Search results for: social network dynamics

Authors: Raquel Camprubí

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Cultural tourism has been postulated as relevant motivation for tourist over the world during the last decades. In this context, museums are the main attraction for cultural tourists who are seeking to connect with the history and culture of the visited place. From the point of view of an urban destination, museums and other cultural resources are essential to have a strong tourist supply at the destination, in order to be capable of catching attention and interest of cultural tourists. In particular, museums’ challenge is to be prepared to offer the best experience to their visitors without to forget their mission-based mainly on protection of its collection and other social goals. Thus, museums individually want to be competitive and have good positioning to achieve their strategic goals. The life cycle of the destination and the level of maturity of its tourism product influence the need of tourism agents to cooperate and collaborate among them, in order to rejuvenate their product and become more competitive as a destination. Additionally, prior studies have considered an approach of different models of a public and private partnership, and collaborative and cooperative relations developed among the agents of a tourism destination. However, there are no studies that pay special attention to museums and the strategic alliances developed to obtain mutual benefits. Considering this background, the purpose of this study is to analyze in what extent museums of a given urban destination have established strategic links and relations among them, in order to improve their competitive position at both individual and destination level. In order to achieve the aim of this study, the city of Girona (Spain) and the museums located in this city are taken as a case study. Data collection was conducted using in-depth interviews, in order to collect all the qualitative data related to nature, strengthen and purpose of the relational ties established among the museums of the city or other relevant tourism agents of the city. To conduct data analysis, a Social Network Analysis (SNA) approach was taken using UCINET software. Position of the agents in the network and structure of the network was analyzed, and qualitative data from interviews were used to interpret SNA results. Finding reveals the existence of strong ties among some of the museums of the city, particularly to create and promote joint products. Nevertheless, there were detected outsiders who have an individual strategy, without collaboration and cooperation with other museums or agents of the city. Results also show that some relational ties have an institutional origin, while others are the result of a long process of cooperation with common projects. Conclusions put in evidence that collaboration and cooperation of museums had been positive to increase the attractiveness of the museum and the city as a cultural destination. Future research and managerial implications are also mentioned.

Keywords: cultural tourism, competitiveness, museums, Social Network analysis

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Authors: Xingyue Yang

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This study focused on Chinese social media stars and the relationship between their level of fame on the social media platform Sina Weibo and their sales revenue on the E-commerce platform Taobao/Tmall.com. This was viewed from the perspective of Adler’s superstardom theory and Rosen and MacDonald’s theories examining the economics of celebrities who build their audience using digital, rather than traditional platforms. Theory and empirical research support the assertion that stars of traditional media achieve popular success due to a combination of talent and market concentration, as well as a range of other factors. These factors are also generally considered relevant to the popularisation of social media stars. However, success across digital media platforms also involves other variables - for example, upload strategies, cross-platform promotions, which often have no direct corollary in traditional media. These factors were the focus of our study, which investigated the relationship between popularity, promotional strategy and sales revenue for 15 social media stars who specialised in culinary topics on the Chinese social media platform Sina Weibo. In 2019, these food bloggers made a total of 2076 Sina Weibo posts, and these were compiled alongside calculations made to determine each food blogger’s sales revenue on the eCommerce platforms Taobao/Tmall. Quantitative analysis was then performed on this data, which determined that certain upload strategies on Weibo - such as upload time, posting format and length of video - have an important impact on the success of sales revenue on Taobao/Tmall.com.

Keywords: attention economics, digital media, network effect, social media stars

Procedia PDF Downloads 233

Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

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In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: communication, computer network, data collection, probe

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Authors: Andra Blumberga, Armands Gravelsins, Haralds Vigants, Dagnija Blumberga

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The paper discovers biotechonomy development analysis by use of system dynamics modelling. The research is connected with investigations of biomass application for production of bioproducts with higher added value. The most popular bioresource is wood, and therefore, the main question today is about future development and eco-design of products. The paper emphasizes and evaluates energy sector which is open for use of wood logs, wood chips, wood pellets and so on. The main aim for this research study was to build a framework to analyse development perspectives for wood pellet production. To reach the goal, a system dynamics model of energy wood supplies, processing, and consumption is built. Production capacity, energy consumption, changes in energy and technology efficiency, required labour source, prices of wood, energy and labour are taken into account. Validation and verification tests with available data and information have been carried out and indicate that the model constitutes the dynamic hypothesis. It is found that the more is invested into pellets production, the higher the specific profit per production unit compared to wood logs and wood chips. As a result, wood chips production is decreasing dramatically and is replaced by wood pellets. The limiting factor for pellet industry growth is availability of wood sources. This is governed by felling limit set by the government based on sustainable forestry principles.

