Search results for: resolution digital data

Authors: Francesca Spagnoli, Shenja van der Graaf, Pieter Ballon

Abstract:

Humans do not behave rationally. We are emotional, easily influenced by others, as well as by our context. The study of human behaviour became a supreme endeavour within many academic disciplines, including economics, sociology, and clinical and social psychology. Understanding what motivates humans and triggers them to perform certain activities, and what it takes to change their behaviour, is central both for researchers and companies, as well as policy makers to implement efficient public policies. While numerous theoretical approaches for diverse domains such as health, retail, environment have been developed, the methodological models guiding the evaluation of such research have reached for a long time their limits. Within this context, digitisation, the Information and communication technologies (ICT) and wearable, the Internet of Things (IoT) connecting networks of devices, and new possibilities to collect and analyse massive amounts of data made it possible to study behaviour from a realistic perspective, as never before. Digital technologies make it possible to (1) capture data in real-life settings, (2) regain control over data by capturing the context of behaviour, and (3) analyse huge set of information through continuous measurement. Within this complex context, this paper describes a new framework for initiating behavioural change, capitalising on the digital developments in applied research projects and applicable both to academia, enterprises and policy makers. By applying this model, behavioural research can be conducted to address the issues of different domains, such as mobility, environment, health or media. The Modular Behavioural Analysis Approach (MBAA) is here described and firstly validated through a concrete use case within the domain of health. The results gathered have proven that disclosing information about health in connection with the use of digital apps for health, can be a leverage for changing behaviour, but it is only a first component requiring further follow-up actions. To this end, a clear definition of different 'behavioural profiles', towards which addressing several typologies of interventions, it is essential to effectively enable behavioural change. In the refined version of the MBAA a strong focus will rely on defining a methodology for shaping 'behavioural profiles' and related interventions, as well as the evaluation of side-effects on the creation of new business models and sustainability plans.

Keywords: behavioural change, framework, health, nudging, sustainability

Procedia PDF Downloads 222

Authors: Peter U. Eze, P. Udaya, Robin J. Evans

Abstract:

Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

Procedia PDF Downloads 194

Authors: Yaping Gao

Abstract:

With the increasing globalization of education and the continued momentum and wider adoption of online education and digital learning all over the world, post pandemic, it is crucial that best practices and extensive experience and knowledge gained from the higher education community over the past few decades be adopted and adapted to benefit the broader international communities, which can be vastly different culturally and pedagogically. Schools and institutions worldwide should consider to adopt, adapt and apply these proven practices to develop strategic plans for digital transformation at institutional levels, and to improve or develop 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 standards, best practices, online teaching and learning

Procedia PDF Downloads 29

Authors: Renkai Wang, Tingcun Wei

Abstract:

In this paper, a digital control algorithm based on delta-operator is presented for high-frequency digitally-controlled DC-DC switching converters. The stability and the controlling accuracy of the DC-DC switching converters are improved by using the digital control algorithm based on delta-operator without increasing the hardware circuit scale. The design method of voltage compensator in delta-domain using PID (Proportion-Integration- Differentiation) control is given in this paper, and the simulation results based on Simulink platform are provided, which have verified the theoretical analysis results very well. It can be concluded that, the presented control algorithm based on delta-operator has better stability and controlling accuracy, and easier hardware implementation than the existed control algorithms based on z-operator, therefore it can be used for the voltage compensator design in high-frequency digitally- controlled DC-DC switching converters.

