Search results for: link prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3359

Search results for: link prediction

2369 Text Mining Techniques for Prioritizing Pathogenic Mutations in Protein Families Known to Misfold or Aggregate

Authors: Khaleel Saleh Al-Rababah

Abstract:

Amyloid fibril forming regions, which are known as protein aggregates, in sequences of some protein families are associated with a number of diseases known as amyloidosis. Mutations play a role in forming fibrils by accelerating the fibril formation process. In this paper we want to extract diseases that caused by those mutations as a result of the impact of the mutations on structural and functional properties of the aggregated protein. We propose a text mining system, to automatically extract mutations, diseases and relations between mutations and diseases. We presented an algorithm based on finite state to cluster mutations found in the same sentence as a sentence could contain different mutation cause different diseases. Also, we presented a co reference algorithm that enables cross-link sentences.

Keywords: amyloid, amyloidosis, co reference, protein, text mining

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2368 Synchronization of a Perturbed Satellite Attitude Motion

Authors: Sadaoui Djaouida

Abstract:

In this paper, the predictive control method is proposed to control the synchronization of two perturbed satellites attitude motion. Based on delayed feedback control of continuous-time systems combines with the prediction-based method of discrete-time systems, this approach only needs a single controller to realize synchronization, which has considerable significance in reducing the cost and complexity for controller implementation.

Keywords: predictive control, synchronization, satellite attitude, control engineering

Procedia PDF Downloads 551
2367 Coupling Random Demand and Route Selection in the Transportation Network Design Problem

Authors: Shabnam Najafi, Metin Turkay

Abstract:

Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

Procedia PDF Downloads 637
2366 Multiscale Analysis of Shale Heterogeneity in Silurian Longmaxi Formation from South China

Authors: Xianglu Tang, Zhenxue Jiang, Zhuo Li

Abstract:

Characterization of shale multi scale heterogeneity is an important part to evaluate size and space distribution of shale gas reservoirs in sedimentary basins. The origin of shale heterogeneity has always been a hot research topic for it determines shale micro characteristics description and macro quality reservoir prediction. Shale multi scale heterogeneity was discussed based on thin section observation, FIB-SEM, QEMSCAN, TOC, XRD, mercury intrusion porosimetry (MIP), and nitrogen adsorption analysis from 30 core samples in Silurian Longmaxi formation. Results show that shale heterogeneity can be characterized by pore structure and mineral composition. The heterogeneity of shale pore is showed by different size pores at nm-μm scale. Macropores (pore diameter > 50 nm) have a large percentage of pore volume than mesopores (pore diameter between 2~ 50 nm) and micropores (pore diameter < 2nm). However, they have a low specific surface area than mesopores and micropores. Fractal dimensions of the pores from nitrogen adsorption data are higher than 2.7, what are higher than 2.8 from MIP data, showing extremely complex pore structure. This complexity in pore structure is mainly due to the organic matter and clay minerals with complex pore network structures, and diagenesis makes it more complicated. The heterogeneity of shale minerals is showed by mineral grains, lamina, and different lithology at nm-km scale under the continuous changing horizon. Through analyzing the change of mineral composition at each scale, random arrangement of mineral equal proportion, seasonal climate changes, large changes of sedimentary environment, and provenance supply are considered to be the main reasons that cause shale minerals heterogeneity from microcosmic to macroscopic. Due to scale effect, the change of shale multi scale heterogeneity is a discontinuous process, and there is a transformation boundary between homogeneous and in homogeneous. Therefore, a shale multi scale heterogeneity changing model is established by defining four types of homogeneous unit at different scales, which can be used to guide the prediction of shale gas distribution from micro scale to macro scale.

Keywords: heterogeneity, homogeneous unit, multiscale, shale

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2365 Environmental Impacts on Urban Agriculture in Algiers

Authors: Sara Bouzekri, Said Madani

Abstract:

In many Mediterranean cities such as Algiers, the human activity, the strong mobility the urban sprawl, the air pollution, the problems of waste management, the wasting of the resources and the degradation of the environment weaken in an unquestionable way the farming. The question of sustainable action vis-a-vis these threats arises then in order to maintain a level of desired local development. The methodology is based on a multi-criteria method based on the AFOM diagnosis, which classifies agricultural strength indicators and those of threat, according to an analytical approach. In a sustainable development perspective, it will be appropriate to link the threat factors of the case study with the factors of climate change to see their impact on the future of agriculture. This will be accompanied by a SWOT analysis, which crosses the most significant criteria to arrive at the necessary recommendations based on future projects for urban agriculture.

