Search results for: Survey data visualization.

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

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Authors: Tomáš Seidler, Marek Mihola, Denisa Cihlarova

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The article presents analysis results of maps of expected subsidence in undermined areas for road repair management. The analysis was done in the area of Karvina district in the Czech Republic, including undermined areas with ongoing deep mining activities or finished deep mining in years 2003 - 2009. The article discusses the possibilities of local road maintenance authorities to determine areas that will need most repairs in the future with limited data available. Using the expected subsidence maps new map of surface curvature was calculated. Combined with road maps and historical data about repairs the result came for five main categories of undermined areas, proving very simple tool for management.

Keywords: GIS, Map of Subsidence, Road, Undermined Area

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Authors: Z. Zainuddin, W. K. Lye

Abstract:

In this paper, a clustering algorithm named KHarmonic means (KHM) was employed in the training of Radial Basis Function Networks (RBFNs). KHM organized the data in clusters and determined the centres of the basis function. The popular clustering algorithms, namely K-means (KM) and Fuzzy c-means (FCM), are highly dependent on the initial identification of elements that represent the cluster well. In KHM, the problem can be avoided. This leads to improvement in the classification performance when compared to other clustering algorithms. A comparison of the classification accuracy was performed between KM, FCM and KHM. The classification performance is based on the benchmark data sets: Iris Plant, Diabetes and Breast Cancer. RBFN training with the KHM algorithm shows better accuracy in classification problem.

Keywords: Neural networks, Radial basis functions, Clusteringmethod, K-harmonic means.

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Authors: Mohammad Javadi

Abstract:

Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.

Keywords: Brain segmentation, DTI, hierarchical, SVM.

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Authors: Soumiya Bhattacharjee, P. K. Champati Ray, Shovan L. Chattoraj, Mrinmoy Dhara

Abstract:

The entire Himalayan range is globally renowned for rainfall-induced landslides. The prime focus of the study is to determine rainfall based threshold for initiation of landslides that can be used as an important component of an early warning system for alerting stake holders. This research deals with temporal dimension of slope failures due to extreme rainfall events along the National Highway-58 from Karanprayag to Badrinath in the Garhwal Himalaya, India. Post processed 3-hourly rainfall intensity data and its corresponding duration from daily rainfall data available from Tropical Rainfall Measuring Mission (TRMM) were used as the prime source of rainfall data. Landslide event records from Border Road Organization (BRO) and some ancillary landslide inventory data for 2013 and 2014 have been used to determine Intensity Duration (ID) based rainfall threshold. The derived governing threshold equation, I= 4.738D^-0.025, has been considered for prediction of landslides of the study region. This equation was validated with an accuracy of 70% landslides during August and September 2014. The derived equation was considered for further prediction of landslides of the study region. From the obtained results and validation, it can be inferred that this equation can be used for initiation of landslides in the study area to work as a part of an early warning system. Results can significantly improve with ground based rainfall estimates and better database on landslide records. Thus, the study has demonstrated a very low cost method to get first-hand information on possibility of impending landslide in any region, thereby providing alert and better preparedness for landslide disaster mitigation.

Keywords: Landslide, intensity-duration, rainfall threshold, Tropical Rainfall Measuring Mission, slope, inventory, early warning system.

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Authors: A. K. Abd El-Aleem, W. F. Abd El-wahed, N. A. Ismail, F. A. Torkey

Abstract:

This study suggests a model of a new set of evaluation criteria that will be used to measure the efficiency of real-world E-commerce websites. Evaluation criteria include design, usability and performance for websites, the Data Envelopment Analysis (DEA) technique has been used to measure the websites efficiency. An efficient Web site is defined as a site that generates the most outputs, using the smallest amount of inputs. Inputs refer to measurements representing the amount of effort required to build, maintain and perform the site. Output is amount of traffic the site generates. These outputs are measured as the average number of daily hits and the average number of daily unique visitors.

Keywords: Data Envelopment Analysis, E-commerce, Efficiency.

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Authors: Chiung-Hui Chen

Abstract:

Diagram and drawing are important ways to communicate and the reproduce of architectural design, Due to the development of information and communication technology, the professional thinking of architecture and interior design are also change rapidly. In development process of design, diagram always play very important role. This study is based on diagram theories, observe and record interaction between man and objects, objects and space, and space and time in a modern nuclear family. Construct a method for diagram to systematically and visualized describe the space plan of a modern nuclear family toward an intelligent design, to assist designer to retrieve information and review event pattern of past and present.