Keywords: digitally-controlled DC-DC switching converter, digital voltage compensator, delta-operator, finite word length, stability

Procedia PDF Downloads 412

Authors: Chan Ka Lok Sobel

Abstract:

The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

Procedia PDF Downloads 114

Authors: Annabelle Onyefulu-Kingston

Abstract:

One of the major purposes of AI today is to evaluate and analyze millions of micro and macro data in order to determine what is relevant in a particular case and proffer it in an adequate manner. Microdata, as far as it relates to AI in international arbitration, is the millions of key issues specifically mentioned by either one or both parties or by their counsels, arbitrators, or arbitral tribunals in arbitral proceedings. This can be qualifications of expert witness and admissibility of evidence, amongst others. Macro data, on the other hand, refers to data derived from the resolution of the dispute and, consequently, the final and binding award. A notable example of this includes the rationale of the award and specific and general damages awarded, amongst others. This paper aims to critically evaluate and analyze the possibility of technological inclusion in international arbitration. This research will be imploring the qualitative method by evaluating existing literature on the consequence of applying AI to both micro and macro data in international arbitration, and how this can be of assistance to parties, counsels, and arbitrators.

Keywords: AI-based technologies, algorithms, arbitrators, international arbitration

Procedia PDF Downloads 95

Authors: Ashwini Kumar, Vinod Nayak, Shankar M. Bakkannavar

Abstract:

The identification of humans is important in forensic investigations not only in living but also in dead, especially in cases of mass disorders. The procedure followed in dead known as post-mortem identification is a challenging task for the forensic pathologist. However, it is mandatory in terms of the law to fulfill the social norms. Many times, due to mutilation of body parts, the normal methods of identification using skeletal remains cannot be used in the process of identification. In such cases, the intact components of the skeletal remains or bony parts play an important role in identification. In these situations, digital forensics can come to our rescue. The authors hereby made a study for determination of sex based on nasal index by using (Big Bore 16 Slice) Multidetector Computed Tomography 2D Scans. The results are represented as a poster.

Keywords: sex determination, multidetector computed tomography, nasal index, digital forensic

Procedia PDF Downloads 398

Authors: Govind Kumar

Abstract:

The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

Procedia PDF Downloads 99

Authors: Isabell Koinig, Sandra Diehl

Abstract:

In recent years, the health-care context has not been left unaffected by technological developments. In recent years, the Internet of Medical Things (IoMT)has not only led to a collaboration between disease management and advanced care coordination but also to more personalized health care and patient empowerment. With more than 40 % of all health technology being IoMT-related by 2020, questions regarding privacy become more prevalent, even more so during COVID-19when apps allowing for an intensive tracking of people’s whereabouts and their personal contacts cause privacy advocates to protest and revolt. There is a widespread tendency that even though users may express concerns and fears about their privacy, they behave in a manner that appears to contradict their statements by disclosing personal data. In literature, this phenomenon is discussed as a privacy paradox. While there are some studies investigating the privacy paradox in general, there is only scarce research related to the privacy paradox in the health sector and, to the authors’ knowledge, no empirical study investigating young people’s attitudes toward data security when using wearables and health apps. The empirical study presented in this paper tries to reduce this research gap by focusing on the area of digital and mobile health. It sets out to investigate the degree of importance individuals attribute to protecting their privacy and individual privacy protection strategies. Moreover, the question to which degree individuals between the ages of 20 and 30 years are willing to grant commercial parties access to their private data to use digital health services and apps are put to the test. To answer this research question, results from 6 focus groups with 40 participants will be presented. The focus was put on this age segment that has grown up in a digitally immersed environment. Moreover, it is particularly the young generation who is not only interested in health and fitness but also already uses health-supporting apps or gadgets. Approximately one-third of the study participants were students. Subjects were recruited in August and September 2019 by two trained researchers via email and were offered an incentive for their participation. Overall, results indicate that the young generation is well informed about the growing data collection and is quite critical of it; moreover, they possess knowledge of the potential side effects associated with this data collection. Most respondents indicated to cautiously handle their data and consider privacy as highly relevant, utilizing a number of protective strategies to ensure the confidentiality of their information. Their willingness to share information in exchange for services was only moderately pronounced, particularly in the health context, since health data was seen as valuable and sensitive. The majority of respondents indicated to rather miss out on using digital and mobile health offerings in order to maintain their privacy. While this behavior might be an unintended consequence, it is an important piece of information for app developers and medical providers, who have to find a way to find a user base for their products against the background of rising user privacy concerns.

