Search results for: spatial information network

Authors: Yasaman Sanayei, Alireza Bahiraie

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This paper presents a systematic methodology based on the application of artificial neural networks for sequencing batch reactor (SBR). The SBR is a fill-and-draw biological wastewater technology, which is specially suited for nutrient removal. Employing reactive dye by Sphingomonas paucimobilis bacteria at sequence batch reactor is a novel approach of dye removal. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter was a= 0.44. In orderto adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation with R2> 0.99 and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics. Note that SBR are normally operated with constant predefined duration of the stages, thus, resulting in low efficient operation. Data obtained from the on-line electronic sensors installed in the SBR and from the control quality laboratory analysis have been used to develop the optimal architecture of two different ANN. The results have shown that the developed models can be used as efficient and cost-effective predictive tools for the system analysed.

Keywords: artificial neural network, COD removal, SBR, Sphingomonas paucimobilis

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Authors: Aravind G., Arshinder Kaur, Pushpavanam S.

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There is a strong emphasis on shifting to electric vehicles (EVs) throughout the globe for reducing the impact on global warming following the Paris climate accord. Lithium-ion batteries (LIBs) are predominantly used in EVs, and these can be a significant threat to the environment if not disposed of safely. Lithium is also a valuable resource not widely available. There are several research groups working on developing an efficient recycling process for LIBs. Two routes - pyrometallurgical and hydrometallurgical processes have been proposed for recycling LIBs. In this paper, we focus on life cycle assessment (LCA) as a tool to quantify the environmental impact of these recycling processes. We have defined the boundary of the LCA to include only the recycling phase of the end-of-life (EoL) of the battery life cycle. The analysis is done assuming ideal conditions for the hydrometallurgical and a combined hydrometallurgical and pyrometallurgical process in the inventory analysis. CML-IA method is used for quantifying the impact assessment across eleven indicators. Our results show that cathode, anode, and foil contribute significantly to the impact. The environmental impacts of both hydrometallurgical and combined recycling processes are similar across all the indicators. Further, the results of LCA are used in developing a multi-objective optimization model for the design of lithium-ion battery recycling network. Greenhouse gas emissions and cost are the two parameters minimized for the optimization study.

Keywords: life cycle assessment, lithium-ion battery recycling, multi-objective optimization, network design, reverse supply chain

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Authors: Ruijia Hu, Susanna T.Y. Tong

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Light detection and ranging (LiDAR) and four-channel red, green, blue, and near-infrared (RGBI) remote sensed imageries allow an accurate quantification and contiguous measurement of vegetation characteristics and forest structures. This information facilitates the generation of habitat structure variables for forest species distribution modelling. However, applications of remote sensing data, especially the combination of structural and spectral information, to support evidence-based decisions in forest managements and conservation practices at local scale are not widely adopted. In this study, we examined the habitat requirements of pileated woodpecker (Dryocopus pileatus) (PW) in Hamilton County, Ohio, using ecologically relevant forest structural and vegetation characteristics derived from LiDAR and RGBI data. We hypothesized that the habitat of PW is shaped by vegetation characteristics that are directly associated with the availability of food, hiding and nesting resources, the spatial arrangement of habitat patches within home range, as well as proximity to water sources. We used 186 PW presence or absence locations to model their presence and absence in generalized additive model (GAM) at two scales, representing foraging and home range size, respectively. The results confirm PW’s preference for tall and large mature stands with structural complexity, typical of late-successional or old-growth forests. Besides, the crown size of dead trees shows a positive relationship with PW occurrence, therefore indicating the importance of declining living trees or early-stage dead trees within PW home range. These locations are preferred by PW for nest cavity excavation as it attempts to balance the ease of excavation and tree security. In addition, we found that PW can adjust its travel distance to the nearest water resource, suggesting that habitat fragmentation can have certain impacts on PW. Based on our findings, we recommend that forest managers should use different priorities to manage nesting, roosting, and feeding habitats. Particularly, when devising forest management and hazard tree removal plans, one needs to consider retaining enough cavity trees within high-quality PW habitat. By mapping PW habitat suitability for the study area, we highlight the importance of riparian corridor in facilitating PW to adjust to the fragmented urban landscape. Indeed, habitat improvement for PW in the study area could be achieved by conserving riparian corridors and promoting riparian forest succession along major rivers in Hamilton County.

