Search results for: digital image watermarking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5199

Search results for: digital image watermarking

4329 Educational Turn towards Digitalization by Changing Leadership, Networks and Qualification Concepts

Authors: Patricia Girrbach

Abstract:

Currently, our society is facing a new and incremental upheaval technological revolution named digitalization. In order to face the relating challenges organizations have to be prepared. They need appropriate circumstances in order to cope with current issues concerning digital transformation processes. Nowadays digitalization emerged as top issues for companies and business leaders. In this context, it is a pressure on companies to have a positive, productive digital culture. And indeed, Organizations realize that they need to address this important issue. In this context 87 percent of organizations quote culture and engagement as one of their top challenges in terms of any change process, but especially in terms of the digital turn. Executives can give their company a competitive advantage and attract top talent by having a strong workplace culture that supports digitalization. Many current studies attest that fact. Digital-oriented companies can hire more easily, they have the lowest voluntary turnover rates, deliver better customer service, and are more profitable over the long run. Based on this background it is important to provide companies starting points and practical measurements how to reach this goal. The major findings are that firms need to make sense out of digitalization. In this context, they should focus on internal but also on external stakeholders. Furthermore, they should create certain working conditions and they should support the qualification of employees, e.g. by Virtual Reality. These measurements can create positive experiences in terms of digitalization in order to ensure the support of stuff in terms of the digital turn. Based on several current studies and literature research this paper provides concrete measurements for companies in order to enable the digital turn. Therefore, the aim of this paper is providing possible practical starting points which support both the education of employees by digitalization as well as the digital turn itself within the organization.

Keywords: digitalization, industry 4.0, education 4.0, virtual reality

Procedia PDF Downloads 159
4328 An Application-Driven Procedure for Optimal Signal Digitization of Automotive-Grade Ultrasonic Sensors

Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

Abstract:

In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished through the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: analog to digital conversion, digitization, sampling rate, ultrasonic

Procedia PDF Downloads 207
4327 Economic Life of Iranians on Instagram and the Disturbance in Politics

Authors: Mohammad Zaeimzade

Abstract:

The development of communication technologies is clearly and rapidly moving towards reducing the distance between the virtual and real worlds. Of course, living in a two-spatial or two-globalized world or any other interpretation that means mixing real and virtual life is still relevant and debatable. In the present age of communication, where social networks have transformed the message equation and turned the audience out of passivity and turned into a user. Platforms have penetrated widely in various aspects of human life, from culture and education and economy. Among the messengers, Instagram, which is one of the most extensive image-based interactive networks, plays a significant role in the new economic life. It doesn't need much explanation that the era of thinking of every messenger as a non-insulating conductor that is just a neutral load has passed. Every messenger has its own economic, political and of course security background, Instagram is no exception to this rule and of course it leaves its effects in bio-economics as well. Iran, as the 19th largest economy in the world, has not been unaffected by new platforms, including Instagram, and their consequences in the economy. Generally, in the policy-making space, there are two simple and inflexible pessimistic or optimistic views on this issue, and each of the holders of these views usually have their own one-dimensional policy recommendations regarding how to deal with Instagram. Prescriptions that are usually very different and sometimes contradictory. In this article, we show that this confusion of policymakers is the result of not accurately describing the reality of its effect, and the reason for this inaccurate description is the existence of a conflict of interests in the eyes of describers and researchers. In this article, we first take a look at the main indicators of the Iranian economy, estimate the role of the digital economy in Iran's economic growth, then study the conflicting descriptions of the Instagram-based digital economy, the statistics that show the tolerance of economic users of Instagram in Iran. 300 thousand to 9 million have been estimated. Finally, we take a look at the government's actions in this matter, especially in the context of street riots in October and November 2022. And we suggest an intermediate idea.

