bluuebunny/crossref_metadata_2025 huggingface dataset:
Change in Density of Duck Nest Cavities at Forests in the North Central United States
Authors: Denton John C. , Roy Charlotte L. , Soulliere Gregory J. , Potter Bradly A.
Published: March 2012

During the past century, clear-cut hardwood forests of the north central United States have regenerated, and trees have matured into size classes increasingly capable of producing cavities suitable for nesting ducks. We determined the density of natural cavities suitable for cavity-nesting ducks, compared suitable cavity-tree distribution by size class and species, and assessed how forest maturation impacted suitable cavity density and distribution over time at four sites in the north central United States. During 2006–2008, cavities suitable for nesting ducks occurred at densities of 1.76, 1.40, 1.84, and 0.92/ha at Mingo National Wildlife Refuge (NWR) in Missouri, Shiawassee NWR in Michigan, Muscatatuck NWR in Indiana, and a study site including Mead State Wildlife Area in Wisconsin, respectively. Suitable nest-cavity densities increased at Mingo NWR (+300%) since 1965 and Shiawassee NWR (+900%) since 1973, but they remained similar at study sites examined during the mid-1980s (Muscatatuck NWR and Mead Wildlife Area) when previous site-specific cavity-suitability criteria were applied to our cavity data. Differences among sites were due to variation in tree species composition, stage of forest maturation, and potentially forest harvest regimes. Comparison of size distributions of all trees and those with suitable nest cavities indicated these forests have yet to mature into the most prolific cavity-producing size classes. Our findings suggest nest sites are not limiting duck populations at these four sites and hardwood forests with similar composition and structure. Rather than using the traditional practice of supplementing duck nest sites, wildlife managers in the North Central region should assess actual limiting factors before developing habitat management prescriptions for local cavity-nesting duck populations.
Adaptive Computation Paradigm in Knowledge Representation
Authors: Gavrilova Marina L.
Published: March 2012

The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.
Measuring Textual Context Based on Cognitive Principles
Authors: Fang Ning , Luo Xiangfeng , Xu Weimin
Published: March 2012

Based on the principle of cognitive economy, the complexity and the information of textual context are proposed to measure subjective cognitive degree of textual context. Based on minimization of Boolean complexity in human concept learning, the complexity and the difficulty of textual context are defined in order to mimic human’s reading experience. Based on maximal relevance principle, the information and cognitive degree of textual context are defined in order to mimic human’s cognitive sense. Experiments verify that more contexts are added, more easily the text is understood by a machine, which is consistent with the linguistic viewpoint that context can help to understand a text; furthermore, experiments verify that the author-given sentence sequence includes the less complexity and the more information than other sentence combinations, that is to say, author-given sentence sequence is more easily understood by a machine. So the principles of simplicity and maximal relevance actually exist in text writing process, which is consistent with the cognitive science viewpoint. Therefore, this chapter’s measuring methods are validated from the linguistic and cognitive perspectives, and it could provide a theoretical foundation for machine-based text understanding.
A Lexical Knowledge Representation Model for Natural Language Understanding
Authors: Chen Ping , Ding Wei , Ding Chengmin
Published: March 2012

Knowledge representation is essential for semantics modeling and intelligent information processing. For decades researchers have proposed many knowledge representation techniques. However, it is a daunting problem how to capture deep semantic information effectively and support the construction of a large-scale knowledge base efficiently. This paper describes a new knowledge representation model, SenseNet, which provides semantic support for commonsense reasoning and natural language processing. SenseNet is formalized with a Hidden Markov Model. An inference algorithm is proposed to simulate human-like natural language understanding procedure. A new measurement, confidence, is introduced to facilitate the natural language understanding. The authors present a detailed case study of applying SenseNet to retrieving compensation information from company proxy filings.
Exploring the Cognitive Foundations of Software Engineering
Authors: Wang Yingxu , Patel Shushma
Published: March 2012

It is recognized that software is a unique abstract artifact that does not obey any known physical laws. For software engineering to become a matured engineering discipline like others, it must establish its own theoretical framework and laws, which are perceived to be mainly relied on cognitive informatics and denotational mathematics, supplementing to computing science, information science, and formal linguistics. This paper analyzes the basic properties of software and seeks the cognitive informatics foundations of software engineering. The nature of software is characterized by its informatics, behavioral, mathematical, and cognitive properties. The cognitive informatics foundations of software engineering are explored on the basis of the informatics laws of software and software engineering psychology. A set of fundamental cognitive constraints of software engineering, such as intangibility, complexity, indeterminacy, diversity, polymorphism, inexpressiveness, inexplicit embodiment, and unquantifiable quality measures, is identified. The conservative productivity of software is revealed based on the constraints of human cognitive capacity.
Positive and Negative Innovations in Software Engineering
Authors: Jones Capers
Published: March 2012

