Search results for: simulation – based optimization.

Authors: Fabio Fabris, Alex A. Freitas

Abstract:

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: A. Ince

Abstract:

In this paper, an analytical simplified method for calculating elasto-plastic stresses strains of notched bodies subject to non-proportional loading paths is discussed. The method was based on the Neuber notch correction, which relates the incremental elastic and elastic-plastic strain energy densities at the notch root and the material constitutive relationship. The validity of the method was presented by comparing computed results of the proposed model against finite element numerical data of notched shaft. The comparison showed that the model estimated notch-root elasto-plastic stresses strains with good accuracy using linear-elastic stresses. The prosed model provides more efficient and simple analysis method preferable to expensive experimental component tests and more complex and time consuming incremental non-linear FE analysis. The model is particularly suitable to perform fatigue life and fatigue damage estimates of notched components subjected to nonproportional loading paths.

Keywords: Elasto-plastic, stress-strain, notch analysis, nonprortional loadings, cyclic plasticity, fatigue.

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Authors: A. Zanaz, S. Yotte, F. Fouchal, A. Chateauneuf

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This paper presents a methodology for probabilistic assessment of bearing capacity and prediction of failure mechanism of masonry vaults at the ultimate state with consideration of the natural variability of Young’s modulus of stones. First, the computation model is explained. The failure mode corresponds to the four-hinge mechanism. Based on this consideration, the study of a vault composed of 16 segments is presented. The Young’s modulus of the segments is considered as random variable defined by a mean value and a coefficient of variation. A relationship linking the vault bearing capacity to the voussoirs modulus variation is proposed. The most probable failure mechanisms, in addition to that observed in the deterministic case, are identified for each variability level as well as their probability of occurrence. The results show that the mechanism observed in the deterministic case has decreasing probability of occurrence in terms of variability, while the number of other mechanisms and their probability of occurrence increases with the coefficient of variation of Young’s modulus. This means that if a significant change in the Young’s modulus of the segments is proven, taking it into account in computations becomes mandatory, both for determining the vault bearing capacity and for predicting its failure mechanism.

Keywords: Masonry, mechanism, probability, variability, vault.

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Authors: Hamide Özyürek, Metin Yılmaz

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Standard processes, similar and limited production lines, the production of high direct costs will be more accurate than the use of parts of the traditional cost systems in the literature. However, direct costs, overhead expenses, in turn, decrease the burden of increasingly sophisticated production facilities, a situation that led the researchers to look for the cost of traditional systems of alternative techniques. Variety cost management approaches for example Total quality management (TQM), just-in-time (JIT), benchmarking, kaizen costing, targeting cost, life cycle costs (LLC), activity-based costing (ABC) value engineering have been introduced. Management and cost applications have changed over the past decade and will continue to change. Modern cost systems can provide relevant and accurate cost information. These methods provide the decisions about customer, product and process improvement. The aim of study is to describe and explain the adoption and application of costing systems in SME. This purpose reports on a survey conducted during 2014 small and medium sized enterprises (SME) in Ankara. The survey results were evaluated using SPSS18 package program.

Keywords: Cost Accounting, Costing, Modern Costing Systems, Managerial Accounting.

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Authors: Chng Pei Eng, Boon Yih Mah, Chng Pei Cheng

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In this cyber age, the job market has been rapidly transforming and being digitalized. Submitting a paper-based curriculum vitae (CV) nowadays does not grant a job seeker a high employability rate. This paper calls for attention on the creation of mobile Curriculum Vitae or m-CV (http://mcurriculumvitae. blogspot.com), a sample of an individual CV developed using weblog, which can enhance the job hunter especially fresh graduate-s higher marketability rate. This study is designed to identify the perceptions held by Malaysian university students regarding m-CV grounded on a modified Technology Acceptance Model (TAM). It measures the strength and the direction of relationships among three major variables – Perceived Ease of Use (PEOU), Perceived Usefulness (PU) and Behavioral Intention (BI) to use. The finding shows that university students generally accepted adopting m-CV since they perceived m-CV to be more useful rather than easy to use. Additionally, this study has confirmed TAM to be a useful theoretical model in helping to understand and explain the behavioral intention to use Web 2.0 application-weblog publishing their CV. The result of the study has underlined another significant positive value of using weblog to create personal CV. Further research of m-CV has been highlighted in this paper.

