Search results for: Data science

Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

Abstract:

Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: Database, forensic genetics, genetic analysis, sample management, software solution.

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

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

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

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Authors: Mark Joseph Quinto, Roan Beronilla, Guiller Damian, Eliza Camaso, Ronaldo Alberto

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Forest inventories are essential to assess the composition, structure and distribution of forest vegetation that can be used as baseline information for management decisions. Classical forest inventory is labor intensive and time-consuming and sometimes even dangerous. The use of Light Detection and Ranging (LiDAR) in forest inventory would improve and overcome these restrictions. This study was conducted to determine the possibility of using LiDAR derived data in extracting high accuracy forest biophysical parameters and as a non-destructive method for forest status analysis of San Manual, Pangasinan. Forest resources extraction was carried out using LAS tools, GIS, Envi and .bat scripts with the available LiDAR data. The process includes the generation of derivatives such as Digital Terrain Model (DTM), Canopy Height Model (CHM) and Canopy Cover Model (CCM) in .bat scripts followed by the generation of 17 composite bands to be used in the extraction of forest classification covers using ENVI 4.8 and GIS software. The Diameter in Breast Height (DBH), Above Ground Biomass (AGB) and Carbon Stock (CS) were estimated for each classified forest cover and Tree Count Extraction was carried out using GIS. Subsequently, field validation was conducted for accuracy assessment. Results showed that the forest of San Manuel has 73% Forest Cover, which is relatively much higher as compared to the 10% canopy cover requirement. On the extracted canopy height, 80% of the tree’s height ranges from 12 m to 17 m. CS of the three forest covers based on the AGB were: 20819.59 kg/20x20 m for closed broadleaf, 8609.82 kg/20x20 m for broadleaf plantation and 15545.57 kg/20x20m for open broadleaf. Average tree counts for the tree forest plantation was 413 trees/ha. As such, the forest of San Manuel has high percent forest cover and high CS.

Keywords: Carbon stock, forest inventory, LiDAR, tree count.

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

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

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

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Authors: Somlak Wannarumon, Apichai Ritvirool, Thana Boonrit

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The paper proposes a new concept in developing collaborative design system. The concept framework involves applying simulation of supply chain management to collaborative design called – 'SCM–Based Design Tool'. The system is developed particularly to support design activities and to integrate all facilities together. The system is aimed to increase design productivity and creativity. Therefore, designers and customers can collaborate by the system since conceptual design. JAG: Jewelry Art Generator based on artificial intelligence techniques is integrated into the system. Moreover, the proposed system can support users as decision tool and data propagation. The system covers since raw material supply until product delivery. Data management and sharing information are visually supported to designers and customers via user interface. The system is developed on Web–assisted product development environment. The prototype system is presented for Thai jewelry industry as a system prototype demonstration, but applicable for other industry.

Keywords: Collaborative design, evolutionary art, jewelry design, supply chain management.

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Authors: Somlak Wannarumon, Apichai Ritvirool, Thana Boonrit

Abstract:

The paper proposes a new concept in developing collaborative design system. The concept framework involves applying simulation of supply chain management to collaborative design called – 'SCM–Based Design Tool'. The system is developed particularly to support design activities and to integrate all facilities together. The system is aimed to increase design productivity and creativity. Therefore, designers and customers can collaborate by the system since conceptual design. JAG: Jewelry Art Generator based on artificial intelligence techniques is integrated into the system. Moreover, the proposed system can support users as decision tool and data propagation. The system covers since raw material supply until product delivery. Data management and sharing information are visually supported to designers and customers via user interface. The system is developed on Web–assisted product development environment. The prototype system is presented for Thai jewelry industry as a system prototype demonstration, but applicable for other industry.

Keywords: Collaborative design, evolutionary art, jewelry design, supply chain management.

