Search results for: Learning activity

Authors: Rana M. Zeina, Laila Al-Ayadhi, Shahid Bashir

Abstract:

Autism Spectrum Disorders (ASDs) are characterized by abnormalities in social interaction and communication, as well as repetitive and stereotyped behaviors. Although various studies have been conducted in ASDs etiology across the world, it seems that they are still unknown in Middle East. Some scientific researches have been conducted on ASDs in Middle East (ME) especially in Kingdom of Saudi Arabia (KSA). A systematic literature review was performed to identify the ASDs studies in KSA. Accordingly, PubMed, ISI web of Science and Google were searched to find KSA and ME studies in ASDs. The main focus of this review work is to outline an improved understanding of the underpinnings of ASD in order to achieve therapeutic interventions and we will discuss the main problem we waiting for solution with reference with role of Transcranial Magnetic Stimulation (TMS) to modulate cortical activity improve understanding ASD.

Keywords: Autism, Neurodevelopmental disorder

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Authors: Kholoud A. Al-Shammery , Badr El-Sabah A. Fetoh, Ahmed M. Alshammari

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Protein and Esterase electrophoresis were used to genetically identify two Saudi tick species. Engorged females of the camel tick Hyalomma dromedarii (Koch) (Acari: Ixodidae) and the cattle tick Boophilus annulatus (Say) (Acari: Ixodidae) ticks collected from infested camels and cattle in the animals resting house at Hail region in KSA were used. The results showed that there are a variation in both of protein and esterase activity levels and a high polymorphism within and between the genera and species of Hyalomma and Boophilus . In conclusion, the protein and esterase electrophoretic analysis used in the present study could successfully distinguish among tick species, commonly found in Saudi Arabia.

Keywords: Molecular biology, The camel tick Hyalomma dromedarii, The cattle tick Boophilus annulatus , Ticks.

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Authors: E. Bene

Abstract:

Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Centre for Agricultural Sciences of University of Debrecen, in 2012-2014. The paper contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences the leaf area index and the activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying the effects of each other, develop average yields.

Keywords: Sowing date, hybrid, leaf area index, photosynthetic capacity.

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Authors: Zh. Nurbekova, Z. Zhanazarova, A. Beissenova

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This article is devoted to the analysis of results of sociological researches carried out by authors directed on studying of opinion of representatives of small, medium and big business on formation of the Customs Union, Common Free Market Zone with participation of Kazakhstan, Russia and Belarus. It-s forecasted that companies, their branches will interpenetrate with registration and moving their businesses to regions with more beneficial conditions. They say that in Kazakhstan there are more profitable geo-strategic operating environment for business and lower taxes. Russia using this opportunity will create new conditions for expansion into other countries of Central Asia and China. Opinions of participants of questionnaire and expert poll different in estimation of value of these two integration mechanisms since market segments on the one hand extend, but also on the other hand - loss of exclusive influence in certain fields of activity.

Keywords: Customs Union, Kazakhstan, sociological research.

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Authors: Eva Pajorová, Ladislav Hluchý

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Developed tool is one of system tools for easier access to various scientific areas and real time interactive learning between lecturer and for hearing impaired students. There is no demand for the lecturer to know Sign Language (SL). Instead, the new software tools will perform the translation of the regular speech into SL, after which it will be transferred to the student. On the other side, the questions of the student (in SL) will be translated and transferred to the lecturer in text or speech. One of those tools is presented tool. It-s too for developing the correct Speech Visemes as a root of total communication method for hearing impared students.

Keywords: Impared people, sing language, communication methods.

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Authors: Said Hadjerrouit

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Wikis are considered to be part of Web 2.0 technologies that potentially support collaborative learning and writing. Wikis provide opportunities for multiple users to work on the same document simultaneously. Most wikis have also a page for written group discussion. Nevertheless, wikis may be used in different ways depending on the pedagogy being used, and the constraints imposed by the course design. This work explores students- uses of wiki in teacher education. The analysis is based on a taxonomy for classifying students- activities and actions carried out on the wiki. The article also discusses the implications for using wikis as collaborative writing tools in teacher education.