Keywords: digital economy, instagram, conflict of interest, social networks

Procedia PDF Downloads 76
4326 Video Stabilization Using Feature Point Matching

Authors: Shamsundar Kulkarni

Abstract:

Video capturing by non-professionals will lead to unanticipated effects. Such as image distortion, image blurring etc. Hence, many researchers study such drawbacks to enhance the quality of videos. In this paper, an algorithm is proposed to stabilize jittery videos .A stable output video will be attained without the effect of jitter which is caused due to shaking of handheld camera during video recording. Firstly, salient points from each frame from the input video are identified and processed followed by optimizing and stabilize the video. Optimization includes the quality of the video stabilization. This method has shown good result in terms of stabilization and it discarded distortion from the output videos recorded in different circumstances.

Keywords: video stabilization, point feature matching, salient points, image quality measurement

Procedia PDF Downloads 313
4325 Examination of Readiness of Teachers in the Use of Information-Communication Technologies in the Classroom

Authors: Nikolina Ribarić

Abstract:

This paper compares the readiness of chemistry teachers to use information and communication technologies in chemistry in 2018. and 2021. A survey conducted in 2018 on a sample of teachers showed that most teachers occasionally use visualization and digitization tools in chemistry teaching (65%) but feel that they are not educated enough to use them (56%). Also, most teachers do not have adequate equipment in their schools and are not able to use ICT in teaching or digital tools for visualization and digitization of content (44%). None of the teachers find the use of digitization and visualization tools useless. Furthermore, a survey conducted in 2021 shows that most teachers occasionally use visualization and digitization tools in chemistry teaching (83%). Also, the research shows that some teachers still do not have adequate equipment in their schools and are not able to use ICT in chemistry teaching or digital tools for visualization and digitization of content (14%). Advances in the use of ICT in chemistry teaching are linked to pandemic conditions and the obligation to conduct online teaching. The share of 14% of teachers who still do not have adequate equipment to use digital tools in teaching is worrying.

Keywords: chemistry, digital content, e-learning, ICT, visualization

Procedia PDF Downloads 155
4324 Empowering Certificate Management with Blockchain Technology

Authors: Yash Ambekar, Kapil Vhatkar, Prathamesh Swami, Kartikey Singh, Yashovardhan Kaware

Abstract:

The rise of online courses and certifications has created new opportunities for individuals to enhance their skills. However, this digital transformation has also given rise to coun- terfeit certificates. To address this multifaceted issue, we present a comprehensive certificate management system founded on blockchain technology and strengthened by smart contracts. Our system comprises three pivotal components: certificate generation, authenticity verification, and a user-centric digital locker for certificate storage. Blockchain technology underpins the entire system, ensuring the immutability and integrity of each certificate. The inclusion of a cryptographic hash for each certificate is a fundamental aspect of our design. Any alteration in the certificate’s data will yield a distinct hash, a powerful indicator of potential tampering. Furthermore, our system includes a secure digital locker based on cloud storage that empowers users to efficiently manage and access all their certificates in one place. Moreover, our project is committed to providing features for certificate revocation and updating, thereby enhancing the system’s flexibility and security. Hence, the blockchain and smart contract-based certificate management system offers a robust and one-stop solution to the escalating problem of counterfeit certificates in the digital era.

Keywords: blockchain technology, smart contracts, counterfeit certificates, authenticity verification, cryptographic hash, digital locker

Procedia PDF Downloads 46
4323 Comparison of Slope Data between Google Earth and the Digital Terrain Model, for Registration in Car

Authors: André Felipe Gimenez, Flávia Alessandra Ribeiro da Silva, Roberto Saverio Souza Costa

Abstract:

Currently, the rural producer has been facing problems regarding environmental regularization, which is precisely why the CAR (Rural Environmental Registry) was created. CAR is an electronic registry for rural properties with the purpose of assimilating notions about legal reserve areas, permanent preservation areas, areas of limited use, stable areas, forests and remnants of native vegetation, and all rural properties in Brazil. . The objective of this work was to evaluate and compare altimetry and slope data from google Earth with a digital terrain model (MDT) generated by aerophotogrammetry, in three plots of a steep slope, for the purpose of declaration in the CAR (Rural Environmental Registry). The realization of this work is justified in these areas, in which rural landowners have doubts about the reliability of the use of the free software Google Earth to diagnose inclinations greater than 25 degrees, as recommended by federal law 12651/2012. Added to the fact that in the literature, there is a deficiency of this type of study for the purpose of declaration of the CAR. The results showed that when comparing the drone altimetry data with the Google Earth image data, in areas of high slope (above 40% slope), Google underestimated the real values of terrain slope. Thus, it is concluded that Google Earth is not reliable for diagnosing areas with an inclination greater than 25 degrees (46% declivity) for the purpose of declaration in the CAR, being essential to carry out the local topographic survey.

Keywords: MDT, drone, RPA, SiCar, photogrammetry

Procedia PDF Downloads 131
4322 An Enhanced Digital Forensic Model for Internet of Things Forensic

Authors: Tina Wu, Andrew Martin

Abstract:

The expansion of the Internet of Things (IoT) brings a new level of threat. Attacks on IoT are already being used by criminals to form botnets, launch Distributed Denial of Service (DDoS) and distribute malware. This opens a whole new digital forensic arena to develop forensic methodologies in order to have the capability to investigate IoT related crimes. However, existing proposed IoT forensic models are still premature requiring further improvement and validation, many lack details on the acquisition and analysis phase. This paper proposes an enhanced theoretical IoT digital forensic model focused on identifying and acquiring the main sources of evidence in a methodical way. In addition, this paper presents a theoretical acquisition framework of the different stages required in order to be capable of acquiring evidence from IoT devices.

Keywords: acquisition, Internet of Things, model, zoning

Procedia PDF Downloads 271
4321 Applying Semi-Automatic Digital Aerial Survey Technology and Canopy Characters Classification for Surface Vegetation Interpretation of Archaeological Sites

Authors: Yung-Chung Chuang

Abstract:

The cultural layers of archaeological sites are mainly affected by surface land use, land cover, and root system of surface vegetation. For this reason, continuous monitoring of land use and land cover change is important for archaeological sites protection and management. However, in actual operation, on-site investigation and orthogonal photograph interpretation require a lot of time and manpower. For this reason, it is necessary to perform a good alternative for surface vegetation survey in an automated or semi-automated manner. In this study, we applied semi-automatic digital aerial survey technology and canopy characters classification with very high-resolution aerial photographs for surface vegetation interpretation of archaeological sites. The main idea is based on different landscape or forest type can easily be distinguished with canopy characters (e.g., specific texture distribution, shadow effects and gap characters) extracted by semi-automatic image classification. A novel methodology to classify the shape of canopy characters using landscape indices and multivariate statistics was also proposed. Non-hierarchical cluster analysis was used to assess the optimal number of canopy character clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy character classification (seven categories). Therefore, people could easily predict the forest type and vegetation land cover by corresponding to the specific canopy character category. The results showed that the semi-automatic classification could effectively extract the canopy characters of forest and vegetation land cover. As for forest type and vegetation type prediction, the average prediction accuracy reached 80.3%~91.7% with different sizes of test frame. It represented this technology is useful for archaeological site survey, and can improve the classification efficiency and data update rate.

Keywords: digital aerial survey, canopy characters classification, archaeological sites, multivariate statistics

Procedia PDF Downloads 142
4320 A Fast, Reliable Technique for Face Recognition Based on Hidden Markov Model

Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

Abstract:

Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

Procedia PDF Downloads 331
4319 The Learning Impact of a 4-Dimensional Digital Construction Learning Environment

Authors: Chris Landorf, Stephen Ward

Abstract:

This paper addresses a virtual environment approach to work integrated learning for students in construction-related disciplines. The virtual approach provides a safe and pedagogically rigorous environment where students can apply theoretical knowledge in a simulated real-world context. The paper describes the development of a 4-dimensional digital construction environment and associated learning activities funded by the Australian Office for Learning and Teaching. The environment was trialled with over 1,300 students and evaluated through questionnaires, observational studies and coursework analysis. Results demonstrate a positive impact on students’ technical learning and collaboration skills, but there is need for further research in relation to critical thinking skills and work-readiness.

