Search results for: star network
Commenced in January 2007
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Edition: International
Paper Count: 4791

Search results for: star network

2361 Deep Learning Based Polarimetric SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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2360 Investigation of Wind Farm Interaction with Ethiopian Electric Power’s Grid: A Case Study at Ashegoda Wind Farm

Authors: Fikremariam Beyene, Getachew Bekele

Abstract:

Ethiopia is currently on the move with various projects to raise the amount of power generated in the country. The progress observed in recent years indicates this fact clearly and indisputably. The rural electrification program, the modernization of the power transmission system, the development of wind farm is some of the main accomplishments worth mentioning. As it is well known, currently, wind power is globally embraced as one of the most important sources of energy mainly for its environmentally friendly characteristics, and also that once it is installed, it is a source available free of charge. However, integration of wind power plant with an existing network has many challenges that need to be given serious attention. In Ethiopia, a number of wind farms are either installed or are under construction. A series of wind farm is planned to be installed in the near future. Ashegoda Wind farm (13.2°, 39.6°), which is the subject of this study, is the first large scale wind farm under construction with the capacity of 120 MW. The first phase of 120 MW (30 MW) has been completed and is expected to be connected to the grid soon. This paper is concerned with the investigation of the wind farm interaction with the national grid under transient operating condition. The main concern is the fault ride through (FRT) capability of the system when the grid voltage drops to exceedingly low values because of short circuit fault and also the active and reactive power behavior of wind turbines after the fault is cleared. On the wind turbine side, a detailed dynamic modelling of variable speed wind turbine of a 1 MW capacity running with a squirrel cage induction generator and full-scale power electronics converters is done and analyzed using simulation software DIgSILENT PowerFactory. On the Ethiopian electric power corporation side, after having collected sufficient data for the analysis, the grid network is modeled. In the model, a fault ride-through (FRT) capability of the plant is studied by applying 3-phase short circuit on the grid terminal near the wind farm. The results show that the Ashegoda wind farm can ride from voltage deep within a short time and the active and reactive power performance of the wind farm is also promising.

Keywords: squirrel cage induction generator, active and reactive power, DIgSILENT PowerFactory, fault ride-through capability, 3-phase short circuit

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2359 Development of Alternative Fuels Technologies: Compressed Natural Gas Home Refueling Station

Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Adam Szurlej

Abstract:

Compressed natural gas (CNG) represents an excellent compromise between the availability of a technology that is proven and relatively easy to use in many areas of the automotive industry and incurred costs. This fuel causes a lower corrosion effect due to the lower content of products causing the potential difference on the walls of the engine system. Natural gas powered vehicles (NGVs) do not emit any substances that can contaminate water or land. The absence of carcinogenic substances in gaseous fuel extends the life of the engine. In the longer term, it contributes positively to waste management as well as waste disposal. Popularization of propulsion systems powered by natural gas CNG positively affects the reduction of heavy duty transport. For these reasons, CNG as a fuel stimulates considerable interest around the world. Over the last few years, technologies related to use of natural gas as an engine fuel have been developed and improved. These solutions have evolved from the prototype phase to the industrial scale implementation. The widespread availability of gaseous fuels has led to the development of a technology that allows the CNG fuel to be refueled directly from the urban gas network to the vehicle tank (ie. HYGEN - CNGHRS). Home refueling installations, although they have been known for many years, are becoming increasingly important in the present day. The major obstacle in the sale of this technology was, until recently, quite high capital expenditure compared to the later benefits. Home refueling systems allow refueling vehicle tank, with full control of fuel costs and refueling time. CNG Home Refueling Stations (such as HYGEN) allow gas value chain to overcome the dogma that there is a lack of refueling infrastructure allowing companies in gas value chain to participate in transportation market. Technology is based on one stage hydraulic compressor (instead of multistage mechanical compressor technology) which provides the possibility to compress low pressure gas from distribution gas network to 200 bar for its further usage as a fuel for NGVs. This boosts revenues and profits of gas companies by expanding its presence in higher margin of energy sector.

