Search results for: digital image receptor

Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

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Authors: Chen Zhang; Qiang Wang

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With the rapid development of the new generation of digital technology, various industries have created more and more value by using digital technology, accelerating the digital transformation of various industries. The economic form of human society has evolved with the progress of technology, and in this context, the power conversion, transformation and upgrading of the manufacturing industry in terms of quality, efficiency and energy change has become a top priority. Based on the digitalization background, this paper analyzes the transformation and upgrading efficiency of the manufacturing industry and evaluates the impact of the driving factors, which have very important theoretical and practical significance. This paper utilizes qualitative research methods, entropy methods, data envelopment analysis methods and econometric models to explore the transformation and upgrading efficiency of manufacturing enterprises and driving factors. The study shows that the transformation and upgrading efficiency of the manufacturing industry shows a steady increase, and regions rich in natural resources and social resources provide certain resources for transformation and upgrading. The ability of scientific and technological innovation has been improved, but there is still much room for progress in the transformation of scientific and technological innovation achievements. Most manufacturing industries pay more attention to green manufacturing and sustainable development. In addition, based on the existing problems, this paper puts forward suggestions for improving infrastructure construction, developing the technological innovation capacity of enterprises, green production and sustainable development.

Keywords: digitization, manufacturing firms, transformation and upgrading, efficiency, driving factors

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: Nurit Carmi

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There are many endangered species that are not popular but whose conservation is, nonetheless, important. The present study deals with sharks who suffer from demonization and, accordingly, from public indifference to the deteriorating state of their conservation. We used the seasonal appearance of sharks in the Israeli coastal zone to study public perceptions and attitudes towards sharks prior to ("control group") and after ("visitors") shark watching during a visit in an information center. We found that shark’s image was significantly more positive among the "visitors" compared to the control group. We found that visiting in the information center was strongly related to a more positive shark image, attitudes toward shark conservation, and willingness to act to preserve them.

Keywords: wildlife tourism, shark conservation, attitudes towards animals, human-animal relationships, Smith's salience index

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Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

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Authors: Doriane Micaela Andeme Bikoro, Samuel Fosso Wamba, Jean Robert Kala Kamdjoug

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Currently one of the leading fields in the market of technological innovation is digital health. In developed countries, this booming innovation is experiencing an exponential speed. We understand that in developed countries, e-health could also revolutionize the practice of medicine and therefore fill the many failures observed in medical care. Everything leads to believe that future technology is oriented towards the medical sector. The aim of this work is to explore at the same time the technological resources and the potential of health care based on new technologies; it is a case study in a rural area of Southern Cameroon. Among other things, we will make a census of the shortcomings and problems encountered, and we will propose various appropriate solutions. The work methodology used here is essentially qualitative. We used two qualitative data collection techniques, direct observation, and interviews. In fact, we spent two weeks in the field observing and conducting some semi-directive interviews with some of those responsible for these health structures. This study was conducted in three health facilities in the south of the country; including two health centers and a rural hospital. Many technological failures have been identified in the day-to-day management of these health facilities and especially in the administration of health care to patients. We note major problems such as the digital divide, the lack of qualified personnel, the state of isolation of this area. This is why various proposals are made to improve the health sector in Cameroon both technologically and medically.

Keywords: Cameroon, capacities, census, digital health, qualitative method, rural area

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Authors: Anil Kumar Pandey

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Power plane noise is the most significant source of signal integrity (SI) issues in a high-speed digital design. In this paper, power integrity (PI) analysis of multiple power planes in a power delivery system of a 12-layer high-speed FPGA board is presented. All 10 power planes of HSD board are analyzed separately by using 3D Electromagnetic based PI solver, then the transient simulation is performed on combined PI data of all planes along with voltage regulator modules (VRMs) and 70 current drawing chips to get the board level power noise coupling on different high-speed signals. De-coupling capacitors are placed between power planes and ground to reduce power noise coupling with signals.

