Search results for: social networks

Authors: Juan Sebastián Hernández

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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

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Authors: K. P. Valdés García, E. I. Rodríguez Fonseca, L. G. Juárez Cantú

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Suicide is a global, multidimensional and dynamic problem of mental health, which requires a constant study for its understanding and prevention. When research of this phenomenon is done, it is necessary to consider the different characteristics it may have because of the individual and sociocultural variables, the importance of this consideration is related to the generation of effective treatments and interventions. Adolescents are a vulnerable population due to the characteristics of the development stage. The investigation was carried out with the objective of identifying and describing the conceptualization of adolescents of suicide, and in this process, we find possible differences between men and women. The study was carried out in Saltillo, Coahuila, Mexico. The sample was composed of 418 volunteer students aged between 11 and 18 years. The ethical aspects of the research were reviewed and considered in all the processes of the investigation with the participants, their parents and the schools to which they belonged, psychological attention was offered to the participants and preventive workshops were carried in the educational institutions. Natural semantic networks were the instrument used, since this hybrid method allows to find and analyze the social concept of a phenomenon; in this case, the word suicide was used as an evocative stimulus and participants were asked to evoke at least five words and a maximum 10 that they thought were related to suicide, and then hierarchize them according to the closeness with the construct. The subsequent analysis was carried with Excel, yielding the semantic weights, affective loads and the distances between each of the semantic fields established according to the words reported by the subjects. The results showed similarities in the conceptualization of suicide in adolescents, men and women. Seven semantic fields were generated; the words were related in the discourse analysis: 1) death, 2) possible triggering factors, 3) associated moods, 4) methods used to carry it out, 5) psychological symptomatology that could affect, 6) words associated with a rejection of suicide, and finally, 7) specific objects to carry it out. One of the necessary aspects to consider in the investigations of complex issues such as suicide is to have a diversity of instruments and techniques that adjust to the characteristics of the population and that allow to understand the phenomena from the social constructs and not only theoretical. The constant study of suicide is a pressing need, the loss of a life from emotional difficulties that can be solved through psychiatry and psychological methods requires governments and professionals to pay attention and work with the risk population.

Keywords: adolescents, psychological construct, semantic networks, suicide

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Authors: Shiyin He, Zheng Huang

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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

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Authors: Sima Najafzadehkhoei, George Vega Yon

Abstract:

This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

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The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas, and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It's is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain. Then we try to describe various application areas, challenges, and future directions in the healthcare sector where blockchain platforms merge with IoT networks.

Keywords: IoT, blockchain, cryptocurrency, healthcare, consensus, data

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Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: Faihan Alotaibi

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This study explores Saudi teachers’ perceptions of the efficacy of social stories in the development of social skills in students with autism in Riyadh, Saudi Arabia in two phases. Data were collected in sequential quantitative and qualitative phases. Participants in this study were 100 teachers in the quantitative phase and 15 teachers were interviewed. In this poster, the researcher will present the data result in the qualitative second phase in which an understanding of teachers’ experiences was deepened by conducting semi-structured interviews with a purposeful sample of fifteen teachers of diverse experience, covering six initial themes: the social story concept, sources of social stories, the effectiveness of social stories in improving social skills in students with autism, barriers to using social stories for students with autism, cultural consideration and context of social stories, and factors which contribute to the best use of social stories to developing of social skills for students with autism.

Keywords: autism, social storyteachers’ perceptions, intervention, social skills

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Authors: Michael Vallely

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This paper uses data from waves 1 to 10 (2009-2019) of the UK Household Longitudinal Study to examine the social origin pay gap in the UK labour market. We find that regardless of how we proxy social origin, whether it be using the dominance approach, total parental occupation, parental education, total parental education, or the higher parental occupation and higher parental education, the results have one thing in common; in all cases, we observe a significant social origin pay gap for those from the lower social origins with the largest pay gap observed for those from the ‘lowest’ social origin. The results may indicate that when we consider the occupational status and education of both parents, previous estimates of social origin pay gaps and the number of individuals affected may have been underestimated. We also observe social origin pay gaps within educational attainment groups, such as degree holders, and within professional and managerial occupations. Therefore, this paper makes a valuable contribution to the social origin pay gap literature as it provides empirical evidence of a social origin pay gap using a large-scale UK dataset and challenges the argument that education is the great ‘social leveller’.

