Search results for: traditional approach

Authors: Khalid Minaoui, Thierry Chonavel, Benayad Nsiri, Driss Aboutajdine

Abstract:

This paper deals with efficient quadrature formulas involving functions that are observed only at fixed sampling points. The approach that we develop is derived from efficient continuous quadrature formulas, such as Gauss-Legendre or Clenshaw-Curtis quadrature. We select nodes at sampling positions that are as close as possible to those of the associated classical quadrature and we update quadrature weights accordingly. We supply the theoretical quadrature error formula for this new approach. We show on examples the potential gain of this approach.

Keywords: Gauss-Legendre, Clenshaw-Curtis, quadrature, Peano kernel, irregular sampling.

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Authors: Hazem M. El-Bakry, Nikos Mastorakis

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Fast forecasting of stock market prices is very important for strategic planning. In this paper, a new approach for fast forecasting of stock market prices is presented. Such algorithm uses new high speed time delay neural networks (HSTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented HSTDNNs is less than that needed by traditional time delay neural networks (TTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Forecasting, Stock Market Prices, Time Delay NeuralNetworks, Cross Correlation, Frequency Domain.

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Authors: Zviad Ghadua, Biswa Bhattacharya

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The Flash Flood Guidance (FFG) provides the rainfall amount of a given duration necessary to cause flooding. The approach is based on the development of rainfall-runoff curves, which helps us to find out the rainfall amount that would cause flooding. An alternative approach, mostly experimented with Italian Alpine catchments, is based on determining threshold discharges from past events and on finding whether or not an oncoming flood has its magnitude more than some critical discharge thresholds found beforehand. Both approaches suffer from large uncertainties in forecasting flash floods as, due to the simplistic approach followed, the same rainfall amount may or may not cause flooding. This uncertainty leads to the question whether a probabilistic model is preferable over a deterministic one in forecasting flash floods. We propose the use of a Bayesian probabilistic approach in flash flood forecasting. A prior probability of flooding is derived based on historical data. Additional information, such as antecedent moisture condition (AMC) and rainfall amount over any rainfall thresholds are used in computing the likelihood of observing these conditions given a flash flood has occurred. Finally, the posterior probability of flooding is computed using the prior probability and the likelihood. The variation of the computed posterior probability with rainfall amount and AMC presents the suitability of the approach in decision making in an uncertain environment. The methodology has been applied to the Posina basin in Italy. From the promising results obtained, we can conclude that the Bayesian approach in flash flood forecasting provides more realistic forecasting over the FFG.

Keywords: Flash flood, Bayesian, flash flood guidance, FFG, forecasting, Posina.

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Authors: Ramin Halavati, Mansour Jamzad, Mahdieh Soleymani

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Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in cases that the words where chosen from a prespecified list.

Keywords: Image Processing, Pattern Recognition.

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Authors: Victoria C. Valdebenito

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Located within the context of accelerating globalization in the 21^st-century knowledge society, this paper focuses on one selected university in Chile at which radical curriculum policy changes have been taking place, diverging from the traditional curriculum in Chile at the undergraduate level as a section of a larger investigation. Using a ‘policy trajectory’ framework, and guided by the interpretivist approach to research, interview transcripts and institutional documents were analyzed in relation to the meso (university administration) and the micro (academics) level. Inside the case study, participants from the university administration and academic levels were selected both via snow-ball technique and purposive selection, thus they had different levels of seniority, with some participating actively in the curriculum reform processes. Guided by an interpretivist approach to research, documents and interview transcripts were analyzed to reveal major themes emerging from the data. A further ‘bigger picture’ analysis guided by critical theory was then undertaken, involving interrogation of underlying ideologies and how political and economic interests influence the cultural production of policy. The case-study university was selected because it represents a traditional and old case of university setting in the country, undergoing curriculum changes based on international trends such as the competency model and the liberal arts. Also, it is representative of a particular socioeconomic sector of the country. Access to the university was gained through email contact. Qualitative research methods were used, namely interviews and analysis of institutional documents. In all, 18 people were interviewed. The number was defined by when the saturation criterion was met. Semi-structured interview schedules were based on the four research questions about influences, policy texts, policy enactment and longer-term outcomes. Triangulation of information was used for the analysis. While there was no intention to generalize the specific findings of the case study, the results of the research were used as a focus for engagement with broader themes, often evident in global higher education policy developments. The research results were organized around major themes in three of the four contexts of the ‘policy trajectory’. Regarding the context of influences and the context of policy text production, themes relate to hegemony exercised by first world countries’ universities in the higher education field, its associated neoliberal ideology, with accountability and the discourse of continuous improvement, the local responses to those pressures, and the value of interdisciplinarity. Finally, regarding the context of policy practices and effects (enactment), themes emerged around the impacts of the curriculum changes on university staff, students, and resistance amongst academics. The research concluded with a few recommendations that potentially provide ‘food for thought’ beyond the localized settings of this study, as well as possibilities for further research.

