Understanding and Designing Situation-Aware Mobile and Ubiquitous Computing Systems

Using spatial models as a shared common basis of information about the environment for different kinds of contextaware systems has been a heavily researched topic in the last years. Thereby the research focused on how to create, to update, and to merge spatial models so as to enable highly dynamic, consistent and coherent spatial models at large scale. In this paper however, we want to concentrate on how context-aware applications could use this information so as to adapt their behavior according to the situation they are in. The main idea is to provide the spatial model infrastructure with a situation recognition component based on generic situation templates. A situation template is – as part of a much larger situation template library – an abstract, machinereadable description of a certain basic situation type, which could be used by different applications to evaluate their situation. In this paper, different theoretical and practical issues – technical, ethical and philosophical ones – are discussed important for understanding and developing situation dependent systems based on situation templates. A basic system design is presented which allows for the reasoning with uncertain data using an improved version of a learning algorithm for the automatic adaption of situation templates. Finally, for supporting the development of adaptive applications, we present a new situation-aware adaptation concept based on workflows.

Photogrammetry and GIS Integration for Archaeological Documentation of Ahl-Alkahf, Jordan

Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.

Maydis stigma Improves Physical Traits and Unchanged Sensory Properties of Beef and Chicken Patties

The proximate composition, physical traits and sensory properties of beef and chicken patties incorporated with various level of dried cornsilk (Maydis stigma) were studied. The beef and chicken patties were formulated with either 2%, 4% or 6% of cornsilk. Both cooked beef and chicken patties incorporated with 6% cornsilk recorded the highest protein concentration at 23.3% and 28.42%, respectively. Both cooked beef and chicken patties containing 6% cornsilk significantly recorded the lowest concentration of fat at 11.4% and 14.60%, respectively. Beef and chicken patties formulated with 6% cornsilk recorded the highest cooking yield at 80.13% and 83.03% compared to other treatments. The inclusion of cornsilk did not change the sensory properties and consumer acceptability of cornsilk-based beef and chicken patties. Cornsilk fibre has been effective in improving cooking yield, moisture and fat retention of beef and chicken patties

Valuing Environmental Impact of Air Pollution in Moscow with Hedonic Prices

The main purpose of this research is the calculation of implicit prices of the environmental level of air quality in the city of Moscow on the basis of housing property prices. The database used contains records of approximately 20 thousand apartments and has been provided by a leading real estate agency operating in Russia. The explanatory variables include physical characteristics of the houses, environmental (industry emissions), neighbourhood sociodemographic and geographic data: GPS coordinates of each house. The hedonic regression results for ecological variables show «negative» prices while increasing the level of air contamination from such substances as carbon monoxide, nitrogen dioxide, sulphur dioxide, and particles (CO, NO2, SO2, TSP). The marginal willingness to pay for higher environmental quality is presented for linear and log-log models.

A National Idea in Conditions of the Islamic Revival

Discussion and development of principles of the uniform nation formation within the limits of the Kazakhstan state obviously became one of the most pressing questions of the day. The fact that this question has not been solved "from above" as many other questions has caused really brisk discussion, shows us increase of civil consciousness in Kazakhstan society, and also the actuality of this theme which can be carried in the category of fatal questions. In any sense, nation building has raised civil society to a much higher level. It would be better to begin with certain definitions. First is the word "nation". The second is the "state". Both of these terms are very closely connected with each other, so that in English language they are in general synonyms. In Russian more shades of these terms exist. For example in Kazakhstan the citizens of the country irrespective of nationality (but mainly with reference to non-kazakhs) are called «kazakhstanians», while the name of the title nation is \"Kazakhs\". The same we can see in Russia, where, for example, the Chechen or the Yakut –are \"Rossiyane\" which means “the citizens of Russian Federation, but not \"Russians\". The paper was written under the research project “Islam in modern Kazakhstan: the nature and outcome of the religious revival”.