Keywords: CV, mobile curriculum vitae, Technology Acceptance Model, weblog

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Authors: Sahar Y. Al-Okbi, Doha A. Mohamed, Thanaa E. Hamed, Ahmed Ms Hussein

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In the present research, two nutraceuticals made from red grape and walnut that showed previously to improve kidney dysfunction were incorporated separately into functional foods' bread made from barley and rice bran. The functional foods were evaluated in rats in which chronic renal failure was induced through feeding diet rich in adenine and phosphate (APD). The evaluation based on assessing kidney function, oxidative stress, inflammatory biomarkers and body weight gain. Results showed induction of chronic kidney failure reflected in significant increase in plasma urea, creatinine, malondialdehyde, tumor necrosis factor- α and low density lipoprotein cholesterol along with significant reduction of plasma albumin, and total antioxidant and creatinine clearance and body weight gain on feeding APD compared to control healthy group. Feeding the functional foods produced amelioration in the different biochemical parameters and body weight gain indicating improvement in kidney function.

Keywords: Functional food, kidney dysfunction, rats.

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Authors: A. Reyes-Salazar, M. D. Llanes-Tizoc, E. Bojorquez, F. Valenzuela-Beltran, J. Bojorquez, J. R. Gaxiola-Camacho, A. Haldar

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Seismic analysis of steel buildings is usually based on the use of the concentrated mass (ML) matrix and the Rayleigh damping matrix (C). Similarly, the initial stiffness matrix (KO) and the first two modes associated to lateral vibrations are commonly used to develop the matrix C. The evaluation of the accuracy of these practices for the particular case of steel buildings with moment-resisting steel frames constitutes the main objective of this research. For this, the nonlinear seismic responses of three models of steel frames, representing low-, medium- and high-rise steel buildings, are considered. Results indicate that if the ML matrix is used, shears and bending moments in columns are underestimated by up to 30% and 65%, respectively, when compared to the corresponding results obtained with the consistent mass matrix (MC). It is also shown that if KO is used in C instead the tangent stiffness matrix (Kt), axial loads in columns are underestimated by up to 80%. It is concluded that the consistent mass matrix should be used in the structural modelling of moment resisting steel frames and the tangent stiffness matrix should be used to develop the Rayleigh damping matrix.

Keywords: Moment-resisting steel frames, consistent and concentrated mass matrices, nonlinear seismic response, Rayleigh damping.

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Authors: Elif Derya UBEYLI, Inan GULER

Abstract:

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

Keywords: Chaotic signal, Electroencephalogram (EEG) signals, Feature extraction/selection, Lyapunov exponents

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Authors: Jong Han Joo, Jeong Hun Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. However, the effects of echo path changes should be considered for eliminating the undesired echoes. We describe a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: Acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector.

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Authors: Tushar Vasant Salunkhe, Sariput M. Nawghare, Maheboobsab B. Nadaf, Sushovan Dutta, J. N. Mandal

Abstract:

The model tests were conducted in the laboratory without and with Plastic recycled polymer in fly ash steep slopes overlaying soft foundation soils like fly ash and powai soil in order to check the stability of steep slope. In this experiment, fly ash is used as a filling material and Plastic Recycled Polymers of diameter = 3mm and length = 4mm were made from waste plastic product (lower grade plastic product). The properties of fly ash and Plastic recycled polymers are determined. From the experiments, load and settlement have measured. From these data, load –settlement curves have reported. It has been observed from test results that load carrying capacity of mixture fly ash with Plastic Recycled Polymers slope is more than that of fly ash slope. The deformation of Plastic Recycled Polymers slope is slightly more than that of fly ash slope. A Finite Element Method (F.E.M.) was also evaluated using PLAXIS 3D version. The failure pattern, deformations and factor of safety are reported based on analytical programme. The results from experimental data and analytical programme are compared and reported.

Keywords: Fly ash, Plastic recycled polymer, Factor of safety, Finite element method (FEM), Bishop’s simplified method.

