Search results for: automated stock investment system.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9000

Search results for: automated stock investment system.

8580 Tibyan Automated Arabic Correction Using Machine-Learning in Detecting Syntactical Mistakes

Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

Abstract:

The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic Language acquisition and learning, natural language processing, morphological analyzer, part-of-speech.

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8579 Risk Classification of SMEs by Early Warning Model Based on Data Mining

Authors: Nermin Ozgulbas, Ali Serhan Koyuncugil

Abstract:

One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.

Keywords: Early Warning Systems, Data Mining, Financial Risk, SMEs.

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8578 A Model for Collaborative COTS Software Acquisition (COSA)

Authors: Torsti Rantapuska, Sariseelia Sore

Abstract:

Acquiring commercial off-the-shelf (COTS) software applications is becoming routine in organizations. However, eliciting user requirements, finding the candidate COTS products and making the decision is a complex task, especially for SMEs who do not have the time and knowledge needed to do the task properly. The existing models intended to help the decision makers are originally designed for professional use. SMEs are obligated to rely on the software vendor’s ability to solve the problem with the systems provided.  In this paper, we develop a model for SMEs for the acquisition of Commercial Off-The-Shelf (COTS) software products. A leading idea of the model is that the ICT investment is basically a change initiative and therefore it should also be taken as a process of organizational learning. The model is designed bearing three objectives in mind: 1) business orientation, 2) agility, and 3) Learning and knowledge management orientation. The model can be applied to ICT investments in SMEs which have a professional team leader with basic business and IT knowledge. 

 

Keywords: COTS acquisition, ICT investment, organizational learning, ICT adoption.

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8577 Skin Lesion Segmentation Using Color Channel Optimization and Clustering-based Histogram Thresholding

Authors: Rahil Garnavi, Mohammad Aldeen, M. Emre Celebi, Alauddin Bhuiyan, Constantinos Dolianitis, George Varigos

Abstract:

Automatic segmentation of skin lesions is the first step towards the automated analysis of malignant melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most effective color space for melanoma application. This paper proposes an automatic segmentation algorithm based on color space analysis and clustering-based histogram thresholding, a process which is able to determine the optimal color channel for detecting the borders in dermoscopy images. The algorithm is tested on a set of 30 high resolution dermoscopy images. A comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm, applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. By performing ROC analysis and ranking the metrics, it is demonstrated that the best results are obtained with the X and XoYoR color channels, resulting in an accuracy of approximately 97%. The proposed method is also compared with two state-of-theart skin lesion segmentation methods.

Keywords: Border detection, Color space analysis, Dermoscopy, Histogram thresholding, Melanoma, Segmentation.

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8576 Application of the Virtual Reality Modeling Language for Design of Automated Workplaces

Authors: Jozef Novak-Marcincin

Abstract:

Virtual Reality Modelling Language (VRML) is description language, which belongs to a field Window on World virtual reality system. The file, which is in VRML format, can be interpreted by VRML explorer in three-dimensional scene. VRML was created with aim to represent virtual reality on Internet easier. Development of 3D graphic is connected with Silicon Graphic Corporation. VRML 2.0 is the file format for describing interactive 3D scenes and objects. It can be used in collaboration with www, can be used for 3D complex representations creating of scenes, products or VR applications VRML 2.0 enables represent static and animated objects too. Interesting application of VRML is in area of manufacturing systems presentation.

Keywords: Virtual reality, virtual reality modelling language, design of workplaces, technological workplaces.

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8575 Efficient Use of Energy through Incorporation of a Gas Turbine in Methanol Plant

Authors: M. Azadi, N. Tahouni, M. H. Panjeshahi

Abstract:

A techno-economic evaluation for efficient use of energy in a large scale industrial plant of methanol is carried out. This assessment is based on integration of a gas turbine with an existing plant of methanol in which the outlet gas products of exothermic reactor is expanded to power generation. Also, it is decided that methanol production rate is constant through addition of power generation system to the existing methanol plant. Having incorporated a gas turbine with the existing plant, the economic results showed total investment of MUSD 16.9, energy saving of 3.6 MUSD/yr with payback period of approximately 4.7 years.

