AN ALGORITHM FOR GENERATING NATURAL COLOR IMAGES FROM FALSE COLOR USING SPECTRAL TRANSFORMATION TECHNIQUE WITH HIGHER POLYNOMIAL ORDER

Satellite imageries in True color composite or Natural Color composite (NCC) serves the best combination for visual interpretation. Red, Green and Infrared channels form false color composite which might not be as useful as NCC to a non-remote sensing professional. As blue band is affected by large atmospheric scattering, satellites like IRS-LISS IV, SPOT do not have blue band. To generate NCC from such satellite data blue band must be simulated. Existing algorithms of spectral transformation do not provide robust coefficients leading to wrong NCC colors especially in water bodies. To achieve more robust coefficients, we have proposed new algorithm to generate NCC for IRS-LISS IV data using second order polynomial regression technique. Second order polynomial transformation functions consider even minor variability present in the image as compared to 1st order so that the derived coefficients are adjustable to accommodate spatial and temporal variability while generating NCC. In this study, Sentinel-2 image was used for deriving coefficients with blue band as dependent and green, red and infrared as independent variables. Simulated Sentinel band showed high accuracy with correlation of 0.93 and 0.97 for two test sites. Using the same coefficients, blue band was simulated for LISS-IV which also showed good correlation of 0.90 with sentinel original blue band. On comparing LISS-IV simulated NCC with simulated NCC from other algorithms, it was observed that higher order polynomial transformation was able to achieve higher accuracy especially for water bodies where expected color is green. Thus, proposed algorithms can be used for transforming false color image to natural color images

Handbook of Optical and Laser Scanning

From its initial publication titled Laser Beam Scanning in 1985 to Handbook of Optical and Laser Scanning, now in its second edition, this reference has kept professionals and students at the forefront of optical scanning technology. Carefully and meticulously updated in each iteration, the book continues to be the most comprehensive scanning resource on the market. It examines the breadth and depth of subtopics in the field from a variety of perspectives. The Second Edition covers: Technologies such as piezoelectric devices Applications of laser scanning such as Ladar (laser radar) Underwater scanning and laser scanning in CTP As laser costs come down, and power and availability increase, the potential applications for laser scanning continue to increase. Bringing together the knowledge and experience of 26 authors from England, Japan and the United States, the book provides an excellent resource for understanding the principles of laser scanning. It illustrates the significance of scanning in society today and would help the user get started in developing system concepts using scanning. It can be used as an introduction to the field and as a reference for persons involved in any aspect of optical and laser beam scanning

Handbook of Optical and Laser Scanning

From its initial publication titled Laser Beam Scanning in 1985 to Handbook of Optical and Laser Scanning, now in its second edition, this reference has kept professionals and students at the forefront of optical scanning technology. Carefully and meticulously updated in each iteration, the book continues to be the most comprehensive scanning resource on the market. It examines the breadth and depth of subtopics in the field from a variety of perspectives. The Second Edition covers: Technologies such as piezoelectric devices Applications of laser scanning such as Ladar (laser radar) Underwater scanning and laser scanning in CTP As laser costs come down, and power and availability increase, the potential applications for laser scanning continue to increase. Bringing together the knowledge and experience of 26 authors from England, Japan and the United States, the book provides an excellent resource for understanding the principles of laser scanning. It illustrates the significance of scanning in society today and would help the user get started in developing system concepts using scanning. It can be used as an introduction to the field and as a reference for persons involved in any aspect of optical and laser beam scanning

