Search results for: social network potentials
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13816

Search results for: social network potentials

11716 Earthquake Identification to Predict Tsunami in Andalas Island, Indonesia Using Back Propagation Method and Fuzzy TOPSIS Decision Seconder

Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

Abstract:

Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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11715 Enhanced Retrieval-Augmented Generation (RAG) Method with Knowledge Graph and Graph Neural Network (GNN) for Automated QA Systems

Authors: Zhihao Zheng, Zhilin Wang, Linxin Liu

Abstract:

In the research of automated knowledge question-answering systems, accuracy and efficiency are critical challenges. This paper proposes a knowledge graph-enhanced Retrieval-Augmented Generation (RAG) method, combined with a Graph Neural Network (GNN) structure, to automatically determine the correctness of knowledge competition questions. First, a domain-specific knowledge graph was constructed from a large corpus of academic journal literature, with key entities and relationships extracted using Natural Language Processing (NLP) techniques. Then, the RAG method's retrieval module was expanded to simultaneously query both text databases and the knowledge graph, leveraging the GNN to further extract structured information from the knowledge graph. During answer generation, contextual information provided by the knowledge graph and GNN is incorporated to improve the accuracy and consistency of the answers. Experimental results demonstrate that the knowledge graph and GNN-enhanced RAG method perform excellently in determining the correctness of questions, achieving an accuracy rate of 95%. Particularly in cases involving ambiguity or requiring contextual information, the structured knowledge provided by the knowledge graph and GNN significantly enhances the RAG method's performance. This approach not only demonstrates significant advantages in improving the accuracy and efficiency of automated knowledge question-answering systems but also offers new directions and ideas for future research and practical applications.

Keywords: knowledge graph, graph neural network, retrieval-augmented generation, NLP

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11714 An Approach to Analyze Testing of Nano On-Chip Networks

Authors: Farnaz Fotovvatikhah, Javad Akbari

Abstract:

Test time of a test architecture is an important factor which depends on the architecture's delay and test patterns. Here a new architecture to store the test results based on network on chip is presented. In addition, simple analytical model is proposed to calculate link test time for built in self-tester (BIST) and external tester (Ext) in multiprocessor systems. The results extracted from the model are verified using FPGA implementation and experimental measurements. Systems consisting 16, 25, and 36 processors are implemented and simulated and test time is calculated. In addition, BIST and Ext are compared in terms of test time at different conditions such as at different number of test patterns and nodes. Using the model the maximum frequency of testing could be calculated and the test structure could be optimized for high speed testing.

Keywords: test, nano on-chip network, JTAG, modelling

Procedia PDF Downloads 478
11713 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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11712 Influence of Nutritional and Health Education of Families and Communities on the School-Age Children for the Attainment of Universal Basic Education Goals in the Rural Riverine Areas of Ogun State, Nigeria

Authors: Folasade R. Sulaiman

Abstract:

Pupils’ health and nutrition are basically important to their schooling. The preponderance of avoidable deaths among children in Africa (WHO, 2000) may not be unconnected with the nutritional and health education status of families and communities that have their children as school clients. This study adopted a descriptive survey design focusing on the assessment of the level of nutritional and health education of families and community members in the rural riverine areas of Ogun State. Two research questions were raised. The Nutritional and Health Education of Families and Communities Inventory (NHEFCI) was used to collect data from 250 rural child-bearing aged women, and 0.73 test-retest reliability coefficient was established to determine the strength of the instrument. Data collected were analysed using descriptive statistics of frequency counts, percentages and mean in accordance with research questions raised in the study. The findings revealed amongst others: that 65% of the respondents had low level of nutritional and health education among the families and community members; while 72% had low level of awareness of the possible influence of nutritional and health education on the learning outcomes of the children. Based on the findings, it was recommended among others that government should intensify efforts on sensitization, mass literacy campaign etc.; also improve upon the already existing School Feeding Programme in Nigerian primary schools to provide at least one balanced diet for children while in school; community health workers, social workers, Non-Governmental Organizations (NGO) should collaborate with international Organizations like UNICEF, UNESCO, WHO etc. to organize sensitization programmes for members of the rural riverine communities on the importance of meeting the health and nutritional needs of their children in order to attain their educational potentials.

