Search results for: Large scale VLSI neural net

Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: H. Panahi, S. Asadi

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In this paper, the estimation of the stress-strength parameter R = P(Y < X), when X and Y are independent and both are Lomax distributions with the common scale parameters but different shape parameters is studied. The maximum likelihood estimator of R is derived. Assuming that the common scale parameter is known, the bayes estimator and exact confidence interval of R are discussed. Simulation study to investigate performance of the different proposed methods has been carried out.

Keywords: Stress-Strength model; maximum likelihoodestimator; Bayes estimator; Lomax distribution

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Authors: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: Rapid urbanization, traditional street space, space re-construction, bottom-up design.

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Authors: Lambros V. Skarlas, Grigorios N. Beligiannis, Efstratios F. Georgopoulos, Adam V. Adamopoulos

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The aim of this contribution is to present a new approach in modeling the electrical activity of the human heart. A recurrent artificial neural network is being used in order to exhibit a subset of the dynamics of the electrical behavior of the human heart. The proposed model can also be used, when integrated, as a diagnostic tool of the human heart system. What makes this approach unique is the fact that every model is being developed from physiological measurements of an individual. This kind of approach is very difficult to apply successfully in many modeling problems, because of the complexity and entropy of the free variables describing the complex system. Differences between the modeled variables and the variables of an individual, measured at specific moments, can be used for diagnostic purposes. The sensor fusion used in order to optimize the utilization of biomedical sensors is another point that this paper focuses on. Sensor fusion has been known for its advantages in applications such as control and diagnostics of mechanical and chemical processes.

Keywords: Artificial Neural Networks, Diagnostic System, Health Condition Modeling Tool, Heart Diagnostics Model, Heart Electricity Model.

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Authors: Jamshaid ur Rehman, Shahida Wizarat

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The principal focus of this study is on the measurement and analysis of labor learnings in Pakistan. The study at the aggregate economy level focus on the labor productivity movements and at large-scale manufacturing level focus on the cost structure, with isolating the contribution of the learning curve. The analysis of S-shaped curve suggests that learnings are only below one half of aggregate learning curve and other half shows the retardation in learning, hence retardation in productivity movements. The study implies the existence of learning economies in term of cost reduction that is input cost per unit produced decreases by 0.51 percent every time the cumulative production output doubles.

Keywords: Cost, Inflection Point, Learning Curve, Minima, Maxima, and Productivity

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Authors: Zhiwei Yan, Jong-Hyouk Lee, Yong-Jin Park, Xiaodong Lee

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In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.

Keywords: CCN, handover, NEMO, mobility management.

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Authors: Musa Alhassan, Alhaji Mohammed Mustapha

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Review of studies carried out on the use of bagasse ash for the improvement of deficient soils in Nigeria, with emphasis on lateritic and black cotton soils is presented. Although, the bagasse ash is mostly used as additive to the conventional soil stabilizers (cement and lime), the studies generally showed improvement in the geotechnical properties of the soils, either modified or stabilized with the ash. This showed the potentials of using this agricultural waste (bagasse ash) in the improvement of geotechnical properties of deficient soils, thus suggesting that using this material at large scale level in geotechnical engineering practice could help in the provision of stable and durable structures, reduce cost of soil improvement and also reduces environmental nuisance caused by the unused waste in Nigeria.

Keywords: Bagasse ash, Black cotton soil, Deficient soil, Laterite, Soil improvement.

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems do not scale well on cluster containing multiple Central Processing Units (multi-CPUs cluster) or cluster containing multiple Graphics Processing Units (multi-GPUs cluster). For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration, instead of two for standard CG (Conjugate Gradient). The standard and pipelined CG methods need the vector entries generated by current GPU and other GPUs for matrix-vector product. So the communication between GPUs becomes a major performance bottleneck on miltiGPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: Conjugate Gradient, GPU, parallel programming, pipelined algorithm.