The software engineering field has been a fountain of innovation. Ideas and inventions from the software domain have literally changed the world as we know it. For software development, we have a few proven innovations. The way software is built remains surprisingly primitive. Even in 2008 major software applications are cancelled, overrun their budgets and schedules, and often have hazardously bad quality levels when released. There have been many attempts to improve software development, but progress has resembled a drunkard’s walk. Some attempts have been beneficial, but others have been either ineffective or harmful. This article puts forth the hypothesis that the main reason for the shortage of positive innovation in software development methods is due to a lack of understanding of the underlying problems of the software development domain. A corollary hypothesis is that lack of understanding of the problems is due to inadequate measurement of quality, productivity, costs, and the factors that affect project outcomes.
Machine Learning and Value-Based Software Engineering
Authors: Zhang Du
Published: March 2012

Software engineering research and practice thus far are primarily conducted in a value-neutral setting where each artifact in software development such as requirement, use case, test case, and defect, is treated as equally important during a software system development process. There are a number of shortcomings of such value-neutral software engineering. Value-based software engineering is to integrate value considerations into the full range of existing and emerging software engineering principles and practices. Machine learning has been playing an increasingly important role in helping develop and maintain large and complex software systems. However, machine learning applications to software engineering have been largely confined to the value-neutral software engineering setting. In this paper, the general message to be conveyed is to apply machine learning methods and algorithms to value-based software engineering. The training data or the background knowledge or domain theory or heuristics or bias used by machine learning methods in generating target models or functions should be aligned with stakeholders’ value propositions. An initial research agenda is proposed for machine learning in value-based software engineering.
Measurement of Cognitive Functional Sizes of Software
Authors: Misra Sanjay
Published: March 2012

One of the major issues in software engineering is the measurement. Since traditional measurement theory has problem in defining empirical observations on software entities in terms of their measured quantities, Morasca tried to solve this problem by proposing Weak Measurement theory. Further, in calculating complexity of software, the emphasis is mostly given to the computational complexity, algorithm complexity, functional complexity, which basically estimates the time, efforts, computability and efficiency. On the other hand, understandability and compressibility of the software which involves the human interaction are neglected in existing complexity measures. Recently, cognitive complexity (CC) to calculate the architectural and operational complexity of software was proposed to fill this gap. In this paper, we evaluated CC against the principle of weak measurement theory. We find that, the approach for measuring CC is more realistic and practical in comparison to existing approaches and satisfies most of the parameters required from measurement theory.
Motivational Gratification
Authors: Mariappanadar Sugumar
Published: March 2012

Researchers in the field of information system (IS) endorse the view that there is always a discrepancy between the expressions of client’s automation requirements and IS designers understanding of such requirement because of difference in the field of expertise. In this article an attempt is taken to develop a motivational gratification model (MGM) from the cognitive informatics perspective for the automation of employee motivation measurement, instead of developing a motivation theory from a management perspective and expecting the IS designers to develop a system based on the understanding of the theory that is alien to his/her field of expertise. Motivational Gratification is an integrated work motivation model which theoretically explains how employees self-regulate their effort intensity for ‘production’ or ‘reduction’ of motivational force towards future high performance, and it is developed using taxonomies of system approach from psychology and management. The practical implications of MGM in management and IS analysis and design are discussed.
Hierarchical Function Approximation with a Neural Network Model
Authors: de Mingo Luis F. , Gómez Nuria , Arroyo Fernando , Castellanos Juan
Published: March 2012

This article presents a neural network model that permits to build a conceptual hierarchy to approximate functions over a given interval. Bio-inspired axo-axonic connections are used. In these connections the signal weight between two neurons is computed by the output of other neuron. Such arquitecture can generate polynomial expressions with lineal activation functions. This network can approximate any pattern set with a polynomial equation. This neural system classifies an input pattern as an element belonging to a category that the system has, until an exhaustive classification is obtained. The proposed model is not a hierarchy of neural networks, it establishes relationships among all the different neural networks in order to propagate the activation. Each neural network is in charge of the input pattern recognition to any prototyped category, and also in charge of transmitting the activation to other neural networks to be able to continue with the approximation.
Prevalence of Metabolic Syndrome in Subjects with Osteoarthritis Stratified by Age and Sex
Authors: Joshi Ashish
Published: March 2012

