Search results for: health social network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19880

Search results for: health social network

19370 Personalized Social Resource Recommender Systems on Interest-Based Social Networks

Authors: C. L. Huang, J. J. Sia

Abstract:

The interest-based social networks, also known as social bookmark sharing systems, are useful platforms for people to conveniently read and collect internet resources. These platforms also providing function of social networks, and users can share and explore internet resources from the social networks. Providing personalized internet resources to users is an important issue on these platforms. This study uses two types of relationship on the social networks—following and follower and proposes a collaborative recommender system, consisting of two main steps. First, this study calculates the relationship strength between the target user and the target user's followings and followers to find top-N similar neighbors. Second, from the top-N similar neighbors, the articles (internet resources) that may interest the target user are recommended to the target user. In this system, users can efficiently obtain recent, related and diverse internet resources (knowledge) from the interest-based social network. This study collected the experimental dataset from Diigo, which is a famous bookmark sharing system. The experimental results show that the proposed recommendation model is more accurate than two traditional baseline recommendation models but slightly lower than the cosine model in accuracy. However, in the metrics of the diversity and executing time, our proposed model outperforms the cosine model.

Keywords: recommender systems, social networks, tagging, bookmark sharing systems, collaborative recommender systems, knowledge management

Procedia PDF Downloads 149
19369 Recognition of Gene Names from Gene Pathway Figures Using Siamese Network

Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

Abstract:

The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

Procedia PDF Downloads 253
19368 Wireless Network and Its Application

Authors: Henok Mezemr Besfat, Haftom Gebreslassie Gebregwergs

Abstract:

wireless network is one of the most important mediums of transmission of information from one device to another devices. Wireless communication has a broad range of applications, including mobile communications through cell phones and satellites, Internet of Things (IoT) connecting several devices, wireless sensor networks for traffic management and environmental monitoring, satellite communication for weather forecasting and TV without requiring any cable or wire or other electronic conductors, by using electromagnetic waves like IR, RF, satellite, etc. This paper summarizes different wireless network technologies, applications of different wireless technologies and different types of wireless networks. Generally, wireless technology will further enhance operations and experiences across sectors with continued innovation. This paper suggests different strategies that can improve wireless networks and technologies.

Keywords: wireless senser, wireless technology, wireless network, internet of things

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19367 Health Benefit and Mechanism from Green Open Space: A Pathway to Connect Health to Design and Planning

Authors: Ming Ma, Rui Li

Abstract:

In the highly urbanized district, green open space is playing an important role in human’s health and wellbeing as a physical, aesthetic and natural environment resources. The aim of this paper is to close this gap through providing a comprehensive, qualitative meta-analysis of existing studies related to this issue. A systematic scoping of current quantitative research is conducted which mostly focused on cross-sectional survey and experimental studies. Health benefits from contact with green open space could be categorized into physical health, psychological health and social wellbeing. Mechanism for the health related to green open space could be clearly identified with the regard to natural restoration, physical activities and social capital. These results indicate a multiple pathways framework between the health benefits and mechanism. In order to support design and planning, the most evident relationship was picked up that people could psychologically benefit from green open space through outdoors physical activities. Additionally, three design and planning strategies are put forward. Various and multi-level contacts with green open space would be considered as an explanation of the pathway results and tie to bridge the health to design and planning. There is a need to carry out long-term research emphasizing on causal relationship between health and green open space through excluding cofounding factors such as self-selection.

Keywords: urban green open space, planning and design, health benefit, mechanism, pathway framework

Procedia PDF Downloads 286
19366 Design of Circular Patch Antenna in Terahertz Band for Medical Applications

Authors: Moulfi Bouchra, Ferouani Souheyla, Ziani Kerarti Djalal, Moulessehoul Wassila

Abstract:

The wireless body network (WBAN) is the most interesting network these days and especially with the appearance of contagious illnesses such as covid 19, which require surveillance in the house. In this article, we have designed a circular microstrip antenna. Gold is the material used respectively for the patch and the ground plane and Gallium (εr=12.94) is chosen as the dielectric substrate. The dimensions of the antenna are 82.10*62.84 μm2 operating at a frequency of 3.85 THz. The proposed, designed antenna has a return loss of -46.046 dB and a gain of 3.74 dBi, and it can measure various physiological parameters and sensors that help in the overall monitoring of an individual's health condition.

