Common Acceptable Cuisine in Multicultural Countries: Towards Building the National Food Identity

Common acceptable cuisine usually discussed in the multicultural/ethnic nation as it represents the process of sharing it among the ethnic groups. The common acceptable cuisine is also considered as a precursor in the process of constructing the national food identity within ethnic groups in the multicultural countries. The adaptation of certain ethnic cuisines through its types of food, methods of cooking, ingredients and eating decorum by ethnic groups is believed creating or enhancing the process of formation on common acceptable cuisines in a multicultural country. Malaysia as the multicultural country without doubt is continuing to experience cross-culturing processes among the ethnic groups including cuisine. This study empirically investigates the adaptation level of Malay, Chinese and Indian chefs on each other ethnic cuisine attributes toward the formation on common acceptable cuisines and national food identity.

A Signal Driven Adaptive Resolution Short-Time Fourier Transform

The frequency contents of the non-stationary signals vary with time. For proper characterization of such signals, a smart time-frequency representation is necessary. Classically, the STFT (short-time Fourier transform) is employed for this purpose. Its limitation is the fixed timefrequency resolution. To overcome this drawback an enhanced STFT version is devised. It is based on the signal driven sampling scheme, which is named as the cross-level sampling. It can adapt the sampling frequency and the window function (length plus shape) by following the input signal local variations. This adaptation results into the proposed technique appealing features, which are the adaptive time-frequency resolution and the computational efficiency.

Effect of VA-Mycorrhiza on Growth and Yield of Sunflower (Helianthus annuus L.) at Different Phosphorus Levels

The effect of seed inoculation by VA- mycorrhiza and different levels of phosphorus fertilizer on growth and yield of sunflower (Azargol cultivar) was studied in experiment farm of Islamic Azad University, Karaj Branch during 2008 growing season. The experiment treatments were arranged in factorial based on a complete randomized block design with three replications. Four phosphorus fertilizer levels of 25%, 50% 75% and 100% P recommended with two levels of Mycorrhiza: with and without Mycorrhiza (control) were assigned in a factorial combination. Results showed that head diameter, number of seeds in head, seed yield and oil yield were significantly higher in inoculated plants than in non-inoculated plants. Head diameter, number of seeds in head, 1000 seeds weight, biological yield, seed yield and oil yield increased with increasing P level above 75% P recommended in non-inoculated plants, whereas no significant difference was observed between 75% and 100% P recommended. The positive effect of mycorrhizal inoculation decreased with increasing P levels due to decreased percent root colonization at higher P levels. According to the results of this experiment, application of mycorrhiza in present of 50% P recommended had an appropriate performance and could increase seed yield and oil production to an acceptable level, so it could be considered as a suitable substitute for chemical phosphorus fertilizer in organic agricultural systems.

Microarrays Denoising via Smoothing of Coefficients in Wavelet Domain

We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on a smoothing of the coefficients of the highest subbands. Specifically, we decompose the noisy microarray into wavelet subbands, apply smoothing within each highest subband, and reconstruct a microarray from the modified wavelet coefficients. This process is applied a single time, and exclusively to the first level of decomposition, i.e., in most of the cases, it is not necessary a multirresoltuion analysis. Denoising results compare favorably to the most of methods in use at the moment.

Backplane Serial Signaling and Protocol for Telecom Systems

In this paper, we implement a modern serial backplane platform for telecommunication inter-rack systems. For combination high reliability and low cost protocol property, we applied high level data link control (HDLC) protocol with low voltage differential signaling (LVDS) bus for card to card communicated over backplane. HDLC protocol is a high performance with several operation modes and is famous in telecommunication systems. LVDS bus is a high reliability with high immunity against electromagnetic interference (EMI) and noise.

Dexamethasone: Impact on Testicular Activity

Dexamethasone (Dex) is a synthetic glucocorticoid that is used in therapy. However prolonged treatments with high doses are often required. This causes side effects that interfere with the activity of several endocrine systems, including the gonadotropic axis. The aim of our study is to determine the effect of Dex on testicular function in prepubertal Wistar rats. Newborn Wistar rats are submitted to intraperitoneal injection of Dex (1μg of Dex dissolved in NaCl 0.9% / 5g bw) for 20 days and then sacrificed at the age of 40days. A control group received NaCl 0.9%. The rat is weighed daily. The plasmatic levels of testosterone, LH and FSH were measured by radioimmunoassay. A histomorphometric study was performed on sections of testis. Treated groups showed a significant decrease in body weight (p

