bluuebunny/crossref_metadata_2025 huggingface dataset:
Production Management in the Elderly Care Services
Authors: Ekroos Nora , Vauramo Erkki
Published: May 2010

In western countries, the so-called demographic time bomb, that is, the ageing of the baby-boom generation, has become one of the most challenging issues. Although it has become almost clichéd in health care planning, its effects are being felt rather acutely in reality. The situation in Finland, as in many other western countries, is compounded by the fact that as demand for elderly care is increasing, the service systems are suffering from severe labor and tax funding shortages. In fact, population in Finland is aging faster than any other OECD country (Antolin, Oxley, & Suyker, 2001). Elderly care centers have difficulties in hiring qualified professional staff. Nursing staff are also burdened by heavy workloads. The situation will worsen by time as the number of elderly people in our population increases further, leading to increased strain on health care resources. The present service structure is not going to be able to respond to this demand. Yet health care funding, which depends on public financing, will decrease as the number of taxpayers declines due to the aging of our workforce. “Elderly dependence ratio,” a key demographic indicator, will approximately double over the next two decades (Eurostat, 2005).
A Rehabilitative Eye-Tracking Based Brain-Computer Interface for the Completely Locked-In Patient
Authors: Abu-Faraj Ziad O. , Bou Sleiman Habib C. , Al Katergi Waleed M. , Heneine Jean-Louis D. , Mashaalany Maya J.
Published: May 2010

This article describes the design and development of a low-cost eye tracking-based brain-computer interface system for the rehabilitation of the completely locked-in patient having an intact ocular motor control to serve as an alternative means of communication (Abu-Faraj, Mashaalany, Bou Sleiman, Heneine, & Katergi, 2006). The developed system has been designed according to the following criteria: low cost, low processing power, simplicity of operation, little training requirements, minimal disturbance to the patient, and ease of customization to any mother tongue.
The Relevance of Computer-Aided-Diagnosis Systems in Microscopy Applications to Medicine and Biology
Authors: Soda Paolo , Iannello Giulio
Published: May 2010

In this article, we discuss the use of computerbased systems in microscopy, focusing on cytological images. We initially present recent results on image segmentation, and then we argue that it makes sense moving from a structural approach to a semantic interpretation of micrographs. In this respect, we focus on the relevance of using CAD tools to overcome the current limitations of microscopy, investigating several peculiar objectives of such systems. A short review of the literature demonstrates that the development of a flexible CAD applicable to various working scenarios is a future trend in microscopy healthcare systems. To support our position, we briefly describe a tool that analyzes and classifies fluorescence images.
Restructuring a Military Medical Department Research Center
Authors: Lawless W. F. , Wood Joseph , Tung Hui-Lien
Published: May 2010

This case study is of a military medical department research center (MDRC) with access to advanced information systems (IS), yet struggling to determine the quality of its residents in training and their scholarly productivity (see the article on “Theory Driven Organizational Metrics” in this encyclopedia). Based on theory, this case study was guided by stories captured from MDRC in the collapse of four interdependent variables: planning, execution, resources, and time. Our primary goals for this case study were to: (1) Formulate recommendations to utilize the IS available to reduce the overall operational cost of MDRC; (2) increase the operational efficiency and growth of MDRC by enhancing its ability to attract new extramural funds; and (3) further explore the link between practice and theory. To the extent possible, all organizational names, references, and locations have been revised to fictitious ones.
Robust Blood-Glucose Control of Type I Diabetes Patients Under Intensive Care Using Mathematica
Authors: Paláncz Béla , Kovács Levente , Benyó Balázs , Benyó Zoltán
Published: May 2010

This article presents a robust control design method on frequency domain using Mathematica for regularization of glucose level in Type I diabetes persons under intensive care. The method originally proposed under Mathematica by Helton and Merino (1998) is now improved with a disturbance rejection constraint inequality, and is tested on the three-state minimal model. Nonlinear closed loop simulation in state-space, in case of standard meal disturbances, demonstrates the robustness of the resulted high-order linear controller. The obtained results are compared with H8 design implemented with Matlab, proving that the controller (for the considered model parameters) can operate properly, even in case of parameter values of the worst-case scenario.
Support Vector Machines in Neuroscience
Authors: Seref Onur , Kundakcioglu O. Erhun , Bewernitz Michael
Published: May 2010