Keywords: Algiers, environment, urban agriculture, threat factors

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2364 Development of Algorithms for the Study of the Image in Digital Form for Satellite Applications: Extraction of a Road Network and Its Nodes

Authors: Zineb Nougrara

Abstract:

In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

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2363 Fatigue Analysis and Life Estimation of the Helicopter Horizontal Tail under Cyclic Loading by Using Finite Element Method

Authors: Defne Uz

Abstract:

Horizontal Tail of helicopter is exposed to repeated oscillatory loading generated by aerodynamic and inertial loads, and bending moments depending on operating conditions and maneuvers of the helicopter. In order to ensure that maximum stress levels do not exceed certain fatigue limit of the material and to prevent damage, a numerical analysis approach can be utilized through the Finite Element Method. Therefore, in this paper, fatigue analysis of the Horizontal Tail model is studied numerically to predict high-cycle and low-cycle fatigue life related to defined loading. The analysis estimates the stress field at stress concentration regions such as around fastener holes where the maximum principal stresses are considered for each load case. Critical element identification of the main load carrying structural components of the model with rivet holes is performed as a post-process since critical regions with high-stress values are used as an input for fatigue life calculation. Once the maximum stress is obtained at the critical element and the related mean and alternating components, it is compared with the endurance limit by applying Soderberg approach. The constant life straight line provides the limit for several combinations of mean and alternating stresses. The life calculation based on S-N (Stress-Number of Cycles) curve is also applied with fully reversed loading to determine the number of cycles corresponds to the oscillatory stress with zero means. The results determine the appropriateness of the design of the model for its fatigue strength and the number of cycles that the model can withstand for the calculated stress. The effect of correctly determining the critical rivet holes is investigated by analyzing stresses at different structural parts in the model. In the case of low life prediction, alternative design solutions are developed, and flight hours can be estimated for the fatigue safe operation of the model.

Keywords: fatigue analysis, finite element method, helicopter horizontal tail, life prediction, stress concentration

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2362 Performance and Limitations of Likelihood Based Information Criteria and Leave-One-Out Cross-Validation Approximation Methods

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

Abstract:

Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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2361 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 162
2360 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 150
2359 Prediction of Formation Pressure Using Artificial Intelligence Techniques

Authors: Abdulmalek Ahmed

Abstract:

Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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2358 Secular Ethics from the Viewpoint of Mostafa Malekian (Analyze, Review, and Critique)

Authors: Hamideh Rahmani

Abstract:

The subject matter of ethics is being changed in modern life, which had been an issue for a long time and aimed to define its moral boundaries in human's intellectual and everyday life. This has led to the introduction of notions based on the separation of religion from ethics in recent decades. It is in conflict with the traditional view, which introduces ethics as raised from religion and religion as the most crucial credit for ethics. The purpose of this study is to investigate the elements of secular ethics from the perspective of Mostafa Malekian, seeking to achieve his notions. After examining the strengths of secular ethics parameters from the viewpoint of Malekian, this research found his ethics in his interpretation of the ideal life which he treats as ethics, got a very strong link with his secularist project known as rationality and spirituality. We will analyze, review, and critique his ethics in the following.

Keywords: secular ethics, Mostafa Malakian, global ethics, rationality, spirituality

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2357 Psychological Well-Being at Work Among Sport Coaches: A Systematic Review and Perspectives

Authors: Ouazoul Abdelouahd, Jemjami Nadia

Abstract:

The concept of well-being at work is one of today's major challenges in maintaining quality of life and managing psycho-social risks at work. Indeed, work in the sports sector has evolved over time, and this exponential evolution, marked by increasing demands and psychological, physical and/or social challenges, which sometimes exceed the resources of sports players, influences their sense of well-being at work. Well-being and burnout as antagonists provide information on the quality of working life in sports. The main objective of this literature review was to examine the scientific corpus dealing with the subject of psychological well-being at work in the sports sector and, more specifically, with sports coaches while exploring the link between sports burnout and well-being. The results reveal the richness of the conceptual approaches and the difficulties of putting them into practice. Prospects for future research were put forward.