Keywords: Energy saving, Gas turbine, Methanol, Power generation.

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8574 Application of the Data Distribution Service for Flexible Manufacturing Automation

Authors: Marco Ryll, Svetan Ratchev

Abstract:

This paper discusses the applicability of the Data Distribution Service (DDS) for the development of automated and modular manufacturing systems which require a flexible and robust communication infrastructure. DDS is an emergent standard for datacentric publish/subscribe middleware systems that provides an infrastructure for platform-independent many-to-many communication. It particularly addresses the needs of real-time systems that require deterministic data transfer, have low memory footprints and high robustness requirements. After an overview of the standard, several aspects of DDS are related to current challenges for the development of modern manufacturing systems with distributed architectures. Finally, an example application is presented based on a modular active fixturing system to illustrate the described aspects.

Keywords: Flexible Manufacturing, Publish/Subscribe, Plug & Produce.

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8573 Embodiment Design of an Azimuth-Altitude Solar Tracker

Authors: M. Culman, O. Lengerke

Abstract:

To provide an efficient solar generation system, the embodiment design of a two axis solar tracker for an array of photovoltaic (PV) panels destiny to supply the power demand on off-the-grid areas was developed. Photovoltaic cells have high costs in relation to t low efficiency; and while a lot of research and investment has been made to increases its efficiency a few points, there is a profitable solution that increases by 30-40% the annual power production: two axis solar trackers. A solar tracker is a device that supports a load in a perpendicular position toward the sun during daylight. Mounted on solar trackers, the solar panels remain perpendicular to the incoming sunlight at day and seasons so the maximum amount of energy is outputted. Through a preview research done it was justified why the generation of solar energy through photovoltaic panels mounted on dual axis structures is an attractive solution to bring electricity to remote off-the-grid areas. The work results are the embodiment design of an azimuth-altitude solar tracker to guide an array of photovoltaic panels based on a specific design methodology. The designed solar tracker is mounted on a pedestal that uses two slewing drives‚ with a nominal torque of 1950 Nm‚ to move a solar array that provides 3720 W from 12 PV panels.

Keywords: Azimuth-altitude sun tracker, dual-axis solar tracker, photovoltaic system, solar energy, stand-alone power system.

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8572 Economic and Environmental Benefits of the Best Available Technique Application in a Food Processing Plant

Authors: Frantisek Bozek, Pavel Budinsky, Ignac Hoza, Alexandr Bozek, Magdalena Naplavova

Abstract:

A cleaner production project was implemented in a bakery. The project is based on the substitution of the best available technique for an obsolete leaven production technology. The new technology enables production of durable, high-quality leavens. Moreover, 25% of flour as the original raw material can be replaced by pastry from the previous day production which has not been sold. That pastry was previously disposed in a waste incineration plant. Besides the environmental benefits resulting from less waste, lower consumption of energy, reduction of sewage waters quantity and floury dustiness there are also significant economic benefits. Payback period of investment was calculated with help of static method of financial analysis about 2.6 years, using dynamic method 3.5 years and an internal rate of return more than 29%. The supposed annual average profit after taxationin the second year of operation was incompliance with the real profit.

Keywords: Bakery, best available technology, cleaner production, costs, economic benefit, efficiency, energy, environmental benefit, investment, savings.

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8571 Intelligent Control of Robotized Workcell by Augmented Reality Application

Authors: L. Novakova-Marcincinova, J. Novak-Marcincin, M. Janak

Abstract:

The computer aided for design, analysis, control, visualization and simulation of robotized workcells is very interesting in this time. Computer Aided Robot Control (CARC) is a subsystem of the system CIM including the computer aided systems of all activities connected with visualization and working of robotized workcells. There are three basic ideas: current CAD/CAM/CAE systems for design and 3D visualization, special PC based control and simulation systems and Augmented Reality Aided Manufacturing (ARAM) systems. This paper describes example of Open Source software application that can to be utilized at planning of the robotized workcells, visualization and off-line programming the automated processes realized by authors.

Keywords: Intelligent control, augmented reality, robot.