Keywords: nutritional and health education, learning capacities, school-age children, universal basic education, rural riverine areas

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11711 Social Integration of Visually Impaired Persons in Georgia

Authors: Vakhtang Nozadze, Luiza Arutinova, Khatuna Martskvishvili

Abstract:

The social empowerment of most needed individuals is a challenging issue, especially for developing countries. The current study explores the effects of visual impairment on individuals’ satisfaction with different aspects of life (i.e. education, job, income, family) and coping strategies. Furthermore, the difference between groups according to health status is revealed. Other demographic variables (education, employment, and marital status) is also considered. The cross-sectional design and self-reported questionnaires were adopted. Seventy-two visually impaired males and females (age range 13-66) and seventy healthy individuals participated in the study. The results reveal the importance of health status on the accessibility of social amenities, individuals’ satisfaction with life, and a diversity of coping strategies, irrespective of the age. The research has an important implication for social integration research and policy.

Keywords: coping strategies, life satisfaction, social integration, visual impairment

Procedia PDF Downloads 327
11710 Music Piracy Revisited: Agent-Based Modelling and Simulation of Illegal Consumption Behavior

Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

Abstract:

National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

Procedia PDF Downloads 182
11709 Using Historical Data for Stock Prediction

Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

Procedia PDF Downloads 174
11708 A Palmprint Identification System Based Multi-Layer Perceptron

Authors: David P. Tantua, Abdulkader Helwan

Abstract:

Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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11707 Public Squares and Their Potential for Social Interactions: A Case Study of Historical Public Squares in Tehran

Authors: Asma Mehan

Abstract:

Under the thrust of technological changes, population growth and vehicular traffic, Iranian historical squares have lost their significance and they are no longer the main social nodes of the society. This research focuses on how historical public squares can inspire designers to enhance social interactions among citizens in Iranian urban context. Moreover, the recent master plan of Tehran demonstrates the lack of public spaces designed for the purpose of people’s social gatherings. For filling this gap, first the current situation of 7 selected primary historical public squares in Tehran including Sabze Meydan, Arg, Topkhaneh, Baherstan, Mokhber-al-dole, Rah Ahan and Hassan Abad have been compared. Later, the influencing elements on social interactions of the public squares such as subjective factors (human relationships and memories) and objective factors (natural and built environment) have been investigated. As a conclusion, some strategies are proposed for improving social interactions in historical public squares like; holding cultural, national, athletic and religious events, defining different and new functions in public squares’ surrounding, increasing pedestrian routs, reviving the collective memory, demonstrating the historical importance of square, eliminating visual obstacles across the square, organization the natural elements of the square, appropriate pavement for social activities. Finally, it is argued that the combination of all influencing factors which are: human interactions, natural elements and built environment criteria will lead to enhance the historical public squares’ potential for social interaction.

Keywords: historical square, Iranian public square, social interaction, Tehran

Procedia PDF Downloads 393
11706 UniFi: Universal Filter Model for Image Enhancement

Authors: Aleksei Samarin, Artyom Nazarenko, Valentin Malykh

Abstract:

Image enhancement is becoming more and more popular, especially on mobile devices. Nowadays, it is a common approach to enhance an image using a convolutional neural network (CNN). Such a network should be of significant size; otherwise, a possibility for the artifacts to occur is overgrowing. The existing large CNNs are computationally expensive, which could be crucial for mobile devices. Another important flaw of such models is they are poorly interpretable. There is another approach to image enhancement, namely, the usage of predefined filters in combination with the prediction of their applicability. We present an approach following this paradigm, which outperforms both existing CNN-based and filter-based approaches in the image enhancement task. It is easily adaptable for mobile devices since it has only 47 thousand parameters. It shows the best SSIM 0.919 on RANDOM250 (MIT Adobe FiveK) among small models and is thrice faster than previous models.

