Finite Volume Model to Study the Effect of Buffer on Cytosolic Ca2+ Advection Diffusion

Calcium [Ca2+] is an important second messenger which plays an important role in signal transduction. There are several parameters that affect its concentration profile like buffer source etc. The effect of stationary immobile buffer on Ca2+ concentration has been incorporated which is a very important parameter needed to be taken into account in order to make the model more realistic. Interdependence of all the important parameters like diffusion coefficient and influx over [Ca2+] profile has been studied. Model is developed in the form of advection diffusion equation together with buffer concentration. A program has been developed using finite volume method for the entire problem and simulated on an AMD-Turion 32-bit machine to compute the numerical results.

Investigating Determinants of Medical User Expectations from Hospital Information System

User satisfaction is one of the most used success indicators in the research of information system (IS). Literature shows user expectations have great influence on user satisfaction. Both expectation and satisfaction of users are important for Hospital Information Systems (HIS). Education, IS experience, age, attitude towards change, business title, sex and working unit of the hospital, are examined as the potential determinant of the medical users’ expectations. Data about medical user expectations are collected by the “Expectation Questionnaire” developed for this study. Expectation data are used for calculating the Expectation Meeting Ratio (EMR) with the evaluation framework also developed for this study. The internal consistencies of the answers to the questionnaire are measured by Cronbach´s Alpha coefficient. The multivariate analysis of medical user’s EMRs of HIS is performed by forward stepwise binary logistic regression analysis. Education and business title is appeared to be the determinants of expectations from HIS.

Characterizations of Ordered Semigroups by (∈,∈ ∨q)-Fuzzy Ideals

Let S be an ordered semigroup. In this paper we first introduce the concepts of (∈,∈ ∨q)-fuzzy ideals, (∈,∈ ∨q)-fuzzy bi-ideals and (∈,∈ ∨q)-fuzzy generalized bi-ideals of an ordered semigroup S, and investigate their related properties. Furthermore, we also define the upper and lower parts of fuzzy subsets of an ordered semigroup S, and investigate the properties of (∈,∈ ∨q)-fuzzy ideals of S. Finally, characterizations of regular ordered semigroups and intra-regular ordered semigroups by means of the lower part of (∈ ,∈ ∨q)-fuzzy left ideals, (∈,∈ ∨q)-fuzzy right ideals and (∈,∈ ∨q)- fuzzy (generalized) bi-ideals are given.

Estimating Saturated Hydraulic Conductivity from Soil Physical Properties using Neural Networks Model

Saturated hydraulic conductivity is one of the soil hydraulic properties which is widely used in environmental studies especially subsurface ground water. Since, its direct measurement is time consuming and therefore costly, indirect methods such as pedotransfer functions have been developed based on multiple linear regression equations and neural networks model in order to estimate saturated hydraulic conductivity from readily available soil properties e.g. sand, silt, and clay contents, bulk density, and organic matter. The objective of this study was to develop neural networks (NNs) model to estimate saturated hydraulic conductivity from available parameters such as sand and clay contents, bulk density, van Genuchten retention model parameters (i.e. r θ , α , and n) as well as effective porosity. We used two methods to calculate effective porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s θ is saturated water content, FC θ is water content retained at -33 kPa matric potential, and inf θ is water content at the inflection point. Total of 311 soil samples from the UNSODA database was divided into three groups as 187 for the training, 62 for the validation (to avoid over training), and 62 for the test of NNs model. A commercial neural network toolbox of MATLAB software with a multi-layer perceptron model and back propagation algorithm were used for the training procedure. The statistical parameters such as correlation coefficient (R2), and mean square error (MSE) were also used to evaluate the developed NNs model. The best number of neurons in the middle layer of NNs model for methods (1) and (2) were calculated 44 and 6, respectively. The R2 and MSE values of the test phase were determined for method (1), 0.94 and 0.0016, and for method (2), 0.98 and 0.00065, respectively, which shows that method (2) estimates saturated hydraulic conductivity better than method (1).

An Efficient Algorithm for Delay Delay-variation Bounded Least Cost Multicast Routing

Many multimedia communication applications require a source to transmit messages to multiple destinations subject to quality of service (QoS) delay constraint. To support delay constrained multicast communications, computer networks need to guarantee an upper bound end-to-end delay from the source node to each of the destination nodes. This is known as multicast delay problem. On the other hand, if the same message fails to arrive at each destination node at the same time, there may arise inconsistency and unfairness problem among users. This is related to multicast delayvariation problem. The problem to find a minimum cost multicast tree with delay and delay-variation constraints has been proven to be NP-Complete. In this paper, we propose an efficient heuristic algorithm, namely, Economic Delay and Delay-Variation Bounded Multicast (EDVBM) algorithm, based on a novel heuristic function, to construct an economic delay and delay-variation bounded multicast tree. A noteworthy feature of this algorithm is that it has very high probability of finding the optimal solution in polynomial time with low computational complexity.

