Search results for: resolution digital data

Authors: Qiming Zhang, Youda Ye, Qinxue Jiang

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Accurate prediction of external flowfield and aero-heating at the wall of hypersonic vehicle is very crucial for the design of aircrafts. Unstructured/hybrid meshes have more powerful advantages than structured meshes in terms of pre-processing, parallel computing and mesh adaptation, so it is imperative to develop high-resolution numerical methods for the calculation of aerothermal environment on unstructured/hybrid meshes. The inviscid flux scheme is one of the most important factors affecting the accuracy of unstructured/ hybrid mesh heat flux calculation. Here, a new hybrid flux scheme is developed and the approach of interface type selection is proposed: i.e. 1) using the exact Riemann scheme solution to calculate the flux on the faces parallel to the wall; 2) employing Sterger-Warming (S-W) scheme to improve the stability of the numerical scheme in other interfaces. The results of the heat flux fit the one observed experimentally and have little dependence on grids, which show great application prospect in unstructured/ hybrid mesh.

Keywords: aero-heating prediction, computational fluid dynamics, hybrid meshes, hybrid schemes

Procedia PDF Downloads 249

Authors: Sedat Bilgili, Alper K. Demir

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The current Internet has become the dominant use with continuing growth in the home, medical, health, smart cities and industrial automation applications. Internet of Things (IoT) is an emerging technology to enable such applications in our lives. Moreover, Named Data Networking (NDN) is also emerging as a Future Internet architecture where it fits the communication needs of IoT networks. The aim of this study is to provide an NDN protocol stack implementation running on the Contiki operating system (OS). Contiki OS is an OS that is developed for constrained IoT devices. In this study, an NDN protocol stack that can work on top of IEEE 802.15.4 link and physical layers have been developed and presented.

Keywords: internet of things (IoT), named-data, named data networking (NDN), operating system

Procedia PDF Downloads 171

Authors: Arūnas Gudinavičius, Vincas Grigas

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Purpose: The current study aims to identify and explore causes and consequences of unauthorized use of books from readers’, publishers’, and authors’ points of view. The case of Lithuania also assessed, especially historical background (banned alphabet, book smuggling, theft as the social norm in Soviet times) of the country. Design/methodology/approach: Aiming for more understanding why readers, authors and publishers are using or not using technology for unauthorized access of books, technology acceptance model approach was used, a total of 30 respondents (publishers, authors and readers) were interviewed in semi-structured face-to-face interviews and thematic analysis of collected qualitative data was conducted. Interviews were coded in English with coding software for further analysis. Findings: Findings indicate that the main cause for the unauthorized use of books is a lack of legal e-book titles and acquisition options. This mainly points at publishers, however, instead of using unauthorized sources as opportunities for author promotion or marketing, they rather concentrate on the causes of unauthorized use of books which they are not in control of, including access to unauthorized sources, habits, and economic causes. Some publishers believe that the lack of legal e-book titles is the consequence of unauthorized use of book rather than its cause. Originality: This research contributed to the body of knowledge by investigating unauthorized use of books from readers’, publishers’, and authors’ points of view which renders to have a better understanding of the causes and consequences of such behavior, as well as differences between these roles. We suggest that these causes lead to the intention to use and actual use of technology which is easier to use and which gives more perceived advantages – technology for unauthorized downloading and reading of books vs legal e-book acquisition options.

Keywords: digital piracy, unauthorized access, publishing industry, book reader, intellectual property rights

Procedia PDF Downloads 172

Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

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For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

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Authors: Radek Novotný, Martina Maněnová

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This article presents a summary of reviews on gender differences in perception of information and communication technology (ICT) by pupils in primary education. The article outlines the meaning of ICT in primary education then summarizes different studies of the use of ICT in primary education from the point of view of gender. The article also presents the specific differences of gender in the knowledge of modalities of use of specialized digital tools and the perception and value assigned to ICT, accordingly the article provides insight into the background of gender differences in performance in relation to ICT to determinate the complex meaning of pupils attitudes to the ICT.