Keywords: psychological well-being, burnout, quality of life, sports coaching

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2356 Experimental and Theoratical Methods to Increase Core Damping for Sandwitch Cantilever Beam

Authors: Iyd Eqqab Maree, Moouyad Ibrahim Abbood

Abstract:

The purpose behind this study is to predict damping effect for steel cantilever beam by using two methods of passive viscoelastic constrained layer damping. First method is Matlab Program, this method depend on the Ross, Kerwin and Unger (RKU) model for passive viscoelastic damping. Second method is experimental lab (frequency domain method), in this method used the half-power bandwidth method and can be used to determine the system loss factors for damped steel cantilever beam. The RKU method has been applied to a cantilever beam because beam is a major part of a structure and this prediction may further leads to utilize for different kinds of structural application according to design requirements in many industries. In this method of damping a simple cantilever beam is treated by making sandwich structure to make the beam damp, and this is usually done by using viscoelastic material as a core to ensure the damping effect. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. There is a very good agreement of the experimental results with the theoretical findings. The main ideas of this thesis are to find the transition region for damped steel cantilever beam (4mm and 8mm thickness) from experimental lab and theoretical prediction (Matlab R2011a). Experimentally and theoretically proved that the transition region for two specimens occurs at modal frequency between mode 1 and mode 2, which give the best damping, maximum loss factor and maximum damping ratio, thus this type of viscoelastic material core (3M468) is very appropriate to use in automotive industry and in any mechanical application has modal frequency eventuate between mode 1 and mode 2.

Keywords: 3M-468 material core, loss factor and frequency, domain method, bioinformatics, biomedicine, MATLAB

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2355 Augmented Reality and Storytelling in Cities: An Application to Lisbon Street Art

Authors: Francisco Guimarães, Mauro Figueiredo, José Rodrigues

Abstract:

Cities are spaces of memory with several zones (parts of cities) with their own history and cultural events. Today, cities are also marked by a form of intangible cultural heritage like street art, which creates a visual culture based on the process of reflection about the city and the world. To link these realities and create a personal user interaction with this cultural heritage it is important to capture the story and aesthetics, and find alternatives to immerse the user in these spaces of memory. To that end, this article presents a project which combines Augmented Reality technologies and concepts of Transmedia Storytelling applied to Lisbon City, using Street Art artifacts as markers in a framework of digital media-art.

Keywords: augmented reality, cultural heritage, street art, transmedia storytelling, digital media-art

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2354 Structural Strength Evaluation and Wear Prediction of Double Helix Steel Wire Ropes for Heavy Machinery

Authors: Krunal Thakar

Abstract:

Wire ropes combine high tensile strength and flexibility as compared to other general steel products. They are used in various application areas such as cranes, mining, elevators, bridges, cable cars, etc. The earliest reported use of wire ropes was for mining hoist application in 1830s. Over the period, there have been substantial advancement in the design of wire ropes for various application areas. Under operational conditions, wire ropes are subjected to varying tensile loads and bending loads resulting in material wear and eventual structural failure due to fretting fatigue. The conventional inspection methods to determine wire failure is only limited to outer wires of rope. However, till date, there is no effective mathematical model to examine the inter wire contact forces and wear characteristics. The scope of this paper is to present a computational simulation technique to evaluate inter wire contact forces and wear, which are in many cases responsible for rope failure. Two different type of ropes, IWRC-6xFi(29) and U3xSeS(48) were taken for structural strength evaluation and wear prediction. Both ropes have a double helix twisted wire profile as per JIS standards and are mainly used in cranes. CAD models of both ropes were developed in general purpose design software using in house developed formulation to generate double helix profile. Numerical simulation was done under two different load cases (a) Axial Tension and (b) Bending over Sheave. Different parameters such as stresses, contact forces, wear depth, load-elongation, etc., were investigated and compared between both ropes. Numerical simulation method facilitates the detailed investigation of inter wire contact and wear characteristics. In addition, various selection parameters like sheave diameter, rope diameter, helix angle, swaging, maximum load carrying capacity, etc., can be quickly analyzed.

Keywords: steel wire ropes, numerical simulation, material wear, structural strength, axial tension, bending over sheave

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2353 Modeling and Prediction of Hot Deformation Behavior of IN718

Authors: M. Azarbarmas, J. M. Cabrera, J. Calvo, M. Aghaie-Khafri

Abstract:

The modeling of hot deformation behavior for unseen conditions is important in metal-forming. In this study, the hot deformation of IN718 has been characterized in the temperature range 950-1100 and strain rate range 0.001-0.1 s-1 using hot compression tests. All stress-strain curves showed the occurrence of dynamic recrystallization. These curves were implemented quantitatively in mathematics, and then constitutive equation indicating the relationship between the flow stress and hot deformation parameters was obtained successfully.

