Impact of Height of Silicon Pillar on Vertical DG-MOSFET Device

Vertical Double Gate (DG) Metal Oxide Semiconductor Field Effect Transistor (MOSFET) is believed to suppress various short channel effect problems. The gate to channel coupling in vertical DG-MOSFET are doubled, thus resulting in higher current density. By having two gates, both gates are able to control the channel from both sides and possess better electrostatic control over the channel. In order to ensure that the transistor possess a superb turn-off characteristic, the subs-threshold swing (SS) must be kept at minimum value (60-90mV/dec). By utilizing SILVACO TCAD software, an n-channel vertical DG-MOSFET was successfully designed while keeping the sub-threshold swing (SS) value as minimum as possible. From the observation made, the value of sub-threshold swing (SS) was able to be varied by adjusting the height of the silicon pillar. The minimum value of sub-threshold swing (SS) was found to be 64.7mV/dec with threshold voltage (VTH) of 0.895V. The ideal height of the vertical DG-MOSFET pillar was found to be at 0.265 µm.

Humor Roles of Females in a Product Color Matrix

Healthcare providers sometimes use the power of humor as a treatment and therapy for buffering mental health or easing mental disorders because humor can provide relief from distress and conflict. Humor is also very suitable for advertising because of similar benefits. This study carefully examines humor's widespread use in advertising and identifies relationships among humor mechanisms, female depictions, and product types. The purpose is to conceptualize how humor theories can be used not only to successfully define a product as fitting within one of four color categories of the product color matrix, but also to identify compelling contemporary female depictions through humor in ads. The results can offer an idealization for marketing managers and consumers to help them understand how female role depictions can be effectively used with humor in ads. The four propositions developed herein are derived from related literature, through the identification of marketing strategy formulations that achieve product memory enhancement by adopting humor mechanisms properly matched with female role depictions.

Ant Colony Optimization for Feature Subset Selection

The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.

Visualization of Sediment Thickness Variation for Sea Bed Logging using Spline Interpolation

This paper discusses on the use of Spline Interpolation and Mean Square Error (MSE) as tools to process data acquired from the developed simulator that shall replicate sea bed logging environment. Sea bed logging (SBL) is a new technique that uses marine controlled source electromagnetic (CSEM) sounding technique and is proven to be very successful in detecting and characterizing hydrocarbon reservoirs in deep water area by using resistivity contrasts. It uses very low frequency of 0.1Hz to 10 Hz to obtain greater wavelength. In this work the in house built simulator was used and was provided with predefined parameters and the transmitted frequency was varied for sediment thickness of 1000m to 4000m for environment with and without hydrocarbon. From series of simulations, synthetics data were generated. These data were interpolated using Spline interpolation technique (degree of three) and mean square error (MSE) were calculated between original data and interpolated data. Comparisons were made by studying the trends and relationship between frequency and sediment thickness based on the MSE calculated. It was found that the MSE was on increasing trends in the set up that has the presence of hydrocarbon in the setting than the one without. The MSE was also on decreasing trends as sediment thickness was increased and with higher transmitted frequency.

Investigating Feed Mix Problem Approaches: An Overview and Potential Solution

Feed is one of the factors which play an important role in determining a successful development of an aquaculture industry. It is always critical to produce the best aquaculture diet at a minimum cost in order to trim down the operational cost and gain more profit. However, the feed mix problem becomes increasingly difficult since many issues need to be considered simultaneously. Thus, the purpose of this paper is to review the current techniques used by nutritionist and researchers to tackle the issues. Additionally, this paper introduce an enhance algorithm which is deemed suitable to deal with all the issues arise. The proposed technique refers to Hybrid Genetic Algorithm which is expected to obtain the minimum cost diet for farmed animal, while satisfying nutritional requirements. Hybrid GA technique with artificial bee algorithm is expected to reduce the penalty function and provide a better solution for the feed mix problem.

Expert System for Sintering Process Control based on the Information about solid-fuel Flow Composition

Usually, the solid-fuel flow of an iron ore sinter plant consists of different types of the solid-fuels, which differ from each other. Information about the composition of the solid-fuel flow usually comes every 8-24 hours. It can be clearly seen that this information cannot be used to control the sintering process in real time. Due to this, we propose an expert system which uses indirect measurements from the process in order to obtain the composition of the solid-fuel flow by solving an optimization task. Then this information can be used to control the sintering process. The proposed technique can be successfully used to improve sinter quality and reduce the amount of solid-fuel used by the process.