Keywords: digital health, privacy, privacy paradox, IoMT

Procedia PDF Downloads 136

Authors: Arjun Prakash, Samanvitha H.

Abstract:

BACKGROUND: Breast cancer is the commonest malignancy among women globally, with an estimated incidence of 2.3 million new cases as of 2020, representing 11.7% of all malignancies. As per Globocan data 2020, it accounted for 13.5% of all cancers and 10.6% of all cancer deaths in India. Early diagnosis and treatment can improve the overall morbidity and mortality, which necessitates the importance of differentiating benign from malignant breast masses. OBJECTIVE: The objective of the present study was to evaluate and compare the role of Digital Mammography (DM), B mode Ultrasound (USG), Shear Wave Elastography (SWE) and Strain Elastography (SE) in differentiating benign and malignant breast masses (ACR BI-RADS 3 - 5). Histo-Pathological Examination (HPE) was considered the Gold standard. MATERIALS & METHODS: We conducted a cross-sectional study on 53 patients with 64 breast masses over a period of 10 months. All patients underwent DM, USG, SWE and SE. These modalities were individually assessed to know their accuracy in differentiating benign and malignant masses. All Digital Mammograms were done using the Fujifilm AMULET Innovality Digital Mammography system and all Ultrasound examinations were performed on SAMSUNG RS 80 EVO Ultrasound system equipped with 2 to 9 MHz and 3 – 16 MHz linear transducers. All masses were subjected to HPE. Independent t-test and Chi-square or Fisher’s exact test were used to assess continuous and categorical variables, respectively. ROC analysis was done to assess the accuracy of diagnostic tests. RESULTS: Of 64 lesions, 51 (79.68%) were malignant and 13 (20.31%) (p < 0.0001) were benign. SE was the most specific (100%) (p < 0.0001) and USG (98%) (p < 0.0001) was the most sensitive of all the modalities. E max, E mean, E max ratio, E mean ratio and Strain Ratio of the malignant masses significantly differed from those of the benign masses. Maximum SWE value showed the highest sensitivity (88.2%) (p < 0.0001) among the elastography parameters. A combination of USG, SE and SWE had good sensitivity (86%) (p < 0.0001). CONCLUSION: A combination of USG, SE and SWE improves overall diagnostic yield in differentiating benign and malignant breast masses. Early diagnosis and treatment of breast carcinoma will reduce patient mortality and morbidity.

Keywords: digital mammography, breast cancer, ultrasound, elastography

Procedia PDF Downloads 106

Authors: Walid A. Attia, Taher M. Bazan, Fawzy Eltohamy, Mahmoud Fathy

Abstract:

System performance evaluation is an essential stage in the design of high-resolution satellite telescopes prior to the development process. In this paper, a system performance evaluation of a very high-resolution satellite telescope is investigated. The evaluated system has a Korsch optical scheme design. This design has been discussed in another paper with respect to three-mirror anastigmat (TMA) scheme design and the former configuration showed better results. The investigated system is based on the Korsch optical design integrated with a time-delay and integration charge coupled device (TDI-CCD) sensor to achieve a ground sampling distance (GSD) of 25 cm. The key performance metrics considered are the spatial resolution, the signal to noise ratio (SNR) and the total modulation transfer function (MTF) of the system. In addition, the national image interpretability rating scale (NIIRS) metric is assessed to predict the image quality according to the modified general image quality equation (GIQE). Based on the orbital, optical and detector parameters, the estimated GSD is found to be 25 cm. The SNR has been analyzed at different illumination conditions of target albedos, sun and sensor angles. The system MTF has been computed including diffraction, aberration, optical manufacturing, smear and detector sampling as the main contributors for evaluation the MTF. Finally, the system performance evaluation results show that the computed MTF value is found to be around 0.08 at the Nyquist frequency, the SNR value was found to be 130 at albedo 0.2 with a nadir viewing angles and the predicted NIIRS is in the order of 6.5 which implies a very good system image quality.

