Search results for: social network ties
10759 Well-being at Work in the Sports Sector: Systematic Review and Perspectives
Authors: Ouazoul Abdeloauhd, Jemjami Nadia
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The concept of well-being at work is one of today's significant challenges in maintaining quality of life and managing psycho-social risks at work. Indeed, work in the sports sector has evolved, and this exponential evolution, marked by increasing demands and psychological, physical, and social challenges, which sometimes exceed the resources of sports actors, influences their sense of well-being at work. Well-being and burnout as antagonists provide information on the quality of working life in sports. The Basic aim of this literature review is to analyze the scientific corpus dealing with the subject of well-being at work in the sports sector while exploring the link between sports burnout and well-being. The results reveal the richness of the conceptual approaches and the difficulties of implementing them. Prospects for future research have, therefore, been put forward.Keywords: well-being, burnout, quality of life, psycho-social risk, work on sports sector
Procedia PDF Downloads 9110758 Study on Practice of Improving Water Quality in Urban Rivers by Diverting Clean Water
Authors: Manjie Li, Xiangju Cheng, Yongcan Chen
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With rapid development of industrialization and urbanization, water environmental deterioration is widespread in majority of urban rivers, which seriously affects city image and life satisfaction of residents. As an emergency measure to improve water quality, clean water diversion is introduced for water environmental management. Lubao River and Southwest River, two urban rivers in typical plain tidal river network, are identified as technically and economically feasible for the application of clean water diversion. One-dimensional hydrodynamic-water quality model is developed to simulate temporal and spatial variations of water level and water quality, with satisfactory accuracy. The mathematical model after calibration is applied to investigate hydrodynamic and water quality variations in rivers as well as determine the optimum operation scheme of water diversion. Assessment system is developed for evaluation of positive and negative effects of water diversion, demonstrating the effectiveness of clean water diversion and the necessity of pollution reduction.Keywords: assessment system, clean water diversion, hydrodynamic-water quality model, tidal river network, urban rivers, water environment improvement
Procedia PDF Downloads 27610757 A Unified Deep Framework for Joint 3d Pose Estimation and Action Recognition from a Single Color Camera
Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin
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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.Keywords: human action recognition, pose estimation, D-CNN, deep learning
Procedia PDF Downloads 14610756 Impact of Solar Energy Based Power Grid for Future Prospective of Pakistan
Authors: Muhammd Usman Sardar, Mazhar Hussain Baloch, Muhammad Shahbaz Ahmad, Zahir Javed Paracha
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Likewise other developing countries in the world, Pakistan is furthermore suffering from electrical energy deficiency as adverse well-being nominated. Its generation of electricity has become reliant onto a great range of conventional sources since the last ten of years. The foreseeable exhaustion of petroleum and conventional resources will be alarming in continued growth and development for future in Pakistan so renewable energy interchange have to be employed by interesting the majority of power grid network. Energy adding-up through solar photovoltaic based systems and projects can offset the shortfall to such an extent with this sustainable natural resources and most promising technologies. An assessment of solar energy potential for electricity generation is being presented for fulfilling the energy demands with higher level of reliability. This research study estimates the present and future approaching renewable energy resource for power generation to off-grid independent setup or energizing the existed conventional power grids of Pakistan to becoming self-sustained for its entire outfit.Keywords: powergrid network, solar photovoltaic setups, solar power generation, solar energy technology
Procedia PDF Downloads 43410755 Cooperative Agents to Prevent and Mitigate Distributed Denial of Service Attacks of Internet of Things Devices in Transportation Systems
Authors: Borhan Marzougui
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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.Keywords: IoT, DDoS, attacks, botnet, security, agents
Procedia PDF Downloads 14310754 The Relationship between Representational Conflicts, Generalization, and Encoding Requirements in an Instance Memory Network
Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy
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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence
Procedia PDF Downloads 12710753 Intrusion Detection and Prevention System (IDPS) in Cloud Computing Using Anomaly-Based and Signature-Based Detection Techniques
Authors: John Onyima, Ikechukwu Ezepue
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Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection
Procedia PDF Downloads 30710752 The Effect of Corporate Social Responsibility on Human Resource Performance in the Selected Medium-Size Manufacturing Organisation in South Africa