Keywords: power integrity, power-aware signal integrity analysis, electromagnetic simulation, channel simulation

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Authors: Armin Bodaghkhani, Bruce Colbourne, Yuri S. Muzychka

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The process of spray-cloud formation and flow kinematics produced from breaking wave impact on vertical and slant lab-scale bow-shaped models were experimentally investigated. Bubble Image Velocimetry (BIV) and Image Processing (IP) techniques were applied to study the various types of wave-model impacts. Different wave characteristics were generated in a tow tank to investigate the effects of wave characteristics, such as wave phase velocity, wave steepness on droplet velocities, and behavior of the process of spray cloud formation. The phase ensemble-averaged vertical velocity and turbulent intensity were computed. A high-speed camera and diffused LED backlights were utilized to capture images for further post processing. Various pressure sensors and capacitive wave probes were used to measure the wave impact pressure and the free surface profile at different locations of the model and wave-tank, respectively. Droplet sizes and velocities were measured using BIV and IP techniques to trace bubbles and droplets in order to measure their velocities and sizes by correlating the texture in these images. The impact pressure and droplet size distributions were compared to several previously experimental models, and satisfactory agreements were achieved. The distribution of droplets in front of both models are demonstrated. Due to the highly transient process of spray formation, the drag coefficient for several stages of this transient displacement for various droplet size ranges and different Reynolds number were calculated based on the ensemble average method. From the experimental results, the slant model produces less spray in comparison with the vertical model, and the droplet velocities generated from the wave impact with the slant model have a lower velocity as compared with the vertical model.

Keywords: spray charachteristics, droplet size and velocity, wave-body interactions, bubble image velocimetry, image processing

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Authors: Taus Muganda

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This research explores the intricate relationship between e-procurement adoption and effective service delivery in the Uganda Coffee Industry, focusing on the processes involved, key actors, and the impact of digital transformation. The study is guided by three prominent theories, Actor-Network Theory, Resource-Based View Theory, and Institutional Theory to comprehensively explore the dynamics of e-procurement in the context of the coffee sector. The primary aim of this project is to examine the e-procurement adoption process and its role in enhancing service delivery within the Uganda Coffee Industry. The research questions guiding this inquiry are: firstly, whether e-procurement adoption and implementation contribute to achieving quality service delivery; and secondly, how e-procurement adoption can be effectively realized within the Uganda Coffee Industry. To address these questions, the study has laid out specific objectives. Firstly, it seeks to investigate the impact of e-procurement on effective service delivery, analysing how the integration of digital processes influences the overall quality of services provided in the coffee industry. Secondly, it aims to critically analyse the measures required to achieve effective delivery outcomes through the adoption and implementation of e-procurement, assessing the strategies that can maximize the benefits of digital transformation. Furthermore, the research endeavours to identify and examine the key actor’s instrumental in achieving effective service delivery within the Uganda Coffee Industry. By utilizing Actor-Network Theory, the study will elucidate the network of relationships and collaborations among actors involved in the e-procurement process. The research contributes to addressing a critical gap in the sector. Despite coffee being the leading export crop in Uganda, constituting 16% of total exports, there is a recognized need for digital transformation, specifically in the realm of e-procurement, to enhance the productivity of producers and contribute to the economic growth of the country. The study aims to provide insights into transforming the Uganda Coffee Industry by focusing on improving the e-procurement services delivered to actors in the coffee sector. The three forms of e-procurement investigated in this research—E-Sourcing, E-Payment, and E-Invoicing—serve as focal points in understanding the multifaceted dimensions of digital integration within the Uganda Coffee Industry. This research endeavours to offer practical recommendations for policymakers, industry stakeholders, and the UCDA to strategically leverage e-procurement for the benefit of the entire coffee value chain.

Keywords: e-procurement, effective service delivery, actors, actor-network theory, resource-based view theory, institutional theory, e-invocing, e-payment, e-sourcing

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Authors: Paul Koffitse Agobia