In vivo Antidiabetic and Antioxidant Potential of Pseudovaria macrophylla Extract

This study has investigated the antidiabetic and antioxidant potential of Pseudovaria macrophylla bark extract on streptozotocin–nicotinamide induced type 2 diabetic rats. LCMSQTOF and NMR experiments were done to determine the chemical composition in the methanolic bark extract. For in vivo experiments, the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.) induced diabetic rats were treated with methanolic extract of Pseuduvaria macrophylla (200 and 400 mg/kg·bw) and glibenclamide (2.5 mg/kg) as positive control respectively. Biochemical parameters were assayed in the blood samples of all groups of rats. The pro-inflammatory cytokines, antioxidant status and plasma transforming growth factor βeta-1 (TGF-β1) were evaluated. The histological study of the pancreas was examined and its expression level of insulin was observed by immunohistochemistry. In addition, the expression of glucose transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by western blot analysis. The outcomes of the study displayed that the bark methanol extract of Pseuduvaria macrophylla has potentially normalized the elevated blood glucose levels and improved serum insulin and C-peptide levels with significant increase in the antioxidant enzyme, reduced glutathione (GSH) and decrease in the level of lipid peroxidation (LPO). Additionally, the extract has markedly decreased the levels of serum pro-inflammatory cytokines and transforming growth factor beta-1 (TGF-β1). Histopathology analysis demonstrated that Pseuduvaria macrophylla has the potential to protect the pancreas of diabetic rats against peroxidation damage by downregulating oxidative stress and elevated hyperglycaemia. Furthermore, the expression of insulin protein, GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced. The findings of this study support the anti-diabetic claims of Pseudovaria macrophylla bark.

e-Collaborative Learning Circles

In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.

Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case

A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.

The Weight of Corporate Social Responsibility Indicators in Measurement Procedure

The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.

Cardiac Function and Morphological Adaptations in Endurance and Resistance Athletes: Evaluation using a new Method

Background: Tissue Doppler Echocardiography (TDE) assesses diastolic function more accurately than routine pulse Doppler echo. Assessment of the effects of dynamic and static exercises on the heart by using TDE can provides new information about the athlete-s heart syndrome. Methods: This study was conducted on 20 elite wrestlers, 14 endurance runners at national level and 21 non-athletes as the control group. Participants underwent two-dimensional echocardiography, standard Doppler and TDE. Results: Wrestlers had the highest left ventricular mass index, enddiastolic inter-ventricular septum thickness and left ventricular Posterior wall thickness. Runners had the highest Left ventricular end-diastolic volume, LV ejection fraction, stroke volume and cardiac output. In TDE, the early diastolic velocity of mitral annulus to the late diastolic velocity ratio in athletic groups was greater than the controls with no significant difference. Conclusion: In spite of cardiac morphological changes in athletes, TDE shows that cardiac diastolic function won-t be adversely affected.

A Cognitive Robot Collaborative Reinforcement Learning Algorithm

A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

SWNT Sensors for Monitoring the Oxidation of Edible Oils

There are several means to measure the oxidation of edible oils, such as the acid value, the peroxide value, and the anisidine value. However, these means require large quantities of reagents and are time-consuming tasks. Therefore, a more convenient and time-saving way to measure the oxidation of edible oils is required. In this report, an edible oil condition sensor was fabricated by using single-walled nanotubes (SWNT). In order to test the sensor, oxidized edible oils, each one at a different acid value, were prepared. The SWNT sensors were immersed into these oxidized oils and the resistance changes in the sensors were measured. It was found that the conductivity of the sensors decreased as the oxidation level of oil increased. This result suggests that a change of the oil components induced by the oxidation process in edible oils is related to the conductivity change in the SWNT sensor.

Level of Concentration in Banking Markets and Length of EU Membership

The purpose of this article is to analyze the degree of concentration in the banking market in EU member states as well as to determine the impact of the length of EU membership on the degree of concentration. In that sense several analysis were conducted, specifically, panel analysis, calculation of correlation coefficient and regression analysis of the impact of the length of EU membership on the degree of concentration. Panel analysis was conducted to determine whether there is a similar trend of concentration in three groups of countries - countries with a low, moderate and high level of concentration. The conducted panel analysis showed that in EU countries with a moderate level of concentration, the level of concentration decreases. The calculation of correlation showed that, to some extent, with other influential factors, the length of EU membership negatively affects the market concentration of the banking market. Using the regression analysis for investigation of the influence of the length of EU membership on the level of concentration in the banking sector in a particular country, the results reveal that there is a negative effect of the length in EU membership on market concentration, although it is not significantly influential variable.