Keywords: universal filter, image enhancement, neural networks, computer vision

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11705 Bi-objective Network Optimization in Disaster Relief Logistics

Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

Abstract:

Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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11704 Green Closed-Loop Supply Chain Network Design Considering Different Production Technologies Levels and Transportation Modes

Authors: Mahsa Oroojeni Mohammad Javad

Abstract:

Globalization of economic activity and rapid growth of information technology has resulted in shorter product lifecycles, reduced transport capacity, dynamic and changing customer behaviors, and an increased focus on supply chain design in recent years. The design of the supply chain network is one of the most important supply chain management decisions. These decisions will have a long-term impact on the efficacy and efficiency of the supply chain. In this paper, a two-objective mixed-integer linear programming (MILP) model is developed for designing and optimizing a closed-loop green supply chain network that, to the greatest extent possible, includes all real-world assumptions such as multi-level supply chain, the multiplicity of production technologies, and multiple modes of transportation, with the goals of minimizing the total cost of the chain (first objective) and minimizing total emissions of emissions (second objective). The ε-constraint and CPLEX Solver have been used to solve the problem as a single-objective problem and validate the problem. Finally, the sensitivity analysis is applied to study the effect of the real-world parameters’ changes on the objective function. The optimal management suggestions and policies are presented.

Keywords: closed-loop supply chain, multi-level green supply chain, mixed-integer programming, transportation modes

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11703 Determination of the Botanical Origin of Honey by the Artificial Neural Network Processing of PARAFAC Scores of Fluorescence Data

Authors: Lea Lenhardt, Ivana Zeković, Tatjana Dramićanin, Miroslav D. Dramićanin

Abstract:

Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and artificial neural networks (ANN) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. Fluorescence spectra were described with a six-component PARAFAC model, and PARAFAC scores were further processed with two types of ANN’s (feed-forward network and self-organizing maps) to obtain algorithms for classification of honey on the basis of their botanical origin. Both ANN’s detected fake honey samples with 100% sensitivity and specificity.

Keywords: honey, fluorescence, PARAFAC, artificial neural networks

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11702 The Special Testimony as a Methodology for Social Workers to Ensure the Rights of Children and Adolescents Who Are Victims of Sexual Violence

Authors: Natany Rodrigues De Carvalho, Denise Bomtempo Birche De Carvalho

Abstract:

The purpose of this study is to analyze the Special Testimony as a methodology for social workers to ensure the rights of children and adolescents who are victims of sexual violence. The specific objectives are: a) to contextualize, through the specialized literature, the social history of childhood and adolescence; b) to investigate, in the scientific literature, the sexual violence against children and adolescents as an analytical category; c) identify, with the social workers, if there is any defense of children and adolescents in the special testimony. To answer the research objectives we use qualitative research, in three axes that complement each other: a) participant observation through the insertion in the research field (supervised internship I and II); b) survey of literature on the subject; c) semi-structured interviews with social workers of the TJDFT. We used content analysis to systematize and interpret the collected data. The results of the research were organized into three chapters with the following contents: a) literature review, contextualizing the social history of childhood and adolescence to the present; b) sexual violence against children and adolescents and their categories of analysis; c) understanding of the special testimony in the Federal District and Territories in guaranteeing the rights of children and adolescents, identifying their main points from the perspective of social workers. The results showed how the lack of interdisciplinarity in the Special Testimony can lead to the non-integral protection of children and adolescents victims of sexual violence.