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In 2020 the Ministry of Education in Ghana and the National Council for Curriculum and Assessment (NaCCA) rolled out a new curriculum, Common Core Programme (CCP) for Basic 7 to 10, that lays emphasis on character building and values which are important to the Ghanaian society by providing education that will produce character–minded learners, with problem solving skills, who can play active roles in dealing with the increasing challenges facing Ghana and the global society. Therefore, learning and teaching approaches that prioritise the use of digital learning resources and active learning are recommended. The new challenge facing Ghanaian teachers is the ability to use new technologies together with the appropriate content pedagogical knowledge to help learners develop, aside the communication skills in French, the essential 21st century skills as recommended in the new curriculum. This article focusses on the pedagogical approaches that are recommended by NaCCA. The study seeks to examine French language teachers’ understanding of the recommended pedagogical approaches and how they use digital learning resources in class to foster the development of these essential skills and values. 54 respondents, comprised 30 teachers and 24 head teachers, were selected in 6 Junior High schools in rural districts (both private and public) and 6 from Junior High schools in an urban setting. The schools were selected in three regions: Volta, Central and Western regions. A class observation checklist and an interview guide were used to collect data for the study. The study reveals that some teachers adopt teaching techniques that do not promote active learning. They demonstrate little understanding of the core competences and values, therefore, fail to integrate them in their lessons. However, some other teachers, despite their lack of understanding of learning and teaching philosophies, adopted techniques that can help learners develop some of the core competences and values. In most schools, digital learning resources are not utilized, though teachers have smartphones or laptops.

Keywords: active learning, core competences, digital learning resources, pedagogical approach, values.

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Authors: Maulik Parmar, Sumeet Sandhu

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The online fashion industry experiences high product return rates. Many returns are because of size/fit mismatches -the size scale on labels can vary across brands, the size parameters may not capture all fit measurements, or the product may have manufacturing defects. Warehouse quality check of garment sizes can be semi-automated to improve speed and accuracy. This paper presents an approach for automatically measuring garment sizes from a single image of the garment -using Deep Learning to learn garment keypoints. The paper focuses on the waist size measurement of jeans and can be easily extended to other garment types and measurements. Experimental results show that this approach can greatly improve the speed and accuracy of today’s manual measurement process.

Keywords: convolutional neural networks, deep learning, distortion, garment measurements, image warping, keypoints

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Authors: Salim H. Al Salmani, Kevin Tansey, Mohammed S. Ozigis

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The study of the growth of built-up areas and settlement expansion is a major exercise that city managers seek to undertake to establish previous and current developmental trends. This is to ensure that there is an equal match of settlement expansion needs to the appropriate levels of services and infrastructure required. This research aims at demonstrating the potential of satellite image processing technique, harnessing the utility of single feature probability-object based image analysis technique in assessing the urban growth dynamics of the Muscat Governorate in Oman for the period 1990, 2002 and 2013. This need is fueled by the continuous expansion of the Muscat Governorate beyond predicted levels of infrastructural provision. Landsat Images of the years 1990, 2002 and 2013 were downloaded and preprocessed to forestall appropriate radiometric and geometric standards. A novel approach of probability filtering of the target feature segment was implemented to derive the spatial extent of the final Built-Up Area of the Muscat governorate for the three years period. This however proved to be a useful technique as high accuracy assessment results of 55%, 70%, and 71% were recorded for the Urban Landcover of 1990, 2002 and 2013 respectively. Furthermore, the Normalized Differential Built – Up Index for the various images were derived and used to consolidate the results of the SFP-OBIA through a linear regression model and visual comparison. The result obtained showed various hotspots where urbanization have sporadically taken place. Specifically, settlement in the districts (Wilayat) of AL-Amarat, Muscat, and Qurayyat experienced tremendous change between 1990 and 2002, while the districts (Wilayat) of AL-Seeb, Bawshar, and Muttrah experienced more sporadic changes between 2002 and 2013.

Keywords: urban growth, single feature probability, object based image analysis, landcover change

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Authors: Kohei Shimasaki, Tomoaki Okamura, Idaku Ishii

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We propose a vibration imaging method for high frame rate (HFR)-video-based localization of vibrating objects with large translations. When the ratio of the translation speed of a target to its vibration frequency is large, obtaining its frequency response in image intensities becomes difficult because one or no waves are observable at the same pixel. Our method can precisely localize moving objects with vibration by virtually translating multiple image sequences for pixel-level short-time Fourier transform to observe multiple waves at the same pixel. The effectiveness of the proposed method is demonstrated by analyzing several HFR videos of flying insects in real scenarios.

