Search results for: social network dynamics

Authors: Tarek Sadraoui, Ahlem Nasr Othman

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Our research deal with studying and testing the effects of social media on the cryptocurrency price during the period 2020-2023. The rise of the phenomena of cryptocurrency in the world raises questions about the importance of sentiment analysis of social media on the price of the cryptocurrency. Using panel data, we show that the positive and negative twits have a positive and statistically significant impact on the price of the cryptocurrency, and neutral twits have exerted a negative and significant effect on the cryptocurrency price. Specifically, we determine the causal relationship, short-term and long-term relationship with ARDL approach between the cryptocurrency price and social media using the Granger causality test.

Keywords: social media, Twitter, Google trend, panel, cryptocurrency

Procedia PDF Downloads 100

Authors: Imen Bouazzi

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The IEEE-802.15.4 standard utilizes the CSMA-CA mechanism to control nodes access to the shared wireless communication medium. It is becoming the popular choice for various applications of surveillance and control used in wireless sensor network (WSN). The benefit of this standard is evaluated regarding of the packet loss probability who depends on the configuration of IEEE 802.15.4 MAC parameters and the traffic load. Our exigency is to evaluate the effects of various configurable MAC parameters on the performance of beaconless IEEE 802.15.4 networks under different traffic loads, static values of IEEE 802.15.4 MAC parameters (macMinBE, macMaxCSMABackoffs, and macMaxFrame Retries) will be evaluated. To performance analysis, we use ns-2[2] network simulator.

Keywords: WSN, packet loss, CSMA/CA, IEEE-802.15.4

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Authors: Omar M. Elmabrouk

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The cutting tool, in the high-speed machining process, is consistently dealing with high localized stress at the tool tip, tip temperature exceeds 800°C and the chip slides along the rake face. These conditions are affecting the tool wear, the cutting tool performances, the quality of the produced parts and the tool life. Therefore, a thin film coating on the cutting tool should be considered to improve the tool surface properties while maintaining its bulks properties. One of the general coating processes in applying thin film for hard coating purpose is PVD magnetron sputtering. In this paper, the prediction of the effects of PVD magnetron sputtering coating process parameters, sputter power in the range of (4.81-7.19 kW), bias voltage in the range of (50.00-300.00 Volts) and substrate temperature in the range of (281.08-600.00 °C), were studied using artificial neural network (ANN). The results were compared with previously published results using RSM model. It was found that the ANN is more accurate in prediction of tool hardness, and hence, it will not only improve the tool life of the tool but also significantly enhances the efficiency of the machining processes.

Keywords: artificial neural network, hardness, prediction, titanium aluminium nitrate coating

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Authors: Minimol M. C.

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The study provides insights into the consumer’s trust on user generated brand recommendations on social networking sites and also investigates the role of ad scepticism in generating consumer trust in user generated brand recommendations. The work contributes to a better understanding of trust development in the context of social networking sites. Specifically, the study reveals that not all dimensions of trustworthiness are equal. The individual user characteristics vary according to the person. The major finding of this study is that high degrees of trust toward user generated brand recommendations can be generated on the basis of high trust toward social networking sites and ad scepticism. Consumers trust the user generated brand recommendations based on the individual’s trust in the particular social networking platform and the level of their individual ad-scepticism. The study pinpoints that as consumers’ trust in user generated brand recommendations is affected by their trust in social networking sites, it is influenced by benevolence, integrity, the propensity to trust, and individual user characteristics to a great extent, and hence, it is imperative for brands should attempt to build on these factors so that they can engage consumers to generate user generated content on social media.