Keywords: social class, social origin, pay gaps, wage inequality

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: Mohd Adib Abd Muin

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Social entrepreneurship has become a new phenomenon in a country in order to reduce social problems and eradicate poverty communities. However, the study based on Islamic social entrepreneurship from the social entrepreneurial activity is still new especially in the Islamic perspective. In addition, this research found that is lacking of model on social entrepreneurship that focus on Islamic perspective. Therefore, the objective of this paper is to identify the issues and research gap based on Islamic perspective from existing models and to develop a concept of Islamic social entrepreneurship according to Islamic perspective and Maqasid Shari’ah. The research method used in this study is literature review and comparative analysis from 11 existing models of social entrepreneurship. The research finding shows that 11 existing models on social entrepreneurship has been analyzed and it shows that the existing models on social entrepreneurship do not emphasize on Islamic perspective.

Keywords: component, social entrepreneurship, Islamic perspective, research gap

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Authors: Brahim Bellali, Fatima Bellali

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The integration of information technology systems (ITS) into a company's human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of information technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova

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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterize a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: complexity, hypergraphs, reciprocity, metabolism

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Authors: Aynur Bütün Ayhan, Utku Beyazıt

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Adolescents can be heavily influenced by social media content as they develop their identities and body images. Therefore, the intensive use of social media platforms may have important effects on their body image beliefs. In this context, the objective of the present study was to assess the relationship between adolescents' social media use and their body image concerns. The study included 265 adolescents (133 girls and 132 boys) between the ages of 15 and 17 who were attending a high school in Ankara, Türkiye. In the study, the adolescents were administered the Social Media Addiction Scale to assess their level of social media use and the Social Appearance Anxiety Scale to assess their social appearance anxiety. Prior to analysis, a normality test was applied, and it was determined that the data displayed a non-parametric distribution. As a result, a significant positive relationship (r=.322, p<.01) was found between adolescents' level of social use and social appearance anxiety. It was also determined that social media addiction and social appearance anxiety significantly differed (p<.05) according to adolescents' opinions about their own bodies, being influenced by body images they see on social media and weight perceptions. The findings suggest that social media use should be managed carefully for adolescents to develop a healthy body image.

Keywords: social media, adolescent, social appearence, anxiety

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Authors: P. Prasanna Murali Krishna, M. V. Subramanyam, K. Satya Prasad

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File sharing in networks are generally achieved using Peer-to-Peer (P2P) applications. Structured P2P approaches are widely used in adhoc networks due to its distributed and scalability features. Efficient mechanisms are required to handle the huge amount of data distributed to all peers. The intrinsic characteristics of P2P system makes for easier content distribution when compared to client-server architecture. All the nodes in a P2P network act as both client and server, thus, distributing data takes lesser time when compared to the client-server method. CHORD protocol is a resource routing based where nodes and data items are structured into a 1- dimensional ring. The structured lookup algorithm of Chord is advantageous for distributed P2P networking applications. Though, structured approach improves lookup performance in a high bandwidth wired network it could contribute to unnecessary overhead in overlay networks leading to degradation of network performance. In this paper, the performance of existing CHORD protocol on Wireless Mesh Network (WMN) when nodes are static and dynamic is investigated.

Keywords: wireless mesh network (WMN), structured P2P networks, peer to peer resource sharing, CHORD Protocol, DHT

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Authors: Rahul Malhotra

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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 558

Authors: A. Irudaya Veni Mary, M. Victor Louis Anthuvan, P. Christie, A. Indira

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In India, social enterprises are working to create social value in various fields including education; health; women and child development; environment protection and community development. Although social enterprises have brought about tremendous changes in the lives of beneficiaries, the importance of their works is not understood thoroughly. One of the ways to prove themselves is to measure the impact, which in recent times has received much attention. This paper focuses on the study of social value created by the social enterprises in the field of community development. It also aims to put forth a research tool for measuring the social value created by the social enterprises in the field of community development. A close-ended interview schedule was prepared to measure the social value creation and it was administered among 60 beneficiaries of two social enterprises who work in the field of community development. The study results show that the social enterprises have brought four types of impact in the life of their beneficiaries; economic impact, social impact, political impact and cultural impact. This study is limited to the social enterprises those who work towards community development. This empirical finding will enable the reader to understand various types of social value created by the social enterprises working in the field of community development. This study will also serve as guide for social enterprises in community development activities to measure their impact and thereby improve their operation towards the betterment of the society. This paper is derived from an empirical research carried out to describe the different types of social value created by the social enterprises in India.

