95 research outputs found

    Data Hiding and Its Applications

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    Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

    Cybersecurity: Past, Present and Future

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    The digital transformation has created a new digital space known as cyberspace. This new cyberspace has improved the workings of businesses, organizations, governments, society as a whole, and day to day life of an individual. With these improvements come new challenges, and one of the main challenges is security. The security of the new cyberspace is called cybersecurity. Cyberspace has created new technologies and environments such as cloud computing, smart devices, IoTs, and several others. To keep pace with these advancements in cyber technologies there is a need to expand research and develop new cybersecurity methods and tools to secure these domains and environments. This book is an effort to introduce the reader to the field of cybersecurity, highlight current issues and challenges, and provide future directions to mitigate or resolve them. The main specializations of cybersecurity covered in this book are software security, hardware security, the evolution of malware, biometrics, cyber intelligence, and cyber forensics. We must learn from the past, evolve our present and improve the future. Based on this objective, the book covers the past, present, and future of these main specializations of cybersecurity. The book also examines the upcoming areas of research in cyber intelligence, such as hybrid augmented and explainable artificial intelligence (AI). Human and AI collaboration can significantly increase the performance of a cybersecurity system. Interpreting and explaining machine learning models, i.e., explainable AI is an emerging field of study and has a lot of potentials to improve the role of AI in cybersecurity.Comment: Author's copy of the book published under ISBN: 978-620-4-74421-

    Trustworthiness in Mobile Cyber Physical Systems

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    Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

    NASA Tech Briefs, May 1994

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    Topics covered include: Robotics/Automation; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences; Life Sciences; Books and Reports

    2020 Program and Abstracts for the Celebration of Student Scholarship

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    Program and Abstracts from the Celebration of Student Scholarship held in the Spring of 2020

    A survey of the application of soft computing to investment and financial trading

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    Vegetation change detection and soil erosion risk assessment modelling in the Man River basin, Central India

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    Land use change directly increased soil erosion risk, which is a very sensitive environmental issue in Central India. To evaluate the response of land use changes on soil erosion risk, research was implemented using remote sensing techniques, coupled with ground information, to develop an integrated modelling approach to study the factors driving land use changes in the Man River basin, Central India. Results were used to assess the impact of land use change on soil erosion risk. First, a series of sub methods were applied to monitor and verify land use land cover change in the study area which included pre-processing, classification and assessment of land use transaction from 1971 to 2013 using Landsat time series imagery. Additionally, an independent spatial assessment of deforestation, forest degradation and responsible drivers for the period 2009-2013 was conducted to enable a deeper analysis of forestry activates using the GIS based direct interpretation approach. The research also developed a robust accuracy assessment method to check the quality of the 2009 and 2013 classification maps using good quality Google Earth TM imagery and a field measured GPS dataset. These approaches were largely based on the GOFC- GOLD (2010) and IPCC good recommendations for land use land cover mapping and verification. The information obtained from an accuracy assessment was also used to estimate deforestation area and construct confidence intervals that reflect the uncertainty of the area estimates obtained. Such analysis is rarely applied in current published verification assessments. In the second phase of the study, a Geo-spatial interface for process-based Water Erosion Prediction Project (GeoWEPP) was implemented, to estimate the response of land use and land cover change on soil erosion risk in several scenarios derived from both ground and satellite based precipitation, DEMs and vegetation change. GeoWEPP was used at the hillslope scale in three selected watersheds within the Man River basin using Landsat, LISSIII, Cartosat-1, ASTER, SRTM, TRMM and ground based datasets. The results highlight that the study developed a realistic approach using remote sensing techniques to understand the pattern and process of landscape change in the Man River basin and its response on soil erosion risk. Over the last four decades, forest and agriculture areas were found to be the most dynamic land use /land cover categories. During the last four decades, around 54200 ha (33.7 %) forest area has been decreased due to the expansion of agriculture, forest harvesting and infrastructure development. The direct interpretation approach estimated similar patterns of deforestation and forest degradation associated with iii drivers for the 2009 to 2013 time period, but this approach also provided more accurate and location specific information than automatic analysis. The overall correspondence between the map and reference data are a good measure for 2009 and 2013; 94.03 % and 92.8 % respectively. User‘s and producer‘s accuracies of individual classes range from 75 % to 99 %. Using the accuracy assessment data and a simple set of equations, an error-adjusted estimate of the area of deforestation was obtained (± 95% confidence interval) of 23382 ± 550 ha. The estimated average annual soil loss for all three watersheds is 21 T/ha which was found to be comparable to similar studies carried out in the study region. The highest soil loss rates occurred in areas of agriculture (301 T. /ha /yr) and fallow land (158 T/ha/yr), while the lowest rates were recorded in forest land (33.45 T/ha/yr). Agriculture extension (316.5 ha) due to forest harvesting (234 ha) in the last four decades is one of the significant drivers to speed up soil erosion (7.37 T/ha/yr.) in all three watersheds. The spatial pattern of erosion risk indicates that areas with forest cover have minimum rates of soil erosion, while areas with extensive human intervention such as agriculture and fallow land, have high estimated rates of soil erosion. The different DEMs generated varied topographic and hydrologic attributes, which in turn led to significantly different erosion simulations. GeoWEPP using Cartosat-1 (30 m) and SRTM (90 m) produced the most accurate estimation of soil loss which was close to similar already published studies in the area. TRMM rainfall data has good to use as a rainfall parameter for soil erosion risk mapping in study area. Overall, the integrated approach using remote sensing and GIS allowed a clear understanding of the factors that drive land use/land cover change to be developed and enabled the impact of this change on soil erosion risk in the Man River basin, Central India to be assessed