Keywords: childhood and adolescence, sexual violence, special testimony, social work

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11701 The Impact on the Network Deflectometry

Authors: Djamel–Eddine Yassine Boutiba

Abstract:

In this present memory, we present the various impacts deflectometer leading to the sizing by strengthening of existing roadways. It reminds that the road network in Algeria plays a major role with regard to drainage in major strategic areas and especially in the fringe northern Algeria. Heavy traffic passing through the northern fringe (between 25% and 30% heavy vehicles) causes substantial degradations at both the surface layer and base layer. The work on site by means within the laboratory CTTP such as deflectographe Lacroix, allowed us to record a large number of deflection localized bending on RN19A (Carrefour CW73-Ain- Merane), whose analysis of the results led us to opt for a building throughout the band's project . By the recorder against HWD (Heavy Weight déflectometer) allowed us to learn about the behavior of the pavement on the banks. In addition, the Software Alize III has been essential in the verification of the increase in the thickness dimensioned.

Keywords: capacity, deflection, deflectograph lacroix, degradation, hwd

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11700 New Subculture in Social Media

Authors: Maryam Mousivand

Abstract:

Subculture is one of the important concepts in social sciences and the field of cultural studies, which falls under the huge concept of culture. In general, subculture is a kind of movement and experience of collective resistance that is manifested by a population as a reaction against the acceptance of official identities approved by custom and society. Subcultures exist in the virtual world in the new era, and they emerged in various forms, such as the emergence of a subculture under common concepts and interests in the form of sites, channels, and groups of virtual space, which will be discussed in this article.

Keywords: subculture, social media, cultural studies, culture

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11699 Flame Retardant Study of Methylol Melamine Phosphate-Treated Cotton Fibre

Authors: Nurudeen Afolami Ayeni, Kasali Bello

Abstract:

Methylolmelamine with increasing degree of methylol substitution and the phosphates derivatives were used to resinate cotton fabric (CF). The resination was carried out at different curing time and curing temperature. Generally, the results show a reduction in the flame propagation rate of the treated fabrics compared to the untreated cotton fabric (CF). While the flame retardancy of methylolmelamine-treated fibre could be attributed to the degree of crosslinking of fibre-resin network which promotes stability, the methylolmelamine phosphate-treated fabrics show better retardancy due to the intumescences action of the phosphate resin upon decomposition in the resin – fabric network.

Keywords: cotton fabric, flame retardant, methylolmelamine, crosslinking, resination

Procedia PDF Downloads 375
11698 Speech Emotion Recognition: A DNN and LSTM Comparison in Single and Multiple Feature Application

Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

Abstract:

Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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11697 Centering Critical Sociology for Social Justice and Inclusive Education

Authors: Al Karim Datoo

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Abstract— The presentation argues for an urgent case to center and integrate critical sociology in enriching potency of educational thought and practice to counteract inequalities and social injustices. COVID phenomenon has starkly exposed burgeoning of social-economic inequalities and widening marginalities which have been historically and politically constructed through deep-seated social and power imbalances and injustices in the world. What potent role could education possibly play to combat these issues? A point of departure for this paper highlights increasing reductionist and exclusionary ‘mind-set’ of education that has been developed through trends in education such as: the commodification of knowledge, standardisation, homogenization, and reification which are products of the positivist ideology of knowledge coopted to serve capitalist interests. To redress these issues of de-contextualization and de-humanization of education, it is emphasized that there is an urgent need to center the role of interpretive and critical epistemologies and pedagogies of social sciences. In this regard, notions of problem-posing versus problem-solving, generative themes, instrumental versus emancipatory reasoning will be discussed. The presentation will conclude by illustrating the pedagogic utility of these critically oriented notions to counteract the social reproduction of exclusionary and inequality in and through education.