Keywords: HFR video analysis, pixel-level vibration source localization, short-time Fourier transform, virtual translation

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Authors: Chen Jin

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This topic seeks to re-examine the New Women Incident in 1935 Shanghai from the perspective of the influence of leftist cinematic aesthetics on public discourse in 1930s Shanghai. Accordingly, an original means of interpreting the death of Ruan Lingyu will be provided. On 8th March 1935, Ruan Lingyu, the queen of Chinese silent film, committed suicide through overdosing on sleeping tablets. Her last words, ‘gossip is fearful thing’, interlinks her destiny with the protagonist she played in the film The New Women (Cai Chusheng, 1935). The coincidence was constantly questioned by the masses following her suicide, constituting the enduring question: ‘who killed Ruan Lingyu?’ Responding to this query, previous scholars primarily analyze the characters played by women -particularly new women as part of the leftist movement or public discourse of 1930s Shanghai- as a means of approaching the truth. Nevertheless, alongside her status as a public celebrity, Ruan Lingyu also plays as a screen image of mechanical reproduction. The overlap between her screen image and personal destiny attracts limited academic focus in terms of the effect and implications of leftist aesthetics of reality in relation to her death, which itself has provided impetus to this research. With the reconfiguration of early Chinese film theory in the 1980s, early discourses on the relationship between cinematic reality and consciousness proposed by Hou Yao and Gu Kenfu in the 1920s are integrated into the category of Chinese film ontology, which constitutes a transcultural contrast with the Euro-American ontology that advocates the representation of reality. The discussion of Hou and Gu overlaps cinematic reality with effect, which emphasizes the empathy of cinema that is directly reflected in the leftist aesthetics of the 1930s. As the main purpose of leftist cinema is to encourage revolution through depicting social reality truly, Ruan Lingyu became renowned for her natural and realistic acting proficiency, playing leading roles in several esteemed leftist films. The realistic reproduction and natural acting skill together constitute the empathy of leftist films, which establishes a dialogue with the virtuous female image within the 1930s public discourse. On this basis, this research considers Chinese cinematic ontology and affect theory as the theoretical foundation for investigating the relationship between the screen image of Ruan Lingyu reproduced by the leftist film The New Women and the female image in the 1930s public discourse. Through contextualizing Ruan Lingyu’s death within the Chinese leftist movement, the essay indicates that the empathy embodied within leftist cinematic reality limits viewers’ cognition of the actress, who project their sentiments for the perfect screen image on to Ruan Lingyu’s image in reality. Essentially, Ruan Lingyu is imprisoned in her own perfect replication. Consequently, this article states that alongside leftist anti-female consciousness, the leftist aesthetics of reality restricts women in a passive position within public discourse, which ultimately plays a role in facilitating the death of Ruan Lingyu.

Keywords: cinematic reality, leftist aesthetics, Ruan Lingyu, The New Women

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Authors: Ahmed Abdel Sattar Khalil, Hazem Omar

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Background: Image-guided hepatic interventions are integral to the management of infective and neoplastic liver lesions. Over the past decades, 2D ultrasound was used for guidance of hepatic interventions; with the recent advances in ultrasound technology, 3D ultrasound was used to guide hepatic interventions. The aim of this study was to illustrate the added value of 3D image guided hepatic interventions by x matrix technology. Patients and Methods: This prospective study was performed on 100 patients who were divided into two groups; group A included 50 patients who were managed by 2D ultrasonography probe guidance, and group B included 50 patients who were managed by 3D X matrix ultrasonography probe guidance. Thermal ablation was done for 70 patients, 40 RFA (20 by the 2D probe and 20 by the 3D x matrix probe), and 30 MWA (15 by the 2D probe and 15 by the 3D x matrix probe). Chemical ablation (PEI) was done on 20 patients (10 by the 2D probe and 10 by the 3D x matrix probe). Drainage of hepatic collections and biopsy from undiagnosed hepatic focal lesions was done on 10 patients (5 by the 2D probe and 5 by the 3D x matrix probe). Results: The efficacy of ultrasonography-guided hepatic interventions by 3D x matrix probe was higher than the 2D probe but not significantly higher, with a p-value of 0.705, 0.5428 for RFA, MWA respectively, 0.5312 for PEI, 0.2918 for drainage of hepatic collections and biopsy. The complications related to the use of the 3D X matrix probe were significantly lower than the 2D probe, with a p-value of 0.003. The timing of the procedure was shorter by the usage of 3D x matrix probe in comparison to the 2D probe with a p-value of 0.08,0.34 for RFA and PEI and significantly shorter for MWA, and drainage of hepatic collection, biopsy with a P-value of 0.02,0.001 respectively. Conclusions: 3D ultrasonography-guided hepatic interventions by  x matrix probe have better efficacy, less complication, and shorter time of procedure than the 2D ultrasonography-guided hepatic interventions.