Keywords: social enterprise, social entrepreneurs, social impact, social value, tool for social impact measurement

Procedia PDF Downloads 275

Authors: Brahim Bellali, Fatima Bellali

Abstract:

The integration of information technology systems (ITS) into a company's ‘human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of information technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

Procedia PDF Downloads 13

Authors: Bellali Brahim, Bellali Fatima

Abstract:

The integration of information technology systems (ITS) into a company's ‘human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of nformation technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Mbida Mohamed, Ezzati Abdellah

Abstract:

A strong challenge in the wireless sensor networks (WSN) is to save the energy and have a long life time in the network without having a high rate of loss information. However, topology control (TC) protocols are designed in a way that the network is divided and having a standard system of exchange packets between nodes. In this article, we will propose a clustering based and centralized routing table protocol of TC (CBCRT) which delegates a leader node that will encapsulate a single routing table in every cluster nodes. Hence, if a node wants to send packets to the sink, it requests the information's routing table of the current cluster from the node leader in order to root the packet.

Keywords: mobile wireless sensor networks, routing, topology of control, protocols

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Authors: Rashi Jain

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The Wireless Body Area Networks (WBANs) is an emerging interdisciplinary area where small sensors are placed on/within the human body. These sensors monitor the physiological activities and vital statistics of the body. The data from these sensors is aggregated and communicated to a remote doctor for immediate attention or to a database for records. On 6 Feb 2012, the IEEE 802.15.6 task group approved the standard for Body Area Network (BAN) technologies. The standard proposes the physical and MAC layer for the WBANs. The work provides an introduction to WBANs and overview of the physical and MAC layers of the standard. The physical layer specifications have been covered. A comparison of different protocols used at MAC layer is drawn. An introduction to the network layer and security aspects of the WBANs is made. The WBANs suffer certain limitations such as regulation of frequency bands, minimizing the effect of transmission and reception of electromagnetic signals on the human body, maintaining the energy efficiency among others. This has slowed down their implementation.

Keywords: vehicular networks, sensors, MicroController 8085, LTE

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Authors: Nane Giloyan

Abstract:

The rapid development of social networks in the 21st century increases the interests towards the role and impact of social media on the success or failure of a revolution. Even though studies are investigating the role of social media on the outcome of a revolution, still, the conclusions on this matter are ambiguous so far. Hence, this research aims to investigate the role of social media in the success or failure of a revolution and make a contribution to the literature gap. The study aims to examine the research question whether the use of social media explains the success or failure of revolutions in 2008 and 2018 in Armenia. The research question is investigated through content analysis of two cases; failed revolution in 2008 and the successful revolution in 2018 in Armenia. The secondary data analysis was based on information devoted to two revolutions using local and major international news articles, journal and critical articles, in Armenian, Russian and English, also videos, posts and live streams of the revolutionary leaders. There can be many factors explaining the success or failure of a revolution. However, the investigation of the factors and their role to explain the outcome of a revolution other than the use of social media is beyond the scope of this research study. The study holds other variables constant and concludes that in the cases of 2008 and 2018 revolutions in Armenia the mobilization of society through social media explains the differences in the outcomes (failed or successful). The comparative case study of the revolutions in 2008 and 2018 in Armenia emphasizes the important role and impact of the use of social media on the success or failure of a revolution. The results highlight that the use of the Internet, particularly social media and live streams, by the opposition was the essential difference between two revolutions. Social media platforms, live streams, and communication apps that were absent in the revolutionary situation in 2008 were fundamental to the Armenian Velvet Revolution in 2018. The changes in the situation in favor of the opposition, so the outcome of the protests, were mainly based on the Internet-based mobilization of the society. It is also important to take into consideration that the country experienced a great increase in penetration rates over the decade. The percentage of access to the Internet drastically increased between 2008 and 2018. This fact may help to have a clearer understanding of the use of the Internet and social media by the opposition and the reliance on social media by society. According to the results of the continent analysis, the use of social media to direct the protests and to mobilize the society, have a vital role and positive impact on the outcome of a revolution. Thus the study concludes that it is the use of social media to initiate, organize, and direct the protests that explain the success or failure of two Armenian revolutions.