Authors: Itumeleng Judith Maome, Robert Walter Dumisani Zondo
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The concept of Corporate Social Responsibility (CSR) has gained popularity as a management philosophy in companies. They integrate social and environmental concerns into their operations and interactions with stakeholders. While CSR has mostly been associated with large organisations, it contributes to societal goals by engaging in activities or supporting volunteering or ethically oriented practices. However, small and medium enterprises (SMEs) have been recognised for their contributions to the social and economic development of any country. Consequently, this study examines the effect of CSR practices on human resource performance in the selected manufacturing SME in South Africa. This study was quantitative in design and examined the production and related experiences of the manufacturing SME organisation that had adopted a CSR strategy for human resource improvement. The study was achieved by collecting pre- and post-quarterly data, overtime, for employee turnover and labour absenteeism for analysis using the regression model. The results indicate that both employee turnover and labour absenteeism have no relationship with human resource performance post-CSR implementation. However, CSR has a relationship with human resource performance. Any increase in CSR activities results in an increase in human resource performance.Keywords: corporate social responsibility, employee turnover, human resource, labour absenteeism, manufacturing SME
Procedia PDF Downloads 7610751 Analysis and Modeling of Graphene-Based Percolative Strain Sensor
Authors: Heming Yao
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Graphene-based percolative strain gauges could find applications in many places such as touch panels, artificial skins or human motion detection because of its advantages over conventional strain gauges such as flexibility and transparency. These strain gauges rely on a novel sensing mechanism that depends on strain-induced morphology changes. Once a compression or tension strain is applied to Graphene-based percolative strain gauges, the overlap area between neighboring flakes becomes smaller or larger, which is reflected by the considerable change of resistance. Tiny strain change on graphene-based percolative strain sensor can act as an important leverage to tremendously increase resistance of strain sensor, which equipped graphene-based percolative strain gauges with higher gauge factor. Despite ongoing research in the underlying sensing mechanism and the limits of sensitivity, neither suitable understanding has been obtained of what intrinsic factors play the key role in adjust gauge factor, nor explanation on how the strain gauge sensitivity can be enhanced, which is undoubtedly considerably meaningful and provides guideline to design novel and easy-produced strain sensor with high gauge factor. We here simulated the strain process by modeling graphene flakes and its percolative networks. We constructed the 3D resistance network by simulating overlapping process of graphene flakes and interconnecting tremendous number of resistance elements which were obtained by fractionizing each piece of graphene. With strain increasing, the overlapping graphenes was dislocated on new stretched simulation graphene flake simulation film and a new simulation resistance network was formed with smaller flake number density. By solving the resistance network, we can get the resistance of simulation film under different strain. Furthermore, by simulation on possible variable parameters, such as out-of-plane resistance, in-plane resistance, flake size, we obtained the changing tendency of gauge factor with all these variable parameters. Compared with the experimental data, we verified the feasibility of our model and analysis. The increase of out-of-plane resistance of graphene flake and the initial resistance of sensor, based on flake network, both improved gauge factor of sensor, while the smaller graphene flake size gave greater gauge factor. This work can not only serve as a guideline to improve the sensitivity and applicability of graphene-based strain sensors in the future, but also provides method to find the limitation of gauge factor for strain sensor based on graphene flake. Besides, our method can be easily transferred to predict gauge factor of strain sensor based on other nano-structured transparent optical conductors, such as nanowire and carbon nanotube, or of their hybrid with graphene flakes.Keywords: graphene, gauge factor, percolative transport, strain sensor
Procedia PDF Downloads 41610750 Optimal Maintenance Clustering for Rail Track Components Subject to Possession Capacity Constraints
Authors: Cuong D. Dao, Rob J.I. Basten, Andreas Hartmann
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This paper studies the optimal maintenance planning of preventive maintenance and renewal activities for components in a single railway track when the available time for maintenance is limited. The rail-track system consists of several types of components, such as rail, ballast, and switches with different preventive maintenance and renewal intervals. To perform maintenance or renewal on the track, a train free period for maintenance, called a possession, is required. Since a major possession directly affects the regular train schedule, maintenance and renewal activities are clustered as much as possible. In a highly dense and utilized railway network, the possession time on the track is critical since the demand for train operations is very high and a long possession has a severe impact on the regular train schedule. We present an optimization model and investigate the maintenance schedules with and without the possession capacity constraint. In addition, we also integrate the social-economic cost related to the effects of the maintenance time to the variable possession cost into the optimization model. A numerical example is provided to illustrate the model.Keywords: rail-track components, maintenance, optimal clustering, possession capacity