Commercializing Technology Solutions- Moving from Products to Solutions

The paper outlines the drivers behind the movement from products to solutions in the Hi-Tech Business-to-Business markets. The paper lists out the challenges in enabling the transformation from products to solutions and also attempts to explore strategic and operational recommendations based on the authors- factual experiences with Japanese Hi-tech manufacturing organizations. Organizations in the Hi-Tech Business-to-Business markets are increasingly being compelled to move to a solutions model from the conventional products model. Despite the added complexity of solutions, successful technology commercialization can be achieved by making prudent choices in defining a relevant solutions model, by backing the solution model through appropriate organizational design, and by overhauling the new product development process and supporting infrastructure.

Fracture Characterization of Plain Woven Fabric Glass-Epoxy Composites

Delamination between layers in composite materials is a major structural failure. The delamination resistance is quantified by the critical strain energy release rate (SERR). The present investigation deals with the strain energy release rate of two woven fabric composites. Materials used are made of two types of glass fiber (360 gsm and 600 gsm) of plain weave and epoxy as matrix. The fracture behavior is studied using the mode I, double cantilever beam test and the mode II, end notched flexure test, in order to determine the energy required for the initiation and growth of an artificial crack. The delamination energy of these two materials is compared in order to study the effect of weave and reinforcement on mechanical properties. The fracture mechanism is also analyzed by means of scanning electron microscopy (SEM). It is observed that the plain weave fabric composite with lesser strand width has higher inter laminar fracture properties compared to the plain weave fabric composite with more strand width.

Labeling Method in Steganography

In this paper a way of hiding text message (Steganography) in the gray image has been presented. In this method tried to find binary value of each character of text message and then in the next stage, tried to find dark places of gray image (black) by converting the original image to binary image for labeling each object of image by considering on 8 connectivity. Then these images have been converted to RGB image in order to find dark places. Because in this way each sequence of gray color turns into RGB color and dark level of grey image is found by this way if the Gary image is very light the histogram must be changed manually to find just dark places. In the final stage each 8 pixels of dark places has been considered as a byte and binary value of each character has been put in low bit of each byte that was created manually by dark places pixels for increasing security of the main way of steganography (LSB).

Stock Market Integration Measurement: Investigation of Malaysia and Singapore Stock Markets

This paper tests the level of market integration between Malaysia and Singapore stock markets with the world market. Kalman Filter (KF) methodology is used on the International Capital Asset Pricing Model (ICAPM) and the pricing errors estimated within the framework of ICAPM are used as a measure of market integration or segmentation. The advantage of the KF technique is that it allows for time-varying coefficients in estimating ICAPM and hence able to capture the varying degree of market integration. Empirical results show clear evidence of varying degree of market integration for both case of Malaysia and Singapore. Furthermore, the results show that the changes in the level of market integration are found to coincide with certain economic events that have taken placed. The findings certainly provide evidence on the practicability of the KF technique to estimate stock markets integration. In the comparison between Malaysia and Singapore stock market, the result shows that the trends of the market integration indices for Malaysia and Singapore look similar through time but the magnitude is notably different with the Malaysia stock market showing greater degree of market integration. Finally, significant evidence of varying degree of market integration shows the inappropriate use of OLS in estimating the level of market integration.

Speckle Reducing Contourlet Transform for Medical Ultrasound Images

Speckle noise affects all coherent imaging systems including medical ultrasound. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. Even though wavelets have been extensively used for denoising speckle images, we have found that denoising using contourlets gives much better performance in terms of SNR, PSNR, MSE, variance and correlation coefficient. The objective of the paper is to determine the number of levels of Laplacian pyramidal decomposition, the number of directional decompositions to perform on each pyramidal level and thresholding schemes which yields optimal despeckling of medical ultrasound images, in particular. The proposed method consists of the log transformed original ultrasound image being subjected to contourlet transform, to obtain contourlet coefficients. The transformed image is denoised by applying thresholding techniques on individual band pass sub bands using a Bayes shrinkage rule. We quantify the achieved performance improvement.

Improved IDR(s) Method for Gaining Very Accurate Solutions

The IDR(s) method based on an extended IDR theorem was proposed by Sonneveld and van Gijzen. The original IDR(s) method has excellent property compared with the conventional iterative methods in terms of efficiency and small amount of memory. IDR(s) method, however, has unexpected property that relative residual 2-norm stagnates at the level of less than 10-12. In this paper, an effective strategy for stagnation detection, stagnation avoidance using adaptively information of parameter s and improvement of convergence rate itself of IDR(s) method are proposed in order to gain high accuracy of the approximated solution of IDR(s) method. Through numerical experiments, effectiveness of adaptive tuning IDR(s) method is verified and demonstrated.