Keywords: Behaviorism, collaborative writing, socioconstructivism, taxonomy, web 2.0 technology, wiki

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Authors: Ilyes Jenhani, Salem Benferhat, Zied Elouedi

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This paper investigates the issue of building decision trees from data with imprecise class values where imprecision is encoded in the form of possibility distributions. The Information Affinity similarity measure is introduced into the well-known gain ratio criterion in order to assess the homogeneity of a set of possibility distributions representing instances-s classes belonging to a given training partition. For the experimental study, we proposed an information affinity based performance criterion which we have used in order to show the performance of the approach on well-known benchmarks.

Keywords: Data mining from uncertain data, Decision Trees, Possibility Theory.

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Authors: Arpiruk Hokpunna, Michael Manhart

Abstract:

We present a Large-Eddy simulation of a vortex cell with circular shaped. The results show that the flow field can be sub divided into four important zones, the shear layer above the cavity, the stagnation zone, the vortex core in the cavity and the boundary layer along the wall of the cavity. It is shown that the vortex core consits of solid body rotation without much turbulence activity. The vortex is mainly driven by high energy packets that are driven into the cavity from the stagnation point region and by entrainment of fluid from the cavity into the shear layer. The physics in the boundary layer along the cavity-s wall seems to be far from that of a canonical boundary layer which might be a crucial point for modelling this flow.

Keywords: Turbulent flow, Large eddy simulations, boundary layer and cavity flow, vortex cell flow.

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Authors: S. Gais, F. Fazouane, A. Mechakra

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The present study describes the biosynthesis of a milkclotting protease by solid state fermentation (SSF) of a locally isolated mould, Rhizopus stolonifer. The production medium was prepared using wheat bran at 50% (w/v). The production conditions are optimized by varying 7 parameters: carbon and nitrogen sources, medium moisture, temperature, pH, fermentation time and inoculum-s size. The maximum enzyme synthesis was measured after 96 h of incubation time at temperature of 28°C. The optimum pH determined was 6 and the inoculum size was 3.106spores/ml. The optimum initial moisture content is comprised between 50 to 70%. The formation of milk clotting protease is enhanced when galactose and peptone are used at 10% (w/v) and 1% (w/v) concentrations respectively. The maximum production of milk clotting protease is 120 US/ml.

Keywords: Milk clotting activity, protease production, Rhizopus stolonifer, Solid state fermentation.

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Authors: Dimitris Balios, Stefanos Tantos

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Economic growth and social evolution are connected to trust relationships in a society. The quality of the accounting information, the tax information system and the tax audit mechanism evolve multiple benefits in an economy. Tax evasion, the illegal practice where people and companies do not pay taxes, is a crime because of the negative effect in economy and society. In this paper, we describe a theoretical framework on the characteristics of a fair and efficient tax auditing information system which could be a tool against tax evasion, a tool for an economy to grow, especially in countries that face fluctuations in economic activity. We conclude that a fair and efficient tax auditing information system increases the reliability of tax administration, improves taxpayers’ tax compliance and causes a developmental trajectory for the economy.

Keywords: Auditing information system, auditing mechanism, tax evasion, taxation, quality of accounting information.

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: Attributed community, attribute detection, community, social network.

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Authors: Hanna Ziętara

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Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, foodservice is strongly related to logistics processes, and areas of foodservice that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support, occurring in the catering business, and affecting the scope of the logistic processes implemented. The aim of the paper is implemented through a plural homogeneous approach, based on direct observation, text analysis of current documents, and in-depth free targeted interviews.

Keywords: Gastronomy, competitive advantage, logistics, logistics support.