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Authors: Ahmed Mohammed Youssef Mohammed, Mohammad Reza Okhovat, Koichi Maekawa

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Small-scale RC models of both piles and tunnel ducts were produced as mockups of reality and loaded under soil confinement conditionsto investigate the damage evolution of structural RC interacting with soil. Experimental verifications usinga 3D nonlinear FE analysis program called COM3D, which was developed at the University of Tokyo, are introduced. This analysis has been used in practice for seismic performance assessment of underground ducts and in-ground LNG storage tanks in consideration of soil-structure interactionunder static and dynamic loading. Varying modes of failure of RCpilessubjected to different magnitudes of soil confinement were successfully reproduced in the proposed small-scale experiments and numerically simulated as well. Analytical simulation was applied to RC tunnel mockups under a wide variety of depth and soil confinement conditions, and reasonable matching was confirmed.

Keywords: Soil-Structure Interaction, RC pile, RC Tunnel

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Authors: Maysam Saidi, Reza Maddahian, Bijan Farhanieh

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Hydrocyclones flow field study is conducted by performing a parametric study. Effect of cone angle on deoiling hydrocyclones flow behaviour is studied in this research. Flow field of hydrocyclone is obtained by three-dimensional simulations with OpenFOAM code. Because of anisotropic behaviour of flow inside hydrocyclones LES is a suitable method to predict the flow field since it resolves large scales and model isotropic small scales. Large eddy simulation is used to predict the flow behavior of three different cone angles. Differences in tangential velocity and pressure distribution are reported in some figures.

Keywords: Deoiling hydrocyclones, Flow field, Hydrocyclone cone angle, Large Eddy Simulation, Pressure distribution

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Authors: Sen-Chi Yu, Wei-Hsin Hsu, Min-Ning Yu, Hao-Yi Hsu

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The aim of this study was to investigate the correlation between Facebook involvement and internet addiction. We sampled 577 university students in Taiwan and administered a survey of Facebook usage, Facebook involvement scale (FIS), and internet addiction scale. The FIS comprises three factors (salience, emotional support, and amusement). Results showed that the Facebook involvement scale had good reliability and validity. The correlation between Facebook involvement and internet addiction was measured at .395. This means that a higher degree of Facebook involvement indicates a greater degree of psychological dependency on the internet, and a greater propensity towards social withdrawal and other negative psychological consequences associated with internet addiction. Besides, the correlations between three factors of FIS (salience, emotional support, and amusement) and internet addiction ranged from .313-372, indicating that these neither of these factors (salience, emotional support, and amusement) is more effective than the others in predicting internet dependency.

Keywords: Social networking sites, Facebook, Facebook Involvement, Internet Addiction

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Authors: Buntheng Chhorn, WooYoung Jung

Abstract:

Large-scale swing has been used in entertainment and performance, especially in circus, for a very long time. To increase the safety of this type of structure, a thorough analysis for displacement and bearing stress was performed for an extreme condition where a full cycle swing occurs. Different masses, ranging from 40 kg to 220 kg, and velocities were applied on the swing. Then, based on the solution of differential dynamics equation, swing velocity response to harmonic force was obtained. Moreover, the resistance capacity was estimated based on ACI steel structure design guide. Subsequently, numerical analysis was performed in ABAQUS to obtain the stress on each frame of the swing. Finally, the analysis shows that the expansion of swing structure frame section was required for mass bigger than 150kg.

Keywords: Swing structure, displacement, bearing stress, dynamic loads response, finite element analysis.

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Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang

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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.

Keywords: Acute hepatitis, Medical resource cost, Artificial neural network, Support vector regression.

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Authors: J. Hrabovský, M. Chabičovský, J. Horský

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Water spray cooling is a technique typically used in heat treatment and other metallurgical processes where controlled temperature regimes are required. Water spray cooling is used in static (without movement) or dynamic (with movement of the steel plate) regimes. The static regime is notable for the fixed position of the hot steel plate and fixed spray nozzle. This regime is typical for quenching systems focused on heat treatment of the steel plate. The second application of spray cooling is the dynamic regime. The dynamic regime is notable for its static section cooling system and moving steel plate. This regime is used in rolling and finishing mills. The fixed position of cooling sections with nozzles and the movement of the steel plate produce nonhomogeneous water distribution on the steel plate. The length of cooling sections and placement of water nozzles in combination with the nonhomogeneity of water distribution lead to discontinued or interrupted cooling conditions. The impact of static and dynamic regimes on cooling intensity and the heat transfer coefficient during the cooling process of steel plates is an important issue. Heat treatment of steel is accompanied by oxide scale growth. The oxide scale layers can significantly modify the cooling properties and intensity during the cooling. The combination of static and dynamic (section) regimes with the variable thickness of the oxide scale layer on the steel surface impact the final cooling intensity. The study of the influence of the oxide scale layers with different cooling regimes was carried out using experimental measurements and numerical analysis. The experimental measurements compared both types of cooling regimes and the cooling of scale-free surfaces and oxidized surfaces. A numerical analysis was prepared to simulate the cooling process with different conditions of the section and samples with different oxide scale layers.

