Search results for: Social support
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3164

Search results for: Social support

2744 Social Work Practice to Labour Welfare: A Proposed Model of Field Work Practicum and Role of Social Worker in India

Authors: Naeem Ahmed

Abstract:

Social work is a professional activity based on the approach of “helping people to help themselves” (Stroup). Social work education and practice both are based on humanitarian philosophy in which social workers try to increase the happiness of the society and to reduce the problems of society. Labour welfare is a specialised field of social work which especially focuses on welfare of organised and unorganised labour. In India labour is facing numerous problems in both organised and unorganised sectors because of ignorance, illiteracy, high rate of unemployment etc. In most of the Indian social work institutions we have this specialization with different names like Human Resource Management or Industrial Relation and Personnel Management or Industrial Relations and Labour Welfare or Industrial Social Work etc. Field work practice is integrated part of social work education curriculum in all specialised field. In India we have different field work practice models being followed in different institutions. The main objective of this paper is to prepare a universal field work practicum model in the field of labour welfare. This paper is exploratory in nature, researcher used personal experience and secondary data (model of field work practice in different institutions like Aligarh Muslim University, Pondicherry University, Central University of Karnataka, University of Lucknow, MJP Rohilkhand University Bareilly etc.) Researcher found that there is an immediate need to upgrade the curriculum or field work practice in this particular field, as more than 40 percent of total population engaged in either unorganised or organised sector (NSSO 2011-12) and they are not aware about their rights. In this way a social worker can play an important role in existing labour welfare facilities by making them aware.

Keywords: Fieldwork, labour welfare, organised labour, social work practice, unorganised labour.

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2743 A Promising Approach to Supporting Knowledge-Intensive Business Processes: Business Case Management

Authors: Zeljko Panian

Abstract:

Through the course of this paper we define Business Case Management and its characteristics, and highlight its link to knowledge workers. Business Case Management combines knowledge and process effectively, supporting the ad hoc and unpredictable nature of cases, and coordinate a range of other technologies to appropriately support knowledge-intensive processes. We emphasize the growing importance of knowledge workers and the current poor support for knowledge work automation. We also discuss the challenges in supporting this kind of knowledge work and propose a novel approach to overcome these challenges.

Keywords: Knowledge management, knowledge workers, business process management, business case management, automation.

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2742 Movie Genre Preference Prediction Using Machine Learning for Customer-Based Information

Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: Computational social science, movie preference, machine learning, SVM.

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2741 Prediction of Writer Using Tamil Handwritten Document Image Based on Pooled Features

Authors: T. Thendral, M. S. Vijaya, S. Karpagavalli

Abstract:

Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.

Keywords: Classification, Feature extraction, Support vector machine, Training, Writer.

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2740 Prediction of Writer Using Tamil Handwritten Document Image Based on Pooled Features

Authors: T. Thendral, M. S. Vijaya, S. Karpagavalli

Abstract:

Tamil handwritten document is taken as a key source of data to identify the writer. Tamil is a classical language which has 247 characters include compound characters, consonants, vowels and special character. Most characters of Tamil are multifaceted in nature. Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. It has been reported on 100% of prediction accuracy by RBF and polynomial kernel based classification model.

Keywords: Classification, Feature extraction, Support vector machine, Training, Writer.

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2739 Numerical Modeling of Various Support Systems to Stabilize Deep Excavations

Authors: M. Abdallah

Abstract:

Urban development requires deep excavations near buildings and other structures. Deep excavation has become more a necessity for better utilization of space as the population of the world has dramatically increased. In Lebanon, some urban areas are very crowded and lack spaces for new buildings and underground projects, which makes the usage of underground space indispensable. In this paper, a numerical modeling is performed using the finite element method to study the deep excavation-diaphragm wall soil-structure interaction in the case of nonlinear soil behavior. The study is focused on a comparison of the results obtained using different support systems. Furthermore, a parametric study is performed according to the remoteness of the structure.

Keywords: Deep excavation, ground anchors, interaction, struts.