Keywords: alternative fuels, CNG (compressed natural gas), CNG stations, NGVs (natural gas vehicles), gas value chain

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2358 Cloud Design for Storing Large Amount of Data

Authors: M. Strémy, P. Závacký, P. Cuninka, M. Juhás

Abstract:

Main goal of this paper is to introduce our design of private cloud for storing large amount of data, especially pictures, and to provide good technological backend for data analysis based on parallel processing and business intelligence. We have tested hypervisors, cloud management tools, storage for storing all data and Hadoop to provide data analysis on unstructured data. Providing high availability, virtual network management, logical separation of projects and also rapid deployment of physical servers to our environment was also needed.

Keywords: cloud, glusterfs, hadoop, juju, kvm, maas, openstack, virtualization

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2357 Estimation of Small Hydropower Potential Using Remote Sensing and GIS Techniques in Pakistan

Authors: Malik Abid Hussain Khokhar, Muhammad Naveed Tahir, Muhammad Amin

Abstract:

Energy demand has been increased manifold due to increasing population, urban sprawl and rapid socio-economic improvements. Low water capacity in dams for continuation of hydrological power, land cover and land use are the key parameters which are creating problems for more energy production. Overall installed hydropower capacity of Pakistan is more than 35000 MW whereas Pakistan is producing up to 17000 MW and the requirement is more than 22000 that is resulting shortfall of 5000 - 7000 MW. Therefore, there is a dire need to develop small hydropower to fulfill the up-coming requirements. In this regards, excessive rainfall, snow nurtured fast flowing perennial tributaries and streams in northern mountain regions of Pakistan offer a gigantic scope of hydropower potential throughout the year. Rivers flowing in KP (Khyber Pakhtunkhwa) province, GB (Gilgit Baltistan) and AJK (Azad Jammu & Kashmir) possess sufficient water availability for rapid energy growth. In the backdrop of such scenario, small hydropower plants are believed very suitable measures for more green environment and power sustainable option for the development of such regions. Aim of this study is to estimate hydropower potential sites for small hydropower plants and stream distribution as per steam network available in the available basins in the study area. The proposed methodology will focus on features to meet the objectives i.e. site selection of maximum hydropower potential for hydroelectric generation using well emerging GIS tool SWAT as hydrological run-off model on the Neelum, Kunhar and the Dor Rivers’ basins. For validation of the results, NDWI will be computed to show water concentration in the study area while overlaying on geospatial enhanced DEM. This study will represent analysis of basins, watershed, stream links, and flow directions with slope elevation for hydropower potential to produce increasing demand of electricity by installing small hydropower stations. Later on, this study will be benefitted for other adjacent regions for further estimation of site selection for installation of such small power plants as well.

Keywords: energy, stream network, basins, SWAT, evapotranspiration

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2356 Research on Internet Attention of Tourism and Marketing Strategy in Northeast Sichuan Economic Zone in China Based on Baidu Index

Authors: Chuanqiao Zheng, Wei Zeng, Haozhen Lin

Abstract:

As of March 2020, the number of Chinese netizens has reached 904 million. The proportion of Internet users accessing the Internet through mobile phones is as high as 99.3%. Under the background of 'Internet +', tourists have a stronger sense of independence in the choice of tourism destinations and tourism products. Tourists are more inclined to learn about the relevant information on tourism destinations and other tourists' evaluations of tourist products through the Internet. The search engine, as an integrated platform that contains a wealth of information, is highly valuable to the analysis of the characteristics of the Internet attention given to various tourism destinations, through big data mining and analysis. This article uses the Baidu Index as the data source, which is one of the products of Baidu Search. The Baidu Index is based on big data, which collects and shares the search results of a large number of Internet users on the Baidu search engine. The big data used in this article includes search index, demand map, population profile, etc. The main research methods used are: (1) based on the search index, analyzing the Internet attention given to the tourism in five cities in Northeast Sichuan at different times, so as to obtain the overall trend and individual characteristics of tourism development in the region; (2) based on the demand map and the population profile, analyzing the demographic characteristics and market positioning of the tourist groups in these cities to understand the characteristics and needs of the target groups; (3) correlating the Internet attention data with the permanent population of each province in China in the corresponding to construct the Boston matrix of the Internet attention rate of the Northeast Sichuan tourism, obtain the tourism target markets, and then propose development strategies for different markets. The study has found that: a) the Internet attention given to the tourism in the region can be categorized into tourist off-season and peak season; the Internet attention given to tourism in different cities is quite different. b) tourists look for information including tour guide information, ticket information, traffic information, weather information, and information on the competing tourism cities; with regard to the population profile, the main group of potential tourists searching for the keywords of tourism in the five prefecture-level cities in Northeast Sichuan are youth. The male to female ratio is about 6 to 4, with males being predominant. c) through the construction of the Boston matrix, it is concluded that the star market for tourism in the Northeast Sichuan Economic Zone includes Sichuan and Shaanxi; the cash cows market includes Hainan and Ningxia; the question market includes Jiangsu and Shanghai; the dog market includes Hubei and Jiangxi. The study concludes with the following planning strategies and recommendations: i) creating a diversified business format that integrates cultural and tourism; ii) creating a brand image of niche tourism; iii) focusing on the development of tourism products; iv) innovating composite three-dimensional marketing channels.

Keywords: Baidu Index, big data, internet attention, tourism

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2355 Cleaning of Polycyclic Aromatic Hydrocarbons (PAH) Obtained from Ferroalloys Plant

Authors: Stefan Andersson, Balram Panjwani, Bernd Wittgens, Jan Erik Olsen

Abstract:

Polycyclic Aromatic hydrocarbons are organic compounds consisting of only hydrogen and carbon aromatic rings. PAH are neutral, non-polar molecules that are produced due to incomplete combustion of organic matter. These compounds are carcinogenic and interact with biological nucleophiles to inhibit the normal metabolic functions of the cells. Norways, the most important sources of PAH pollution is considered to be aluminum plants, the metallurgical industry, offshore oil activity, transport, and wood burning. Stricter governmental regulations regarding emissions to the outer and internal environment combined with increased awareness of the potential health effects have motivated Norwegian metal industries to increase their efforts to reduce emissions considerably. One of the objective of the ongoing industry and Norwegian research council supported "SCORE" project is to reduce potential PAH emissions from an off gas stream of a ferroalloy furnace through controlled combustion. In a dedicated combustion chamber. The sizing and configuration of the combustion chamber depends on the combined properties of the bulk gas stream and the properties of the PAH itself. In order to achieve efficient and complete combustion the residence time and minimum temperature need to be optimized. For this design approach reliable kinetic data of the individual PAH-species and/or groups thereof are necessary. However, kinetic data on the combustion of PAH are difficult to obtain and there is only a limited number of studies. The paper presents an evaluation of the kinetic data for some of the PAH obtained from literature. In the present study, the oxidation is modelled for pure PAH and also for PAH mixed with process gas. Using a perfectly stirred reactor modelling approach the oxidation is modelled including advanced reaction kinetics to study influence of residence time and temperature on the conversion of PAH to CO2 and water. A Chemical Reactor Network (CRN) approach is developed to understand the oxidation of PAH inside the combustion chamber. Chemical reactor network modeling has been found to be a valuable tool in the evaluation of oxidation behavior of PAH under various conditions.

Keywords: PAH, PSR, energy recovery, ferro alloy furnace

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2354 A Social Network Analysis for Formulating Construction Defect Generation Mechanisms

Authors: Hamad Aljassmi, Sangwon Han

Abstract:

Various solutions for preventing construction defects have been suggested. However, a construction company may have difficulties adopting all these suggestions due to financial and practical constraints. Based on this recognition, this paper aims to identify the most significant defect causes and formulate their defect generation mechanism in order to help a construction company to set priorities of its defect prevention strategies. For this goal, we conducted a questionnaire survey of 106 industry professionals and identified five most significant causes including: (1) organizational culture, (2) time pressure and constraints, (3) workplace quality system, (4) financial constraints upon operational expenses and (5) inadequate employee training or learning opportunities.