Keywords: bioenergy, biotechonomy, system dynamics modelling, wood pellets

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Authors: Ghada Moussa, Mamoud Owais

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Transit Route Network Design Problem (TrNDP) is the most important component in Transit planning, in which the overall cost of the public transportation system highly depends on it. The main purpose of this study is to develop a novel solution methodology for the TrNDP, which goes beyond pervious traditional sophisticated approaches. The novelty of the solution methodology, adopted in this paper, stands on the deterministic operators which are tackled to construct bus routes. The deterministic manner of the TrNDP solution relies on using linear and integer mathematical formulations that can be solved exactly with their standard solvers. The solution methodology has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this research is able to improve the given network solution in terms of number of constructed routes, direct transit service coverage, transfer directness and solution reliability. Although the set of routes resulted from the methodology would stand alone as a final efficient solution for TrNDP, it could be used as an initial solution for meta-heuristic procedures to approach global optimal. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.

Keywords: integer programming, transit route design, transportation, urban planning

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Authors: N. Nalini, Lokesh B. Bhajantri

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In Distributed Sensor Networks, the sensor nodes are prone to failure due to energy depletion and some other reasons. In this regard, fault tolerance of network is essential in distributed sensor environment. Energy efficiency, network or topology control and fault-tolerance are the most important issues in the development of next-generation Distributed Sensor Networks (DSNs). This paper proposes a node fault detection and recovery using Genetic Algorithm (GA) in DSN when some of the sensor nodes are faulty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using GA, which is used to detect the faulty nodes in the network based on the energy depletion of node and link failure between nodes. The proposed fault detection model is used to detect faults at node level and network level faults (link failure and packet error). Finally, the performance parameters for the proposed scheme are evaluated.

Keywords: distributed sensor networks, genetic algorithm, fault detection and recovery, information technology

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Authors: Ali Asmari, Alex Symington, Htaik Than, Austin Caradonna, John Senft

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This paper presents the collaborative effort between ULC Technologies and Con Edison in developing a groundbreaking robotic cable splicing machine. The focus is on the machine's design, which integrates advanced robotics and automation to enhance safety and efficiency in power network maintenance. The paper details the operational steps of the machine, including cable grounding, cutting, and removal of different insulation layers, and discusses its novel technological approach. The significant benefits over traditional methods, such as improved worker safety and reduced outage times, are highlighted based on the field data collected during the validation phase of the project. The paper also explores the future potential and scalability of this technology, emphasizing its role in transforming the landscape of power network maintenance.

Keywords: cable splicing machine, power network maintenance, electric distribution, electric transmission, medium voltage cable

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Authors: Stephan Schiffer, Andreas Kain, Philipp Wilde, Maximilian Helbing, Bernard Bäker

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Automobile manufacturers progressively focus on a downsizing strategy to meet the EU's CO2 requirements concerning type-approval consumption cycles. The reduction in naturally aspirated engine power is compensated by increased levels of turbocharging. By downsizing conventional engines, CO2 emissions are reduced. However, it also implicates major challenges regarding longitudinal dynamic characteristics. An example of this circumstance is the delayed turbocharger-induced torque reaction which leads to a partially poor response behavior of the vehicle during acceleration operations. That is why it is important to focus conventional drive train design on real customer driving again. The currently considered dynamic maneuvers like the acceleration time 0-100 km/h discussed by journals and car manufacturers describe longitudinal dynamics experienced by a driver inadequately. For that reason we present the realization and evaluation of a comprehensive proband study. Subjects are provided with different vehicle concepts (electrified vehicles, vehicles with naturally aspired engines and vehicles with different concepts of turbochargers etc.) in order to find out which dynamic criteria are decisive for a subjectively strong acceleration and response behavior of a vehicle. Subsequently, realistic acceleration criteria are derived. By weighing the criteria an evaluation metric is developed to objectify customer-oriented transient dynamics. Fully-electrified vehicles are the benchmark in terms of customer-oriented longitudinal dynamics. The electric machine provides the desired torque almost without delay. This advantage compared to combustion engines is especially noticeable at low engine speeds. In conclusion, we will show the degree to which extent customer-relevant longitudinal dynamics of conventional vehicles can be approximated to electrified vehicle concepts. Therefore, various technical measures (turbocharger concepts, 48V electrical chargers etc.) and drive train designs (e.g. varying the final drive) are presented and evaluated in order to strengthen the vehicle’s customer-relevant transient dynamics. As a rating size the newly developed evaluation metric will be used.