Keywords: Curriculum, policy, higher education, global-local dynamics.

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Authors: Vinod Kumar, Jatinder Kumar

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The use of hard and brittle material has become increasingly more extensive in recent years. Therefore processing of these materials for the parts fabrication has become a challenging problem. However, it is time-consuming to machine the hard brittle materials with the traditional metal-cutting technique that uses abrasive wheels. In addition, the tool would suffer excessive wear as well. However, if ultrasonic energy is applied to the machining process and coupled with the use of hard abrasive grits, hard and brittle materials can be effectively machined. Ultrasonic machining process is mostly used for the brittle materials. The present research work has developed models using finite element approach to predict the mechanical stresses sand strains produced in the tool during ultrasonic machining process. Also the flow behavior of abrasive slurry coming out of the nozzle has been studied for simulation using ANSYS CFX module. The different abrasives of different grit sizes have been used for the experimentation work.

Keywords: Stress, MRR, Flow, Ultrasonic Machining

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Authors: M. Mlhem

Abstract:

Geotechnical engineers face many problematic soils upon construction and they have the choice for replacing these soils with more appropriate soils or attempting to improve the engineering properties of the soil through a suitable soil stabilization technique. Mostly, improving soils is environmental, easier and more economical than other solutions. Stabilization soils technique is applied by introducing a cementing agent or by injecting a substance to fill the pore volume. Chemical stabilizers are divided into two groups: traditional agents such as cement or lime and non-traditional agents such as polymers. This paper studies the effect of epoxy additives on the compression strength of four types of soil and then compares with the effect of cement on the compression strength for the same soils. Overall, the epoxy additives are more effective in increasing the strength for different types of soils regardless its classification. On the other hand, there was no clear relation between studied parameters liquid limit, passing No.200, unit weight and between the strength of samples for different types of soils.

Keywords: Additives, clay, compression strength, epoxy, stabilization.

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Authors: Heung Seok Chae, Jaegeol Park

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Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.

Keywords: RFID middleware, Adaptive load balancing.

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Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

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With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: Location-based recommendation, map-reduce, recommendation system, trajectory search.

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Authors: Liudmyla Koliechkina, Olena Dvirna

Abstract:

The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps.

Keywords: Discrete set, linear combinatorial optimization, multi-objective optimization, multipermutation, Pareto solutions, partial permutation set, permutation, structural graph.

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Authors: Costin Pribeanu

Abstract:

The model-based approach to user interface design relies on developing separate models capturing various aspects about users, tasks, application domain, presentation and dialog structures. This paper presents a task modeling approach for user interface design and aims at exploring mappings between task, domain and presentation models. The basic idea of our approach is to identify typical configurations in task and domain models and to investigate how they relate each other. A special emphasis is put on applicationspecific functions and mappings between domain objects and operational task structures. In this respect, we will address two layers in task decomposition: a functional (planning) layer and an operational layer.

Keywords: task modeling, user interface design, unit tasks, basic tasks, operational task model.

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Authors: Yinggan Tang, Xinping Guan

Abstract:

Color image segmentation can be considered as a cluster procedure in feature space. k-means and its adaptive version, i.e. competitive learning approach are powerful tools for data clustering. But k-means and competitive learning suffer from several drawbacks such as dead-unit problem and need to pre-specify number of cluster. In this paper, we will explore to use competitive and cooperative learning approach to perform color image segmentation. In competitive and cooperative learning approach, seed points not only compete each other, but also the winner will dynamically select several nearest competitors to form a cooperative team to adapt to the input together, finally it can automatically select the correct number of cluster and avoid the dead-units problem. Experimental results show that CCL can obtain better segmentation result.

Keywords: Color image segmentation, competitive learning, cluster, k-means algorithm, competitive and cooperative learning.