Keywords: architectural education, construction industry, digital learning environments, immersive learning

Procedia PDF Downloads 411
4318 Large Neural Networks Learning From Scratch With Very Few Data and Without Explicit Regularization

Authors: Christoph Linse, Thomas Martinetz

Abstract:

Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

Procedia PDF Downloads 88
4317 Innovative Business Models in the Era of Digital Tourism: Examining Their Impact on International Travel, Local Businesses, and Residents’ Quality of Life

Authors: Madad Ali

Abstract:

In the contemporary landscape of international travel, the infusion of digital technologies has given rise to innovative business models that are reshaping the dynamics of tourism. This research delves into the transformative potential of these novel business models within the realm of digital tourism and their multifaceted impact on local businesses, residents' quality of life, and the overall travel experience. The study focuses on the captivating backdrop of Yunnan Province, China, renowned for its rich cultural heritage and diverse ethnic minorities, to uncover the intricate nuances of this phenomenon. The primary objectives of this research encompass the identification and categorization of emerging business models facilitated by digital technologies, their implications on tourist engagement, and their integration into the operations of local businesses. By employing a mixed-methods approach, blending qualitative techniques like interviews and content analysis with quantitative tools such as surveys and data analysis, the study provides a comprehensive evaluation of these business models' effects on various dimensions of the tourism landscape. The distinctiveness of this research lies in its exclusive focus on Yunnan Province, China. By concentrating on Yunnan Province, the research contributes exceptional insights into the interplay between digital tourism, ethnic diversity, cultural heritage, and sustainable development. The study's outcomes hold significance for both scholarly discourse and the stakeholders involved in shaping the region's tourism strategies.

Keywords: business model, digital tourism, international travel, local businesses, quality of life

Procedia PDF Downloads 57
4316 Computer Countenanced Diagnosis of Skin Nodule Detection and Histogram Augmentation: Extracting System for Skin Cancer

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

Abstract:

Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

Procedia PDF Downloads 150
4315 Design of a Virtual Reality Application Based Digital Heritage Mediation: The Case of 'Djerba View VR'

Authors: Hela Ben Maallem

Abstract:

Applications based on virtual reality offer many benefits to the heritage and tourism sector. Digital heritage mediation is a constantly emerging field that aims to reconstruct the history of heritage items and sites, while at the same time highlighting the identity of a community or region and encouraging public engagement. This research focuses on the analysis of a virtual reality application used in a heritage digital mediation project. The modality introduced is examined through a case study of Djerba View VR application. The aim of this study is to understand the nature and potential uses of this immersive technology and to focus on the study of the possibilities of this medium. The goal of this article is to analyze how 3D reconstruction and immersive storytelling can offer an immersive, interactive and engaging user experience, while meeting the expectations and needs of visitors in a context of technological transition and user-centred design.

Keywords: digital heritage mediation, technological transition, virtual reality, 3D reconstruction, immersive storytelling, user experience, user centered design, interactivity, immersion

Procedia PDF Downloads 53
4314 PET Image Resolution Enhancement

Authors: Krzysztof Malczewski

Abstract:

PET is widely applied scanning procedure in medical imaging based research. It delivers measurements of functioning in distinct areas of the human brain while the patient is comfortable, conscious and alert. This article presents the new compression sensing based super-resolution algorithm for improving the image resolution in clinical Positron Emission Tomography (PET) scanners. The issue of motion artifacts is well known in Positron Emission Tomography (PET) studies as its side effect. The PET images are being acquired over a limited period of time. As the patients cannot hold breath during the PET data gathering, spatial blurring and motion artefacts are the usual result. These may lead to wrong diagnosis. It is shown that the presented approach improves PET spatial resolution in cases when Compressed Sensing (CS) sequences are used. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. The application of CS to PET has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the goal is to combine super-resolution image enhancement algorithm with CS framework to achieve high resolution PET output. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity.