Keywords: Heat transfer coefficient, numerical analysis, oxide layer, spray cooling.

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Authors: M. A. Ghorbani, M. Pasbani Khiavi, F. Rezaie Moghaddam

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In the analysis of structures, the nonlinear effects due to large displacement, large rotation and materially-nonlinear are very important and must be considered for the reliable analysis. The non-linear fmite element analysis has potential as usable and reliable means for analyzing of civil structures with the availability of computer technology. In this research the large displacements and materially nonlinear behavior of shear wall is presented with developing of fmite element code using the standard Galerkin weighted residual formulation. Two-dimensional plane stress model was carried out to present the shear wall response. Total Lagangian formulation, which is computationally more effective, is used in the formulation of stiffness matrices and the Newton-Raphson method is applied for the solution of nonlinear transient equations. The details of the program formulation are highlighted and the results of the analyses are presented, along with a comparison of the response of the structure with Ansys software results. The presented model in this paper can be developed for nonlinear analysis of civil engineering structures with different material behavior and complicated geometry.

Keywords: Finite element, large displacements, materially nonlinear, shear wall.

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Authors: Greeshma Sharma, Sushil Chandra, Vijander Singh, Alok Prakash Mittal

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Navigational ability requires spatial representation, planning, and memory. It covers three interdependent domains, i.e. cognitive and perceptual factors, neural information processing, and variability in brain microstructure. Many attempts have been made to see the role of spatial representation in the navigational ability, and the individual differences have been identified in the neural substrate. But, there is also a need to address the influence of planning, memory on navigational ability. The present study aims to evaluate relations of aforementioned factors in the navigational ability. Total 30 participants volunteered in the study of a virtual shopping complex and subsequently were classified into good and bad navigators based on their performances. The result showed that planning ability was the most correlated factor for the navigational ability and also the discriminating factor between the good and bad navigators. There was also found the correlations between spatial memory recall and navigational ability. However, non-verbal episodic memory and spatial memory recall were also found to be correlated with the learning variable. This study attempts to identify differences between people with more and less navigational ability on the basis of planning and memory.

Keywords: Memory, planning navigational ability, virtual reality.

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Authors: Maryam Mirdehghani, S. Amirhassan Monadjemi

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Web sites are rapidly becoming the preferred media choice for our daily works such as information search, company presentation, shopping, and so on. At the same time, we live in a period where visual appearances play an increasingly important role in our daily life. In spite of designers- effort to develop a web site which be both user-friendly and attractive, it would be difficult to ensure the outcome-s aesthetic quality, since the visual appearance is a matter of an individual self perception and opinion. In this study, it is attempted to develop an automatic system for web pages aesthetic evaluation which are the building blocks of web sites. Based on the image processing techniques and artificial neural networks, the proposed method would be able to categorize the input web page according to its visual appearance and aesthetic quality. The employed features are multiscale/multidirectional textural and perceptual color properties of the web pages, fed to perceptron ANN which has been trained as the evaluator. The method is tested using university web sites and the results suggested that it would perform well in the web page aesthetic evaluation tasks with around 90% correct categorization.

Keywords: Web Page Design, Web Page Aesthetic, Color Spaces, Texture, Neural Networks

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Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen

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Applying strong electric field on piezoelectric actuators, on one hand very significant electroelastic material nonlinear effects will occur, on the other hand piezo plates and shells may undergo large displacements and rotations. In order to give a precise prediction of piezolaminated smart structures under large electric field, this paper develops a finite element (FE) model accounting for both electroelastic material nonlinearity and geometric nonlinearity with large rotations based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is applied to analyze a piezolaminated semicircular shell structure.