Keywords: deadwood detection, generalized additive model, individual tree crown delineation, LiDAR, pileated woodpecker, RGBI aerial imagery, species distribution models

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Authors: Xabier Barandiaran, Igone Guerra

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The economic and financial crisis that hit European countries in 2008 revealed the inability of governments to respond unilaterally to the so-called “wicked” problems that affect our societies. Closely linked to this, the increasing disaffection of citizens towards politics has resulted in growing distrust of the citizenry not only in the institutions in general but also in the political system, in particular. Precisely, these two factors provoked the action of the local government of Gipuzkoa (Basque Country) to move from old ways of “doing politics” to a new way of “thinking politics” based on a collaborative approach, in which innovative modes of public decision making are prominent. In this context, in 2015, the initiative Etorkizuna Eraikiz (Building the Future), a contemporary form of networked governance, was launched by the Provincial Government. The paper focuses on the Etorkizuna Eraikiz initiative, a sound commitment from a local government to build jointly with the citizens the future of the territory. This paper will present preliminary results obtained from three different experiences of co-creation developed within Etorkizuna Eraikiz in which the formulation of networked governance is a mandatory pre-requisite. These experiences show how the network building approach among the different agents of the territory as well as the co-creation of public policies is the cornerstone of this challenging mission. Through the analysis of the information and documentation gathered during the four years of Etorkizuna-Eraikiz, and, specifically by delving into the strategy promoted by the initiative, some emerging analytical conclusions resulting from the promotion of this collaborative culture will be presented. For example, some preliminary results have shown a significant positive relationship between shared leadership and the formulation of the public good. In the period 2016-2018, a total of 73 projects were launched and funding by the Provincial Government of Gipuzkoa within the Etorkizuna Eraikiz initiative, that indicates greater engagement of the citizenry in the process of policy-making and therefore improving, somehow, the quality of the public policies. These statements have been supported by the last survey about the perspectives of the citizens toward politics and policies. Some of the more prominent results show us that there is still a high level of distrust in Politics (78,9% of respondents) but a greater trust in institutions such the Political Government of Gipuzkoa (40,8% of respondents declared as “good” the performance of this provincial institution). Regarding the Etorkizuna Eraikiz Initiative, it is being more readily recognized by citizens over this period of time (25,4% of the respondents in June 2018 agreed to know about the initiative giving it a mark of 5,89 ) and thus build trust and a sense of ownership. Although, there is a clear requirement for further research on the linkages between collaborative governance and level of trust, the paper, based on these findings, will provide some managerial and theoretical implications for collaborative governance in the territory.

Keywords: network governance, collaborative governance, public sector innovation, citizen participation, trust

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Authors: Daryl Clement Knutt, Neela Badrie, Marsha Singh

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Quality assurance and product labelling are vital in the food and drink industry, as a tactical tool in a competitive environment. The food label is a principal marketing tool which also serves as a regulatory mechanism in the safeguarding of consumer well –being. The objective of this study was to evaluate the level of consumers’ use and understanding of food labeling information and knowledge pertaining to food quality assurance systems. The study population consisted of Trinidadian adults, who were over the age of 18 (n=384). Data collection was conducted via a self-administered questionnaire, which contained 31 questions, comprising of four sections: I. socio demographic information; II. food quality and quality assurance; III. use of Labeling information; and IV. laws and regulations. Sampling was conducted at six supermarkets, in five major regions of the country over a period of three weeks in 2014. The demographic profile of the shoppers revealed that majority was female (63.6%). The gender factor and those who were concerned about the nutrient content of their food, were predictive indicators of those who read food labels. Most (93.1%) read food labels before purchase, 15.4% ‘always’; 32.5% ‘most times’ and 45.2% ‘sometimes’. Some (42%) were often satisfied with the information presented on food labels, whilst 35.7% of consumers were unsatisfied. When the respondents were questioned on their familiarity with terms ‘food quality’ and ‘food quality assurance’, 21.3% of consumers replied positively - ‘I have heard the terms and know a lot’ whilst 37% were only ‘somewhat familiar’. Consumers were mainly knowledgeable of the International Standard of Organization (ISO) (51.5%) and Good Agricultural Practices GAP (38%) as quality tools. Participants ranked ‘nutritional information’ as the number one labeling element that should be better presented, followed by ‘allergy notes’ and ‘best before date’. Females were more inclined to read labels being the household shoppers. The shoppers would like better presentation of the food labelling information so as to guide their decision to purchase a product.