Keywords: ICT in primary education, attitudes to ICT, gender differences, gender and ICT

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Authors: Soufiane Zerraf, Malika Tridane, Said Belaaouad

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CuHPO₃.2H₂O was synthesized by the direct method. CuHPO₃.2H₂O crystallizes in the orthorhombic system, space group P2₁2₁2₁, a = 6.7036 (2) Å, b = 7.3671 (4) Å, c = 8.9749 (4) Å, Z = 4, V = 443.24 (4) ų. The crystal structure was refined to R₁= 0.0154, R₂= 0.0380 for 19018 reflections satisfying criterion I ≥ 2σ (I). The structural resolution shows the existence of chains of ions HPO₃- linked together by hydrogen bonds. The crystalline structure is formed by chains consisting of Cu[O₃(H₂O)₃] deformed octahedral, which are connected to the vertices. The chains extend parallel to b and are mutually linked by PO₃ groups. The structure is closely related to that of CuSeO₃.2H₂O and CuTeO₃.2H₂O. The experimental studies of the infrared and Raman spectra were used to confirm the presence of the phosphate ion and were compared in the (0-4000) cm-1 region with the theoretical results calculated by the density functional theory (DFT) method to provide reliable assignments of all observed bands in the experimental spectra.

Keywords: crystal structure, X-ray diffraction, vibration study, thermal behavior, density functional theory

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Authors: D. van der Merwe

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Despite unprecedented changes in the media formats, typologies, delivery channels, and content that can be seen between Walter Benjamin’s writings from the era of modernity and those observable in the contemporary era of metamodernity, parallels can be drawn between the media effects experienced by audiences across the temporal divide. This paper will explore alignments between these two eras as evidenced by various media effects. First, convergence in the historical paradigm of film will be compared with the same effect as seen within the digital domain. Second, the uses and gratifications theory will be explored to delineate parallels in terms of user behaviours across both eras, regardless of medium. Third, cultivation theory and its role in manipulation via the media in both modernity and metamodernity will be discussed. Lastly, similarities between the archetypal personae populating each era will be unpacked.

Keywords: convergence, cultivation theory, media effects, metamodernity, uses and gratifications theory

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Authors: Nick Papanikolaou

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In modern world politics, International relations are very complex not only in their construction but also in their interpretation the ex-Yugoslavian(western Balkans) countries, due to the establishment of independent states, have also risen pending geopolitical and territorial issues such as the Kosovo dispute widely known as an active frozen conflict. Science of anthropology and its subfield of anthropology of conflict can suggest a sustainable plan of communities coexistence and abolishment of fondamentalism. The 1244 Security Council Resolution provides a framework of implementation of a transitional international joint international armed presence for ensuring control and stability in the territory. The changing international relations landscape and the rise of the integration of the Western Balkans in the European Union have brought the question of Kosovo and all the till now internationally controlled system of governance to a dead end. A new solution that will ensure a sustainable future needs to be applied in order to solve this case in a way that rights of both albanians and Serbians will be equally respected and both populations will coexist peacefully. What this presentation aims for is to present a plan for the peaceful coexistence and sovreignty of habitants of Kosovo in a whole new way of governance.

Keywords: sovereignty, Kosovo, Western Balkans, anthropology of conflict

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Authors: Alissa Lefebre

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It might seem intuitive to hope for a fast decision on the patent grant. After all, a granted patent provides you with a monopoly position, which allows you to obstruct others from using your technology. However, this does not take into account the strategic advantages one can obtain from keeping their patent applications pending. First, you have the financial advantage of postponing certain fees, although many applicants would probably agree that this is not the main benefit. As the scope of the patent protection is only decided upon at the grant, the pendency period introduces uncertainty amongst rivals. This uncertainty entails not knowing whether the patent will actually get granted and what the scope of protection will be. Consequently, rivals can only depend upon limited and uncertain information when deciding what technology is worth pursuing. One way to keep patent applications pending, is the use of divisional applications. These applicants can be filed out of a parent application as long as that parent application is still pending. This allows the applicant to pursue (part of) the content of the parent application in another application, as the divisional application cannot exceed the scope of the parent application. In a fast-moving and complex market such as the tele- and digital communications, it might allow applicants to obtain an actual monopoly position as competitors are discouraged to pursue a certain technology. Nevertheless, this practice also has downsides to it. First of all, it has an impact on the workload of the examiners at the patent office. As the number of patent filings have been increasing over the last decades, using strategies that increase this number even more, is not desirable from the patent examiners point of view. Secondly, a pending patent does not provide you with the protection of a granted patent, thus not only create uncertainty for the rivals, but also for the applicant. Consequently, the European patent office (EPO) has come up with a “raising the bar initiative” in which they have decided to tackle the strategic use of divisional applications. Over the past years, two rules have been implemented. The first rule in 2010 introduced a time limit, upon which divisional applications could only be filed within a 24-month limit after the first communication with the patent office. However, after carrying-out a user feedback survey, the EPO abolished the rule again in 2014 and replaced it by a fee mechanism. The fee mechanism is still in place today, which might be an indication of a better result compared to the first rule change. This study tests the impact of these rules on the strategic use of divisional applications in the tele- and digital communication industry and provides empirical evidence on their success. Upon using three different survival models, we find overall evidence that divisional applications prolong the pendency time and that only the second rule is able to tackle the strategic patenting and thus decrease the pendency time.