Keywords: Consumer trust, user-generated brand recommendations, ad scepticism, social networking sites

Procedia PDF Downloads 91

Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Michal Biały, Konrad Pietrykowski, Rafal Sochaczewski

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The kinematics and dynamics analysis of crank-piston system of aircraft engine. The object of the study was the high power aircraft engine ASz 62-IR. This engine is produced by a Polish company WSK "PZL-KALISZ" S.A.". All analyzes were performed numerically using CAD and CAE environment. Three-dimensional model of the crank-piston system was developed based on real engine located in the Laboratory of Centre of Innovation and Advanced Technologies of Lublin University of Technology. During the development of the model, the technique of reverse engineering - 3D scanning was used. ASz 62-IR engine is characterized by a radial type of crank-piston system. In this system the cylinders are arranged radially around the circle. This crank-piston system consists of a main connecting rod and eight additional connecting rods. In addition, three-dimensional model consists of a piston pins, pistons and piston rings. As a result of the specific engine design, characteristics of the piston individual movement are slightly different from each other. But the model assumes that they are the same during the analysis. Three-dimensional model of the engine was implemented into the MSC Adams software. The environment of MSC Adams allows for multibody simulation of the dynamic phenomena. This determines the state parameters of the moving elements, among which the load or force distribution on each kinematic node can be distinguished. Materials and characteristic materials parameters were adopted on the basis of commonly used materials for engine parts. The mass values of individual elements were adopted on the basis of real engine parts. The piston gas forces were replaced by calculation of pressure variations recorded during engine tests on the engine test bench. The research the changes of forces acting in the individual kinematic pairs of crank-piston system. The model allows to determine the load on the crankshaft main bearings. This gives the possibility for the main supports forces analysis The model allows for testing and simulation of kinematics and dynamics of a radial aircraft engine. This is the first stage of the work, which aims to numerical simulation of vibration of multi-cylinder aircraft engine. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: aircraft engine, CAD, CAE, dynamics, kinematics, MSC Adams, numerical simulation

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Authors: Christine K. Fulmer

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Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: social work education, problem-based learning, pedagogy, experiential learning, constructivist theoretical approach

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Authors: Fathi Soliman

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With the ultimate goal of developing the separation of n-paraffin as phase change material (PCM) by means of molecular dynamic simulations, we attempt to predict the solubility of aromatic n-paraffin in two organic solvents: Butyl Acetate (BA) and Methyl Iso Butyl Ketone (MIBK). A simple model of aromatic paraffin: 2-hexadecylantharacene with amorphous molecular structure and periodic boundary conditions was constructed. The results showed that MIBK is the best solvent to separate ultra-pure phase change materials and this data was compatible with experimental data done to separate ultra-pure n-paraffin from waste petroleum aromatic paraffin wax, the separated n-paraffin was characterized by XRD, TGA, GC and DSC, moreover; data revealed that the n-paraffin separated by using MIBK is better as PCM than that separated using BA.

Keywords: molecular dynamics simulation, n-paraffin, organic solvents, phase change materials, solvent extraction

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Authors: Sh. Gofurov, O. Ismailova, U. Makhmanov, A. Kokhkharov

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The refractometric method has been used to determine optical properties of concentration features of aqueous solutions of ethanol, tetrahydrofuran and dimethylformamide at the room temperature. Changes in dielectric permittivity of aqueous solutions of ethanol, tetrahydrofuran and dimethylformamide in a wide range of concentrations (0÷1.0 molar fraction) have been studied using molecular dynamics method. The curves depending on the concentration of experimental data on excess refractive indices and excess dielectric permittivity were compared. It has been shown that stable heteromolecular complexes in binary solutions are formed in the concentration range of 0.3÷0.4 mole fractions. The real and complex part of dielectric permittivity was obtained from dipole-dipole autocorrelation functions of molecules. At the concentrations of C = 0.3 / 0.4 m.f. the heteromolecular structures with hydrogen bonds are formed. This is confirmed by the extremum values of excessive dielectric permittivity and excessive refractive index of aqueous solutions.