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Authors: Zundong Zhang, Limin Jia, Zhao Tian, Yanfang Yang

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Travel Demands influence micro-level traffic behavior, furthermore traffic states. In order to evaluate the effect of travel demands on traffic states, this paper introduces the Demand- Motivation-Behaviors (DMB) micro traffic behavior analysis model which denotes that vehicles behaviors are determines by motivations that relies on traffic demands from the perspective of behavior science. For vehicles, there are two kinds of travel demands: reaching travel destinations from orientations and meeting expectations of travel speed. To satisfy travel demands, the micro traffic behaviors are delivered such as car following behavior, optional and mandatory lane changing behaviors. Especially, mandatory lane changing behaviors depending on travel demands take strong impact on traffic states. In this paper, we define the DMB-based cellular automate traffic simulation model to evaluate the effect of travel demands on traffic states under the different δ values that reflect the ratio of mandatory lane-change vehicles.

Keywords: Demand-Motivation-Behavior, Mandatory Lane Changing, Traffic Cellular Automata.

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Authors: Dominic Wentworth-Linton, Shian Gao

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This project was aimed at investigating the effect of velocity stacks on the intakes of internal combustion engines for motorsport applications. The intake systems in motorsport are predominantly fuel injection with a plate mounted for the stacks. Using Computational Fluid Dynamics software, the relationship between the stack length and power and torque delivery across the engine’s rev range was investigated and the results were used to choose the best option for its intended motorsport discipline. The test results are expected to vary with engine geometry and its natural manufacturer characteristics. The test was also relevant in bridging between computational data and real simulation as the results show flow, pressure and velocity readings but the behaviour of the engine is inferred from the nature of each test. The results of the data analysis were tested in a real-life simulation on a dynamometer to prove the theory of stack length on power and torque delivery, which helps determine the most suitable stack for the Vauxhall engine for rallying in the Caribbean.

Keywords: CFD simulation, internal combustion engine, intake system, dynamometer test.

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Authors: Andreia Guimarães Farnese, Mateus Fernandes Réu Urban, Leandro Procópio, Renato Zângaro, Regiane Albertini

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Senescence changes include postural balance, inferring the risk of falls, and can lead to fractures, bedridden, and the risk of death. Physical activity, e.g., cardiovascular exercises, is notable for improving balance due to brain cell stimulations, but fine coordination exercises also elevate cell brain metabolism. This study aimed to verify whether the elderly person who performs fine motor activity has a balance similar to that of those who practice physical activity. The subjects were divided into three groups according to the activity practice: control group (CG) with seven participants for the sedentary individuals, motor coordination group (MCG) with six participants, and physical activity group (PAG) with eight participants. Data comparisons were from the Berg balance scale, Time up and Go test, and stabilometric analysis. Descriptive statistical and ANOVA analyses were performed for data analysis. The results reveal that including fine motor activities can improve the balance of the elderly and indirectly decrease the risk of falls.

Keywords: Balance, barapodometer, coordination, elderly.

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Authors: Stefaan Pauwels, Koen Inghelbrecht, Dries Heyman, Pieter Marius

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Literature reveals that many investors rely on technical trading rules when making investment decisions. If stock markets are efficient, one cannot achieve superior results by using these trading rules. However, if market inefficiencies are present, profitable opportunities may arise. The aim of this study is to investigate the effectiveness of technical trading rules in 34 emerging stock markets. The performance of the rules is evaluated by utilizing White-s Reality Check and the Superior Predictive Ability test of Hansen, along with an adjustment for transaction costs. These tests are able to evaluate whether the best model performs better than a buy-and-hold benchmark. Further, they provide an answer to data snooping problems, which is essential to obtain unbiased outcomes. Based on our results we conclude that technical trading rules are not able to outperform a naïve buy-and-hold benchmark on a consistent basis. However, we do find significant trading rule profits in 4 of the 34 investigated markets. We also present evidence that technical analysis is more profitable in crisis situations. Nevertheless, this result is relatively weak.

Keywords: technical trading rules, Reality Check, Superior Predictive Ability, emerging stock markets, data snooping

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Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

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In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: Game-based learning, knowledge based engineering, product modelling, design automation.