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Authors: József Valyon, Gábor Horváth

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Among neural models the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they eliminate certain crucial questions involved by neural network construction. The main drawback of standard SVM is its high computational complexity, therefore recently a new technique, the Least Squares SVM (LS–SVM) has been introduced. In this paper we present an extended view of the Least Squares Support Vector Regression (LS–SVR), which enables us to develop new formulations and algorithms to this regression technique. Based on manipulating the linear equation set -which embodies all information about the regression in the learning process- some new methods are introduced to simplify the formulations, speed up the calculations and/or provide better results.

Keywords: Function estimation, Least–Squares Support VectorMachines, Regression, System Modeling

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Authors: Fatimah Almah Saaid, Darfiana Nur, Robert King

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This paper presents a procedure for estimating VAR using Sequential Discounting VAR (SDVAR) algorithm for online model learning to detect fraudulent acts using the telecommunications call detailed records (CDR). The volatility of the VAR is observed allowing for non-linearity, outliers and change points based on the works of [1]. This paper extends their procedure from univariate to multivariate time series. A simulation and a case study for detecting telecommunications fraud using CDR illustrate the use of the algorithm in the bivariate setting.

Keywords: Telecommunications Fraud, SDVAR Algorithm, Multivariate time series, Vector Autoregressive, Change points.

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Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

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Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: A classifier, Algorithms decision tree, knowledge extraction, Support Vector Machine.

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Authors: Ayuko Itsuki, Sachiyo Aburatani

Abstract:

Soil enzyme activities in Kasuga-yama Hill Primeval Forest (Nara, Japan) were examined to determine levels of mineralization and metabolism. Samples were selected from the soil surrounding laurel-leaved (B_B-1) and Carpinus japonica (B_B-2 and P_w) trees for analysis. Cellulase, β-xylosidase, and protease activities were higher in B_B-1 samples those in B_B-2 samples. These activity levels corresponded to the distribution of cellulose and hemicellulose in the soil horizons. Cellulase, β-xylosidase, and chymotrypsin activities were higher in soil from the P_w forest than in that from the B_B-2 forest. The relationships between the soil enzymes calculated by Spearman’s rank correlation indicate that the interactions between enzymes in B_B-2 samples were more complex than those in P_w samples.

Keywords: Comparative analysis, enzyme activities, forest soil, Spearman’s rank correlation.

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Authors: Walid S. Abd El-hamid, Sherif S. El-Etriby, Mohiy M. Hadhoud

Abstract:

Regression testing is a maintenance activity applied to modified software to provide confidence that the changed parts are correct and that the unchanged parts have not been adversely affected by the modifications. Regression test selection techniques reduce the cost of regression testing, by selecting a subset of an existing test suite to use in retesting modified programs. This paper presents the first general regression-test-selection technique, which based on code and allows selecting test cases for any programs written in any programming language. Then it handles incomplete program. We also describe RTSDiff, a regression-test-selection system that implements the proposed technique. The results of the empirical studied that performed in four programming languages java, C#, Cµ and Visual basic show that the efficiency and effective in reducing the size of test suit.

Keywords: Regression testing, testing, test selection, softwareevolution, software maintenance.

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Authors: Asım Egitmen, Aysen Demir, Burcu Darendeli, Fatma Ulusal, Bilgehan Güzel

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Synthesizing supercritical carbon dioxide (scCO₂) soluble precursors would be helpful for many processes of material syntheses based on scCO₂. Ligand (amphi-(1Z, 2Z)-N-(2-fluoro-3-(trifluoromethyl) phenyl)-N'-hydroxy-2-(hydroxyimino) were synthesized from chloro glyoxime and flourus aniline and Pd(II) complex (precursor) prepared. For scCO₂ deposition method, organometallic precursor was dissolved in scCO₂ and impregnated onto the SBA-15 at 90 °C and 3000 psi. Then the organometallic precursor was reduced with H₂ in the CO₂ mixture (150 psi H₂ + 2850 psi CO₂). Pd deposited support material was characterized by ICP-OES, XRD, FE-SEM, TEM and EDX analyses. The Pd loading of the prepared catalyst, measured by ICP-OES showed a value of about 1.64% mol/g Pd of catalyst. Average particle size was found 5.3 nm. The catalytic activity of prepared catalyst was investigated over Suzuki-Miyaura C-C coupling reaction in different solvent with K₂CO₃ at 50 ^oC. The conversion ratio was determined by gas chromatography.