Design and Development of an MPH Program for Distance Education Delivery

The Master-s of Public Health (MPH) degree is growing in popularity among a number of higher education institutions throughout the world as a distance education graduate program. This paper offers an overview of program design and development strategies that promote successful distance delivery of MPH programs. Design and development challenges are discussed in terms of type of distance delivery, accreditation, student demand, faculty development, user needs, course content, and marketing strategies. The ongoing development of a distance education MPH program at Utah State University will be used to highlight and consider various aspects of this important but challenging process.

Study on the Characteristics of the Measurement System for pH Array Sensors

A measurement system for pH array sensors is introduced to increase accuracy, and decrease non-ideal effects successfully. An array readout circuit reads eight potentiometric signals at the same time, and obtains an average value. The deviation value or the extreme value is counteracted and the output voltage is a relatively stable value. The errors of measuring pH buffer solutions are decreased obviously with this measurement system, and the non-ideal effects, drift and hysteresis, are lowered to 1.638mV/hr and 1.118mV, respectively. The efficiency and stability are better than single sensor. The whole sensing characteristics are improved.

A Phenomic Algorithm for Reconstruction of Gene Networks

The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.

Target Detection using Adaptive Progressive Thresholding Based Shifted Phase-Encoded Fringe-Adjusted Joint Transform Correlator

A new target detection technique is presented in this paper for the identification of small boats in coastal surveillance. The proposed technique employs an adaptive progressive thresholding (APT) scheme to first process the given input scene to separate any objects present in the scene from the background. The preprocessing step results in an image having only the foreground objects, such as boats, trees and other cluttered regions, and hence reduces the search region for the correlation step significantly. The processed image is then fed to the shifted phase-encoded fringe-adjusted joint transform correlator (SPFJTC) technique which produces single and delta-like correlation peak for a potential target present in the input scene. A post-processing step involves using a peak-to-clutter ratio (PCR) to determine whether the boat in the input scene is authorized or unauthorized. Simulation results are presented to show that the proposed technique can successfully determine the presence of an authorized boat and identify any intruding boat present in the given input scene.

Design of Reliable and Low Cost Substrate Heater for Thin Film Deposition

The substrate heater designed for this investigation is a front side substrate heating system. It consists of 10 conventional tungsten halogen lamps and an aluminum reflector, total input electrical power of 5 kW. The substrate is heated by means of a radiation from conventional tungsten halogen lamps directed to the substrate through a glass window. This design allows easy replacement of the lamps and maintenance of the system. Within 2 to 6 minutes the substrate temperature reaches 500 to 830 C by varying the vertical distance between the glass window and the substrate holder. Moreover, the substrate temperature can be easily controlled by controlling the input power to the system. This design gives excellent opportunity to deposit many deferent films at deferent temperatures in the same deposition time. This substrate heater was successfully used for Chemical Vapor Deposition (CVD) of many thin films, such as Silicon, iron, etc.

Modeling Stress-Induced Regulatory Cascades with Artificial Neural Networks

Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.

Immobilization of Aspergillus awamori 1-8 for Subsequent Pectinase Production

The overall objective of this research is a strain improvement technology for efficient pectinase production. A novel cells cultivation technology by immobilization of fungal cells has been studied in long time continuous fermentations. Immobilization was achieved by using of new material for absorption of stores of immobilized cultures which was for the first time used for immobilization of microorganisms. Effects of various conditions of nitrogen and carbon nutrition on the biosynthesis of pectolytic enzymes in Aspergillus awamori 1-8 strain were studied. Proposed cultivation technology along with optimization of media components for pectinase overproduction led to increased pectinase productivity in Aspergillus awamori 1-8 from 7 to 8 times. Proposed technology can be applied successfully for production of major industrial enzymes such as α-amylase, protease, collagenase etc.

Case Based Reasoning Technology for Medical Diagnosis

Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.

Surface Roughness Optimization in End Milling Operation with Damper Inserted End Milling Cutters

This paper presents a study of the Taguchi design application to optimize surface quality in damper inserted end milling operation. Maintaining good surface quality usually involves additional manufacturing cost or loss of productivity. The Taguchi design is an efficient and effective experimental method in which a response variable can be optimized, given various factors, using fewer resources than a factorial design. This Study included spindle speed, feed rate, and depth of cut as control factors, usage of different tools in the same specification, which introduced tool condition and dimensional variability. An orthogonal array of L9(3^4)was used; ANOVA analyses were carried out to identify the significant factors affecting surface roughness, and the optimal cutting combination was determined by seeking the best surface roughness (response) and signal-to-noise ratio. Finally, confirmation tests verified that the Taguchi design was successful in optimizing milling parameters for surface roughness.

