bluuebunny/crossref_metadata_2025 huggingface dataset:
A Publicly Verifiable Dynamic Secret Sharing Protocol for Secure and Dependable Data Storage in Cloud Computing
Authors: Kumar P. Syam , Ashok Marie Stanislas , Subramanian R.
Published: October 2012

Data storage is an important application of cloud computing, where the users can remotely store their data into the cloud. This new paradigm of data storage service also introduces security challenges, such as Confidentiality, Integrity and Availability of data. The protection of these issues in cloud is a very challenging and potentially formidable task, especially for the users with constrained resources. Therefore, an independent auditing service is required to address these issues of data stored in the cloud. The existing schemes may not scale well for this purpose. This paper proposes a publicly verifiable dynamic secret sharing scheme for the Availability, Integrity and Confidentiality of data. Their scheme takes advantages of both Secret Sharing and Tornado code which can achieve the computational security and maintain low communication overhead in terms of shortened data dispersing size. The authors’ model gives probabilistic proofs of Integrity of data by challenging random blocks from the server to reduce the computation and communication overhead, and also supports dynamic data operations to data shares in cloud using index table. Through extensive security analysis, their scheme can provide secure, dependable, and publicly verifiable cloud data storage in the Cloud against threats. Through the performance and experimental results, the authors prove that their scheme is efficient than existing schemes.
Both Hands’ Fingers’ Angle Calculation from Live Video
Authors: Chaudhary Ankit , Raheja Jagdish L. , Das Karen , Raheja Shekhar
Published: October 2012

In the last few years gesture recognition and gesture-based human computer interaction has gained a significant amount of popularity amongst researchers all over the world. It has a number of applications ranging from security to entertainment. Gesture recognition is a form of biometric identification that relies on the data acquired from the gesture depicted by an individual. This data, which can be either two-dimensional or three-dimensional, is compared against a database of individuals or is compared with respective thresholds based on the way of solving the riddle. In this paper, a novel method for angle calculation of both hands’ bended fingers is discussed and its application to a robotic hand control is presented. For the first time, such a study has been conducted in the area of natural computing for calculating angles without using any wired equipment, colors, marker or any device. The system deploys a simple camera and captures images. The pre-processing and segmentation of the region of interest is performed in a HSV color space and a binary format respectively. The technique presented in this paper requires no training for the user to perform the task.
Augmented Small-Scale Database to Improve the Performance of Eigenface Recognition Technique
Authors: Mousa Allam , Salameh Rana , Abu-Shmais Rawan
Published: October 2012

Eigenface recognition technique reserves limitations in achieving good performance. This includes the large-scale database required, its sensitivity to improper illumination, as well as to different expressions of a human face, and image background. This paper presents an efficient and accessible solution for some of these limitations by improving the database’s design. Face recognition accuracy has been enhanced via the inclusion of a modified version of the images in the database. Illumination and various face positions have been integrated into the already available small-scale database. Recognition is sensitive to the illuminated side of a face under consideration. Applying the proposed approach and choosing proper pre-processing values, has improved the system’s performance.
On Predicting the Results of Applying Workflow Management in a Healthcare Context
Authors: Chermin Bob , Frey Ingmar , Reijers Hajo , Smeets Harm
Published: October 2012

Even though workflow management systems are currently not being applied on a wide scale in healthcare settings, their benefits with respect to operational efficiency and reducing patient risk seem enticing. The authors show how an approach that is rooted in simulation can be useful to predict the benefits of using a workflow management system. The approach is discussed and its application is demonstrated in the setting of the pre-operative process as being executed in the Bronovo hospital. The approach is considered useful for other healthcare organizations in search for a better foundation for the application of workflow technology.
A Comprehensive Survey of Event Analytics
Authors: Gidwani T. , Argano M. J. , Yan W. , Issa F.
Published: October 2012

Analytics has emerged as an important area of study as it avoids further incidents or risks after the events have occurred; this is done by analysing computer events and making further statistics. The purpose of this survey is to gain knowledge for the authors’ own event knowledge database which will consist of how unusual events work and how they are related to other events. The algorithms mentioned in this paper have been used to build their future development, resulting in a knowledge database designed to be similar to an internet browser engine where it can search events and their relationships. The research and algorithms have helped the authors to decide on the technology they will be using for the knowledge database.
Effects of Redundancy and Paraphrasing in University Lessons
Authors: Paoletti Gisella , Bortolotti Elena , Zanon Francesca
Published: October 2012

