The Influence Of Supply Chain Relationships On Quality Performance In The Context Of China Automotive Industry

Industri pembuatan China kini menghadapi cabaran daripada persaingan global. The global competition is becoming more furious for China manufacturing industry

Enterprise Resource Planning (ERP) System and Company Performance

Enterprise resources planning (ERP) system, from business perspective, is following the need for integration of company's information in the real time environment as one of key success factors in strategic and operational decision making process. This research paper was conducted to identify and evaluate for the ERP system implementation in Jabil Green Point in term of the performance's improvement. Operations performance was treated as the dependent variables while Control, Integration and Contagion were the independent variables respectively. The Control variable was measured with respect to the ERP ability in control for the cost and inventory. Integration variable was measured in term for the system to integrate various functions in Jabil Green Point. Contagion variable was measured the connection between the organization's cultural and the ERP system implementation. A total of 50 respondents from the population of 65 staff in Jabil Green Point participated in this research paper. The data collection was conducted through the distribution of questionnaires, which was designed to measure the operations performance with a statement on a five likert scale point, ranging from one (strongly disagree) to five (strongly agree). Three hypotheses were tested for this research paper. Data was analyzed using the SPSS software to obtain the frequencies, means, median, standard deviation and correlations between variables. Descriptive analysis, Reliability analysis and Correlation & Relationship analysis were conducted to test the data collected. The results show that the Control and Integration variables have the positive relationship with operations performance while Contagion variable stated for the negative relationship with operations performance. In conclusion, this research paper shows that successfully for the ERP implementation were resulted in the improvement of the organization's performance. The suggestion for the future research was the research study have to involved for more companies especially for the multinational companies, thus the statistical generalization can be made

Coherent-incoherent transition in a Cooper-pair-box coupled to a quantum oscillator: an equilibrium approach

Temperature effect on quantum tunneling in a Cooper-pair-box coupled to a quantum oscillator is studied by both numerical and analytical calculations. It is found that, in strong coupling regions, coherent tunneling of a Cooper-pair-box can be destroyed by its coupling to a quantum oscillator and the tunneling becomes thermally activated as the temperature rises, leading to failure of the Cooper-pair-box. The transition temperature between the coherent tunneling and thermo-activated hopping is determined and physics analysis based on small polaron theory is also provided.Comment: 8 pages, 7 figure

Upper Water Structure and Mixed Layer Depth in Tropical Waters: The SEATS Station in the Northern South China Sea

The variability of the upper water hydrographic structure, the efficacy of the different schemes for estimating the mixed layer depth (MLD), the inter-comparability estimation of the MLDs and diurnal and intra-annual MLD climatology in the tropical waters in the northern South China Sea were accessed in 702 depth-profiles of potential temperature (θ) and salinity collected in 64 cruises between 17.5 and 18.5°N and 115.3 and 116.3°E from 1997 to 2013. The hydrographic structure may be subdivided into three principal types: the classical type, with quasi-isopycnal surface mixed layer followed by an abrupt increase in the depth-gradient in θ and potential density (σθ) to mark the MLD; the stepwise type, with one or more small stepwise decreases in θ and/or increases in σθ in the mixed layer; and the graded type, with a general decrease in θ and increases in σθ with depth into the main pycnocline without a clear break to mark the MLD. These three types of upper waters were found in 75, 10, and 15% of the cruises. Out. of the 10 schemes for estimating the MLD, only the fixed temperature difference method of 0.5 and 0.8°C from the 10-m temperature yielded consistent results, with root mean square error and mean absolute percentage difference of 2 m and 2%. MLD varied diurnally with an average standard deviation of 4 m from the mean. The monthly average MLD reached a maximum of 80 m in December/January and dropped to a minimum of 25 m in May

Factors associated with perceived effectiveness of training among academics in Universiti Malaysia Sarawak

