Search results for: project approach

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events is important to improve safety and reliability of machine operations and reduce losses caused by failures. Improper set-ups or aligning of parts often leads to severe problems in many machines. The construction of prediction models for predicting faulty conditions is quite essential in making decisions on when to perform machine maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of machine measurement data. The calibration model is used to predict two faulty conditions from historical reference data. This approach utilizes genetic algorithms (GA) based variable selection, and we evaluate the predictive performance of several prediction methods using real data. The results shows that the calibration model based on supervised probabilistic principal component analysis (SPPCA) yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: Prediction, operation monitoring, on-line data, nonlinear statistical methods, empirical model.

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Authors: Yew Mun Hung, Ching Sze Lim, Tiew Wei Ting, Ningqun Guo

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The effect of streamwise conduction on the thermal characteristics of forced convection for nanofluidic flow in rectangular microchannel heat sinks under isothermal wall has been investigated. By applying the fin approach, models with and without streamwise conduction term in the energy equation were developed for hydrodynamically and thermally fully-developed flow. These two models were solved to obtain closed form analytical solutions for the nanofluid and solid wall temperature distributions and the analysis emphasized details of the variations induced by the streamwise conduction on the nanofluid heat transport characteristics. The effects of the Peclet number, nanoparticle volume fraction, thermal conductivity ratio on the thermal characteristics of forced convection in microchannel heat sinks are analyzed. Due to the anomalous increase in the effective thermal conductivity of nanofluid compared to its base fluid, the effect of streamwise conduction is expected to be more significant. This study reveals the significance of the effect of streamwise conduction under certain conditions of which the streamwise conduction should not be neglected in the forced convective heat transfer analysis of microchannel heat sinks.

Keywords: fin approach, microchannel heat sink, nanofluid, streamwise conduction

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Authors: Gelareh Mohammadi, Parisa Shoushtari, Behnam Molaee Ardekani, Mohammad B. Shamsollahi

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A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

Keywords: Person Identification, Autoregressive Model, EEG, Neural Network

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Authors: Kanso Hassan, Elhore Ali, Soule-dupuy Chantal, Tazi Said

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Information Retrieval has the objective of studying models and the realization of systems allowing a user to find the relevant documents adapted to his need of information. The information search is a problem which remains difficult because the difficulty in the representing and to treat the natural languages such as polysemia. Intentional Structures promise to be a new paradigm to extend the existing documents structures and to enhance the different phases of documents process such as creation, editing, search and retrieval. The intention recognition of the author-s of texts can reduce the largeness of this problem. In this article, we present intentions recognition system is based on a semi-automatic method of extraction the intentional information starting from a corpus of text. This system is also able to update the ontology of intentions for the enrichment of the knowledge base containing all possible intentions of a domain. This approach uses the construction of a semi-formal ontology which considered as the conceptualization of the intentional information contained in a text. An experiments on scientific publications in the field of computer science was considered to validate this approach.

Keywords: Information research, text analyzes, intentionalstructure, segmentation, ontology, natural language processing.

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Authors: Orhan Çoban, Nuryağdı Rozıyev, Fehmi Karasioğlu

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Sustainable development is one of the most debated issues, recently. In terms of providing more livable Earth continuity, while Production activities are going on, on the other hand protecting the environment has importance. As a strategy for sustainable development, eco-innovation is the application of innovations to reduce environmental burdens. Endeavors to understand ecoinnovation processes have been affected from environmental economics and innovation economics from neoclassical economics, and evolutionary economics other than neoclassical economics. In the light of case study analyses, this study aims to display activities in this field through case studies after explaining the theoretical framework of eco-innovations. This study consists of five sections including introduction and conclusion. In the second part of the study identifications of the concepts related with eco-innovation are described and eco-innovations are classified. Third section considers neoclassical and evolutionary approaches from neoclassical economics and evolutionary economics, respectively. Fourth section gives the case studies of successful eco-innovations. Last section is the conclusion part and offers suggestions for future eco-innovation research according to the theoretical framework and the case studies.

