a powerful tool for planning and scheduling highly repetitive tasks in a construction project. However,
sensitivity analysis has to be utilized to find the best resource combination to execute the construction tasks. By performing the
sensitivity analysis, various resource combinations can be evaluated in terms of their effects on the operation’s production and
cost. The results of the sensitivity analysis can assist project managers in planning effective resource assignments based on their
goals, such as maximizing the system’s production rate or minimizing the system’s unit cost. However, it is time-consuming to
conduct the sensitivity analysis if there are a large number of resource alternatives available. This paper proposes a hybrid
mechanism that integrates heuristic algorithms and genetic algorithms to efficiently locate the best resource combination for the
construction simulation optimization. Results show that this new hybrid mechanism not only locates the optimal solution but
also reduces tremendous computational efforts.
16. Feng, C-W., Cheng, T.-M., and Wu, S.-T., "Optimizing the schedule of dispatching RMC trucks through genetic algorithms," Automation in Construction, 13(3), 327-340. (SCI, EI), May, 2004.
Effectively and efficiently delivering Ready Mixed Concrete (RMC) to construction sites is an important issue to the RMC
batch plant manager. The RMC batch plant manager has to consider both timeliness and flexibility to develop an efficient schedule
of dispatching RMC trucks, which balances the operations at the construction sites and the batch plant. The requests of RMC
deliveries from different construction sites usually swamp into the batch plant at certain working hours. As a result, the batch plant
manager has to quickly decide a dispatching schedule that can satisfy the needs from different construction sites. The existing
dispatching schedule mainly depends on the experiences and preferences of the dispatcher. For example, the RMC plant manager
may dispatch as manyRMCtrucks as possible to the busiest construction site. However, such an approach might result in theRMC
trucks line up at the busiest job site while keeping other construction sites waiting for the arrivals of RMC trucks. A systematic
approach to such a problem has seldom been taken due to the complexity and uncertainty involved within the dispatching process.
Therefore, there is a need to develop a systematic model that optimizes the schedule of dispatching RMC trucks. This paper first
analyzes the factors that impact the RMC delivery process, then builds a model based on Genetic Algorithms and the simulation
technique to find the best dispatching schedule which minimizes the total waiting duration of RMC trucks at construction sites and
satisfies the needs of RMC deliveries from different construction sites. In addition, a user-friendly computer program is built to
help the batch plant manager streamline the dispatching process. Results show that this new systematic model along with the
implemented computer program can quickly generate efficient and flexible solutions to dispatching RMC trucks.
17. Cheng, T.-M., and Feng, C.-W., "An effective simulation mechanism for construction operations," Automation in Construction, 12(3), 227-244. (SCI, EI), May, 2003.
Construction project planners have used computer simulation to predict the performance of the construction operation in
terms of process flows and resource selection for decades. Traditionally, however, to find the best resource utilization of the
construction operation, all possible resource combinations should be tested within the simulation process. That is, an exhaustive
enumeration of resource combinations should be conducted, which is not economic if the possible resource combinations
increase explosively. Therefore, simulation is not considered as an optimization technique. Genetic Algorithms (GA), developed
by John Holland in 1975, has been widely applied to different disciplines of research for solving the optimization problems. GA
is also known for its flexibility in hybridizing with other methodologies to obtain better solutions of the simulation systems.
This paper presents a new mechanism that integrates simulation with GA to find the best resource combination for the
construction operation. Results show that the new simulation mechanism can effectively locate the optimal resource
combination for the construction operation and enhance the optimization capability of the construction simulation. In addition, a
user-friendly computer simulation system—Genetic Algorithms with Construction Operation Simulation Tool (GACOST) was
developed to provide the construction planner an efficient means of analyzing and optimizing the construction operation.
國際性會議論文
1. Tao-Ming Cheng, Hsing-yu Hou, Dinesh Agrawal, Rung-Ching Chen, Sung-Chi Hsu, "Improving Students Learning Performance from Learning Engagement," ICOED'2017 (Scopus), Nov, 2017.
2. Chih-Hung Chiang, Keng-Tsang Hsu, Cia-Chi Cheng, Chi-Luen Huang, Tao-Ming Cheng, "Dynamic survey of wind turbine vibrations," SPIE Smart Structures, Mar, 2016.
3. Hsiao, W.-T., Wu, H,-T., Cheng, T.-M., and Tsai, Y., "Mental workloads during form system assembly in environments with various bacjground music," 2014 International Conference on Advances in Management Engineering and Information Technology, Sep, 2014.
4. 1. Hsiao, W.-T., Wu, H.-T., and Cheng, T.-M., Chiang, C.-C., and Chen, Y.-J, "Using thermal image of the face to monitor construction foreman’s performance," Thirteen East Asia-Pacific Conference on Structural Engineering and Construction, Sep, 2013.
5. Hsiao, W.-T., Wu, H.-T., and Cheng, T.-M., and Chang, H.-N., "Using nose tip temperature to monitor crew’s performance," The First Australia and South East Asia Conference in Structural Engineering and Construction, Nov, 2012.
6. Hsiao, W.-T., Wu, H.-T., and Cheng, T.-M., "A Study on Crew Performance Measurement by Using Heart Rate and Oxygen Consumption," Construction Research Congress 2012, May, 2012.
7. Wu, H.-T., Hsiao, W.-T., Lin, C.-T., and Cheng, T.-M., "Application of genetic algorithm to the development of artificial intelligence module system," The 2nd International Conference on Intelligent Control and Information Processing, (EI), Jul, 2011.
8. Hsiao, W.-T., Lin, C.-T., Wu, H.-T., and Cheng, T.-M., "A hybrid optimization mechanism used to generate truck fleet to perform earthmoving operations," Geotechnical International Conference II, (EI), Jun, 2011.
9. Lin, C.-T., Hsiao, W.-T., Cheng, T.-M., and Wu, H.-T., "Simulation of NATM tunneling construction in gravel formation—lessons learned from Pakuashan highway tunnel project in Taiwan," Geotechnical International Conference I, (EI), Aug, 2009.
10. Hsiao, W.-T. and Cheng, T.-M., "A model of generating kob rotation schedule for construction workers," The 12th International Conference on Computing in Civil and Building Engineering, Oct, 2008.
11. Horng, C.-H., Hu, C.-C., and Cheng, T.-M., "“Evaluating the effectiveness of FDM in identifying important factors in a dynamic flowshop," The 18th International Conference on Flexible Automation and Intelligent Manufacturing, Jun, 2008.
12. Cheng, T.-M., and Chen, Y.-L., "A genetic algorithm simulation mechanism for time-cost trade-off analysis," The Fifth International Conference on Engineering Computational Technology, Sep, 2006.
13. Cheng, T.-M., and Chen, Y.-L., "Construction simulation using fuzzy durations," The Fifth International Conference on Engineering Computational Technology, Sep, 2006.
14. Cheng, T.-M., and Chen, Y.-L., "Optimization the design of an attribute double sampling plan," The 10th International Conference on Civil, Structural and Environmental Engineering Computing, Aug, 2005.
15. Cheng, T.-M., Hsu, M.Y., Chen, P. C., and Lin, C. C., "Automatic design mechanism for resource distribution for construction operations simulation," The 21st International Symposium on Automation and Robotics in Construction, Sep, 2004.