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8570 Detecting Earnings Management via Statistical and Neural Network Techniques

Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

Abstract:

Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: Earnings management, generalized regression neural networks, linear regression, multi-layer perceptron, Tehran stock exchange.

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8569 Using Data Mining Methodology to Build the Predictive Model of Gold Passbook Price

Authors: Chien-Hui Yang, Che-Yang Lin, Ya-Chen Hsu

Abstract:

Gold passbook is an investing tool that is especially suitable for investors to do small investment in the solid gold. The gold passbook has the lower risk than other ways investing in gold, but its price is still affected by gold price. However, there are many factors can cause influences on gold price. Therefore, building a model to predict the price of gold passbook can both reduce the risk of investment and increase the benefits. This study investigates the important factors that influence the gold passbook price, and utilize the Group Method of Data Handling (GMDH) to build the predictive model. This method can not only obtain the significant variables but also perform well in prediction. Finally, the significant variables of gold passbook price, which can be predicted by GMDH, are US dollar exchange rate, international petroleum price, unemployment rate, whole sale price index, rediscount rate, foreign exchange reserves, misery index, prosperity coincident index and industrial index.

Keywords: Gold price, Gold passbook price, Group Method ofData Handling (GMDH), Regression.

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8568 Competitiveness of the Baltic States within the International Ratings

Authors: Ilze Stokmane

Abstract:

Baltic competitiveness is quite controversial. In a situation with the rapid structural changes, economy develops in balance very rarely - in different fields will always be more rapid changes in another more stagnation. Analyzing different economic indices developed by international organizations the situation in three Baltic countries are described from a different competitiveness positions highlighting strengths and weaknesses of each country. Exploring the openness of the economy, it is possible to observe certain risks included in the reports describing situation of competitiveness where government policies competing in the tax system, the rates of labour market policies, investment environment, etc. This is a very important factor resulting in competitive advantage. Baltic countries are still at a weak position from a technological perspective, and need to borrow the knowledge and technology from more developed countries.

Keywords: Baltic countries, Baltic region, competitiveness, indices of competitiveness.

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8567 Analysis of Image Segmentation Techniques for Diagnosis of Dental Caries in X-ray Images

Authors: V. Geetha, K. S. Aprameya

Abstract:

Early diagnosis of dental caries is essential for maintaining dental health. In this paper, method for diagnosis of dental caries is proposed using Laplacian filter, adaptive thresholding, texture analysis and Support Vector Machine (SVM) classifier. Analysis of the proposed method is compared with Otsu thresholding, watershed segmentation and active contouring method. Adaptive thresholding has comparatively better performance with 96.9% accuracy and 96.1% precision. The results are validated using statistical method, two-way ANOVA, at significant level of 5%, that shows the interaction of proposed method on performance parameter measures are significant. Hence the proposed technique could be used for detection of dental caries in automated computer assisted diagnosis system.

Keywords: Computer assisted diagnosis, dental caries, dental radiography, image segmentation.

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8566 A New Approach to Polynomial Neural Networks based on Genetic Algorithm

Authors: S. Farzi

Abstract:

Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, we introduce GPNN (genetic polynomial neural network) to improve the performance of PNN. GPNN determines the number of input variables and the order of all neurons with GA (genetic algorithm). We use GA to search between all possible values for the number of input variables and the order of polynomial. GPNN performance is obtained by two nonlinear systems. the quadratic equation and the time series Dow Jones stock index are two case studies for obtaining the GPNN performance.

Keywords: GMDH, GPNN, GA, PNN.

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8565 Tuning of Thermal FEA Using Krylov Parametric MOR for Subsea Application

Authors: A. Suleng, T. Jelstad Olsen, J. Šindler, P. Bárta

Abstract:

A dead leg is a typical subsea production system component. CFD is required to model heat transfer within the dead leg. Unfortunately its solution is time demanding and thus not suitable for fast prediction or repeated simulations. Therefore there is a need to create a thermal FEA model, mimicking the heat flows and temperatures seen in CFD cool down simulations. This paper describes the conventional way of tuning and a new automated way using parametric model order reduction (PMOR) together with an optimization algorithm. The tuned FE analyses replicate the steady state CFD parameters within a maximum error in heat flow of 6 % and 3 % using manual and PMOR method respectively. During cool down, the relative error of the tuned FEA models with respect to temperature is below 5% comparing to the CFD. In addition, the PMOR method obtained the correct FEA setup five times faster than the manually tuned FEA.