The underlying optimization problem for the maximal margin classifier is only feasible if the two classes of pattern vectors are linearly separable. However, most of the real life classification problems are not linearly separable. Nevertheless, the maximal margin classifier encompasses the fundamental methods used in standard SVM classifiers. The solution to the optimization problem in the maximal margin classifier minimizes the bound on the generalization error (Vapnik, 1998). The basic premise of this method lies in the minimization of a convex optimization problem with linear inequality constraints, which can be solved efficiently by many alternative methods (Bennett & Campbell, 2000).
A Theoretical Model of Observed Health Benefits of PACS Implementation
Authors: Firth Lucy , Lederman Reeva , Ali Mazin
Published: May 2010

Picture Archiving and Communication Systems (PACS) is an important e-health application, playing a significant operational role within hospitals in electronically transmitting image-based data. Various authors have attributed a range of benefits to PACS, including diagnostic accuracy (Scott et al., 1995; Slasky et al., 1990), interpretation time savings (Kato et al., 1995), workflow (Gale, Gale, Schwartz, Muse & Walker, 2000) and user satisfaction (Philling, 1999). While there is general consensus that PACS brings some or all of these benefits, there is little agreement as to the mechanism through which these benefits are generated. The work of Delone and McLean (2003) provides a generalized model that attributes information systems success to benefits accruing from relationships between characteristics of the information system (e.g., information quality, system quality, service quality) and user intention to use and user satisfaction (see Figure 1). This chapter provides empirical evidence that the Delone and McLean (2003) model with modifications explains the source of PACS benefits. Not only do we suggest a new model, but we also recommend that each specific information system context may require specific modification of Delone and McLean’s (2003) model to explain the source of success.
Volumetric Analysis and Modeling of the Heart Using Active Appearance Model
Authors: Szilágyi Sándor Miklós , Szilágyi László , Benyó Zoltán
Published: May 2010

Echocardiography is the fastest, least expensive, and least invasive heart imaging method. Accordingly, it is one of the most commonly used techniques to quantify the ventricular systolic function in patients. The examination is based on visual analysis of myocardial wall motion and deformation by an experienced and trained physiologist. This investigation is subjective, experience dependent, and the obtained results are only partially quantitative. The segmentation of the measured image sequences focuses on finding the exact boundaries of particular objects of interest, but it usually requires manual assistance.
Wireless Sensor Network to Support Home Care in Telemedicine Applications
Authors: Jiménez-Fernández Silvia , Cobo-Sánchez-de-Rojas Antonio , Araujo-Pinto Álvaro , Malagón Pedro , Nieto-Taladriz Octavio , de Toledo Paula , del Pozo Francisco
Published: May 2010

The care of patients suffering from chronic diseases is a growing source of expense for health care services around the world. The implementation of new models for patients’ treatment and follow-up needs to be faced in order to increase patients’ quality of life, and to reduce the costs associated. In this article, we propose a point-of-care for home care scenarios that is based on the remote monitoring of biomedical parameters.
Deriving Document Keyphrases for Text Mining
Authors: Brook Wu Yi-fang , Li Quanzhi
Published: May 2010

Document keyphrases provide semantic metadata which can characterize documents and produce an overview of the content of a document. This chapter describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified domain keyphrases to assign weights to the candidate keyphrases. The logic of our algorithm is: the more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. To obtain human identified positive inputs, KIP first populates its glossary database using manually identified keyphrases and keywords. It then checks the composition of all noun phrases extracted from a document, looks up the database and calculates scores for all these noun phrases. The ones having higher scores will be extracted as keyphrases. KIP’s learning function can enrich the glossary database by automatically adding new identified keyphrases to the database.
Intelligent Text Mining
Authors: Atkinson John
Published: May 2010

This chapter introduces a novel evolutionary model for intelligent text mining. The model deals with issues concerning shallow text representation and processing for mining purposes in an integrated way. Its aims are to look for interesting explanatory knowledge across text documents. The approach uses natural-language technology and genetic algorithms to produce explanatory novel hidden patterns. The proposed approach involves a mixture of different techniques from evolutionary computation and other kinds of text mining methods. Accordingly, new kinds of genetic operations suitable for text mining are proposed. Some experiments and results and their assessment by human experts are discussed which indicate the plausibility of the model for effective knowledge discovery from texts. With this chapter, authors hope the readers to understand the principles, theoretical foundations, implications, and challenges of a promising linguistically motivated approach to text mining.
Partially Supervised Text Categorization
Authors: Li Xiao-Li
Published: May 2010

