A Novel Genetic Algorithm Designed for Hardware Implementation

A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.

Effects of Environmental Factors on Polychaete Assemblage in Penang National Park, Malaysia

Macrobenthos distribution along the coastal waters of Penang National Park was studid to estimate the effect of different environmental parameters at three stations, during six sampling months, from June 2010 to April 2011. The aim of this survey was to investigate different environment stress over soft bottom polychaete community along Teluk Ketapang and Pantai Acheh (Penang National Park) over a year period. Variations in the polychaete community were evaluated using univariate and multivariate methods. A total of 604 individuals were examined which was grouped into 23 families. Family Nereidae was the most abundant (22.68%), followed by Spionidae (22.02%), Hesionidae (12.58%), Nephtylidae (9.27%) and Orbiniidae (8.61%). It is noticeable that good results can only be obtained on the basis of good taxonomic resolution. The maximum Shannon-Wiener diversity (H'=2.16) was recorded at distance 200m and 1200m (August 2010) in Teluk Ketapang and lowest value of diversity was found at distance 1200m (December 2010) in Teluk Ketapang.

Novel Dual Stage Membrane Bioreactor for the Continuous Remediation of Electroplating Wastewater

In this study, the designed dual stage membrane bioreactor (MBR) system was conceptualized for the treatment of cyanide and heavy metals in electroplating wastewater. The design consisted of a primary treatment stage to reduce the impact of fluctuations and the secondary treatment stage to remove the residual cyanide and heavy metal contaminants in the wastewater under alkaline pH conditions. The primary treatment stage contained hydrolyzed Citrus sinensis (C. sinensis) pomace and the secondary treatment stage contained active Aspergillus awamori (A. awamori) biomass, supplemented solely with C. sinensis pomace extract from the hydrolysis process. An average of 76.37%, 95.37%, 93.26 and 94.76% and 99.55%, 99.91%, 99.92% and 99.92% degradation efficiency for total cyanide (T-CN), including the sorption of nickel (Ni), zinc (Zn) and copper (Cu) were observed after the first and second treatment stages, respectively. Furthermore, cyanide conversion by-products degradation was 99.81% and 99.75 for both formate (CHOO-) and ammonium (NH4 +) after the second treatment stage. After the first, second and third regeneration cycles of the C. sinensis pomace in the first treatment stage, Ni, Zn and Cu removal achieved was 99.13%, 99.12% and 99.04% (first regeneration cycle), 98.94%, 98.92% and 98.41% (second regeneration cycle) and 98.46 %, 98.44% and 97.91% (third regeneration cycle), respectively. There was relatively insignificant standard deviation detected in all the measured parameters in the system which indicated reproducibility of the remediation efficiency in this continuous system.

Feasibility Investigation of Near Infrared Spectrometry for Particle Size Estimation of Nano Structures

Determination of nano particle size is substantial since the nano particle size exerts a significant effect on various properties of nano materials. Accordingly, proposing non-destructive, accurate and rapid techniques for this aim is of high interest. There are some conventional techniques to investigate the morphology and grain size of nano particles such as scanning electron microscopy (SEM), atomic force microscopy (AFM) and X-ray diffractometry (XRD). Vibrational spectroscopy is utilized to characterize different compounds and applied for evaluation of the average particle size based on relationship between particle size and near infrared spectra [1,4] , but it has never been applied in quantitative morphological analysis of nano materials. So far, the potential application of nearinfrared (NIR) spectroscopy with its ability in rapid analysis of powdered materials with minimal sample preparation, has been suggested for particle size determination of powdered pharmaceuticals. The relationship between particle size and diffuse reflectance (DR) spectra in near infrared region has been applied to introduce a method for estimation of particle size. Back propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near infrared diffuse reflectance spectra. Thirty five different nano TiO2 samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP- ANN.

Emotion Classification by Incremental Association Language Features

The Major Depressive Disorder has been a burden of medical expense in Taiwan as well as the situation around the world. Major Depressive Disorder can be defined into different categories by previous human activities. According to machine learning, we can classify emotion in correct textual language in advance. It can help medical diagnosis to recognize the variance in Major Depressive Disorder automatically. Association language incremental is the characteristic and relationship that can discovery words in sentence. There is an overlapping-category problem for classification. In this paper, we would like to improve the performance in classification in principle of no overlapping-category problems. We present an approach that to discovery words in sentence and it can find in high frequency in the same time and can-t overlap in each category, called Association Language Features by its Category (ALFC). Experimental results show that ALFC distinguish well in Major Depressive Disorder and have better performance. We also compare the approach with baseline and mutual information that use single words alone or correlation measure.