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2738 An Anomaly Detection Approach to Detect Unexpected Faults in Recordings from Test Drives

Authors: Andreas Theissler, Ian Dear

Abstract:

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

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2737 Efficient Scheduling Algorithm for QoS Support in High Speed Downlink Packet Access Networks

Authors: MohammadReza HeidariNezhad, Zuriati Ahmad Zukarnain, Nur Izura Udzir, Mohamed Othman

Abstract:

In this paper, we propose APO, a new packet scheduling scheme with Quality of Service (QoS) support for hybrid of real and non-real time services in HSDPA networks. The APO scheduling algorithm is based on the effective channel anticipation model. In contrast to the traditional schemes, the proposed method is implemented based on a cyclic non-work-conserving discipline. Simulation results indicated that proposed scheme has good capability to maximize the channel usage efficiency in compared to another exist scheduling methods. Simulation results demonstrate the effectiveness of the proposed algorithm.

Keywords: Scheduling Algorithm, Quality of Service, HSDPA.

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2736 Corporate Social Responsibility and Creating Shared Value: Case of Latvia

Authors: Inga Lapiņa, Indra Borkus, Olga Stariņeca

Abstract:

Creating shared value (CSV) is a newly introduced concept whose essence and expressions, relationship to Corporate social responsibility (CSR) and implications for the business and society is now at the core of management and social responsibility debates of the scientific world. The aim of the paper is to gain clearer understanding of the CSR and CSV concepts, their implementation and role in sustainable development of organizations in Latvia. In this paper the authors discuss and compare the two conceptsand, based on the results of Sustainability Index (SI) initiative and analysis of publically available company information, evaluate their implementation in Latvia and draw conclusions on the development trends and potential of these approaches in Latvian market.

Keywords: Corporate Social Responsibility, Creating Shared Value, Sustainability Index.

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2735 The Association between Affective States and Sexual/Health-Related Status among Men Who Have Sex with Men in China: An Exploration Study Using Social Media Data

Authors: Zhi-Wei Zheng, Zhong-Qi Liu, Jia-Ling Qiu, Shan-Qing Guo, Zhong-Wei Jia, Chun Hao

Abstract:

Objectives: The purpose of this study was to understand and examine the association between diurnal mood variation and sexual/health-related status among men who have sex with men (MSM) using data from MSM Chinese Twitter messages. The study consists of 843,745 postings of 377,610 MSM users located in Guangdong that were culled from the MSM Chinese Twitter App. Positive affect, negative affect, sexual related behaviors, and health-related status were measured using the Simplified Chinese Linguistic Inquiry and Word Count. Emotions, including joy, sadness, anger, fear, and disgust were measured using the Weibo Basic Mood Lexicon. A positive sentiment score and a positive emotions score were also calculated. Linear regression models based on a permutation test were used to assess associations between affective states and sexual/health-related status. In the results, 5,871 active MSM users and their 477,374 postings were finally selected. MSM expressed positive affect and joy at 8 a.m. and expressed negative affect and negative emotions between 2 a.m. and 4 a.m. In addition, 25.1% of negative postings were directly related to health and 13.4% reported seeking social support during that sensitive period. MSM who were senior, educated, overweight or obese, self-identified as performing a versatile sex role, and with less followers, more followers, and less chat groups mainly expressed more negative affect and negative emotions. MSM who talked more about sexual-related behaviors had a higher positive sentiment score (β=0.29, p < 0.001) and a higher positive emotions score (β = 0.16, p < 0.001). MSM who reported more on their health status had a lower positive sentiment score (β = -0.83, p < 0.001) and a lower positive emotions score (β = -0.37, p < 0.001). The study concluded that psychological intervention based on an app for MSM should be conducted, as it may improve mental health.

Keywords: Affect, men who have sex with men, sexual-related behaviors, health-related status, social media.

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2734 Motivations for Using Social Networking Sites by College Students for Educational Purposes

Authors: Kholoud H. Al-Zedjali, Abir S. Al-Harrasi, Ali H. Al-Badi

Abstract:

Recently there has been a dramatic proliferation in the number of social networking sites (SNSs) users; however, little is published about what motivates college students to use SNSs in education. The main goal of this research is to explore the college students’ motives for using SNSs in education. A conceptual framework has therefore been developed to identify the main factors that influence/motivate students to use social networking sites for learning purposes. To achieve the research objectives a quantitative method was used to collect data. A questionnaire has been distributed amongst college students. The results reveal that social influence, perceived enjoyment, institute regulation, perceived usefulness, ranking up-lift, attractiveness, communication tools, free of charge, sharing material and course nature all play an important role in the motivation of college students to use SNSs for learning purposes.