Keywords: divisional applications, regulatory changes, strategic patenting, EPO

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Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

Procedia PDF Downloads 286

Authors: Andrea Ando

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The development of the blockchain has been a major innovation in the technology field. It opened the door to the creation of novel cyberassets and currencies. In more recent times, the non-fungible tokens have started to be at the centre of media attention. Their popularity has been increasing since 2021, and they represent the latest in the world of distributed ledger technologies and cryptocurrencies. It seems more and more likely that NFTs will play a more important role in our online interactions. They are indeed increasingly taking part in the arts and technology sectors. Their impact on society and the market is still very difficult to define, but it is very likely that there will be a turning point in the world of digital assets. There are some examples of their peculiar behaviour and effect in our contemporary tech-market: the former CEO of the famous social media site Twitter sold an NFT of his first tweet for around £2,1 million ($2,5 million), or the National Basketball Association has created a platform to sale unique moment and memorabilia from the history of basketball through the non-fungible token technology. Their growth, as imaginable, paved the way for civil disputes, mostly regarding their position under the current intellectual property law in each jurisdiction. In April 2022, the High Court of England and Wales ruled in the OpenSea case that non-fungible tokens can be considered properties. The judge, indeed, concluded that the cryptoasset had all the indicia of property under common law (National Provincial Bank v. Ainsworth). The research has demonstrated that the ruling of the High Court is not providing enough answers to the dilemma of whether minting an NFT is a violation or not of intellectual property and/or property rights. Indeed, if, on the one hand, the technology follows the framework set by the case law (e.g., the 4 criteria of Ainsworth), on the other hand, the question that arises is what is effectively protected and owned by both the creator and the purchaser. Then the question that arises is whether a person has ownership of the cryptographed code, that it is indeed definable, identifiable, intangible, distinct, and has a degree of permanence, or what is attached to this block-chain, hence even a physical object or piece of art. Indeed, a simple code would not have any financial importance if it were not attached to something that is widely recognised as valuable. This was demonstrated first through the analysis of the expectations of intellectual property law. Then, after having laid the foundation, the paper examined the OpenSea case, and finally, it analysed whether the expectations were met or not.

Keywords: technology, technology law, digital law, cryptoassets, NFTs, NFT, property law, intellectual property law, copyright law

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Authors: Burçin Saltık, Levent Genç

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In this study, it was aimed to determine a route for identification of rice cultivation areas within Thrace and Marmara regions of Turkey using remote sensing and GIS. Landsat 8 (OLI-TIRS) imageries acquired in production season of 2013 with 181/32 Path/Row number were used. Four different seasonal images were generated utilizing original bands and different transformation techniques. All images were classified individually using supervised classification techniques and Land Use Land Cover Maps (LULC) were generated with 8 classes. Areas (ha, %) of each classes were calculated. In addition, district-based rice distribution maps were developed and results of these maps were compared with Turkish Statistical Institute (TurkSTAT; TSI)’s actual rice cultivation area records. Accuracy assessments were conducted, and most accurate map was selected depending on accuracy assessment and coherency with TSI results. Additionally, rice areas on over 4° slope values were considered as mis-classified pixels and they eliminated using slope map and GIS tools. Finally, randomized rice zones were selected to obtain maximum-minimum value ranges of each date (May, June, July, August, September images separately) NDVI, LSWI, and LST images to test whether they may be used for rice area determination via raster calculator tool of ArcGIS. The most accurate classification for rice determination was obtained from seasonal LSWI LULC map, and considering TSI data and accuracy assessment results and mis-classified pixels were eliminated from this map. According to results, 83151.5 ha of rice areas exist within study area. However, this result is higher than TSI records with an area of 12702.3 ha. Use of maximum-minimum range of rice area NDVI, LSWI, and LST was tested in Meric district. It was seen that using the value ranges obtained from July imagery, gave the closest results to TSI records, and the difference was only 206.4 ha. This difference is normal due to relatively low resolution of images. Thus, employment of images with higher spectral, spatial, temporal and radiometric resolutions may provide more reliable results.