Keywords: defect, quality, failure, risk

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2353 Survey: Topology Hiding in Multipath Routing Protocol in MANET

Authors: Akshay Suhas Phalke, Manohar S. Chaudhari

Abstract:

In this paper, we have discussed the multipath routing with its variants. Our purpose is to discuss the different types of the multipath routing mechanism. Here we also put the taxonomy of the multipath routing. Multipath routing is used for the alternate path routing, reliable transmission of data and for better utilization of network resources. We also discussed the multipath routing for topology hiding such as TOHIP. In multipath routing, different parameters such as energy efficiency, packet delivery ratio, shortest path routing, fault tolerance play an important role. We have discussed a number of multipath routing protocol based on different parameters lastly.

Keywords: multi-path routing, WSN, topology, fault detection, trust

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2352 A Local Tensor Clustering Algorithm to Annotate Uncharacterized Genes with Many Biological Networks

Authors: Paul Shize Li, Frank Alber

Abstract:

A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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2351 Collaborative and Experimental Cultures in Virtual Reality Journalism: From the Perspective of Content Creators

Authors: Radwa Mabrook

Abstract:

Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: collaborative culture, content creation, experimental culture, virtual reality

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2350 An Introspective look into Hotel Employees Career Satisfaction

Authors: Anastasios Zopiatis, Antonis L. Theocharous

Abstract:

In the midst of a fierce war for talent, the hospitality industry is seeking new and innovative ways to enrich its image as an employer of choice and not a necessity. Historically, the industry’s professions are portrayed as ‘unattractive’ due to their repetitious nature, long and unsocial working schedules, below average remunerations, and the mental and physical demands of the job. Aligning with the industry, hospitality and tourism scholars embarked on a journey to investigate pertinent topics with the aim of enhancing our conceptual understanding of the elements that influence employees at the hospitality world of work. Topics such as job involvement, commitment, job and career satisfaction, and turnover intentions became the focal points in a multitude of relevant empirical and conceptual investigations. Nevertheless, gaps or inconsistencies in existing theories, as a result of both the volatile complexity of the relationships governing human behavior in the hospitality workplace, and the academic community’s unopposed acceptance of theoretical frameworks mainly propounded in the United States and United Kingdom years ago, necessitate our continuous vigilance. Thus, in an effort to enhance and enrich the discourse, we set out to investigate the relationship between intrinsic and extrinsic job satisfaction traits and the individual’s career satisfaction, and subsequent intention to remain in the hospitality industry. Reflecting on existing literature, a quantitative survey was developed and administered, face-to-face, to 650 individuals working as full-time employees in 4- and 5- star hotel establishments in Cyprus, whereas a multivariate statistical analysis method, namely Structural Equation Modeling (SEM), was utilized to determine whether relationships existed between constructs as a means to either accept or reject the hypothesized theory. Findings, of interest to both industry stakeholders and academic scholars, suggest that the individual’s future intention to remain within the industry is primarily associated with extrinsic job traits. Our findings revealed that positive associations exist between extrinsic job traits, and both career satisfaction and future intention. In contrast, when investigating the relationship of intrinsic traits, a positive association was revealed only with career satisfaction. Apparently, the local industry’s environmental factors of seasonality, excessive turnover, overdependence on seasonal, and part-time migrant workers, prohibit industry stakeholders in effectively investing the time and resources in the development and professional growth of their employees. Consequently intrinsic job satisfaction factors such as advancement, growth, and achievement, take backstage to the more materialistic extrinsic factors. Findings from the subsequent mediation analysis support the notion that intrinsic traits can positively influence future intentions indirectly only through career satisfaction, whereas extrinsic traits can positively impact both career satisfaction and future intention both directly and indirectly.