Keywords: refractometric method, aqueous solution, molecular dynamics, dielectric constant

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Authors: Susan P. Teru, Jerome Nyameh

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Many contemporary organizations are placing a greater emphasis on business enterprise systems as a means of generating higher levels of economic development and sustainability. Many business research and literature has also concur that enterprise drive economic development, giving little or no credit to social enterprise, whose profit is reinvest to the community development compare to the business enterprise that share their profit to shareholders. Economic development and corporate sustainability includes economic policies that affect the beneficiaries of the economic entity and how it support corporate sustainability as a multifaceted concept that requires organizational change and adaptation on different levels. In this paper, we provide a closer examination of this suggested link between the social enterprise orientation of an organization and the pursuit of corporate sustainability. We suggest that producing social enterprise increments may be best achieved by orienting social enterprise entrepreneurs system to promote economic development and corporate sustainability, which is the new approach to organizational excellent. To this end, we describe a new approach to the social enterprise process that includes social entrepreneur and the key drivers of economic development and corporate sustainability at each stage. We present a model of social enterprise that incorporates the main ideas of the paper and suggests a new perspective for thinking about how to foster and manage social enterprise to achieve high levels of economic development and corporate sustainability as a new ways of achieving organizational excellence. Specifically, we seek to assess (1) what constitutes a corporate sustainability-oriented organization culture, (2) whether it is possible for organizations to display a unified corporate sustainability as a result of social enterprise (3) whether organizations can become more sustainable through social enterprise change.

Keywords: social enterprise orientation, organization, the pursuit of corporate sustainability, business and management

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Authors: A. Andreasyan, C. Connors

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The Elliptic Curve Digital Signature algorithm-based X509v3 certificates are becoming more popular due to their short public and private key sizes. Moreover, these certificates can be stored in Internet of Things (IoT) devices, with limited resources, using less memory and transmitted in network security protocols, such as Internet Key Exchange (IKE), Transport Layer Security (TLS) and Secure Shell (SSH) with less bandwidth. The proposed method gives another advantage, in that it increases the performance of the above-mentioned protocols in terms of key exchange by saving one scalar multiplication operation.

Keywords: cryptography, elliptic curve digital signature algorithm, key exchange, network security protocol

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Wanjiku Karanja

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Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: Amit Bhattacharyya

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The economic scenario of any region does not show the real picture for the measurement of overall development. Therefore, economic development must be accompanied by social development to be able to make an assessment to measure the level of development. The spatial variation with respect to social development has been discussed taking into account the quality of functioning of a social system in a specific area. In this paper, an attempt has been made to study the spatial distribution of social infrastructural facilities and analyze the magnitude of regional disparities at inter- block level in Barddhman district. It starts with the detailed account of the selection process of social infrastructure indicators and describes the methodology employed in the empirical analysis. Analyzing the block level data, this paper tries to identify the disparity among the blocks in the levels of social development. The results have been subsequently explained using both statistical analysis and geo spatial technique. The paper reveals that the social development is not going on at the same rate in every part of the district. Health facilities and educational facilities are concentrated at some selected point. So overall development activities come to be concentrated in a few centres and the disparity is seen over the blocks.

Keywords: disparity, inter-block, social development, spatial variation

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Authors: Ummeh Saika, Toshio Kikuchi

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Population growth and urbanization is a global phenomenon. As the rapid progress of technology, many cities in the international community are facing serious problems of urbanization. There is no doubt that the urbanization will proceed to have significant impact on the ecology, economy and society at local, regional, and global levels. The inhabitants of Dhaka city suffer from lack of proper urban facilities. The green spaces are needed for different functional and leisure activities of the urban dwellers. Again growing densification, a number of green space are transferred into open space in the Dhaka city. As a result greenery of the city's decreases gradually. Moreover, the existing green space is frequently threatened by encroachment. The role of green space, both at community and city level, is important to improve the natural environment and social ties for future generations. Therefore, it seems that the green space needs to be more effective for public interaction. The main objective of this study is to address the effectiveness of urban green space (Urban Park) of Dhaka City. Two approaches are selected to fulfill the study. Firstly, analyze the long-term spatial changes of urban green space using GIS and secondly, investigate the relationship of urban park network with physical and social environment. The case study site covers eight urban parks of Dhaka metropolitan area of Bangladesh. Two aspects (Physical and Social) are applied for this study. For physical aspect, satellite images and aerial photos of different years are used to find out the changes of urban parks. And for social aspect, methods are used as questionnaire survey, interview, observation, photographs, sketch and previous information of parks to analyze about the social environment of parks. After calculation of all data by descriptive statistics, result is shown by maps using GIS. According to physical size, parks of Dhaka city are classified into four types: Small, Medium, Large and Extra Large parks. The observed result showed that the physical and social environment of urban parks varies with their size. In small size parks physical environment is moderate by newly tree plantation and area expansion. However, in medium size parks physical environment are poor, example- tree decrease, exposed soil increase. On the other hand, physical environment of large size and extra large size parks are in good condition, because of plenty of vegetation and well management. Again based on social environment, in small size parks people mainly come from surroundings area and mainly used as waiting place. In medium-size parks, people come to attend various occasion from different places. In large size and extra large size parks, people come from every part of the city area for tourism purpose. Urban parks are important source of green space. Its influence both physical and social environment of urban area. Nowadays green space area gradually decreases and transfer into open space. The consequence of this research reveals that changes of urban parks influence both physical and social environment and also impact on urban life.