Keywords: Critical pedagogy, social justice, inclusion , education

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11696 Emotional Impact and Moral Panic in Swedish Social Media during the COVID-19 Crisis

Authors: Sophia Yakhlef

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In spring 2020, the spread of coronavirus disease 2019 (COVID-19) reached the epidemiological criteria to be declared a global pandemic. Global action was taken in order to stop the spread of the virus, such as, for example, restrictions regarding spending time outside of your home and, in several countries, periods of mandatory quarantine. Sweden's method of handling the pandemic has stood out among other European nations, and the tactic of relying on citizens' sense of civic solidarity, rather than enforcing legal restrictions preventing people from spending time outside, has been highly criticised in international news media. This situation has entailed a moral dilemma concerning the proper conduct of behaviour in everyday situations in Sweden, which is also reflected in public news media and social media. This media study focuses on Swedish social media debates and attitudes concerning moral dilemmas of handling this sense of civic solidarity. Comments on social media forums expressing outrage and anger regarding, amongst others, the actions of public media figures (such as celebrities, journalists, and bloggers) are analyzed. Drawing on a social psychological perspective on emotions, the study identifies ambiguities of moral disagreements and moral panics as ways of expressing that a moral norm has been violated. The findings suggest that social media is used in order to handle such ambiguities and make sense of the loosely defined norms of civic solidarity.

Keywords: COVID-19 crisis, moral disagreements, moral panic, social media, social norms, social psychology, Sweden

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11695 Potentials, Challenges And Prospects Of Halal Tourism Development In Ethiopia

Authors: Mohammed Jemal Ahmed

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Some anti-Islam attributes, such as alcoholism and voyeurism, have become de facto manifestations of the tourism sector. This eventually causes a paradoxical relationship between tourism and Islam. Hence, on the one hand, Islam inherently encourages Muslims to engage in tourism, the interest of Muslims to engage in tourism is steadily increasing. On the other hand, haram activities and products that are not allowed to Muslims as per the Islamic law and doctrine have surrounded tourism. Therefore, halal tourism has emerged as the best mediator to reconcile the conflicts between secular interests and religious values. Recent studies have confirmed that halal tourism is an emerging cultural phenomenon and secular rather than religious. The central aim of halal tourism is to have delighted customers irrespective of their religious and cultural backgrounds while promoting environmental conservation and social coexistence. This study appraises halal tourism development in Ethiopia from commercial, socio-cultural and diplomatic perspectives. Employing qualitative methodologies, the study, firstly, tried to clarify the existing terminological ambiguities between halal tourism and Islamic tourism and redefine both concepts. Then, it assessed perceptions of local communities and stakeholders towards halal tourism and identified halal tourism resources of Ethiopia. Accordingly, five clusters of halal visitor attractions and five potential halal tourism routes were identified and proposed. Furthermore, the comparative advantages of Ethiopia in terms of halal tourism development and potential barriers to halal tourism development in the country were rigorously appraised. The findings of this study reveal that halal tourism could inject hard currency into the national economy and create job opportunities for the locals. It could also support the mainstream tourism industry through product diversification and curving seasonality. Moreover, socially, halal tourism reinforces interreligious cohesion, relationship and coextensive in multi-religious, multicultural and multiethnic Ethiopia. Politically, it strengthens Ethiopia's foreign diplomatic relationship with the Islamic world and its near and distant neighbor Muslim Countries.

Keywords: halal-conscious travelers, halal tourism, Islamic tourism, tourism resources

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11694 Demand Forecasting Using Artificial Neural Networks Optimized by Particle Swarm Optimization

Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

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Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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11693 Strategies for Community Openness and Social Integration in Urban Villages in Chinese County Cities - Based on a Multi-Case Study in Chongqing

Authors: Ren Guangchun

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The village in the city is surrounded by formal cities but retains distinct social and morphological characteristics of the countryside, and has the ability of self-growth. County is the basic unit of urban-rural integration development, and urban village is the key focus of integration. At present, the flow of urban and rural factors in Chongqing does not match the development needs of urban villages. Based on the multi-case study of Chongqing 's districts and counties, this paper studies the characteristics of its geospatial advantages, composite functions, open spatial structure, pluralistic social structure, and reciprocity. From the aspects of community governance, social relations and space construction, this paper analyzes the dilemma of lack of subjectivity and social atomization faced by the interaction between urban villages and cities, and explores the strategies of community opening and social integration in urban villages, so as to present diversified landscapes and value spaces.