Keywords: Nanoparticle, nanotube, oximes, precursor, supercritical CO2.

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Authors: Jochen Nelles, Susanne Kohns, Julia Spies, Friederike Schmitz-Buhl, Roland Thietje, Christopher Brandl, Alexander Mertens, Christopher M. Schlick

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Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.

Keywords: Assistance robot, human-robot-interaction, motion capture, stress-strain-concept, surface electromyography, tetraplegia.

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Authors: Ilqar Ramazanli

Abstract:

The matrix completion problem has been studied broadly under many underlying conditions. In many real-life scenarios, we could expect elements from distinct columns or distinct positions to have a different cost. In this paper, we explore this generalization under adaptive conditions. We approach the problem under two different cost models. The first one is that entries from different columns have different observation costs, but, within the same column, each entry has a uniform cost. The second one is any two entry has different observation cost, despite being the same or different columns. We provide complexity analysis of our algorithms and provide tightness guarantees.

Keywords: Matrix completion, adaptive learning, heterogeneous cost, Matroid optimization.

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Authors: Ibrahim I. Elshahawy

Abstract:

The objective of the present study was to investigate the effect of green tea extract on serum oxidant and antioxidant profile, liver and kidney function. 40 Friesian calves are included in this study and allocated into two groups: Group I (n=20) clinically healthy calves showing no clinical abnormalities, not receiving any treatment and served as control; group II (n=20) received green tea extract (GTE) for 30 days. Non-significant changes in blood urea nitrogen (BUN) were detected between groups, on contrary, serum creatinine and activities of liver enzymes aspartate transaminase (AST) and alanine transaminase (ALT) were significantly different between two groups. There were significant increases in the mean values of serum antioxidative parameters (total antioxidant capacity, catalase, superoxide dismutase, reduced glutathione and glutathione peroxidase) in group II. Whereas, the activity of lipid peroxidase significantly decreased in GTE treated calves when compared to control.

Keywords: Green tea extract, antioxidants, oxidants, calves.

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Authors: Bahareh Hajirostamloo

Abstract:

Recent research has shown that milk proteins can yield bioactive peptides with opioid, mineral binding, cytomodulatory, antihypertensive, immunostimulating, antimicrobial and antioxidative activity in the human body. Bioactive peptides are encrypted in milk proteins and are only released by enzymatic hydrolysis in vivo during gastrointestinal digestion, food processing or by microbial enzymes in fermented products. At present significant research is being undertaken on the health effects of bioactive peptides. A variety of naturally formed bioactive peptides have been found in fermented dairy products, such as yoghurt, sour milk and cheese. In particular, antihypertensive peptides have been identified in fermented milks, whey and ripened cheese. Some of these peptides have been commercialized in the form of fermented milks. Bioactive peptides have the potential to be used in the formulation of health-enhancing nutraceuticals, and as potent drugs with well defined pharmacological effects.

Keywords: Milk protein, Bioactive peptides, Health effects, Dairy product.

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Authors: Е. V. Kutsina, S. A. Tarasova

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In this article we present a methodology which enables preschool and primary school unlanguaged children to remember words, phrases and texts with the help of graphic signs - letters, syllables and words. Reading for a child becomes a support for speech development. Teaching is based on the principle "from simple to complex", "a letter - a syllable - a word - a proposal - a text." Availability of multi-level texts allows using this methodology for working with children who have different levels of speech development.

Keywords: Alalia, analytic-synthetic method, development of coherent speech, formation of vocabulary, learning to read, , sentence formation, three-level stories, unlanguaged children.