Keywords: Smart structures, piezolamintes, material nonlinearity, geometric nonlinearity, strong electric field.

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Authors: Drahoslava Janovska, Vladimir Janovsky, Kunio Tanabe

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A proof of convergence of a new continuation algorithm for computing the Analytic SVD for a large sparse parameter– dependent matrix is given. The algorithm itself was developed and numerically tested in [5].

Keywords: Analytic Singular Value Decomposition, large sparse parameter–dependent matrices, continuation algorithm of a predictorcorrector type.

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Authors: Janhavi Inamdar, S.K. Singh

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Laboratory experiments have been performed to investigate photocatalytic detoxification by using TiO2 photocatalyst for treating dairy effluent. Various operational parameters such as catalyst concentration, initial concentration, angle of tilt of solar flat plate reactor and flow rate were investigated. Results indicated that the photocatalytic detoxification process can efficiently treat dairy effluent. Experimental runs with dairy wastewater can be used to identify the optimum operational parameters to perform wastewater degradation on large scale for recycling purpose. Also effect of two different types of reactors on degradation process was analyzed.

Keywords: Photocatalytic detoxification, TiO2 photocatalyst, solar flat plate reactor, Zero effluent discharge.

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Authors: Eronini Umez-Eronini

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Compressed air energy storage (CAES) coupled with wind farms have gained attention as a means to address the intermittency and variability of wind power. However, most existing studies and implementations focus on bulk or centralized CAES plants. This study presents a dynamic model of a hybrid wind farm with distributed CAES, using air storage tanks and compressor and expander trains at each wind turbine station. It introduces the concept of a distributed CAES with linked air cooling and heating, and presents an approach to scheduling and regulating the production of compressed air and power in such a system. Mathematical models of the dynamic components of this hybrid wind farm system, including a simple transient wake field model, were developed and simulated using MATLAB, with real wind data and Transmission System Operator (TSO) absolute power reference signals as inputs. The simulation results demonstrate that the proposed ad hoc supervisory controller is able to track the minute-scale power demand signal within an error band size comparable to the electrical power rating of a single expander. This suggests that combining the global distributed CAES control with power regulation for individual wind turbines could further improve the system’s performance. The round trip electrical storage efficiency computed for the distributed CAES was also in the range of reported round trip storage electrical efficiencies for improved bulk CAES. These findings contribute to the enhancement of efficiency of wind farms without access to large-scale storage or underground caverns.

Keywords: Distributed CAES, compressed air, energy storage, hybrid wind farm, wind turbines, dynamic simulation.

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Authors: Pedro Campos, Miguel Campos, Carlos Ferreira

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Interactive installations for public spaces are a particular kind of interactive systems, the design of which has been the subject of several research studies. Sensor-based applications are becoming increasingly popular, but the human-computer interaction community is still far from reaching sound, effective large-scale interactive installations for public spaces. The 6DSpaces project is described in this paper as a research approach based on studying the role of multisensory interactivity and how it can be effectively used to approach people to digital, scientific contents. The design of an entire scientific exhibition is described and the result was evaluated in the real world context of a Science Centre. Conclusions bring insight into how the human-computer interaction should be designed in order to maximize the overall experience.

Keywords: interaction design, human-computer interaction, multimedia, multisensory installations

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Authors: Pradeep Kumar, Abdul Wahid

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Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.

Keywords: Classification, Cascade Correlation Neural Network, Random Forest, Software reliability, TreeNet.

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: Simulation data, data summarization, spatial histograms, exploration and visualization.

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Authors: Zhifeng Kong

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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.

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Authors: Yuan-Hong Ho, Chiung-Ju Huang

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This article presents a monitoring indicators system that predicts whether a local government in Taiwan is heading for fiscal distress and identifies a suitable fiscal policy that would allow the local government to achieve fiscal balance in the long run. This system is relevant to stockholders’ interest, simple for national audit bodies to use, and provides an early warning of fiscal distress that allows preventative action to be taken.

Keywords: Fiscal distress, fiscal health, monitoring signals, 10-point scale.