Procedia PDF Downloads 26210749 Design an Development of an Agorithm for Prioritizing the Test Cases Using Neural Network as Classifier
Authors: Amit Verma, Simranjeet Kaur, Sandeep Kaur
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Test Case Prioritization (TCP) has gained wide spread acceptance as it often results in good quality software free from defects. Due to the increase in rate of faults in software traditional techniques for prioritization results in increased cost and time. Main challenge in TCP is difficulty in manually validate the priorities of different test cases due to large size of test suites and no more emphasis are made to make the TCP process automate. The objective of this paper is to detect the priorities of different test cases using an artificial neural network which helps to predict the correct priorities with the help of back propagation algorithm. In our proposed work one such method is implemented in which priorities are assigned to different test cases based on their frequency. After assigning the priorities ANN predicts whether correct priority is assigned to every test case or not otherwise it generates the interrupt when wrong priority is assigned. In order to classify the different priority test cases classifiers are used. Proposed algorithm is very effective as it reduces the complexity with robust efficiency and makes the process automated to prioritize the test cases.Keywords: test case prioritization, classification, artificial neural networks, TF-IDF
Procedia PDF Downloads 39710748 Social Support and Depressive Symptoms in Participants of a University of the Third Age: Evidences From a Cross-Sectional Study in Brazil
Authors: Ana Luiza Blanco, Juliana Cordeiro Carvalho, Tábatta Renata Pereira Brito, Ariene Angelini dos Santos Orlandi, Ligiana Pires Corona, Daniella Pires Nunes
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Depressive symptoms are recurrent in older adults and affect the quality of life and well-being of individuals. One of the strategies to reduce depression is social support, but studies are still needed to determine which types of social support are most effective in moderating this effect in certain populations. The objective was to identify the relationship between social support and depressive symptoms in participants of a University of the Third Age. This is a cross-sectional study. Participants were 82 individuals (≥ 50 years) who responded to the Geriatric Depression Scale - GDS and the Medical Outcomes Study - MOS. Data collection was carried out from November 2020 to May 2021. The Chi-Square and Mann Whitney tests were used, at a significance level of 5% for data analysis. Among the participants, 83.4% were female, 57.3% were age between 60 to 69 years, 83.1% studied 12 year or more and 48.1% receive from 4 to 10 minimum wages. The prevalence of depressive symptoms was 12.2%. The type of support with the highest median score was affective (100 points) and the lowest, or emotional (87.5 points). The results showed that participants without depressive symptoms had higher median scores for informational support when compared to those with depressive symptoms (p=0.029). The other types of social support were not statistically significant. The findings suggested that informational support is related to depressive symptoms in older adults. Promote informational support and educational actions in Universities of the Third Age may be an important strategy for preventing depressive symptoms and improve the quality of life of this population.Keywords: aged, depressive symptoms, social support, university of the third age
Procedia PDF Downloads 12210747 Social Participation and Associated Life Satisfaction among Older Adults in India: Moderating Role of Marital Status and Living Arrangements
Authors: Varsha Pandurang Nagargoje, K. S. James
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Background: Social participation is considered as one of the central components of successful and healthy aging. This study aimed to examine the moderating role of marital status and living arrangement in the relationship between social participation and life satisfaction and other potential factors associated with life satisfaction of Indian older adults. Method: For analyses, the nationally representative study sample of 31,464 adults aged ≥60 years old was extracted from the Longitudinal Ageing Study in India (LASI) wave 1, 2017-18. Descriptive statistics and bivariate analysis have been performed to determine the proportion of life satisfaction. The first set of multivariable linear regression analyses examined Diener’s Satisfaction with Life Scale and its association with various predictor variables, including social participation, marital status, living arrangements, socio-demographic, economic, and health-related variables. Further, the second and third sets of regression investigated the moderating role of marital status and living arrangements respectively in the association of social participation and level of life satisfaction among Indian older adults. Results: Overall, the proportion of life satisfaction among older men was relatively higher than women counterparts in most background characteristics. Regression results stressed the importance of older adults’ involvement in social participation [β = 0.39, p < 0.05], being in marital union [β = 0.68, p < 0.001] and co-residential living arrangements either only with spouse [β = 1.73, p < 0.001] or with other family members [β = 2.18, p < 0.001] for the improvement of life satisfaction. Results also showed that some factors were significant for life satisfaction: in particular, increased age, having a higher level of educational status, MPCE quintile, and caste category. Higher risk of life dissatisfaction found among Indian older adults who were exposed to vulnerabilities like consuming tobacco, poor self-rated health, having difficulty in performing ADL and IADL were of major concern. The interaction effect of social participation with marital status or with living arrangements explained that currently married older individuals, and those older adults who were either co-residing with their spouse only or with other family members irrespective of their involvement in social participation remained an important modifiable factor for life satisfaction. Conclusion: It would be crucial for policymakers and practitioners to advocate social policy programs and service delivery oriented towards meaningful social connections, especially for those Indian older adults who were staying alone or currently not in the marital union to enhance their overall life satisfaction.Keywords: Indian, older adults, social participation, life satisfaction, marital status, living arrangement
Procedia PDF Downloads 12910746 Relationship between Pain, Social Support and Socio-Economic Indicators in Individuals with Spinal Cord Injury
Authors: Zahra Khazaeipour, Ehsan Ahmadipour, Vafa Rahimi-Movaghar, Fereshteh Ahmadipour
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Research Objectives: Chronic pain is one of the common problems associated with spinal cord injuries (SCI), which causes many complications. Therefore, this study intended to evaluate the relationship between pain and demographic, injury characteristics, socio-economic and social support in individuals with spinal cord Injury in Iran. Design: Descriptive cross-sectional study. Setting: Brain and Spinal Cord Injury Research Center (BASIR), Tehran University of Medical Sciences, Tehran, Iran, between 2012 and 2013. Participants: The participants were 140 individuals with SCI, 101 (72%) men and 39 (28%) women, with mean age of 29.4 ±7.9 years. Main Outcome Measure: The Persian version of the Brief Pain Inventory (BPI) was used to measure the pain, and the Multidimensional Scale of Perceived Social Support (MSPSS) was used to measure social support. Results: About 50.7% complained about having pain, which 79.3% had bilateral pain. The most common locations of pain were lower limbs and back. The most quality of pain was described as aching (41.4%), and tingling (32.9%). Patients with a medium level of education had the least pain compared to high and low level of education. SCI individuals with good economic situation reported higher frequency of having pain. There was no significant relationship between pain and social support. There was positive correlation between pain and impairment of mood, normal work, relations with other people and lack of sleep (P < 0.001). Conclusion: These findings revealed the importance of socioeconomic factors such as economic situation and educational level in understanding chronic pain in people with SCI and provide further support for the bio-psychosocial model. Hence, multidisciplinary evaluations and treatment strategies are advocated, including biomedical, psychological, and psycho-social interventions.Keywords: pain, social support, socio-economic indicators, spinal cord injury
Procedia PDF Downloads 29610745 E-Procurement Adoption and Effective Service Delivery in the Uganda Coffee Industry
Authors: Taus Muganda
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This research explores the intricate relationship between e-procurement adoption and effective service delivery in the Uganda Coffee Industry, focusing on the processes involved, key actors, and the impact of digital transformation. The study is guided by three prominent theories, Actor-Network Theory, Resource-Based View Theory, and Institutional Theory to comprehensively explore the dynamics of e-procurement in the context of the coffee sector. The primary aim of this project is to examine the e-procurement adoption process and its role in enhancing service delivery within the Uganda Coffee Industry. The research questions guiding this inquiry are: firstly, whether e-procurement adoption and implementation contribute to achieving quality service delivery; and secondly, how e-procurement adoption can be effectively realized within the Uganda Coffee Industry. To address these questions, the study has laid out specific objectives. Firstly, it seeks to investigate the impact of e-procurement on effective service delivery, analysing how the integration of digital processes influences the overall quality of services provided in the coffee industry. Secondly, it aims to critically analyse the measures required to achieve effective delivery outcomes through the adoption and implementation of e-procurement, assessing the strategies that can maximize the benefits of digital transformation. Furthermore, the research endeavours to identify and examine the key actor’s instrumental in achieving effective service delivery