Keywords: landsat 8 (OLI-TIRS), LST, LSWI, LULC, NDVI, rice

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Authors: Ying Ying Liu, Austin Cooke, Parimala Thulasiraman

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Internet of Things (IoT) has attracted a recent spark in research on Internet of Vehicles (IoV). In this paper, we focus on one research area in IoV: preserving location privacy of vehicle data. We discuss existing location privacy preserving techniques and provide a scheme for evaluating these techniques under IoV traffic condition. We propose a different strategy in applying Differential Privacy using k-d tree data structure to preserve location privacy and experiment on real world Gowalla data set. We show that our strategy produces differentially private data, good preservation of utility by achieving similar regression accuracy to the original dataset on an LSTM (Long Term Short Term Memory) neural network traffic predictor.

Keywords: differential privacy, internet of things, internet of vehicles, location privacy, privacy preservation scheme

Procedia PDF Downloads 179

Authors: Carlo Bianchini, Lorenzo Catena

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The appearance of 3D scanners and then, more recently, of image-based systems that generate point clouds directly from common digital images have deeply affected the survey process in terms of both capturing and 2D/3D modelling. In this context, low cost and mobile systems are increasingly playing a key role and actually paving the way to the democratization of what in the past was the realm of few specialized technicians and expensive equipment. The application of Google Tango on the ancient church of Santa Maria delle Vigne in Pratica di Mare – Rome presented in this paper is one of these examples.

Keywords: the architectural survey, augmented/mixed/virtual reality, Google Tango project, image-based 3D capturing

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Authors: Sakshi Bhalla

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On the one hand, given their seemingly simplistic, near universal usage and understanding, emoji are discarded as a potential step back in the evolution of communication. On the other, their effectiveness, pervasiveness, and adaptability across and within contexts are undeniable. In this study, the responses of 40 people (categorized by age) were recorded based on a uniform two-part questionnaire where they were required to a) identify the meaning of 15 emoji when placed in isolation, and b) interpret the meaning of the same 15 emoji when placed in a context-defining posting on Twitter. Their responses were studied on the basis of deviation from their responses that identified the emoji in isolation, as well as the originally intended meaning ascribed to the emoji. Based on an analysis of these results, it was discovered that each of the five age categories uses, understands and perceives emoji differently, which could be attributed to the degree of exposure they have undergone. For example, in the case of the youngest category (aged < 20), it was observed that they were the least accurate at correctly identifying emoji in isolation (~55%). Further, their proclivity to change their response with respect to the context was also the least (~31%). However, an analysis of each of their individual responses showed that these first-borns of social media seem to have reached a point where emojis no longer inspire their most literal meanings to them. The meaning and implication of these emoji have evolved to imply their context-derived meanings, even when placed in isolation. These trends carry forward meaningfully for the other four groups as well. In the case of the oldest category (aged > 35), however, the trends indicated inaccuracy and therefore, a higher incidence of a proclivity to change their responses. When studied in a continuum, the responses indicate that slowly and steadily, emoji are evolving from pictograms to ideograms. That is to suggest that they do not just indicate a one-to-one relation between a singular form and singular meaning. In fact, they communicate increasingly complicated ideas. This is much like the evolution of ancient hieroglyphics on papyrus reed or cuneiform on Sumerian clay tablets, which evolved from simple pictograms to progressively more complex ideograms. This evolution within communication is parallel to and contingent on the simultaneous evolution of communication. What’s astounding is the capacity of humans to leverage different platforms to facilitate such changes. Twiterese, as it is now called, is one of the instances where language is adapting to the demands of the digital world. That it does not have a spoken component, an ostensible grammar, and lacks standardization of use and meaning, as some might suggest, may seem like impediments in qualifying it as the 'language' of the digital world. However, that kind of a declarative remains a function of time, and time alone.

Keywords: communication, emoji, language, Twitter

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Authors: Yuhanis Yusof, Zuriani Mustaffa, Siti Sakira Kamaruddin

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Data mining is a fundamental technique in identifying patterns from large data sets. The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical. Prior to that, data are consolidated so that the resulting mining process may be more efficient. This study investigates the effect of different data normalization techniques, which are Min-max, Z-score, and decimal scaling, on Swarm-based forecasting models. Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC). Forecasting models are later developed to predict the daily spot price of crude oil and gasoline. Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max. Nevertheless, the GWO is more superior that ABC as its model generates the highest accuracy for both crude oil and gasoline price. Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.