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Authors: Maria C. Proença, Maria T. Rebelo, Maria J. Alves, Sofia Cunha

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Vector-borne diseases are transmitted to humans by mosquitos, sandflies, bugs, ticks, and other vectors. Some are re-transmitted between vectors, if the infected human has a new contact when his levels of infection are high. The vector is infected for lifetime and can transmit infectious diseases not only between humans but also from animals to humans. Some vector borne diseases are very disabling and globally account for more than one million deaths worldwide. The mosquitoes from the complex Culex pipiens sl. are the most abundant in Portugal, and we dispose in this moment of a data set from the surveillance program that has been carried on since 2006 across the country. All mosquitos’ species are included, but the large coverage of Culex pipiens sl. and its importance for public health make this vector an interesting candidate to assess risk of disease amplification. This work focus on ports and airports identified as key areas of high density of vectors. Mosquitoes being ectothermic organisms, the main factor for vector survival and pathogen development is temperature. Minima and maxima local air temperatures for each area of interest are averaged by month from data gathered on a daily basis at the national network of meteorological stations, and interpolated in a geographic information system (GIS). The range of temperatures ideal for several pathogens are known and this work shows how to use it with the meteorological data in each port and airport facility, to focus an efficient implementation of countermeasures and reduce simultaneously risk transmission and mitigation costs. The results show an increased alert with decreasing latitude, which corresponds to higher minimum and maximum temperatures and a lower amplitude range of the daily temperature.

Keywords: Human health, risk assessment, risk management, vector-borne diseases.

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Authors: Lele Zhang, HuiLeng Choo, Alexander Konyukhov, Shuguang Li

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China is currently the world's largest producer and distributor of electric bicycle (e-bike). The increasing number of e-bikes on the road is accompanied by rising injuries and even deaths of e-bike drivers. Therefore, there is a growing need to improve the safety structure of e-bikes. This 3D frictionless contact analysis is a preliminary, but necessary work for further structural design improvement of an e-bike. The contact analysis between e-bike and the ground was carried out as follows: firstly, the Penalty method was illustrated and derived from the simplest spring-mass system. This is one of the most common methods to satisfy the frictionless contact case; secondly, ANSYS static analysis was carried out to verify finite element (FE) models with contact pair (without friction) between e-bike and the ground; finally, ANSYS transient analysis was used to obtain the data of the penetration p(u) of e-bike with respect to the ground. Results obtained from the simulation are as estimated by comparing with that from theoretical method. In the future, protective shell will be designed following the stability criteria and added to the frame of e-bike. Simulation of side falling of the improvedsafety structure of e-bike will be confirmed with experimental data.

Keywords: Frictionless contact, penalty method, e-bike, finite element.

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Authors: Dr. L. Arockiam, A. Aloysius

Abstract:

In general, class complexity is measured based on any one of these factors such as Line of Codes (LOC), Functional points (FP), Number of Methods (NOM), Number of Attributes (NOA) and so on. There are several new techniques, methods and metrics with the different factors that are to be developed by the researchers for calculating the complexity of the class in Object Oriented (OO) software. Earlier, Arockiam et.al has proposed a new complexity measure namely Extended Weighted Class Complexity (EWCC) which is an extension of Weighted Class Complexity which is proposed by Mishra et.al. EWCC is the sum of cognitive weights of attributes and methods of the class and that of the classes derived. In EWCC, a cognitive weight of each attribute is considered to be 1. The main problem in EWCC metric is that, every attribute holds the same value but in general, cognitive load in understanding the different types of attributes cannot be the same. So here, we are proposing a new metric namely Attribute Weighted Class Complexity (AWCC). In AWCC, the cognitive weights have to be assigned for the attributes which are derived from the effort needed to understand their data types. The proposed metric has been proved to be a better measure of complexity of class with attributes through the case studies and experiments

Keywords: Software Complexity, Attribute Weighted Class Complexity, Weighted Class Complexity, Data Type

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Authors: Haoyu Ma, Bin Hu, Mike Jackson, Jingzhi Yan, Wen Zhao

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In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Keywords: Sleep, Sleep stage, Automatic sleep scoring, Electroencephalography, Decision tree, Artificial neural network

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Authors: Chin S. Y., Radzi, S. N. R., Maharon, I. H., Shafawi, M. A.