Keywords: Digital diagram, information model, context aware, data analysis.

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Authors: A. A. Zaidan, Anas Majeed, B. B. Zaidan

Abstract:

Nowadays, the rapid development of multimedia and internet allows for wide distribution of digital media data. It becomes much easier to edit, modify and duplicate digital information Besides that, digital documents are also easy to copy and distribute, therefore it will be faced by many threatens. It-s a big security and privacy issue with the large flood of information and the development of the digital format, it become necessary to find appropriate protection because of the significance, accuracy and sensitivity of the information. Nowadays protection system classified with more specific as hiding information, encryption information, and combination between hiding and encryption to increase information security, the strength of the information hiding science is due to the non-existence of standard algorithms to be used in hiding secret messages. Also there is randomness in hiding methods such as combining several media (covers) with different methods to pass a secret message. In addition, there are no formal methods to be followed to discover the hidden data. For this reason, the task of this research becomes difficult. In this paper, a new system of information hiding is presented. The proposed system aim to hidden information (data file) in any execution file (EXE) and to detect the hidden file and we will see implementation of steganography system which embeds information in an execution file. (EXE) files have been investigated. The system tries to find a solution to the size of the cover file and making it undetectable by anti-virus software. The system includes two main functions; first is the hiding of the information in a Portable Executable File (EXE), through the execution of four process (specify the cover file, specify the information file, encryption of the information, and hiding the information) and the second function is the extraction of the hiding information through three process (specify the steno file, extract the information, and decryption of the information). The system has achieved the main goals, such as make the relation of the size of the cover file and the size of information independent and the result file does not make any conflict with anti-virus software.

Keywords: Cryptography, Steganography, Portable ExecutableFile.

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Authors: Bikramaditya Das, Susmita Das

Abstract:

Study on suppression of interference in time domain equalizers is attempted for high data rate impulse radio (IR) ultra wideband communication system. The narrow band systems may cause interference with UWB devices as it is having very low transmission power and the large bandwidth. SRAKE receiver improves system performance by equalizing signals from different paths. This enables the use of SRAKE receiver techniques in IRUWB systems. But Rake receiver alone fails to suppress narrowband interference (NBI). A hybrid SRake-MMSE time domain equalizer is proposed to overcome this by taking into account both the effect of the number of rake fingers and equalizer taps. It also combats intersymbol interference. A semi analytical approach and Monte-Carlo simulation are used to investigate the BER performance of SRAKEMMSE receiver on IEEE 802.15.3a UWB channel models. Study on non-line of sight indoor channel models (both CM3 and CM4) illustrates that bit error rate performance of SRake-MMSE receiver with NBI performs better than that of Rake receiver without NBI. We show that for a MMSE equalizer operating at high SNR-s the number of equalizer taps plays a more significant role in suppressing interference.

Keywords: IR-UWB, UWB, IEEE 802.15.3a, NBI, data rate, bit error rate.

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

Abstract:

The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: Optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization.

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Authors: N. Burtebayev, Sh. Hamada, Zh. Kerimkulov, D. K. Alimov, A. V. Yushkov, N. Amangeldi, A. N. Bakhtibaev

Abstract:

The main aim of the current work is to examine if 14N  is candidate to be clusterized nuclei or not. In order to check this  attendance, we have measured the angular distributions for 14N ion  beam elastically scattered on 12C target nuclei at different low  energies; 17.5, 21, and 24.5MeV which are close to the Coulomb  barrier energy for 14N+12C nuclear system. Study of various transfer  reactions could provide us with useful information about the  attendance of nuclei to be in a composite form (core + valence). The  experimental data were analyzed using two approaches;  Phenomenological (Optical Potential) and semi-microscopic (Double  Folding Potential). The agreement between the experimental data and  the theoretical predictions is fairly good in the whole angular range.

 

Keywords: Deuteron Transfer, Elastic Scattering, Optical Model, Double Folding, Density Distribution.

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Authors: Insaf Mehani, N. Settou

Abstract:

Natural ventilation is an important means to improve indoor thermal comfort and reduce the energy consumption. A solar chimney system is an enhancing natural draft device, which uses solar radiation to heat the air inside the chimney, thereby converting the thermal energy into kinetic energy. The present study considered some parameters such as chimney width and solar intensity, which were believed to have a significant effect on space ventilation. Fluent CFD software was used to predict buoyant air flow and flow rates in the cavities. The results were compared with available published experimental and theoretical data from the literature. There was an acceptable trend match between the present results and the published data for the room air change per hour, ACH. Further, it was noticed that the solar intensity has a more significant effect on ACH.