Modeling Content Lifespan in Online Social Networks Using Data Mining

Online Social Networks (OSNs) are integrated into business, entertainment, politics, and education; they are integrated into nearly every facet of our everyday lives. They have played essential roles in milestones for humanity, such as the social revolutions in certain countries, to more day-to-day activities, such as streaming entertaining or educational materials. Not surprisingly, social networks are the subject of study, not only for computer scientists, but also for economists, sociologists, political scientists, and psychologists, among others. In this dissertation, we build a model that is used to classify content on the OSNs of Reddit, 4chan, Flickr, and YouTube according the types of lifespan their content have and the popularity tiers that the content reaches. The proposed model is evaluated using 10-fold cross-validation, using data mining techniques of Sequential Minimal Optimization (SMO), which is a support vector machine algorithm, Decision Table, Naïve Bayes, and Random Forest. The run times and accuracies are compared across OSNs, models, and data mining algorithms. The peak/death category of Reddit content can be classified with 64% accuracy. The peak/death category of 4Chan content can be classified with 76% accuracy. The peak/death category of Flickr content can classified with 65% accuracy. We also used 10-fold cross-validation to measure the accuracy in which the popularity tier of content can be classified. The popularity tier of content on Reddit can be classified with 84% accuracy. The popularity tier of content on 4chan can be classified with 70% accuracy. The popularity tier of content on Flickr can be classified with 66% accuracy. The popularity tier of content on YouTube can be classified with only 48% accuracy. Our experiments compared the runtimes and accuracy of SMO, Naïve Bayes, Decision Table, and Random Forest to classify the lifespan of content on Reddit, 4chan, and Flickr as well as classify the popularity tier of content on Reddit, 4chan, Flickr, and YouTube. The experimental results indicate that SMO is capable of outperforming the other algorithms in runtime across all OSNs. Decision Table has the longest observed runtimes, failing to complete analysis before system crashes in some cases. The statistical analysis indicates, with 95% confidence, there is no statistically significant difference in accuracy between the algorithms across all OSNs. Reddit content was shown, with 95% confidence, to be the OSN least likely to be misclassified. All other OSNs, were shown to have no statistically significant difference in terms of their content being more or less likely to be misclassified when compared pairwise with each other

Constraints and opportunities for increasing the adoption of technologies for reducing postharvest maize losses in Sub-Saharan Africa : a case study of Zambia

The annual global food wastage of 1.3 billion tons valued at US$2.6 trillion impedes food security and precipitates climate change. There is a need to increase food production to feed the estimated 9.1 billion people by 2050. Grain losses in sub-Saharan Africa are about 50$ 4 billion. Reducing food wastage is one approach to increase food availability. The inadequacy of information on postharvest losses makes Zambia suitable for such a study. Despite the availability of technologies for reducing postharvest losses, their adoption remains low among smallholder farmers in Zambia. The study used the interpretive paradigm to investigate and explain the factors responsible for the low technology adoption by farmers. Empirical data was collected using the case study strategy. The study adopted the Unified Theory of Acceptance and Use of Technology framework. Data collected from 100 respondents was analysed using the Statistical Package for Social Scientists and the Grounded Theory approach. The study findings are presented as factors responsible for the low adoption of technologies for reducing postharvest maize losses by farmers in Zambia. These factors include lack of information and knowledge of the available technologies and associated benefits, perceived cost, non-availability and challenges of operating the technologies. With support from literature the study findings have been used in developing the CAD and Cooperative Postharvest Management Models for increasing technology adoption. In terms of contribution to knowledge and practice the study played a role in developing the Food Loss and Waste Accounting and Reporting Standard. Furthermore, it strengthened the food and income security of farmers and grain traders in the region through capacity building. Additionally, it helped to increase the number of farmers using the hermetic storage technology. The study also enriched the database on the prevalence of the larger grain borer in Zambia

Laser Scanner Technology

Laser scanning technology plays an important role in the science and engineering arena. The aim of the scanning is usually to create a digital version of the object surface. Multiple scanning is sometimes performed via multiple cameras to obtain all slides of the scene under study. Usually, optical tests are used to elucidate the power of laser scanning technology in the modern industry and in the research laboratories. This book describes the recent contributions reported by laser scanning technology in different areas around the world. The main topics of laser scanning described in this volume include full body scanning, traffic management, 3D survey process, bridge monitoring, tracking of scanning, human sensing, three-dimensional modelling, glacier monitoring and digitizing heritage monuments