Keywords: Sustainable Development, Innovation, Ecoinnovation, Neoclassical Approach, Evolutionary Approach, Case Studies

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Authors: Abdallah S. Abdallah, A. Lynn Abbott, Mohamad Abou El-Nasr

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This paper presents a new technique for detection of human faces within color images. The approach relies on image segmentation based on skin color, features extracted from the two-dimensional discrete cosine transform (DCT), and self-organizing maps (SOM). After candidate skin regions are extracted, feature vectors are constructed using DCT coefficients computed from those regions. A supervised SOM training session is used to cluster feature vectors into groups, and to assign “face" or “non-face" labels to those clusters. Evaluation was performed using a new image database of 286 images, containing 1027 faces. After training, our detection technique achieved a detection rate of 77.94% during subsequent tests, with a false positive rate of 5.14%. To our knowledge, the proposed technique is the first to combine DCT-based feature extraction with a SOM for detecting human faces within color images. It is also one of a few attempts to combine a feature-invariant approach, such as color-based skin segmentation, together with appearance-based face detection. The main advantage of the new technique is its low computational requirements, in terms of both processing speed and memory utilization.

Keywords: Face detection, skin color segmentation, self-organizingmap.

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Authors: Sophie Sturup

Abstract:

Mega urban transport projects (MUTPs) are increasingly being used in urban environments to ameliorate the problem of congestion. However, a number of problems with regard to mega projects have been identified. In particular the seemingly institutionalised over estimation of economic benefits and persistent cost over runs, could mean that the wrong projects are selected, and that the projects that are selected cost more than they should. Studies to date have produced a number of solutions to these problems, perhaps most notably, the various methods for the inclusion of the private sector in project provision. However the problems have shown significant intractability in the face of these solutions. This paper provides a detailed examination of some of the problems facing mega projects and then examines Foucault-s theory of 'governmentality' as a possible frame of analysis which might shed light on the intractability of the problems that have been identified, through an identification of the art of government in which MUTPs occur.

Keywords: Michel Foucault, Governmentality, Mega projects, Transport.

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Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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Authors: Ramli Nazir, Hossein Moayedi

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Soil confinement systems serve as effective solutions to any erosion control project. Various confinements systems, namely triangular, circular and rectangular with the size of 50, 100, and 150 mm, and with a depth of 10 mm, were embedded in soil samples at slope angle of 60°. The observed soil mass losses for the confined soil systems were much smaller than those from unconfined system. As a result, the size of confinement and rainfall intensity have a direct effect on the soil mass loss. The triangular and rectangular confinement systems showed the lowest and highest soil loss masses, respectively. The slopes also failed much faster in the unconfined system than in the confined slope.

Keywords: Erosion control, Soil confinement, Soil erosion, Slope stability.

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

Abstract:

Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: Pollen recognition, logistic model tree, expectation-maximization, local binary pattern.

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Authors: Jing-ran Lin, Qi-cong Peng, Huai-zong Shao

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The performance of adaptive beamforming degrades substantially in the presence of steering vector mismatches. This degradation is especially severe in the near-field, for the 3-dimensional source location is more difficult to estimate than the 2-dimensional direction of arrival in far-field cases. As a solution, a novel approach of near-field robust adaptive beamforming (RABF) is proposed in this paper. It is a natural extension of the traditional far-field RABF and belongs to the class of diagonal loading approaches, with the loading level determined based on worst-case performance optimization. However, different from the methods solving the optimal loading by iteration, it suggests here a simple closed-form solution after some approximations, and consequently, the optimal weight vector can be expressed in a closed form. Besides simplicity and low computational cost, the proposed approach reveals how different factors affect the optimal loading as well as the weight vector. Its excellent performance in the near-field is confirmed via a number of numerical examples.