The aim of the study was to determine association between osteoarthritis and metabolic syndrome stratified by age and gender categories. A final sample of 16,149 US residents aged 17 years or older was analyzed using the database National Health and Nutrition Examination Survey (NAHNES III). Variables assessed include age, gender, race, education, poverty income ratio, body mass index, smoking history, metabolic syndrome and its risk components. Continuous and categorical variables were compared in the 2 groups using T and chi-square statistics as appropriate. Multivariate analysis was performed after adjusting for the potential confounders. Five percent subjects self-reported of having osteoarthritis. The prevalence of metabolic syndrome in subjects with osteoarthritis was 40% compared to 21% with no osteoarthritis. Subjects with osteoarthritis were significantly older; were females, non-Hispanic whites, less educated and had high prevalence of diabetes, hypertension and high cholesterol. Age, being female, higher education, being non-Hispanic White, absence of osteoporosis, and body mass index were significant predictors of osteoarthritis. Metabolic syndrome was a risk factor for osteoarthritis in males.
An Effective Streams Clustering Method for Biomedical Signals
Authors: Chaovalit Pimwadee
Published: March 2012

In the healthcare industry, the ability to monitor patients via biomedical signals assists healthcare professionals in detecting early signs of conditions such as blocked arteries and abnormal heart rhythms. Using data clustering, it is possible to interpret these signals to look for patterns that may indicate emerging or developing conditions. This can be accomplished by basing monitoring systems on a fast clustering algorithm that processes fast-paced streams of raw data effectively. This paper presents a clustering method, POD-Clus, which can be useful in computer-aided diagnosis. The proposed method clusters data streams in linear time and outperforms a competing algorithm in capturing changes of clusters in data streams.
Medical Outcome Prediction for Intensive Care Unit Patients
Authors: Ludwig Simone A. , Roos Stefanie , Frize Monique , Yu Nicole
Published: March 2012

The rate of people dying from medical errors in hospitals each year is very high. Errors that frequently occur during the course of providing health care are adverse drug events and improper transfusions, surgical injuries and wrong-site surgery, suicides, restraint-related injuries or death, falls, burns, pressure ulcers, and mistaken patient identities. Medical decision support systems play an increasingly important role in medical practice. By assisting physicians in making clinical decisions, medical decision support systems improve the quality of medical care. Two approaches have been investigated for the prediction of medical outcomes: “hours of ventilation” and the “mortality rate” in the adult intensive care unit. The first approach is based on neural networks with the weight-elimination algorithm, and the second is based on genetic programming. Both approaches are compared to commonly used machine learning algorithms. Results show that both algorithms developed score well for the outcomes selected.
Grid Platform Applied to the Vehicle Routing Problem with Time Windows for the Distribution of Products
Authors: Cruz-Chávez Marco Antonio , Rodríguez-León Abelardo , Rivera-López Rafael , Juárez-Pérez Fredy , Peralta-Abarca Carmen , Martínez-Oropeza Alina
Published: March 2012

Around the world there have recently been new and more powerful computing platforms created that can be used to work with computer science problems. Some of these problems that are dealt with are real problems of the industry; most are classified by complexity theory as hard problems. One such problem is the vehicle routing problem with time windows (VRPTW). The computational Grid is a platform which has recently ventured into the treatment of hard problems to find the best solution for these. This chapter presents a genetic algorithm for the vehicle routing problem with time windows. The algorithm iteratively applies a mutation operator, first of the intelligent type and second of the restricting type. The algorithm takes advantage of Grid computing to increase the exploration and exploitation of the solution space of the problem. The Grid performance is analyzed for a genetic algorithm and a measurement of the latencies that affect the algorithm is studied. The convenience of applying this new computing platform to the execution of algorithms specially designed for Grid computing is presented.
An Evolutionary Algorithm for Graph Drawing with a Multiobjective Approach
Authors: Aranda Sergio Enríquez , Sentí Eunice E. Ponce de León , Díaz Elva Díaz , Díaz Alejandro Padilla , Soto María Dolores Torres , Soto Aurora Torres , Ortiz Zezzatti Carlos Alberto Ochoa
Published: March 2012