This paper is about the use of a widespread teaching tool: the slide presentation used in face-to-face, system-paced university lessons. It is produced by lecturers to support students’ comprehension during listening; nevertheless it poses elaboration requests to the audience which should be taken into consideration at the planning stage and in formulating its verbal content. The paper reports the results of a survey conducted with 163 University students who were asked to listen to a lecture accompanied by a PowerPoint presentation, prepared according to the most frequent formats. The written presentation had 3 degrees of concision/redundancy: it had a fully redundant with the oral message, partially redundant (main points in key words), or had a different linguistic form (paraphrase of the message). Furthermore, information in written text and spoken message could have had the same order or they could be scrambled. The results showed that, subjectively, students judged comprehensible every kind of presentation. However, learning tests demonstrated that paraphrasing negatively affected learning, while changes in the order of presentation did not, at least in the synthetic main point – key word presentations. The study suggested that the concise, only partially redundant, presentation is the one which leads to better results, both in the ordered and in the scrambled version.
Peer Learning and Peer Assessment to Enhance Participation in Online Courses
Authors: Limone Pierpaolo
Published: October 2012

The essay discusses the development of a peer assessment approach in an online learning community composed of teachers enrolled in a course on Specific Learning Disabilities (SLD). The experience was prompted by the need to promote meaningful learning and online interaction among teachers, then collaborative assessment activities proved to be an efficient strategy to foster engagement.
Weblog
Authors: Baldassarre Michele
Published: October 2012

The internet and blogging has become the Agorà of the 21st century and, within such a context, regarded as a “recounting” technology with a double objective: “recounting about oneself to other people” and “recounting to oneself about oneself.” The “weblog” phenomenon accounts for the triumph of the principle of democracy in the Internet which is no longer considered as a “center” which provides information, but rather as a “many to many” branching system under which each user becomes at once the consumer and the producer of information, messages, and contents. This study demonstrates that weblogs are tools to account for an education opportunity since self-narration enables gives a form and a meaning to the continuity of one’s own life: an unrenouncable chance to uncover and make visible connections across the different “stances” of one’s soul. The authors present the case of an online diary with 224 posts (the blog of A.), analyzed with a set of linguistic and statistical software tools. Content analysis has been resorted to for assessing the narrative strategies used by A. to share his life experience with others through metaphors, punctuation marks, and syntactic structures. This demonstrates that the blog accounts for a training ground of the Self for people experiencing important and decisive times in their lives as it enhances the self-narrative skills of the internauts.
An Empirical Study of Determinants of E-Commerce Adoption in SMEs in Vietnam
Authors: Van Huy Le , Rowe Frantz , Truex Duane , Huynh Minh Q.
Published: October 2012

Experts and business pundits forecasted drastic changes in Vietnam’s fledgling e-commerce when the Southeast Asian country became an official member of the World Trade Organization (WTO) in 2007. Over the past few years, as part of the Reform – called Doi moi – some Vietnamese enterprises have adopted e-commerce and already benefitted from it. In this research, the authors adapt the Technology-Organization-Environment (TOE) framework and test a model of e-commerce adoption including numerous internal and external factors identified in empirical studies. The final sample of 926 small and medium-sized enterprises in Vietnam includes both adopter and non-adopter firms. The policy implications of this study on promoting e-commerce adoption by SMEs in transition economies, such as Vietnam, are discussed.
A Cross-Cultural Analysis of Communication Tools and Communication Outcomes
Authors: Hung Shin-Yuan , Kang Tsan-Ching , Yen David , Huang Albert , Chen Kuanchin
Published: October 2012

Computer mediated communication (CMC) technologies have benefited business organizations in many ways. Although there have been numerous studies on email use, studies have only begun to emerge regarding use patterns of instant messaging (IM). This study investigated the use of email and IM within two different cultural settings: United States and Taiwan. Students enrolled in MIS courses from each country were split randomly into the IM and email groups for a problem-solving assignment. The variations of communication outcomes (as measured in volume, quality, and use satisfaction), are checked against two categorical variables (i.e., culture and communication tools), and at the same time controlled for perception on tool ease of use. Results show that culture and communication tools jointly affect all three outcome variables individually. The main effects were also statistically significant for volume and quality, but not for satisfaction. Respondents from different cultures prefer different communication methods, which are also collectively constrained by other factors like preference over contextual information and social norms. Such a difference in media preference, combined with media traits jointly affects the outcomes of communication. Managerial implications are provided.
On-Line Course Registration Systems Usability
Authors: Tchouakeu Louis-Marie Ngamassi , Hills Michael K. , Jarrahi Mohammad Hossein , Du Honglu
Published: October 2012