Keywords: Robust adaptive beamforming (RABF), near-field, steering vector mismatches, diagonal loading, worst-case performanceoptimization.

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Authors: Murat Gunduz, Mohanad H. A. AbuHassan

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Construction industry mainly focuses on the superstructure, infrastructure, and oil and gas industry. The development of infrastructure projects in developing countries attracted a lot of foreign construction contractors, consultants, suppliers and diversified workforce to interfere and to be evolved in such huge investment. Reducing worksite delays in such projects require knowledge and attention. Therefore, it is important to identify the influencing delay attributes affecting construction projects. The significant project factors affecting construction delays were investigated. Data collection was carried out through an online web survey system to capture significant factors. Significant factors were determined with importance index and relevant recommendations are made. The output of the data analysis would lead the industry experts better assess the impact of construction delays on construction projects.

Keywords: Construction industry, delays, importance index.

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Authors: Raghad Jawad Ahmed

Abstract:

Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Keywords: Color image segmentation, Genetic algorithm, Markov random field, Scale space filter.

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Authors: Sami Baraketi, Jean-Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision making, management and planning of healthcare and related activities. However, user resistances, unique position of medical data content and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. Success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose a HA process model with features from rational unified process (RUP) model and agile methodology.

Keywords: Agile methodology, health analytics, unified process model, UML.

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Authors: Ahmad Sharieh, R Bremananth

Abstract:

Artificial Intelligence based gaming is an interesting topic in the state-of-art technology. This paper presents an automation of a tradition Omani game, called Al-Hawalees. Its related issues are resolved and implemented using artificial intelligence approach. An AI approach called mini-max procedure is incorporated to make a diverse budges of the on-line gaming. If number of moves increase, time complexity will be increased in terms of propositionally. In order to tackle the time and space complexities, we have employed a back propagation neural network (BPNN) to train in off-line to make a decision for resources required to fulfill the automation of the game. We have utilized Leverberg- Marquardt training in order to get the rapid response during the gaming. A set of optimal moves is determined by the on-line back propagation training fashioned with alpha-beta pruning. The results and analyses reveal that the proposed scheme will be easily incorporated in the on-line scenario with one player against the system.

Keywords: Artificial neural network, back propagation gaming, Leverberg-Marquardt, minimax procedure.

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Authors: Giuliano Raimondo, Jörg Wangemann, Peer Drechsel

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In systems development involving Fuel Cells generators, it is important to have from an early stage of the project a dynamic model for the electrical behavior of the stack to be shared between involved development parties. It allows independent and early design and tests of fuel cell related power electronic. This paper presents an empirical Fuel Cell system model derived from characterization tests on a real system. Moreover, it is illustrated how the obtained model is used to build and validate a real-time Fuel Cell system emulator which is used for aerospace electrical integration testing activities.

Keywords: Fuel cell dynamics, real time simulation, fuel cell, modelling, testing.

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Authors: Fetoon K. Algarawi, Wejdan A. Alslamah, Ahlam A. Alhabib, Afnan S. Alfehaid, Dina M. Ibrahim

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Over the past 20 years, technology was rapidly developed and no one expected what will come next. Advancements in technology open new opportunities for immersive learning environments. There is a need to transmit education to a level that makes it more effective for the student. Augmented reality is one of the most popular technologies these days. This paper is an experience of applying Augmented Reality (AR) technology using a marker-based approach in E-learning system to transmitting virtual objects into the real-world scenes. We present a marker-based approach for transmitting virtual objects into real-world scenes to explain information in a better way after we developed a mobile phone application. The mobile phone application was then tested on students to determine the extent to which it encouraged them to learn and understand the subjects. In this paper, we talk about how the beginnings of AR, the fields using AR, how AR is effective in education, the spread of AR these days and the architecture of our work. Therefore, the aim of this paper is to prove how creating an interactive e-learning system using AR technology will encourage students to learn more.

Keywords: Augmented reality, e-learning, marker-based, monitor-based.