A Study of Visual Attention in Diagnosing Cerebellar Tumours

Visual attention allows user to select the most relevant information to ongoing behaviour. This paper presents a study on; i) the performance of people measurements, ii) accurateness of people measurement of the peaks that correspond to chemical quantities from the Magnetic Resonance Spectroscopy (MRS) graphs and iii) affects of people measurements to the algorithm-based diagnosis. Participant-s eye-movement was recorded using eye-tracker tool (Eyelink II). This experiment involves three participants for examining 20 MRS graphs to estimate the peaks of chemical quantities which indicate the abnormalities associated with Cerebellar Tumours (CT). The status of each MRS is verified by using decision algorithm. Analysis involves determination of humans-s eye movement pattern in measuring the peak of spectrograms, scan path and determining the relationship of distributions of fixation durations with the accuracy of measurement. In particular, the eye-tracking data revealed which aspects of the spectrogram received more visual attention and in what order they were viewed. This preliminary investigation provides a proof of concept for use of the eye tracking technology as the basis for expanded CT diagnosis.

Magnesium Waste Evaluation in Moderate Temperature (70oC) Magnesium Borate Synthesis

Waste problem is becoming a future problem all over the world. Magnesium wastes which can be used in recycling processes are produced by many industrial activities. Magnesium borates which have useful properties such as; high heat resistance, corrosion resistance, supermechanical strength, superinsulation, light weight, high coefficient of elasticity and so on. Addition, magnesium borates have great potential in the development of ceramic and detergents industry, whisker-reinforced composites, antiwear, and reducing friction additives. In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC with different reaction times. Several reaction times of waste magnesium to H3BO3 were selected as; 30, 60, 120, 240 minutes. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques were applied to products. As a result, the forms of Admontite [MgO(B2O3)3.7(H2O)] and Mcallisterite [Mg2(B6O7(OH)6)2.9(H2O)] were synthesized.

Strategy for Optimal Configuration Design of Existing Structures by Topology and Shape Optimization Tools

A strategy is implemented to find the improved configuration design of an existing aircraft structure by executing topology and shape optimizations. Structural analysis of the Initial Design Space is performed in ANSYS under the loads pertinent to operating and ground conditions. By using the FEA results and data, an initial optimized layout configuration is attained by exploiting nonparametric topology optimization in TOSCA software. Topological optimized surfaces are then smoothened and imported in ANSYS to develop the geometrical features. Nodes at the critical locations of resulting voids are selected for sketching rough profiles. Rough profiles are further refined and CAD feasible geometric features are generated. The modified model is then analyzed under the same loadings and constraints as defined for topology optimization. Shape at the peak stress concentration areas are further optimized by exploiting the shape optimization in TOSCA.shape module. The harmonized stressed model with the modified surfaces is then imported in CATIA to develop the final design.

A Lossless Watermarking Based Authentication System For Medical Images

In this paper we investigate the watermarking authentication when applied to medical imagery field. We first give an overview of watermarking technology by paying attention to fragile watermarking since it is the usual scheme for authentication.We then analyze the requirements for image authentication and integrity in medical imagery, and we show finally that invertible schemes are the best suited for this particular field. A well known authentication method is studied. This technique is then adapted here for interleaving patient information and message authentication code with medical images in a reversible manner, that is using lossless compression. The resulting scheme enables on a side the exact recovery of the original image that can be unambiguously authenticated, and on the other side, the patient information to be saved or transmitted in a confidential way. To ensure greater security the patient information is encrypted before being embedded into images.

A Novel Implementation of Application Specific Instruction-set Processor (ASIP) using Verilog

The general purpose processors that are used in embedded systems must support constraints like execution time, power consumption, code size and so on. On the other hand an Application Specific Instruction-set Processor (ASIP) has advantages in terms of power consumption, performance and flexibility. In this paper, a 16-bit Application Specific Instruction-set processor for the sensor data transfer is proposed. The designed processor architecture consists of on-chip transmitter and receiver modules along with the processing and controlling units to enable the data transmission and reception on a single die. The data transfer is accomplished with less number of instructions as compared with the general purpose processor. The ASIP core operates at a maximum clock frequency of 1.132GHz with a delay of 0.883ns and consumes 569.63mW power at an operating voltage of 1.2V. The ASIP is implemented in Verilog HDL using the Xilinx platform on Virtex4.