Keywords: 3D, X matrix, 2D, ultrasonography, MWA, RFA, PEI, drainage of hepatic collections, biopsy

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: Lae-Jeong Park, Kyusoo Chung, Jungho Moon

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This paper introduces an effective method of segmenting Korean text (place names in Korean) from a Korean road sign image. A Korean advanced directional road sign is composed of several types of visual information such as arrows, place names in Korean and English, and route numbers. Automatic classification of the visual information and extraction of Korean place names from the road sign images make it possible to avoid a lot of manual inputs to a database system for management of road signs nationwide. We propose a series of problem-specific heuristics that correctly segments Korean place names, which is the most crucial information, from the other information by leaving out non-text information effectively. The experimental results with a dataset of 368 road sign images show 96% of the detection rate per Korean place name and 84% per road sign image.

Keywords: segmentation, road signs, characters, classification

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Authors: Kulwinder Singh Mann

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The innovative features of information system, known as Radiology Information System (RIS), for electronic medical records has shown a good impact in the hospital. The objective is to help and make their work easier; such as for a physician to access the patient’s data and for a patient to check their bill transparently. The interoperability of RIS with the other intra-hospital information systems it interacts with, dealing with the compatibility and open architecture issues, are accomplished by two novel mechanisms. The first one is the particular message handling system that is applied for the exchange of information, according to the Health Level Seven (HL7) protocol’s specifications and serves the transfer of medical and administrative data among the RIS applications and data store unit. The second one implements the translation of information between the formats that HL7 and Digital Imaging and Communication in Medicine (DICOM) protocols specify, providing the communication between RIS and Picture and Archive Communication System (PACS) which is used for the increasing incorporation of modern medical imaging equipment.

Keywords: RIS, PACS, HIS, HL7, DICOM, messaging service, interoperability, digital images

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Authors: Nikhat Nawaz, S. Srinivasulu, P. Kesava Rao

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Feature extraction plays an important role in many remote sensing applications. Automatic extraction of water bodies is of great significance in many remote sensing applications like change detection, image retrieval etc. This paper presents a procedure for automatic extraction of water information from remote sensing images. The algorithm uses the relative location of R-colour component of the chromaticity diagram. This method is then integrated with the effectiveness of the spatial scale transformation of whole method. The whole method is based on water index fitted from spectral library. Experimental results demonstrate the improved accuracy and effectiveness of the integrated method for automatic extraction of water bodies.

Keywords: feature extraction, remote sensing, image retrieval, chromaticity, water index, spectral library, integrated method

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Authors: Chun Chen Yea, Wen Huei Chou

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Many chemical changes in the atmosphere and the ocean are invisible to the naked eye, but they have profound impacts. These changes not only confirm the phenomenon of global carbon pollution, but also forewarn that more changes are coming. The carbon dioxide gases emitted from the burning of fossil fuels dissolve into the ocean and chemically react with seawater to form carbonic acid, which increases the acidity of the originally alkaline seawater. This gradual acidification is occurring at an unprecedented rate and will affect the effective formation of carapace of some marine organisms such as corals and crustaceans, which are almost entirely composed of calcium carbonate. The carapace of these organisms will become more dissoluble. Acidified seawater not only threatens the survival of marine life, but also negatively impacts the global ecosystem via the food chain. Faced with the threat of ocean acidification, all humans are duty-bound. The industrial sector outputs the highest level of carbon dioxide emissions in Taiwan, and the petrochemical industry is the major contributor. Ever since the construction of Formosa Plastics Group's No. 6 Naphtha Cracker Plant in Yunlin County, there have been many environmental concerns such as air pollution and carbon dioxide emission. The marine life along the coast of Yunlin is directly affected by ocean acidification arising from the carbon emissions. Societal change demands our willingness to act, which is what social advocacy promotes. This study uses digital storytelling for social advocacy and ocean acidification as the subject of a visual narrative in visualization to demonstrate the subsequent promotion of social advocacy. Storytelling can transform dull knowledge into an engaging narrative of the crisis faced by marine life. Digital dissemination is an effective social-work practice. The visualization promoting awareness on ocean acidification disseminated via social media platforms, such as Facebook and Instagram. Social media enables users to compose their own messages and share information across different platforms, which helps disseminate the core message of social advocacy.