Harmonic Analysis and Performance Improvement of a Wind Energy Conversions System with Double Output Induction Generator

Wind turbines with double output induction generators can operate at variable speed permitting conversion efficiency maximization over a wide range of wind velocities. This paper presents the performance analysis of a wind driven double output induction generator (DOIG) operating at varying shafts speed. A periodic transient state analysis of DOIG equipped with two converters is carried out using a hybrid induction machine model. This paper simulates the harmonic content of waveforms in various points of drive at different speeds, based on the hybrid model (dqabc). Then the sinusoidal and trapezoidal pulse-width–modulation control techniques are used in order to improve the power factor of the machine and to weaken the injected low order harmonics to the supply. Based on the frequency spectrum, total harmonics distortion, distortion factor and power factor. Finally advantages of sinusoidal and trapezoidal pulse width modulation techniques are compared.

Optimal Manufacturing Scheduling for Dependent Details Processing

The increasing competitiveness in manufacturing industry is forcing manufacturers to seek effective processing schedules. The paper presents an optimization manufacture scheduling approach for dependent details processing with given processing sequences and times on multiple machines. By defining decision variables as start and end moments of details processing it is possible to use straightforward variables restrictions to satisfy different technological requirements and to formulate easy to understand and solve optimization tasks for multiple numbers of details and machines. A case study example is solved for seven base moldings for CNC metalworking machines processed on five different machines with given processing order among details and machines and known processing time-s duration. As a result of linear optimization task solution the optimal manufacturing schedule minimizing the overall processing time is obtained. The manufacturing schedule defines the moments of moldings delivery thus minimizing storage costs and provides mounting due-time satisfaction. The proposed optimization approach is based on real manufacturing plant problem. Different processing schedules variants for different technological restrictions were defined and implemented in the practice of Bulgarian company RAIS Ltd. The proposed approach could be generalized for other job shop scheduling problems for different applications.

Formosa3: A Cloud-Enabled HPC Cluster in NCHC

This paper proposes a new approach to offer a private cloud service in HPC clusters. In particular, our approach relies on automatically scheduling users- customized environment request as a normal job in batch system. After finishing virtualization request jobs, those guest operating systems will dismiss so that compute nodes will be released again for computing. We present initial work on the innovative integration of HPC batch system and virtualization tools that aims at coexistence such that they suffice for meeting the minimizing interference required by a traditional HPC cluster. Given the design of initial infrastructure, the proposed effort has the potential to positively impact on synergy model. The results from the experiment concluded that goal for provisioning customized cluster environment indeed can be fulfilled by using virtual machines, and efficiency can be improved with proper setup and arrangements.

Bone Generation through Mechanical Loading

Bones are dynamic and responsive organs, they regulate their strength and mass according to the loads which they are subjected. Because, the Wnt/β-catenin pathway has profound effects on the regulation of bone mass, we hypothesized that mechanical loading of bone cells stimulates Wnt/β-catenin signaling, which results in the generation of new bone mass. Mechanical loading triggers the secretion of the Wnt molecule, which after binding to transmembrane proteins, causes GSK-3β (Glycogen synthase kinase 3 beta) to cease the phosphorylation of β-catenin. β-catenin accumulation in the cytoplasm, followed by its transport into the nucleus, binding to transcription factors (TCF/LEF) that initiate transcription of genes related to bone formation. To test this hypothesis, we used TOPGAL (Tcf Optimal Promoter β-galactosidase) mice in an experiment in which cyclic loads were applied to the forearm. TOPGAL mice are reporters for cells effected by the Wnt/β-catenin signaling pathway. TOPGAL mice are genetically engineered mice in which transcriptional activation of β- catenin, results in the production of an enzyme, β-galactosidase. The presence of this enzyme allows us to localize transcriptional activation of β-catenin to individual cells, thereby, allowing us to quantify the effects that mechanical loading has on the Wnt/β-catenin pathway and new bone formation. The ulnae of loaded TOPGAL mice were excised and transverse slices along different parts of the ulnar shaft were assayed for the presence of β-galactosidase. Our results indicate that loading increases β-catenin transcriptional activity in regions where this pathway is already primed (i.e. where basal activity is already higher) in a load magnitude dependent manner. Further experiments are needed to determine the temporal and spatial activation of this signaling in relation to bone formation.

Comparison of Three Meta Heuristics to Optimize Hybrid Flow Shop Scheduling Problem with Parallel Machines

This study compares three meta heuristics to minimize makespan (Cmax) for Hybrid Flow Shop (HFS) Scheduling Problem with Parallel Machines. This problem is known to be NP-Hard. This study proposes three algorithms among improvement heuristic searches which are: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). SA and TS are known as deterministic improvement heuristic search. GA is known as stochastic improvement heuristic search. A comprehensive comparison from these three improvement heuristic searches is presented. The results for the experiments conducted show that TS is effective and efficient to solve HFS scheduling problems.

