Search results for: digital images

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: Camilla G. Goncalves, Benedito Christ, Walter Miyakawa, Antonio J. Abdalla

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This work aims to investigate the properties and microstructure of diamond-like carbon film deposited by pulsed laser deposition by ablation of a graphite target in a vacuum chamber on a steel substrate. The equipment was mounted to provide one laser beam. The target of high purity graphite and the steel substrate were polished. The mechanical and tribological properties of the film were characterized using Raman spectroscopy, nanoindentation test, scratch test, roughness profile, tribometer, optical microscopy and SEM images. It was concluded that the pulsed laser deposition (PLD) technique associated with the low-pressure chamber and a graphite target provides a good fraction of sp3 bonding, that the process variable as surface polishing and laser parameter have great influence in tribological properties and in adherence tests performance. The optical microscopy images are efficient to identify the metallurgical bond.

Keywords: characterization, DLC, mechanical properties, pulsed laser deposition

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Authors: Prabhu Thangaraju, Manoj Deepak, A. Sivakumar

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Removal of inter vertebral disc along with spinal fusion has many disadvantages such as causing stress fractures. If it is possible regenerate the spine it would be possible avoid the complications of the surgery and achieve better results. Our study involves the use of mesenchymal stem cells in regenerating the discs. Our study involved 10 patients who presented with degenerative disc disease between 2008-2011 in our hospital. After adequate pre-operative check prepared mesenchymal stem cells were injected into the disc spaces. These patients were subjected to conservative therapy for a minimum of six weeks before they were accepted into the study. They were followed up regularly for a minimum of 2years with serial radiographs and MRI. 8 out of the 10 patients had completed reduction in the pain. The T2 weighted MRI images in 9 out of the 10 patients showed a bright signal compared the previous Images which indicated that there was improvement in the hydration levels. From the case study of 10 patients who were subjected to mesenchymal cell therapy in our hospital, we can conclude that the use of mesenchymal cells in treatment of intervertebral disc degeneration in a safe and effective option.

Keywords: mesenchymal stem cells, intervertebral disc, the spine, disc degeneration

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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: 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: R. Rama Kishore, Sunesh

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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

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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: 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: 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: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar

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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.

Keywords: block matching, exhaustive search motion estimation, three step search, video compression

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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: 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: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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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: 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: 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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Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration

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Authors: Ida Srdić, Luka Mandić, LidijaMandić

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Digitization and intensive use of tablets, smartphones, the internet, mobile, and web applications have massively disrupted our habits, and the way audiences (especially youth) consume content. To introduce educational content in games and animations, and at the same time to keep it interesting and compelling for kids, is a challenge. In our work, we are comparing the different possibilities and potentials that digital games could provide to successfully mitigate direct connection with education. We analyze the main directions and educational methods in game-based learning and the possibilities of interactive modeling through questionnaires for user experience and requirements. A pre and post-quantitative survey will be conducted in order to measure levels of objective knowledge as well as the games perception. This approach enables quantitative and objective evaluation of the impact the game has on participants. Also, we will discuss the main barriers to the use of games in education and how games can be best used for learning.

Keywords: Bloom’s taxonomy, epistemic games, learning objectives, virtual learning environments

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Authors: Vivek Anand, Rainer Naegele

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Industry 4.0 is a global mega-trend revolutionizing the world of advanced manufacturing, but also bringing up challenges for SMEs. In response, many regional, as well as digital Industry 4.0 Platforms, have been set up to boost the competencies of established enterprises as well as SMEs. The concept of 'Clusters' is a policy tool that aims to be a starting point to establish sustainable and self-supporting structures in industries of a region by identifying competencies and supporting cluster actors with services that match their growth needs. This paper is motivated by the idea that Clusters have the potential to enable firms, particularly SMEs, to accelerate the innovation process and transition to digital technologies. In this research, the efficacy of Industry 4.0 platforms as Cluster ecosystems is evaluated, especially for SMEs. Focusing on the Baden Wurttemberg region in Germany, an action research method is employed to study how SMEs leverage other actors on Industry 4.0 Platforms to further their Industry 4.0 journeys. The aim is to evaluate how such Industry 4.0 platforms stimulate innovation, cooperation and competitiveness. Additionally, the barriers to these platforms fulfilling their promise to serve as capacity building cluster ecosystems for SMEs in a region will also be identified. The findings will be helpful for academicians and policymakers alike, who can leverage a ‘cluster policy’ to enable Industry 4.0 ecosystems in their regions. Furthermore, relevant management and policy implications stem from the analysis. This will also be of interest to the various players in a cluster ecosystem - like SMEs and service providers - who benefit from the cooperation and competition. The paper will improve the understanding of how a dialogue orientation, a bottom-up approach and active integration of all involved cluster actors enhance the potential of Industry 4.0 Platforms. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position Industry 4.0 Platforms at the forefront of the industrial renaissance. Motivated by this argument and based on the results of the qualitative research, a roadmap will be proposed to position Industry 4.0 Platforms as effective clusters ecosystems to support Industry 4.0 adoption in a region.