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Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

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The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

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Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

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Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

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Authors: Mingyang Sun, Guozheng Yan, Dasheng Liu, Lei Yang

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Driven by the demand of intelligent monitoring in rehabilitation centers or hospitals, a high accuracy real-time location system based on UWB (ultra-wideband) technology was proposed. The system measures precise location of a specific person, traces his movement and visualizes his trajectory on the screen for doctors or administrators. Therefore, doctors could view the position of the patient at any time and find them immediately and exactly when something emergent happens. In our design process, different algorithms were discussed, and their errors were analyzed. In addition, we discussed about a , simple but effective way of correcting the antenna delay error, which turned out to be effective. By choosing the best algorithm and correcting errors with corresponding methods, the system attained a good accuracy. Experiments indicated that the ranging error of the system is lower than 7 cm, the locating error is lower than 20 cm, and the refresh rate exceeds 5 times per second. In future works, by embedding the system in wearable IoT (Internet of Things) devices, it could provide not only physical parameters, but also the activity status of the patient, which would help doctors a lot in performing healthcare.

Keywords: Intelligent monitoring, IoT devices, real-time location, smart healthcare, ultra-wideband technology.

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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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Authors: Yi Yu, Vu Xuan Nguyen, Gaoxi Xiao

Abstract:

Opinion formation in complex social networks may exhibit complex system dynamics even when based on some simplest system evolution models. An interesting and important issue is the effects of the initial state on the final steady-state opinion distribution. By carrying out extensive simulations and providing necessary discussions, we show that, while different initial opinion distributions certainly make differences to opinion evolution in social systems without noises, in systems with noises, given enough time, different initial states basically do not contribute to making any significant differences in the final steady state. Instead, it is the basal distribution of the preferred opinions that contributes to deciding the final state of the systems. We briefly explain the reasons leading to the observed conclusions. Such an observation contradicts with a long-term belief on the roles of system initial state in opinion formation, demonstrating the dominating role that opinion mutation can play in opinion formation given enough time. The observation may help to better understand certain observations of opinion evolution dynamics in real-life social networks.

Keywords: Opinion formation, Deffuant model, opinion mutation, consensus making.

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Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

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The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: Data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background.

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Authors: Vahhab Attar Olyaee, Fouad Attar Olyaee

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Many IT projects come to failure because of having technical approach, focusing on the final product and lack of proper attention to strategic alignment. Project management models quite often have technical management view [4], [8], [13], [14]. These models focus greatly on the finalization of the project product and the delivery of the product to the customer. However, many project problems are due to lack of attention to the needs and capabilities of the organizations or disregarding how to deploy and use the product in the organization. In this regard, in the current research we are trying to present a solution with the purpose of raising the value of the project in an organization. This way, the project outputs will be properly deployed in the organization. Therefore, a comprehensive model is presented which takes into account the whole processes from initial step of project definition to the deployment of the final outputs in the organization and then the definition of all roles and responsibilities to put the model into practice. Taking into account the opinions of experts and project managers, to prove the performance of the model, the project problems were recognized and based on the model, categorized and analyzed. And at the end it is made clear that ignoring the proper definition of the project and not having a proper understanding of the expected value on the one hand and not supervising the emerged value in the process of production and installment are among the most important factors that bring a project to failure.

Keywords: IT Governance, Project Model, Roles and Responsibilities of Project

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Authors: C. Ardil

Abstract:

Multiple criteria decision making analysis (MCDMA) methods are applied to many real - life problems in different fields of engineering science and technology. The "preference analysis for reference ideal solution (PARIS)" method is proposed for an efficient MCDMA evaluation of decision problems. The multiple criteria aircraft evaluation approach is based on the integrated the mean weight, entropy weight, PARIS, and TOPSIS method, which eliminates the subjective importance weight assignment process. The evaluation criteria were identified from an extensive literature review of aircraft selection process. The aim of this study is to propose an efficient methodology for handling the aircraft selection process in which the proposed method solves effectively the MCDMA problem. A numerical example is presented to demonstrate the applicability and validity of the proposed MCDMA approach. 

Keywords: aircraft selection, aircraft, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS, VIKOR, ELECTRE, PROMETHEE

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Authors: J. Grasaesom, S. Thong-om, W. Payakcho, A. Oonsivilai, B. Marungsri

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This paper presents the experimental results on ageing deterioration of silicone rubber outdoor polymer insulator under salt water dip wheel test based on IEC 62217. In order to comparison effect of chemical contents, silicone rubber outdoor polymer insulators having same configuration and leakage distant from two manufactures were tested together continuously 30,000 test cycles. Many discharge activities were observed in during the test. After 30,000 test cycles, in spite of same configuration, differences in degree of surface aging were observed. Physical analysis such as decreasing in hydrophobicity and increasing in hardness measurement were measured on two-type tested specimen surface in order to confirm degree of surface ageing. Furthermore, chemical analysis by ATR-FTIR to diagnose the chemical change of tested specimen surface was conducted to confirm the physical analysis results.