Keywords: food labels, food quality, nutrition, marketing, Trinidad, Tobago

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Authors: Zdravko Trivic, Kelvin E. Y. Low, Darko Radovic, Raymond Lucas

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Our understanding and experience of the built environment are primarily shaped by multi‐sensory, emotional and symbolic modes of exchange with spaces. Associated sensory and cognitive declines that come with ageing substantially affect the overall quality of life of the elderly citizens and the ways they perceive and use urban environment. Reduced mobility and increased risk of falls, problems with spatial orientation and communication, lower confidence and independence levels, decreased willingness to go out and social withdrawal are some of the major consequences of sensory declines that challenge almost all segments of the seniors’ everyday living. However, contemporary urban environments are often either sensory overwhelming or depleting, resulting in physical, mental and emotional stress. Moreover, the design and planning of housing neighbourhoods hardly go beyond the passive 'do-no-harm' and universal design principles, and the limited provision of often non-integrated eldercare and inter-generational facilities. This paper explores and discusses the largely neglected relationships between the 'hard' and 'soft' aspects of housing neighbourhoods and urban experience, focusing on seniors’ perception and multi-sensory experience as vehicles for design and planning of high-density housing neighbourhoods that are inclusive and empathetic yet build senior residents’ physical and mental abilities at different stages of ageing. The paper outlines methods and key findings from research conducted in two high-density housing neighbourhoods in Singapore with aims to capture and evaluate multi-sensorial qualities of two neighbourhoods from the perspective of senior residents. Research methods employed included: on-site sensory recordings of 'objective' quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, spatial mapping of patterns of elderly users’ transient and stationary activity, socio-sensory perception surveys and sensorial journeys with local residents using eye-tracking glasses, and supplemented by walk-along or post-walk interviews. The paper develops a multi-sensory framework to synthetize, cross-reference, and visualise the activity and spatio-sensory rhythms and patterns and distill key issues pertinent to ageing-friendly and health-supportive neighbourhood design. Key findings show senior residents’ concerns with walkability, safety, and wayfinding, overall aesthetic qualities, cleanliness, smell, noise, and crowdedness in their neighbourhoods, as well as the lack of design support for all-day use in the context of Singaporean tropical climate and for inter-generational social interaction. The (ongoing) analysis of eye-tracking data reveals the spatial elements of senior residents’ look at and interact with the most frequently, with the visual range often directed towards the ground. With capacities to meaningfully combine quantitative and qualitative, measured and experienced sensory data, multi-sensory framework shows to be fruitful for distilling key design opportunities based on often ignored aspects of subjective and often taken-for-granted interactions with the familiar outdoor environment. It offers an alternative way of leveraging the potentials of housing neighbourhoods to take a more active role in enabling healthful living at all stages of ageing.

Keywords: ageing-friendly neighbourhoods, eye-tracking, high-density environment, multi-sensory approach, perception

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Authors: Margarita Zavala, Julio Rolón, Gabriel Chavira, José González, Jorge Orozco, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally at this stage is when the middle school level is studied. In 2006 in Mexico incorporated “mentoring" space to assist students in their integration and participation in life. In public middle schools, is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. Whit this they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Nyashadzashe Chiraga, Anthony Walker, Glen Bright