Keywords: circular patch antenna, Terahertz transmission, WBAN applications, real-time monitoring

Procedia PDF Downloads 289
19365 Design of Neural Predictor for Vibration Analysis of Drilling Machine

Authors: İkbal Eski

Abstract:

This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

Procedia PDF Downloads 363
19364 Promoting Psychosocial Intervention in Social Work to Manage Intersectional Stigma among Sexual Minorities during COVID-19 Pandemic in Uganda: Implications for Social Work Practice

Authors: Simon Mwima, Kasule Solomon Kibirige, Evans Jennifer Mann, Bosco Mukuba, Edson Chipalo, Agnes Nzomene, Eusebius Small, Moses Okumu

Abstract:

Introduction: Social workers must create, implement, and evaluate client-centered psychosocial interventions (CCPI) to reduce the impact of intersectional stigma on HIV service utilization among sexual minorities. We contribute to the scarcity of evidence about sexual minorities in Uganda by using social support theory to explore clients' perceptions that shape CCPI. Based on Focused Group Discussion (FGD) with 31 adolescents recruited from Kampala's HIV clinics in 2021, our findings reveal the positive influence of instrumental, informational, esteem, emotional, and social network support as intersectional stigma reduction interventions. Men who have sex with men, lesbians, and bisexual women used such strategies to navigate a heavily criminalized and stigmatizing setting during the COVID-19 pandemic in Uganda. Conclusion: This study provides evidence for the social work profession to develop and implement psychosocial interventions that reduce HIV stigma and discrimination among MSM, lesbians, and bisexual young people living with HIV in Uganda.

Keywords: pyschosocial interventions, social work, intersectional stigma, HIV/AIDS, adolescents, sexual minorities, Uganda

Procedia PDF Downloads 83
19363 Exploring Deep Neural Network Compression: An Overview

Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

Abstract:

The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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19362 Development of a Congestion Controller of Computer Network Using Artificial Intelligence Algorithm

Authors: Mary Anne Roa

Abstract:

Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

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19361 Aggregate Fluctuations and the Global Network of Input-Output Linkages

Authors: Alexander Hempfing

Abstract:

The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.

Keywords: economic integration, industrial organization, input-output economics, network economics, production networks

Procedia PDF Downloads 248
19360 The Friendship Network Stability of Preschool Children during One Pedagogical Season

Authors: Yili Wang, Jarmo Kinos, Tuire Palonen, Tarja-Riitta Hurme

Abstract:

This longitudinal study aims to examine how five- and six-year-old children’s peer relationships are formed and fostered during one preschool year in a southwestern Finnish preschool. All 16 kindergarteners participated in the study (at dyad level N=240; i.e., 16 x 15 relationships among the children). The children were divided into four daily groups, based on the table order during the daily routines, and four intervention groups, based on the teachers’ pedagogical plan. During the intervention, one iPad was given to each group in order to stimulate interaction among peers and, thus, enable the children to form new peer relationships. In the data gathering, sociometric nomination techniques were used to investigate the nature (i.e., stability and mutuality) of the peer relationships. The data was collected five times during the year to see what kind of peer relationship changes occurred at the dyad level and the group level, i.e., in establishing and losing friendship ties among the children. Social network analyses were used to analyze the data. The results indicate that the children’s preference for gender segregation was strong compared to age preference and intervention. In all, the number of reciprocal friendship ties and the mutual absence of friendship ties increased towards the end of the year, whereas the number of unilateral friendship ties decreased. This indicates that children’s nominations narrow down; thus, the group structure becomes more crystalized. Instead of extending their friendship networks, children seek stable and mutual relationships with their peers in their middle childhood years. The intervention only had a slightly negative influence on children’s peer relationships.

Keywords: intervention study, peer relationship, preschool education, social network analysis, sociometric ratings

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19359 Transmit Power Optimization for Cooperative Beamforming in Reverse-Link MIMO Ad-Hoc Networks

Authors: Younghyun Jeon, Seungjoo Maeng

Abstract:

In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.

Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power

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19358 A Multi-Objective Evolutionary Algorithm of Neural Network for Medical Diseases Problems

Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

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19357 Intermittent Demand Forecast in Telecommunication Service Provider by Using Artificial Neural Network

Authors: Widyani Fatwa Dewi, Subroto Athor

Abstract:

In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

Procedia PDF Downloads 140
19356 Detection of COVID-19 Cases From X-Ray Images Using Capsule-Based Network

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

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19355 Learning a Bayesian Network for Situation-Aware Smart Home Service: A Case Study with a Robot Vacuum Cleaner

Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

Procedia PDF Downloads 501
19354 Network Analysis and Sex Prediction based on a full Human Brain Connectome

Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

Abstract:

we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

Procedia PDF Downloads 121
19353 Efficient Positioning of Data Aggregation Point for Wireless Sensor Network

Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

Abstract:

Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

Procedia PDF Downloads 137
19352 Patient Understanding of Health Information: Implications for Organizational Health Literacy in Germany

Authors: Florian Tille, Heide Weishaar, Bernhard Gibis, Susanne Schnitzer

Abstract:

Introduction: The quality of patient-doctor communication and of written health information is central to organizational health literacy (HL). Whether patients understand their doctors’ explanations and textual material on health, however, is understudied. This study identifies the overall levels of patient understanding of health information and its associations with patients’ social characteristics in outpatient health care in Germany. Materials & Methods: This analysis draws on data collected via a 2017 national health survey with a sample of 6,105 adults. Quality of communication was measured for consultations with general practitioners (GPs) and specialists (SPs) via the Ask Me 3 program questions, and through a question on written health material. Correlations with social characteristics were explored employing bivariate and multivariate logistic regression analyses. Results: Over 90% of all respondents reported that they had understood their doctors’ explanations during the last consultation. Failed understanding was strongly correlated with patients’ very poor health (Odds Ratio [OR]: 5.19; 95% confidence interval [CI]: 2.23–12.10; ref. excellent/very good health), current health problem (OR: 6.54, CI: 1.70–25.12; ref. preventive examination) and age 65 years and above (OR: 2.97, CI: 1.10–8.00; ref. 18 to 34 years). Fewer patients answered they understood written material well (86.7% for las visit at GP, 89.7% at SP). Understanding written material poorly was highly associated with basic education (OR: 4.20, CI: 2.76–6.39; ref. higher education) and 65 years old and above (OR: 2.66, CI: 1.43–4.96). Discussion: Overall ratings of oral patient-doctor communication and written communication of health information are high. Yet, a considerable share of patients reports not-understanding their doctors and poor understanding of the written health-related material. Interventions that can contribute to improving organizational HL in outpatient care in Germany include HL training for doctors, reducing system barriers to easily-accessible health information for patients and combining oral and written health communication means. Conclusion: This work adds to the study of organizational HL in Germany. To increase patient understanding of health-relevant information and thereby possibly reduce health disparities, meeting the communication needs especially of persons in different age groups, with basic education and in very poor health is suggested.

Keywords: health survey, organizational health literacy, patient-doctor communication, social characteristics, outpatient care, Ask Me 3

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19351 Analysis of Spamming Threats and Some Possible Solutions for Online Social Networking Sites (OSNS)

Authors: Dilip Singh Sisodia, Shrish Verma

Abstract:

Spamming is the most common issue seen nowadays in the Internet especially in Online Social Networking Sites (like Facebook, Twitter, and Google+ etc.). Spam messages keep wasting Internet bandwidth and the storage space of servers. On social network sites; spammers often disguise themselves by creating fake accounts and hijacking user’s accounts for personal gains. They behave like normal user and they continue to change their spamming strategy. To prevent this, most modern spam-filtering solutions are deployed on the receiver side; they are good at filtering spam for end users. In this paper we are presenting some spamming techniques their behaviour and possible solutions. We have analyzed how Spammers enters into online social networking sites (OSNSs) and how they target it and the techniques they use for it. The five discussed techniques of spamming techniques which are clickjacking, social engineered attacks, cross site scripting, URL shortening, and drive by download. We have used elgg framework for demonstration of some of spamming threats and respective implementation of solutions.