within the Uganda Coffee Industry. By utilizing Actor-Network Theory, the study will elucidate the network of relationships and collaborations among actors involved in the e-procurement process. The research contributes to addressing a critical gap in the sector. Despite coffee being the leading export crop in Uganda, constituting 16% of total exports, there is a recognized need for digital transformation, specifically in the realm of e-procurement, to enhance the productivity of producers and contribute to the economic growth of the country. The study aims to provide insights into transforming the Uganda Coffee Industry by focusing on improving the e-procurement services delivered to actors in the coffee sector. The three forms of e-procurement investigated in this research—E-Sourcing, E-Payment, and E-Invoicing—serve as focal points in understanding the multifaceted dimensions of digital integration within the Uganda Coffee Industry. This research endeavours to offer practical recommendations for policymakers, industry stakeholders, and the UCDA to strategically leverage e-procurement for the benefit of the entire coffee value chain.Keywords: e-procurement, effective service delivery, actors, actor-network theory, resource-based view theory, institutional theory, e-invocing, e-payment, e-sourcing
Procedia PDF Downloads 7110744 Probing Syntax Information in Word Representations with Deep Metric Learning
Authors: Bowen Ding, Yihao Kuang
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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.Keywords: deep metric learning, syntax tree probing, natural language processing, word representations
Procedia PDF Downloads 6810743 Re-thinking Trust in Refugee Resettlement: A Contextual Perspective and Proposal for Reciprocal Integration
Authors: Mahfoudha Sid'Elemine
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The refugee resettlement process profoundly shapes the trajectories of individuals in their new host countries, exerting lasting effects on their long-term integration. Prevailing literature underscores the pivotal role of trust in facilitating successful refugee resettlement. However, this research challenges the notion of trust as universally paramount, contending that its significance is contingent upon variables such as the nature of resettlement programs and the diverse backgrounds and perspectives of refugees. Rather than advocating for a blanket approach to trust-building, this research contends that for certain resettlement programs, trust may prove counterproductive amidst resource constraints and tight service timelines. Moreover, trust may not uniformly emerge as a primary requisite for all refugees, presenting formidable challenges in its establishment. Focusing specifically on resettlement in the United States, this study illustrates how the temporal constraints of resettlement services, coupled with refugees' varied cultural experiences, can impede the cultivation of trust between aid workers and refugees. As an alternative paradigm, this research proposes an approach centered on fostering opportunities for reciprocal engagement, positioning refugees as active contributors within their newfound communities. Embracing reciprocity as the cornerstone of burgeoning relationships promises to fortify refugees' ties with the broader community, bolster their autonomy, and facilitate sustained integration over time. The research draws upon qualitative analyses of in-depth interviews conducted with a subset of resettled refugees, as well as aid workers and volunteers involved in refugee resettlement endeavors within Hampton Roads, Virginia, over the past decade. Through this nuanced examination, the study offers insights into the complexities of trust dynamics in refugee resettlement contexts and advocates for a paradigm shift towards reciprocal integration strategies.Keywords: Resettlement programs, Trust dynamics, Reciprocity, Long-term integration
Procedia PDF Downloads 3610742 Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System
Authors: Zhou Mo, Dennis Chow
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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols
Procedia PDF Downloads 52410741 A Destination Marketing Study on Capitalising on the Cultural Link between Ireland and North America Using Social Media
Authors: Colm Barcoe, Garvan Whelan
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This study examines how a destination marketing organisation can use social media channels to engage the interests of the US and Canadian markets in a way that maximises the number of visits (and revisits) to Ireland. The research reveals how the cultural link between Ireland and North America is exploited through the use of social media strategies. The findings are based on quantitative and qualitative empirical data obtained through a survey of North American holidaymakers in the pre, during and post trip phases coupled with in-depth interviews of 20 industry experts who are responsible for the implementation of relationship marketing strategies for this segment. The qualitative data was analysed using Netnography in order to provide insights into the effectiveness of various social media channels in developing cultural links between Ireland and North American tourists. The findings of this investigation will extend an under-researched body of literature pertaining to Ireland and North America. The empirical evidence of this study will be of value to both academics and industry practitioners.Keywords: Ireland, marketing, North America, relationship, strategies