Keywords: CFD, convective heat, FEA, model tuning, subseaproduction

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8564 Gender Differences in Risk Aversion Behavior: Case Study of Saudi Arabia and Jordan

Authors: Razan Salem

Abstract:

Men and women have different approaches towards investing, both in terms of strategies and risk attitudes. This study aims to focus mainly on investigating the financial risk behaviors of Arab women investors and to examine the financial risk tolerance levels of Arab women relative to Arab men investors. Using survey data on 547 Arab men and women investors, the results of Wilcoxon Signed-Rank (One-Sample) test Mann-Whitney U test reveal that Arab women are risk-averse investors and have lower financial risk tolerance levels relative to Arab men. Such findings can be explained by the fact of women's nature and lower investment literacy levels. Further, the current political uncertainty in the Arab region may be considered as another explanation of Arab women’s risk aversion behavior. The study's findings support the existing literature by validating the stereotype of “women are more risk-averse than men” in the Arab region. Overall, when it comes to investment and financial behaviors, women around the world behave similarly.

Keywords: Arab region, financial risk behavior, gender differences, women investors.

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8563 Performance of the Aptima® HIV-1 Quant Dx Assay on the Panther System

Authors: Siobhan O’Shea, Sangeetha Vijaysri Nair, Hee Cheol Kim, Charles Thomas Nugent, Cheuk Yan William Tong, Sam Douthwaite, Andrew Worlock

Abstract:

The Aptima® HIV-1 Quant Dx Assay is a fully automated assay on the Panther system. It is based on Transcription- Mediated Amplification and real time detection technologies. This assay is intended for monitoring HIV-1 viral load in plasma specimens and for the detection of HIV-1 in plasma and serum specimens. Nine-hundred and seventy nine specimens selected at random from routine testing at St Thomas’ Hospital, London were anonymised and used to compare the performance of the Aptima HIV-1 Quant Dx assay and Roche COBAS® AmpliPrep/COBAS® TaqMan® HIV-1 Test, v2.0. Two-hundred and thirty four specimens gave quantitative HIV-1 viral load results in both assays. The quantitative results reported by the Aptima Assay were comparable to those reported by the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 with a linear regression slope of 1.04 and an intercept on -0.097. The Aptima assay detected HIV-1 in more samples than the COBAS assay. This was not due to lack of specificity of the Aptima assay because this assay gave 99.83% specificity on testing plasma specimens from 600 HIV-1 negative individuals. To understand the reason for this higher detection rate a side-by-side comparison of low level panels made from the HIV-1 3rd international standard (NIBSC10/152) and clinical samples of various subtypes were tested in both assays. The Aptima assay was more sensitive than the COBAS assay. The good sensitivity, specificity and agreement with other commercial assays make the HIV-1 Quant Dx Assay appropriate for both viral load monitoring and detection of HIV-1 infections.

Keywords: HIV viral load, Aptima, Roche, Panther system.

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8562 Testing Object-Oriented Framework Applications Using FIST2 Tool: A Case Study

Authors: Jehad Al Dallal

Abstract:

An application framework provides a reusable design and implementation for a family of software systems. Frameworks are introduced to reduce the cost of a product line (i.e., a family of products that shares the common features). Software testing is a timeconsuming and costly ongoing activity during the application software development process. Generating reusable test cases for the framework applications during the framework development stage, and providing and using the test cases to test part of the framework application whenever the framework is used reduces the application development time and cost considerably. This paper introduces the Framework Interface State Transition Tester (FIST2), a tool for automated unit testing of Java framework applications. During the framework development stage, given the formal descriptions of the framework hooks, the specifications of the methods of the framework-s extensible classes, and the illegal behavior description of the Framework Interface Classes (FICs), FIST2 generates unitlevel test cases for the classes. At the framework application development stage, given the customized method specifications of the implemented FICs, FIST2 automates the use, execution, and evaluation of the already generated test cases to test the implemented FICs. The paper illustrates the use of the FIST2 tool for testing several applications that use the SalesPoint framework.