Keywords: gated community, open community, city update, Urban village

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11692 Artificial Neural Network to Predict the Optimum Performance of Air Conditioners under Environmental Conditions in Saudi Arabia

Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

Abstract:

In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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11691 Multidisciplinarity, Interdisciplinarity and Transdisciplinarity in Peace Education and Peace Studies: A Content Analysis

Authors: Frances Bernard Kominkiewicz

Abstract:

Demonstrating the ability to build social justice and peace is integral in undergraduate and graduate education. Many disciplines are involved in peace education and peace studies, and the collaboration of those disciplines are examined in this paper. To the author’s best knowledge, no content analysis research previously existed regarding peace studies and peace education from a multidisciplinarity, interdisciplinarity, and transdisciplinarity perspective. Peacebuilding is taught through these approaches, which adds to the depth, breadth, and richness of peace education and peace studies. This paper presents a content analysis of academic peace studies programs and course descriptions. Variables studied include contributions and foci of disciplines in peace studies programs and students’ engagement in community peacebuilding. The social work discipline, for example, focuses on social and economic justice as one of the nine competencies that undergraduate and graduate students must attain before earning a Bachelor of Social Work degree or a Master of Social Work degree and becoming social work practitioners. Demonstrating the ability to build social justice and peace is integral in social work education. Peacebuilding is taught through such social work courses as conflict resolution, and social work practice with communities and organizations, and these courses are examined in this research through multidisciplinarity, interdisciplinarity, and transdisciplinarity approach. Peace and social justice are linked terms in various fields, including social work. Social justice is of paramount importance in social work programs, and social workers are trained to advocate for human rights and social, economic, and environmental justice. Social workers use knowledge of oppression, globally as well as nationally, in the practice of peace education and peace studies. Social work is at the forefront in advocating for social justice as a discipline and joins with other educators in strengthening the peacebuilding opportunities for students. The content analysis, conducted through a random sample of peace studies and peace education university and college programs in the United States, found that although courses teach the concepts of peace education and peace studies, courses often are not given these titles in the social work discipline. Therefore, this analysis also includes a discussion of the multidisciplinarity, interdisciplinarity, and transdisciplinarity approach to peace education, peace studies, and peacebuilding and the importance of these approaches in educating students about peace. The content analysis further found great variability in the number of disciplines involved in peace studies programs, the focus of those disciplines in peace education, the placement of peace studies and peace education within the university or college, and the number of courses and concentrations available in peace studies and peace education. In conclusion, the research points toward very robust and diverse approaches to peace education with opportunities for further research and discussion.

Keywords: content analysis, interdisciplinarity, multidisciplinarity, peace education programs

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11690 Tourism Oriented Planning Experience in the Historical City Center of Trabzon (Turkey) with Strategic Spatial Planning Approach: Evaluation of Approach and Process

Authors: Emrehan Ozcan, Dilek Beyazlı

Abstract:

The development of tourism depends on an accurate planning approach as well as on the right planning process. This dependency is also a key factor in ensuring sustainability of tourism. The types of tourism, social expectations, planning practice, the socio-economic and the cultural structure of the region are determinants of planning approaches for tourism development. The tourism plans prepared for the historic city centers are usually based on the revitalization of cultural and historical values. The preservation and development of the tourism potentials of the historic city centers are important for providing an economic contribution to the locality, creating livable solutions for local residents and also the sustainability of tourism. This research is about experiencing and discussing a planning approach that will provide tourism development based on historical and cultural values. Historical and cultural values in the historical city center of Trabzon -which has a settlement history of approximately 4000 years, is located on the Black Sea coast of Turkey- wear out over years and lose their tourism potential. A planning study has been experienced with strategic spatial planning approach for Trabzon, which has not done a tourism-oriented planning study until now. The stages of the planning process provided by strategic spatial planning approach are an assessment of the current situation; vision, strategies, and actions; action planning; designing and implementation of actions and monitoring-evaluation. In the discussion section, the advantages, planning process, methods and techniques of the approach are discussed for the possibilities and constraints in terms of tourism planning. In this context, it is aimed to put forth tourism planning process, stages, and implementation tools within the scope of strategic spatial planning approach by comparing approaches used in the tourism-oriented/priority planning of historical city centers. Suggestions on the position and effect of the preferred planning approach in the existing spatial planning practice are the outputs of the study.