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Authors: M. Priscila Ramos, Omar O. Chisari, Juan Pablo Vila Martínez

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Current literature about trade liberalization of environmental goods and services (EGS) raises doubts about the extent of the triple win-win situation for trade, development and the environment. However, much of this literature does not consider the possibility that this agreement carries technological transmissions, either through trade or foreign direct investment. This paper presents a computable general equilibrium model calibrated for Argentina, where there are alternative technologies (one dirty and one clean according to carbon emissions) to produce the same goods. In this context, the trade liberalization of EGS allows to increase GDP, trade, reduce unemployment and improve the households welfare. However, the capital mobility appears as the key assumption to jointly reach the environmental target, when the positive scale effect generated by the increase in trade is offset by the change in the composition of production (composition and technical effects by the use of the clean alternative technology) and of consumption (composition effect by substitution of relatively lesspolluting imported goods).

Keywords: CGE modeling, CO2 emissions, composition effect, scale effect, technique effect, trade liberalization of EGS.

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Authors: B.-Y.-S. Lau, Y.-C.-T. Jonathan, M.-S. Alias

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Heritage trees are natural large, individual trees with exceptionally value due to association with age or event or distinguished people. In Malaysia, there is an abundance of tropical heritage trees throughout the country. It is essential to set up a repository of heritage trees to prevent valuable trees from being cut down. In this cross domain study, a web-based online expert system namely the Heritage Tree Expert Assessment and Classification (HTEAC) is developed and deployed for public to nominate potential heritage trees. Based on the nomination, tree care experts or arborists would evaluate and verify the nominated trees as heritage trees. The expert system automatically rates the approved heritage trees according to pre-defined grades via Delphi technique. Features and usability test of the expert system are presented. Preliminary result is promising for the system to be used as a full scale public system.

Keywords: Arboriculture, Delphi, expert system, heritage tree, urban forestry.

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Authors: Zuhair Kadhim Jahanger, S. Joseph Antony

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The available studies in the literature which dealt with the scale effects of strip footings on different sand packing systematically still remain scarce. In this research, the variation of ultimate bearing capacity and deformation pattern of soil beneath strip footings of different widths under plane-strain condition on the surface of loose, medium-dense and dense sand have been systematically studied using experimental and noninvasive methods for measuring microscopic deformations. The presented analyses are based on model scale compression test analysed using Particle Image Velocimetry (PIV) technique. Upper bound analysis of the current study shows that the maximum vertical displacement of the sand under the ultimate load increases for an increase in the width of footing, but at a decreasing rate with relative density of sand, whereas the relative vertical displacement in the sand decreases for an increase in the width of the footing. A well agreement is observed between experimental results for different footing widths and relative densities. The experimental analyses have shown that there exists pronounced scale effect for strip surface footing. The bearing capacity factors Nγ rapidly decrease up to footing widths B=0.25 m, 0.35 m, and 0.65 m for loose, medium-dense and dense sand respectively, after that there is no significant decrease in Nγ. The deformation modes of the soil as well as the ultimate bearing capacity values have been affected by the footing widths. The obtained results could be used to improve settlement calculation of the foundation interacting with granular soil.

Keywords: PIV, granular mechanics, scale effect, upper bound analysis.

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Authors: Thanut Kallaka, Ching-Jong Wang

Abstract:

High level and high velocity flood flows are potentially harmful to bridge piers as evidenced in many toppled piers, and among them the single-column piers were considered as the most vulnerable. The flood flow characteristic parameters including drag coefficient, scouring and vortex shedding are built into a pier-flood interaction model to investigate structural safety against flood hazards considering the effects of local scouring, hydrodynamic forces, and vortex induced resonance vibrations. By extracting the pier-flood simulation results embedded in a neural networks code, two cases of pier toppling occurred in typhoon days were reexamined: (1) a bridge overcome by flash flood near a mountain side; (2) a bridge washed off in flood across a wide channel near the estuary. The modeling procedures and simulations are capable of identifying the probable causes for the tumbled bridge piers during heavy floods, which include the excessive pier bending moments and resonance in structural vibrations.

Keywords: Bridge piers, Neural networks, Scour depth, Structural safety, Vortex shedding

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