Procedia PDF Downloads 18410740 Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices
Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi
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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.Keywords: Iot, activity recognition, automatic classification, unconstrained environment
Procedia PDF Downloads 22410739 Network Analysis to Reveal Microbial Community Dynamics in the Coral Reef Ocean
Authors: Keigo Ide, Toru Maruyama, Michihiro Ito, Hiroyuki Fujimura, Yoshikatu Nakano, Shoichiro Suda, Sachiyo Aburatani, Haruko Takeyama
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Understanding environmental system is one of the important tasks. In recent years, conservation of coral environments has been focused for biodiversity issues. The damage of coral reef under environmental impacts has been observed worldwide. However, the casual relationship between damage of coral and environmental impacts has not been clearly understood. On the other hand, structure/diversity of marine bacterial community may be relatively robust under the certain strength of environmental impact. To evaluate the coral environment conditions, it is necessary to investigate relationship between marine bacterial composition in coral reef and environmental factors. In this study, the Time Scale Network Analysis was developed and applied to analyze the marine environmental data for investigating the relationship among coral, bacterial community compositions and environmental factors. Seawater samples were collected fifteen times from November 2014 to May 2016 at two locations, Ishikawabaru and South of Sesoko in Sesoko Island, Okinawa. The physicochemical factors such as temperature, photosynthetic active radiation, dissolved oxygen, turbidity, pH, salinity, chlorophyll, dissolved organic matter and depth were measured at the coral reef area. Metagenome and metatranscriptome in seawater of coral reef were analyzed as the biological factors. Metagenome data was used to clarify marine bacterial community composition. In addition, functional gene composition was estimated from metatranscriptome. For speculating the relationships between physicochemical and biological factors, cross-correlation analysis was applied to time scale data. Even though cross-correlation coefficients usually include the time precedence information, it also included indirect interactions between the variables. To elucidate the direct regulations between both factors, partial correlation coefficients were combined with cross correlation. This analysis was performed against all parameters such as the bacterial composition, the functional gene composition and the physicochemical factors. As the results, time scale network analysis revealed the direct regulation of seawater temperature by photosynthetic active radiation. In addition, concentration of dissolved oxygen regulated the value of chlorophyll. Some reasonable regulatory relationships between environmental factors indicate some part of mechanisms in coral reef area.Keywords: coral environment, marine microbiology, network analysis, omics data analysis
Procedia PDF Downloads 25410738 Impact of Drainage Defect on the Railway Track Surface Deflections; A Numerical Investigation
Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman
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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA
Procedia PDF Downloads 15210737 Spectrogram Pre-Processing to Improve Isotopic Identification to Discriminate Gamma and Neutrons Sources
Authors: Mustafa Alhamdi
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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification
Procedia PDF Downloads 15010736 Using Machine Learning to Classify Different Body Parts and Determine Healthiness
Authors: Zachary Pan
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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.Keywords: body part, healthcare, machine learning, neural networks
Procedia PDF Downloads 10310735 Prevention of Green Gentrification: The Case of the Sustainable Urban Policy in Paris
Authors: Elise Machline
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In the late 1980’s, sustainable urban development emerged in Europe. Sustainable neighborhoods are one attempt to implement sustainable urban energy planning in the city. So, for twenty years, projects of sustainable neighborhoods (or ‘eco-neighborhoods’) have emerged in Europe. Debates about sustainability no longer restrict it to environmental concerns (to limit greenhouse gas emissions), but rather extend to the economic and social dimensions. A growing number of empirical studies demonstrate that sustainable urbanism yield rental/sale premia, as well as higher occupancy rates and thus higher asset values. For example, European eco neighborhood projects usually focus on the middle to upper classes, given the costs involved in renting or buying the dwellings built in such projects. As a result sustainable residential buildings are not affordable and their construction tends to have a gentrifying effect. An increasing number of countries are institutionalizing green strategies for affordable housing. In France, the sustainable neighborhoods ‘ecoquartier’ must meet environmental performance criteria, have a potential for economic development and, provide social and functional diversity. The issue of social diversity trough the provision of affordable housing has emerged as a dimension of public housing policies. Thus, the ecoquartier residential buildings must be both energy efficient and affordable. Through the Parisian example our study considers how the concept of social diversity and other elements of sustainability are illustrated in the ecoquartiers and whether the authorities have been able to avoid gentrification when implementing a sustainable urban policy.Keywords: sustainable neighborhoods, social diversity, social housing policies, green buildings