Keywords: cluster policy, digital transformation, industry 4.0, innovation clusters, innovation policy, SMEs and startups

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Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

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Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Qian Pei, Hengjian Tong, Weitao Chen, Hai Wang, Yanrong Feng

Abstract:

Horizontal parallax is the foundation of stereoscopic viewing. However, the human eye will feel uncomfortable and it will occur diplopia if horizontal parallax is larger than eye separation. Therefore, we need to do parallax refining before conducting stereoscopic observation. Although some scholars have been devoted to online remote sensing refining, the main work of image refining is completed on the server side. There will be a significant delay when multiple users access the server at the same time. The emergence of HTML5 technology in recent years makes it possible to develop rich browser web application. Authors complete the image parallax refining on the browser side based on HTML5, while server side only need to transfer image data and parallax file to browser side according to the browser’s request. In this way, we can greatly reduce the server CPU load and allow a large number of users to access server in parallel and respond the user’s request quickly.

Keywords: 3D remote sensing images, parallax, online refining, rich browser web application, HTML5

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Authors: Pankhudi Khandelwal

Abstract:

The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

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Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

Abstract:

High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

Abstract:

To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

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Authors: Shyam Sajan, Kamal Bijlani

Abstract:

The widespread effects of digital media help people to explore the world more and get entertained with no effort. People became fond of these kind of sedentary life style. The increase in sedentary time and a decrease in physical activities has negative impacts on human health. Even though the addiction to video games has been exploited in exergames, to make people exercise and enjoy game challenges, the contribution is restricted only to physical wellness. This paper proposes creation and implementation of a game with the help of digital media in a virtual environment. The game is designed by collaborating ideas from neural linguistic programming and Stroop effect that can also be used to identify a person’s mental state, to improve concentration and to eliminate various phobias. The multiplayer game is played in a virtual environment created with Kinect sensor, to make the game more motivating and interactive.

Keywords: exergaming, Kinect Sensor, Neural Linguistic Programming, Stroop Effect

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Authors: Khalid. M. O. Elmabrok, M. L. Burby, G. G. Nasr

Abstract:

Flow instability during gas lift operation is caused by three major phenomena – the density wave oscillation, the casing heading pressure and the flow perturbation within the two-phase flow region. This paper focuses on the causes and the effect of flow instability during gas lift operation and suggests ways to control it in order to maximise productivity during gas lift operations. A laboratory-scale two-phase flow system to study the effects of flow perturbation was designed and built. The apparatus is comprised of a 2 m long by 66 mm ID transparent PVC pipe with air injection point situated at 0.1 m above the base of the pipe. This is the point where stabilised bubbles were visibly clear after injection. Air is injected into the water filled transparent pipe at different flow rates and pressures. The behavior of the different sizes of the bubbles generated within the two-phase region was captured using a digital camera and the images were analysed using the advanced image processing package. It was observed that the average maximum bubbles sizes increased with the increase in the length of the vertical pipe column from 29.72 to 47 mm. The increase in air injection pressure from 0.5 to 3 bars increased the bubble sizes from 29.72 mm to 44.17 mm and then decreasing when the pressure reaches 4 bars. It was observed that at higher bubble velocity of 6.7 m/s, larger diameter bubbles coalesce and burst due to high agitation and collision with each other. This collapse of the bubbles causes pressure drop and reverse flow within two phase flow and is the main cause of the flow instability phenomena.

Keywords: gas lift instability, bubbles forming, bubbles collapsing, image processing

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Authors: Marilyn U. Balagtas, Maria Ruth M. Regalado, Carmelina E. Barrera, Ramer V. Oxiño, Rosarito T. Suatengco, Josephine E. Tondo

Abstract:

This study presents the perceptions of the students and teachers from kindergarten to tertiary level of the image of the 21st century teacher to provide basis in designing teacher development programs in Teacher Education Institutions (TEIs) in the Philippines. The highlights of the report are the personal, psychosocial, and professional images of the 21st century teacher in basic education and the teacher educators based on a survey done to 612 internal stakeholders of nine member institutions of the National Network of Normal Schools (3NS). Data were obtained through the use of a validated researcher-made instrument which allowed generation of both quantitative and qualitative descriptions of the teacher image. Through the use of descriptive statistics, the common images of the teacher were drawn, which were validated and enriched by the information drawn from the qualitative data. The study recommends a repertoire of teacher development programs to create the good image of the 21st century teachers for a better Philippines.

Keywords: teacher image, 21st century teacher, teacher education, development program

Procedia PDF Downloads 359