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Authors: A. R. Rahmani, H. R. Ghaffari, M. T. Samadi

Abstract:

The present work was conducted for Arsenic (III) removal, which one of the most poisonous groundwater pollutants, by synthetic nano size zerovalent iron (nZVI). Batch experiments were performed to investigate the influence of As (III), nZVI concentration, pH of solution and contact time on the efficiency of As (III) removal. nZVI was synthesized by reduction of ferric chloride by sodium borohydrid. SEM and XRD were used to determine particle size and characterization of produced nanoparticles. Up to 99.9% removal efficiency for arsenic (III) was obtained by nZVI dosage of 1 g/L at time equal to 10 min. and pH=7. It could be concluded that the removal efficiency were enhanced with increasing of ZVI dosage and reaction time, but decreased with increasing of arsenic concentration and pH for nano sized ZVI. nZVI presented an outstanding ability to remove As (III) due to not only a high surface area and low particle size but also to high inherent activity.

Keywords: Arsenic removal, aqueous solution, zero valent iron.

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Authors: U. Bottigli, M.Carpinelli, P.L. Fiori, B. Golosio, A. Marras, G. L. Masala, P. Oliva

Abstract:

The counting process of cell colonies is always a long and laborious process that is dependent on the judgment and ability of the operator. The judgment of the operator in counting can vary in relation to fatigue. Moreover, since this activity is time consuming it can limit the usable number of dishes for each experiment. For these purposes, it is necessary that an automatic system of cell colony counting is used. This article introduces a new automatic system of counting based on the elaboration of the digital images of cellular colonies grown on petri dishes. This system is mainly based on the algorithms of region-growing for the recognition of the regions of interest (ROI) in the image and a Sanger neural net for the characterization of such regions. The better final classification is supplied from a Feed-Forward Neural Net (FF-NN) and confronted with the K-Nearest Neighbour (K-NN) and a Linear Discriminative Function (LDF). The preliminary results are shown.

Keywords: Automatic cell counting, neural network, region growing, Sanger net.

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Authors: Ch.V.Rama Rao, Gowthami., Harsha., Rajkumar., M.B.Rama Murthy, K.Srinivasa Rao, K.AnithaSheela

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This paper presents a new method for estimating the nonstationary noise power spectral density given a noisy signal. The method is based on averaging the noisy speech power spectrum using time and frequency dependent smoothing factors. These factors are adjusted based on signal-presence probability in individual frequency bins. Signal presence is determined by computing the ratio of the noisy speech power spectrum to its local minimum, which is updated continuously by averaging past values of the noisy speech power spectra with a look-ahead factor. This method adapts very quickly to highly non-stationary noise environments. The proposed method achieves significant improvements over a system that uses voice activity detector (VAD) in noise estimation.

Keywords: Noise estimation, Non-stationary noise, Speechenhancement.

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Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade

Abstract:

The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.

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Authors: Shoji Katagiri

Abstract:

This study deals with wage inequality in organization and shows the relationship between ICT and wage in organization. To do so, we incorporate ICT’s factors in organization into our model. ICT’s factors are efficiencies of Enterprise Resource Planning (ERP), Computer Assisted Design/Computer Assisted Manufacturing (CAD/CAM), and NETWORK. The improvement of ICT’s factors decrease the learning cost to solve problem pertaining to the hierarchy in organization. The improvement of NETWORK increases the wage inequality within workers and decreases within managers and entrepreneurs. The improvements of CAD/CAM and ERP increases the wage inequality within all agent, and partially increase it between the agents in hierarchy.

Keywords: Endogenous economic growth, ICT, inequality, capital accumulation, technology.

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Authors: Ahmed Amin Mousa, Tamer M. Ismail, M. Abd El Salam

Abstract:

This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.

Keywords: CR-Cube, robotic cube, conceptual robot, conceptual cube, colour concept, early childhood education.

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