Electronic course registration systems allow students to select courses and giving student to access course offerings through these on-line systems as well as the ability to complete various administrative functions allows for better management of curriculum decisions in the context of academic objectives. The objective of these systems is to make this process more convenient and easier to achieve which has been met with varying levels of success. This study looks closely at one particular system, the e-Lion system at the Pennsylvania State University. Data was collected using semi-structured interviews and an online survey. The findings are discussed through the lens of the Delone and McLeane (D&M) information systems success model and are of interest to business practitioners fielding on-line systems in the areas of e-commerce and e-learning as well as many others, providing considerable insight into the importance of system usability.
Software Project Costing
Authors: Edelist Liran , Gelbard Roy , Kantor Jeffrey
Published: October 2012

This study puts forward a generic and comprehensive costing framework for software projects that aims for simplicity. This is achieved by integrating commonly used CMMI (Capability Maturity Model Integration) and PMBOK (Project Management Body of Knowledge) costing concepts in a broader organizational context. The costing framework comprises three layers: costing targets, costing activities, and policy evaluation. While the first two layers are derived from commonly used software engineering elements, the third integrates an organizational perspective through software engineers, project managers, accountants and top management. Employment of CMMI and PMBOK standards allows for easy adoption of the proposed model by organizations that are already relying on these standards.
An introduction to the theological politico-ethical thinking of Koos Vorster
Authors: Van Wyk Jan H. , Vorster Nico
Published: October 2012

Koos Vorster had a productive career as theologian and published on a wide variety of subjects. However, he will especially be remembered for his contribution to political and social ethics. This article discussed his theological politico-ethical thinking. Firstly, this article examined his epistemology, with special reference to his revelational-historical approach, his hermeneutics, preference of deontological ethics and his renouncement of ethical absolutism, which characterises fundamentalist approaches to ethics. Secondly, it examined his views on Apartheid and the ‘struggle’ in the 1970s and 1980s. Vorster renounced Apartheid and pleaded for non-violent change brought about by an evangelical change of hearts and attitude that had to be accompanied with real efforts to address poverty and unjust structures. Finally, the article discussed his views on human dignity, human rights and relations between the state and religion, as well as his views on society and economics.‘n Inleiding tot die teologiese, politieke en etiese denke van Koos Vorster. Koos Vorster het ‘n besonderse produktiewe en vrugbare akademiese loopbaan gehad en oor ‘n verskeidenheid van onderwerpe gepubliseer. Hy sal egter veral onthou word vir sy bydrae tot politieke en sosiale etiek. Hierdie artikel ondersoek die teologies-polities etiese denke van Koos Vorster. Die  eerste  deel  bespreek  sy  epistemologiese  uitgangspunte,  waaronder  sy  omvattende openbarings-historiese benadering, sy hermeneutiek, voorliefde vir ‘n deontologiese etiek, en sy afwysing van etiese absolutisme soos veral vergestalt in fundamentalistiese benaderings tot die etiek. Die tweede deel bespreek sy houding teenoor Apartheid en die ‘struggle’ in die 1970s en 1980s. Vorster het die vergrype van Apartheid geïdentifiseer en aangespreek, maar terselfdertyd geweldadige verset verwerp, en ‘n evangeliese verandering van gesindhede bepleit wat gepaard gaan met die opheffing van onderdrukte gemeenskappe en ontbinding van onregverdige strukture. Die laaste deel van die artikel bespreek Vorster se sienings oor menswaardigheid, menseregte, die verhouding tussen kerk en godsdiens, asook sy siening oor die samelewing en die ekonomie.
Gaining Feedback from People with Learning Disabilities
Authors: Ball Jo , Shanks Andrew
Published: October 2012

Introduction:

Person-centred approaches and service user involvement are integral to occupational therapy, but evidence is lacking about how occupational therapists working in the field of learning disabilities gather feedback from service users.

Method:

This research aimed to explore how members of the College of Occupational Therapists Specialist Section — People with Learning Disabilities gathered feedback from their service users. Questionnaires were completed by 70 occupational therapists and 12 of them participated in semi-structured interviews.

Findings:

The occupational therapists were passionate about service user feedback, but they were likely to use informal methods rather than established methods with a more robust evidence base. Despite research indicating greater potential for bias when asking people with learning disabilities for feedback, almost half the participants did not take measures to reduce this. The interviews suggest that this is due to service pressures, lack of confidence and the complexity of service users' needs.