In this chapter a hybrid algorithm is constructed, implemented and tested for the optimization of graph drawing employing a multiobjective approach. The multiobjective optimization problem for graph drawing consists of three objective functions: minimizing the number of edge crossing, minimizing the graph area, and minimizing the aspect ratio. The population of feasible solutions is generated using a hybrid algorithm and at each step a Pareto front is calculated. This hybrid algorithm combines a global search algorithm (EDA — Estimation of Distribution Algorithm) with a local search Algorithm (HC — Hill Climbing) in order to maintain a balance between the exploration and exploitation. Experiments were performed employing planar and non-planar graphs. A quality index of the obtained solutions by the hybrid MOEA-HCEDA (Multiobjective Evolutionary Algorithm - Hill Climbing & Univariate Marginal Distribution Algorithm) is constructed based on the Pareto front defined in this chapter. A factorial experiment using the algorithm parameters was performed. The factors are number of generations and population size, and the result is the quality index. The best combination of factors levels is obtained.
Handwritten Signature Verification Using Multi Objective Optimization with Genetic Algorithms in a Forensic Architecture
Authors: Luna Francisco , Romo Julio César Martínez , Mora-González Miguel , Martínez-Cano Evelia , Rivas Valentín López
Published: March 2012

This chapter presents the use of multi-objective optimization for on-line automatic verification of handwritten signatures; as discriminating features of each signer are used here some functions of time and space of the position of the pen on the paper; these functions are directly used in a multi-objective optimization task in order to obtain high values of false positives indicators (FAR False Acceptance Rate) and false negatives (FFR, false rejection rate). The genetic algorithms are used to create a signer´s model that optimally characterizes him, thus rejecting the skilled forgeries and recognizing genuine signatures with large variation with respect to the training set.
Mass Media Strategies
Authors: Ortiz Zezzatti Carlos Alberto Ochoa , Young Darwin , Chira Camelia , Azpeitia Daniel , Calvillo Alán
Published: March 2012

Evolve computing is a generic name given to the resolution of computational problems with base in models of an evolutionary process. Most of the evolutionary algorithms propose biological paradigms, and concepts of natural selection, mutation, and reproduction. Nevertheless other paradigms exist and can be adopted in the creation of evolutionary algorithms. Many problems involve environments not structured which can be solved from the perspective of cultural paradigms, which offer plenty of category models, where one does which do not know the possible solutions at problem, a common situation in the real life. The intention of this research is analyze the Crowdfunding Model, supporting to a social networking to an Indie Pop Band. Sociological research shows that Crowdfunding tends to reveal a bias toward social similarity. Therefore, in order to model this Project supported with Crowdfunding developing an Agent-Based Model that already manages the social interaction, together with featuring information of MySpace Music evolutionary belief spaces. To introduce these theoretical concepts the authors decided use Cultural Algorithms in our approach, explaining the process in detail.
Optimization of the Impeller and Diffuser of Hydraulic Submersible Pump using Computational Fluid Dynamics and Artificial Neural Networks
Authors: Coeto Juan Bernardo Sosa , Beltrán Gustavo Urquiza , Castrejon Juan Carlos García , Gómez Laura Lilia Castro , Reggio Marcelo
Published: March 2012

Overall performance of hydraulic submersible pump is strongly linked to its geometry, impeller speed and physical properties of the fluid to be pumped. During the design stage, given a fluid and an impeller speed, the pump blades profiles and the diffuser shape has to be determined in order to achieve maximum power and efficiency. Using Computational Fluid Dynamics (CFD) to calculate pressure and velocity fields, inside the diffuser and impeller of pump, represents a great advantage to find regions where the behavior of fluid dynamics could be adverse to the pump performance. Several trials can be run using CFD with different blade profiles and different shapes and dimensions of diffuser to calculate the effect of them over the pump performance, trying to find an optimum value. However the optimum impeller and diffuser would never be obtained using lonely CFD computations, by this means are necessary the application of Artificial Neural Networks, which was used to find a mathematical relation between these components (diffusers and blades) and the hydraulic head obtained by CFD calculations. In the present chapter artificial neural network algorithms are used in combinations with CFD computations to reach an optimum in the pumps performance.
Software Asset Re-Use
Authors: Millham Richard
Published: March 2012

In this chapter, the author examines the migration process of a legacy system, as a software-as-a-service model, to the Web, and he looks at some of the reasons that drive this legacy system migration. As migration is often a multi-step process, depending on the legacy system being migrated, the author outlines several techniques and transformations for each step of the migration process in order to enable legacy systems, of different types, to be migrated to the cloud. Of particular interest are the different methods to handle data-intensive legacy systems to enable them to function in a cloud computing environment with reduced bandwidth. Unlike the migration of an unstructured legacy system to a locally-distributed desktop system, system migration to a cloud computing environment poses some unique challenges such as restricted bandwidth, scalability, and security. Part of this migration process is adapting the transformed legacy system to be able to function in such an environment. At the end of the chapter, several small case studies of legacy systems, each of a different nature successfully migrated to the cloud, will be given.
Reuse across ESB Systems
Authors: Kumara Indika , Gamage Chandana
Published: March 2012