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Authors: Reza Ziaie Moayed, Hamidreza Rahmani

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Today, with developments in science and technology, there is an excessive potential for the use of nanomaterials in various fields of geotechnical project such as soil stabilization. This study investigates the effect of Nano-SiO₂ solution on the unconfined compression strength and Young's elastic modulus of Kaolinite. For this purpose, nano-SiO₂ was mixed with kaolinite in five different contents: 1, 2, 3, 4 and 5% by weight of the dry soil and a series of the unconfined compression test with curing time of one-day was selected as laboratory test. Analyses of the tests results show that stabilization of kaolinite with Nano-SiO₂ solution can improve effectively the unconfined compression strength of modified soil up to 1.43 times compared to  the pure soil.

Keywords: Kaolinite, nano-SiO2, stabilization, unconfined compression test, Young's modulus.

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Authors: Moulay A. Akhloufi

Abstract:

In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques are designed for static cameras environments. When the camera is moving, tracking moving objects become more difficult and many techniques fail to detect and track the desired targets. The problem becomes more complex when we want to track a specific object in real-time using a moving Pan and Tilt camera system to keep the target within the image. This type of tracking is of high importance in surveillance applications. When a target is detected at a certain zone, the possibility of automatically tracking it continuously and keeping it within the image until action is taken is very important for security personnel working in very sensitive sites. This work presents a real-time tracking system permitting the detection and continuous tracking of targets using a Pan and Tilt camera platform. A novel and efficient approach for dealing with occlusions is presented. Also a new intelligent forget factor is introduced in order to take into account target shape variations and avoid learning non desired objects. Tests conducted in outdoor operational scenarios show the efficiency and robustness of the proposed approach.

Keywords: Tracking, surveillance, target detection, Pan and tilt.

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Authors: Jayendra Krishna, Laxmi Srivastava

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Power flow (PF) study, which is performed to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state operating condition of a system, is very important and is the most frequently carried out study by power utilities for power system planning, operation and control. In this paper, a counterpropagation neural network (CPNN) is proposed to solve power flow problem under different loading/contingency conditions for computing bus voltage magnitudes and angles of the power system. The counterpropagation network uses a different mapping strategy namely counterpropagation and provides a practical approach for implementing a pattern mapping task, since learning is fast in this network. The composition of the input variables for the proposed neural network has been selected to emulate the solution process of a conventional power flow program. The effectiveness of the proposed CPNN based approach for solving power flow is demonstrated by computation of bus voltage magnitudes and voltage angles for different loading conditions and single line-outage contingencies in IEEE 14-bus system.

Keywords: Admittance matrix, counterpropagation neural network, line outage contingency, power flow

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Authors: Hajar Aman Key Yekani, Yusra Mushtaq, Behnaz Farahani, Hamed Abdi

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This study explores associations between parental restriction and children's appetitive traits, putting to test the hypothesis that parental “restriction” is associated with having a child with stronger food approach tendencies (food enjoyment (FE) and food over responsiveness (FR)). The participants, from 55 nationalities, targeting 1081 parents of 5- to 11-year-old children from 7 private schools in Dubai, UAE, who completed self-reported questionnaires over the 2011-2012 school year. The questionnaire has been a tailored amalgamation of CEBQ and CFQ in order to measure the children’s appetitive traits and parental restriction, respectively. The findings of this quantitative, descriptive, cross-sectional analysis confirmed the hypothesis in that “parental restriction” was positively associated with child food responsiveness (r, 0.183), food enjoyment (r, 0.102). To conclude, as far as the figures depict, the parents controlling their children’s food intake would seemingly a reverse impact on their eating behavior in the short term.

Keywords: Parental Restriction, Children Eating Behavior, Approach Tendency, Avoidance Tendency.