In traditional text categorization, a classifier is built using labeled training documents from a set of predefined classes. This chapter studies a different problem: partially supervised text categorization. Given a set P of positive documents of a particular class and a set U of unlabeled documents (which contains both hidden positive and hidden negative documents), we build a classifier using P and U to classify the data in U as well as future test data. The key feature of this problem is that there is no labeled negative document, which makes traditional text classification techniques inapplicable. In this chapter, we introduce the main techniques S-EM, PEBL, Roc-SVM and A-EM, to solve the partially supervised problem. In many application domains, partially supervised text categorization is preferred since it saves on the labor-intensive effort of manual labeling of negative documents.
Image Classification and Retrieval with Mining Technologies
Authors: Zhang Yu-Jin
Published: May 2010

Mining techniques can play an important role in automatic image classification and content-based retrieval. A novel method for image classification based on feature element through association rule mining is presented in this chapter. The effectiveness of this method comes from two sides. The visual meanings of images can be well captured by discrete feature elements. The associations between the description features and the image contents can be properly discovered with mining technology. Experiments with real images show that the new approach provides not only lower classification and retrieval error but also higher computation efficiency.
Using the Text Categorization Framework for Protein Classification
Authors: Rakotomalala Ricco , Mhamdi Faouzi
Published: May 2010

In this chapter, we are interested in proteins classification starting from their primary structures. The goal is to automatically affect proteins sequences to their families. The main originality of the approach is that we directly apply the text categorization framework for the protein classification with very minor modifications. The main steps of the task are clearly identified: we must extract features from the unstructured dataset, we use the fixed length n-grams descriptors; we select and combine the most relevant one for the learning phase; and then, we select the most promising learning algorithm in order to produce accurate predictive model. We obtain essentially two main results. First, the approach is credible, giving accurate results with only 2-grams descriptors length. Second, in our context where many irrelevant descriptors are automatically generated, we must combine aggressive feature selection algorithms and low variance classifiers such as SVM (Support Vector Machine).
Swarm Intelligence in Text Document Clustering
Authors: Cui Xiaohui
Published: May 2010

In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. The major challenge of today’s information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role in helping users to effectively navigate, summarize, and organize the overwhelmed information. The swarm intelligence clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools, and ant food forage. Compared to the traditional clustering algorithms, the swarm algorithms are usually flexible, robust, decentralized, and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document clustering.
Some Efficient and Fast Approaches to Document Clustering
Authors: Viswanth P.
Published: May 2010

Clustering is a process of finding natural grouping present in a dataset. Various clustering methods are proposed to work with various types of data. The quality of the solution as well as the time taken to derive the solution is important when dealing with large datasets like that in a typical documents database. Recently hybrid and ensemble based clustering methods are shown to yield better results than conventional methods. The chapter proposes two clustering methods; one is based on a hybrid scheme and the other based on an ensemble scheme. Both of these are experimentally verified and are shown to yield better and faster results.
A Multi-Agent Neural Network System for Web Text Mining
Authors: Yu Lean , Wang Shouyang , Lai Kin Keung
Published: May 2010

With the rapid increase of the huge amount of online information, there is a strong demand for Web text mining which helps people discover some useful knowledge from Web documents. For this purpose, this chapter first proposes a back-propagation neural network (BPNN)-based Web text mining system for decision support. In the BPNN-based Web text mining system, four main processes, Web document search, Web text processing, text feature conversion, and BPNN-based knowledge discovery, are involved. Particularly, BPNN is used as an intelligent learning agent that learns about underlying Web documents. In order to scale the individual intelligent agent with the large number of Web documents, we then provide a multi-agent-based neural network system for Web text mining in a parallel way. For illustration purpose, a simulated experiment is performed. Experiment results reveal that the proposed multi-agent neural network system is an effective solution to large scale Web text mining.
Concept-Based Text Mining
Authors: Loh Stanley , Wives Leandro Krug , Lichtnow Daniel , de Oliveira José Palazzo M.
Published: May 2010

