Realization of modular multidimensional complex digital filters using GIC concept

It is known that complex digital filters possess certain advantages over real digital filters in processing complex signals such as increased computational speed and efficiency. In this paper, a simple and systematic procedure which can be implemented through a computer program is presented for realizing a specific class of multidimensional (M-D) complex digital filters. The proposed filter structures are derived from analog reference configurations comprising generalized immittance converters and resistors by making use of wave concept. These filters possess many salient properties such as low noise, low sensitivity and capability of realizing multiple transfer functions simultaneously which are inherited from the reference analog filters they are derived from. These features make them attractive for very large-scale integrated (VLSI) implementation. It is shown that the proposed filter structures can be obtained directly from the specified M-D discrete transfer function without the need for realizing any analog reference configuration.     

An elitist strategy genetic algorithm using simulated annealing algorithm as local search for facility layout design

A well-planned arrangement of manufacturing departments on a two-dimensional planar region considerably increases the efficiency of its production systems, which is termed facility layout problem (FLP). Conventional layout design approach often designs intercell layout (determining exact location of each department on shop floor area) and flow path layout design of material handling system (MHS) step by step in a sequential manner. This results in suboptimal solutions for FLP. In this paper, an integrated approach is adopted to design the intercell layout and the flow path layout of MHS simultaneously. The quality of the final layout is evaluated by minimizing total material handling cost. Sequence pair (SP) representation is used for layout encoding. The translation from SP to layout is efficiently made by longest common subsequence (LCS) methodology. An elitist strategy genetic algorithm using simulated annealing (E-GASAA) as a local search mechanism is developed and tested with four test problem instances available in the literature. Elitist strategy is incorporated to enhance convergence characteristic of the proposed algorithm. It is found that the proposed E-GASAA is able to produce best solutions consistently for the test problem instance of different sizes within acceptable computational effort. In addition to that, we tried to reduce the computational load with the help of adopted LCS computation methodology and achieved a good improvement.     

Differential evolution variants to schedule flexible assembly lines

Scarce resources such as material, labor, and equipment are to be optimized to improve the performance and lower production costs in flexible assembly lines. These resources are usually allocated optimally through the generation of schedules. In this paper, variants of a differential evolution-based algorithm are employed to schedule flexible assembly lines (FAL). The performance of the assembly line is optimized based on two performance criteria, namely the weighted sum of Earliness/Tardiness penalties and the balance of the assembly line. Different variants of the Bi-level differential evolution (BiDE) algorithms are developed to study the effects of three FAL problems. The parameters of BiDE algorithm for FAL problems are fine-tuned. The performance of the BiDE algorithm is evaluated using the datasets and the Bi-level Genetic Algorithm (BiGA) available in the literature. The experimental results show that the proposed differential evolution-based algorithm outperforms BiGA in terms of mean best fitness.     

Secondary population implementation in multi-objective evolutionary algorithm for scheduling of FMS

Any practical implementation of any multi-objective evolutionary algorithm (MOEA) must include a secondary population composed of all Pareto-optimal solutions found during its search process. Such an implementation with an active participation of solutions from the secondary population into the generational population of the genetic cycle is expected to improve the effectiveness of the MOEA. In this work, two kinds of secondary population, one with set of non-dominated solutions and another with a set of inferior solutions, accrued out of the generation cycles are constructed, and with different combinations of feeding of solutions from these two secondary populations, seven different implementation schemes are designed with an aim of intensifying the convergence and diversification capabilities of the genetic process of MOEA. All the schemes were implemented in a genetic algorithm-based MOEA designed to solve the scheduling problem with dual objectives for a flexible manufacturing system and tested with common experimental data. The performances of the schemes are compared, and the most appropriate implementation scheme is proposed.     

A Golgi localization signal identified in the Menkes recombinant protein

Menkes disease arises from a genetic impairment in copper transport. The gene responsible for the phenotype has been identified as a copper transporting ATPase ( ATP7A ). Recently, the protein encoded by the ATP7A gene has been localized to the Golgi complex. In order to investigate the role of the Menkes disease protein in copper transport, recombinant constructs containing both the full-length open reading frame and an alternatively spliced form have been successfully expressed and localized in mammalian cells. Other studies of a patient with occipital horn syndrome, an allelic variant of Menkes disease, have demonstrated that only this alternatively spliced isoform and not the full-length form is expressed in this patient. The milder form of this patient's phenotype suggests that the alternatively spliced isoform has some functional role in copper transport. In the present study the full-length recombinant Menkes protein was shown by immunofluorescence to localize to the Golgi apparatus and the alternatively spliced form, lacking sequences for transmembrane domains 3 and 4 encoded by exon 10, was shown to localize to the endoplasmic reticulum. Using sequences from exon 10 fused to a non-Golgi reporter molecule, a 38 amino acid sequence containing transmembrane domain 3 of the Menkes protein was found to be sufficient for localization to the Golgi complex. Therefore, the protein sequence encoded by exon 10 may be responsible for this differential localization and both isoforms may be required for comprehensive transport of copper within the cell.     