Keywords: online social networking sites, spam, attacks, internet, clickjacking / likejacking, drive-by-download, URL shortening, networking, socially engineered attacks, elgg framework

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19350 A Linearly Scalable Family of Swapped Networks

Authors: Richard Draper

Abstract:

A supercomputer can be constructed from identical building blocks which are small parallel processors connected by a network referred to as the local network. The routers have unused ports which are used to interconnect the building blocks. These connections are referred to as the global network. The address space has a global and a local component (g, l). The conventional way to connect the building blocks is to connect (g, l) to (g’,l). If there are K blocks, this requires K global ports in each router. If a block is of size M, the result is a machine with KM routers having diameter two. To increase the size of the machine to 2K blocks, each router connects to only half of the other blocks. The result is a larger machine but also one with greater diameter. This is a crude description of how the network of the CRAY XC® is designed. In this paper, a family of interconnection networks using routers with K global and M local ports is defined. Coordinates are (c,d, p) and the global connections are (c,d,p)↔(c’,p,d) which swaps p and d. The network is denoted D3(K,M) and is called a Swapped Dragonfly. D3(K,M) has KM2 routers and has diameter three, regardless of the size of K. To produce a network of size KM2 conventionally, diameter would be an increasing function of K. The family of Swapped Dragonflies has other desirable properties: 1) D3(K,M) scales linearly in K and quadratically in M. 2) If L < K, D3(K,M) contains many copies of D3(L,M). 3) If L < M, D3(K,M) contains many copies of D3(K,L). 4) D3(K,M) can perform an all-to-all exchange in KM2+KM time which is only slightly more than the time to do a one-to-all. This paper makes several contributions. It is the first time that a swap has been used to define a linearly scalable family of networks. Structural properties of this new family of networks are thoroughly examined. A synchronizing packet header is introduced. It specifies the path to be followed and it makes it possible to define highly parallel communication algorithm on the network. Among these is an all-to-all exchange in time KM2+KM. To demonstrate the effectiveness of the swap properties of the network of the CRAY XC® and D3(K,16) are compared.

Keywords: all-to-all exchange, CRAY XC®, Dragonfly, interconnection network, packet switching, swapped network, topology

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19349 Max-Entropy Feed-Forward Clustering Neural Network

Authors: Xiaohan Bookman, Xiaoyan Zhu

Abstract:

The outputs of non-linear feed-forward neural network are positive, which could be treated as probability when they are normalized to one. If we take Entropy-Based Principle into consideration, the outputs for each sample could be represented as the distribution of this sample for different clusters. Entropy-Based Principle is the principle with which we could estimate the unknown distribution under some limited conditions. As this paper defines two processes in Feed-Forward Neural Network, our limited condition is the abstracted features of samples which are worked out in the abstraction process. And the final outputs are the probability distribution for different clusters in the clustering process. As Entropy-Based Principle is considered into the feed-forward neural network, a clustering method is born. We have conducted some experiments on six open UCI data sets, comparing with a few baselines and applied purity as the measurement. The results illustrate that our method outperforms all the other baselines that are most popular clustering methods.

Keywords: feed-forward neural network, clustering, max-entropy principle, probabilistic models

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19348 Examining the Impact of Fake News on Mental Health of Residents in Jos Metropolis

Authors: Job Bapyibi Guyson, Bangripa Kefas

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The advent of social media has no doubt provided platforms that facilitate the spread of fake news. The devastating impact of this does not only end with the prevalence of rumours and propaganda but also poses potential impact on individuals’ mental well-being. Therefore, this study on examining the impact of fake news on the mental health of residents in Jos metropolis among others interrogates the impact of exposure to fake news on residents' mental health. Anchored on the Cultivation Theory, the study adopted quantitative method and surveyed two the opinions of hundred (200) social media users in Jos metropolis using purposive sampling technique. The findings reveal that a significant majority of respondents perceive fake news as highly prevalent on social media, with associated feelings of anxiety and stress. The majority of the respondents express confidence in identifying fake news, though a notable proportion lacks such confidence. Strategies for managing the mental impact of encountering fake news include ignoring it, fact checking, discussing with others, reporting to platforms, and seeking professional support. Based on these insights, recommendations were proposed to address the challenges posed by fake news. These include promoting media literacy, integrating fact-checking tools, adjusting algorithms and fostering digital well-being features among others.