Keywords: career satisfaction, Cyprus, hotel employees, structural equation modeling, SEM

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2349 Extracting Attributes for Twitter Hashtag Communities

Authors: Ashwaq Alsulami, Jianhua Shao

Abstract:

Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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2348 Minimizing Fresh and Wastewater Using Water Pinch Technique in Petrochemical Industries

Authors: Wasif Mughees, Malik Al-Ahmad, Muhammad Naeem

Abstract:

This research involves the design and analysis of pinch-based water/wastewater networks to minimize water utility in the petrochemical and petroleum industries. A study has been done on Tehran Oil Refinery to analyze feasibilities of regeneration, reuse and recycling of water network. COD is considered as a single key contaminant. Amount of freshwater was reduced about 149m3/h (43.8%) regarding COD. Re-design (or retrofitting) of water allocation in the networks was undertaken. The results were analyzed through graphical method and mathematical programming technique which clearly demonstrated that amount of required water would be determined by mass transfer of COD.

Keywords: minimization, water pinch, water management, pollution prevention

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2347 An Artificial Neural Network Model Based Study of Seismic Wave

Authors: Hemant Kumar, Nilendu Das

Abstract:

A study based on ANN structure gives us the information to predict the size of the future in realizing a past event. ANN, IMD (Indian meteorological department) data and remote sensing were used to enable a number of parameters for calculating the size that may occur in the future. A threshold selected specifically above the high-frequency harvest reached the area during the selected seismic activity. In the field of human and local biodiversity it remains to obtain the right parameter compared to the frequency of impact. But during the study the assumption is that predicting seismic activity is a difficult process, not because of the parameters involved here, which can be analyzed and funded in research activity.

Keywords: ANN, Bayesion class, earthquakes, IMD

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2346 Results of Three-Year Operation of 220kV Pilot Superconducting Fault Current Limiter in Moscow Power Grid

Authors: M. Moyzykh, I. Klichuk, L. Sabirov, D. Kolomentseva, E. Magommedov

Abstract:

Modern city electrical grids are forced to increase their density due to the increasing number of customers and requirements for reliability and resiliency. However, progress in this direction is often limited by the capabilities of existing network equipment. New energy sources or grid connections increase the level of short-circuit currents in the adjacent network, which can exceed the maximum rating of equipment–breaking capacity of circuit breakers, thermal and dynamic current withstand qualities of disconnectors, cables, and transformers. Superconducting fault current limiter (SFCL) is a modern solution designed to deal with the increasing fault current levels in power grids. The key feature of this device is its instant (less than 2 ms) limitation of the current level due to the nature of the superconductor. In 2019 Moscow utilities installed SuperOx SFCL in the city power grid to test the capabilities of this novel technology. The SFCL became the first SFCL in the Russian energy system and is currently the most powerful SFCL in the world. Modern SFCL uses second-generation high-temperature superconductor (2G HTS). Despite its name, HTS still requires low temperatures of liquid nitrogen for operation. As a result, Moscow SFCL is built with a cryogenic system to provide cooling to the superconductor. The cryogenic system consists of three cryostats that contain a superconductor part and are filled with liquid nitrogen (three phases), three cryocoolers, one water chiller, three cryopumps, and pressure builders. All these components are controlled by an automatic control system. SFCL has been continuously operating on the city grid for over three years. During that period of operation, numerous faults occurred, including cryocooler failure, chiller failure, pump failure, and others (like a cryogenic system power outage). All these faults were eliminated without an SFCL shut down due to the specially designed cryogenic system backups and quick responses of grid operator utilities and the SuperOx crew. The paper will describe in detail the results of SFCL operation and cryogenic system maintenance and what measures were taken to solve and prevent similar faults in the future.

