With the improvement of people’s living quality, more attention has been paid in food safety and quality. This is especially true for perishable agricultural and dairy products. It is quite often that customers receive poor or broken products due to mistakes or wrong ways in transportation. This leads customers the unsatisfied for companies’ products are relatively low. To solve the above problem, this paper proposes a new approach of using frequent closed sequential mining technology to analysis logistics data for helping companies to track the possible transportation problems. The approach consists of several important steps: RFID-enabled raw data collection, frequent sequential patterns mining, and patterns analysis. The experiment shows the proposed analysis method can discover many inside transportation service causes.
This paper presents our empirical observations related to the evolution of a large automated test system. The system observed is used in the industry as a test tool for complex telecommunication systems, itself consisting of more than one million lines of source code. This study evaluates how different changes during the development have changed the number of observed Code Smells in the test system. We have monitored the development of the test scripts and measured the code quality characteristics over a five years period.
The observations show that the introduction of continuous integration, the existence of tool support for quality improvements in itself, changing the development methodologies (from waterfall to agile), changing technical and line management structure and personnel caused no measurable change in the trends of the observed Code Smells. Internal quality improvements were achieved mainly by individuals intrinsic motivation. Our measurements show similarities with earlier results on software systems evolutions presented by Lehman.
Workshop on Formal Approaches to Testing of Software (TestCom/FATES 2007 ), June 26-29, 2007, Tallinn, Estonia. Lecture Notes in Computer Science (LNCS) 4581, 2007 pp. 228-243. → 85
 PMD, http://pmd.sourceforge.net →80, 84
 R. van Solingen, E. Berghout, The Goal/Question/Metric Method, a Practical Method for QualityImprovement of Software Development, McGraw-Hill, 1999. →78
 K. Szabados, Structural analysis of large TTCN-3 projects, Proc. 21st IFIP WG 6.1 International Conference on Testing of Software and
) recommended the use of patient safety reporting systems (PSRS) to reduce future mistakes from the incurred incidents ( Brennan et al., 1991 ; Erickson et al., 2003 ; Kohn, Corrigan, & Donaldson, 2000 ). Moving from paper-based reporting systems to electronic systems, the development of PSRS has been documented since the late 1970s ( Elliott, Martin, & Neville, 2014 ). A well-functioning PSRS benefits the communication efficiency ( Cochrane et al., 2009 ; Elliott et al., 2014 ), the qualityimprovement of reports across various healthcare settings and types of errors
network unbalance using PI-R current regulators , IEEE Trans. Ind. Electron., 2009, 56(2), 439–451.
 S antos -M artin D., R odriguez -A menedo J.L., A rnalte S., Direct power control applied to doubly fed induction generator under unbalanced grid voltage conditions , IEEE Trans. Power Electron., 2008, 23(5), 2328–2336.
 H u J., Z hu J., D orrell D.G., Predictive direct power control of doubly fed induction generators under unbalanced grid voltage conditions for power qualityimprovement , IEEE Trans. Sustain. Energy, 2015, 6(3), 943
assessment of a street-drainage bioretention system. Water Environ Res.; 82(2):109–119. DOI: 10.2175/106143009´426112.
 DeBusk, K.M., Wynn, T.M. (2011): Storm-water bioretention for runoff quality and quantity mitigation. J Environ Eng.; 137(9): 800–808. DOI: 10.1061/(ASCE)EE.1943-7870.0000388.
 Davis, A.P., Hunt, W., Traver, R., Clar, M. (2009): Bioretention technology: Overview of current practice and future needs. J. Environ. Eng.; 135 , 109–117.
 Davis, A.P., Shokouhian, M., Sharma, H. and Minami, C. (2006): Water qualityimprovement
Liang Hong, Mengqi Luo, Ruixue Wang, Peixin Lu, Wei Lu and Long Lu
comorbidities, and rely on objective data, such as laboratory values or other machine-collected variables that do not require subjective interpretation and input of hospital personnel.
A study was conducted by Anderson and Chang (2015) was conducted to determine whether machine-collected data elements could perform as well as a traditional, full risk-adjustment model that includes other physician-assessed and physician-recorded data elements. This research uses all available The National Surgical QualityImprovement Program (NSQIP) data from January 1, 2005, to December
Abdallah, A. B. (2013). The Influence of Soft and Hard Total Quality Management (TQM) Practises on Total Productive Maintenance (TPM) in Jordanian manufactiuring Companies. International Journal of Business and Management, 8(21), 1.
Abdullah, M. M. B., Uli, J., and Tari, J. J. (2008). The influence of soft factors on qualityimprovement and performance: Perceptions from managers. The TQM Journal, 20(5), 436-452.
Abdullah, M. M. B., Uli, J., and Tarí, J. J. (2009). The relationship of performance with soft factors and quality