Keywords: digital storytelling, visualization, ocean acidification, social advocacy

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Authors: Zikun Li, Regine Talleyrand

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Negative body image is one of the most common causes of eating disorders, and it is not only happening to women. Regardless of the increasing attention that researchers and practitioners have been paying to the male population and their body image concerns, men of color have yet to be fully represented or studied. Given the consensus that the sociocultural experiences of people of color may play a significant role in their health and well-being, this study focused on assessing the mechanism through which sociocultural factors may influence men of color’s perceptions of body image. In particular, this study focused on untangling how interpersonal and media pressure, as well as ethnic-racial identities and perceptions, would impact body dissatisfaction in terms of muscularity, body fat, and height in men of color and how this mechanism is moderated across different ethnic-racial groups. The structural equation modeling approach was therefore applied to achieve the research goal. With the sample size of 181 self-identified Black, Indigenous, and People of Color male participants aged 20-50 (M=33.33, SD=6.9) through surveying on Amazon’s MTurk platform, the proposed model achieved a modestly acceptable model fit with the pooled sample, X2(836) = 1412.184, CFI = 0.900, RMSEA = 0.062 [0.056, 0.067]. And SRMR = 0.088, And it explained 89.5% of the variance in body dissatisfaction. The results showed that of all the direct effects on body dissatisfaction, interpersonal appearance pressure exhibited the strongest effect (β = 0.410***), followed by media appearance pressure (β = 0.272**) and self-hatred feeling (β = 0.245**). The ethnic-racial related factors (i.e., stereotype endorsement, ethnic-racial salience, and nationalistic assimilation) statistically influenced body dissatisfaction through the mediators of media appearance pressure and/or self-hatred feeling. Furthermore, the moderation analysis between Black/African American men and non-Black/African American men revealed the substantial differences in how ethnic/racial identity impacts one’s perception of body image, and the Black/African American men were found to be influenced by sociocultural factors at a higher level, compared with their counterparts. The impacts of demographic characteristics (i.e., SES, weight, height) on body dissatisfaction were also examined. Instead of considering interpersonal appearance pressure and media pressure as two subscales under one construct, this study considered them as two separate and distinct sociocultural factors. The good model fit to the data indicates this rationality and encourages scholars to reconsider the impacts of two sources of social pressures on body dissatisfaction. In addition, this study also provided empirical evidence of the moderation effect existing within the population of men of color, which reveals the heterogeneity existing across different ethnic-racial groups and implies the necessity to study individual ethnic-racial groups so as to better understand the mechanism of sociocultural influences on men of color’s body dissatisfaction. These findings strengthened the current understanding of the body image concerns exciting among men of color and meanwhile provided empirical evidence for practitioners to provide tailored health prevention and treatment options for this growing population in the United States.

Keywords: men of color, body image concerns, sociocultural factors, structural equation modeling

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Authors: Linung Kresno Adikusumo, Ivan Ramos Sampe Immanuel, Liston Sitanggang

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An excellent, well work program in the oil and gas industry can have numerous positive business impacts, contributing to operational efficiency, increased production, enhanced safety, and improved financial performance. In summary, an excellent, well work program not only ensures the immediate success of specific projects but also has a broader positive impact on the overall business performance and reputation of the oil and gas company. It positions the company for long-term success in a competitive and dynamic industry. Nevertheless, a number of challenges were encountered when developing a good work program, such as the poor quality and lack of integration of well documentation, the incompleteness of the well history, and the low accessibility of well documentation. As a result, the well work program was delivered less accurately, plus well damage was managed slowly. Our solution implementing digital technology by developing a web-based database and application not only solves those issues but also provides an easy-to-access report and user-friendly display for management as well as engineers to analyze the report’s content. This application aims to revolutionize the documentation of well history in the field of oil and gas exploration and production. The current lack of a streamlined and comprehensive system for capturing, organizing, and accessing well-related data presents challenges in maintaining accurate and up-to-date records. Our innovative solution introduces a user-friendly and efficient platform designed to capture well history documentation seamlessly.