Keywords: physical environment, social environment, urban life, urban parks

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Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo

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A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.

Keywords: behavioural biometric, face biometric, neural network, physical biometric, signature biometric

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Authors: Paula M. Lantz

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In the United States, significant socioeconomic and racial inequalities exist in many population-based indicators of health and social welfare. Although a number of effective prevention programs and interventions are available, local and state governments often do not pursue prevention in the face of budgetary constraints and more acute problems. There is growing interest in and excitement about Pay for Success” (PFS) strategies, also referred to as social impact bonds, as an approach to financing and implementing promising prevention programs and services that help the public sector either save money or achieve greater value for an investment. The PFS finance model implements evidence-based interventions using capital from investors who only receive a return on their investment from the government if agreed-upon, measurable outcomes are achieved. This paper discusses the current landscape regarding social impact bonds in the U.S., and their potential and challenges in addressing serious health and social problems. The paper presents an analysis of a number of social science issues that are fundamental to the potential for social impact bonds to successfully address social inequalities in health and social welfare. This includes: a) the economics of the intervention and a potential public payout; b) organizational and management issues in intervention implementation; c) evaluation research design and methods; d) legal/regulatory issues in public payouts to investors; e) ethical issues in the design of social impact bond deals and their evaluation; and f) political issues. Despite significant challenges in the U.S. context, there is great potential for social impact bonds as a type of social impact investing to encourage private investments in evidence-based interventions that address important public health and social problems in underserved populations and provide a return on investment.

Keywords: pay for success, public/private partnerships, social impact bonds, social impact investing

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Authors: Mansour Abdi

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The aim of this study has been the investigation of coronavirus influence/impact on social adjustment and depression of Arak University students. The samples of study are 100 available female students at Arak University. They were assessed by the Bell Social Adjustment Questionnaire and Beck Depression. They were asked to answer two situations before the corona outbreak and the present. The result of evaluating/assessing the difference between social adjustment before and after coronavirus was not significant but, the averages indicate a decrease in the adjustment of students before and after the coronavirus. Meanwhile, there was no significant difference in depression findings but, in the present, the average amount of depression indicated an increase than its amount before the corona.

Keywords: depression, social adjustment student, coronavirus, student

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Authors: Obasan Kehinde

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Social Infrastructure such as transport, telecommunications, energy, water, health, housing, and educational facilities have become part and parcel of human existence and have since been seen as prerequisite for the development of any economy. It is difficult to imagine a modern world without these facilities. Using a survey research design, data was gathered through a multi-stage sampling and a random sampling method from a total of 117 respondents, the study investigates the role of social infrastructure on the performance of entrepreneurs drawn from 10 Local Government Areas across two carefully selected states in the South-West, Nigeria. The data was analyzed using a descriptive statistical analysis and a t-test. The result shows that the impact of social infrastructure on entrepreneur performance is significant at 0.00 level of significant. Thus, this study recommends that entrepreneurs should take note of the social infrastructures available in the environment for the purpose of citing business in order to reduce the cost of production and other business costs.