Procedia PDF Downloads 35810734 Education For Social Justice: A Comparative Study of University Teachers' Conceptions and Practice
Authors: Digby Warren, Jiri Kropac
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This comparative study seeks to develop a deeper understanding of what is meant by “education for social justice” (ESJ) - an aspiration articulated by universities, though often without much definition. The research methodology involved thematic analysis of data from in-depth interviews with academics (voluntary participants) in different disciplines and institutions in the UK, Czech Republic and other EU countries. The interviews explored lecturers’ conceptions of ESJ, their practice of it, and associated challenges and enabling factors. Main findings are that ESJ is construed as provision of equitable and conscientising education opportunities that run across the whole higher education (HE) journey, from widening access to HE to stimulating critical learning and awareness that can empower graduates to transform their lives and societies. Teaching practice featured study of topics related to social justice; collaborative and creative learning activities, and assignments offering choice and connection to students’ realities. Student responses could be mixed, occasionally resistant, but mostly positive in terms of gaining increased confidence and awareness of equality and social responsibility. Influences at the macro, meso and mico level could support or limit scope for ESJ. Overall, the study highlights the strong, values-based commitment of HE teachers to facilitating student learning engagement, wellbeing and development towards building a better world.Keywords: higher education, social justice, inclusivity, diversity
Procedia PDF Downloads 7510733 Sustainable Energy Supply in Social Housing
Authors: Rolf Katzenbach, Frithjof Clauss, Jie Zheng
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The final energy use can be divided mainly in four sectors: commercial, industrial, residential, and transportation. The trend in final energy consumption by sector plays as a most straightforward way to provide a wide indication of progress for reducing energy consumption and associated environmental impacts by different end use sectors. According to statistics the average share of end use energy for residential sector in the world was nearly 20% until 2011, in Germany a higher proportion is between 25% and 30%. However, it remains less studied than energy use in other three sectors as well its impacts on climate and environment. The reason for this involves a wide range of fields, including the diversity of residential construction like different housing building design and materials, living or energy using behavioral patterns, climatic condition and variation as well other social obstacles, market trend potential and financial support from government. This paper presents an extensive and in-depth analysis of the manner by which projects researched and operated by authors in the fields of energy efficiency primarily from the perspectives of both technical potential and initiative energy saving consciousness in the residential sectors especially in social housing buildings.Keywords: energy efficiency, renewable energy, retro-commissioning, social housing, sustainability
Procedia PDF Downloads 44210732 Supporting 'vulnerable' Students to Complete Their Studies During the Economic Crisis in Greece: The Umbrella Program of International Hellenic University
Authors: Rigas Kotsakis, Nikolaos Tsigilis, Vasilis Grammatikopoulos, Evridiki Zachopoulou
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During the last decade, Greece has faced an unprecedented financial crisis, affecting various aspects and functionalities of Higher Education. Besides the restricted funding of academic institutions, the students and their families encountered economical difficulties that undoubtedly influenced the effective completion of their studies. In this context, a fairly large number of students in Alexander campus of International Hellenic University (IHU) delay, interrupt, or even abandon their studies, especially when they come from low-income families, belong to sensitive social or special needs groups, they have different cultural origins, etc. For this reason, a European project, named “Umbrella”, was initiated aiming at providing the necessary psychological support and counseling, especially to disadvantaged students, towards the completion of their studies. To this end, a network of various academic members (academic staff and students) from IHU, namely iMentor, were implicated in different roles. Specifically, experienced academic staff trained students to serve as intermediate links for the integration and educational support of students that fall into the aforementioned sensitive social groups and face problems for the completion of their studies. The main idea of the project is held upon its person-centered character, which facilitates direct student-to-student communication without the intervention of the teaching staff. The backbone of the iMentors network are senior students that face no problem in their academic life and volunteered for this project. It should be noted that there