Keywords: 48V, customer-oriented driving dynamics, electric charger, electrified vehicles, vehicle concepts

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Authors: Rosyidah Muhamad

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New media is facilitating collective action in ways never thought possible. Although the broader political climate may have a powerful influence on the success or failure of emerging social movement organizations, the Internet is enabling groups previously incapable of political action to find their voices Whether this shift is offering greater relative benefit to previously underrepresented or incumbent political fixtures is subject to debate, but it is clear that like-minded people are now able to better locate and converse with each other via many Internet. The recent social movement in Malaysia – the BERSIH Movement had attracted demonstrators from countries all over the world. The movement with an unforeseen mixture of nationalities became world news. Interestingly, the new media seemed to play a crucial role in the organization of the protests around the world. This article maps this movement via an analysis of their websites. It examines the contribution of these websites based on the collective identity, actual mobilization and a network of organizations. This research indicates signs of an integration of different organizations that contributed to an important role of the new media.

Keywords: Bersih Movement, Malaysian politics, new media, social movement

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Authors: Ihab Elaff

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Simulating the heart’s electrical stimulation is essential in modeling and evaluating the electrophysiology behavior of the heart. For achieving that, there are two structures in concern: the ventricles’ Myocardium, and the ventricles’ Conduction Network. Ventricles’ Myocardium has been modeled as anisotropic material from Diffusion Tensor Imaging (DTI) scan, and the Conduction Network has been extracted from DTI as a case-based structure based on the biological properties of the heart tissues and the working methodology of the Magnetic Resonance Imaging (MRI) scanner. Results of the produced activation were much similar to real measurements of the reference model that was presented in the literature.

Keywords: diffusion tensor, DTI, heart, conduction network, excitation propagation

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Authors: Ioannis Binas, Marios Moschakis

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Electrical faults in transmission and distribution networks can have great impact on the electrical equipment used. Fault effects depend on the characteristics of the fault as well as the network itself. It is important to anticipate the network’s behavior during faults when planning a new equipment installation, as well as troubleshooting. Moreover, working backwards, we could be able to estimate the characteristics of the fault when checking the perceived effects. Different transformer winding connections dominantly used in the Greek power transfer and distribution networks and the effects of 1-phase to neutral, phase-to-phase, 2-phases to neutral and 3-phase faults on different locations of the network were simulated in order to present voltage sag characteristics. The study was performed on a generic network with three steps down transformers on two voltage level buses (one 150 kV/20 kV transformer and two 20 kV/0.4 kV). We found that during faults, there are significant changes both on voltage magnitudes and on phase angles. The simulations and short-circuit analysis were performed using the PSCAD simulation package. This paper presents voltage characteristics calculated for the simulated network, with different approaches on the transformer winding connections during symmetrical and asymmetrical faults on various locations.

Keywords: Phase angle shift, power quality, transformer winding connections, voltage sag propagation

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Sami Baraketi, Jean Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods.

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt

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Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

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Authors: Yassine Meraihi, Dalila Acheli, Rabah Meraihi

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Vehicular Ad hoc Network (VANET) is a special case of Mobile Ad hoc Network (MANET) used to establish communications and exchange information among nearby vehicles and between vehicles and nearby fixed infrastructure. VANET is seen as a promising technology used to provide safety, efficiency, assistance and comfort to the road users. Routing is an important issue in Vehicular Ad Hoc Network to find and maintain communication between vehicles due to the highly dynamic topology, frequently disconnected network and mobility constraints. This paper evaluates the performance of two most popular proactive routing protocols OLSR and DSDV in real city traffic scenario on the basis of three metrics namely Packet delivery ratio, throughput and average end to end delay by varying vehicles density and transmission range.