Keywords: Social networking sites (SNSs), education, college students.

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2733 Two Concurrent Convolution Neural Networks TC*CNN Model for Face Recognition Using Edge

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution neural network, edges, face recognition, support vector machine.

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2732 Polymer Aerostatic Thrust Bearing under Circular Support for High Static Stiffness

Authors: S. W. Lo, C.-H. Yu

Abstract:

A new design of aerostatic thrust bearing is proposed for high static stiffness. The bearing body, which is mead of polymer covered with metallic membrane, is held by a circular ring. Such a support helps form a concave air gap to grasp the air pressure. The polymer body, which can be made rapidly by either injection or molding is able to provide extra damping under dynamic loading. The smooth membrane not only serves as the bearing surface but also protects the polymer body. The restrictor is a capillary inside a silicone tube. It can passively compensate the variation of load by expanding the capillary diameter for more air flux. In the present example, the stiffness soars from 15.85 N/μm of typical bearing to 349.85 N/μm at bearing elevation 9.5 μm; meanwhile the load capacity also enhances from 346.86 N to 704.18 N.

Keywords: Aerostatic, bearing, polymer, static stiffness.

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2731 Design and Implementation of a Software Platform Based on Artificial Intelligence for Product Recommendation

Authors: G. Settanni, A. Panarese, R. Vaira, A. Galiano

Abstract:

Nowadays, artificial intelligence is used successfully in the field of e-commerce for its ability to learn from a large amount of data. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them the most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Also, Long Short-Term Memory algorithms have been implemented and trained on historical data in order to predict customer scores of the different items. Items with the highest scores are recommended to customers.

Keywords: Deep Learning, Long Short-Term Memory, Machine Learning, Recommender Systems, Support Vector Machine.

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2730 Social Media as a Distribution Channel for Thailand’s Rice Berry Product

Authors: Phutthiwat Waiyawuththanapoom, Wannapong Waiyawuththanapoom, Pimploi Tirastittam

Abstract:

Nowadays, it is a globalization era which social media plays an important role to the lifestyle as an information source, tools to connect people together and etc. This research is object to find out about the significant level of the social media as a distribution channel to the agriculture product of Thailand. In this research, the agriculture product is the Rice Berry which is the cross-bred unmilled rice producing dark violet grain, is a combination of Hom Nin Rice and Thai Jasmine/ Fragrant Rice 105. Rice Berry has a very high nutrition and nice aroma so the product is in the growth stage of the product cycle. The problem for the Rice Berry product in Thailand is the production and the distribution channel. This study is to confirm that the social media is another option as the distribution channel for the product which is not a mass production product. This will be the role model for the other niche market product to select the distribution channel.

Keywords: Distribution, Social Media, Rice Berry, Distribution Channel.

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2729 The Internet, its Social and Ethical Problem to the Young and How Curriculum Can Address the Issue

Authors: R. Ramli

Abstract:

The impact of the information revolution is double edged. While it is applauded for its versatility and performance robustness and acclaimed for making life smooth and easy, on the other hand people are concerned about its dark side especially to younger generations. The education system should extend its educating role beyond the school to home. Parents should be included in forming the policies of Internet use as well as in the curriculum delivery. This paper discusses how curriculum can be instrumental in addressing social and ethical issues resulted from the Internet.

Keywords: Curriculum, Ethics, Internet Addiction, Social Issues

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2728 Role of Social Capital on Consumer Attitudes, Peer Influence and Behavioral Intentions: A Social Media Perspective

Authors: Qazi Mohammed Ahmed, Osman Sadiq Paracha, Iftikhar Hussain

Abstract:

The study aims to explore the unaddressed relationship between social capital and consumers’ underlying behavioral intentions. The study postulates that this association is mediated by the role of attitudes and peer influence. The research attains evidence from a usable sample of 673 responses. The majority consists of the young and energetic social media users of Pakistan that utilize virtual communities as a way of life. A variance based structural equation modeling has been applied through SmartPLS 3. The results reveal that social capital exerts a statistically supportive association with both attitudes and peer influence. Contrastingly, this predictor variable shows an insignificant linkage with behavioral intentions but this relationship is fully mediated by consumer attitudes and peer influence. The paper enhances marketing literature with respect to an unexplored society of Pakistan. It also provides a lens for the contemporary advertisers, in terms of supporting their social media campaigns with affiliative and cohesive elements. The study also identifies a series of predictor variables that could further be tested with attitudes, subjective norms and behavioral responses.