Keywords: digital, drilling, well work, application

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Authors: Caja Thimm

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Already well before the Corona pandemic hit the world, ‘fake news‘ were no longer regarded as harmless twists of the truth but as intentionally composed disinformation, often with the goal of manipulative populist propaganda. During the Corona crisis, particularly conspiracy narratives have become a worldwide phenomenon with dangerous consequences (anti vaccination myths). The success of these manipulated news need s to be counteracted by trustworthy news, which in Europe particularly includes public broadcasting media and their social media channels. To understand better how the main public broadcasters in Germany, the UK, and France used Instagram strategically, a comparative study was carried out. The study – comparative analysis of Instagram during the Corona Crisis In our empirical study, we compared the activities by selected formats during the Corona crisis in order to see how the public broadcasters reached their audiences and how this might, in the longer run, affect journalistic strategies on social media platforms. First analysis showed that the increase in the use of social media overall was striking. Almost one in two adult online users (48 %) obtained information about the virus in social media, and in total, 38% of the younger age group (18-24) looked for Covid19 information on Instagram, so the platform can be regarded as one of the central digital spaces for Corona related information searches. Quantitative measures showed that 47% of recent posts by the broadcasters were related to Corona, and 7% treated conspiracy myths. For the more detailed content analysis, the following categories of analysis were applied: • Digital storytelling and instastories • Textuality and semantic keys • links to information • stickers • videochat • fact checking • news ticker • service • infografics and animated tables Additionally to these basic features, we particularly looked for new formats created during the crisis. Journalistic use of social media platforms opens up immediate and creative ways of applying the media logics of the respective platforms, and particularly the BBC and ARD formats proved to be interactive, responsive, and entertaining. Among them were new formats such as a space for user questions and personal uploads, interviews, music, comedy, etc. Particularly the fact checking channel got a lot of attention, as many user questions were focused on the conspiracy theories, which dominated the public discourse during many weeks in 2020. In the presentation, we will introduce eight particular strategies that show how public broadcasting journalism can adopt digital platforms and use them creatively and, hence help to counteract against conspiracy narratives and fake news.

Keywords: fake news, social media, digital journalism, digital methods

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Qasim HamaKhurshid HamaMurad, Normal Mat Jusoh, Uznir Ujang

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The concept of the city with an infrastructure of (information and communication) Technology embraces several definitions depending on the meanings of the word "smart" are (intelligent city, smart city, knowledge city, ubiquitous city, sustainable city, digital city). Many definitions of the city exist, but this chapter explores which one has been universally acknowledged. From literature analysis, it emerges that Smart City is the most used terminologies in literature through the digital database to indicate the smartness of a city. This paper share exploration the research from main seven website digital databases and journal about Smart City from "January 2015 to the February of 2020" to (a) Time research, to examine the causes of the Smart City phenomenon and other concept literature in the last five years (b) Review of words, to see how and where the smart city specification and relation different definition And(c) Geographical research to consider where Smart Cities' greatest concentrations are in the world and are Malaysia has interacting with the smart city, and (d) how many papers published from all Malaysia from 2015 to 2020 about smart citie. Three steps are followed to accomplish the goal. (1)The analysis covered publications Build a systematic literature review search strategy to gather a representative sub-set of papers on Smart City and other definitions utilizing (GoogleScholar, Elsevier, Scopus, ScienceDirect, IEEEXplore, WebofScience, Springer) January2015-February2020. (2)A bibliometric map was formed based on the bibliometric evaluation using the mapping technique VOSviewer to visualize differences. (3)VOSviewer application program was used to build initial clusters. The Map of Bibliometric Visualizes the analytical findings which targeted the word harmony.