Keywords: social infrastructure, entrepreneur performance, entrepreneurship, business

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Authors: A. Sewell

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The paper reports a research project which investigated the social interactions of nine to ten-year-olds in a mainstream primary school. The project implemented an adaption of a whole class, behavioural intervention known as 'The Good Behaviour Game (TGBG)'. TGBG is an evidence-based intervention traditionally used to reduce low-level disruptive behaviours in a classroom setting. TGBG was adapted to encourage pupil’s engagement in pro-social behaviour during lessons. A mixed methods research design was employed to evaluate intervention effects and pupil’s perceptions of their social interactions and relationships with others. Single-case research design was used to evaluate behaviour change, and Personal Construct Psychology (PCP) repertory grids were used to explore pupil’s perceptions. The findings demonstrated that TGBG could be successfully adapted to positively influence pupil’s engagement in pro-social behaviours. The findings from the PCP repertory grid interviews revealed the complexities of how children construct their social interactions and relationships with others, and how an understanding of these could be used to design better social skills interventions. It is concluded that TGBG is a cost-effective, simple to implement intervention for promoting positive social interactions and relationships at the whole class level. The paper presents the aims, design, findings, and conclusions of the study in further detail and relates limitations and potential future extensions of the research. The outcomes have direct application and relevance for practitioners interested in children’s social development and how to promote positive outcomes in this critical aspect of childhood.

Keywords: social skills, social development, social competency, the good behaviour game

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Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

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Authors: Stefano Ruggieri, Rubinia C. Bonfanti

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Research on leadership in sports organizations has proved extremely fruitful in recent decades, favoring the growing and diffusion of figures such as mental coaches, trainers, etc. Recent scholarly attention on organizations has been directed towards the phenomenon of leader self-sacrifice, wherein leaders who display such behavior are perceived by their followers as more effective, charismatic, and legitimate compared to those who prioritize self-interest. This growing interest reflects the importance of leaders who prioritize the collective welfare over personal gain, as they inspire greater loyalty, trust, and dedication among their followers, ultimately fostering a more cohesive and high-performing team environment. However, there is limited literature on the mechanisms through which self-sacrifice influences both group dynamics (such as cohesion and team identification) and individual factors (such as self-competence). The aim of the study is to analyze the impact of the leader self-sacrifice on cohesion, team identification and self-competence. Team identification is a crucial determinant of individual identity, delineated by the extent to which a team member aligns with a specific organizational team rather than broader social collectives. This association motivates members to synchronize their actions with the collective interests of the group, thereby fostering cohesion among its constituents, and cultivating a shared sense of purpose and unity within the team. In the domain of team sports, particularly soccer and water polo, two studies involving 447 participants (men = 238, women = 209) between 22 and 35 years old (M = 26.36, SD = 5.51) were conducted. The first study employed a correlational methodology to investigate the predictive capacity of self-sacrifice on cohesion, team identification, self-efficacy, and self-competence. The second study utilized an experimental design to explore the relationship between team identification and self-sacrifice. Together, these studies provided comprehensive insights into the multifaceted nature of leader self-sacrifice and its profound implications for group cohesion and individual well-being within organizational settings. The findings underscored the pivotal role of leader self-sacrifice in not only fostering stronger bonds among team members but also in enhancing critical facets of group dynamics, ultimately contributing to the overall effectiveness and success of the team.

Keywords: cohesion, leadership, self-sacrifice, sports organizations, team-identification