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A kinetic model for propane dehydrogenation in an industrial moving bed reactor is developed based on the reported reaction scheme. The kinetic parameters and activity constant are fine tuned with several sets of balanced plant data. Plant data at different operating conditions is applied to validate the model and the results show a good agreement between the model predictions and plant observations in terms of the amount of main product, propylene produced. The simulation analysis of key variables such as inlet temperature of each reactor (Tinrx) and hydrogen to total hydrocarbon ratio (H2/THC) affecting process performance is performed to identify the operating condition to maximize the production of propylene. Within the range of operating conditions applied in the present studies, the operating condition to maximize the propylene production at the same weighted average inlet temperature (WAIT) is ΔTinrx1= -2, ΔTinrx2= +1, ΔTinrx3= +1 , ΔTinrx4= +2 and ΔH2/THC= -0.02. Under this condition, the surplus propylene produced is 7.07 tons/day as compared with base case.

Keywords: kinetic model, dehydrogenation, simulation, modeling, propane

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Authors: Parvinder Singh Sandhu, Dalwinder Singh Salaria, Hardeep Singh

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Software Reusability is primary attribute of software quality. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. In this paper, we have devised the framework of metrics that uses McCabe-s Cyclometric Complexity Measure for Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling Metric values of the software component as input attributes and calculated reusability of the software component. Here, comparative analysis of the fuzzy, Neuro-fuzzy and Fuzzy-GA approaches is performed to evaluate the reusability of software components and Fuzzy-GA results outperform the other used approaches. The developed reusability model has produced high precision results as expected by the human experts.

Keywords: Software Reusability, Software Metrics, Neural Networks, Genetic Algorithm, Fuzzy Logic.

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Authors: Yasaswi Palagummi, Sareh Rowlands

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Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GZSL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets - AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: Generalised Zero-shot Learning, Inductive Learning, Shifted-Window Attention, Swin Transformer, Vision Transformer.

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Authors: Z. Zainuddin, W. D. Wan Rosli, R. Lanouette, S. Sathasivam

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This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, pulping modeling, neural networks, preconditioned conjugate gradient.

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Authors: L. Agneni, F. Carta, C. Micheletta, V. Tersigni

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The development of a qualitative method to profile jobseekers is needed to improve the quality of the Public Employment Services (PES) in Italy. This is why the National Agency for Active Labour Market Policies (ANPAL) decided to introduce a Qualitative Profiling Service in the context of the activities carried out by local employment offices’ operators. The qualitative profiling service provides information and data regarding the jobseeker’s personal transition status, through a semi-structured questionnaire administered to PES clients during the guidance interview. The questionnaire responses allow PES staff to identify, for each client, proper activities and policy measures to support jobseekers in their reintegration into the labour market. Data and information gathered by the qualitative profiling tool are the following: frequency, modalities and motivations for clients to apply to local employment offices; clients’ expectations and skills; difficulties that they have faced during the previous working experiences; strategies, actions undertaken and activated channels for job search. These data are used to assess jobseekers’ personal and career characteristics and to measure their employability level (qualitative profiling index), in order to develop and deliver tailor-made action programmes for each client. This paper illustrates the use of the above-mentioned qualitative profiling service on the national territory and provides an overview of the main findings of the survey: concerning the difficulties that unemployed people face in finding a job and their perception of different aspects related to the transition in the labour market. The survey involved over 10.000 jobseekers registered with the PES. Most of them are beneficiaries of the “citizens' income”, a specific active labour policy and social inclusion measure. Furthermore, data analysis allows classifying jobseekers into a specific group of clients with similar features and behaviours, on the basis of socio-demographic variables, customers' expectations, needs and required skills for the profession for which they seek employment. Finally, the survey collects PES staff opinions and comments concerning clients’ difficulties in finding a new job and also their strengths. This is a starting point for PESs’ operators to define adequate strategies to facilitate jobseekers’ access or reintegration into the labour market.