Keywords: modulation transfer function, national image interpretability rating scale, signal to noise ratio, satellite telescope performance evaluation

Procedia PDF Downloads 384

Authors: Dariusz Jemielniak

Abstract:

The near future will bring significant changes to contemporary organizations and management, because of the rapidly increasing role of immaterial goods and knowledge workers. The area of copyright, IP, as well as digital (non-material) goods and media redistribution seems to be one of the major challenges for the economy and society in general, and management and organization studies in particular. The proposed paper shows the views and perceptions of fairness of digital media sharing among Harvard Law School LL.M. students, basing on 50 qualitative interviews and 100 questionnaires. The researcher took an ethnographic approach to the study and joined the 2016 Harvard LL.M. Facebook group, which allowed natural socializing and joining for in-person events and private parties more easily. After making acquaintance with many of the students, the researcher conducted a quantitative questionnaire with 100 respondents, allowing to better understand the respondents perception of fairness in digital files sharing in different contexts (depending on the price of the media, its availability, regional licensing, status of the copyright holder, etc.). Basing on the results of the questionnaire, the researcher followed up with long-term, open ended, loosely structured ethnographic interviews (50 interviews were conducted) to further deepen the understanding of the results. The major finding of the study is that Harvard lawyers, in spite of the highest possible understanding of law, as well as professional standards, generally approve of digital piracy in certain contexts. Interestingly, they are also more likely to approve of it if they work for the government rather than the private sector. The conclusions from this study allow a better understanding of how ‘fairness’ is perceived by the younger generation of law professionals, and also open grounds for a more rational licensing policing.

Keywords: piracy, digital sharing, perception of fairness, legal profession

Procedia PDF Downloads 219

Authors: Cansu Bozer, Saadet İrem Turgut

Abstract:

Artificial intelligence (AI) has become one of the most important technologies of the digital age and is transforming many sectors, including education. The advantages offered by AI, such as automation, personalised learning, and data analytics, create new opportunities for both teachers and students in education systems. Preschool education plays a fundamental role in the cognitive, social, and emotional development of children. In this period, the foundations of children's creative thinking, problem-solving, and critical thinking skills are laid. Educational technologies, especially artificial intelligence-based applications, are thought to contribute to the development of these skills. For example, artificial intelligence-supported digital learning tools can support learning processes by offering activities that can be customised according to the individual needs of each child. However, the successful use of artificial intelligence-based applications in preschool education can be realised under the guidance of teachers who have the right knowledge about this technology. Therefore, it is of great importance to measure preschool teachers' awareness levels of artificial intelligence and to understand which variables affect this awareness. The aim of this study is to measure preschool teachers' awareness levels of artificial intelligence and to determine which factors are related to this awareness. In line with this purpose, teachers' level of knowledge about artificial intelligence, their thoughts about the role of artificial intelligence in education, and their attitudes towards artificial intelligence will be evaluated. The study will be conducted with 100 teachers working in Turkey using a descriptive survey model. In this context, ‘Artificial Intelligence Awareness Level Scale for Teachers’ developed by Ferikoğlu and Akgün (2022) will be used. The collected data will be analysed using SPSS (Statistical Package for the Social Sciences) software. Descriptive statistics (frequency, percentage, mean, standard deviation) and relationship analyses (correlation and regression analyses) will be used in data analysis. As a result of the study, the level of artificial intelligence awareness of preschool teachers will be determined, and the factors affecting this awareness will be identified. The findings obtained will contribute to the determination of studies that can be done to increase artificial intelligence awareness in preschool education.