Automatic Sleep Stage Scoring with Wavelet Packets Based on Single EEG Recording

Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

A Study of RSCMAC Enhanced GPS Dynamic Positioning

The purpose of this research is to develop and apply the RSCMAC to enhance the dynamic accuracy of Global Positioning System (GPS). GPS devices provide services of accurate positioning, speed detection and highly precise time standard for over 98% area on the earth. The overall operation of Global Positioning System includes 24 GPS satellites in space; signal transmission that includes 2 frequency carrier waves (Link 1 and Link 2) and 2 sets random telegraphic codes (C/A code and P code), on-earth monitoring stations or client GPS receivers. Only 4 satellites utilization, the client position and its elevation can be detected rapidly. The more receivable satellites, the more accurate position can be decoded. Currently, the standard positioning accuracy of the simplified GPS receiver is greatly increased, but due to affected by the error of satellite clock, the troposphere delay and the ionosphere delay, current measurement accuracy is in the level of 5~15m. In increasing the dynamic GPS positioning accuracy, most researchers mainly use inertial navigation system (INS) and installation of other sensors or maps for the assistance. This research utilizes the RSCMAC advantages of fast learning, learning convergence assurance, solving capability of time-related dynamic system problems with the static positioning calibration structure to improve and increase the GPS dynamic accuracy. The increasing of GPS dynamic positioning accuracy can be achieved by using RSCMAC system with GPS receivers collecting dynamic error data for the error prediction and follows by using the predicted error to correct the GPS dynamic positioning data. The ultimate purpose of this research is to improve the dynamic positioning error of cheap GPS receivers and the economic benefits will be enhanced while the accuracy is increased.

Overviews of Rainwater Harvesting and Utilization in Thailand: Bangsaiy Municipality

In developing countries located in monsoon areas like Thailand where rainwater is currently of no value for urban dwellers due to easily access to piped water supply at each household, studies in rainwater harvesting for domestic use are of low interest. However it is needed to undertake research to find out appropriate rainwater harvesting systems particularly for small urban communities that are recently developed from a full rural structure to urban context. As a matter of fact, in such transitional period, relying on only common water resources is risky. With some specific economic settings, land use patterns, and historical and cultural context that dominate perceptions of water users in the study area, the level of service in this study may certainly be different from megacities or cities located in industrial zone. The overviews of some available technologies and background of rainwater harvesting including alternate resource are included in this paper. Among other sources of water supply, ground water use as the water resource of Thailand and also in the study area.

Measuring the Level of Housing Defects in the Build-Then-Sell Housing Delivery System

When the Malaysian government announced the implementation of the Build-Then-Sell (BTS) system in 2007, the proponents of the BTS have argued that the implementation of this new system may provide houses with low defects. However, there has been no empirical data to support their argument. Therefore, this study is conducted to measure the level of housing defects in the BTS housing delivery system. A survey was conducted to the occupiers in six BTS residential areas. The BTS residential areas have been identified through the media and because of the small number of population, all households in the BTS residential areas were required to participate in the study to enable the researcher to collect the data concerning defects. Questionnaire had been employed as the data collection instrument and was distributed to the respondents of this study. The result has shown that the level of defects in the BTS houses is low, as the rate of defects for all elements are slight. Such low level of defects has apparently only affected the aesthetic value of the houses.

Risk Assessment Results in Biogas Production from Agriculture Biomass

The use of renewable energy sources incl. biogas has become topical in accordance with the increasing demand for energy, decrease of fossil energy resources and the efforts to reduce greenhouse gas emissions as well as to increase energy independence from the territories where fossil energy resources are available. As the technologies of biogas production from agricultural biomass develop, risk assessment and risk management become necessary for farms producing such a renewable energy. The need for risk assessments has become particularly topical when discussions on changing the biogas policy in the EU take place, which may influence the development of the sector in the future, as well as the operation of existing biogas facilities and their income level. The current article describes results of the risk assessment for farms producing biomass from agriculture biomass in Latvia, the risk assessment system included 24 risks, that affect the whole biogas production process and the obtained results showed the high significance of political and production risks.

Voice Driven Applications in Non-stationary and Chaotic Environment

Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.

Effect of Dietary Supplementation of Different Levels of Black Seed (Nigella Sativa L.) on Growth Performance, Immunological, Hematological and Carcass Parameters of Broiler Chicks