Keywords: Labour market transition, Public Employment Services, qualitative profiling, vocational guidance.

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Authors: Ming-Ta Yang, Jyh-Cherng Gu, Chun-Wei Huang, Jin-Lung Guan

Abstract:

Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.

Keywords: Circuit breaker, Condition base maintenance, Intelligent electronic device, Time base maintenance, SCADA.

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Authors: Toby Gibbs, Suwaree Yordchim

Abstract:

This research analyzes factors affecting the success of Litecoin Value within Thailand and develops a guideline for selfreliance for effective business implementation. Samples in this study included 119 people through surveys. The results revealed four main factors affecting the success as follows: 1) Future Career training should be pursued in applied Litecoin development. 2) Didn't grasp the concept of a digital currency or see the benefit of a digital currency. 3) There is a great need to educate the next generation of learners on the benefits of Litecoin within the community. 4) A great majority didn't know what Litecoin was. The guideline for self-reliance planning consisted of 4 aspects: 1) Development planning: by arranging meet up groups to conduct further education on Litecoin and share solutions on adoption into every day usage. Local communities need to develop awareness of the usefulness of Litecoin and share the value of Litecoin among friends and family. 2) Computer Science and Business Management staff should develop skills to expand on the benefits of Litecoin within their departments. 3) Further research should be pursued on how Litecoin Value can improve business and tourism within Thailand. 4) Local communities should focus on developing Litecoin awareness by encouraging street vendors to accept Litecoin as another form of payment for services rendered.

Keywords: Litecoin, Mining, Confirmations.

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: Banking system, data envelopment analysis, DEA, integrated resilience engineering, IRE, performance evaluation, perturbation analysis.

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Authors: A. Khosravi, S. Ghadirian, J. S. McCartney

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Evaluation of the seismic-induced settlement of an unsaturated soil layer depends on several variables, among which the small strain shear modulus, G_max, and soil’s state of stress have been demonstrated to be of particular significance. Recent interpretation of trends in G_max revealed considerable effects of the degree of saturation and hydraulic hysteresis on the shear stiffness of soils in unsaturated states. Accordingly, the soil layer is expected to experience different settlement behaviors depending on the soil saturation and seasonal weathering conditions. In this study, a semi-empirical formulation was adapted to extend an existing G_max model to infer hysteretic effects along different paths of the SWRC including scanning curves. The suitability of the proposed approach is validated against experimental results from a suction-controlled resonant column test and from data reported in literature. The model was observed to follow the experimental data along different paths of the SWRC, and showed a slight hysteresis in shear modulus along the scanning curves.

Keywords: Hydraulic hysteresis, Scanning path, Small strain shear modulus, Unsaturated soil.

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Authors: A. A. Betah

Abstract:

This research was performed to evaluate the attitudes of rural women towards education, health and work outside the home. The study was based on a random sample of 147 rural women, Kafr-Rahmaniyah village was chosen for the study because its life expectancy at birth for females, education and percentage of females in the labor force, were the highest in the district. The study data were collected from rural female respondents, using a face-to-face questionnaire. In addition, the study estimated several factors like age, main occupation, family size, monthly household income, geographic cosmopolites, and degree of social participation for rural women respondents. Using Statistical Package for the Social Sciences (SPSS), data were analyzed by non-parametric statistical methods. The main finding in this study was a significant relationship between each of the previous variables and each of rural women’s attitudes toward education, health, and work outside home. The study concluded with some recommendations. The most important element is ensuring attention to rural women’s needs, requirements and rights via raising their health awareness, education and their contributions in their society.

Keywords: Attitudes, education, health, rural women, work outside the home.