Enterprise Service Bus (ESB) is a middleware that provides solutions for enterprise application integration. Although the contemporary ESB products exhibit diverse architectural styles and standards such as service component architecture and Java business integration, they mostly provide the same set of ESB services such as data transformation, security, et cetera. The quality attributes of a software system are primarily attributed to the system’s architecture, and a set of systems having different architectures can meet the requirements from a great variety of users. To produce several ESB variations successfully, a systematic reuse across ESB systems is crucial. Therefore, the commonality in ESB products, which is comprised mainly of ESB services, should be strategically exploited, and this chapter discusses an approach to realize it. The author presents a platform that can derive architecturally heterogeneous ESB products from reusable ESB services. The approach for building the platform leverages aspect-oriented programming.
Understanding Cloud Computing
Authors: Hassan Qusay F. , Riad Alaa M. , Hassan Ahmed E.
Published: March 2012

Cloud computing is simply considered the realization of the long-held dream of using computing resources in the same way as accessing public utilities. Although the term “cloud computing” has been added to the IT jargon for about four years, many people are still in doubt as to what its actual meaning is. Some people even argue that cloud computing might just be an old technology under a new name. Many questions are raised when it comes to this subject. Why cloud computing? Is it the same thing as web hosting on third party servers? What is the difference between it and other popular terms such as grid computing? Why should organizations consider it? And, is it risk-free? IT, business, and academia folks are continuously asking about cloud computing with the intention of better understanding and realizing it. This chapter tries to demystify cloud computing by means of introducing and simplifying its terms to readers with different IT interests.
Social CRM
Authors: Ayanso Anteneh
Published: March 2012

This chapter provides an overview of social customer relationship management (CRM) and explores the Web-based platforms that provide social CRM solution in software as a service (SaaS) model as well as the applications and tools that complement traditional CRM systems. Based on a review of current practices, the chapter also outlines the potential benefits social CRM provides to organizations in their sales, service, and marketing efforts. Furthermore, while the Web and its new breed of technologies and applications open new opportunities for businesses, these technologies also pose several new challenges for organizations in implementation, integration, data security, and consumer privacy, among others. In addition, these technologies can be exploited in a negative way to propagate misinformation against businesses and their reputations. In view of this, this chapter also examines ethical and legal challenges businesses could face in embracing social media technologies at the core of their customer management processes and systems.
A Site Specific Study on Evaluation of Design Ground Motion Parameters
Authors: Boominathan A. , S. Krishna Kumar
Published: March 2012

Design ground motions are usually developed by one of the two approaches: site-specific analyses or from provisions of building codes. Although contemporary codes do consider approximately the site effects, they provide more conservative estimates. Hence it is preferred to carry out site specific analysis which involves both the seismic hazard analysis and ground response analysis. This article presents a site specific analysis for a seismically vulnerable site near Ahmedabad, Gujarat. The seismic hazard analysis was carried out by DSHA approach considering seismicity and seismotectonics within 250km radius. The site is predominantly characterized by deep stiff sandy clay deposits. Extensive shear wave velocity measurement by cross hole test is used for site classification and ground response analysis. The ground response analysis was carried out by equivalent linear approach using SHAKE2000. It is found that the deep stiff soil site considered is found to amplify the ground motion. The site specific response spectra obtained from RRS analysis is compared with the codal provision which reveals high spectral acceleration in site specific spectra for mid period range.
Dynamic Tensile Test of Coal, Shale and Sandstone Using Split Hopkinson Pressure Bar
Authors: Xia Kaiwen , Huang Sheng , Jha Ajay Kumar
Published: March 2012

The dynamic tensile strength plays a pivotal role in rock fragmentation affecting the overall economics under the present ‘Mine to Mill Concept’. In this paper, a modified SHPB technique and Brazilian test method is presented to test the dynamic tensile strength of coal, shale and sandstone rock samples collected from three opencast mines of Coal India Limited and is compared with the static strength value. The dynamic tensile strength of coal and rock is much higher than static strength and tensile strength of coal and rock samples increase with loading rate. The result shows that the dynamic strength of the coal sample is 1.5 times higher than static strength and the dynamic strength of the sandstone sample is 3 times higher than the static strength.
Investigations on Impact of Blasting in Tunnels
Authors: Dey Kaushik , Murthy V. M. S. R.
Published: March 2012