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Authors: M. Izvercianu, L. Ivascu

Abstract:

This paper presents an innovative computer system that contributes to sustainable development of the enterprise. The research refers to a rethinking of traditional systems of collaboration and risk assessment, present in any organization, leading to a sustainable enterprise. This concept integrates emerging tools that allow the implementation and exploitation of the collective intelligence of the enterprise, allowing the exchange of contextual, agile and simplified information, and collaboration with networks of customers and partners in an environment where risks are controlled. Risk assessment is done in a systemic way: the enterprise as the system compared to the contained departments and the enterprise as a subsystem compared to: families of international standards and sustainability-s responsibilities. The enterprise, in this systemic vision, responds to the requirements that any existing system to operate continuously in an indefinite future without reaching key resource depletion. The research is done by integrating collaborative science, engineering, management, psychology, obtaining thus a cornerstone of sustainable development of the enterprise.

Keywords: Enterprise 2.0, ISO, Risk management, Sustainable development

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Authors: Yue Zhao, Chao Li

Abstract:

Camera calibration is an important step in 3D reconstruction. Camera calibration may be classified into two major types: traditional calibration and self-calibration. However, a calibration method in using a checkerboard is intermediate between traditional calibration and self-calibration. A self is proposed based on a square in this paper. Only a square in the planar template, the camera self-calibration can be completed through the single view. The proposed algorithm is that the virtual circle and straight line are established by a square on planar template, and circular points, vanishing points in straight lines and the relation between them are be used, in order to obtain the image of the absolute conic (IAC) and establish the camera intrinsic parameters. To make the calibration template is simpler, as compared with the Zhang Zhengyou-s method. Through real experiments and experiments, the experimental results show that this algorithm is feasible and available, and has a certain precision and robustness.

Keywords: Absolute conic, camera calibration, circle point, vanishing point.

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Authors: S. Sieniutycz

Abstract:

This paper unifies power optimization approaches in various energy converters, such as: thermal, solar, chemical, and electrochemical engines, in particular fuel cells. Thermodynamics leads to converter-s efficiency and limiting power. Efficiency equations serve to solve problems of upgrading and downgrading of resources. While optimization of steady systems applies the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. In reacting systems chemical affinity constitutes a prevailing component of an overall efficiency, thus the power is analyzed in terms of an active part of chemical affinity. The main novelty of the present paper in the energy yield context consists in showing that the generalized heat flux Q (involving the traditional heat flux q plus the product of temperature and the sum products of partial entropies and fluxes of species) plays in complex cases (solar, chemical and electrochemical) the same role as the traditional heat q in pure heat engines. The presented methodology is also applied to power limits in fuel cells as to systems which are electrochemical flow engines propelled by chemical reactions. The performance of fuel cells is determined by magnitudes and directions of participating streams and mechanism of electric current generation. Voltage lowering below the reversible voltage is a proper measure of cells imperfection. The voltage losses, called polarization, include the contributions of three main sources: activation, ohmic and concentration. Examples show power maxima in fuel cells and prove the relevance of the extension of the thermal machine theory to chemical and electrochemical systems. The main novelty of the present paper in the FC context consists in introducing an effective or reduced Gibbs free energy change between products p and reactants s which take into account the decrease of voltage and power caused by the incomplete conversion of the overall reaction.

Keywords: Power yield, entropy production, chemical engines, fuel cells, exergy.

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Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The paper proposes an approach for design of modular systems based on original technique for modeling and formulation of combinatorial optimization problems. The proposed approach is described on the example of personal computer configuration design. It takes into account the existing compatibility restrictions between the modules and can be extended and modified to reflect different functional and users- requirements. The developed design modeling technique is used to formulate single objective nonlinear mixedinteger optimization tasks. The practical applicability of the developed approach is numerically tested on the basis of real modules data. Solutions of the formulated optimization tasks define the optimal configuration of the system that satisfies all compatibility restrictions and user requirements.

Keywords: Constrained discrete combinatorial choice, modular systems design, optimization problem, PC configuration.

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Authors: Khalid M. Aamir, Mohammad A. Maud

Abstract:

Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).

Keywords: Power Spectral Density (PSD), Wiener-KhintchineTheorem, Periodogram, Short Time Fourier Transform (STFT), TheSliding DFT.

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Authors: Ahmad T. Al-Taani, Abdullah M. AL-Issa

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In this work we propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by dividing the cover into blocks of equal sizes and then embeds the message in the edge of the block depending on the number of ones in left four bits of the pixel. The proposed approach is tested on a database consists of 100 different images. Experimental results, compared with other methods, showed that the proposed approach hide more large information and gave a good visual quality stego-image that can be seen by human eyes.