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Authors: Muhammad Javed, Yalemisew M. Abgaz, Claus Pahl

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Ontology-based modelling of multi-formatted software application content is a challenging area in content management. When the number of software content unit is huge and in continuous process of change, content change management is important. The management of content in this context requires targeted access and manipulation methods. We present a novel approach to deal with model-driven content-centric information systems and access to their content. At the core of our approach is an ontology-based semantic annotation technique for diversely formatted content that can improve the accuracy of access and systems evolution. Domain ontologies represent domain-specific concepts and conform to metamodels. Different ontologies - from application domain ontologies to software ontologies - capture and model the different properties and perspectives on a software content unit. Interdependencies between domain ontologies, the artifacts and the content are captured through a trace model. The annotation traces are formalised and a graph-based system is selected for the representation of the annotation traces.

Keywords: Consistent Content Management, Impact Categorisation, Trace Model, Ontology Evolution

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Authors: Dag A.H. Samuelsen, Olaf H. Graven

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Introducing Electromagnetic Interference and Electromagnetic Compatibility, or “The Art of Black Magic", for engineering students might be a terrifying experience both for students and tutors. Removing the obstacle of large, expensive facilities like a fully fitted EMC laboratory and hours of complex theory, this paper demonstrates a design of a laboratory setup for student exercises, giving students experience in the basics of EMC/EMI problems that may challenge the functionality and stability of embedded system designs. This is done using a simple laboratory installation and basic measurement equipment such as a medium cost digital storage oscilloscope, at the cost of not knowing the exact magnitude of the noise components, but rather if the noise is significant or not, as well as the source of the noise. A group of students have performed a trial exercise with good results and feedback.

Keywords: EMC, EMI, engineering project, student laboratory.

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Authors: Siyu Wang, Anthony Ward

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Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Keywords: Emotional intelligence, EI, Group EI, multi-method research, teamwork.

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Authors: Ali Kheyroddin, Niloufar Mashhadiali, Frazaneh Kheyroddin

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In last decades, tubular systems employed for tall buildings were efficient structural systems. However, increasing the height of a building leads to an increase in structural material corresponding to the loads imposed by lateral loads. Based on this approach, new structural systems are emerging to provide strength and stiffness with the minimum premium for height. In this research, selected tube-type structural systems such as framed tubes, braced tubes, diagrids and hexagrid systems were applied as a single tube, tubular structures combined with braced core and outrigger trusses on a set of 48, 72, and 96-story, respectively, to improve integrated structural systems. This paper investigated structural material consumption by model structures focusing on the premium for height. Compared analytical results indicated that as the height of the building increased, combination of the structural systems caused the framed tube, hexagrid and braced tube system to pay fewer premiums to material tonnage while in diagrid system, combining the structural system reduced insignificantly the steel material consumption.

Keywords: Braced tube, diagrid, framed tube, hexagrid.

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Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar

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The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.

Keywords: 4G, QC-LDPC, CDMA, IDMA.

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: Algorithm recommendation, meta-learning, bioinformatics, hierarchical classification.

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Authors: K. A. Kydyrbayev, B.N. Zhubatova, G.E. Nadirova, A.A. Mustafayeva

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Transliteration is frequently used especially in writing geographic denominations, personal names (onyms) etc. Proper names (onyms) of all languages must sound similarly in translated works as well as in scientific projects and works written in mother tongue, because we can get introduced with the nation, its history, culture, traditions and other spiritual values through the onyms of that nation. Therefore it is necessary to systematize the different transliterations of onyms of foreign languages. This paper is dedicated to the problem of making the project of transliterating Kazakh onyms into Arabic. In order to achieve this goal we use scientific or practical types of transliteration. Because in this type of transliteration provides easy reading writing source language's texts in the target language without any diacritical symbols, it is limited by the target language's alphabetic system.

Keywords: The Arabic, Kazakh languages, onyms, transliterating

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Authors: Sanjeev Gupta, Mayank Dave

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The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.

Keywords: Cluster head, data reliability, real time communication, wireless sensor networks.

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