Keywords: social media, revolution, Armenia, success, failure

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Authors: N. Meddeb, A. M. Makhlouf, M. A. Ben Ayed

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Due to the real-time requirement of message in Vehicular Ad hoc NETworks (VANET), it is necessary to authenticate vehicles to achieve security, efficiency, and conditional privacy-preserving. Privacy is of utmost relevance in VANETs. For this reason, we have proposed a new protocol called ‘Multilevel Authentication Protocol’ (MAP) that considers different vehicle categories. The proposed protocol is based on our Multilevel Authentication protocol for Vehicular networks (MAVnet). But the MAP leads to human safety, where the priority is given to the ambulance vehicles. For evaluation, we used the Java language to develop a demo application and deployed it on the Network Security Simulation (Nessi2). Compared with existing authentication protocols, MAP markedly enhance the communication overhead and decreases the delay of exchanging messages while preserving conditional privacy.

Keywords: Vehicular Ad hoc NETworks (VANET), vehicle categories, safety, databases, privacy, authentication, throughput, delay

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Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: Rachid Dehini, Brahim Berbaoui

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The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

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Authors: Rania Khadim, Mohammed Erritali, Abdelhakim Maaden

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Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to those networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. In this paper we choose to evaluate the performance of two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing) for Wireless Sensor Network. The simulations were performed using NS2 simulator to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR). This work presents also a new scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost, the location query cost and the storage cost.

Keywords: location based-services, routing protocols, scalability, wireless sensor networks

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Authors: Farideh Halakou, Emel Sen, Attila Gursoy, Ozlem Keskin

Abstract:

Protein–Protein Interactions (PPIs) mediate major biological processes in living cells. The study of PPIs as networks and analyze the network properties contribute to the identification of genes and proteins associated with diseases. In this study, we have created the sub-networks of brain and lung metastasis from primary tumor in breast cancer. To do so, we used seed genes known to cause metastasis, and produced their interactions through a network-topology based prioritization method named GUILDify. In order to have the experimental support for the sub-networks, we further curated them using STRING database. We proceeded by modeling structures for the interactions lacking complex forms in Protein Data Bank (PDB). The functional enrichment analysis shows that KEGG pathways associated with the immune system and infectious diseases, particularly the chemokine signaling pathway, are important for lung metastasis. On the other hand, pathways related to genetic information processing are more involved in brain metastasis. The structural analyses of the sub-networks vividly demonstrated their difference in terms of using specific interfaces in lung and brain metastasis. Furthermore, the topological analysis identified genes such as RPL5, MMP2, CCR5 and DPP4, which are already known to be associated with lung or brain metastasis. Additionally, we found 6 and 9 putative genes that are specific for lung and brain metastasis, respectively. Our analysis suggests that variations in genes and pathways contributing to these different breast metastasis types may arise due to change in tissue microenvironment. To show the benefits of using structural PPI networks instead of traditional node and edge presentation, we inspect two case studies showing the mutual exclusiveness of interactions and effects of mutations on protein conformation which lead to different signaling.

Keywords: breast cancer, metastasis, PPI networks, protein conformational changes

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Anita Chhatwal

Abstract:

Purpose: The purpose of this paper is to evaluate and investigate the scope of usage of Academic Social Networking Websites (ASNs) by the Science faculty members across universities of North India, viz. Panjab University, Punjabi University and University of Delhi, Delhi. Design/Methodology/Approach: The present study is based upon the primary data collected from 81 science faculty participants from three universities of North India. Questionnaire method was used as an instrument for survey. The study is descriptive and research-based to investigate the popular ASNs amongst the participants from three sample universities and the purpose for which they use them along with the problems they encounter while using ASNs. Findings: The findings of the study revealed that majority of the participants were using ASNs for their academic needs. It was observed that majority of the participants (78%) used ASNs to access scientific papers, while 73.8% of the participants used them to share their research publications. ResearchGate (60.5%) and Google Scholar (59.7%) were the top two most preferred and widely used ASNs by the participants. The critical analysis of the data shows that laptops (86.3%) emerged as major tools for accessing ASNs. Shortage of computers was found to be the chief obstacle in accessing ASNs by the participants. Results of the study demonstrate that 56.3% of participants suggested conduct of seminars and training as the most effective method to increase the awareness of ASNs. Research Limitations/Implications: The study in hand absorbed the 81 faculty (Assistant Professors) members from 15 Science teaching departments across three sample universities of North India. The findings of this study will help the Government of India to regulate and simultaneously make effort to develop and enhance ASNs usage among faculty, researchers, and students. The present study will add to the existing library and information science literature and will be advantageous for all the information professionals as well. Originality/Value: This study is original survey based on primary data investigate the usage of ASNs by the academia. This study will be useful for research scholars, academicians and students all over the world.

Keywords: academic social networks, awareness and usage, North India, scholarly communication, web 2.0

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