Processing, Morphological, Thermal and Absorption Behavior of PLA/Thermoplastic Starch/Montmorillonite Nanocomposites

Thermoplastic starch, polylactic acid glycerol and maleic anhydride (MA) were compounded with natural montmorillonite (MMT) through a twin screw extruder to investigate the effects of different loading of MMT on structure, thermal and absorption behavior of the nanocomposites. X-ray diffraction analysis (XRD) showed that sample with MMT loading 4phr exhibited exfoliated structure while sample that contained MMT 8 phr exhibited intercalated structure. FESEM images showed big lump when MMT loading was at 8 phr. The thermal properties were characterized by using differential scanning calorimeter (DSC). The results showed that MMT increased melting temperature and crystallization temperature of matrix but reduction in glass transition temperature was observed Meanwhile the addition of MMT has improved the water barrier property. The nanosize MMT particle is also able to block a tortuous pathway for water to enter the starch chain, thus reducing the water uptake and improved the physical barrier of nanocomposite.

Rethinking the Analysis of Means-End Chain Data in Marketing Research

This paper proposes a new procedure for analyzing means-end chain data in marketing research. Most commonly the collected data is summarized in the Hierarchical Value Map (HVM) illustrating the main attribute-consequence-value linkages. This paper argues that traditionally constructed HVM may give an erroneous impression of the results of a means-end study. To justify the arguments, an alternative procedure to (1) determine the dominant attribute-consequence-value linkages and (2) construct HVM in a precise manner is presented. The current approach makes a contribution to means-end analysis, allowing marketers to address a set of marketing problems, such as advertising strategy.

Sustainability of Urban Cemeteries and the Transformation of Malay Burial Practices in Kuala Lumpur Metropolitan Region

Land shortage for burials is one of many issues that emerge out of accelerated urban growth in most developing Asian cities, including Kuala Lumpur. Despite actions taken by the federal government and local authorities in addressing this issue, there is no strategic solution being formulated. Apart from making provisions for land to be developed as new cemeteries, the future plan is merely to allocate reserve land to accommodate the increasing demands of burial grounds around the city. This paper examines problems that arise from the traditional practices of Malay funerary as well as an insight to current urban practices in managing Muslim burial spaces around Kuala Lumpur metropolitan region. This paper will also provide some solutions through design approach that can be applied to counter the existing issues.

Parameter Selections of Fuzzy C-Means Based on Robust Analysis

The weighting exponent m is called the fuzzifier that can have influence on the clustering performance of fuzzy c-means (FCM) and mÎ[1.5,2.5] is suggested by Pal and Bezdek [13]. In this paper, we will discuss the robust properties of FCM and show that the parameter m will have influence on the robustness of FCM. According to our analysis, we find that a large m value will make FCM more robust to noise and outliers. However, if m is larger than the theoretical upper bound proposed by Yu et al. [14], the sample mean will become the unique optimizer. Here, we suggest to implement the FCM algorithm with mÎ[1.5,4] under the restriction when m is smaller than the theoretical upper bound.

Instruction Resource Recommendation Services for Elementary Schools in Taiwan

In the past, there were more researches of recommendation system in applied electronic commerce. However, because all circles promote information technology integrative instruction actively, the quantity of instruction resources website is more and more increasing on the Internet. But there are less website including recommendation service, especially for teachers. This study established an instruction resource recommendation website that analyzed teaching style of teachers, then provided appropriate instruction resources for teachers immediately. We used the questionnaire survey to realize teacher-s suggestions and satisfactions with the instruction resource contents and recommendation results. The study shows: (1)The website used “Transactional Ability Inventory" that realized teacher-s style and provided appropriate instruction resources for teachers in a short time, it reduced the step of data filter. (2)According to the content satisfaction of questionnaire survey, four styles teachers were almost satisfied with the contents of the instruction resources that the website recommended, thus, the conception of developing instruction resources with different teaching style is accepted. (3) According to the recommendation satisfaction of questionnaire survey, four styles teachers were almost satisfied with the recommendation service of the website, thus, the recommendation strategy that provide different results for teachers in different teaching styles is accepted.