Keywords: DSDV, OLSR, quality of service, routing protocols, VANET

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Authors: Waleed Basuliman

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Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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Authors: Moses Abrahamson

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This paper examines Edgar Degas’s The Rehearsal of the Ballet Onstage (1874) through the lens of gaze, spatiality, and women’s labor within the context of 19th-century Parisian modernity. Degas’s depiction of ballet dancers, who were often subject to sexual exploitation by wealthy patrons of the Paris Opera, extends beyond a mere aesthetic rendering of performance. Instead, the painting highlights the Opera’s backstage dynamics, where class and gender intersect through power imbalances. By analyzing the gazes of the Opera’s male patrons and ballet masters, the paper explores the implicit commodification of the dancers, drawing on Mulvey’s theory of the male gaze and its manifestation in the portrayal of working-class women. Degas’s positioning of these figures, coupled with his perspective as both artist and patron, reveals his engagement with the spatial layout of the Opera and the modern social hierarchies it embodies. The painting serves as a microcosm of broader sociocultural transformations, where Degas reflects on the labor of ballet dancers as both private toil and public spectacle, connecting his artistic process to the gendered and classed politics of modern Parisian society.

Keywords: class dynamics, male gaze, spatiality, modernity

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Authors: Mario Gianni, Manuel A. Ruiz Garcia, Fiora Pirri

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In this work, we present a Bayesian non-parametric approach to model the motion control of ATVs. The motion control model is based on a Dirichlet Process-Gaussian Process (DP-GP) mixture model. The DP-GP mixture model provides a flexible representation of patterns of control manoeuvres along trajectories of different lengths and discretizations. The model also estimates the number of patterns, sufficient for modeling the dynamics of the ATV.

Keywords: Dirichlet processes, gaussian mixture models, learning motion patterns, tracked robots for urban search and rescue

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Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

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Authors: Amanda R. R. Oliveira, Caio F. F. C. Cunha, Juan C. L. Junior, Amorim H. P. Junior

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Children deaths are traumatic events that most often can be prevented. The technology of prevention and intervention in cases of infant deaths is available at low cost and with solid evidence and favorable results, however, with low access cover. Weight is one of the main factors related to death in the neonatal period, so the newborns of low birth weight are a population at high risk of death in the neonatal period, especially early neonatal period. This paper describes the development of a model based in neural network analysis to predict the mortality risk rating in the early neonatal period for newborns of low birth weight to identify the individuals of this population with increased risk of death. The neural network applied was trained with a set of newborns data obtained from Brazilian health system. The resulting network presented great success rate in identifying newborns with high chances of death, which demonstrates the potential for using this tool in an integrated manner to the health system, in order to direct specific actions for improving prognosis of newborns.

Keywords: low birth weight, neonatal death risk, neural network, newborn

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Authors: Ibrahim Obeidat

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Reaching a fully-connected network of mobile nodes in rural areas got a great attention between network researchers. This attention rose due to the complexity and high costs while setting up the needed infrastructures for these networks, in addition to the low transmission range these nodes has. Terranet technology, as an example, employs ad-hoc mesh network where each node has a transmission range not exceed one kilometer, this means that every two nodes are able to communicate with each other if they are just one kilometer far from each other, otherwise a third-party will play the role of the “relay”. In Terranet, and as an idea to reduce network setup cost, every node in the network will be considered as a router that is responsible of forwarding data between other nodes which result in a decentralized collaborative environment. Most researches on Terranet presents the idea of how to encourage mobile nodes to become more cooperative by letting their devices in “ON” state as long as possible while accepting to play the role of relay (router). This research presents the issue of finding the percentage of nodes in ad-hoc mesh network within rural areas that should play the role of relay at every time slot, relating to what is the actual area coverage of nodes in order to have the network reach the fully-connectivity. Far from our knowledge, till now there is no current researches discussed this issue. The research is done by making an implementation that depends on building adjacency matrix as an indicator to the connectivity between network members. This matrix is continually updated until each value in it refers to the number of hubs that should be followed to reach from one node to another. After repeating the algorithm on different area sizes, different coverage percentages for each size, and different relay percentages for several times, results extracted shows that for area coverage less than 5% we need to have 40% of the nodes to be relays, where 10% percentage is enough for areas with node coverage greater than 5%.