Keywords: Behavioral intentions, consumer attitudes, peer influence, social capital.

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2727 Interdisciplinary Principles of Field-Like Coordination in the Case of Self-Organized Social Systems1

Authors: D. Plikynas, S. Masteika, A. Budrionis

Abstract:

This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.

Keywords: field-based coordination, multi-agent systems, information-rich social networks, pervasive information field

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2726 The Integration of Cleaner Production Innovation and Creativity for Supply Chain Sustainability of Bogor Batik SMEs

Authors: Sawarni Hasibuan, Juliza Hidayati

Abstract:

Competitiveness and sustainability issues not only put pressure on big companies, but also small and medium enterprises (SMEs). SMEs Batik Bogor is one of the local culture-based creative industries in Bogor city which is also dealing with the issue of sustainability. The purpose of this research is to develop framework of sustainability at SMEs Batik Indonesia case of SMEs Batik Bogor by integrating innovation of cleaner production in its supply chain. The approach used is desk study, field survey, in-depth interviews, and benchmarking best practices of SMEs sustainability. In-depth interviews involve stakeholders to identify the needs and standards of sustainability of SMEs Batik. Data analysis was done by benchmarking method, Multi Dimension Scaling (MDS) method, and Strength, Weakness, Opportunity, Threat (SWOT) analysis. The results recommend the framework of sustainability for SMEs Batik in Indonesia. The sustainability status of SMEs Batik Bogor is classified as Moderate Sustainable. Factors that support the sustainability of SMEs Batik Bogor such is a strong commitment of top management in adopting cleaner production innovation and creativity approach. Successful cleaner production innovations are implemented primarily in the substitution of dye materials from toxic to non-toxic, reducing the intensity of non-renewable energy use, as well as the reuse and recycle of solid waste. “Mosaic Batik” is one of the innovations of solid waste utilization of batik waste produced by company R&D center that gives benefit to three pillars of sustainability, that is financial benefit, environmental benefit, and social benefit. The sustainability of SMEs Batik Bogor cannot be separated from the support of Bogor City Government which proactively facilitates the promotion of sustainable innovation produced by SMEs Batik Bogor.

Keywords: Cleaner production innovation, creativity, SMEs Batik, sustainability supply chain.

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2725 A Hybrid Machine Learning System for Stock Market Forecasting

Authors: Rohit Choudhry, Kumkum Garg

Abstract:

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators of highly correlated stocks, not only the stock to be predicted. The genetic algorithm is used to select the set of most informative input features from among all the technical indicators. The results show that the hybrid GA-SVM system outperforms the stand alone SVM system.

Keywords: Genetic Algorithms, Support Vector Machines, Stock Market Forecasting.

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2724 Breast Motion and Discomfort of Chinese Women in Three Breast Support Conditions

Authors: X.N. Chen, J.P. Wang, D. Jiang, S.M. Shen, Y.K. Yang

Abstract:

Breast motion and discomfort has been studied in Australia, Britain and the United States, while little information was known about the breast motion conditions of Chinese women. The aim of this paper was to study the breast motion and discomfort of Chinese women in no bra condition, daily bra condition and sports bra condition. Breast motion and discomfort of 8 participants was assessed during walking at 5km h-1 and running at 10km h-1. Statistical methods were used to analyze the difference and relationship between breast displacement, perceived breast motion and breast discomfort. Three indexes were developed to evaluate the functions of bras on reducing objective breast motion, subjective breast motion and breast discomfort. The result showed that breast motion of Chinese women was smaller than previous research, which may be resulted from smaller breast size in Asian women.

Keywords: Breast discomfort, breast motion, breast support conditions, Chinese women.

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2723 Holistic Simulation-Based Impact Analysis Framework for Sustainable Manufacturing

Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

Abstract:

The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: Life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development.