Keywords: Automated testing, class testing, FICs, FIST2, object-oriented framework, object-oriented testing.

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8561 Modern Trends in Foreign Direct Investments in Georgia

Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

Abstract:

Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: Foreign Direct Investments, methods, statistics, analysis.

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8560 Three-phases Model of the Induction Machine Taking Account the Stator Faults

Authors: Djalal Eddine Khodja, Aissa Kheldoun

Abstract:

In this work we present the modelling of the induction machine, taking into consideration the stator defects of the induction machine. It is based on the theory of electromagnetic coupling of electrical circuits. In fact, for the modelling of stationary defects such as short circuit between turns in the same phase, we introduce only in the matrix the coefficients of resistance and inductance of stator and in the mutual inductance stator-rotor. These coefficients take account the number of turns in short-circuit deducted from the total number of turns in the same phase; in this way we obtain the number of useful turns. In addition, all these faults involved, will be used for the creation of the database that will be used to develop an automated system failures of the induction machine.

Keywords: Asynchronous machine, Indicatory Values Statorfaults, Multi-turns Model, Three-phases Model.

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8559 Application of Legendre Transformation to Portfolio Optimization

Authors: Peter Benneth, Tsaroh N. Theophilus, Prince Benjamin

Abstract:

This research work aims at studying the application of Legendre Transformation Method (LTM) to Hamilton Jacobi Bellman (HJB) equation which is an example of optimal control problem. We discuss the steps involved in modelling the HJB equation as it relates to mathematical finance by applying the Ito’s lemma and maximum principle theorem. By applying the LTM and dual theory, the resultant HJB equation is transformed to a linear Partial Differential Equation (PDE). Also, the Optimal Investment Strategy (OIS) and the optimal value function were obtained under the exponential utility function. Furthermore, some numerical results were also presented with observations that the OIS under exponential utility is directly proportional to the appreciation rate of the risky asset and inversely proportional to the instantaneous volatility, predetermined interest rate, risk averse coefficient. Finally, it was observed that the optimal fund size is an increasing function of the risk free interest rate. This result is consistent with some existing results.

Keywords: Legendre transformation method, Optimal investment strategy, Ito’s lemma, Hamilton Jacobi Bellman equation, Geometric Brownian motion, financial market.

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8558 An Overview of Georgia’s Economic Growth Since 2012: Current Status, Challenges, and Opportunities for Future Development

Authors: V. Benidze

Abstract:

After the Rose Revolution of 2003, Georgia has achieved an unparalleled socioeconomic success. However, economic growth since 2012 has been sluggish and certainly not enough to rapidly improve the county’s standard of living that still remains substantially low compared to that in developed nations. Recent poor economic performance has shown that some key challenges need to be addressed if Georgia is to achieve high future economic growth that will decrease the poverty rate and create a middle class in the country. This paper offers in detail analysis of the economic performance of Georgia since 2012 and identifies key challenges facing the country’s economy. The main challenge going forward will be transforming Georgia from a consumption-driven to a production-oriented economy. It is identified that mobilizing domestic investment through savings, attracting foreign investment in tradable sectors and expanding the country’s export base will be crucial in the facilitation of the above-mentioned structural transformation. As the outcome of the research, the paper suggests a strategy for accelerating Georgia’ future economic growth and offers recommendations based on the relevant conclusions.

Keywords: Challenges, development, economic growth, economic policy, Georgia.

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8557 Allometric Models for Biomass Estimation in Savanna Woodland Area, Niger State, Nigeria

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

Abstract:

The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. F-test values for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: Allometriy, biomass, carbon stock, model, regression equation, woodland, inventory.