Keywords: PET, super-resolution, image reconstruction, pattern recognition

Procedia PDF Downloads 371
4313 Image Segmentation Using Active Contours Based on Anisotropic Diffusion

Authors: Shafiullah Soomro

Abstract:

Active contour is one of the image segmentation techniques and its goal is to capture required object boundaries within an image. In this paper, we propose a novel image segmentation method by using an active contour method based on anisotropic diffusion feature enhancement technique. The traditional active contour methods use only pixel information to perform segmentation, which produces inaccurate results when an image has some noise or complex background. We use Perona and Malik diffusion scheme for feature enhancement, which sharpens the object boundaries and blurs the background variations. Our main contribution is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. By minimizing an energy function using partial differential framework the proposed method captures semantically meaningful boundaries instead of catching uninterested regions. Finally, we use a Gaussian kernel which eliminates the problem of reinitialization in level set function. We use several synthetic and real images from different modalities to validate the performance of the proposed method. In the experimental section, we have found the proposed method performance is better qualitatively and quantitatively and yield results with higher accuracy compared to other state-of-the-art methods.

Keywords: active contours, anisotropic diffusion, level-set, partial differential equations

Procedia PDF Downloads 161
4312 Improvement of Piezoresistive Pressure Sensor Accuracy by Means of Current Loop Circuit Using Optimal Digital Signal Processing

Authors: Peter A. L’vov, Roman S. Konovalov, Alexey A. L’vov

Abstract:

The paper presents the advanced digital modification of the conventional current loop circuit for pressure piezoelectric transducers. The optimal DSP algorithms of current loop responses by the maximum likelihood method are applied for diminishing of measurement errors. The loop circuit has some additional advantages such as the possibility to operate with any type of resistance or reactance sensors, and a considerable increase in accuracy and quality of measurements to be compared with AC bridges. The results obtained are dedicated to replace high-accuracy and expensive measuring bridges with current loop circuits.

Keywords: current loop, maximum likelihood method, optimal digital signal processing, precise pressure measurement

Procedia PDF Downloads 529
4311 The Role of Digital Text in School and Vernacular Literacies: Students Digital Practices at Cybercafés in Mexico

Authors: Guadalupe López-Bonilla

Abstract:

Students of all educational levels participate in literacy practices that may involve print or digital media. Scholars from the New Literacy Studies distinguish practices that fulfill institutional purposes such as those established at schools from literate practices aimed at doing other kinds of activities, such as reading instructions in order to play a video game; the first are known as institutional practices while the latter are considered vernacular literacies. When students perform these kinds of activities they engage with print and digital media according to the demands of the task. In this paper, it is aimed to discuss the results of a research project focusing on literacy practices of high school students at 10 urban cybercafés in Mexico. The main objective was to analyze the literacy practices of students performing both school tasks and vernacular literacies. The methodology included a focused ethnography with online and face to face observations of 10 high school students (5 male and 5 female) and interviews after performing each task. In the results, it is presented how students treat texts as open, dynamic and relational artifacts when engaging in vernacular literacies; while texts are conceived as closed, authoritarian and fixed documents when performing school activities. Samples of each type of activity are shown followed by a discussion of the pedagogical implications for improving school literacy.

