An Exploration on Competency-Based Curricula in Integrated Circuit Design

In this paper the relationships between professional competences and school curriculain IC design industry are explored. The semi-structured questionnaire survey and focus group interview is the research method. Study participants are graduates of microelectronics engineering professional departments who are currently employed in the IC industry. The IC industries are defined as the electronic component manufacturing industry and optical-electronic component manufacturing industry in the semiconductor industry and optical-electronic material devices, respectively. Study participants selected from IC design industry include IC engineering and electronic & semiconductor engineering. The human training with IC design professional competence in microelectronics engineering professional departments is explored in this research. IC professional competences of human resources in the IC design industry include general intelligence and professional intelligence.

The Link between Money Market and Economic Growth in Nigeria: Vector Error Correction Model Approach

The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Simulation of Polymeric Precursors Production from Wine Industrial Organic Wastes

The production of Dimethyl acetal, Isovaleradehyde and Pyridine were simulated using Aspen Plus simulation. Upgrading cleaning water from wine industrial production is the main objective of the project. The winery waste composes of Acetaldehyde, Methanol, Ethyl Acetate, 1-propanol, water, iso-amyl alcohol and iso-butyl alcohol. The project is separated into three parts; separation, reaction, and purification. Various processes were considered to maximize the profit along with obtaining high purity and recovery of each component with optimum heat duty. The results show a significant value of the product with purity more than 75% and recovery over 98%.

A Relationship between Expectation (Before) and Satisfaction (After) Receiving Services of Thai Consumers from Domestic Low-Cost Airlines

This study employs sampling of 400 Thai people who live in Bangkok and have used air transportation to travel. A random convenience sampling technique is used to collect data. The results found that at 0.05 significance level the differences of means of Thai consumers’ expectations (before) and satisfaction (after) receiving services in the service marketing mix, the results of all aspects are different both in general and for each aspect of the service marketing mix. Average levels of expectations before receiving services are higher than satisfaction after receiving services in all aspects, as well. When analyzing further to the correlation between average means, the means of expectations before receiving services are higher than those of satisfaction after receiving services in general. As in all aspects of the service marketing mix, any aspect that has a big difference between expectations before receiving services and satisfaction after receiving services has low correlation.

Can EEG Test Helps in Identifying Brain Tumor?

Brain tumor is inherently serious and life-threatening disease. Brain tumor builds the intracranial pressure in the brain, by shifting the brain or pushing against the skull, and also damaging nerves and healthy brain tissues. This intracranial pressure affects and interferes with normal brain functionality, which results in generation of abnormal electrical activities from brain. With recent development in the medical engineering and instruments, EEG instruments are able to record the brain electric activities with high accuracy, which establishes EEG as a primary tool for diagnosing the brain abnormalities. Research scholars and general physicians, often face difficulty in understanding EEG patterns. This paper presents the EEG patterns associated with brain tumor by combing medicine theory and neurologist experience. Paper also explains the pros-cons of the EEG based brain tumor identification.

High Performance of Hollow Fiber Supported Liquid Membrane to Separate Silver Ions from Medicinal Wastewater

The separation of silver ions from medicinal wastewater via hollow fiber supported liquid membrane (HFSLM) was examined to promote the performance of this technique. The wastewater consisting of 30mg/L silver ions and 120mg/L ferric ions was used as the feed solution. LIX84I dissolving in kerosene and sodium thiosulfate pentahydrate solution were used as the liquid membrane and stripping solution, respectively. In order to access the highest performance of HFSLM, the optimum condition was investigated via several influential variables. Final concentration of silver ions in feed solution was obtained 0.2mg/L which was lower than the discharge limit of Thailand’s mandatory.

Effect of pH and Ionic Exchange on the Reactivity of Bioglass/Chitosan Composites Used as a Bone Graft Substitute

Chitosan (CH) material reinforced by bioactive glass (46S6) was fabricated. 46S6 containing 17% wt% CH was studied in vitro and in vivo. Physicochemical techniques, such as Fourier transform infrared spectroscopy (FT-IR), coupled plasma optical emission spectrometry (ICP-OES) analysis were used. The behavior of 46S6CH17 was studied by measuring the in situ pH in a SBF solution. The 46S6CH17 was implanted in the rat femoral condyl. In vitro 46S6CH17 gave an FTIR - spectrum in which three absorption bands with the maxima at 565, 603 and 1039cm-1 after 3 days of soaking in physiological solution. They are assigned to stretching vibrations of PO4^3- group in phosphate crystalline. Moreover, the pH measurement was decreased in the SBF solution. The stability of the calcium phosphate precipitation depended on the pH value. In vivo, a rise in the Ca and phosphate P ions concentrations in the implanted microenvironment was determined.

Amplitude and Phase Analysis of EEG Signal by Complex Demodulation

Analysis of amplitude and phase characteristics for delta, theta, and alpha bands at localized time instant from EEG signals is important for the characterizing information processing in the brain. In this paper, complex demodulation method was used to analyze EEG (Electroencephalographic) signal, particularly for auditory evoked potential response signal, with sufficient time resolution and designated frequency bandwidth resolution required. The complex demodulation decomposes raw EEG signal into 3 designated delta, theta, and alpha bands with complex EEG signal representation at sampled time instant, which can enable the extraction of amplitude envelope and phase information. Throughout simulated test data, and real EEG signal acquired during auditory attention task, it can extract the phase offset, phase and frequency changing instant and decomposed amplitude envelope for delta, theta, and alpha bands. The complex demodulation technique can be efficiently used in brain signal analysis in case of phase, and amplitude information required.