Keywords: superconductivity, current limiter, SFCL, HTS, utilities, cryogenics

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2345 Ant-Tracking Attribute: A Model for Understanding Production Response

Authors: Prince Suka Neekia Momta, Rita Iheoma Achonyeulo

Abstract:

Ant Tracking seismic attribute applied over 4-seconds seismic volume revealed structural features triggered by clay diapirism, growth fault development, rapid deltaic sedimentation and intense drilling. The attribute was extracted on vertical seismic sections and time slices. Mega tectonic structures such as growth faults and clay diapirs are visible on vertical sections with obscured minor lineaments or fractures. Fractures are distinctively visible on time slices yielding recognizable patterns corroborating established geologic models. This model seismic attribute enabled the understanding of fluid flow characteristics and production responses. Three structural patterns recognized in the field include: major growth faults, minor faults or lineaments and network of fractures. Three growth faults mapped on seismic section form major deformation bands delimiting the area into three blocks or depocenters. The growth faults trend E-W, dip down-to-south in the basin direction, and cut across the study area. The faults initiating from about 2000ms extended up to 500ms, and tend to progress parallel and opposite to the growth direction of an upsurging diapiric structure. The diapiric structures form the major deformational bands originating from great depths (below 2000ms) and rising to about 1200ms where series of sedimentary layers onlapped and pinchout stratigraphically against the diapir. Several other secondary faults or lineaments that form parallel streaks to one another also accompanied the growth faults. The fracture networks have no particular trend but form a network surrounding the well area. Faults identified in the study area have potentials for structural hydrocarbon traps whereas the presence of fractures created a fractured-reservoir condition that enhanced rapid fluid flow especially water. High aquifer flow potential aided by possible fracture permeability resulted in rapid decline in oil rate. Through the application of Ant Tracking attribute, it is possible to obtain detailed interpretation of structures that can have direct influence on oil and gas production.

Keywords: seismic, attributes, production, structural

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2344 Is There a Group of "Digital Natives" at Secondary Schools?

Authors: L. Janská, J. Kubrický

Abstract:

The article describes a research focused on the influence of the information and communication technology (ICT) on the pupils' learning. The investigation deals with the influences that distinguish between the group of pupils influenced by ICT and the group of pupils not influenced by ICT. The group influenced by ICT should evince a different approach in number of areas (in managing of two and more activities at once, in a quick orientation and searching for information on the Internet, in an ability to quickly and effectively assess the data sources, in the assessment of attitudes and opinions of the other users of the network, in critical thinking, in the preference to work in teams, in the sharing of information and personal data via the virtual social networking, in insisting on the immediate reaction on their every action etc.).

Keywords: ICT influence, digital natives, pupil´s learning

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2343 Power Management in Wireless Combustible Gas Sensors

Authors: Denis Spirjakin, Alexander Baranov, Saba Akbari, Natalia Kalenova, Vladimir Sleptsov

Abstract:

In this paper we propose the approach to power management in wireless combustible gas sensors. This approach makes possible drastically prolong sensor nodes autonomous lifetime. That is necessary to tie battery replacement to every year technical service procedures which are claimed by safety standards. Using this approach the current consumption of the wireless combustible gas sensor node was decreased from 80 mA to less than 2 mA and the power consumption from more than 220 mW to 4.6 mW. These values provide autonomous lifetime of the node more than one year.

Keywords: Gas sensors, power management, wireless sensor network

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2342 AIR SAFE: an Internet of Things System for Air Quality Management Leveraging Artificial Intelligence Algorithms

Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

Abstract:

Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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2341 Feedback of Using Set-Up Candid Clips as New Media

Authors: Miss Suparada Prapawong

Abstract:

The objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire and in-depth interview from experts. The findings showed the advantages and disadvantages of communication for publicizing and advertising via new media in the form of set up candid clip including with the specific target group for this kind of advertising. It will be useful for fields of publicizing and advertising in the new media forms at the present.