Keywords: bibliometric research, smart city, ICT, VOSviewer, urban modernization

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Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

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In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

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Authors: Mengistu G. Woldu, Hani Y. Zaki, Areeg Faggad, Badreldin E. Abdalla

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Background: Type 2 diabetes mellitus (T2DM) is a complex, degenerative, and multi-factorial disease, which is culpable for huge mortality and morbidity worldwide. Even though relatively significant numbers of studies are conducted on the genetics domain of this disease in the developed world, there is huge information gap in the sub-Saharan Africa region in general and in Eritrea in particular. Objective: The principal aim of this study was to investigate the association of common variants of the Insulin Receptor Substrate 1 (IRS1) and Transcription Factor 7-Like 2 (TCF7L2) genes with T2DM in the Eritrean population. Method: In this cross-sectional case control study 200 T2DM patients and 112 non-diabetes subjects were participated and genotyping of the IRS1 (rs13431179, rs16822615, 16822644rs, rs1801123) and TCF7L2 (rs7092484) tag SNPs were carries out using PCR-RFLP method of analysis. Haplotype analyses were carried out using Plink version 1.07, and Haploview 4.2 software. Linkage disequilibrium (LD), and Hardy-Weinberg equilibrium (HWE) analyses were performed using the Plink software. All descriptive statistical data analyses were carried out using SPSS (Version-20) software. Throughout the analysis p-value ≤0.05 was considered statistically significant. Result: Significant association was found between rs13431179 SNP of the IRS1 gene and T2DM under the recessive model of inheritance (OR=9.00, 95%CI=1.17-69.07, p=0.035), and marginally significant association found in the genotypic model (OR=7.50, 95%CI=0.94-60.06, p=0.058). The rs7092484 SNP of the TCF7L2 gene also showed markedly significant association with T2DM in the recessive (OR=3.61, 95%CI=1.70-7.67, p=0.001); and allelic (OR=1.80, 95%CI=1.23-2.62, p=0.002) models. Moreover, eight haplotypes of the IRS1 gene found to have significant association withT2DM (p=0.013 to 0.049). Assessments made on the interactions of genotypes of the rs13431179 and rs7092484 SNPs with various parameters demonstrated that high density lipoprotein (HDL), low density lipoprotein (LDL), waist circumference (WC), and systolic blood pressure (SBP) are the best T2DM onset predicting models. Furthermore, genotypes of the rs7092484 SNP showed significant association with various atherogenic indexes (Atherogenic index of plasma, LDL/HDL, and CHLO/HDL); and Eritreans carrying the GG or GA genotypes were predicted to be more susceptible to cardiovascular diseases onset. Conclusions: Results of this study suggest that IRS1 (rs13431179) and TCF7L2 (rs7092484) gene polymorphisms are associated with increased risk of T2DM in Eritreans.

Keywords: IRS1, SNP, TCF7L2, type 2 diabetes

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Annette Cosgrove, Carina Ginty, Tony Hall, Cornelia Connolly

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The objectives of this research study is to examine the impact of professional development in Technology Enhanced Learning (TEL) and the digitization of learning in teaching communities across multiple higher education sites in the ATU (Atlantic Technological University *) ( 2020-2025), including the proposal of an evidence-based digital teaching model for use in a future pandemic. The research strategy undertaken for this study is a multi-site study using mixed methods. Qualitative & quantitative methods are being used in the study to collect data. A pilot study was carried out initially, feedback was collected and the research instrument was edited to reflect this feedback before being administered. The purpose of the staff questionnaire is to evaluate the impact of professional development in the area of TEL, and to capture the practitioner's views on the perceived impact on their teaching practice in the higher education sector across ATU (West of Ireland – 5 Higher education locations ). The phenomenon being explored is ‘ the impact of professional development in the area of technology-enhanced learning and on teaching practice in a higher education institution. The research methodology chosen for this study is an Action based Research Study. The researcher has chosen this approach as it is a prime strategy for developing educational theory and enhancing educational practice. This study includes quantitative and qualitative methods to elicit data that will quantify the impact that continuous professional development in the area of digital teaching practice and technologies has on the practitioner’s teaching practice in higher education. The research instruments/data collection tools for this study include a lecturer survey with a targeted TEL Practice group ( Pre and post covid experience) and semi-structured interviews with lecturers. This research is currently being conducted across the ATU multi-site campus and targeting Higher education lecturers that have completed formal CPD in the area of digital teaching. ATU, a West of Ireland university, is the focus of the study. The research questionnaire has been deployed, with 75 respondents to date across the ATU - the primary questionnaire and semi-formal interviews are ongoing currently – the purpose being to evaluate the impact of formal professional development in the area of TEL and its perceived impact on the practitioners teaching practice in the area of digital teaching and learning. This paper will present initial findings, reflections and data from this ongoing research study.

Keywords: TEL, technology, digital, education

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