Reliability Improvement with Optimal Placement of Distributed Generation in Distribution System

This paper presents the optimal placement and sizing of distributed generation (DG) in a distribution system. The problem is to reliability improvement of distribution system with distributed generations. The technique employed to solve the minimization problem is based on a developed Tabu search algorithm and reliability worth analysis. The developed methodology is tested with a distribution system of Roy Billinton Test System (RBTS) bus 2. It can be seen from the case study that distributed generation can reduce the customer interruption cost and therefore improve the reliability of the system. It is expected that our proposed method will be utilized effectively for distribution system operator.

Particle Swarm Optimization with Interval-valued Genotypes and Its Application to Neuroevolution

The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.

Comparison of Two Interval Models for Interval-Valued Differential Evolution

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Transmission Expansion Planning with Economic Dispatch and N-1Constraints

This paper proposes a mathematical model for transmission expansion employing optimization method with scenario analysis approach. Economic transmission planning, on the other hand, seeks investment opportunities so that network expansions can generate more economic benefits than the costs. This approach can be used as a decision model for building new transmission lines added to the existing transmission system minimizing costs of the entire system subject to various system’s constraints and consider of loss value of transmission system and N-1 checking. The results show that the proposed model is efficient to be applied for the larger scale of power system topology.

Real Time Acquisition and Psychoacoustic Analysis of Brain Wave

Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analyzing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuro headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.

Changes in EEG and HRV during Event-Related Attention

Determination of attentional status is important because working performance and an unexpected accident is highly related with the attention. The autonomic nervous and the central nervous systems can reflect the changes in person’s attentional status. Reduced number of suitable pysiological parameters among autonomic and central nervous systems related signal parameters will be critical in optimum design of attentional devices. In this paper, we analyze the EEG (Electroencephalography) and HRV (Heart Rate Variability) signals to demonstrate the effective relation with brain signal and cardiovascular signal during event-related attention, which will be later used in selecting the minimum set of attentional parameters. Time and frequency domain parameters from HRV signal and frequency domain parameters from EEG signal are used as input to the optimum feature parameters selector.

A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

CMOS-Compatible Deposited Materials for Photonic Layers Integrated above Electronic Integrated Circuit

Silicon photonics has generated an increasing interest in recent years mainly for optical communications optical interconnects in microelectronic circuits or bio-sensing applications. The development of elementary passive and active components (including detectors and modulators), which are mainly fabricated on the silicon on insulator platform for CMOS-compatible fabrication, has reached such a performance level that the integration challenge of silicon photonics with microelectronic circuits should be addressed. Since crystalline silicon can only be grown from another silicon crystal, making it impossible to deposit in this state, the optical devices are typically limited to a single layer. An alternative approach is to integrate a photonic layer above the CMOS chip using back-end CMOS fabrication process. In this paper, various materials, including silicon nitride, amorphous silicon, and polycrystalline silicon, for this purpose are addressed.

A Hybrid Classification Method using Artificial Neural Network Based Decision Tree for Automatic Sleep Scoring

In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Microencapsulation of Ascorbic Acid by Spray Drying: Influence of Process Conditions

Ascorbic acid (AA), commonly known as vitamin C, is essential for normal functioning of the body and maintenance of metabolic integrity. Among its various roles are as an antioxidant, a cofactor in collagen formation and other reactions, as well as reducing physical stress and maintenance of the immune system. Recent collaborative research between the Australian Defence Science and Technology Organisation (DSTO) in Scottsdale, Tasmania and RMIT University has sought to overcome the problems arising from the inherent instability of ascorbic acid during processing and storage of foods. The recent work has demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. The purpose of this current study has been focused upon the influence of spray drying conditions on the properties of encapsulated ascorbic acid. The process was carried out according to a central composite design. Independent variables were: inlet temperature (80-120° C) and feed flow rate (7-14 mL/minute). Process yield, ascorbic acid loss, moisture content, water activity and particle size distribution were analysed as responses. The results have demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. Vitamin retention, moisture content, water activity and process yield were influenced positively by inlet air temperature and negatively by feed flow rate.

Contribution to the Study of Thermal Conductivity of Porous Silicon Used In Thermal Sensors

The porous silicon (PS), formed from the anodization of a p+ type substrate silicon, consists of a network organized in a pseudo-column as structure of multiple side ramifications. Structural micro-topology can be interpreted as the fraction of the interconnected solid phase contributing to thermal transport. The reduction of dimensions of silicon of each nanocristallite during the oxidation induced a reduction in thermal conductivity. Integration of thermal sensors in the Microsystems silicon requires an effective insulation of the sensor element. Indeed, the low thermal conductivity of PS consists in a very promising way in the fabrication of integrated thermal Microsystems.In this work we are interesting in the measurements of thermal conductivity (on the surface and in depth) of PS by the micro-Raman spectroscopy. The thermal conductivity is studied according to the parameters of anodization (initial doping and current density. We also, determine porosity of samples by spectroellipsometry.

Audio Watermarking Using Spectral Modifications

In this paper, we present a non-blind technique of adding the watermark to the Fourier spectral components of audio signal in a way such that the modified amplitude does not exceed the maximum amplitude spread (MAS). This MAS is due to individual Discrete fourier transform (DFT) coefficients in that particular frame, which is derived from the Energy Spreading function given by Schroeder. Using this technique one can store double the information within a given frame length i.e. overriding the watermark on the host of equal length with least perceptual distortion. The watermark is uniformly floating on the DFT components of original signal. This helps in detecting any intentional manipulations done on the watermarked audio. Also, the scheme is found robust to various signal processing attacks like presence of multiple watermarks, Additive white gaussian noise (AWGN) and mp3 compression.