Physiological constraints on the ecology of activity-limited ectotherms

Organismal exchanges of heat, water, and metabolizable energy with their environment are important influences on their behavior, physiology and, life history. Where extreme climates and resource-poor environments restrict an organism‘s overall activity budget, physiology—through performance, tolerance, acclimation, and trade-offs—becomes a primary influence on that organism‘s ecology. Vertebrate ectotherms exemplify these physiological constraints because their body temperatures are closely tied to thermal and hydric exchanges with their environment; they are typically highly tolerant of a broad range of conditions; and they exhibit boom-and-bust cycles related to release from constraints. This dissertation examines physiological constraints on wood frogs (Rana sylvatica) at the extreme southwestern edge of their range, desert tortoises (Gopherus agassizii) which spend >98% of their lives in burrows, and the eggs of leatherback turtles (Dermochelys coriacea) which incubate for months on a tropical beach during the dry season. The distribution of microhabitats available to each focal ectotherm delineated where and when these organisms could be surface-active, what constituted adequate refugia for intolerable surface periods, and why these activity-limited organisms behave differently from conspecifics elsewhere. Direct measurements of physiological performance (metabolic rates, locomotion) over the focal organism‘s tolerated range of body temperatures and hydrations assessed the consequences of thermal and hydric exchanges with suboptimal microhabitats. These exercises constitute a quantification of important influences on the physiological ecology of activity-limited vertebrate ectotherms. Comparative analysis of the allometry of physiological traits in a variety of mammals served to elucidate the functional and phylogenetic constraints on physiological adaptation. This quantitative and model-based approach is useful for quantifying risk (e.g., desiccation risk), estimating processes that are hard to measure (e.g., metabolic heating of sea turtle eggs buried 1 m deep in sand), and predicting responses to future changes (e.g., global warming). These qualities recommend this approach as a practical tool in conservation biology.Ph.D., Environmental Science -- Drexel University, 201

THE SOCIAL MEDIA IMAGE: MODES OF VISUAL ORDERING ON SOCIAL MEDIA

My dissertation considers the organization of large sets of user-generated photographs across social media platforms, and delineates the ways in which time and place are mediated through their presentation and analyses. Addressing the unprecedented scale of social media visual expressions, together with their implementation, structure and presentation within specific media platforms, I examine how visual social media data is processed, structured, and presented, and theorize the consequences of these forms for the ways we culturally understand and experience contemporary visual information. Taking an integrated approach, this work offers a qualitative and quantitative analysis, and draws on methodologies from media theory, information science, software studies, art history, cultural studies, and computer science. I combine distant critical reading of larger organizational patterns and their cultural meanings (studying visual arrangement in exiting platforms, experimental computational research, and artistic works) with a close analytical reading of groups of photos, using computational and visualization tools. This twin process allows me to develop my theoretical understanding based on particular results, but also illustrates the problem that is the focus of this dissertation: how to understand new visual production scales, their organizations, and their interpretation

Cyberspace and Real-World Behavioral Relationships: Towards the Application of Internet Search Queries to Identify Individuals At-risk for Suicide

The Internet has become an integral and pervasive aspect of society. Not surprisingly, the growth of ecommerce has led to focused research on identifying relationships between user behavior in cyberspace and the real world - retailers are tracking items customers are viewing and purchasing in order to recommend additional products and to better direct advertising. As the relationship between online search patterns and real-world behavior becomes more understood, the practice is likely to expand to other applications. Indeed, Google Flu Trends has implemented an algorithm that accurately charts the relationship between the number of people searching for flu-related topics on the Internet, and the number of people who actually have flu symptoms in that region. Because the results are real-time, studies show Google Flu Trends estimates are typically two weeks ahead of the Center for Disease Control. The Air Force has devoted considerable resources to suicide awareness and prevention. Despite these efforts, suicide rates have remained largely unaffected. The Air Force Suicide Prevention Program assists family, friends, and co-workers of airmen in recognizing and discussing behavioral changes with at-risk individuals. Based on other successes in correlating behaviors in cyberspace and the real world, is it possible to leverage online activities to help identify individuals that exhibit suicidal or depression-related symptoms? This research explores the notion of using Internet search queries to classify individuals with common search patterns. Text mining was performed on user search histories for a one-month period from nine Air Force installations. The search histories were clustered based on search term probabilities, providing the ability to identify relationships between individuals searching for common terms. Analysis was then performed to identify relationships between individuals searching for key terms associated with suicide, anxiety, and post-traumatic stress