Keywords: education, child development, artificial intelligence, preschool teachers

Procedia PDF Downloads 19

Authors: Matthias Haerri, Tobias Huettche, Clemens Kustner

Abstract:

This article discusses the impact of digitization on business valuation. In order to become and remain ‘digital’, investments are necessary whose return on investment (ROI) often remains vague. This uncertainty is contradictory for a valuation, that rely on predictable cash flows, fixed capital structures and the steady state. However digitisation does not make a company valuation impossible, but traditional approaches must be reconsidered. The authors identify four areas that are to be changing: (1) Tools instead of intuition - In the future, company valuation will neither be art nor science, but craft. This does not require intuition, but experience and good tools. Digital evaluation tools beyond Excel will therefore gain in importance. (2) Real-time instead of deadline - At present, company valuations are always carried out on a case-by-case basis and on a specific key date. This will change with the digitalization and the introduction of web-based valuation tools. Company valuations can thus not only be carried out faster and more efficiently, but can also be offered more frequently. Instead of calculating the value for a previous key date, current and real-time valuations can be carried out. (3) Predictive planning instead of analysis of the past - Past data will also be needed in the future, but its use will not be limited to monovalent time series or key figure analyses. With pictures of ‘black swans’ and the ‘turkey illusion’ it was made clear to us that we build forecasts on too few data points of the past and underestimate the power of chance. Predictive planning can help here. (4) Convergence instead of residual value - Digital transformation shortens the lifespan of viable business models. If companies want to live forever, they have to change forever. For the company valuation, this means that the business model valid on the valuation date only has a limited service life.

Keywords: business valuation, corporate finance, digitisation, disruption

Procedia PDF Downloads 133

Authors: Rihab Hamdi, Amel Hadri Hamida, Ouafae Bennis, Sakina Zerouali

Abstract:

This paper features a performance analysis and robustness assessment of a digitally controlled DC-DC three-cell buck converter associated in parallel, operating in continuous conduction mode (CCM), facing feeding parameters variation and loads disturbance. The control strategy relies on the continuous-time with an averaged modeling technique for high-frequency switching converter. The methodology is to modulate the complete design procedure, in regard to the existence of an instantaneous current operating point for designing the digital closed-loop, to the same continuous-time domain. Moreover, the adopted approach is to include a digital voltage control (DVC) technique, taking an account for digital control delays and sampling effects, which aims at improving efficiency and dynamic response and preventing generally undesired phenomena. The results obtained under load change, input change, and reference change clearly demonstrates an excellent dynamic response of the proposed technique, also as provide stability in any operating conditions, the effectiveness is fast with a smooth tracking of the specified output voltage. Simulations studies in MATLAB/Simulink environment are performed to verify the concept.

Keywords: continuous conduction mode, digital control, parallel multi-cells converter, performance analysis, power electronics

Procedia PDF Downloads 150

Authors: Tanapat Chongkamunkong

Abstract:

The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

Procedia PDF Downloads 198

Authors: Gerard Van Es

Abstract:

In this study, the use of a high resolution surface laser scanner to assess the micro texture of runway surfaces was investigated experimentally. Micro texture is one of the important surface components that helps to provide high braking friction between aircraft tires and a wet runway surface. Algorithms to derive different parameters that characterise micro texture was developed. Surface scans with a high resolution laser scanner were conducted on 40 different runway (like) surfaces. For each surface micro texture parameters were calculated from the laser scan data. These results were correlated with results obtained from a British pendulum tester that was used on the same surface. Results obtained with the British pendulum tester are generally considered to be indicative for the micro texture related friction characteristics. The results show that a meaningful correlation can be found between different parameters that characterise micro texture obtained with the laser scanner and the British pendulum tester results. Surface laser scanners are easier to operate and give more consistent results than a British pendulum tester. Therefore for airport operators surface laser scanners can be a useful tool to determine if their runway becomes slippery when wet due to a smooth micro texture.

