Abstract: The garment manufacturing industry involves
sequential processes that are subjected to uncontrollable variations.
The industry depends on the skill of labour in handling the varieties
of fabrics and accessories, machines, as well as complicated sewing
operation. Due to these reasons, garment manufacturers have created
systems to monitor and to control the quality of the products on a
regular basis by conducting quality approaches to minimize variation.
With that, the aim of this research has been to ascertain the quality
approaches deployed by Malaysian garment manufacturers in three
key areas - quality systems and tools; quality control and types of
inspection; as well as sampling procedures chosen for garment
inspection. Besides, the focus of this research was to distinguish the
quality approaches adopted by companies that supplied finished
garments to both domestic and international markets. Feedback from
each company representative has been obtained via online survey,
which comprised of five sections and 44 questions on the
organizational profile and the quality approaches employed in the
garment industry. As a result, the response rate was 31%. The results
revealed that almost all companies have established their own
mechanism of process control by conducting a series of quality
inspections for daily production, either it was formally set up or
otherwise. In addition, quality inspection has been the predominant
quality control activity in the garment manufacturing, while the level
of complexity of these activities was substantially dictated by the
customers. Moreover, AQL-based sampling was utilized by
companies dealing with exports, whilst almost all the companies that
only concentrated on the domestic market were comfortable using
their own sampling procedures for garment inspection. Hence, this
research has provided insights into the implementation of a number
of quality approaches that were perceived as important and useful in
the garment manufacturing sector, which is truly labour-intensive.
Abstract: Events discrimination and decision maker in sport field are the subject of many interesting studies in computer vision and artificial intelligence. A large volume of research has been conducted for automatic semantic event detection and summarization of sports videos. Indeed the results of these researches have a very significant contribution, as well to television broadcasts as to the football teams, since the result of sporting event can be reflected on the economic field. In this paper, we propose a novel fuzzy sequential technique which lead to discriminate events and specify the technico-tactics on going the game, nor the fuzzy system or the sequential one, may be able to respond to the asked question, in fact fuzzy process is not sufficient, it does not respect the chronological order according the time of various events, similarly the sequential process needs flexibility about the parameters used in this study, it may affect a membership degree of each parameter on the one hand and respect the sequencing of events for each frame on the other hand. Indeed this technique describes special events such as dribbling, headings, short sprints, rapid acceleration or deceleration, turning, jumping, kicking, ball occupation, and tackling according velocity vectors of the two players and the ball direction.
Abstract: This study was to search for the desirable direction of
the sidewalk planning in Korea by establishing the concepts of
walking and pedestrian space, and analyzing the advanced precedents
in and out of country. Also, based on the precedent studies and
relevant laws, regulations, and systems, it aimed for the following
sequential process: firstly, to derive design elements from the
functions and characteristics of sidewalk and cluster the similar
elements by each characteristics, sampling representative
characteristics and making them hierarchical; then, to analyze their
significances via the first questionnaire survey, and the relative
weights and priorities of each elements via the Analytic Hierarchy
Process(AHP); finally, based on the analysis result, to establish the
frame of suggesting the direction of policy to improve the pedestrian
environment of sidewalk in urban commercial district for the future
planning and design of pedestrian space.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: The Programmable Logic Controller (PLC) plays a
vital role in automation and process control. Grafcet is used for
representing the control logic, and traditional programming
languages are used for describing the pure algorithms. Grafcet is used
for dividing the process to be automated in elementary sequences that
can be easily implemented. Each sequence represent a step that has
associated actions programmed using textual or graphical languages
after case. The programming task is simplified by using a set of
subroutines that are used in several steps. The paper presents an
example of implementation for a punching machine for sheets and
plates. The use the graphical languages the programming of a
complex sequential process is a necessary solution. The state of
Grafcet can be used for debugging and malfunction determination.
The use of the method combined with a set of knowledge acquisition
for process application reduces the downtime of the machine and
improve the productivity.
Abstract: One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.