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2722 Podemos Party Origin: From Social Protest to Spanish Parliament

Authors: Víctor Manuel Muñoz-Sánchez, Antonio Manuel Pérez-Flores

Abstract:

This paper analyzes the institutionalization of social protest in Spain. In the current crisis Podemos party seems to represent the political positions of the most affected citizens by the economic situation. It studies using quantitative techniques (statistical bivariate analysis), focusing on the exploitation of several bases of statistics data from the Center for Sociological and Research of Spanish Government, 15M movement characterization to its institutionalization in the Podemos party. Making a comparison between the participant's profile by the 15M and the social bases of Podemos votes. Data on the transformation of the socio-demographic profile of the fans, connoisseurs and 15M participants and voters are given.

Keywords: Collective action, emerging parties, political parties, social protest.

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2721 Knowledge-Driven Decision Support System Based on Knowledge Warehouse and Data Mining by Improving Apriori Algorithm with Fuzzy Logic

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

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2720 A Bayesian Classification System for Facilitating an Institutional Risk Profile Definition

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining.

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2719 Delineating Concern Ground in Block Caving – Underground Mine Using Ground Penetrating Radar

Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

Abstract:

Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: Block caving, ground penetrating radar, reflectivity, RQD.

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2718 Effect of the Internet on Social Capital

Authors: Safaee Safiollah , Javadi Alimohammad, Javadi Maryam

Abstract:

Internet access is a vital part of the modern world and an important tool in the education of our children. It is present in schools, homes and even shopping malls. Mastering the use of the internet is likely to be an important skill for those entering the job markets of the future. An internet user can be anyone he or she wants to be in an online chat room, or play thrilling and challenging games against other players from all corners of the globe. It seems at present time (or near future) for many people relationships in the real world may be neglected as those in the virtual world increase in importance. Internet is provided a fast mode of transportation caused freedom from family bonds and mixing with different cultures and new communities. This research is an attempt to study effect of Internet on Social capital. For this purpose a survey technique on the sample size amounted 168 students of Payame Noor University of Kermanshah city in country of Iran were considered. Degree of social capital is moderate. With the help of the Multi-variable Regression, variables of Iranian message attractive, Interest to internet with effect of positive and variable Creating a cordial atmosphere with negative effect be significant.

Keywords: Internet, Social Capital, social participation Social trust

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2717 Analysis of the Evolution of Social and Economic Indicators of the Mercosur´s Members: 1980-2012

Authors: L. Aparecida Bastos, J. Leige Lopes, J. Crepaldi, R. Monteiro da Silva

Abstract:

The objective of this study is to analyze the evolution of some social and economic indicators of Mercosur´s economies from 1980 to 2012, based on the statistics of the Latin American Integration Association (LAIA). The objective is to observe if after the accession of these economies to Mercosur (the first accessions occurred in 1994) these indicators showed better performance, in order to demonstrate if economic integration contributed to improved trade, macroeconomic performance, and level of social and economic development of member countries. To this end, the methodologies used will be a literature review and descriptive statistics. The theoretical framework that guides the work are the theories of Integration: Classical Liberal, Marxist and structural-proactive. The results reveal that most social and economic indicators showed better performance in those economies that joined Mercosur after 1994. This work is the result of an investigation already completed.

Keywords: Economic integration, mercosur, social indicators, economic indicators.

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2716 The Antecedents of Facebook Check in Adoption Intention: The Perspective of Social Influence

Authors: Hsiu-Hua Cheng

Abstract:

Recently, the competition between websites becomes intense. How to make users “adopt” their websites is an issue of urgent importance for online communities companies. Social procedures (such as social influence) can possibly explain how and why users’ technologies usage behaviors affect other people to use the technologies. This study proposes two types of social influences on the initial usage of Facebook Check In-friends and group members. Besides, this study combines social influences theory and social network theory to explore the factors influencing initial usage of Facebook Check In. This study indicates that Facebook friends’ previous usage of Facebook Check In and Facebook group members’ previous usage of Facebook Check In will positively influence focal actors’ Facebook Check In adoption intention, and network centrality will moderate the relationships among Facebook friends’ previous usage of Facebook Check In, Facebook group members’ previous usage of Facebook Check In and focal actors’ Facebook Check In adoption intention. The article concludes with contributions to academic research and practice.

Keywords: Social Influence, Adoption Intention, Facebook Check In, Previous Usage behavior.

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2715 Target Detection with Improved Image Texture Feature Coding Method and Support Vector Machine

Authors: R. Xu, X. Zhao, X. Li, C. Kwan, C.-I Chang

Abstract:

An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.

Keywords: Image texture analysis, feature extraction, target detection, pattern classification.

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