Keywords: Data Embedding, Cryptography, Watermarking, Steganography, Least Significant Bit, Information Hiding.

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Authors: Darren Zou

Abstract:

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: Bayesian, Forecast, Stock, BART.

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Authors: J. P. Dubois

Abstract:

Pulse code modulation is a widespread technique in digital communication with significant impact on existing modern and proposed future communication technologies. Its widespread utilization is due to its simplicity and attractive spectral characteristics. In this paper, we present a new approach to the spectral analysis of PCM signals using Riemann-Stieltjes integrals, which is very accurate for high bit rates. This approach can serve as a model for similar spectral analysis of other competing modulation schemes.

Keywords: Coding, discrete Fourier, power spectral density, pulse code modulation, Riemann-Stieltjes integrals.

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Authors: Keun-Chang Kwak

Abstract:

This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.

Keywords: Motion recognition, fuzzy wavelet packet, Vicon physical data.

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Authors: Rosie Borup, Hanifa Shah

Abstract:

This paper aims to describe how student satisfaction is measured for work-based learners as these are non-traditional learners, conducting academic learning in the workplace, typically their curricula have a high degree of negotiation, and whose motivations are directly related to their employers- needs, as well as their own career ambitions. We argue that while increasing WBL participation, and use of SSD are both accepted as being of strategic importance to the HE agenda, the use of WBL SSD is rarely examined, and lessons can be learned from the comparison of SSD from a range of WBL programmes, and increased visibility of this type of data will provide insight into ways to improve and develop this type of delivery. The key themes that emerged from the analysis of the interview data were: learners profiles and needs, employers drivers, academic staff drivers, organizational approach, tools for collecting data and visibility of findings. The paper concludes with observations on best practice in the collection, analysis and use of WBL SSD, thus offering recommendations for both academic managers and practitioners.

Keywords: Student satisfaction data, work based learning, employer engagement, NSS.

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

Abstract:

The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: Data management, digitization, Industry 4.0, knowledge engineering, metamodel.

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Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed

Abstract:

In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.

Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.

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Authors: Bekim Avdiaj

Abstract:

Everyday life is and will be influenced depending on the developments that society undergoes throughout the history. Particularly, countries undergoing transition from one system to another sustain the greatest impact in trying to embrace the modern system. Kosovo society had the fortune to experience a change, which began in late 1999 to continue up to date. One of the 'developments' of the time with the evolution in Kosovo society was the transition from the traditional education system into the modern one. This transformation began immediately after the war, to continue even today. It was started by internationals, which governed and administered Kosovo society, including education. There was a great 'evolution', because almost the entire system was 'changed'. Among other things, for the first time it was enabled the opening of private schools from the lowest level up to the colleges and universities. This paper will address: how much was ready the society to embrace such a 'cultural' change in education, respectively, how much were prepared teachers for such changes; as it was actually thought to be a modern education system, how much was it according to international standards; what are the results and current situation in Kosovo education.

Keywords: Education, evolution, reform, transformation.

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Authors: Mohamed Abdel Fattah, Fuji Ren

Abstract:

This work proposes an approach to address automatic text summarization. This approach is a trainable summarizer, which takes into account several features, including sentence position, positive keyword, negative keyword, sentence centrality, sentence resemblance to the title, sentence inclusion of name entity, sentence inclusion of numerical data, sentence relative length, Bushy path of the sentence and aggregated similarity for each sentence to generate summaries. First we investigate the effect of each sentence feature on the summarization task. Then we use all features score function to train genetic algorithm (GA) and mathematical regression (MR) models to obtain a suitable combination of feature weights. The proposed approach performance is measured at several compression rates on a data corpus composed of 100 English religious articles. The results of the proposed approach are promising.

Keywords: Automatic Summarization, Genetic Algorithm, Mathematical Regression, Text Features.

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Authors: Tarek Elhasia, Bernd Noche, Lima Zhao

Abstract:

In recent years, sustainable supply chain management (SSCM) has been widely researched in academic domain. However, due to the traditional operational role and the complexity of supply chain management in the cement industry, a relatively small amount of research has been conducted on cement supply chain simulation integrated with sustainability criteria. This paper analyses the cement supply chain operations using the Push-Pull supply chain frameworks, the Life Cycle Assessment (LCA) methodology; and proposal integration approach, proposes three supply chain scenarios based on Make-To-Stock (MTS), Pack-To-Order (PTO) and Grind- To-Order (GTO) strategies. A Discrete-Event Simulation (DES) model of SSCM is constructed using Arena software to implement the three-target scenarios. We conclude with the simulation results that (GTO) is the optimal supply chain strategy that demonstrates the best economic, ecological and social performance in the cement industry.