Authentication Analysis of the 802.11i Protocol

IEEE has designed 802.11i protocol to address the security issues in wireless local area networks. Formal analysis is important to ensure that the protocols work properly without having to resort to tedious testing and debugging which can only show the presence of errors, never their absence. In this paper, we present the formal verification of an abstract protocol model of 802.11i. We translate the 802.11i protocol into the Strand Space Model and then prove the authentication property of the resulting model using the Strand Space formalism. The intruder in our model is imbued with powerful capabilities and repercussions to possible attacks are evaluated. Our analysis proves that the authentication of 802.11i is not compromised in the presented model. We further demonstrate how changes in our model will yield a successful man-in-the-middle attack.

Surfactant Stabilized Nanoemulsion: Characterization and Application in Enhanced Oil Recovery

Nanoemulsions are a class of emulsions with a droplet size in the range of 50–500 nm and have attracted a great deal of attention in recent years because it is unique characteristics. The physicochemical properties of nanoemulsion suggests that it can be successfully used to recover the residual oil which is trapped in the fine pore of reservoir rock by capillary forces after primary and secondary recovery. Oil-in-water nanoemulsion which can be formed by high-energy emulsification techniques using specific surfactants can reduce oil-water interfacial tension (IFT) by 3-4 orders of magnitude. The present work is aimed on characterization of oil-inwater nanoemulsion in terms of its phase behavior, morphological studies; interfacial energy; ability to reduce the interfacial tension and understanding the mechanisms of mobilization and displacement of entrapped oil blobs by lowering interfacial tension both at the macroscopic and microscopic level. In order to investigate the efficiency of oil-water nanoemulsion in enhanced oil recovery (EOR), experiments were performed to characterize the emulsion in terms of their physicochemical properties and size distribution of the dispersed oil droplet in water phase. Synthetic mineral oil and a series of surfactants were used to prepare oil-in-water emulsions. Characterization of emulsion shows that it follows pseudo-plastic behaviour and drop size of dispersed oil phase follows lognormal distribution. Flooding experiments were also carried out in a sandpack system to evaluate the effectiveness of the nanoemulsion as displacing fluid for enhanced oil recovery. Substantial additional recoveries (more than 25% of original oil in place) over conventional water flooding were obtained in the present investigation.

The Semantic Web: a New Approach for Future World Wide Web

The purpose of semantic web research is to transform the Web from a linked document repository into a distributed knowledge base and application platform, thus allowing the vast range of available information and services to be more efficiently exploited. As a first step in this transformation, languages such as OWL have been developed. Although fully realizing the Semantic Web still seems some way off, OWL has already been very successful and has rapidly become a defacto standard for ontology development in fields as diverse as geography, geology, astronomy, agriculture, defence and the life sciences. The aim of this paper is to classify key concepts of Semantic Web as well as introducing a new practical approach which uses these concepts to outperform Word Wide Web.

Ferroelectric Relaxor Behaviour in Some Lead- Free Compositions and their Potential Applications as Photocatalyst to Hydrogen Production

New lead-free ferroelectric relaxor ceramics were prepared by conventional solid-state synthesis in the BaTiO3-Bi2O3- Y2O3 systems. Some of these ceramics present a ferroelectric relaxor with transition temperature close to room temperature. These new materials are very interesting for applications and can replace leadbased ceramic to prevent the toxic pollutions during the preparation state. In the other hand, the energy band diagram shows the potentiality of these compounds for the solar energy conversion. Thus, some compositions have been tested successfully for H2 production upon visible light. The best activity occurs in alkaline media with a rate evolution of about 0.15 mL g-1 mn-1 and a quantum yield of 1% under polychromatic light.

A Critical Review of the Adequacy of EIA Reports-Evidence from Pakistan

The preparation of good-quality Environmental Impact Assessment (EIA) reports contribute to enhancing overall effectiveness of EIA. This component of the EIA process becomes more important in situation where public participation is weak and there is lack of expertise on the part of the competent authority. In Pakistan, EIA became mandatory for every project likely to cause adverse environmental impacts from July 1994. The competent authority also formulated guidelines for preparation and review of EIA reports in 1997. However, EIA is yet to prove as a successful decision support tool to help in environmental protection. One of the several reasons of this ineffectiveness is the generally poor quality of EIA reports. This paper critically reviews EIA reports of some randomly selected projects. Interviews of EIA consultants, project proponents and concerned government officials have also been conducted to underpin the root causes of poor quality of EIA reports. The analysis reveals several inadequacies particularly in areas relating to identification, evaluation and mitigation of key impacts and consideration of alternatives. The paper identifies some opportunities and suggests measures for improving the quality of EIA reports and hence making EIA an effective tool to help in environmental protection.