Keywords: ageing of silicone rubber, salt water dip wheel test, silicone rubber polymer insulator

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Authors: A. Badri

Abstract:

Restructured electricity markets may provide opportunities for producers to exercise market power maintaining prices in excess of competitive levels. In this paper an oligopolistic market is presented that all Generation Companies (GenCos) bid in a Cournot model. Genetic algorithm (GA) is applied to obtain generation scheduling of each GenCo as well as hourly market clearing prices (MCP). In order to consider network constraints a multiperiod framework is presented to simulate market clearing mechanism in which the behaviors of market participants are modelled through piecewise block curves. A mixed integer linear programming (MILP) is employed to solve the problem. Impacts of market clearing process on participants- characteristic and final market prices are presented. Consequently, a novel multi-objective model is addressed for security constrained optimal bidding strategy of GenCos. The capability of price-maker GenCos to alter MCP is evaluated through introducing an effective-supply curve. In addition, the impact of exercising market power on the variation of market characteristics as well as GenCos scheduling is studied.

Keywords: Optimal bidding strategy, Cournot equilibrium, market power, network constraints, market auction mechanism

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Authors: Tirtha S. Das, Ayan K. Sau, Subir K. Sarkar

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Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.

Keywords: Spread spectrum modulation, spreading code, signaldecomposition, security, successive bit cancellation

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Authors: Qazi Umer Jamil, Abubakr Siddique, Mubeen Ur Rehman, Nida Aziz, Mohsin I. Tiwana

Abstract:

This paper discusses a brain controlled robotic gait trainer for neurorehabilitation of Spinal Cord Injury (SCI) patients. Patients suffering from Spinal Cord Injuries (SCI) become unable to execute motion control of their lower proximities due to degeneration of spinal cord neurons. The presented approach can help SCI patients in neuro-rehabilitation training by directly translating patient motor imagery into walkers motion commands and thus bypassing spinal cord neurons completely. A non-invasive EEG based brain-computer interface is used for capturing patient neural activity. For signal processing and classification, an open source software (OpenVibe) is used. Classifiers categorize the patient motor imagery (MI) into a specific set of commands that are further translated into walker motion commands. The robotic walker also employs fall detection for ensuring safety of patient during gait training and can act as a support for SCI patients. The gait trainer is tested with subjects, and satisfactory results were achieved.

Keywords: Brain Computer Interface (BCI), gait trainer, Spinal Cord Injury (SCI), neurorehabilitation.

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Authors: Hang Yu

Abstract:

The visualization of geographic information on mobile devices has become popular as the widespread use of mobile Internet. The mobility of these devices brings about much convenience to people-s life. By the add-on location-based services of the devices, people can have an access to timely information relevant to their tasks. However, visual analysis of geographic data on mobile devices presents several challenges due to the small display and restricted computing resources. These limitations on the screen size and resources may impair the usability aspects of the visualization applications. In this paper, a variable-scale visualization method is proposed to handle the challenge of small mobile display. By merging multiple scales of information into a single image, the viewer is able to focus on the interesting region, while having a good grasp of the surrounding context. This is essentially visualizing the map through a fisheye lens. However, the fisheye lens induces undesirable geometric distortion in the peripheral, which renders the information meaningless. The proposed solution is to apply map generalization that removes excessive information around the peripheral and an automatic smoothing process to correct the distortion while keeping the local topology consistent. The proposed method is applied on both artificial and real geographical data for evaluation.

Keywords: Map simplification, visualization, mobile devices.

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Authors: G. S. Dangayach

Abstract:

For any country the project management has been a vital part for its development. The highly competitive business world has created tremendous pressure on the project managers to achieve success. The pressure is derived from survival and profit building in business organizations which compels the project managers to pursue unethical practices. As a result unethical activities in business projects can be found easily where situations or issues arise due to dubious business practice, high corruption, or absolute violation of the law. The recent spur on Commonwealth games to be organized in New Delhi indicates towards the same. It has been seen that the project managers mainly focus on cost, time, and quality rather than social impact and long term effects of the project. Surprisingly the literature as well as the practitioner-s perspective also does not identify the role of ethics in project success. This paper identifies ethics as the fourth most important dimension in the project based organizations. The paper predicts that the approach of considering ethics will result in sustainability of the project. It will increase satisfaction and loyalty of the customers as well as create harmony, trust, brotherhood, values and morality among the team members. This paper is conceptual in nature as inadequate literature exists linking the project success with an ethical approach.