Keywords: Solar chimney, numerical simulation

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Authors: Amanda Abbott-Jones

Abstract:

Adult students with dyslexia can receive support for cognitive needs but may also experience anxiety, which is less understood. This study aims to test the hypothesis that dyslexic learners in higher education have a higher prevalence of academic and social anxiety than their non-dyslexic peers and explores wider emotional consequences of studying with dyslexia and the ways that adults with dyslexia cope cognitively and emotionally. A mixed method approach was used in two stages. Stage one compared survey responses from students with dyslexia (N = 102) and students without dyslexia (N = 72) after completion of an anxiety inventory. Stage two explored emotional consequences of studying with dyslexia and types of coping strategies used through semi-structured interviews with 20 dyslexic students. Results revealed a statistically significant effect for academic anxiety but not for social anxiety. Findings for stage two showed that: (1) students’ emotional consequences were characterised by a mixture of negative and positive responses, yet negative responses were more frequent in response to questions about academic tasks than positive responses; (2) participants had less to say on coping emotionally, than coping cognitively.

Keywords: Dyslexia, higher education, anxiety, emotion.

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Authors: Aji P. Wibawa, Andrew Nafalski, Neil Murray, Wayan F. Mahmudy

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Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Keywords: edit distance coefficient, Javanese, parallel text alignment, phrase pair combination

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Authors: Abhijit Mitra

Abstract:

A special case of floating point data representation is block floating point format where a block of operands are forced to have a joint exponent term. This paper deals with the finite wordlength properties of this data format. The theoretical errors associated with the error model for block floating point quantization process is investigated with the help of error distribution functions. A fast and easy approximation formula for calculating signal-to-noise ratio in quantization to block floating point format is derived. This representation is found to be a useful compromise between fixed point and floating point format due to its acceptable numerical error properties over a wide dynamic range.

Keywords: Block floating point, Roundoff error, Block exponent dis-tribution fuction, Signal factor.

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Authors: Kristoffer Clyde Magsino, H. Srikanth Kamath

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Wireless Sensor Network is widely used in electronics. Wireless sensor networks are now used in many applications including military, environmental, healthcare applications, home automation and traffic control. We will study one area of wireless sensor networks, which is the routing protocol. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we will discuss two routing protocols, such as datacentric and hierarchical routing protocol. We will show the output of the protocols using the NS-2 simulator. This paper will compare the simulation output of the two routing protocol using Nam. We will simulate using Xgraph to find the throughput and delay of the protocol.

Keywords: data-centric routing protocol, hierarchical routingprotocol, Nam, NS-2, Routing Protocol, sensor nodes, SPIN, throughput, Xgraph

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Authors: A. A. Hussen, I. N. Jleta

Abstract:

Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effects of these random errors, they must be accurately modeled. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.

Keywords: Allan variance, accelerometer, gyroscope, stochastic errors.

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Authors: O. Zarrin, M. Ramezanshirazi

Abstract:

The Semi Interlocking Masonry (SIM) system has been developed in Masonry Research Group at the University of Newcastle, Australia. The main purpose of this system is to enhance the seismic resistance of framed structures with masonry panels. In this system, SIM panels dissipate energy through the sliding friction between rows of SIM units during earthquake excitation. This paper aimed to find the applicability of artificial neural network (ANN) to predict the displacement behaviour of the SIM panel under out-of-plane loading. The general concept of ANN needs to be trained by related force-displacement data of SIM panel. The overall data to train and test the network are 70 increments of force-displacement from three tests, which comprise of none input nodes. The input data contain height and length of panels, height, length and width of the brick and friction and geometry angle of brick along the compressive strength of the brick with the lateral load applied to the panel. The aim of designed network is prediction displacement of the SIM panel by Multi-Layer Perceptron (MLP). The mean square error (MSE) of network was 0.00042 and the coefficient of determination (R2) values showed the 0.91. The result revealed that the ANN has significant agreement to predict the SIM panel behaviour.