Threshold accepting and Ant-colony optimization algorithms for scheduling m-machine flow shops with lot streaming

This paper addresses the problem of making sequencing and scheduling decisions for n jobs m machines flow shops under lot sizing environment. Lot streaming (lot sizing) is the process of creating sublots to move the completed portion of a production sublots to down stream machines. There is a scope for efficient algorithms for scheduling problems in m-machine flow shop with lot streaming. In recent years, much attention is given to heuristics and search techniques. On this concern this paper proposes Ant-colony optimization algorithm (ACO) and threshold accepting algorithm (TA) to evolve best sequence for makespan/total flow time criterion for m-machine flow shop involved with lot streaming and setup time. The following two algorithms are used to evaluate the performance of the proposed ACO and TA: (i) Baker's algorithm (BA), an optimal solution procedure for two-machine flow shop problem with lot streaming and makespan objective criterion and (ii) genetic and hybrid genetic algorithm for m-machine flow shop problem with lot streaming and makespan and total flow time criteria.     

Iterated fast local search algorithm for solving quadratic assignment problems

This paper concentrates on multi-row machine layout problems that can be accurately formulated as quadratic assignment problems (QAPs). A genetic algorithm-based local search approach is proposed for solving QAPs. In the proposed algorithm, three different mutation operators namely adjacent, pair-wise and insertion or sliding operators are separately combined with a local search method to form a mutation cycle. Effectiveness of introducing the mutation cycle in place of mutation is studied. Performance of the proposed iterated approach is analyzed and the solution qualities obtained are reported.     

Introductory probabilistic and stochastic analysis and design ofcircuits

The authors introduce the subject of probabilistic and stochastic analysis and design of circuits to nonspecialists and emphasize the need for teaching the subject to senior level undergraduates. It is argued that as this subject area synthesizes ideas from systems theory, electrical circuit analysis and design, matrix methods, probability and stochastic theories, numerical methods, optimization and symbolic algebra, this will be an ideal course to demonstrate the use of most of the background subjects, and relevant computing techniques and software. Problems solved could include electrical engineering problems, and other engineering problems modeled with electrical analogs     

Performance analysis of double-pass oscillating bed solar dryer for drying of non-parboiled paddy grains

Drying of agricultural produce like paddy grains is necessary for reducing moisture content in them to the required level towards diminishing the deterioration and enhancing the storage time. Conventionally, open-space sun drying is widely used to reduce the moisture content of the most of the agricultural produce.. Now-a-day, so many solar dryers are used for drying agricultural produce. In the present work, a double-pass oscillating bed with a double-pass flat plate collector has been used for drying of non-parboiled paddy grains. The bed oscillated at a frequency of 2.75 Hz. The oscillating bed solar dryer can dry 45 kg of non-parboiled paddy grains in just a single day to the required level of moisture content, and the average moisture present in the dried grains was 13.55%. The average dryer thermal efficiency and pick-up efficiency in non-parboiled paddy were 28.79% and 52.17%, respectively.     

Knowledge-based workcell attribute oriented dynamic schedulers for flexible manufacturing systems

The economy of production in flexible manufacturing systems (FMS) depends mainly on how effectively the production is planned and how the resources are used. This requires efficient and dynamic factory scheduling and control procedures. This paper addresses two knowledge-based scheduling schemes (work cell attribute oriented dynamic schedulers WCAODSs) to control the flow of parts efficiently in real-time for FMS in which the part-mix varies continually with the planning horizon. The present work employs a hybrid optimisation approach in the generalised A1 framework. A genetic algorithm that provides an optimal combination of a set of priority dispatching rules, one for each work cell WC (WCwisepdr set), for each of the problem instances characterised by their WC attributes, is used for generating examples. The WC attributes reflect the information about the operating environment of each individual WC. Two inductive learning algorithms are employed to learn the examples, and scheduling rules are formulated as a knowledge base. The learning algorithms employed are: the Genetic CID3 (Continuous Interactive Dichotomister3 algorithm extended with genetic program for weight optimisation) and the Classification Decision Tree algorithm. The knowledge base obtained through the above learning schemes generates robust and effective schedules intelligently with respect to the part-mix changes in real-time, for makespan criteria. The comparison made with a GA-based scheduling methodology shows that WCAODSs provide solutions closer to the optimum.