One-Class Support Vector Machines for Aerial Images Segmentation

Interpretation of aerial images is an important task in various applications. Image segmentation can be viewed as the essential step for extracting information from aerial images. Among many developed segmentation methods, the technique of clustering has been extensively investigated and used. However, determining the number of clusters in an image is inherently a difficult problem, especially when a priori information on the aerial image is unavailable. This study proposes a support vector machine approach for clustering aerial images. Three cluster validity indices, distance-based index, Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative measures of the quality of clustering results. Comparisons on the effectiveness of these indices and various parameters settings on the proposed methods are conducted. Experimental results are provided to illustrate the feasibility of the proposed approach.

Urban Management and China's Municipal Pattern

Not only is municipal pattern the institution basement of urban management, but it also determines the forms of the management results. There-s a considerable possibility of bankruptcy for China-s current municipal pattern as it-s an overdraft of land deal in fact. Based on the analysis of China-s current municipal pattern, the passage proposed an assumption of a new pattern verified legitimacy by conceptual as well as econometric models. Conclusion is: the added supernumerary value of investment in public goods was not included in China-s current municipal pattern, but hidden in the rising housing prices; we should set housing tax or municipal tax to optimize the municipal pattern, to correct the behavior of local governments and to ensure the regular development of China-s urbanization.

Simulation of Roughness Shape and Distribution Effects on Rarefied and Compressible Flows at Slip Flow Regime

A numerical simulation of micro Poiseuille flow has performed for rarefied and compressible flow at slip flow regimes. The wall roughness is simulated in two cases with triangular microelements and random micro peaks distributed on wall surfaces to study the effects of roughness shape and distribution on flow field. Two values of Mach and Knudsen numbers have used to investigate the effects of rarefaction as well as compressibility. The numerical results have also checked with available theoretical and experimental relations and good agreements has achieved. High influence of roughness shape can be seen for both compressible and incompressible rarefied flows. In addition it is found that rarefaction has more significant effect on flow field in microchannels with higher relative roughness. It is also found that compressibility has more significant effects on Poiseuille number when relative roughness increases.

Numerical Simulations of Shear Driven Square and Triangular Cavity by Using Lattice Boltzmann Scheme

In this paper, fluid flow patterns of steady incompressible flow inside shear driven cavity are studied. The numerical simulations are conducted by using lattice Boltzmann method (LBM) for different Reynolds numbers. In order to simulate the flow, derivation of macroscopic hydrodynamics equations from the continuous Boltzmann equation need to be performed. Then, the numerical results of shear-driven flow inside square and triangular cavity are compared with results found in literature review. Present study found that flow patterns are affected by the geometry of the cavity and the Reynolds numbers used.

Determination of in Vitro Susceptibility of the Typhoid Pathogens to Synergistic Action of Euphorbia Hirta, Euphorbia Heterophylla and Phyllanthus Niruri for Possible Development of Effective Anti-Typhoid Drugs

Studies were carried out to determine the in vitro susceptibility of the typhoid pathogens to combined action of Euphorbia hirta, Euphorbia heterophylla and Phyllanthus niruri. Clinical isolates of the typhoid bacilli were subjected to susceptibility testing using agar diffusion technique and the minimum inhibitory concentration (MIC) determined with tube dilution technique. These isolates, when challenged with doses of the extracts from the three medicinal plants showed zones of inhibition as wide as 26±0.2mm, 22±0.1mm and 18±0.0mm respectively. The minimum inhibitory concentration (MIC) revealed organisms inhibited at varying concentrations of extracts: E. hirta (S. typhi 0.250mg/ml, S. paratyphi A 0.125mg/ml, S. paratyphi B 0.185mg/ml and S. paratyphi C 0.225mg/ml), E. heterophylla (S. typhi 0.280mg/ml, S. paratyphi A 0.150mg/ml, S. paratyphi B 0.200mg/ml and S. paratyphi C 0.250mg/ml) and P. niruri (S. typhi 0.150mg/ml, S. paratyphi A 0.100mg/ml, S. paratyphi B 0.115mg/ml and S. paratyphi C 0.125mg/ml). The results of the synergy between the three plants in the ration of 1:1:1 showed very low MICs for the test pathogens as follows S. typhi 0.025mg/ml, S. paratyphi A 0.080mg/ml, S. paratyphi B 0.015mg/ml and S. paratyphi C 0.10mg/ml with the diameter zone of inhibition (DZI) ranging from 35±0.2mm, 28±0.4mm, 20±0.1mm and 32±0.3mm respectively. The secondary metabolites were identified using simple methods and HPLC. Organic components such as anthroquinones, different alkaloids, tannins, 6-ethoxy-1,2,3,4-tetrahydro-2,2,4-trimethyl and steroids were identified. The prevalence of Salmonellae, a deadly infectious disease, is still very high in parts of Nigeria. The synergistic action of these three plants is very high. It is concluded that pharmaceutical companies should take advantage of these findings to develop new anti-typhoid drugs from these plants.