Keywords: Semi interlocking masonry, artificial neural network, ANN, multi-layer perceptron, MLP, displacement, prediction.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Jia-Ru Li, Chih-Hung Wang, Ching-Wen Lin

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Internet addiction has become a critical problem on adolescents in Taiwan, and its negative effects on various dimensions of adolescent development caught the attention of educational and psychological experts. This study examined the correlation between cognitive (locus of control) and emotion (emotion venting strategies) factors on internet addiction of adolescents in Taiwan. Using the Compulsive Internet Use (CIU) and the Emotion Venting Strategy scales, a survey was conducted and 215 effective samples (students ranging from12 to14 years old) returned. Quantitative analysis methods such as descriptive statistics, t-test, ANOVA, Pearson correlations and multiple regression were adopted. The results were as follows: 1. Severity of Internet addiction has significant gender differences; boys were at a higher risk than girls in becoming addicted to the Internet. 2. Emotion venting, locus of control and internet addiction have been shown to be positive correlated with one another. 3. Setting the locus of control as the control variable, emotion venting strategy has positive and significant contribution to internet addiction. The results of this study suggest that coaching deconstructive emotion strategies and cognitive believes are encouraged to integrate with actual field work.

Keywords: Emotion venting strategy, locus of control, adolescent internet addiction.

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Authors: Pascal Gliesche, Kathrin Seibert, Christian Kowalski, Dominik Domhoff, Max Pfingsthorn, Karin Wolf-Ostermann, Andreas Hein

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Robotic assistance in nursing care is an increasingly important area of research and development. Facing a shortage of labor and an increasing number of people in need of care, the German Nursing Care Innovation Center (Pflegeinnovationszentrum, PIZ) aims to address these challenges from the side of technology. Little is known about nurses experiences with existing robotic assistance systems. Especially nurses perspectives on starting points for the development of robotic solutions, that target recurring burdensome tasks in everyday nursing care, are of interest. This paper presents findings focusing on robotics resulting from an explanatory mixed-methods study on nurses experiences with and their expectations for innovative technologies in nursing care in stationary and ambulant care facilities and hospitals in Germany. Based on the findings, eight scenarios for robotic assistance are identified based on the real needs of practitioners. An initial system addressing a single use-case is described to show perspectives for the use of robots in nursing care.

Keywords: Robotics and automation, engineering management, engineering in medicine and biology, medical services, public healthcare.

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Authors: Sh. Hamada

Abstract:

The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both ¹²C and ¹⁶O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+¹²C and α+¹⁶O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (N_r). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.

Keywords: Nuclear rainbow, elastic scattering, optical model, double folding, density distribution.

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Authors: Noor Azlina Mohd Salleh, Salmiah Kasolang, Ahmed Jaffar

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Green Lean Total Quality Management (TQM) System is a system comprises of Environmental Management System (EMS) practices which is integrated to TQM with Lean Manufacturing (LM) principles. The ultimate goal of this system is to focus on achieving total customer satisfaction and environmental care by removing eight wastes available in any process in an organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by SPSS v.17. It was found out that some vendors have been practicing TQM and LM while some have started to implement EMS. This study is only focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development Program. This is the first study conducted to know the current status of TQM, LM and EMS practices in highly active automotive companies in Malaysia. It was found out that EMS has been practiced by 16 companies out of 30. Within these 16 companies the approach is more holistic and green. This is a preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production System SAEJ4000, MAJAICO Lean Production System and EMS.

Keywords: Automotive Industry, Lean Manufacturing, Operational Engineering Management, Total Quality Management. Environmental Management System.

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Authors: N. Bolong, J. Makinda, I. Saad

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Laboratory activities have produced benefits in student learning. With current drives of new technology resources and evolving era of education methods, renewal status of learning and teaching in laboratory methods are in progress, for both learners and the educators. To enhance learning outcomes in laboratory works particularly in engineering practices and testing, learning via handson by instruction may not sufficient. This paper describes and compares techniques and implementation of traditional (expository) with open-ended laboratory (problem-based) for two consecutive cohorts studying environmental laboratory course in civil engineering program. The transition of traditional to problem-based findings and effect were investigated in terms of course assessment student feedback survey, course outcome learning measurement and student performance grades. It was proved that students have demonstrated better performance in their grades and 12% increase in the course outcome (CO) in problem-based open-ended laboratory style than traditional method; although in perception, students has responded less favorable in their feedback.

Keywords: Engineering education, open-ended laboratory, environmental engineering lab.