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The manufacturing industry is currently experiencing a paradigm shift into the Fourth Industrial Revolution in which customers are increasingly at the epicentre of production. The high degree of production customization and personalization requires a flexible manufacturing system that will rapidly respond to the dynamic and volatile changes driven by the market. They are a gap in technology that allows for the optimal flow of information and optimal manufacturing operations on the shop floor regardless of the rapid changes in the fixture and part demands. Information is the reduction of uncertainty; it gives meaning and context on the state of each cell. The amount of information needed to describe cellular manufacturing systems is investigated by two measures: the structural entropy and the operational entropy. Structural entropy is the expected amount of information needed to describe scheduled states of a manufacturing system. While operational entropy is the amount of information that describes the scheduled states of a manufacturing system, which occur during the actual manufacturing operation. Using Anylogic simulator a typical manufacturing job shop was set-up with a cellular manufacturing configuration. The cellular make-up of the configuration included; a Material handling cell, 3D Printer cell, Assembly cell, manufacturing cell and Quality control cell. The factory shop provides manufactured parts to a number of clients, and there are substantial variations in the part configurations, new part designs are continually being introduced to the system. Based on the normal expected production schedule, the schedule adherence was calculated from the structural entropy and operation entropy of varying the amounts of information communicated in simulated runs. The structural entropy denotes a system that is in control; the necessary real-time information is readily available to the decision maker at any point in time. For contractive analysis, different out of control scenarios were run, in which changes in the manufacturing environment were not effectively communicated resulting in deviations in the original predetermined schedule. The operational entropy was calculated from the actual operations. From the results obtained in the empirical study, it was seen that increasing, the efficiency of a factory communication system increases the degree of adherence of a job to the expected schedule. The performance of downstream production flow fed from the parallel upstream flow of information on the factory state was increased.

Keywords: information entropy, communication in manufacturing, mass customisation, scheduling

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Authors: Haikal Achmad Thaha, Pujo Laksono, Dhamma Nibbana Putra

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Customer service is one of the core interest in a service sector of a company, whether as the core business or as service part of the operation. Most of the time, the people and the previous research in service industry is focused on finding the best business model solution for the service sector, usually to decide between total in house customer service, outsourcing, or something in between. Conventionally, to take this decision is some important part of the management job, and this is a process that usually takes some time and staff effort, meanwhile market condition and overall company needs may change and cause loss of income and temporary disturbance in the companies operation . However, in this paper we have offer a new concept model to assist decision making process in service industry. This model will featured information platform as central tool to integrate service industry operation. The result is service information model which would ideally increase response time and effectivity of the decision making. it will also help service industry in switching the service solution system quickly through machine learning when the companies growth and the service solution needed are changing.

Keywords: service industry, customer service, machine learning, decision making, information platform

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Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

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Authors: Cristina Galiana Carballo, Ibon Doval Martínez

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Urban boundaries often result in a controversial limit between countryside and city in Europe. This territory is normally defined by the very limited land uses and the abundance of open space. The dimension and dynamics of peri-urbanization in the last decades have increased this land stock, which has influenced/impacted in several factors in terms of economic costs (maintenance, transport), ecological disturbances of the territory and changes in inhabitant´s behaviour. In an increasingly urbanised world and a growing urban population, cities also face challenges such as Climate Change. In this context, new near-future corrective trends including circular economies for local food supply or decentralised waste management became key strategies towards more sustainable urban models. Those new solutions need to be planned and implemented considering the potential conflict with current land uses. The city of Vitoria-Gasteiz (Basque Country, Spain) has triplicated land consumption per habitant in 10 years, resulting in a vast extension of low-density urban type confronting rural land and threatening agricultural uses, landscape and urban sustainability. Urban planning allows managing and optimum use allocation based on soil vocation and socio-ecosystem needs, while peri-urban space arises as an opportunity for developing different uses which do not match either within the compact city, not in open agricultural lands, such as medium-size agrocomposting systems or biomass plants. Therefore, a qualitative multi-criteria methodology has been developed for Vitoria-Gasteiz city to assess the spatial definition of peri-urban land. Therefore, a qualitative multi-criteria methodology has been developed for Vitoria-Gasteiz city to assess the spatial definition of peri-urban land. Climate change and circular economy were identified as frameworks where to determine future land, soil vocation and urban planning requirements which eventually become estimations of required local food and renewable energy supply along with alternative waste management system´s implementation. By means of it, it has been developed an urban planning proposal which overcomes urban-non urban dichotomy in Vitoria-Gasteiz. The proposal aims to enhance rural system and improve urban sustainability performance through the normative recognition of an agricultural peri-urban belt.