Conclusion:

Occupational therapists need to do more to gain feedback from people with learning disabilities. Further research is required to establish the most effective way of doing this.
Internet Poker: Examining Motivations, Behaviors, Outcomes, and Player Traits using Structural Equations Analysis
Authors: Smith Michael D. , Rousu Matthew C. , Dion Paul
Published: October 2012

Hypotheses explaining outcomes from internet poker were tested by using structural equations modeling: Personal characteristics and traits were proposed to influence motivation, leading to gaming behavior and then to outcomes. One hundred ninety-four participants from an internet poker forum completed online assessment. Three separate outcomes were supported: social-emotional gains, monetary winnings/losses, and negative experiences. One third of the participants reported some negative outcomes and 12% said these were significant; two thirds indicated no negative outcomes. Problems were most linked to the trait of Neuroticism, younger age, and more hours played, but unrelated to amounts won or lost. Gaming for social-emotional benefits mediated fewer negative outcomes. Financial gain motivation was a key mediator for gaming behavior. Findings were consistent with research showing negative emotionality and youth to be associated with poor gambling outcomes. The model suggests concrete actions that can be taken to minimize problem gaming while maximizing healthier involvement with online poker.
La méthodologie au service de l'avancement des connaissances en matière de jeux de hasard et d'argent
Authors: Vitaro Frank
Published: October 2012

Cet article passe en revue trois méthodologies susceptibles de faire avancer les connaissances en matière de jeux de hasard et d'argent: la méthodologie longitudinale, la méthodologie expérimentale et la méthodologie génétique. Des exemples servent à illustrer comment ces méthodologies permettent: a) de documenter le développement des habitudes et des problèmes de jeu; b) d'identifier les facteurs de risque à présomption causale associés à leur apparition, à leur maintien ou à leur aggravation; c) d'explorer la signification de la cooccurrence des problèmes de jeu avec d'autres problèmes de santé mentale; d) d'analyser les possibles liens transactionnels entre les problèmes de jeu et d'autres problèmes d'adaptation; et, enfin, e) de dégager des leçons par rapport à la modélisation théorique et à l'intervention préventive.
Estimating Risk Attitudes in Conventional and Artefactual Lab Experiments: The Importance of the Underlying Assumptions
Authors: Drichoutis Andreas C. , Koundouri Phoebe
Published: October 2012

In this paper we assess the importance of sample type in the estimation of risk preferences. We elicit and compare risk preferences from student subjects and subjects drawn from the general population, using the multiple price list method devised by Holt and Laury in their paper Risk Aversion and Incentive Effects (2002). We find evidence suggesting that under rank dependent utility, students exhibit approximately risk neutral preferences while subjects drawn from the general population exhibit risk loving preferences. However, when we assume an incorrect characterization of risk preferences, in particular we adopt the framework of expected utility theory, our estimation results lead to erroneous inferences. In this case, students are on average risk averse, while subjects drawn from the general population exhibit risk neutrality. Our results have implications for economic policy making under uncertainty.
Collision dynamics and uptake of water on alcohol-covered ice
Authors: Thomson E. S. , Kong X. , Marković N. , Papagiannakopoulos P. , Pettersson J. B. C.
Published: October 2012

Abstract. Molecular scattering experiments are used to investigate water interactions with methanol and n-butanol covered ice between 155 K and 200 K. The inelastically scattered and desorbed products of an incident molecular beam are measured and analyzed to illuminate molecular scale processes. The residence time and uptake coefficients of water impinging on alcohol-covered ice are calculated. The surfactant molecules are observed to affect water transport to and from the ice surface in a manner that is related to the number of carbon atoms they contain. Butanol films are observed to reduce water uptake by ice by 20%, whereas methanol monolayers pose no significant barrier to water transport. Water colliding with methanol covered ice rapidly permeates the alcohol layer, but on butanol has mean surface lifetimes of ≲0.6 ms, enabling some molecules to thermally desorb before reaching the water ice underlying the butanol. These observations are put into the context of cloud and atmospheric scale processes, where such surfactant layers may affect a range of aerosol processes, and thus have implications for cloud evolution, the global water cycle, and long term climate.
Spatial scale dependency of the modelled climatic response to deforestation
Authors: Longobardi P. , Montenegro A. , Beltrami H. , Eby M.
Published: October 2012

Abstract. Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scale land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we determine effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is registered over low latitude deforested areas. Mid latitude SAT response is mixed. For all simulations deforested areas tend to become drier and have lower surface air temperature, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation, cause an increase in soil carbon large enough to generate a previously not reported net drawdown of CO2 from the atmosphere. Our results support previous indications of the importance of changes in cloud cover in the modelled temperature response to deforestation at low latitudes. They also show the complex interaction between soil carbon dynamics and climate and the role this plays on the climatic response to land cover change.
Response of Nodularia spumigena to pCO2 – Part 3: Turnover of phosphorus compounds
Authors: Unger J. , Endres S. , Wannicke N. , Engel A. , Voss M. , Nausch G. , Nausch M.
Published: October 2012