Keywords: digital literacy, text, school literacy, vernacular practices

Procedia PDF Downloads 272
4310 Mutual Information Based Image Registration of Satellite Images Using PSO-GA Hybrid Algorithm

Authors: Dipti Patra, Guguloth Uma, Smita Pradhan

Abstract:

Registration is a fundamental task in image processing. It is used to transform different sets of data into one coordinate system, where data are acquired from different times, different viewing angles, and/or different sensors. The registration geometrically aligns two images (the reference and target images). Registration techniques are used in satellite images and it is important in order to be able to compare or integrate the data obtained from these different measurements. In this work, mutual information is considered as a similarity metric for registration of satellite images. The transformation is assumed to be a rigid transformation. An attempt has been made here to optimize the transformation function. The proposed image registration technique hybrid PSO-GA incorporates the notion of Particle Swarm Optimization and Genetic Algorithm and is used for finding the best optimum values of transformation parameters. The performance comparision obtained with the experiments on satellite images found that the proposed hybrid PSO-GA algorithm outperforms the other algorithms in terms of mutual information and registration accuracy.

Keywords: image registration, genetic algorithm, particle swarm optimization, hybrid PSO-GA algorithm and mutual information

Procedia PDF Downloads 408
4309 Digital Transformation in Developing Countries, A Study into Building Information Modelling Adoption in Thai Design and Engineering Small- and Medium-Sizes Enterprises

Authors: Prompt Udomdech, Eleni Papadonikolaki, Andrew Davies

Abstract:

Building information modelling (BIM) is the major technological trend amongst built environment organisations. Digitalising businesses and operations, BIM brings forth a digital transformation in any built environment industry. The adoption of BIM presents challenges for organisations, especially small- and medium-sizes enterprises (SMEs). The main problem for built-environment SMEs is the lack of project actors with adequate BIM competences. The research highlights learning in projects as the key and explores into the learning of BIM in projects of designers and engineers within Thai design and engineering SMEs. The study uncovers three impeding attributes, which are: a) lack of English proficiency; b) unfamiliarity with digital technologies; and c) absence of public standards. This research expands on the literature on BIM competences and adoption.

Keywords: BIM competences and adoption, digital transformation, learning in projects, SMEs, and developing built environment industry

Procedia PDF Downloads 144
4308 A Methodological Approach to Digital Engineering Adoption and Implementation for Organizations

Authors: Sadia H. Syeda, Zain H. Malik

Abstract:

As systems continue to become more complex and the interdependencies of processes and sub-systems continue to grow and transform, the need for a comprehensive method of tracking and linking the lifecycle of the systems in a digital form becomes ever more critical. Digital Engineering (DE) provides an approach to managing an authoritative data source that links, tracks, and updates system data as it evolves and grows throughout the system development lifecycle. DE enables the developing, tracking, and sharing system data, models, and other related artifacts in a digital environment accessible to all necessary stakeholders. The DE environment provides an integrated electronic repository that enables traceability between design, engineering, and sustainment artifacts. The DE activities' primary objective is to develop a set of integrated, coherent, and consistent system models for the program. It is envisioned to provide a collaborative information-sharing environment for various stakeholders, including operational users, acquisition personnel, engineering personnel, and logistics and sustainment personnel. Examining the processes that DE can support in the systems engineering life cycle (SELC) is a primary step in the DE adoption and implementation journey. Through an analysis of the U.S Department of Defense’s (DoD) Office of the Secretary of Defense (OSD’s) Digital Engineering Strategy and their implementation, examples of DE implementation by the industry and technical organizations, this paper will provide descriptions of the current DE processes and best practices of implementing DE across an enterprise. This will help identify the capabilities, environment, and infrastructure needed to develop a potential roadmap for implementing DE practices consistent with its business strategy. A capability maturity matrix will be provided to assess the organization’s DE maturity emphasizing how all the SELC elements interlink to form a cohesive ecosystem. If implemented, DE can increase efficiency and improve the systems engineering processes' quality and outcomes.