Keywords: compression test, constitutive equation, dynamic recrystallization, hot working

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2352 Comparative Analysis of Identity Semiotics in Iran’s Modern and Traditional House Design

Authors: Maryam Ghasemi

Abstract:

One of the most significant components that provide comfort and protection is having a shelter called a house. Even if components and regions are changed or restored to meet new functions, the house's identity must be preserved. In the contemporary era, houses are increasingly being built regardless of cultural identity. This misunderstanding caused a sense of unease. This study analyses archaic and modern architecture to find semiotic areas and qualities in the latter, using the former as a reference. This study's technique used an exploratory assessment of architectural components from both periods. The Abbasid residence and the Ekbatan architectural complex were used as case studies. The identity of Iranian architecture does not correlate with current buildings. The other part is privacy, which is a missing link between traditional and modern Iranian architecture because it is directly related to the identities of homes based on the cultures of their residents.

Keywords: housing, traditional, contemporary, privacy, semiotic

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2351 Passive Seismic Energy Dissipation Mechanisms for Smart Green Structural System (SGSS)

Authors: Daniel Y. Abebe, Jaehyouk Choi

Abstract:

The design philosophy of building structure has been changing over time. The reason behind this is an increase in human interest regarding the improvements in building materials and technology that will affect how we live, the aim to speed up construction period, and the environmental effect which includes earthquakes and other natural disasters. One technique which takes into account the above case is using a prefabricable structural system, in which each and every structural element is designed and prefabricated and assembled on a site so that the construction speed is increased and the environmental impact is also enhanced. This system has immense advantages such as reduced construction cost, reusability, recyclability, faster construction period and less enviromental effect. In this study, some of the developed and evaluated structural elements of building structures are presented.

Keywords: eccentrically braced frame, natural disaster, prefabricable structural system, removable link, SGSS

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2350 Prediction of Crack Propagation in Bonded Joints Using Fracture Mechanics

Authors: Reza Hedayati, Meysam Jahanbakhshi

Abstract:

In this work, Fracture Mechanics is used to predict crack propagation in the adhesive jointing aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore 2*3=6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases.

Keywords: fracture, adhesive joint, debonding, APDL, LEFM

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2349 The Link Between Knowledge Management, Organizational Learning and Collective Competence

Authors: Amira Khelil, Habib Affes

Abstract:

The XXIst century is characterized by promoting teamwork as one of the main drivers of firms` performance. Collective competence is becoming crucial in developing and maintaining a firm’s competitive advantage, as well as its contributions to organizational innovation. In other words, the improvement of collective competence for a firm is no longer a choice, but rather an obligation. Learning capabilities of a firm in the context of knowledge management are assumed to be the main drivers of collective competence. Although there are some efforts to consider these concepts together; they are mostly discussed separately in the management theory. Thus, this paper aims to offer a holistic approach for development collective competence on the basis of Knowledge Management and Organizational Learning Capabilities. A theoretical model that defines a relationship between knowledge management, organizational learning and collective competence is presented at the end of this paper.

Keywords: collective competence, exploitation learning, exploration learning, knowledge management, organizational learning capabilities

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2348 Predicting Automotive Interior Noise Including Wind Noise by Statistical Energy Analysis

Authors: Yoshio Kurosawa

Abstract:

The applications of soundproof materials for reduction of high frequency automobile interior noise have been researched. This paper presents a sound pressure prediction technique including wind noise by Hybrid Statistical Energy Analysis (HSEA) in order to reduce weight of acoustic insulations. HSEA uses both analytical SEA and experimental SEA. As a result of chassis dynamo test and road test, the validity of SEA modeling was shown, and utility of the method was confirmed.

Keywords: vibration, noise, road noise, statistical energy analysis

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2347 Cognitive Footprints: Analytical and Predictive Paradigm for Digital Learning

Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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2346 Survey on Securing the Optimized Link State Routing (OLSR) Protocol in Mobile Ad-hoc Network

Authors: Kimaya Subhash Gaikwad, S. B. Waykar

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The mobile ad-hoc network (MANET) is collection of various types of nodes. In MANET various protocols are used for communication. In OLSR protocol, a node is selected as multipoint relay (MPR) node which broadcast the messages. As the MANET is open kind of network any malicious node can easily enter into the network and affect the performance of the network. The performance of network mainly depends on the components which are taking part into the communication. If the proper nodes are not selected for the communication then the probability of network being attacked is more. Therefore, it is important to select the more reliable and secure components in the network. MANET does not have any filtering so that only selected nodes can be used for communication. The openness of the MANET makes it easier to attack the communication. The most of the attack are on the Quality of service (QoS) of the network. This paper gives the overview of the various attacks that are possible on OLSR protocol and some solutions. The papers focus mainly on the OLSR protocol.