Abstract. Diazotrophic cyanobacteria often form extensive summer blooms in the Baltic Sea driving their environment into phosphate limitation. One of the main species is the heterocystous cyanobacterium Nodularia spumigena. N. spumigena exhibits accelerated uptake of phosphate through the release of the exoenzyme alkaline phosphatase that also serves as an indicator of the hydrolysis of dissolved organic phosphorus (DOP). The present study investigated the utilization of DOP and its compounds (e.g. ATP) by N. spumigena during growth under varying CO2 concentrations, in order to estimate potential consequences of ocean acidification on the cell's supply with phosphorus. Cell growth, phosphorus pool fractions, and four DOP-compounds (ATP, DNA, RNA, and phospholipids) were determined in three set-ups with different CO2 concentrations (341, 399, and 508 μatm) during a 15-day batch experiment. The results showed rapid depletion of dissolved inorganic phosphorus (DIP) in all pCO2 treatments while DOP utilization increased with elevated pCO2, in parallel with the growth stimulation of N. spumigena. During the growth phase, DOP uptake was enhanced by a factor of 1.32 at 399 μatm and of 2.25 at 508 μatm compared to the lowest pCO2 concentration. Among the measured DOP compounds, none was found to accumulate preferentially during the incubation or in response to a specific pCO2 treatment. However, at the beginning 61.9 ± 4.3% of the DOP were not characterized but comprised the most highly utilized fraction. This is demonstrated by the decrement of this fraction to 27.4 ± 9.9% of total DOP during the growth phase, especially in response to the medium and high pCO2 treatment. Our results indicate a stimulated growth of diazotrophic cyanobacteria at increasing CO2 concentrations that is accompanied by increasing utilization of DOP as an alternative P source.
On-line multistep-ahead inundation depth forecasts by recurrent NARX networks
Authors: Shen H.-Y. , Chang L.-C.
Published: October 2012

Abstract. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields, but relatively scant on flood inundation forecast. This study proposes a recurrent configuration of nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, to forecast multistep-ahead inundation depths in an inundation area. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modeling nonlinear dynamical systems. The models were trained and tested based on a large number of inundation data generated by a well validated two-dimensional simulation model at thirteen inundation-prone sites in Yilan County, Taiwan. We demonstrate that the R-NARX model can effectively inhibit error growth and accumulation when being applied to on-line multistep-ahead inundation forecasts over a long lasting forecast period. For comparison, a feedforward time-delay and an on-line feedback configuration of NARX networks (T-NARX and O-NARX) were performed. The results show that (1) T-NARX networks cannot make on-line forecasts due to unavailable inputs in the constructed networks even though they provide the best performances for reference only; and (2) R-NARX networks consistently outperform O-NARX networks and can be adequately applied to on-line multistep-ahead forecasts of inundation depths in the study area during typhoon events.
A GEO-VISUAL ANALYTICS APPROACH TO BIOLOGICAL SHEPHERDING: MODELLING ANIMAL MOVEMENTS AND IMPACTS
Authors: Benke K. K. , Sheth F. , Betteridge K. , Pettit C. J. , Aurambout J.-P.
Published: October 2012

Abstract. The lamb industry in Victoria is a significant component of the state economy with annual exports in the vicinity of $1 billion. GPS and visualisation tools can be used to monitor grazing animal movements at the farm scale and observe interactions with the environment. Modelling the spatial-temporal movements of grazing animals in response to environmental conditions provides input for the design of paddocks with the aim of improving management procedures, animal performance and animal welfare. The term "biological shepherding" is associated with the re-design of environmental conditions and the analysis of responses from grazing animals. The combination of biological shepherding with geo-visual analytics (geo-spatial data analysis with visualisation) provides a framework for improving landscape design and supports research in grazing behaviour in variable landscapes, heat stress avoidance behaviour during summer months, and modelling excreta distributions (with respect to nitrogen emissions and nitrogen return for fertilising the paddock). Nitrogen losses due to excreta are mainly in the form of gaseous emissions to the atmosphere and leaching into the groundwater. In this study, background and context are provided in the case of biological shepherding and tracking animal movements. Examples are provided of recent applications in regional Australia and New Zealand. Based on experimental data and computer simulation, and using data visualisation and feature extraction, it was demonstrated that livestock excreta are not always randomly located, but concentrated around localised gathering points, sometimes separated by the nature of the excretion. Farmers require information on the nitrogen losses in order to reduce emissions to meet local and international nitrogen leaching and greenhouse gas targets and to improve the efficiency of nutrient management.
MODELLING VAGUE KNOWLEDGE FOR DECISION SUPPORT IN PLANNING ARCHAEOLOGICAL PROSPECTIONS
Authors: Boos S. , Hornung S. , Müller H.
Published: October 2012