Keywords: digital engineering, digital environment, digital maturity model, single source of truth, systems engineering life-cycle

Procedia PDF Downloads 92
4307 The Impact of Smartphone Applications on Consumer Attitude towards Brands

Authors: Nikita Bharadia, Vikas Gupta, Sushant Koshy

Abstract:

Mobile phone applications (“apps”) have generated substantial interest among marketers and researchers because of the developments in the smartphone technology and the availability of affordable phones to a large number of consumers. Apps are enabling brands to engage with consumers at any time and any place. This study utilizes a pre-test/post-test experimental design to determine if apps can have a persuasive impact on the consumer attitude towards the brand and her purchase intention. The study also tests the impact of informational vs. interactive style of apps on categories with high and low level of involvement. The results show that for high involvement brands, consumers have a predetermined brand image and apps that satisfy consumer needs through an interactive interface can increase purchase intention. For low involvement brands, while informational apps do not create substantial engagement, interactive apps can increase consumer focus on the brand and establish personal connect with the consumers. This has a positive impact in the attitude towards the brand. These results suggest that understanding how to maximize the consumer interaction with mobile phone apps will be a key topic of future research. This research indicates that managers need to evaluate the how apps can solve consumer needs before investing resources towards digital marketing campaign for their brands, following the global trend to capitalize on the digital platforms.

Keywords: App execution style, high and low involvement categories, mobile marketing, smartphone applications

Procedia PDF Downloads 398
4306 Film Therapy on Adolescent Body Image: A Pilot Study

Authors: Sonia David, Uma Warrier

Abstract:

Background: Film therapy is the use of commercial or non-commercial films to enhance healing for therapeutic purposes. Objectives: The mixed-method study aims to evaluate the effect of film-based counseling on body image dissatisfaction among adolescents to precisely ascertain the cause of the alteration in body image dissatisfaction due to the said intervention. Method: The one group pre-test post-test research design study using inferential statistics and thematic analysis is based on a pre-test post-test design conducted on 44 school-going adolescents between 13 and 17. The Body Shape Questionnaire (BSQ- 34) was used as a pre-test and post-test measure. The film-based counseling intervention model was used through individual counseling sessions. The analysis involved paired sample t-test used to examine the data quantitatively, and thematic analysis was used to evaluate qualitative data. Findings: The results indicated that there is a significant difference between the pre-test and post-test means. Since t(44)= 9.042 is significant at a 99% confidence level, it is ascertained that film-based counseling intervention reduces body image dissatisfaction. The five distinct themes from the thematic analysis are “acceptance, awareness, empowered to change, empathy, and reflective.” Novelty: The paper originally contributes to the repertoire of research on film therapy as a successful counseling intervention for addressing the challenges of body image dissatisfaction. This study also opens avenues for considering alteration of teaching pedagogy to include video-based learning in various subjects.

Keywords: body image dissatisfaction, adolescents, film-based counselling, film therapy, acceptance and commitment therapy

Procedia PDF Downloads 294
4305 Adopt and Apply Research-Supported Standards and Practices to Ensure Quality for Online Education and Digital Learning at Course, Program and Institutional Levels

Authors: Yaping Gao

Abstract:

With the increasing globalization of education and the continued momentum and wider adoption of online and digital learning all over the world, post pandemic, how could best practices and extensive experience gained from the higher education community over the past few decades be adopted and adapted to benefit international communities, which can be vastly different culturally and pedagogically? How can schools and institutions adopt, adapt and apply these proven practices to develop strategic plans for digital transformation at institutional levels, and to improve or create quality online or digital learning environments at course and program levels to help all students succeed? The presenter will introduce the primary components of the US-based quality assurance process, including : 1) five sets of research-supported standards to guide the design, development and review of online and hybrid courses; 2) professional development offerings and pathways for administrators, faculty and instructional support staff; 3) a peer-review process for course/program reviews resulting in constructive recommendations for continuous improvement, certification of quality and international recognition; and 4) implementation of the quality assurance process on a continuum to program excellence, achievement of institutional goals, and facilitation of accreditation process and success. Regardless language, culture, pedagogical practices, or technological infrastructure, the core elements of quality teaching and learning remain the same across all delivery formats. What is unique is how to ensure quality of teaching and learning in online education and digital learning. No one knows all the answers to everything but no one needs to reinvent the wheel either. Together the international education community can support and learn from each other to achieve institutional goals and ensure all students succeed in the digital learning environments.