Keywords: runway friction, micro texture, aircraft braking performance, slippery runways

Procedia PDF Downloads 121

Authors: Juan Francisco Reinoso Gordo, Francisco Javier Ariza-López, José Rodríguez Avi, Domingo Barrera Rosillo

Abstract:

The evaluation of the quality of a data product is based on the comparison of the product with a reference of greater accuracy. In the case of MDE data products, quality assessment usually focuses on positional accuracy and few studies consider other terrain characteristics, such as slope and orientation. The proposal that is made consists of evaluating the similarity of two DEMs (a product and a reference), through the joint analysis of the distribution functions of the variables of interest, for example, elevations, slopes and orientations. This is a multivariable approach that focuses on distribution functions, not on single parameters such as mean values or dispersions (e.g. root mean squared error or variance). This is considered to be a more holistic approach. The use of the Kolmogorov-Smirnov test is proposed due to its non-parametric nature, since the distributions of the variables of interest cannot always be adequately modeled by parametric models (e.g. the Normal distribution model). In addition, its application to the multivariate case is carried out jointly by means of a single test on the convolution of the distribution functions of the variables considered, which avoids the use of corrections such as Bonferroni when several statistics hypothesis tests are carried out together. In this work, two DEM products have been considered, DEM02 with a resolution of 2x2 meters and DEM05 with a resolution of 5x5 meters, both generated by the National Geographic Institute of Spain. DEM02 is considered as the reference and DEM05 as the product to be evaluated. In addition, the slope and aspect derived models have been calculated by GIS operations on the two DEM datasets. Through sample simulation processes, the adequate behavior of the Kolmogorov-Smirnov statistical test has been verified when the null hypothesis is true, which allows calibrating the value of the statistic for the desired significance value (e.g. 5%). Once the process has been calibrated, the same process can be applied to compare the similarity of different DEM data sets (e.g. the DEM05 versus the DEM02). In summary, an innovative alternative for the comparison of DEM data sets based on a multinomial non-parametric perspective has been proposed by means of a single Kolmogorov-Smirnov test. This new approach could be extended to other DEM features of interest (e.g. curvature, etc.) and to more than three variables

Keywords: data quality, DEM, kolmogorov-smirnov test, multivariate DEM comparison

Procedia PDF Downloads 115

Authors: Rene Hellmuth

Abstract:

Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring of the factory building is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A building information model (BIM) is the planning basis for rebuilding measures and becomes an indispensable data repository to be able to react quickly to changes. Use as a planning basis for restructuring measures in factories only succeeds if the BIM model has adequate data quality. Under this aspect and the industrial requirement, three data quality factors are particularly important for this paper regarding the BIM model: up-to-dateness, completeness, and correctness. The research question is: how can a BIM model be kept up to date with required data quality and which visualization techniques can be applied in a short period of time on the construction site during conversion measures? An as-is analysis is made of how BIM models and digital factory models (including laser scans) are currently being kept up to date. Industrial companies are interviewed, and expert interviews are conducted. Subsequently, the results are evaluated, and a procedure conceived how cost-effective and timesaving updating processes can be carried out. The availability of low-cost hardware and the simplicity of the process are of importance to enable service personnel from facility mnagement to keep digital factory models (BIM models and laser scans) up to date. The approach includes the detection of changes to the building, the recording of the changing area, and the insertion into the overall digital twin. Finally, an overview of the possibilities for visualizations suitable for construction sites is compiled. An augmented reality application is created based on an updated BIM model of a factory and installed on a tablet. Conversion scenarios with costs and time expenditure are displayed. A user interface is designed in such a way that all relevant conversion information is available at a glance for the respective conversion scenario. A total of three essential research results are achieved: As-is analysis of current update processes for BIM models and laser scans, development of a time-saving and cost-effective update process and the conception and implementation of an augmented reality solution for BIM models suitable for construction sites.

