1,721,128 research outputs found
Towards understanding bayesian network-based inferred gene interactions
No full textIt is hoped that this seminar will inculcate the right culture that is geared towards ensuring passion, dedication and commitment for research activities that will be good enough to provide support to the UTM theme “Innovative, Entrepreneurial and Global”. It is also hoped that the seminar will motivate students to participate in national and international conferences. It is anticipated that the students will appreciate the feedback from the various evaluators and get motivated with them
Operation sequencing using modified particle swarm optimization
Full text linkPlanning and scheduling (PS) problems in advanced manufacturing systems, such as flexible manufacturing systems, are composed of a set of interrelated problems, such as operation sequencing, machine selection. routing, and online scheduling. Operation sequencing deals with the problem of determining in what order to perform a set of selected operations such that the resulting sequence satisfies the precedence constraints as well as alternative operation constraints established by both the parts and operations. In this paper, modified particle swarm optimization (MPSO) has been used to generate a feasible operation sequence for a real world manufacturing problem. In addition, the directed mutation is used to accelerate the individuals move toward the optimal solutions. The quality of the result and its numerical performance is discussed in comparison with a standard genetic algorithm (SGA). After to runs, the result from SGA show that the possibilities for the solution to fall in the near optimal solution is about 30% compared with the result from MPSO which always force the constraints to befully satis.fied
Towards gene network estimation with structure learning
Full text linkGene network is a representation of gene interactions. A gene usually collaborates with other genes in order
to function. Understanding these interactions is a crucial step towards understanding how our body
functions. Bayesian Network is a technique that was initially used in Expert System to represent expert
knowledge. Since the pioneer work of Friedman et al. that applied this technique to analyse gene
expression data, other researchers have enhanced the technique further. This research concentrates on
enhancing Bayesian Network technique fro learning gene network. In order to get better results, Bayesian
technique will be used with prior knowledge. The tool that is used to learn the gene network is
PNL(Probabilistic Network Library). Early results show that PNL can be used to recover gene network for
3 subnetworks for S.Cerevisiae. These 3 subnetworks has been learned using PNL with varying success.
The next step in this research is to learn the gene network from the dataset of 800 genes. The knowledge
that will be gained will be used to produce a better approach to learning gene network using Bayesian
network techniqu
A novel text modeling approach for structural comparison and alignment of biomolecules
No full textWithin this paper, a novel strategy for structural alignment of proteins based on text modeling techniques is introduced. The method summarizes the protein secondary and tertiary structure in two textual sequences. The first sequence is used to initial superposition of secondary structure elements and the second sequence is employed to align the 3D-structure of two compared structures. The comparison technique used by the method has been inspired from computational linguistics for analysing and quantifying textual sequences. In this strategy, the cross-entropy measure over n-gram models is used to capture regularities between sequences of protein structures. The performance of the method is evaluated and compared with CE and SSM methods. The results of the experiments reported here provide evidence for the preference and applicability of the new approach in terms of efficiency and effectiveness
Penyelesaian Masalah Penjadualan Dinamik Dengan Menggunakan Pendekatan Taakulan Berasaskan Kes
Full text linkMasalah penjadualan waktu universiti telah menjadi satu masalah yang membebankan pihak pengurusan akhir-akhir ini. Persekitaran aktiviti akademik yang sentiasa berubah menyebabkan berlakunya perubahan kepada jadual semasa. Kebanyakan sistem penjadualan yang sedia ada tidak dapat menyelesaikan masalah ini. Oleh yang demikian, taakulan berasaskan kes (CBR) telah di pilih untuk bertindakbalas terhadap sebarang perubahan di dalam sistem penjadualan untuk memastikan penyelesaiannya sentiasa selari dengan perkembangan persekitaran yang dinami
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Towards implementing reactive scheduling for job shop problem
Full text linkMost of the research literature concerning scheduling concentrates on the static problems, i.e problems where all input data is known and does not change over time. However, the real world scheduling problems are very seldom static. Events like machine breakdown or bottleneck in some situation impossible to predict. Dynamic scheduling is a research field, which take into consideration uncertainty and dynamic changes in the real world scheduling problem. This paper gives an overview of the real problem occured in the filed of dynamic scheduling. Then we propose a hybrid genetic algorithm for solving the dynamic job shop problem
Petri Nets modeling of a real world manufacturing processes
Full text linkEvery company strives to increase their profits. One of the key factors in ensuring the profits is effective utilization of manufacturing resources through application of efficient planning and scheduling approaches. These two main approaches are closely related to the manufacturing processes in a flexible manufacturing system (FMS) which are known as process planning and production scheduling. Process planning is refers to a process plan which is generated for each part to be manufactured in a manufacturing system (Wang and Li, 1991). The process plan specifies operations to be performed and their sequence, required resources and process parameters of each operation. On the other hand, production scheduling determines the most appropriate moment to execute each operation for the planned production, taking into account the due date, a maximum resource utilization, etc., in order to achieve high productivity in a manufacturing system (Kempenaers et al., 1996). One of the objectives of this work is to develop the process models, to help the definition of production processes. These models allow focusing on the second objective, which is to implement an integrated process planning, to specify the operations to be performed in manufacturing a product; and production scheduling, to estimate a start time for the particular operations to be performed in the case of manufacturing an automotive spring product. This chapter concentrates on the modeling of production processes using Petri Nets (PN) in order to understand the dynamic behavior of machine and production processes. Our case study is automotive spring production
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