    Visual search and VDUS

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    This wide-ranging study explored various parameters of visual search in relation to computer screen displays. Its ultimate goal was to help identify factors which could result in improvements in commercially available displays within the 'real world’. Those improvements are generally reflected in suggestions for enhancing efficiency of locatabolity of information through an acknowledgement of the visual and cognitive factors involved. The thesis commenced by introducing an ergonomics approach to the presentation of information on VDUs. Memory load and attention were discussed. In the second chapter, literature on general and theoretical aspects of visual search (with particular regard for VDUs) was reviewed. As an experimental starting point, three studies were conducted involving locating a target within arrays of varying configurations. A model concerning visual lobes was proposed. Two text-editing studies were then detailed showing superior user performances where conspicuity and the potential for peripheral vision are enhanced. Relevant eye movement data was combined with a keystroke analysis derived from an automated protocol analyser. Results of a further search task showed icons to be more quickly located within an array than textual material. Precise scan paths were then recorded and analyses suggested greater systematicity of search strategies for complex items. This led on to a relatively 'pure' search study involving materials of varying spatial frequencies. Results were discussed in terms of verbal material generally being of higher spatial frequencies and how the ease of resolution and greater cues available in peripheral vision can result in items being accessed more directly. In the final (relatively applied) study, differences in eye movement indices were found across various fonts used. One main conclusion was that eye movement monitoring was a valuable technique within the visual search/VDU research area in illuminating precise details of performance which otherwise, at best, could only be inferred

    Attention Restraint, Working Memory Capacity, and Mind Wandering: Do Emotional Valence or Intentionality Matter?

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    Attention restraint appears to mediate the relationship between working memory capacity (WMC) and mind wandering (Kane et al., 2016). Prior work has identifed two dimensions of mind wandering—emotional valence and intentionality. However, less is known about how WMC and attention restraint correlate with these dimensions. Te current study examined the relationship between WMC, attention restraint, and mind wandering by emotional valence and intentionality. A confrmatory factor analysis demonstrated that WMC and attention restraint were strongly correlated, but only attention restraint was related to overall mind wandering, consistent with prior fndings. However, when examining the emotional valence of mind wandering, attention restraint and WMC were related to negatively and positively valenced, but not neutral, mind wandering. Attention restraint was also related to intentional but not unintentional mind wandering. Tese results suggest that WMC and attention restraint predict some, but not all, types of mind wandering
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