Keywords: building information modeling, digital factory model, factory planning, restructuring

Procedia PDF Downloads 114

Authors: Graciela Soares Marcelli, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Claudineia Brazil, Rafael Haag

Abstract:

The sun is a source of renewable energy, and its use as both a source of heat and light is one of the most promising energy alternatives for the future. To measure the thermal or photovoltaic systems a solar irradiation database is necessary. Brazil still has a reduced number of meteorological stations that provide frequency tests, as an alternative to the radio data platform, with reanalysis systems, quite significant. ERA-Interim is a global fire reanalysis by the European Center for Medium-Range Weather Forecasts (ECMWF). The data assimilation system used for the production of ERA-Interim is based on a 2006 version of the IFS (Cy31r2). The system includes a 4-dimensional variable analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the dataset is approximately 80 km at 60 vertical levels from the surface to 0.1 hPa. This work aims to make a comparative analysis between the ERA-Interim data and the data observed in the Solarimmetric Atlas of the State of Rio Grande do Sul, to verify its applicability in the absence of an observed data network. The analysis of the results obtained for a study region as an alternative to the energy potential of a given region.

Keywords: energy potential, reanalyses, renewable energy, solar radiation

Procedia PDF Downloads 164

Authors: Linyu Wang, Mingjun Zhu, Jianhong Xiang, Hanyu Jiang

Abstract:

Aiming at the problem that the spectral efficiency of hybrid precoding (HP) is too low in the current millimeter wave (mmWave) massive multiple input multiple output (MIMO) system, this paper proposes a digital joint equivalent channel hybrid precoding algorithm, which is based on the introduction of digital encoding matrix iteration. First, the objective function is expanded to obtain the relation equation, and the pseudo-inverse iterative function of the analog encoder is derived by using the pseudo-inverse method, which solves the problem of greatly increasing the amount of computation caused by the lack of rank of the digital encoding matrix and reduces the overall complexity of hybrid precoding. Secondly, the analog coding matrix and the millimeter-wave sparse channel matrix are combined into an equivalent channel, and then the equivalent channel is subjected to Singular Value Decomposition (SVD) to obtain a digital coding matrix, and then the derived pseudo-inverse iterative function is used to iteratively regenerate the simulated encoding matrix. The simulation results show that the proposed algorithm improves the system spectral efficiency by 10~20%compared with other algorithms and the stability is also improved.

Keywords: mmWave, massive MIMO, hybrid precoding, singular value decompositing, equivalent channel

Procedia PDF Downloads 96

Authors: Brock Buckingham, Zhe Lin, Wenxuan Guo

Abstract:

Accurate elevation data is critical in deriving topographic attributes for the precision management of crop inputs, especially water and nutrients. Traditional ground-based elevation data acquisition is time consuming, labor intensive, and often inconvenient at the field scale. Various unmanned aerial systems (UAS) provide the capability of generating digital elevation data from high-resolution images. The objective of this study was to compare the performance of two UAS with different global positioning system (GPS) receivers in determining elevation at the field scale. A DJI Phantom 4 Pro and a DJI Phantom 4 RTK(real-time kinematic) were applied to acquire images at three heights, including 40m, 80m, and 120m above ground. Forty ground control panels were placed in the field, and their geographic coordinates were determined using an RTK GPS survey unit. For each image acquisition using a UAS at a particular height, two elevation datasets were generated using the Pix4D stitching software: a calibrated dataset using the surveyed coordinates of the ground control panels and an uncalibrated dataset without using the surveyed coordinates of the ground control panels. Elevation values for each panel derived from the elevation model of each dataset were compared to the corresponding coordinates of the ground control panels. The coefficient of the determination (R²) and the root mean squared error (RMSE) were used as evaluation metrics to assess the performance of each image acquisition scenario. RMSE values for the uncalibrated elevation dataset were 26.613 m, 31.141 m, and 25.135 m for images acquired at 120 m, 80 m, and 40 m, respectively, using the Phantom 4 Pro UAS. With calibration for the same UAS, the accuracies were significantly improved with RMSE values of 0.161 m, 0.165, and 0.030 m, respectively. The best results showed an RMSE of 0.032 m and an R² of 0.998 for calibrated dataset generated using the Phantom 4 RTK UAS at 40m height. The accuracy of elevation determination decreased as the flight height increased for both UAS, with RMSE values greater than 0.160 m for the datasets acquired at 80 m and 160 m. The results of this study show that calibration with ground control panels improves the accuracy of elevation determination, especially for the UAS with a regular GPS receiver. The Phantom 4 Pro provides accurate elevation data with substantial surveyed ground control panels for the 40 m dataset. The Phantom 4 Pro RTK UAS provides accurate elevation at 40 m without calibration for practical precision agriculture applications. This study provides valuable information on selecting appropriate UAS and flight heights in determining elevation for precision agriculture applications.