Keywords: fake news, mental health, social media, impact

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19347 Artificial Neural Networks in Environmental Psychology: Application in Architectural Projects

Authors: Diego De Almeida Pereira, Diana Borchenko

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Artificial neural networks are used for many applications as they are able to learn complex nonlinear relationships between input and output data. As the number of neurons and layers in a neural network increases, it is possible to represent more complex behaviors. The present study proposes that artificial neural networks are a valuable tool for architecture and engineering professionals concerned with understanding how buildings influence human and social well-being based on theories of environmental psychology.

Keywords: environmental psychology, architecture, neural networks, human and social well-being

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19346 Socio-Economic Status and Quality of Life of Construction Workers in Bengaluru Sub-Urban Area in Pre and Post COVID-19

Authors: Priyanka R. Sagar

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Social economic status (SES) is a variable that denotes the social standing of a person in society, and quality of life is a measure of health, happiness, and comfort of an individual. During early 2020, the world was stuck by the blow of the COVID-19 pandemic resulting in minimal or no economic activities to takes place. The present research paper is an attempt to analyze the socioeconomic status and quality of life of construction workers dwelling in the sub-urban areas of Hoskote located in the Bengaluru rural district pre and post-COVID-19. It also tries to analyze the difference in these variables pre and post-COVID-19. The study uses a retrospective design and data collected through a questionnaire survey from the respondents of Hoskote. A total of 100 samples were collected, out of which 73% were men and 27% were women. The mean age group of the participants is 41.04 ± 6.97 years. The overall analysis of the study shows that there is a significant difference in the socioeconomic status of construction workers pre and post-COVID-19. The study shows SES of the workers pre-pandemic is higher than post-pandemic. The other variable is quality of life which consists of physical health, psychological health, social relationships, and environmental domains. The study depicts that the psychological domain alone has been impacted by the pandemic; workers had better mental health pre-COVID-19. The other domains, i.e., physical health, social relationship, and environment, remain unaffected.

Keywords: socio-economic status, quality of life, construction workers, COVID-19

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19345 Analysis of Interleaving Scheme for Narrowband VoIP System under Pervasive Environment

Authors: Monica Sharma, Harjit Pal Singh, Jasbinder Singh, Manju Bala

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In Voice over Internet Protocol (VoIP) system, the speech signal is degraded when passed through the network layers. The speech signal is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss and jitter. The packet loss is the major issue of the degradation in the VoIP signal quality; even a single lost packet may generate audible distortion in the decoded speech signal. In addition to these network degradations, the quality of the speech signal is also affected by the environmental noises and coder distortions. The signal quality of the VoIP system is improved through the interleaving technique. The performance of the system is evaluated for various types of noises at different network conditions. The performance of the enhanced VoIP signal is evaluated using perceptual evaluation of speech quality (PESQ) measurement for narrow band signal.

Keywords: VoIP, interleaving, packet loss, packet size, background noise

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19344 An Application of Self-Health Risk Assessment among Populations Living in The Vicinity of a Fiber-Cement Roofing Factory

Authors: Phayong Thepaksorn

Abstract:

The objective of this study was to assess whether living in proximity to a roofing fiber cement factory in southern Thailand was associated with physical, mental, social, and spiritual health domains measured in a self-reported health risk assessment (HRA) questionnaire. A cross-sectional study was conducted among community members divided into two groups: near population (living within 0-2 km of factory) and far population (living within 2-5 km of factory)(N=198). A greater proportion of those living far from the factory (65.34%) reported physical health problems than the near group (51.04 %)(p=0.032). This study has demonstrated that the near population group had higher proportion of participants with positive ratings on mental assessment (30.34%) and social health impacts (28.42%) than far population group (10.59% and 16.67 %, respectively) (p<0.001). The near population group (29.79%) had similar proportion of participants with positive ratings in spiritual health impacts compared with far population group (27.08%). Among females, but not males, this study demonstrated that a higher proportion of the near population had a positive summative score for the self-HRA, which included all four health domain, compared to the far population (p <0.001 for females; p=0.154 for males). In conclusion, this self-HRA of physical, mental, social, and spiritual health domains reflected the risk perceptions of populations living in the vicinity of the roofing fiber cement factory. This type of tool can bring attention to population concerns and complaints in the factory’s surrounding community. Our findings may contribute to future development of self-HRA for HIA development procedure in Thailand.