Blasting with longer advance per round leaves an impact both visible (in the form of overbreak) and invisible (cracks) in the surrounding rockmass, however, a number of controlled-blasting techniques, that is line drilling, pre-splitting, and smooth blasting, have been developed to minimise this problem. These techniques require additional drilling, controlled charging, and detonation, and thus, are not preferred in regular development activities. Investigations have been carried out in five different horizontal development drivages of metal mines to assess the blasting impact using burn cut and arrive at the blast-induced rock damage (BIRD) model. Vibration monitoring close to the blast was carried out using accelerometers for the first time in India to develop vibration predictors and overbreak threshold levels for individual sites. This paper reports the development of the overbreak predictive model (BIRD) for burn cut blasting in hard rock drivages by combining the relevant rock, blast design, and explosive parameters. A multivariate statistical model has been developed and validated and the same can find ready application in tunnels and mines for exercising suitable engineering controls both in blast design and explosive selection for reduced basting impacts.
A Collaborative Replication Approach for Mobile-P2P Networks
Authors: Mondal Anirban , Kumar Madria Sanjay , Kitsuregawa Masaru
Published: March 2012

This paper proposes CADRE (Collaborative Allocation and De-allocation of Replicas with Efficiency), which is a dynamic replication scheme for improving the typically low data availability in dedicated and cooperative mobile ad-hoc peer-to-peer (M-P2P) networks. In particular, replica allocation and de-allocation are collaboratively performed in tandem to facilitate effective replication. Such collaboration is facilitated by a hybrid super-peer architecture in which some of the mobile hosts act as the ‘gateway nodes’ (GNs) in a given region. GNs facilitate both search and replication. The main contributions of CADRE are as follows. First, it facilitates the prevention of ‘thrashing’ conditions due to its collaborative replica allocation and de-allocation mechanism. Second, it considers the replication of images at different resolutions to optimize the usage of the generally limited memory space of the mobile hosts (MHs). Third, it addresses fair replica allocation across the MHs. Fourth, it facilitates the optimization of the limited energy resources of MHs during replication. The authors’ performance evaluation demonstrates that CADRE is indeed effective in improving data availability in M-P2P networks with significant reduction in query response times and low communication traffic during replication as compared to a recent existing scheme as well as a baseline approach, which does not consider any replication.
Indoor Positioning Using FM Radio
Authors: Papliatseyeu Andrei , Osmani Venet , Mayora Oscar
Published: March 2012

This paper presents an indoor positioning system based on FM radio. The system is built on commercially available short-range FM transmitters. This is the first experimental study of FM performance for indoor localisation. FM radio possesses a number of features, which make it distinct from other localisation technologies. Despite the low cost and off-the-shelf components, this FM positioning system reaches a high performance, comparable to other positioning technologies such as Wi-Fi. The authors’ experiments have yielded a median accuracy of 1.0 m and in 95% of cases the error is below 5 m.
Peer Assist Live Streaming Overlay for Next-Generation-Networks
Authors: Müller Julius , Magedanz Thomas , Fiedler Jens
Published: March 2012

The rapid evolution of the telecommunication domain increases the performance of different access networks continuously. New services, especially in the domain multimedia content distribution, require higher and higher bandwidth at the user’s and service provider’s side. Multimedia services like Video on Demand, IPTV, and live streaming were introduced in the past and are still improved in quality and quantity. Multimedia streams and Peer to Peer (P2P) file sharing dominates the worldwide Internet traffic nowadays and will continue further (Schulze, 2009). The user acceptance of enjoying multimedia content over the Internet will grow steadily together with the increasing quality of the available multimedia content. Network operators and service providers have to face the growths by increasing their service platform with higher performance and bandwidth or introducing a scalable solution. In this paper, the authors present an algorithm for scalable P2P live streaming in Next-Generation-Networks (NGN) that addresses this challenge. An evaluation proves the performance of the implementation of this algorithm in a demo scenario.
Annotation and Auto-Scrolling for Web Page Overview in Mobile Web Browsing
Authors: Arase Yuki , Hara Takahiro , Uemukai Toshiaki , Nishio Shojiro
Published: March 2012

Due to advances in mobile phones, mobile Web browsing has become increasingly popular. In this regard, small screens and poor input capabilities of mobile phones prevent users from comfortably browsing Web pages that are designed for desktop PCs. One of the serious problems of mobile Web browsing is that users often get lost in a Web page and can only view a small portion of a Web page at a time, not able to grasp the entire page’s structure to decide which direction their information of interest is located. To solve this problem, an effective technique is to present an overview of the page. Although prior studies adopted the conventional style of overview, that is, a scaled-down image of the page, this is not sufficient because users cannot see details of the contents. Therefore, in this paper, the authors present annotations on a Web page that provides a functionality which automatically scrolls the page. Results of a user experiment show that annotations are informative for users who want to find contents from a large Web page.
Multidimensional Assessment of Emerging Technologies
Authors: Neshati Ramin , Daim Tugrul
Published: March 2012