Keywords: Cement industry, simulation, supply chain management (SCM), sustainability.

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Authors: Seema Singh, Puja Anand, Alok Bhasin

Abstract:

The interior design profession aims to create aesthetically pleasing design solutions for human habitats but of late, growing awareness about depleting environmental resources, both tangible and intangible, and damages to the eco-system led to the quest for creating healthy and sustainable interior environments. The paper proposes adapting traditionally produced organic wool textiles for the mainstream interior design industry. This can create sustainable livelihoods whereby eco-friendly bridges can be built between Interior designers and consumers and pastoral communities. This study focuses on traditional textiles produced by two pastoral communities from India that use organic wool from indigenous sheep varieties. The Gaddi communities of Himachal Pradesh use wool from the Gaddi sheep breed to create Pattu (a multi-purpose textile). The Kurumas of Telangana weave a blanket called the Gongadi, using wool from the Black Deccani variety of sheep. These communities have traditionally reared indigenous sheep breeds for their wool and produce hand-spun and hand-woven textiles for their own consumption, using traditional processes that are chemical free. Based on data collected personally from field visits and documentation of traditional crafts of these pastoral communities, and using traditionally produced indigenous organic wool, the authors have developed innovative textile samples by including design interventions and exploring dyeing and weaving techniques. As part of the secondary research, the role of pastoralism in sustaining the eco-systems of Himachal Pradesh and Telangana was studied, and also the role of organic wool in creating healthy interior environments. The authors found that natural wool from indigenous sheep breeds can be used to create interior textiles that have the potential to be marketed to an urban audience, and this will help create earnings for pastoral communities. Literature studies have shown that organic & sustainable wool can reduce indoor pollution & toxicity levels in interiors and further help in creating healthier interior environments. Revival of indigenous breeds of sheep can further help in rejuvenating dying crafts, and promotion of these indigenous textiles can help in sustaining traditional eco-systems and the pastoral communities whose way of life is endangered today. Based on research and findings, the authors propose that adapting traditional textiles can have potential for application in Interiors, creating eco-friendly spaces. Interior textiles produced through such sustainable processes can help reduce indoor pollution, give livelihood opportunities to traditional economies, and leave almost zero carbon foot-print while being in sync with available natural resources, hence ultimately benefiting the society. The win-win situation for all the stakeholders in this eco-friendly model makes it pertinent to re-think how we design lifestyle textiles for interiors. This study illustrates a specific example from the two pastoral communities and can be used as a model that can work equally well in any community, regardless of geography.

Keywords: Design Intervention, Eco-Friendly, Healthy Interiors, Indigenous, Organic Wool, Pastoralism, Sustainability.

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Authors: D. Fodorean, D.C. Popa, F. Jurca, M. Ruba

Abstract:

the paper presents the optimization results for several electrical machines dedicated for powered electric wheel-chairs. The optimization, using the Hook-Jeeves algorithm, was employed based on a design approach which takes into consideration the road conditions. Also, through numerical simulations (based on finite element method), the analytical approach was validated. The optimization approach gave satisfactory results and the best suited variant was chosen for the motorization of the wheel-chair.

Keywords: electrical machines, numerical validation, optimization, electric wheel chair.

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Authors: Colette Malyack, Pius Egbelu

Abstract:

Business-to-Customer (B2C) delivery options have improved to meet increased demand in recent years. The change in end users has forced logistics networks to focus on customer service and sentiment that would have previously been the priority of the company or organization of origin. This has led to increased pressure on logistics companies to extend traditional B2B networks into a B2C solution while accommodating additional costs, roadblocks, and customer sentiment; the result has been the creation of the omnichannel delivery network encompassing a number of traditional and modern methods of package delivery. In this paper the many solutions within the omnichannel delivery network are defined and discussed. It can be seen through this analysis that the omnichannel delivery network can be applied to reduce the complexity of package delivery and provide customers with more options. Applied correctly the result is a reduction in cost to the logistics company over time, even with an initial increase in cost to obtain the technology.

Keywords: Network planning, Last Mile Delivery, LMD, omnichannel delivery network, omnichannel logistics.

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