Keywords: Ethics, Loyalty, Morality, Project success

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Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: Energy production, meteorological data, irradiance decomposition, solar photovoltaic system.

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Authors: Robin C. Ladwig

Abstract:

Work experiences and satisfaction as well as the feeling of belonging has been narrowly explored from the perspective of trans and gender diverse individuals. Hence, the study investigates the relationship of values, attitudes, and norms of occupational environments and the working identity of trans and gender diverse people of the Australian workforce. Based on 22 semi-structured interviews with trans and gender diverse individuals regarding their work and career experiences, a first insight about their feeling of belonging through commonality in the workplace could be established. Communality between the values, attitudes and norms of a trans and gender diverse individuals working identities and profession, organization and working environment could increase the feeling of belonging. Further reflection and evaluation of trans and gender diverse identities in the workplace need to be considered to create an equitable and inclusive workplace of the future. Consequently, an essential development step for the future of work and its fundamental values of diversity, inclusion, and belonging will consist of the acknowledgement and inclusion of trans and gender diverse people as part of a broader social identity of the workplace.

Keywords: Belonging, future of work, working identity, trans and gender diverse identity.

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

Abstract:

As internet continues to expand its usage with an  enormous number of applications, cyber-threats have significantly  increased accordingly. Thus, accurate detection of malicious traffic in  a timely manner is a critical concern in today’s Internet for security.  One approach for intrusion detection is to use Machine Learning (ML)  techniques. Several methods based on ML algorithms have been  introduced over the past years, but they are largely limited in terms of  detection accuracy and/or time and space complexity to run. In this  work, we present a novel method for intrusion detection that  incorporates a set of supervised learning algorithms. The proposed  technique provides high accuracy and outperforms existing techniques  that simply utilizes a single learning method. In addition, our  technique relies on partial flow information (rather than full  information) for detection, and thus, it is light-weight and desirable for  online operations with the property of early identification. With the  mid-Atlantic CCDC intrusion dataset publicly available, we show that  our proposed technique yields a high degree of detection rate over 99%  with a very low false alarm rate (0.4%). 

 

Keywords: Intrusion Detection, Supervised Learning, Traffic Classification.

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Authors: Mohammad Lemar Zalmai, Mustafa Nabi Kocakaya, Cemil Akcay, Ekrem Manisali

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In recent years, the Building Information Modeling (BIM) approach has been developed expeditiously. As people see the benefits of this approach, it has begun to be used widely in construction projects and some countries made it mandatory to get more benefits from it. To promote the implementation of BIM in construction projects, it will be helpful to get some relevant information from surveys and interviews. The purpose of this study is to research the current adoption and implementation of BIM in public projects in Turkey. This study specified the challenges of BIM implementation in Turkey and proposed some solutions to overcome them. In this context, the challenges for BIM implementation and the factors that affect the BIM usage are determined based on previous academic researches and expert opinions by conducting interviews and questionnaire surveys. Several methods are used to process information in order to obtain weights of different factors to make BIM widespread in Turkey. This study concluded interviews' and questionnaire surveys' outcomes and proposed some suggestions to promote the implementation of BIM in Turkey. We believe research findings will be a good reference for boosting BIM implementation in Turkey.

Keywords: Building Information Modeling, BIM, BIM implementations, Turkish construction industry, Turkish government sector projects.

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Authors: N. H. Adenan, M. S. M. Noorani

Abstract:

River flow prediction is an essential tool to ensure proper management of water resources and the optimal distribution of water to consumers. This study presents an analysis and prediction by using nonlinear prediction method with monthly river flow data for Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The reconstruction of phase space involves the reconstruction of one-dimension (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. The revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) was employed to compare prediction performance for the nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show that the prediction results using the nonlinear prediction method are better than ARIMA and SVM. Therefore, the results of this study could be used to develop an efficient water management system to optimize the allocation of water resources.

Keywords: River flow, nonlinear prediction method, phase space, local linear approximation.

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

Abstract:

An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: Boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones.

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