Abstract. Most archaeological predictive models lack significance because fuzziness of data and uncertainty in knowledge about human behaviour and natural processes are hardly ever considered. One possibility to cope with such uncertainties is utilization of probability based approaches like Bayes Theorem or Dempster-Shafer-Theory. We analyzed an area of 50 km2 in Rhineland Palatinate (Germany) near a Celtic oppidum by use of Dempster-Shafer's theory of evidence for predicting spatial probability distribution of archaeological sites. This technique incorporates uncertainty by assigning various weights of evidence to defined variables, in that way estimating the probability for supporting a specific hypothesis (in our case the hypothesis presence or absence of a site). Selection of variables for our model relied both on assumptions about settlement patterns and on statistically tested relationships between known archaeological sites and environmental factors. The modelling process was conducted in a Geographic Information System (GIS) by generating raster-based likelihood surfaces. The corresponding likelihood surfaces were aggregated to a final weight of evidence surface, which resulted in a likelihood value for every single cell of being a site or a non-site. Finally the result was tested against a database of known archaeological sites for evaluating the gain of the model. For the purpose of enhancing the gain of our model and sharpening our criteria we used a two-step approach to improve the modelling of former settlement strategies in our study area. Applying the developed model finally yielded a 100 percent success rate of known archaeological sites located in predicted high potential areas.
PATTERN CLASSIFICATION APPROACHES TO MATCHING BUILDING POLYGONS AT MULTIPLE SCALES
Authors: Zhang X. , Zhao X. , Molenaar M. , Stoter J. , Kraak M.-J. , Ai T.
Published: October 2012

Abstract. Matching of building polygons with different levels of detail is crucial in the maintenance and quality assessment of multi-representation databases. Two general problems need to be addressed in the matching process: (1) Which criteria are suitable? (2) How to effectively combine different criteria to make decisions? This paper mainly focuses on the second issue and views data matching as a supervised pattern classification. Several classifiers (i.e. decision trees, Naive Bayes and support vector machines) are evaluated for the matching task. Four criteria (i.e. position, size, shape and orientation) are used to extract information for these classifiers. Evidence shows that these classifiers outperformed the weighted average approach.
ANALYSIS OF LIGHT INTENSITY DATA BY THE DMSP/OLS SATELLITE IMAGE USING EXISTING SPATIAL DATA FOR MONITORING HUMAN ACTIVITY IN JAPAN
Authors: Akiyama Y.
Published: October 2012

Abstract. The main objective of this research is to show how much can be monitored various human activities using night light images by the DMSP/OLS from NOAA/NGDC. In Japan, various human activities can be monitored easily without satellite images because we can use many kinds of detailed spatial dataset and statistics. On the other hand detailed spatial data are not developed adequately especially in developing countries. Night light images by the DMSP/OLS can help to monitor them in such countries. Therefore we discuss how to use night light images of the DMSP/OLS for this objective in Tohoku region, Japan. Human activates were explained by 3 factors, i.e. road distribution, accumulation of buildings and dynamic population. These data and light images of the DMSP/OLS were resampled into the same aggregate unit and compared with a light intensity of the DMSP/OLS. In addition it is shown which factor of human activates explains the light intensity more clear than other factors by multiple regression analyses using all factors. Results of multiple regression analyses show that impacts by road distribution are strong in urban and suburban areas and impacts by building are strong in rural areas. Impacts by dynamic population are weak in all areas. Finally estimated images of light intensities were developed using results of multiple regression analysis and they were compared with the actual image of light intensity. The compared result shows that tendency of spatial distribution of the light intensity by the estimated result agrees rather well with tendency by the DMSP/OLS.
EFFICIENT RECONSTRUCTION OF LARGE UNORDERED IMAGE DATASETS FOR HIGH ACCURACY PHOTOGRAMMETRIC APPLICATIONS
Authors: Abdel-Wahab M. , Wenzel K. , Fritsch D.
Published: October 2012