This experiment was conducted to investigate the effect of dietary supplementation of different levels of black seed (Nigella sativa L.) on the performance and immune response of broiler chicks. A total 240 day-old broiler chicks were used and randomly allotted equally into six experimental groups designated as 1, 2, 3, 4, 5 and 6 having black seed at the rate of 0, 2, 4, 6, 8 and 10 g /kg diet respectively. The study was lasted for 42 days. Average body weight, weight gain, relative growth rate, feed conversion, antibody titer against Newcastle disease, phagocytic activity and phagocytic index, some blood parameters(GOT, GPT, Glucose, Cholesterol, Triglyceride, Total protein, Albumen, WBCs, RBCs, Hb and PCV), dressing percentage, weight of different body organs, abdominal fat weight, were determined. It was found that, N. Sativa significantly improved final body weight, total body gain and feed conversion ratio of groups 2 and 3 when compared with the control group. Higher levels of N. Sativa did not improve growth performance of the chicks. Non significant differences were observed for antibody titer against Newcastle virus, WBCs count, serum GOT, glucose level, dressing %, relative liver, spleen, heart and head percentages. Lymphoid organs (Bursa and Thymus) improved significantly with increasing N. Sativa level in all supplemented groups. Serum cholesterol, triglyceride and visible fat % significantly decreased with Nigella sativa supplementation while serum GPT level significantly increased with nigella sativa supplementation.

Multirate Neural Control for AUV's Increased Situational Awareness during Diving Tasks Using Stochastic Model

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory for a nontrivial mid-small size AUV “r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of noises, and also can be concluded that the proposed research technique will be useful for fast SA of similar AUV systems in real-time search-and-rescue operations.

Discovery and Capture of Organizational Knowledge from Unstructured Information

Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Measurement of UHF Signal Strength Propagating from Road Surface with Vehicle Obstruction

Radio wave propagation on the road surface is a major problem on wireless sensor network for traffic monitoring. In this paper, we compare receiving signal strength on two scenarios 1) an empty road and 2) a road with a vehicle. We investigate the effect of antenna polarization and antenna height to the receiving signal strength. The transmitting antenna is installed on the road surface. The receiving signal is measured 360 degrees around the transmitting antenna with the radius of 2.5 meters. Measurement results show the receiving signal fluctuation around the transmitting antenna in both scenarios. Receiving signal with vertical polarization antenna results in higher signal strength than horizontal polarization antenna. The optimum antenna elevation is 1 meter for both horizon and vertical polarizations with the vehicle on the road. In the empty road, the receiving signal level is unvarying with the elevation when the elevation is greater than 1.5 meters.

Detecting and Tracking Vehicles in Airborne Videos

In this work, we present an automatic vehicle detection system for airborne videos using combined features. We propose a pixel-wise classification method for vehicle detection using Dynamic Bayesian Networks. In spite of performing pixel-wise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. The main novelty of the detection scheme is that the extracted combined features comprise not only pixel-level information but also region-level information. Afterwards, tracking is performed on the detected vehicles. Tracking is performed using efficient Kalman filter with dynamic particle sampling. Experiments were conducted on a wide variety of airborne videos. We do not assume prior information of camera heights, orientation, and target object sizes in the proposed framework. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging dataset.

University Students Awareness on M-Learning

Mobile learning (M-learning) is the current technology that is becoming more popular. It uses the current mobile and wireless computing technology to complement the effectiveness of traditional learning process. The objective of this paper is presents a survey from 90 undergraduate students of Universiti Teknologi PETRONAS (UTP), to identify the students- perception on Mlearning. From the results, the students are willing to use M-learning. The acceptance level of the students is high, and the results obtained revealed that the respondents almost accept M-learning as one method of teaching and learning process and also able to improve the educational efficiency by complementing traditional learning in UTP.

A Learner-Centred or Artefact-Centred Classroom? Impact of Technology, Artefacts, and Environment on Task Processes in an English as a Foreign Language Classroom

This preliminary study attempts to see if a learning environment influences instructor’s teaching strategies and learners’ in-class activities in a foreign language class at a university in Japan. The class under study was conducted in a computer room, while the majority of classes of the same course were offered in traditional classrooms without computers. The study also sees if the unplanned blended learning environment, enhanced, or worked against, in achieving course goals, by paying close attention to in-class artefacts, such as computers. In the macro-level analysis, the course syllabus and weekly itinerary of the course were looked at; and in the microlevel analysis, nonhuman actors in their environments were named and analyzed to see how they influenced the learners’ task processes. The result indicated that students were heavily influenced by the presence of computers, which lead them to disregard some aspects of intended learning objectives.

Adaptive Rfid Positioning System Using Signal Level Matrix

In this paper, we present a method named Signal Level Matrix (SLM) which can improve the accuracy and stability of active RFID indoor positioning system. Considering the accuracy and cost, we use uniform distribution mode to set up and separate the overlapped signal covering areas, in order to achieve preliminary location setting. Then, based on the proposed SLM concept and the characteristic of the signal strength value that attenuates as the distance increases, this system cross-examines the distribution of adjacent signals to locate the users more accurately. The experimental results indicate that the adaptive positioning method proposed in this paper could improve the accuracy and stability of the positioning system effectively and satisfyingly.