Keywords: ad-hoc mesh networks, network connectivity, mobile ad-hoc networks, Terranet, adjacency matrix, simulator, wireless sensor networks, peer to peer networks, vehicular Ad hoc networks, relay

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Authors: Ali Riza Perçin, Eser Bingül

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Internet technologies have created opportunities with which people share their ideologies, thoughts and products. This virtual world, named social media has given the chance of gathering individual users and people from the world's remote locations and establishing an interaction between them. However, to an increasingly higher degree terrorist organizations today use the internet and most notably social-network media to create the effects they desire through a series of on-line activities. These activities, designed to support their activities, include information collection (intelligence), target selection, propaganda, fundraising and recruitment to name a few. Meanwhile, these have been used as the most important tool for recruitment especially from the different region of the world, especially disenfranchised youth, in the West in order to mobilize support and recruit “foreign fighters.” The recruits have obtained the statue, which is not accessible in their society and have preferred the style of life that is offered by the terrorist organizations instead of their current life. Like other terrorist groups, for a while now the terrorist organization Islamic State (IS) in Iraq and Syria has employed a social-media strategy in order to advance their strategic objectives. At the moment, however, IS seems to be more successful in their on-line activities than other similar organizations. IS uses social media strategically as part of its armed activities and for the sustainability of their military presence in Syria and Iraq. In this context, “Generation Y”, which could exist at the critical position and undertake active role, has been examined. Additionally, the explained characteristics of “Generation Y” have been put forward and the duties of families and society have been stated as well.

Keywords: social media, "generation Y", terrorist organization, islamic state IS

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Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

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New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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Authors: Eğinç Simay Ertürk, Ferhan Gezi̇ci̇

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The decline of large cities and the rise of second-tier cities have been observed as a global trend with significant implications for economic development and urban planning. In this context, the concepts of agglomeration shadow and borrowed size have gained importance as network externalities that affect the growth and development of surrounding areas. Istanbul, Izmir, and Ankara are Turkey's most significant metropolitan cities and play a significant role in the country's economy. The surrounding cities rely on these metropolitan cities for economic growth and development. However, the concentration of resources and investment in a single location can lead to agglomeration shadows in the surrounding areas. On the other hand, network connectivity between metropolitan and second-tier cities can result in borrowed function and performance, enabling smaller cities to access resources, investment, and knowledge they would not otherwise have access. The study hypothesizes that the network connectivity between second-tier and metropolitan cities in Turkey enables second-tier cities to increase their urban performance by borrowing size through these networks. Regression analysis will be used to identify specific network connectivity parameters most strongly associated with urban performance. Network connectivity will be measured with parameters such as transportation nodes and telecommunications infrastructure, and urban performance will be measured with an index, including parameters such as employment, education, and industry entrepreneurship, with data at the province levels. The contribution of the study lies in its research on how networking can benefit second-tier cities in Turkey.

Keywords: network connectivity, borrowed size, agglomeration shadow, secondary cities

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Authors: Jessica Torres, James W. Sturges

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This correlational study explored the potential relationship between social media use and social connectedness. College students (n = 190) were surveyed using the revised Social Connectedness Scale (SCS-R) and were asked about the number of hours they used social media platforms such as Instagram, TikTok, Twitter, Snapchat, and Facebook. We also developed and administered a 14-item Social Media Use Scale (SMUS) to measure potentially maladaptive social media use, such as use that likely interfered with other activities. The SMUS was found to have good inter-item consistency (Cronbach’s alpha = .92) and was significantly correlated with hours of use, r(182) = .622, p < .001. As expected, we found that the SCS-R scores were inversely related to total hours of social media use, r(182) = -.188 (p < .005). This suggested that lots of time allocated to online interactions is negatively associated with social connectedness in general. Interestingly, however, higher social connectedness scores were associated specifically with Snapchat use, r(28) = .210, p = .004. This may have to do with the specific nature of the Snapchat experience and perhaps its original use for one-to-one communication. The use of other social media platforms (Tiktok, Instagram, Twitter) was not related to better social connectedness scores. Although we failed to find that scores on our measure of problem use (the SMUS) were correlated with social connectedness, we are hopeful that the SMUS will be of use in identifying patterns of maladaptive social media use that may have an impact on other important outcome measures of adaptive functioning and well-being.