Design of Encoding Calculator Software for Huffman and Shannon-Fano Algorithms

This paper presents a design of source encoding calculator software which applies the two famous algorithms in the field of information theory- the Shannon-Fano and the Huffman schemes. This design helps to easily realize the algorithms without going into a cumbersome, tedious and prone to error manual mechanism of encoding the signals during the transmission. The work describes the design of the software, how it works, comparison with related works, its efficiency, its usefulness in the field of information technology studies and the future prospects of the software to engineers, students, technicians and alike. The designed “Encodia" software has been developed, tested and found to meet the intended requirements. It is expected that this application will help students and teaching staff in their daily doing of information theory related tasks. The process is ongoing to modify this tool so that it can also be more intensely useful in research activities on source coding.

Image Enhancement of Medical Images using Gabor Filter Bank on Hexagonal Sampled Grids

For about two decades scientists have been developing techniques for enhancing the quality of medical images using Fourier transform, DWT (Discrete wavelet transform),PDE model etc., Gabor wavelet on hexagonal sampled grid of the images is proposed in this work. This method has optimal approximation theoretic performances, for a good quality image. The computational cost is considerably low when compared to similar processing in the rectangular domain. As X-ray images contain light scattered pixels, instead of unique sigma, the parameter sigma of 0.5 to 3 is found to satisfy most of the image interpolation requirements in terms of high Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error (MSE) and better image quality by adopting windowing technique.

A Self Supervised Bi-directional Neural Network (BDSONN) Architecture for Object Extraction Guided by Beta Activation Function and Adaptive Fuzzy Context Sensitive Thresholding

A multilayer self organizing neural neural network (MLSONN) architecture for binary object extraction, guided by a beta activation function and characterized by backpropagation of errors estimated from the linear indices of fuzziness of the network output states, is discussed. Since the MLSONN architecture is designed to operate in a single point fixed/uniform thresholding scenario, it does not take into cognizance the heterogeneity of image information in the extraction process. The performance of the MLSONN architecture with representative values of the threshold parameters of the beta activation function employed is also studied. A three layer bidirectional self organizing neural network (BDSONN) architecture comprising fully connected neurons, for the extraction of objects from a noisy background and capable of incorporating the underlying image context heterogeneity through variable and adaptive thresholding, is proposed in this article. The input layer of the network architecture represents the fuzzy membership information of the image scene to be extracted. The second layer (the intermediate layer) and the final layer (the output layer) of the network architecture deal with the self supervised object extraction task by bi-directional propagation of the network states. Each layer except the output layer is connected to the next layer following a neighborhood based topology. The output layer neurons are in turn, connected to the intermediate layer following similar topology, thus forming a counter-propagating architecture with the intermediate layer. The novelty of the proposed architecture is that the assignment/updating of the inter-layer connection weights are done using the relative fuzzy membership values at the constituent neurons in the different network layers. Another interesting feature of the network lies in the fact that the processing capabilities of the intermediate and the output layer neurons are guided by a beta activation function, which uses image context sensitive adaptive thresholding arising out of the fuzzy cardinality estimates of the different network neighborhood fuzzy subsets, rather than resorting to fixed and single point thresholding. An application of the proposed architecture for object extraction is demonstrated using a synthetic and a real life image. The extraction efficiency of the proposed network architecture is evaluated by a proposed system transfer index characteristic of the network.

A Content Based Image Watermarking Scheme Resilient to Geometric Attacks

Multimedia security is an incredibly significant area of concern. The paper aims to discuss a robust image watermarking scheme, which can withstand geometric attacks. The source image is initially moment normalized in order to make it withstand geometric attacks. The moment normalized image is wavelet transformed. The first level wavelet transformed image is segmented into blocks if size 8x8. The product of mean and standard and standard deviation of each block is computed. The second level wavelet transformed image is divided into 8x8 blocks. The product of block mean and the standard deviation are computed. The difference between products in the two levels forms the watermark. The watermark is inserted by modulating the coefficients of the mid frequencies. The modulated image is inverse wavelet transformed and inverse moment normalized to generate the watermarked image. The watermarked image is now ready for transmission. The proposed scheme can be used to validate identification cards and financial instruments. The performance of this scheme has been evaluated using a set of parameters. Experimental results show the effectiveness of this scheme.

A Novel Plausible Deniability Scheme in Secure Steganography

The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message. If suspicion is raised, steganography may fail. The success of steganography depends on the secrecy of the action. If steganography is detected, the system will fail but data security depends on the robustness of the applied algorithm. In this paper, we propose a novel plausible deniability scheme in steganography by using a diversionary message and encrypt it with a DES-based algorithm. Then, we compress the secret message and encrypt it by the receiver-s public key along with the stego key and embed both messages in a carrier using an embedding algorithm. It will be demonstrated how this method can support plausible deniability and is robust against steganalysis.