Abstract. The reconstruction of camera orientations and structure from unordered image datasets, also known as Structure and Motion reconstruction, has become an important task for Photogrammetry. Only with few and rough initial information about the lens and the camera, exterior orientations can be derived precisely and automatically using feature extraction and matching. Accurate intrinsic orientations are estimated as well using self-calibration methods. This enables the recording and processing of image datasets for applications with high accuracy requirements. However, current approaches usually yield on the processing of image collections from the Internet for landmark reconstruction. Furthermore, many Structure and Motion methods are not scalable since the complexity is increasing fast for larger numbers of images. Therefore, we present a pipeline for the precise reconstruction of orientations and structure from large unordered image datasets. The output is either directly used to perform dense reconstruction methods or as initial values for further processing in commercial Photogrammetry software.
OCTREE-BASED SIMD STRATEGY FOR ICP REGISTRATION AND ALIGNMENT OF 3D POINT CLOUDS
Authors: Eggert D. , Dalyot S.
Published: October 2012

Abstract. Matching and fusion of 3D point clouds, such as close range laser scans, is important for creating an integrated 3D model data infrastructure. The Iterative Closest Point algorithm for alignment of point clouds is one of the most commonly used algorithms for matching of rigid bodies. Evidently, scans are acquired from different positions and might present different data characterization and accuracies, forcing complex data-handling issues. The growing demand for near real-time applications also introduces new computational requirements and constraints into such processes. This research proposes a methodology to solving the computational and processing complexities in the ICP algorithm by introducing specific performance enhancements to enable more efficient analysis and processing. An Octree data structure together with the caching of localized Delaunay triangulation-based surface meshes is implemented to increase computation efficiency and handling of data. Parallelization of the ICP process is carried out by using the Single Instruction, Multiple Data processing scheme – based on the Divide and Conquer multi-branched paradigm – enabling multiple processing elements to be performed on the same operation on multiple data independently and simultaneously. When compared to the traditional non-parallel list processing the Octree-based SIMD strategy showed a sharp increase in computation performance and efficiency, together with a reliable and accurate alignment of large 3D point clouds, contributing to a qualitative and efficient application.
3-D FEATURE-BASED MATCHING BY RSTG APPROACH
Authors: Jaw J.-J. , Chuang T.-Y.
Published: October 2012

Abstract. 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.
OBJECT-BASED CLASSIFICATION OF URBAN AIRBORNE LIDAR POINT CLOUDS WITH MULTIPLE ECHOES USING SVM
Authors: Zhang J. X. , Lin X. G.
Published: October 2012

Abstract. Airborne LiDAR point clouds classification is meaningful for various applications. In this paper, an object-based analysis method is proposed to classify the point clouds in urban areas. In the process of classification, outliers in the point clouds are first removed. Second, surface growing algorithm is employed to segment the point clouds into different clusters. The above point cloud segmentation is helpful to derive useful features such as average height, size/area, proportion of multiple echoes, slope/orientation, elevation difference, rectangularity, ratio of length to width, and compactness. At last, SVM-based classification is performed on the segmented point clouds with radial basis function as kernel. Two datasets with high point densities are employed to test the proposed method, and three classes are predefined. The results suggest that our method will produce the overall classification accuracy larger than 97% and the Kappa coefficient larger than 0.95.
BUILDING EDGE DETECTION USING SMALL-FOOTPRINT AIRBORNE FULL-WAVEFORM LIDAR DATA
Authors: Michelin J.-C. , Mallet C. , David N.
Published: October 2012

Abstract. The full-waveform lidar technology allows a complete access to the information related to the emitted and backscattered laser signals. Although most of the common applications of full-waveform lidar are currently dedicated to the study of forested areas, some recent studies have shown that airborne full-waveform data is relevant for urban area analysis. We extend the field to pattern recognition with a focus on retrieval. Our proposed approach combines two steps. In a first time, building edges are coarsely extracted. Then, a physical model based on the lidar equation is used to retrieve a more accurate position of the estimated edge than the size of the lidar footprint. Another consequence is the estimation of more accurate planimetric positions of the extracted echoes.
IMPLICIT SHAPE MODELS FOR OBJECT DETECTION IN 3D POINT CLOUDS
Authors: Velizhev A. , Shapovalov R. , Schindler K.
Published: October 2012

Abstract. We present a method for automatic object localization and recognition in 3D point clouds representing outdoor urban scenes. The method is based on the implicit shape models (ISM) framework, which recognizes objects by voting for their center locations. It requires only few training examples per class, which is an important property for practical use. We also introduce and evaluate an improved version of the spin image descriptor, more robust to point density variation and uncertainty in normal direction estimation. Our experiments reveal a significant impact of these modifications on the recognition performance. We compare our results against the state-of-the-art method and get significant improvement in both precision and recall on the Ohio dataset, consisting of combined aerial and terrestrial LiDAR scans of 150,000 m2 of urban area in total.
3D MODELING FROM GNOMONIC PROJECTIONS
Authors: Barazzetti L. , Previtali M. , Scaioni M.
Published: October 2012