Keywords: cement dust, health impact assessment, risk assessment, walk-though survey

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19343 Performance Evaluation of Vertical Handover on Silom Line BTS

Authors: Silumpa Suboonsan, Suwat Pattaramalai

Abstract:

In this paper, the performance of internet usage by using Vertical Handover (VHO) between cellular network and wireless local area network (WLAN) on Silom line Bangkok Mass Transit System (BTS) is evaluated. In the evaluation model, there is the WLAN on every BTS station and there are cellular base stations along the BTS path. The maximum data rates for cellular network are 7.2, 14.4, 42, and 100Mbps and for WLAN are 54, 150, and 300Mbps. The simulation are based on users using internet, watching VDOs and browsing web pages, on the BTS train from first station to the last station (full time usage) and on the BTS train for traveling some number of stations (random time). The results shows that VHO system has throughput a lot more than using only cellular network when the data rate of WLAN is more than one of cellular network. Lastly, the number of watching HD VDO and Full HD VDO is higher on VHO system on both regular time and rush hour of BTS travelling.

Keywords: vertical handover, WLAN, cellular, silom line BTS

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19342 Testing of Canadian Integrated Healthcare and Social Services Initiatives with an Evidence-Based Case Definition for Healthcare and Social Services Integrations

Authors: S. Cheng, C. Catallo

Abstract:

Introduction: Canada's healthcare and social services systems are failing high risk, vulnerable older adults. Care for vulnerable older Canadians (65 and older) is not optimal in Canada. It does not address the care needs of vulnerable, high risk adults using a holistic approach. Given the growing aging population, and the care needs for seniors with complex conditions is one of the highest in Canada's health care system, there is a sense of urgency to optimize care. Integration of health and social services is an emerging trend in Canada when compared to European countries. There is no common and universal understanding of healthcare and social services integration within the country. Consequently, a clear understanding and definition of integrated health and social services are absent in Canada. Objectives: A study was undertaken to develop a case definition for integrated health and social care initiatives that serve older adults, which was then tested against three Canadian integrated initiatives. Methodology: A limited literature review was undertaken to identify common characteristics of integrated health and social care initiatives that serve older adults, and comprised both scientific and grey literature, in order to develop a case definition. Three Canadian integrated initiatives that are located in the province of Ontario, were identified using an online search and a screening process. They were surveyed to determine if the literature-based integration definition applied to them. Results: The literature showed that there were 24 common healthcare and social services integration characteristics that could be categorized into ten themes: 1) patient-care approach; 2) program goals; 3) measurement; 4) service and care quality; 5) accountability and responsibility; 6) information sharing; 7) Decision-making and problem-solving; 8) culture; 9) leadership; and 10) staff and professional interaction. The three initiatives showed agreement on all the integration characteristics except for those characteristics associated with healthcare and social care professional interaction, collaborative leadership and shared culture. This disagreement may be due to several reasons, including the existing governance divide between the healthcare and social services sectors within the province of Ontario that has created a ripple effect in how professions in the two different sectors interact. In addition, the three initiatives may be at maturing levels of integration, which may explain disagreement on the characteristics associated with leadership and culture. Conclusions: The development of a case definition for healthcare and social services integration that incorporates common integration characteristics can act as a useful instrument in identifying integrated healthcare and social services, particularly given the emerging and evolutionary state of this phenomenon within Canada.

Keywords: Canada, case definition, healthcare and social services integration, integration, seniors health, services delivery

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19341 A Method for Evaluating Gender Equity of Cycling from Rawls Justice Perspective

Authors: Zahra Hamidi

Abstract:

Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

Procedia PDF Downloads 382