Keywords: cultural heritage, tourism oriented planning, Trabzon, strategic spatial Planning

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11689 The Mediator Role of Social Competence in the Relation between Effortful Control and Maths Achievement

Authors: M. A. Fernández-Vilar, M. D. Galián, E. Ato

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The aim of this work was to analyze the relation between children´s effortful control and Maths achievement in a sample of 447 Spanish children aged between 6 and 8 years. Traditionally, the literature confirms that higher level of effortful control has been associated with higher academic achievement, but there are few studies that include the effect that children´s social competence exert to this relation. To measure children’s effortful control parents were given the TMCQ (Temperament in Middle Childhood Questionnaire), and Maths achievement was taken from teacher´s rates. To measure social competence, we used the nominations method in the classroom context. Results confirmed that higher effortful control predicted a better maths achievement, whereas lower effortful control scores predicted lower Maths scores. Using a statistical modeling approach, we tested a mediation model that revealed the mediating role of social competence (popularity and rejection) in the relation between effortful control and Maths achievement. Concretely, higher social competence (higher popularity and lower rejection) seems to mediate the better Maths achievement showed by better self´regulated children. Therefore, an adequate social competence mediates the positive effect that self-regulatory capacity exerts to academic achievement. The clinical implications of the present findings should be considered. Specifically, rejected children must be detected and evaluated in community settings, such as school or community programs, due the relevant role of social competence in the relation between temperament and academic achievement.

Keywords: effortful control, maths achievement, social competence, mediation

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11688 Analysis of Cooperative Hybrid ARQ with Adaptive Modulation and Coding on a Correlated Fading Channel Environment

Authors: Ibrahim Ozkan

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In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

Procedia PDF Downloads 133
11687 Polarisation in Latin America: Examining the Role of Social Media in Ideological Positioning Based on 2018 Census Data

Authors: Sarah Ledoux

Abstract:

This paper analyses the quantitative effects of political content consumption in social media platforms on self-reported ideological preference across the Latin American region. Initially praising the democratic potential of the internet and its social networking websites, digital politics scholars have transitioned their discourse to warning against the undemocratic side-effects it cultivates, such as hate speech, filter bubbles, and ideological polarisation. Holding technology solely responsible for political trends worldwide is an oversimplification of the factors influencing social change. Nonetheless, widespread use of social media in new democracies raises questions on the reproduction of recent trends that have been observed in the US and Western Europe. Through the analysis of ordered logistic regressions on data from the 2018 AmericasBarometer survey, this study examines the extent to which the relationship between the consumption of political content on social media is related to ideological polarisation in Latin America. The findings indicate that there is a close link between consumption of political information on social media, specifically on Facebook and WhatsApp, and ideological positioning on the extremes of the political left- and right-wings. This relation holds when controlling for individual-level demographic and attitudinal factors, as well as country-level effects. These results demonstrate with empirical evidence that viewing political content on social media has a significant positive effect on the likelihood that citizens position themselves on the extreme ends of the left-right ideological spectrum and implies that political polarisation is a phenomenon that accompanies politically driven social media use.

Keywords: Latin America, polarisation, political consumption, political ideology, social media, survey

Procedia PDF Downloads 142