Keywords: communication, MANET, OLSR, QoS

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2345 3D Receiver Operator Characteristic Histogram

Authors: Xiaoli Zhang, Xiongfei Li, Yuncong Feng

Abstract:

ROC curves, as a widely used evaluating tool in machine learning field, are the tradeoff of true positive rate and negative rate. However, they are blamed for ignoring some vital information in the evaluation process, such as the amount of information about the target that each instance carries, predicted score given by each classification model to each instance. Hence, in this paper, a new classification performance method is proposed by extending the Receiver Operator Characteristic (ROC) curves to 3D space, which is denoted as 3D ROC Histogram. In the histogram, the

Keywords: classification, performance evaluation, receiver operating characteristic histogram, hardness prediction

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2344 Journey to Cybercrime and Crime Opportunity: Quantitative Analysis of Cyber Offender Spatial Decision Making

Authors: Sinchul Back, Sun Ho Kim, Jennifer LaPrade, Ilju Seong

Abstract:

Due to the advantage of using the Internet, cybercriminals can reach target(s) without border controls. Prior research on criminology and crime science has largely been void of empirical studies on journey-to-cybercrime and crime opportunity. Thus, the purpose of this study is to understand more about cyber offender spatial decision making associated with crime opportunity factors (i.e., co-offending, offender-stranger). Data utilized in this study were derived from 306 U.S. Federal court cases of cybercrime. The findings of this study indicated that there was a positive relationship between co-offending and journey-to-cybercrime, whereas there was no link between offender-stranger and journey-to-cybercrime. Also, the results showed that there was no relationship between cybercriminal sex, age, and journey-to-cybercrime. The policy implications and limitations of this study are discussed.

Keywords: co-offending, crime opportunity, journey-to-cybercrime, offender-stranger

Procedia PDF Downloads 174
2343 The Education-Development Nexus: The Vision of International Organizations

Authors: Thibaut Lauwerier

Abstract:

This presentation will cover the vision of international organizations on the link between development and education. This issue is very relevant to address the general topic of the conference. 'Educating for development' is indeed at the heart of their discourse. For most of international organizations involved in education, it is important to invest in this field since it is at the service of development. The idea of this presentation is to better understand the vision of development according to these international organizations and how education can contribute to this type of development. To address this issue, we conducted a comparative study of three major international organizations (OECD, UNESCO and World Bank) influencing education policy at the international level. The data come from the strategic reports of these organizations over the period 1990-2015. The results show that the visions of development refer mainly to the neoliberal agenda, despite evolutions, even contradictions. And so, education must increase productivity, improve economic growth, etc. UNESCO, which has a less narrow conception of the development and therefore the aims of education, does not have the same means as the two other organizations to advocate for an alternative vision.

Keywords: development, education, international organizations, poilcy

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2342 System Survivability in Networks in the Context of Defense/Attack Strategies: The Large Scale

Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

Abstract:

We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

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2341 The Rebound Effect of Energy Efficiency in Residential Energy Demand: Case of Saudi Arabia

Authors: Mohammad Aldubyan, Fateh Belaid, Anwar Gasim

Abstract:

This paper aims at linking to link residential energy efficiency to the rebound effect concept, a well-known behavioral phenomenon in which service consumption increases when consumers notice a reduction in monetary spending on energy due to improvements in energy efficiency. It provides insights on into how and why the rebound effect happens when energy efficiency improves and whether this phenomenon is positive or negative. It also shows one technique to estimate the rebound effect on the national residential level. The paper starts with a bird’s eye view of the rebound effect and then dives in in-depth into measuring the rebound effect and evaluating its impact. Finally, the paper estimates the rebound effect in the Saudi residential sector through by linking pre-estimated price elasticities of demand to the Saudi residential building stock.

Keywords: energy efficiency, rebound effect, energy consumption, residential electricity demand

Procedia PDF Downloads 103
2340 A Framework for Investigating Reverse Logistics Capability of E-Tailers

Authors: Wen-Shan Lin, Shu-Lu Hsu

Abstract:

Environmental concern and consumer rights have entailed e-tailers to adopt better strategies to facilitate product returns from customers. As the demand for reverse logistics (RL) continues to grow, little is known about what motivates e-tailers to enhance their RL capabilities and about the role RL capabilities plays in enabling e-tailers to achieve better customer satisfaction and economic performance. Based on resource-based theory and institutional theory, this article proposes that the following factors play a critical role in influencing the RL capability of e-tailers: (a) Financial resource commitment to RL, (b) managerial resource commitment to RL, and (c) institutional pressure to implement RL. Based on the role of these factors, the study provides a framework and propositions that serve to guide future research addressing the link among resources, institutional pressure, and RL capability.

Keywords: reverse logistics, e-tailing, resource-based theory, institutional theory

Procedia PDF Downloads 447