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Authors: Peter Boyes, Sarah Sharples, Paul Tennent, Gary Priestnall, Jeremy Morley

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Significant long-term investment projects can involve complex decisions. These are often described as capital projects and the factors that contribute to their complexity include budgets, motivating reasons for investment, stakeholder involvement, interdependent projects, and the delivery phases required. The complexity of these projects often requires management groups to be established involving stakeholder representatives, these teams are inherently multidisciplinary. This study uses two university campus capital projects as case studies for this type of management group. Due to the interaction of projects with wider campus infrastructure and users, decisions are made at varying spatial granularity throughout the project lifespan. This spatial-related context brings complexity to the group decisions. Sensemaking is the process used to achieve group situational awareness of a complex situation, enabling the team to arrive at a consensus and make a decision. The purpose of this study is to understand the role of people and data in complex spatial related long-term decision and sensemaking processes. The paper aims to identify and present issues experienced in practical settings of these types of decision. A series of exploratory semi-structured interviews with members of the two projects elicit an understanding of their operation. From two stages of thematic analysis, inductive and deductive, emergent themes are identified around the group structure, the data usage, and the decision making within these groups. When data were made available to the group, there were commonly issues with perception of veracity and validity of the data presented; this impacted the ability of the group to reach consensus and therefore for decision to be made. Similarly, there were different responses to forecasted or modelled data, shaped by the experience and occupation of the individuals within the multidisciplinary management group. This paper provides an understanding of further support required for team sensemaking and decision making in complex capital projects. The paper also discusses the barriers found to effective decision making in this setting and suggests opportunities to develop decision support systems in this team strategic decision-making process. Recommendations are made for further research into the sensemaking and decision-making process of this complex spatial-related setting.

Keywords: decision making, decisions under uncertainty, real decisions, sensemaking, spatial, team decision making

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Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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Authors: Yang Wenjuan, Xu Yilun

Abstract:

Based on the comparative analysis of the relevant evaluation methods of walking environment, this paper selects the combined evaluation method of macro urban morphology analysis and micro urban design quality survey, then investigates and analyzes the walking environment of three rail transit station area in Nanjing to explore the influence factor and internal relation of walkability of rail transit station area. Analysis shows that micro urban design factors have greater impact on the walkability of rail transit station area compared with macro urban morphology factors, the convenience is the key factor in the four aspects of convenience, security, identity and comfortability of the urban design factors, the convenience is not only affected by the block network form, but also related to the quality of the street space. The overall evaluation of walkability comes from the overlapping and regrouping of the walking environment at different levels, but some environmental factors play a leading role. The social attributes of pedestrians also partly influence their walking perception and evaluation.

Keywords: Rail transit station area, walkability, evaluation, influence factors.

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Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan

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Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid

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Authors: Wenhao Wang, Xinzhi Xu, Limin Feng, Wei Cong

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This paper comprehensively investigates current development status of global power grids and fossil energy pipelines (oil and natural gas), proposes a standard visual platform of global power and fossil energy based on Geographic Information System (GIS) technology. In this visual platform, a series of systematic visual models is proposed with global spatial data, systematic energy and power parameters. Under this visual platform, the current Global Power Grids Map and Global Fossil Energy Pipelines Map are plotted within more than 140 countries and regions across the world. Using the multi-scale fusion data processing and modeling methods, the world’s global fossil energy pipelines and power grids information system basic database is established, which provides important data supporting global fossil energy and electricity research. Finally, through the systematic and comparative study of global fossil energy pipelines and global power grids, the general status of global fossil energy and electricity development are reviewed, and energy transition in key areas are evaluated and analyzed. Through the comparison analysis of fossil energy and clean energy, the direction of relevant research is pointed out for clean development and energy transition.

Keywords: Energy Transition, geographic information system, fossil energy, power systems.

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Authors: Sherif G. Aly

Abstract:

In this article, we introduce a mechanism by which the same concept of differentiated services used in network transmission can be applied to provide quality of service levels to pervasive systems applications. The classical DiffServ model, including marking and classification, assured forwarding, and expedited forwarding, are all utilized to create quality of service guarantees for various pervasive applications requiring different levels of quality of service. Through a collection of various sensors, personal devices, and data sources, the transmission of contextsensitive data can automatically occur within a pervasive system with a given quality of service level. Triggers, initiators, sources, and receivers are four entities labeled in our mechanism. An explanation of the role of each is provided, and how quality of service is guaranteed.

Keywords: Pervasive systems, quality of service, differentiated services, mobile devices.

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