This study was aimed at determining the perceptions of academics towards the effectiveness of training and the factors associate with the perception towards the training effectiveness. This study was conducted in a public university in Sarawak that is Universiti Malaysia Sarawak (UNIMAS). A survey methodology was used in collecting the data and 100 academics that have undergone the Postgraduate Diploma in Teaching and Learning were selected as the sample in this study. Statistical analysis such as frequency, percentage, t-test, ANOVA, Pearson Correlation and Linear Regression Analysis were used to analyze the data. This study reveals that 68% of the respondents possess positive perceptions towards the effectiveness of training. The findings also reveal insignificant difference among respondents with selected demographic characteristics in term of their perceptions towards the effectiveness of training. The findings of this study also reveal that there are significant relationships between respondents’ perceived effectiveness of training and trainee’s trainability ( r = 0.540, p = 0.000), trainer’s competency( r = 0.450, p = 0.000), training method ( r = 0.333, p = 0.000), training environment ( r = 0.434, p = 0.000) and management support ( r = 0.551, p = 0.000). Linear Regression Analysis also shows that the trainee’s trainability is the most dominant factor that influences the academics’ perceptions. Based on the findings of this study, it can be concluded that the Postgraduate Diploma in Teaching and Learning was perceived as effective, well accepted and favored by the academics attending the training program. Apart from this, trainee’s trainability needs to be given greater attention in assuring higher training effectiveness. It is recommended that the management and the human resource development department should put more effort to increase the trainees’ motivation and abilities before urging them to participate in the training program

Analytical solution of the tooling/workpiece contact interface shape during a flow forming operation

Flow forming involves complicated tooling/workpiece interactions. Purely analytical models of the tool contact area are difficult to formulate, resulting in numerical approaches that are case-specific. Provided are the details of an analytical model that describes the steady-state tooling/workpiece contact area allowing for easy modification of the dominant geometric variables. The assumptions made in formulating this analytical model are validated with experimental results attained from physical modelling. The analysis procedure can be extended to other rotary forming operations such as metal spinning, shear forming, thread rolling and crankshaft fillet rolling.Comment: 28 pages, 11 figure

Efficient Edge Intelligence in the Era of Big Data

Indiana University-Purdue University Indianapolis (IUPUI)Smart wearables, known as emerging paradigms for vital big data capturing, have been attracting intensive attentions. However, one crucial problem is their power-hungriness, i.e., the continuous data streaming consumes energy dramatically and requires devices to be frequently charged. Targeting this obstacle, we propose to investigate the biodynamic patterns in the data and design a data-driven approach for intelligent data compression. We leverage Deep Learning (DL), more specifically, Convolutional Autoencoder (CAE), to learn a sparse representation of the vital big data. The minimized energy need, even taking into consideration the CAE-induced overhead, is tremendously lower than the original energy need. Further, compared with state-of-the-art wavelet compression-based method, our method can compress the data with a dramatically lower error for a similar energy budget. Our experiments and the validated approach are expected to boost the energy efficiency of wearables, and thus greatly advance ubiquitous big data applications in era of smart health. In recent years, there has also been a growing interest in edge intelligence for emerging instantaneous big data inference. However, the inference algorithms, especially deep learning, usually require heavy computation requirements, thereby greatly limiting their deployment on the edge. We take special interest in the smart health wearable big data mining and inference. Targeting the deep learning’s high computational complexity and large memory and energy requirements, new approaches are urged to make the deep learning algorithms ultra-efficient for wearable big data analysis. We propose to leverage knowledge distillation to achieve an ultra-efficient edge-deployable deep learning model. More specifically, through transferring the knowledge from a teacher model to the on-edge student model, the soft target distribution of the teacher model can be effectively learned by the student model. Besides, we propose to further introduce adversarial robustness to the student model, by stimulating the student model to correctly identify inputs that have adversarial perturbation. Experiments demonstrate that the knowledge distillation student model has comparable performance to the heavy teacher model but owns a substantially smaller model size. With adversarial learning, the student model has effectively preserved its robustness. In such a way, we have demonstrated the framework with knowledge distillation and adversarial learning can, not only advance ultra-efficient edge inference, but also preserve the robustness facing the perturbed input.2023-06-0