Keywords: landscape ecology, land-use management, periurban, urban planning

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Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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Authors: Ali Mohammadi

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Whenever there is a need to dig the ground, the presence of a surveyor is required to control the map. In projects such as dams and tunnels, these controls are more important because any mistakes can increase the cost. Also, time is great importance in These projects have and one of the ways to reduce the drilling time is to use techniques that can reduce the mapping time in these projects. Nowadays, with the existence of mobile phones, we can design apps that perform calculations and drawing for us on the mobile phone. Also, if we have a device that requires a computer to access its information, by designing an app, we can transfer its information to the mobile phone and use it, so we will not need to go to the office.

Keywords: app, tunnel, excavation, dam

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Authors: Kurt Maxwell Kusterer, Sylvain Mignot, Annick Vignes

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To our best knowledge YouTube is the largest video hosting platform in the world. A high number of creators, viewers, subscribers and commentators act in this specific eco-system which generates huge sums of money. Views, subscribers, and comments help to increase the popularity of content creators. The most popular creators are sponsored by brands and participate in marketing campaigns. For a few of them, this becomes a financially rewarding profession. This is made possible through the YouTube Partner Program, which shares revenue among creators based on their popularity. We believe that the role of comments in increasing the popularity is to be emphasized. In what follows, YouTube is considered as a bilateral network between the videos and the commentators. Analyzing a detailed data set focused on French YouTubers, we consider each comment as a link between a commentator and a video. Our research question asks what are the predominant features of a video which give it the highest probability to be commented on. Following on from this question, how can we use these features to predict the action of the agent in commenting one video instead of another, considering the characteristics of the commentators, videos, topics, channels, and recommendations. We expect to see that the videos of more popular channels generate higher viewer engagement and thus are more frequently commented. The interest lies in discovering features which have not classically been considered as markers for popularity on the platform. A quick view of our data set shows that 96% of the commentators comment only once on a certain video. Thus, we study a non-weighted bipartite network between commentators and videos built on the sub-sample of 96% of unique comments. A link exists between two nodes when a commentator makes a comment on a video. We run an Exponential Random Graph Model (ERGM) approach to evaluate which characteristics influence the probability of commenting a video. The creation of a link will be explained in terms of common video features, such as duration, quality, number of likes, number of views, etc. Our data is relevant for the period of 2020-2021 and focuses on the French YouTube environment. From this set of 391 588 videos, we extract the channels which can be monetized according to YouTube regulations (channels with at least 1000 subscribers and more than 4000 hours of viewing time during the last twelve months).In the end, we have a data set of 128 462 videos which consist of 4093 channels. Based on these videos, we have a data set of 1 032 771 unique commentators, with a mean of 2 comments per a commentator, a minimum of 1 comment each, and a maximum of 584 comments.

Keywords: YouTube, social networks, economics, consumer behaviour

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Authors: Murtala Mohammed Alamai, Abdullahi Marshal Idris, Adama Idris

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Today, marketing does not only involve selecting target markets, but it also involves communicating with the customers through various means to put across your selling point. Modern marketing involves driving new product development based on customer needs by getting feedback from them. Utilizing the latest technology for better communication with the customers is the latest advancement in Marketing in the 21st century. The survey approach was used where a sample of tourist destinations across the six geographical zones of the country at random was done to ascertain the use of information communication systems in promoting their products and or services, the findings revealed that only a few utilize these modern advanced means in marketing and promoting their products and a need to develop effective and up to date online services for marketing was proffered as solutions to the findings observed.

Keywords: information, communication, travel, trade, promotion

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Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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Authors: Kulvinder Singh Mann

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The usability and simulation of information systems, known as Hospital Information System (HIS), Radiology Information System (RIS), and Picture Archiving, Communication System, for electronic medical records has shown a good impact for actors in the hospital. The objective is to help and make their work easier; such as for a nurse or administration staff to record the medical records of the patient, and for a patient to check their bill transparently. However, several limitations still exists on such area regarding the type of data being stored in the system, ability for data transfer, storage and protocols to support communication between medical devices and digital images. This paper reports the simulation result of integrating several systems to cope with those limitations by using the Modality Worklist and DICOM standard. It succeeds in documenting the reason of that failure so future research will gain better understanding and be able to integrate those systems.