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8556 Shadow Detection for Increased Accuracy of Privacy Enhancing Methods in Video Surveillance Edge Devices

Authors: F. Matusek, G. Pujolle, R. Reda

Abstract:

Shadow detection is still considered as one of the potential challenges for intelligent automated video surveillance systems. A pre requisite for reliable and accurate detection and tracking is the correct shadow detection and classification. In such a landscape of conditions, privacy issues add more and more complexity and require reliable shadow detection. In this work the intertwining between security, accuracy, reliability and privacy is analyzed and, accordingly, a novel architecture for Privacy Enhancing Video Surveillance (PEVS) is introduced. Shadow detection and masking are dealt with through the combination of two different approaches simultaneously. This results in a unique privacy enhancement, without affecting security. Subsequently, the methodology was employed successfully in a large-scale wireless video surveillance system; privacy relevant information was stored and encrypted on the unit, without transferring it over an un-trusted network.

Keywords: Video Surveillance, Intelligent Video Surveillance, Physical Security, WSSU, Privacy, Shadow Detection.

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8555 A System to Adapt Techniques of Text Summarizing to Polish

Authors: Marcin Ciura, Damian Grund, S

Abstract:

This paper describes a system, in which various methods of text summarizing can be adapted to Polish. A structure of the system is presented. A modular construction of the system and access to the system via the Internet are signaled.

Keywords: Automatic summary generation, linguistic analysis, text generation.

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8554 An E-Retailing System Architecture Based on Cloud Computing

Authors: Chanchai Supaartagorn

Abstract:

E-retailing is the sale of goods online that takes place over the Internet. The Internet has shrunk the entire World. World eretailing is growing at an exponential rate in the Americas, Europe and Asia. However, e-retailing costs require expensive investment, such as hardware, software, and security systems. Cloud computing technology is internet-based computing for the management and delivery of applications and services. Cloud-based e-retailing application models allow enterprises to lower their costs with their effective implementation of e-retailing activities. In this paper, we describe the concept of cloud computing and present the architecture of cloud computing, combining the features of e-retailing. In addition, we propose a strategy for implementing cloud computing with e-retailing. Finally, we explain the benefits from the architecture.

Keywords: Architecture, cloud computing, e-retailing, internet-based.

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8553 The Hybrid Dimming Control System for Solar Charging Robot

Authors: A. Won-Yong Chae, B. Hyung-Nam Kim, C. Kyoung-Jun Lee, D. Hee-Je Kim

Abstract:

The renewable energy has been attracting attention as a new alternative energy due to the problem of environmental pollution and resource depletion. In particular, daylighting and PV system are regarded as the solutions. In this paper, the hybrid dimming control system supplied by solar cell and daylighting system was designed. Daylighting system is main source and PV system is spare source. PV system operates the LED lamp which supports daylighting system because daylighting system is unstable due to the variation of irradiance. In addition, PV system has a role charging batteries. Battery charging has a benefit that PV system operate LED lamp in the bad weather. However, LED lamp always can`t turn on that-s why dimming control system was designed. In particular, the solar charging robot was designed to check the interior irradiance intensity. These systems and the application of the solar charging robot are expected to contribute developing alternative energy in the near future.

Keywords: Daylighting system, PV system, LED lamp, Suntracking robot.

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8552 The Prospective Assessment of Zero-Energy Dwellings

Authors: Jovana Dj. Jovanovic, Svetlana M. Stevovic

Abstract:

The highest priority of so called, projected passive houses is to meet the appropriate energy demand. Every single material and layer which is injected into a dwelling has a certain energy quantity stored. The passive houses include optimized insulation levels with minimal thermal bridges, minimum of air leakage through the building, utilization of passive solar and internal gains, and good circulation of air which leans on mechanical ventilation system. The focus of this paper is on passive house features, benefits and targets, their feasibility and energy demands which are set up during each project. Numerous passive house-standards outline the very significant role of zero-energy dwellings towards the modern label of sustainable development. It is clear that the performance of both built and existing housing stock must be addressed if the population across the world sets out the energy objectives. This scientific article examines passive house features since the many passive house cases are launched.

Keywords: Benefits, energy demands, passive houses, sustainable development.

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8551 Computer-Aided Classification of Liver Lesions Using Contrasting Features Difference

Authors: Hussein Alahmer, Amr Ahmed

Abstract:

Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, Fuzzy c means, Liver segmentation.

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