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Authors: Zineb Emrane

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This abstract addresses the issue of radicalization of young people in a context with background of radicalization, in North of Morocco, 5 terrorist of Madrid's Attacts on 11th March, were coming from this context. It were developed a study pilot that describing young people perception about the main causes that lead and motivate for radicalization. Whenever we talk about this topic, we obtain information from studies and investigations by specialists in field, but we don’t give voice to the protagonists who in many cases are victims, specifically, young people at social risk because of social factors. Extremist radicalization is an expanding phenomenon, that affect young people, in north of Morocco. They live in a context with radical background and at risk of social exclusion, their social, economic and familiar needs make them vulnerable. The extremist groups take advantage of this vulnerability to involve them in a process of radicalization, offering them an alternative environment where they can found all they are looking for. This study pilot approaches the main causes that lead and motivates young people to become radicals, analyzing their context with emphasis on influencing factors, and bearing in mind the analysis of young people about how the radical background affect them and their opinion this phenomenon. The pilot study was carried out through the following actions: - Group dynamics with young people to analyze the process of violent radicalization of young people. -A participatory workshop with members of organizations that work directly with young people at risk of radicalization. -Interviews with institutional managers -Participant observation. The implementation of actions has led to the conclusion that young people define violent radicalization as a sequential process, depending on the stage, it can be deconstructed. Young people recognize that they stop feeling belonging to their family, school and neighborhood when they see behavior contrary to what they consider good and evil. The emotional rupture and the search for references outside their circle, push them to sympathize with groups that have an extremist ideology and that offer them what they need. The radicalization is a process with different stages, the main causes and the factors which lead young people to use extremist violence are related their low level of belonging feeling to their context, and lack of critical thinking about important issues. The young people are in a vulnerable stage, searching their identity, a space in which they can be accepted, and when they don't find it they are easily manipulated and susceptible to being attracted by extremist groups.

Keywords: exclusion, radicalization, vulnerability, youth

Procedia PDF Downloads 151

Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

Abstract:

The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

Procedia PDF Downloads 186

Authors: A. Hadadi, M. Abdollahi, A. Dustmohammadi

Abstract:

The growing use of DGs in distribution networks provide many advantages and also cause new problems which should be anticipated and be solved with appropriate solutions. One of the problems is transient voltage drop and short circuit in the electrical network, in the presence of distributed generation - which can lead to instability. The appearance of the short circuit will cause loss of generator synchronism, even though if it would be able to recover synchronizing mode after removing faulty generator, it will be stable. In order to increase system reliability and generator lifetime, some strategies should be planned to apply even in some situations which a fault prevent generators from separation. In this paper, one fault current limiter is installed due to prevent DGs separation from the grid when fault occurs. Furthermore, an innovative objective function is applied to determine the impedance optimal amount of fault current limiter in order to improve transient stability of distributed generation. Fault current limiter can prevent generator rotor's sudden acceleration after fault occurrence and thereby improve the network transient stability by reducing the current flow in a fast and effective manner. In fact, by applying created impedance by fault current limiter when a short circuit happens on the path of current injection DG to the fault location, the critical fault clearing time improve remarkably. Therefore, protective relay has more time to clear fault and isolate the fault zone without any instability. Finally, different transient scenarios of connection plan sustainability of small scale synchronous generators to the distribution network are presented.

Keywords: critical clearing time, fault current limiter, synchronous generator, transient stability, transient states

Procedia PDF Downloads 183

Authors: Edwin Cartledge, Jack Clark, Mazaher Molaei-Chalchooghi

Abstract:

The mixing in the crystallization step of active pharmaceutical ingredient manufacturers was studied via advanced modeling tools to enable a successful scale-up. A virtual representation of the vessel was created, and computational fluid dynamics were used to simulate multiphase flow and, thus, the mixing environment within this vessel. The study identified a significant dead zone in the vessel underneath the impeller and found that increasing the impeller speed and power did not improve the mixing. A series of sensitivity analyses found that to improve mixing, the vessel had to be redesigned, and found that optimal mixing could be obtained by adding two extra cylindrical baffles. The same two baffles from the simulated environment were then constructed and added to the process vessel. By identifying these potential issues before starting the manufacture and modifying the vessel to ensure good mixing, this study mitigated a failed crystallization and potential batch disposal, which could have resulted in a significant loss of high-value material.

Keywords: active pharmaceutical ingredient, baffles, computational fluid dynamics, mixing, modelling

Procedia PDF Downloads 83

Authors: John Segars

Abstract:

Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

Procedia PDF Downloads 168

Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

Procedia PDF Downloads 344