Keywords: HIS, RIS, PACS, modality worklist, DICOM, digital images

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Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

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Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

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Authors: Amit Tribedi

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Genuine Quantumness present in Quantum Systems is the resource for implementing Quantum Information and Computation Protocols which can outperform the classical counterparts. These Quantumness measures encompass non-local ones known as quantum entanglement (QE) and quantum information theoretic (QIT) ones, e.g. Quantum Discord (QD). In this paper, some well-known measures of QE and QD in some wheel-like frustrated molecular magnetic systems have been studied. One of the systems has already been synthesized using coordination chemistry, and the other is hypothetical, where the dominant interaction is the spin-spin exchange interaction. Exact analytical methods and exact numerical diagonalization methods have been used. Some counter-intuitive non-trivial features, like non-monotonicity of quantum correlations with temperature, persistence of multipartite entanglement over bipartite ones etc. indicated by the behaviour of the correlations and the QIT measures have been found. The measures, being operational ones, can be used to realize the resource of Quantumness in experiments.

Keywords: 0D Magnets, discord, entanglement, frustration

Procedia PDF Downloads 228

Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

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Authors: Andrea Miconi

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The research will focus on the results of the Tempus European Project eMEDia dedicated to Cross-Media Journalism. The project is founded by the European Commission as it involves four European partners - IULM University, Tampere University, University of Barcelona, and the Mediterranean network Unimed - and three Tunisian Universities – IPSI La Manouba, Sfax and Sousse – along with the Tunisian Ministry for Higher Education and the National Syndicate of Journalists. The focus on Tunisian condition is basically due to the role played by digital activists in its recent history. The research is dedicated to the relationship between political participation, news-making practices and the spread of social media, as it is affecting Tunisian society. As we know, Tunisia during the Arab Spring had been widely considered as a laboratory for the analysis the use of new technologies for political participation. Nonetheless, the literature about the Arab Spring actually fell short in explaining the genesis of the phenomenon, on the one hand by isolating technologies as a casual factor in the spread of demonstrations, and on the other by analyzing North-African condition through a biased perspective. Nowadays, it is interesting to focus on the consolidation of the information environment three years after the uprisings. And what is relevant, only a close, in-depth analysis of Tunisian society is able to provide an explanation of its history, and namely of the part of digital media in the overall evolution of political system. That is why the research is based on different methodologies: desk stage, interviews, and in-depth analysis of communication practices. Networked journalism is the condition determined by the technological innovation on news-making activities: a condition upon which professional journalist can no longer be considered the only player in the information arena, and a new skill must be developed. Along with democratization, nonetheless, the so-called citizen journalism is also likely to produce some ambiguous effects, such as the lack of professional standards and the spread of information cascades, which may prove to be particularly dangerous in an evolving media market as the Tunisian one. This is why, according to the project, a new profile must be defined, which is able to manage this new condition, and which can be hardly reduced to the parameters of traditional journalistic work. Rather than simply using new devices for news visualization, communication professionals must also be able to dialogue with all new players and to accept the decentralized nature of digital environments. This networked nature of news-making seemed to emerge during the Tunisian revolution, when bloggers, journalists, and activists used to retweet each other. Nonetheless, this intensification of communication exchange was inspired by the political climax of the uprising, while all media, by definition, are also supposed to bring some effects on people’s state of mind, culture and daily life routines. That is why it is worth analyzing the consolidation of these practices in a normal, post-revolutionary situation.

Keywords: cross-media, education, Mediterranean, networked journalism, social media, Tunisia

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Chung-Hung Tsai, Ya-Ping Li

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Tourism industry is highly depended on the natural environment and climate. Compared to other industries, it is more susceptible to environment and climate. Taiwan belongs to a sea island country and located in the subtropical monsoon zone. The events of climate variability, frequency of typhoons and rainfalls raged are caused regularly serious disaster. In traditional disaster assessment, it usually focuses on the disaster damage and risk assessment, which is short of the features from different industries to understand the impact of the restoring force in post-disaster resilience and the main factors that constitute resilience. The object of this study is based on disaster recovery experience of tourism area and to understand the main factors affecting the tourist area of disaster resilience. The combinations of literature review and interviews with experts are prepared an early indicator system of the disaster resilience. Then, it is screened through a Fuzzy Delphi Method and Analytic Network Process for weight analysis. Finally, this study will establish the tourism disaster resilience evaluation index system considering the Taiwan's tourism industry characteristics. We hope that be able to enhance disaster resilience after tourist areas and increases the sustainability of industrial development. It is expected to provide government departments the tourism industry as the future owner of the assets in extreme climates responses.