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Authors: Mohammed B. Abohedma, Milad M. Alshebani

Abstract:

Recent trends in building constructions in Libya are more toward tall (high-rise) building projects. As a consequence, a better estimation of the lateral loading in the design process is becoming the focal of a safe and cost effective building industry. Byin- large, Libya is not considered a potential earthquake prone zone, making wind is the dominant design lateral loads. Current design practice in the country estimates wind speeds on a mere random bases by considering certain factor of safety to the chosen wind speed. Therefore, a need for a more accurate estimation of wind speeds in Libya was the motivation behind this study. Records of wind speed data were collected from 22 metrological stations in Libya, and were statistically analysed. The analysis of more than four decades of wind speed records suggests that the country can be divided into four zones of distinct wind speeds. A computer “survey" program was manipulated to draw design wind speeds contour map for the state of Libya. The paper presents the statistical analysis of Libya-s recorded wind speed data and proposes design wind speed values for a 50-year return period that covers the entire country.

Keywords: Ccontour map, return period, wind speed, and zone.

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

Abstract:

This paper aims to provide an interpretation of artificial neural networks (ANNs) and explore some of its implications. The interpretation views ANNs as a memory which encodes instances of experience. An experiment explores the behavior of encoding and retrieval of instances from memory. A localised representation ANN is created that allows control over encoding and retrieved memory sample size and is experimented with using the MNIST digits dataset. The relationship between input familiarity, conflict within retrieved samples, and error rates is described and demonstrated to be an effective driver for memory encoding. Results indicate that selective encoding and retrieval samples that allow detection of memory conflicts produce optimal performance, and that error rates are normally distributed with input familiarity and conflict. By using input familiarity and sample consistency to guide memory encoding, the number of encoding trials on the dataset were reduced to 18.33% of the training data while maintaining good recognition performance on the test data.

Keywords: Artificial Neural Networks, ANNs, representation, memory, conflict monitoring, confidence.

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Authors: M. H. Ayazi, M. Qamari, N.Hedayat, A. Rohani

Abstract:

Simulation of the flow and sedimentation process in the reservoir dams can be made by two methods of physical and mathematical modeling. The study area was within a region which ranged from the Jelogir hydrometric station to the Karkheh reservoir dam aimed at investigating the effects of stream tubes on the GSTARS-3 model behavior. The methodologies was to run the model based on 5 stream tubes in order to observe the influence of each scenario on longitudinal profiles, cross-section, flow velocity and bed load sediment size. Results further suggest that the use of two stream tubes or more which result in the semi-two-dimensional model will yield relatively closer results to the observational data than a singular stream tube modeling. Moreover, the results of modeling with three stream tubes shown to yield a relatively close results with the observational data. The overall conclusion of the paper is with applying various stream tubes; it would be possible to yield a significant influence on the modeling behavior Vis-a Vis the bed load sediment size.

Keywords: Karkheh, stream tubes, GSTARS-3 Model, Jelogir hydrometric station.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop

Abstract:

The problem of frequent pattern discovery is defined as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a database. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages. Such paradigm is inefficient when set of patterns is large and the frequent pattern is long. We suggest a high-level declarative style of programming apply to the problem of frequent pattern discovery. We consider two languages: Haskell and Prolog. Our intuitive idea is that the problem of finding frequent patterns should be efficiently and concisely implemented via a declarative paradigm since pattern matching is a fundamental feature supported by most functional languages and Prolog. Our frequent pattern mining implementation using the Haskell and Prolog languages confirms our hypothesis about conciseness of the program. The comparative performance studies on line-of-code, speed and memory usage of declarative versus imperative programming have been reported in the paper.

Keywords: Frequent pattern mining, functional programming, pattern matching, logic programming.

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Authors: F. Al-Mufadi, F. Djavanroodi

Abstract:

Ultrafine grained (UFG) and nanostructured (NS) materials have experienced a rapid development during the last decade and made profound impact on every field of materials science and engineering. The present work has been undertaken to develop ultrafine grained pure copper by severe plastic deformation method and to examine the impact property by different characterizing tools.

For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90^°, 17^° and 20mm had been designed and manufactured. Commercial pure copper billets were ECAPed up to four passes by route B_C at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 136HV from 52HV after the final pass. Also, about 285% and 125% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by imposing ECAP process and pass numbers. It is needed to say that about 56% reduction in the impact energy have been attained for the samples as contrasted to annealed specimens. 

Keywords: SPD, ECAP, Pure Cu, Impact property.

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