Keywords: candid clip, communication, new media, social network

Procedia PDF Downloads 287
2340 Politics in Academia: How the Diffusion of Innovation Relates to Professional Capital

Authors: Autumn Rooms Cypres, Barbara Driver

Abstract:

The purpose of this study is to extend discussions about innovations and career politics. Research questions that grounded this effort were: How does an academic learn the unspoken rules of the academy? What happens politically to an academic’s career when their research speaks against the grain of society? Do professors perceive signals that it is time to move on to another institution or even to another career? Epistemology and Methods: This qualitative investigation was focused on examining perceptions of academics. Therefore an open-ended field study, based on Grounded Theory, was used. This naturalistic paradigm (Lincoln & Guba,1985) was selected because it tends to understand information in terms of whole, of patterns, and in relations to the context of the environment. The technique for gathering data was the process of semi-structured, in-depth interviewing. Twenty five academics across the United States were interviewed relative to their career trajectories and the politics and opportunities they have encountered in relation to their research efforts. Findings: The analysis of interviews revealed four themes: Academics are beholden to 2 specific networks of power that influence their sense of job security; the local network based on their employing university and the national network of scholars who share the same field of research. The fights over what counts as research can and does drift from the intellectual to the political, and personal. Academic were able to identify specific instances of shunning and or punishment from their colleagues related directly to the dissemination of research that spoke against the grain of the local or national networks. Academics identified specific signals from both of these networks indicating that their career was flourishing or withering. Implications: This research examined insights from those who persevered when the fights over what and who counts drifted from the intellectual to the political, and the personal. Considerations of why such drifts happen were offered in the form of a socio-political construct called Fit, which included thoughts on hegemony, discourse, and identity. This effort reveals the importance of understanding what professional capital is relative to job security. It also reveals that fear is an enmeshed and often unspoken part of the culture of Academia. Further research to triangulate these findings would be helpful within international contexts.

Keywords: politics, academia, job security, context

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2339 Set Up Candid Clips Effectiveness

Authors: P. Suparada, D. Eakapotch

Abstract:

The objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire and in-depth interview from experts. The findings showed the advantages and disadvantages of communication for publicizing and advertising via new media in the form of set up candid clip including with the specific target group for this kind of advertising. It will be useful for fields of publicizing and advertising in the new media forms at the present.

Keywords: candid clip, communication, new media, social network

Procedia PDF Downloads 223
2338 An Efficient Algorithm for Solving the Transmission Network Expansion Planning Problem Integrating Machine Learning with Mathematical Decomposition

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

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2337 A Horn Antenna Loaded with FSS of Crossed Dipoles

Authors: Ibrahim Mostafa El-Mongy, Abdelmegid Allam

Abstract:

In this article analysis and investigation of the effect of loading a horn antenna with frequency selective surface (FSS) of crossed dipoles of finite size is presented. It is fabricated on Rogers RO4350 (lossy) of relative permittivity 3.33, thickness 1.524 mm and loss tangent 0.004. Basically it is applied for filtering and minimizing the interference and noise in the desired band. The filtration is carried out using a finite FSS of crossed dipoles of overall dimensions 98x58 mm2. The filtration is shown by limiting the transmission bandwidth from 4 GHz (8–12 GHz) to 0.25 GHz (10.75–11 GHz). It is simulated using CST MWS and measured using network analyzer. There is a good agreement between the simulated and measured results.

Keywords: antenna, filtenna, frequency selective surface (FSS), horn

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2336 Clustering the Wheat Seeds Using SOM Artificial Neural Networks

Authors: Salah Ghamari

Abstract:

In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

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2335 Democracy in Gaming: An Artificial Neural Network Based Approach towards Rule Evolution

Authors: Nelvin Joseph, K. Krishna Milan Rao, Praveen Dwarakanath

Abstract:

The explosive growth of Smart phones around the world has led to the shift of the primary engagement tool for entertainment from traditional consoles and music players to an all integrated device. Augmented Reality is the next big shift in bringing in a new dimension to the play. The paper explores the construct and working of the community engine in Delta T – an Augmented Reality game that allows users to evolve rules in the game basis collective bargaining mirroring democracy even in a gaming world.