Keywords: adaptive functioning, college students, social connectedness, social media use

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Authors: Yutaro Kyuma, Sung-Jun Yoo, Kazuhide Ito

Abstract:

A commuter bus remains important as a means to network public transportation between railway stations and terminals within cities. In some cases, the boarding time becomes longer, and the boarding rate tends to be higher corresponding to the development of urban cities. The interior environmental quality, e.g. temperature and air quality, in a commuter bus is relatively heterogeneous and complex compared to that of an indoor environment in buildings due to several factors: solar radiative heat – which comes from large-area windows –, inadequate ventilation rate caused by high density of commuters, and metabolic heat generation from travelers themselves. In addition to this, under conditions where many passengers ride in the enclosed space, contact and airborne infectious risk have attracted considerable attention in terms of public health. From this point of view, it is essential to develop the prediction method for assessment of interior environmental quality and infection risk in commuter bus cabins. In this study, we developed a numerical commuter bus model integrated with computer simulated persons to reproduce realistic indoor environment conditions with high occupancy during commuting. Here, computer simulated persons were newly designed considering different types of geometries, e.g., standing position, seating position, and individual differences. Here we conducted coupled computational fluid dynamics (CFD) analysis with radiative heat transfer analysis under steady state condition. Distributions of heterogeneous air flow patterns, temperature, and moisture surrounding the human body under some different ventilation system were analyzed by using CFD technique, and skin surface temperature distributions were analyzed using thermoregulation model that integrated into computer simulated person. Through these analyses, we discussed the interior environmental quality in specific commuter bus cabins. Further, inhaled air quality of each passenger was also analyzed. This study may have possibility to design the ventilation system in bus for improving thermal comfort of occupants.

Keywords: computational fluid dynamics, CFD, computer simulated person, CSP, contaminant, indoor environment, public health, ventilation

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Authors: Jessica Achebe, Susan Tighe

Abstract:

The recent Canadian infrastructure report card reveals the unhealthy state of municipal infrastructure intensified challenged faced by municipalities to maintain adequate infrastructure performance thresholds and meet user’s required service levels. For a road agency, huge funding gap issue is inflated by growing concerns of the environmental repercussion of road construction, operation and maintenance activities. As the reduction of material consumption and greenhouse gas emission when maintain and rehabilitating road networks can achieve added benefits including improved life cycle performance of pavements, reduced climate change impacts and human health effect due to less air pollution, improved productivity due to optimal allocation of resources and reduced road user cost. Incorporating environmental sustainability measure into pavement management is solution widely cited and studied. However measuring the environmental performance of road network is still a far-fetched practice in road network management, more so an ostensive agency-wide environmental sustainability or sustainable maintenance specifications is missing. To address this challenge, this present research focuses on the environmental sustainability performance of network-level pavement management. The ultimate goal is to develop a framework to incorporate environmental sustainability in pavement management systems for network-level maintenance programming. In order to achieve this goal, this study reviewed previous studies that employed environmental performance measures, as well as the suitability of environmental performance indicators for the evaluation of the sustainability of network-level pavement maintenance strategies. Through an industry practice survey, this paper provides a brief forward regarding the pavement manager motivations and barriers to making more sustainable decisions, and data needed to support the network-level environmental sustainability. The trends in network-level sustainable pavement management are also presented, existing gaps are highlighted, and ideas are proposed for sustainable network-level pavement management.

Keywords: pavement management, sustainability, network-level evaluation, environment measures

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Authors: N. Tahouni, M. Gholami, M. H. Panjeshahi

Abstract:

Gas flaring is one of the most GHG emitting sources in the oil and gas industries. It is also a major way for wasting such an energy that could be better utilized and even generates revenue. Minimize flaring is an effective approach for reducing GHG emissions and also conserving energy in flaring systems. Integrating waste and flared gases into the fuel gas networks (FGN) of refineries is an efficient tool. A fuel gas network collects fuel gases from various source streams and mixes them in an optimal manner, and supplies them to different fuel sinks such as furnaces, boilers, turbines, etc. In this article we use fuel gas network model proposed by Hasan et al. as a base model and modify some of its features and add constraints on emission pollution by gas flaring to reduce GHG emissions as possible. Results for a refinery case study showed that integration of flare gas stream with waste and natural gas streams to construct an optimal FGN can significantly reduce total annualized cost and flaring emissions.

Keywords: flaring, fuel gas network, GHG emissions, stream

Procedia PDF Downloads 347