Keywords: artificial bee colony, data normalization, forecasting, Grey Wolf optimizer

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Authors: Anuta Mukherjee, Saswati Mukherjee

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Data is growing everyday. Social networking sites such as Twitter are becoming an integral part of our daily lives, contributing a large increase in the growth of data. It is a rich source especially for sentiment detection or mining since people often express honest opinion through tweets. However, although sentiment analysis is a well-researched topic in text, this analysis using Twitter data poses additional challenges since these are unstructured data with abbreviations and without a strict grammatical correctness. We have employed collision theory to achieve sentiment analysis in Twitter data. We have also incorporated discourse analysis in the collision theory based model to detect accurate sentiment from tweets. We have also used the retweet field to assign weights to certain tweets and obtained the overall weightage of a topic provided in the form of a query. Hadoop has been exploited for speed. Our experiments show effective results.

Keywords: sentiment analysis, twitter, collision theory, discourse analysis

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Authors: V. V. Fomin, A. P. Mikhailovich, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Ground-level landscape photos can be used as a source of objective data on woody vegetation and vegetation dynamics. We proposed a method for processing, analyzing, and presenting ground photographs, which has the following advantages: 1) researcher has to form holistic representation of the study area in form of a set of interlapping ground-level landscape photographs; 2) it is necessary to define or obtain characteristics of the landscape, objects, and phenomena present on the photographs; 3) it is necessary to create new or supplement existing textual descriptions and annotations for the ground-level landscape photographs; 4) single or multiple ground-level landscape photographs can be used to develop specialized geoinformation layers, schematic maps or thematic maps; 5) it is necessary to determine quantitative data that describes both images as a whole, and displayed objects and phenomena, using algorithms for automated image analysis. It is suggested to match each photo with a polygonal geoinformation layer, which is a sector consisting of areas corresponding with parts of the landscape visible in the photos. Calculation of visibility areas is performed in a geoinformation system within a sector using a digital model of a study area relief and visibility analysis functions. Superposition of the visibility sectors corresponding with various camera viewpoints allows matching landscape photos with each other to create a complete and wholesome representation of the space in question. It is suggested to user-defined data or phenomenons on the images with the following superposition over the visibility sector in the form of map symbols. The technology of geoinformation layers’ spatial superposition over the visibility sector creates opportunities for image geotagging using quantitative data obtained from raster or vector layers within the sector with the ability to generate annotations in natural language. The proposed method has proven itself well for relatively open and clearly visible areas with well-defined relief, for example, in mountainous areas in the treeline ecotone. When the polygonal layers of visibility sectors for a large number of different points of photography are topologically superimposed, a layer of visibility of sections of the entire study area is formed, which is displayed in the photographs. Also, as a result of this overlapping of sectors, areas that did not appear in the photo will be assessed as gaps. According to the results of this procedure, it becomes possible to obtain information about the photos that display a specific area and from which points of photography it is visible. This information may be obtained either as a query on the map or as a query for the attribute table of the layer. The method was tested using repeated photos taken from forty camera viewpoints located on Ray-Iz mountain massif (Polar Urals, Russia) from 1960 until 2023. It has been successfully used in combination with other ground-based and remote sensing methods of studying the climate-driven dynamics of woody vegetation in the Polar Urals. Acknowledgment: This research was collaboratively funded by the Russian Ministry for Science and Education project No. FEUG-2023-0002 (image representation) and Russian Science Foundation project No. 24-24-00235 (automated textual description).

Keywords: woody, vegetation, repeated, photographs

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Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics

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Authors: Hau-Wei Lee, Yu-Chi Liu, Chien-Hung Liu

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A mathematical model is presented for a system that measures rotational errors in a shaft using a ball lens. The geometric optical characteristics of the ball lens mounted on the shaft allows the measurement of rotation axis errors in both the radial and axial directions. The equipment used includes two quadrant detectors (QD), two laser diodes and a ball lens that is mounted on the rotating shaft to be evaluated. Rotational errors in the shaft cause changes in the optical geometry of the ball lens. The resulting deflection of the laser beams is detected by the QDs and their output signals are used to determine rotational errors. The radial and the axial rotational errors can be calculated as explained by the mathematical model. Results from system calibration show that the measurement error is within ±1 m and resolution is about 20 nm. Using a direct drive motor (DD motor) as an example, experimental results show a rotational error of less than 20 m. The most important features of this system are that it does not require the use of expensive optical components, it is small, very easy to set up, and measurements are highly accurate.