The Internet has changed the world in many ways. Online communications, financial and business-to-business transactions, electronic shopping, banking, and entertainment have become the norm in the digital age. The combined package of technologies that comprise the Internet—the information superhighway—have made all of this possible. The aging technological infrastructure that supports these webs of interconnected networks is being stressed to its performance limits. Recent advances in the backbone infrastructure that supports the Internet have helped alleviate some of these problems, but more challenges lie ahead for solving technology-related performance bottlenecks for many online applications, including high-definition interactive gaming. In this paper, the authors developed a technology assessment through multiple perspectives. While different components of the technology such as applications, protocols and network components are identified, other impact areas such as market and management are also evaluated. Elements of user behavior are evaluated within the market perspective. Evaluating technologies through these dimensions concurrently provides a balanced assessment among technical, economical, social and political factors.
Reports from the Field
Authors: Beall Allyson M. , Ford Andrew
Published: March 2012

Since the work of Tansley (1935) and others, many have embraced the concept that an ecosystem is a synergy of its parts. Numerous science-centric approaches have been developed to address ecosystem management, while also taking into account the needs of the public. Participatory environmental modeling using system dynamics is an effective process for facilitating the integration of ecosystem science and social concerns. This integration helps break barriers between disciplines while also identifying important feedbacks between traditionally segregated types of data. Using the art of facilitation and the science of model building, the methodology creates a common language that integrates various types of information into simulation models. This paper describes a diversity of case studies, that have used system dynamics to create platforms through which stakeholders can simultaneously explore their system, stressors to that system, potential tipping points, resilience, and prospective policies that address the environment, social concerns, and long-term sustainability.
Managing Demographic Data Inconsistencies in Healthcare Information Systems
Authors: Esmahi Larbi , Badidi Elarbi
Published: March 2012

Healthcare IT and IS departments have the arduous task of managing the varied information sources into readily accessible, consistent and referential information views. Patient hospital workflows, from admission to discharge, provide a series of data streams for convergences into disparate systems. Protocols such as DICOM and HL7 exist for the purposes of exchanging information within the PACS and RIS information silos in the hospital enterprise. These protocols ensure data confidence for downstream systems, but are not designed to provide referential data cross system in the system-of-systems model. As data crosses the PACS and RIS information domains, data inconsistency is introduced. This paper explores the causes for data disparity and presents a referential data design for disparate systems through the implementation of an XML bus for data exchange and an RDF framework for data semantic.
Verification of a Rational Combination Approach for Agricultural Drought Assessment
Authors: Subash N. , Mohan H. S. Ram
Published: March 2012

Agricultural Drought is characterized by a deficient supply of moisture, resulting either from sub-normal rainfall, erratic rainfall distribution, or higher water with respect to a crop. In spite of technological developments in providing improved crop varieties and better management practices, in India, agriculture has been considered a gamble due to higher spatial and temporal variability. The Rice-Wheat (RW) system is the major cropping system of the Indo-Gangetic Plains (IGP) in India and occupies 10 million hectares. In this paper, the authors have examined the possibility of rationally combining the rainfall anomaly index, a weather based index and an agriculture index based on the Crop Growth Simulation Model for a rice-wheat productivity assessment in selected sites of IGP in India. The district average yields of rice varied from 0.9 t/ha at Samastipur to 3.8 t/ha at Ludhiana. Rice yields decreased from the west to east IGP, and farmers in the western IGP harvested more rice-wheat than those in the eastern regions. The productivity gap showed that all the sites were produced only 50% of the potential in RW system productivity during the triennium ending period 2005. This paper may help researchers and planners to take appropriate measures for improving productivity.
Environmental Education through Envkids Didactical Framework and ICT Tools
Authors: Tsalapata Hariklia , Alimsi Rene , Heidmann Olivier
Published: March 2012