Low-Cost Pre-Treatment of Pharmaceutical Wastewater

Pharmaceutical industries and effluents of sewage treatment plants are the main sources of residual pharmaceuticals in water resources. These emergent pollutants may adversely impact the biophysical environment. Pharmaceutical industries often generate wastewater that changes in characteristics and quantity depending on the used manufacturing processes. Carbamazepine (CBZ), {5Hdibenzo [b,f]azepine-5-carboxamide, (C15H12N2O)}, is a significant non-biodegradable pharmaceutical contaminant in the Jordanian pharmaceutical wastewater, which is not removed by the activated sludge processes in treatment plants. Activated carbon may potentially remove that pollutant from effluents, but the high cost involved suggests that more attention should be given to the potential use of low-cost materials in order to reduce cost and environmental contamination. Powders of Jordanian non-metallic raw materials namely, Azraq Bentonite (AB), Kaolinite (K), and Zeolite (Zeo) were activated (acid and thermal treatment) and evaluated by removing CBZ. The results of batch and column techniques experiments showed around 46% and 67% removal of CBZ respectively.

Quantum Computation using Two Component Bose-Einstein Condensates

Quantum computation using qubits made of two component Bose-Einstein condensates (BECs) is analyzed. We construct a general framework for quantum algorithms to be executed using the collective states of the BECs. The use of BECs allows for an increase of energy scales via bosonic enhancement, resulting in two qubit gate operations that can be performed at a time reduced by a factor of N, where N is the number of bosons per qubit. We illustrate the scheme by an application to Deutsch-s and Grover-s algorithms, and discuss possible experimental implementations. Decoherence effects are analyzed under both general conditions and for the experimental implementation proposed.

Mechanical Properties of Particle Boards from Maize Cob and Urea-Formaldehyde Resin

Particle boards were prepared from Maize cob (MC) and urea-formaldehyde resin (UFR) on compression moulding machine. The amount of MC was varied from 50-120g while 30g of UFR was kept constant. Some mechanical properties of the particle boards were tested using the standard ASM methods. The results show that as the MC content increased from 50- 120g in 30g UFR, the hardness increased from about 6.89 x 102 to7.51 x 102MPa. Impact strength decreased from 3.3x 10-2 to 0.45 x 10-2J/M2, while tensile strength initially increased from 2.63 x 102 to 3.14 x 102 MPa as the MC increased from 50 to 60g in 30g UFR, thereafter, it decreased to about 1.35 x 102MPa at 120g in 30g content.

Mathematical Modeling of Asphaltene Precipitation: A Review

In the Enhanced Oil Recovery (EOR) method, use of Carbon dioxide flooding whereby CO2 is injected into an oil reservoir to increase output when extracting oil resulted significant recovery worldwide. The carbon dioxide function as a pressurizing agent when mixed into the underground crude oil will reduce its viscosity and will enable a rapid oil flow. Despite the CO2’s advantage in the oil recovery, it may result to asphaltene precipitation a problem that will cause the reduction of oil produced from oil wells. In severe cases, asphaltene precipitation can cause costly blockages in oil pipes and machinery. This paper presents reviews of several studies done on mathematical modeling of asphaltene precipitation. The synthesized result from several researches done on this topic can be used as guide in order to better understand asphaltene precipitation. Likewise, this can be used as initial reference for students, and new researchers doing study on asphaltene precipitation.

The Effect of the Tool Geometry and Cutting Conditions on the Tool Deflection and Cutting Forces

In this paper by measuring the cutting forces the effect of the tool shape and qualifications (sharp and worn cutting tools of both vee and knife edge profile) and cutting conditions (depth of cut and cutting speed) in the turning operation on the tool deflection and cutting force is investigated. The workpiece material was mild steel and the cutting tool was made of high speed steel. Cutting forces were measured by a dynamometer (type P.E.I. serial No 154). The dynamometer essentially consisted of a cantilever structure which held the cutting tool. Deflection of the cantilever was measured by an L.V.D.T (Mercer 122) deflection indicator. No cutting fluid was used during the turning operations. A modern CNC lathe machine (Okuma LH35-N) was used for the tests. It was noted that worn vee profile tools tended to produce a greater increase in the vertical force component than the axial component, whereas knife tools tended to show a more pronounced increase in the axial component.