Keywords: ball lens, quadrant detector, axial error, radial error

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Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

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This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

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Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

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Authors: Adel M. Qatawneh

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This paper aimed to determine the importance of knowledge innovation for external audit on anti-corruption in the entire Jordanian bank companies are listed in Amman Stock Exchange (ASE). The study importance arises from the need to recognize the Knowledge innovation for external audit and anti-corruption as the development in the world of business, the variables that will be affected by external audit innovation are: reliability of financial data, relevantly of financial data, consistency of the financial data, Full disclosure of financial data and protecting the rights of investors to achieve the objectives of the study a questionnaire was designed and distributed to the society of the Jordanian bank are listed in Amman Stock Exchange. The data analysis found out that the banks in Jordan have a positive importance of Knowledge innovation for external audit on anti-corruption. They agree on the benefit of Knowledge innovation for external audit on anti-corruption. The statistical analysis showed that Knowledge innovation for external audit had a positive impact on the anti-corruption and that external audit has a significantly statistical relationship with anti-corruption, reliability of financial data, consistency of the financial data, a full disclosure of financial data and protecting the rights of investors.

Keywords: knowledge innovation, external audit, anti-corruption, Amman Stock Exchange

Procedia PDF Downloads 465

Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

Abstract:

New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: information visualization, visual analytics, text mining, visual text analytics tools, big data visualization

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

Abstract:

Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Bekkem Chakradhar Reddy, Y. Soni Priya, Mathivanan G., L. K. Joshila Grace, N. Srinivasan, Asha P.

Abstract:

Currently, there are a lot of problems related to marking attendance in schools, offices, or other places. Organizations tasked with collecting daily attendance data have numerous concerns. There are different ways to mark attendance. The most commonly used method is collecting data manually by calling each student. It is a longer process and problematic. Now, there are a lot of new technologies that help to mark attendance automatically. It reduces work and records the data. We have proposed to implement attendance marking using the latest technologies. We have implemented a system based on face identification and analyzing faces. The project is developed by gathering faces and analyzing data, using deep learning algorithms to recognize faces effectively. The data is recorded and forwarded to the host through mail. The project was implemented in Python and Python libraries used are CV2, Face Recognition, and Smtplib.

Keywords: python, deep learning, face recognition, CV2, smtplib, Dlib.

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Authors: Toni Raurich-Marcet, Joan Llonch-Andreu

Abstract:

This research is focused on the relationship between Search Engine Marketing (SEM) and traditional advertising. The dominant assumption is that SEM does not help brand awareness and only does it in session as if it were the cost of manufacturing the product being sold. The study is methodologically developed using an experiment where the effects were determined to analyze the billboard effect. The research allowed the cross-linking of theoretical and empirical knowledge on digital marketing. This paper has validated this marketing generates retention as traditional advertising would by measuring brand awareness and its improvements. This changes the way performance and brand campaigns are split within marketing departments, effectively rebalancing budgets moving forward.

Keywords: attribution, performance marketing, SEM, marketplaces

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Authors: Nizar Karim Uribe-Orihuela, Fernando Brambila-Paz, Ivette Caldelas, Rodrigo Montufar-Chaveznava

Abstract:

In this paper, we present the advances corresponding to the implementation of a strategy to visualize geographical data using a Software Development Kit (SDK) for video games. We use multispectral images from Landsat 7 platform and Laser Imaging Detection and Ranging (LIDAR) data from The National Institute of Geography and Statistics of Mexican (INEGI). We select a place of interest to visualize from Landsat platform and make some processing to the image (rotations, atmospheric correction and enhancement). The resulting image will be our gray scale color-map to fusion with the LIDAR data, which was selected using the same coordinates than in Landsat. The LIDAR data is translated to 8-bit raw data. Both images are fused in a software developed using Unity (an SDK employed for video games). The resulting image is then displayed and can be explored moving around. The idea is the software could be used for students of geology and geophysics at the Engineering School of the National University of Mexico. They will download the software and images corresponding to a geological place of interest to a smartphone and could virtually visit and explore the site with a virtual reality visor such as Google cardboard.

Keywords: virtual reality, interactive technologies, geographical data visualization, video games technologies, educational material

Procedia PDF Downloads 246

Authors: Chad Brown

Abstract:

This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

Procedia PDF Downloads 41