Global awareness on the need to change everyday behavior towards some more environmentally friendly practices has been on the rise over the last few years in the face of emerging phenomena such as global temperature rising, desertification, extreme weather, sea water level rising, and the potential resulting disruption to everyday life for large populations. Even if in most European countries a certain amount of environmental objectives for primary education are defined, teachers in the field feel a substantial lack of supporting implementation guidelines, especially for digital deployment in the classroom. Addressing this need, the work presented in this paper aims at the development of blended learning activities that deploy an explorative and collaborative didactical framework towards environmental sustainability training for primary education through a combination of in-class instruction, virtual experimentation, storytelling practices, and on-line collaboration. The validation activities carried out so far demonstrate a positive teacher and learner reaction and an easy integration of the methodologies and demonstrators into existing school practices.
Preliminary Analysis of Using Games in Problem Based Learning in Learning Mathematics
Authors: Rosli Zareena Bt , Shahbodin Faaizah
Published: March 2012

The growing awareness of mathematic competency in education and careers has been as an important agenda among parents and students nowadays. Thus, teaching mathematic effectively is a challenge to educators in schools and higher institution. The combination of Problem Based Learning method and game in mathematic environment can be synchronizing to help students mastering mathematic knowledge heuristically. The objective of this paper is to highlight the literature review and the preliminary analysis done in the early phase of the research of Using Game in Problem Based Learning in Learning Mathematic. The paper also discusses the research framework that is divided into 3 parts; control mode, development, and testing.
Assistive Technologies and Environmental Design Concepts for Blended Learning and Teaching for Disabilities within 3D Virtual Worlds and Learning Environments
Authors: Saleeb Noha , Dafoulas Georgios A.
Published: March 2012

3D Virtual Learning Environments (3D VLEs) are increasingly becoming prominent supporters of blended learning for all kinds of students including adult learners with or without disabilities. Due to the evidenced effect of architectural design of physical learning spaces on students’ learning and current lack of design codes for creating 3D virtual buildings, this case study aims at evaluating the suitability of the architectural design elements of existing educational facilities and learning spaces within 3D VLEs specifically for delivering blended e-learning for adult students with disabilities. This comprises capturing student contentment and satisfaction levels from different design elements of the 3D virtual spaces in an attempt to issue recommendations for the development of 3D educational facilities and hence initiate a framework for architectural design of 3D virtual spaces to augment accessibility, appeal and engagement for enhancing the e-learning experience of under-graduate, post-graduate and independent-study adult learners with disabilities within these virtual worlds.
Framework for Evaluating Blended Learning in a University Public-Speaking Course in Singapore
Authors: Fang Linda , Chow Siew Hoong , Man Soo Wai
Published: March 2012

SIM University (UniSIM), Singapore’s first privately-funded university, caters to working adults in Singapore. It currently offers over 40 undergraduate and postgraduate degree programmes through its four schools. The university is committed to helping busy working adult learners manage their studies by providing a flexible learning environment. Blended learning is one such initiative. While courses are designed for adult learners to meet the standards set by the curriculum developers and the university, it is imperative that there are ways to indicate that learning has taken place. This paper proposes an evaluation framework to help identify, capture and reflect learning for Speaking With Confidence (COR 157), a blended learning level one core course for undergraduates. This framework would be of interest to adult learners, faculty and administrators.
Problem-Based Learning Curricula in Engineering
Authors: Krishnan Siva
Published: March 2012

This chapter explores Problem-Based Learning (PBL) curricula in engineering in Australasian universities, in particular its effects on student approaches to learning in PBL teams. Exploring from the three view points: curriculum design and implementation; institutional support structures assisting the transition to PBL for both students and academics; and student learning experiences in PBL teams, this chapter intends to close the loop for institutions and academics using PBL to educate future engineers. In particular, this chapter examines the design of engineering PBL courses or subjects within programs and the ways in which learning experiences are designed for students, the support structures that institutions put in place for both academics and students to transition to PBL, teacher practices and student experiences of learning both individually and as a team in PBL. It is argued that many engineering programs still undermine the need for designing learning experiences to help students achieve the desired learning outcomes; seldom consider the learning cultures adopted by PBL teams and how students engage in learning as individuals and as a team. This chapter argues the need for approaches to PBL that enhance student learning and experiences in engineering and the need for support structures that assist both students and academics in the transition to problem-based learning.
Assessment of Final Year Engineering Projects
Authors: Rasul Mohammad , Nouwens Fons , Swift Rhiannon , Martin Fae , Greensill Colin V.
Published: March 2012

This chapter presents survey results of learning and teaching methodologies and assessment of Final Year Engineering Projects (FYEP) as employed across several participating institutions throughout Australia and New Zealand. As a result of preliminary dialogue with practitioners within each institution, a number of common issues and discrepancies have been revealed. These issues include a lack of transparency and consistency in the field. Report findings indicate the need to engage in further dialogue with supervisors, lecturers, and students engaged in the FYEP process to develop best practice in the FYEP paradigm.