is a provision from the Umbrella structure for substantial and ethical rewards for their engagement. In this context, a well-defined, stringent methodology was implemented for the evaluation of the extent of the problem in IHU and the detection of the profile of the “candidate” disadvantaged students. The first phase included two steps, (a) data collection and (b) data cleansing/ preprocessing. The first step involved the data collection process from the Secretary Services of all Schools in IHU, from 1980 to 2019, which resulted in 96.418 records. The data set included the School name, the semester of studies, a student enrolling criteria, the nationality, the graduation year or the current, up-to-date academic state (still studying, delayed, dropped off, etc.). The second step of the employed methodology involved the data cleansing/preprocessing because of the existence of “noisy” data, missing and erroneous values, etc. Furthermore, several assumptions and grouping actions were imposed to achieve data homogeneity and an easy-to-interpret subsequent statistical analysis. Specifically, the duration of 40 years recording was limited to the last 15 years (2004-2019). In 2004 the Greek Technological Institutions were evolved into Higher Education Universities, leading into a stable and unified frame of graduate studies. In addition, the data concerning active students were excluded from the analysis since the initial processing effort was focused on the detection of factors/variables that differentiated graduate and deleted students. The final working dataset included 21.432 records with only two categories of students, those that have a degree and those who abandoned their studies. Findings of the first phase are presented across faculties and further discussed.Keywords: higher education, students support, economic crisis, mentoring
Procedia PDF Downloads 11510731 Driving and Hindering Forces for the Care of Older People: experiences of Brazilian Family Caregivers
Authors: Adriane Amend, Leidiene Ferreira Santos, Daniella Pires Nunes
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The experience of assuming or caring for older persons dependents by relatives is a complex task that encompasses or affective involvement, the demand for technical activities and or psychological support. It would be necessary to understand the situations related to the caregiver, the person and the environment, which help the family difficulty, as a caregiver to lead this role. Objective: To identify the forces that drive and restrict the care process of family caregivers of the older adults. Method: Descriptive and exploratory research, with a qualitative approach, which has as a reference the Force Field Theory. Five family caregivers of older adult’s dependents residing in the city of Palmas, Tocantins, Brazil will participate. The data were collected from December 2021 to February 2022, through a semi-structured individual interview, and submitted to content analysis. Results: As forces that drive or process of caring for family caregivers were: the account of compassionate attitudes and patience of the caregiver (I); to the collaboration of the other person to the care and to the body structure of the same (Other); and the supports of other people not cared for and structural, such as adaptations in the room, read and bathroom, as in the presence of air conditioners (Environment). Among the restrictive forces of care we mention difficulties in delegating care to another person, or stress of care and other personal demands (I); imposition of the older person about care and e a transfer from bed to hip (Other); e lack of accessibility of the house and absence of air conditioning and hospital bed (Environment). Conclusion: The results show that there are driving forces with the caregiver's attitude and feelings, a bond as an idol and support for the caregiver and the environment. On the other hand, conflicting ties, absence of physical structure and daily and continuous care shifts, can significantly compromise well-being or the cycle of older adult, caregiver and care.Keywords: caregivers, frail elderly, perception, geriatric nursing
Procedia PDF Downloads 9410730 Investigating Melodic Similarities and Instrumental Developments of Turkish and Celtic Bagpipes Based on Social Lives and Geography
Authors: Zeynep Balci
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This article examines the historical points of connection between Celtic Bagpipes and ‘’Tulum’’, which is a type of bagpipes that is culturally played mostly in Eastern Black Sea Regions of Turkey and Georgia, and melodic similarities of the pieces composed for such instruments with respect to sociological and geographical factors. Although the cultural centers of Celtic Bagpipes and ‘’Tulum’’ are separated, they share common geographical conditions, which show similar effects on the development of the folk tunes for such instruments. Geographic living conditions and the social lives that people created under the influence of their surroundings stand out most in ethnic music, and it can be argued that separated groups of people living under similar conditions might have closeness in their social lives and, thus, their ethnic music. Hence, the aim of this research is to understand the musical deviations and unification of the two culturally separated social lives lived near similar mountains and plateaus in two different regions of the world by comparing two closely related ethnic aerophones.Keywords: bagpipes, Celts, Black Sea, Turkish people
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