Keywords: Online Education, Digital Learning, Quality Assurance, Standards and Best Practices

Procedia PDF Downloads 25
4304 Implementation of Achterbahn-128 for Images Encryption and Decryption

Authors: Aissa Belmeguenai, Khaled Mansouri

Abstract:

In this work, an efficient implementation of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written by MATLAB.7.5. At first two different original images are used for validate the proposed design. Then our developed program was used to transform the original images data into image digits file. Finally, we used our implemented program to encrypt and decrypt images data. Several tests are done for proving the design performance including visual tests and security analysis; we discuss the security analysis of the proposed image encryption scheme including some important ones like key sensitivity analysis, key space analysis, and statistical attacks.

Keywords: Achterbahn-128, stream cipher, image encryption, security analysis

Procedia PDF Downloads 532
4303 Application of Semantic Technologies in Rapid Reconfiguration of Factory Systems

Authors: J. Zhang, K. Agyapong-Kodua

Abstract:

Digital factory based on visual design and simulation has emerged as a mainstream to reduce digital development life cycle. Some basic industrial systems are being integrated via semantic modelling, and products (P) matching process (P)-resource (R) requirements are designed to fulfill current customer demands. Nevertheless, product design is still limited to fixed product models and known knowledge of product engineers. Therefore, this paper presents a rapid reconfiguration method based on semantic technologies with PPR ontologies to reuse known and unknown knowledge. In order to avoid the influence of big data, our system uses a cloud manufactory and distributed database to improve the efficiency of querying meeting PPR requirements.

Keywords: semantic technologies, factory system, digital factory, cloud manufactory

Procedia PDF Downloads 487
4302 A Study on Real-Time Fluorescence-Photoacoustic Imaging System for Mouse Thrombosis Monitoring

Authors: Sang Hun Park, Moung Young Lee, Su Min Yu, Hyun Sang Jo, Ji Hyeon Kim, Chul Gyu Song

Abstract:

A near-infrared light source used as a light source in the fluorescence imaging system is suitable for use in real-time during the operation since it has no interference in surgical vision. However, fluorescence images do not have depth information. In this paper, we configured the device with the research on molecular imaging systems for monitoring thrombus imaging using fluorescence and photoacoustic. Fluorescence imaging was performed using a phantom experiment in order to search the exact location, and the Photoacoustic image was in order to detect the depth. Fluorescence image obtained when evaluated through current phantom experiments when the concentration of the contrast agent is 25μg / ml, it was confirmed that it looked sharper. The phantom experiment is has shown the possibility with the fluorescence image and photoacoustic image using an indocyanine green contrast agent. For early diagnosis of cardiovascular diseases, more active research with the fusion of different molecular imaging devices is required.

Keywords: fluorescence, photoacoustic, indocyanine green, carotid artery

Procedia PDF Downloads 601
4301 Reactive and Concurrency-Based Image Resource Management Module for iOS Applications

Authors: Shubham V. Kamdi

Abstract:

This paper aims to serve as an introduction to image resource caching techniques for iOS mobile applications. It will explain how developers can break down multiple image-downloading tasks concurrently using state-of-the-art iOS frameworks, namely Swift Concurrency and Combine. The paper will explain how developers can leverage SwiftUI to develop reactive view components and use declarative coding patterns. Developers will learn to bypass built-in image caching systems by curating the procedure to implement a swift-based LRU cache system. The paper will provide a full architectural overview of a system, helping readers understand how mobile applications are designed professionally. It will cover technical discussion, helping readers understand the low-level details of threads and how they can switch between them, as well as the significance of the main and background threads for requesting HTTP services via mobile applications.

Keywords: main thread, background thread, reactive view components, declarative coding

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4300 Unsupervised Feature Learning by Pre-Route Simulation of Auto-Encoder Behavior Model

Authors: Youngjae Jin, Daeshik Kim

Abstract:

This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

Procedia PDF Downloads 446