Keywords: unmanned aerial system, elevation, precision agriculture, real-time kinematic (RTK)

Procedia PDF Downloads 164

Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

Abstract:

Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

Procedia PDF Downloads 297

Authors: Geng-Gui Wang, Chia-Hao Chang, Jee-Cheng Wu

Abstract:

A shoreline is a line where a body of water and the shore meet. It provides economic and social security to coastal habitations. However, shorelines face multiple threats due to both natural processes and man-made effects because of disasters, rapid urbanization, industrialization, and sand deposition and erosion, etc. In this study, we analyzed multi-temporal satellite images of the Yilan coast, Taiwan from 1978 to 2016, using the United States Geological Survey (USGS) Digital Shoreline Analysis System (DSAS), weather information (as rainfall records and typhoon routes), and man-made construction project data to explore the causes of shoreline changes. The results showed that the shoreline at Yilan coast is greatly influenced by typhoons and anthropogenic interventions.

Keywords: shoreline change, multi-temporal satellite, digital shoreline analysis system, DSAS, Yi-Lan coast

Procedia PDF Downloads 163

Authors: Marton Gergely

Abstract:

Digital experience goods, such as music and video, are readily available and easily accessible through a sundry of illegal mediums. Furthermore, the rate of music theft has been increasing at a seemingly unstoppable rate. Instead of studying the effect of copyright infringement on affected shareholders, this paper aims to examine the overall impact that digital music piracy has on society as a whole. Through a systems dynamics approach, an archetype is built to model the behavior of both legal and illegal music users. Additionally, the effects over time are considered. The conceptual model suggests that if piracy continues to grow at the current pace, industry shareholders will eventually lose the motivation to supply new music. In turn, this tragedy would affect not only the illegal players, but legal consumers as well, by means of a decrease in overall quality of life.

Keywords: music piracy, illegal downloading, tragedy of the commons, system archetypes

Procedia PDF Downloads 357

Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

Abstract:

We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

Procedia PDF Downloads 150

Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

Abstract:

Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

Procedia PDF Downloads 440

Authors: Ahmed Fradi

Abstract:

In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

Procedia PDF Downloads 541

Authors: Sadia Basar, Naila Habib, Awais Adnan

Abstract:

The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

Procedia PDF Downloads 376

Authors: Chunhong Zhao

Abstract:

Remotely sensed land surface temperature (LST) is vital to understand the land-atmosphere energy balance, hydrological cycle, and thus is widely used to describe the urban heat island (UHI) phenomenon. However, due to technical constraints, satellite thermal sensors are unable to provide LST measurement with both high spatial and high temporal resolution. Despite different downscaling techniques and algorithms to generate high spatiotemporal resolution LST. Four major metropolitan areas in Texas, USA: Dallas-Fort Worth, Houston, San Antonio, and Austin all demonstrate UHI effects. Different cities are expected to have varying SUHI effect during the urban development trajectory. With the help of the Landsat, ASTER, and MODIS archives, this study focuses on the spatial patterns of UHIs and the seasonal and annual variation of these metropolitan areas. With Gaussian model, and Local Indicators of Spatial Autocorrelations (LISA), as well as data fusion methods, this study identifies the hotspots and the trajectory of the UHI phenomenon of the four cities. By making comparison analysis, the result can help to alleviate the advent effect of UHI and formulate rational urban planning in the long run.

Keywords: spatiotemporal analysis, land surface temperature, urban heat island evaluation, metropolitan areas of Texas, USA

Procedia PDF Downloads 417