Abstract. The paper presents a strategy able to derive and process high resolution images created by means of gnomonic projections. The implemented pipeline can be split into two phases: first, the sensor resolution of the camera is physically increased by acquiring and merging a set of images with a rotating camera equipped with a long focal lens; then the new set of gnomonic projections is processed with a 3D reconstruction methodology able to deal with very large images. Several issues are addressed in the paper, starting from image acquisition up to 3D modelling. Gnomonic projections have been demonstrated to be powerful tools when traditional pinhole images do not allow the reconstruction of small and fine details. Examples and comparisons aimed at determining the correctness of the mathematical approach for image orientation are illustrated as well.
AUTOMATIC RECONSTRUCTION OF BUILDING ROOFS THROUGH EFFECTIVE INTEGRATION OF LIDAR AND MULTISPECTRAL IMAGERY
Authors: Awrangjeb M. , Zhang C. , Fraser C. S.
Published: October 2012

Abstract. Automatic 3D reconstruction of building roofs from remotely sensed data is important for many applications including city modeling. This paper proposes a new method for automatic 3D roof reconstruction through an effective integration of LIDAR data and multispectral imagery. Using the ground height from a DEM, the raw LIDAR points are separated into two groups. The first group contains the ground points that are exploited to constitute a 'ground mask'. The second group contains the non-ground points that are used to generate initial roof planes. The structural lines are extracted from the grey-scale version of the orthoimage and they are classified into several classes such as 'ground', 'tree', 'roof edge' and 'roof ridge' using the ground mask, the NDVI image (Normalised Difference Vegetation Index from the multi-band orthoimage) and the entropy image (from the grey-scale orthoimage). The lines from the later two classes are primarily used to fit initial planes to the neighbouring LIDAR points. Other image lines within the vicinity of an initial plane are selected to fit the boundary of the plane. Once the proper image lines are selected and others are discarded, the final plane is reconstructed using the selected lines. Experimental results show that the proposed method can handle irregular and large registration errors between the LIDAR data and orthoimagery.
NETWORK SNAKES FOR ADAPTING GIS ROADS TO HEIGHT DATA OF DIFFERENT DATA SOURCES – PERFORMANCE ANALYSIS USING ALS DATA AND STEREO IMAGES
Authors: Göpfert J. , Rottensteiner F. , Heipke C.
Published: October 2012

Abstract. In order to tackle the problem of consistently integrating 2D vector data and a DTM, we presented an approach for the adaptation of 2D GIS road objects to airborne laser scanning (ALS) data using active contours (snakes) in (Göpfert et al., 2011). In this paper the algorithm is modified for the integration of stereo images as an alternative data source for area-wide height information. For that reason, a new image energy is developed that exploits geometric and radiometric features derived from the image data. Afterwards, we compare the applicability of our method with respect to the ALS data and stereo images as input. In addition, a new approach is suggested that analyses the different energy terms of active contours after the optimisation process in order to automatically detect contour parts that did not reach a suitable position in the sensor data. This concept of an internal evaluation is able to guide the user during post processing. Experiments show that the snake approach with an image energy based on stereo images is generally able to adapt GIS road centrelines to the sensor data and thus to improve the quality of the 2D vector data. However, the comparison to the results for ALS data demonstrates that the algorithm perform slightly worse for image data in the high precision level.
URBAN OBJECT EXTRACTION FROM DIGITAL SURFACE MODEL AND DIGITAL AERIAL IMAGES
Authors: Grigillo D. , Kanjir U.
Published: October 2012

Abstract. The paper describes two different methods for extraction of two types of urban objects from lidar digital surface model (DSM) and digital aerial images. Within the preprocessing digital terrain model (DTM) and orthoimages for three test areas were generated from aerial images using automatic photogrammetric methods. Automatic building extraction was done using DSM and multispectral orthoimages. First, initial building mask was created from the normalized digital surface model (nDSM), then vegetation was eliminated from the building mask using multispectral orthoimages. The final building mask was produced employing several morphological operations and buildings were vectorised using Hough transform. Automatic extraction of other green urban features (trees and natural ground) started from orthoimages using iterative object-based classification. This method required careful selection of segmentation parameters; in addition to basic spectral bands also information from nDSM was included. After the segmentation of images the segments were classified based on their attributes (spatial, spectral, geometrical, texture) using rule set classificator. First iteration focused on visible (i.e. unshaded) urban features, and second iteration on objects in deep shade. Results from both iterations were merged into appropriate classes. Evaluation of the final results (completeness, correctness and quality) was carried out on a per-area level and on a per-object level by ISPRS Commission III, WG III/4.