Keywords: augmented reality, artificial neural networks, mobile application, human computer interaction, community engine

Procedia PDF Downloads 299
2334 Applying Transformative Service Design to Develop Brand Community Service in Women, Children and Infants Retailing

Authors: Shian Wan, Yi-Chang Wang, Yu-Chien Lin

Abstract:

This research discussed the various theories of service design, the importance of service design methodology, and the development of transformative service design framework. In this study, transformative service design is applied while building a new brand community service for women, children and infants retailing business. The goal is to enhance the brand recognition and customer loyalty, effectively increase the brand community engagement by embedding the brand community in social network and ultimately, strengthen the impact and the value of the company brand.

Keywords: service design, transformative service design, brand community, innovation

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2333 Topological Analyses of Unstructured Peer to Peer Systems: A Survey

Authors: Hend Alrasheed

Abstract:

Due to their different properties that have led to avoid several limitations of classic client/server systems, there has been a great interest in the development and the improvement of different peer to peer systems. Understanding the properties of complex peer to peer networks is essential for their future improvements. It was shown that the performances of peer to peer protocols are directly related to their underlying topologies. Therefore, multiple efforts have analyzed the topologies of different peer to peer systems. This study presents an overview of major findings of close experimental analyses to different topologies of three unstructured peer to peer systems: BitTorrent, Gnutella, and FreeNet.

Keywords: peer to peer networks, network topology, graph diameter, clustering coefficient, small-world property, random graph, degree distribution

Procedia PDF Downloads 357
2332 Targeting Violent Extremist Narratives: Applying Network Targeting Techniques to the Communication Functions of Terrorist Groups

Authors: John Hardy

Abstract:

Over the last decade, the increasing utility of extremist narratives to the operational effectiveness of terrorist organizations has been evidenced by the proliferation of inspired or affiliated attacks across the world. Famous examples such as regional al-Qaeda affiliates and the self-styled “Islamic State” demonstrate the effectiveness of leveraging communication technologies to disseminate propaganda, recruit members, and orchestrate attacks. Terrorist organizations with the capacity to harness the communicative power offered by digital communication technologies and effective political narratives have held an advantage over their targets in recent years. Terrorists have leveraged the perceived legitimacy of grass-roots actors to appeal to a global audience of potential supporters and enemies alike, and have wielded a proficiency in profile-raising which remains unmatched by counter terrorism narratives around the world. In contrast, many attempts at propagating official counter-narratives have been received by target audiences as illegitimate, top-down and impersonally bureaucratic. However, the benefits provided by widespread communication and extremist narratives have come at an operational cost. Terrorist organizations now face a significant challenge in protecting their access to communications technologies and authority over the content they create and endorse. The dissemination of effective narratives has emerged as a core function of terrorist organizations with international reach via inspired or affiliated attacks. As such, it has become a critical function which can be targeted by intelligence and security forces. This study applies network targeting principles which have been used by coalition forces against a range of non-state actors in the Middle East and South Asia to the communicative function of terrorist organizations. This illustrates both a conceptual link between functional targeting and operational disruption in the abstract and a tangible impact on the operational effectiveness of terrorists by degrading communicative ability and legitimacy. Two case studies highlight the utility of applying functional targeting against terrorist organizations. The first case is the targeted killing of Anwar al-Awlaki, an al-Qaeda propagandist who crafted a permissive narrative and effective propaganda videos to attract recruits who committed inspired terrorist attacks in the US and overseas. The second is a series of operations against Islamic State propagandists in Syria, including the capture or deaths of a cadre of high profile Islamic State members, including Junaid Hussain, Abu Mohammad al-Adnani, Neil Prakash, and Rachid Kassim. The group of Islamic State propagandists were linked to a significant rise in affiliated and enabled terrorist attacks and were subsequently targeted by law enforcement and military agencies. In both cases, the disruption of communication between the terrorist organization and recruits degraded both communicative and operational functions. Effective functional targeting on member recruitment and operational tempo suggests that narratives are a critical function which can be leveraged against terrorist organizations. Further application of network targeting methods to terrorist narratives may enhance the efficacy of a range of counter terrorism techniques employed by security and intelligence agencies.

Keywords: countering violent extremism, counter terrorism, intelligence, terrorism, violent extremism

Procedia PDF Downloads 274