Keywords: resilience, Fuzzy Delphi Method, Analytic Network Process, industrial development

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: Qin Long, Li Xiaoge

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The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

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Authors: Alireza Monzavi Chaleshtari, Mahnaz Aliakbari Dehkordi, Amin Asadi Hieh, Majid Kazemnezhad

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This research was conducted with the aim of determining the effectiveness of sexual cognitive behavioral therapy on psychological performance and openness to experience in women. The type of research was experimental in the form of pre-test-post-test. The statistical population of this research was made up of all working and married women with membership in the researcher's Instagram social network who had problems in marital-sexual relationships (N=900). From the statistical community, which includes working and married women who are members of the researcher's Instagram social network who have problems in marital-sexual relationships, there are 30 people including two groups (15 people in the experimental group and 15 people in the control group) as available sampling and selected randomly. They were placed in two experimental and control groups. The anxiety, stress, and depression scale (DASS) and the Costa and McCree personality questionnaire were used to collect data, and the cognitive behavioral therapy protocol of Dr. Mehrnaz Ali Akbari was used for the treatment sessions. To analyze the data, the covariance test was used in the SPSS22 software environment. The results showed that sexual cognitive behavioral therapy has a positive and significant effect on psychological performance and openness to experience in women. Conclusion: It can be concluded that interventions such as cognitive-behavioral sex can be used to treat marital problems.

Keywords: sexual cognitive behavioral therapy, psychological function, openness to experience, women

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 144

Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew

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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.

Keywords: health, public health, GIS, geographic information system

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Authors: Chariton Christou, David Cornwell

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Production Sharing Contract (PSC) is the type of contract that is being used widely in our time. The financial crisis made the governments tightfisted and they do not have the resources to participate in a development of a field. Therefore, more and more countries introduce the PSC. The companies have the power and the money to develop the field with their own way. The main problem is the transparency of oil and gas companies especially in the PSC and how this can be achieved. Many discussions have been made especially in the U.K. What we are suggesting is a dynamic financial simulation with the help of a flow meter. The flow meter will count the production of each field every day (it will be installed in a pipeline). The production will be the basic input of the simulation. It will count the profit, the costs and more according to the information of the flow meter. In addition it will include the terms of the contract and the costs that have been paid. By all these parameters the simulation will be able to present in real time the information of a field (taxes, employees, R-factor). By this simulation the company will share some information with the government but not all of them. The government will know the taxes that should be paid and what is the sharing percentage of it. All of the other information could be confidential for the company. Furthermore, oil company could control the R-factor by changing the production each day to maximize its sharing percentages and as a result of this the profit. This idea aims to change the way that governments 'control' oil companies and bring a transparency evolution in the industry. With the help of a simulation every country could be next to the company and have a better collaboration.

Keywords: production sharing contracts, transparency, simulation

Procedia PDF Downloads 375

Authors: Xinrong Li, Jiawei Dai

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Food production, food safety, and the food supply chain are causing a great challenge to human health and the environment. Different kinds of food have different environmental costs. Therefore, a healthy diet can alleviate this problem to a certain extent. In this project, an online questionnaire was conducted to understand the purchase behaviour of consumers and their attitudes towards basic food information. However, the data shows that the public's current consumption habits and ideology do not meet the long-term development of sustainable social needs. In order to solve the environmental problems caused by the unbalanced diet of the public and the social problems of unequal food distribution, the purpose of this paper is to explore how to use the emerging media of VR to visualize food supply chain information so as to attract users' attention to the environmental cost of food. In this project, the food supply chain of imported and local cheese was compared side-by-side in the virtual reality environment, including the origin, transportation, sales, and other processes, which can effectively help users understand the difference between the two processes and environmental costs. Besides, the experimental data demonstrated that the participant would like to choose low environmental cost food after experiencing the whole process.

Keywords: virtual reality, information design, food supply chain, environmental cost

Procedia PDF Downloads 97