The goal of this chapter is to present an approach to mine texts through the analysis of higher level characteristics (called “concepts’), minimizing the vocabulary problem and the effort necessary to extract useful information. Instead of applying text mining techniques on terms or keywords labeling or extracted from texts, the discovery process works over concepts extracted from texts. Concepts represent real world attributes (events, objects, feelings, actions, etc.) and, as seen in discourse analysis, they help to understand ideas and ideologies present in texts. A previous classification task is necessary to identify concepts inside the texts. After that, mining techniques are applied over the concepts discovered. The chapter will discuss different concept-based text mining techniques and present results from different applications.
Web Usage Mining for Ontology Management
Authors: Trousse Brigitte , Aufaure Marie-Aude , Le Grand Bénédicte , Lechevallier Yves , Masseglia Florent
Published: May 2010

This chapter proposes an original approach for ontology management in the context of Web-based information systems. Our approach relies on the usage analysis of the chosen Web site, in addition to the existing approaches based onWeb pages content analysis. Our methodology is based on knowledge discovery techniques mainly from HTTP Web logs and aims to confronting the discovered knowledge in terms of usage with the existing ontology in order to propose new relations between concepts. We illustrate our approach on a Web site provided by local French tourism authorities (related to Metz city) with the use of clustering and sequential patterns discovery methods. One major contribution of this chapter is, thus, the application of usage analysis to support ontology evolution and/or Web site reorganization.
Automatic Reference Tracking
Authors: Mahalakshmi G.S. , Sendhilkumar S.
Published: May 2010

Automatic reference tracking involves systematic tracking of reference articles listed for a particular research paper by extracting the references of the input seed publication and further analyzing the relevance of the referred paper with respect to the seed paper. This tracking continues recursively with every reference paper being assumed as seed paper at every track level until the system finds any irrelevant (or far relevant) references deep within the reference tracks which does not help much in the understanding of the input seed research paper at hand. The relevance is analysed based on the keywords collected from the title and abstract of the referred article. The objective of the reference tracking system is to automatically list down closely relevant reference articles to aid the understanding of the seed paper thereby facilitating the literature survey of the aspiring researcher. This paper proposes the system design and evaluation of automatic reference tracking system discussing the observations obtained.
Latent Semantic Analysis and Beyond
Authors: Kao Anne
Published: May 2010

Latent Semantic Analysis (LSA) or Latent Semantic Indexing (LSI), when applied to information retrieval, has been a major analysis approach in text mining. It is an extension of the vector space method in information retrieval, representing documents as numerical vectors but using a more sophisticated mathematical approach to characterize the essential features of the documents and reduce the number of features in the search space. This chapter summarizes several major approaches to this dimensionality reduction, each of which has strengths and weaknesses, and it describes recent breakthroughs and advances. It shows how the constructs and products of LSA applications can be made user-interpretable and reviews applications of LSA beyond information retrieval, in particular, to text information visualization.
Text Mining in Program Code
Authors: Dreweke Alexander , Fischer Ingrid , Werth Tobias , Wörlein Marc
Published: May 2010

Searching for frequent pieces in a database with some sort of text is a well-known problem. A special sort of text is program code as e.g. C++ or machine code for embedded systems. Filtering out duplicates in large software projects leads to more understandable programs and helps avoiding mistakes when reengineering the program. On embedded systems the size of the machine code is an important issue. To ensure small programs, duplicates must be avoided. Several different approaches for finding code duplicates based on the text representation of the code or on graphs representing the data and control flow of the program and graph mining algorithms.
Multitarget Classifiers for Mining in Bioinformatics
Authors: Liberati Diego
Published: May 2010

Building effective multitarget classifiers is still an on-going research issue: this chapter proposes the use of the knowledge gleaned from a human expert as a practical way for decomposing and extend the proposed binary strategy. The core is a greedy feature selection approach that can be used in conjunction with different classification algorithms, leading to a feature selection process working independently from any classifier that could then be used. The procedure takes advantage from the Minimum Description Length principle for selecting features and promoting accuracy of multitarget classifiers. Its effectiveness is asserted by experiments, with different state-of-the-art classification algorithms such as Bayesian and Support Vector Machine classifiers, over dataset publicly available on the Web: gene expression data from DNA micro-arrays are selected as a paradigmatic example, containing a lot of redundant features due to the large number of monitored genes and the small cardinality of samples. Therefore, in analysing these data, like in text mining, a major challenge is the definition of a feature selection procedure that highlights the most relevant genes in order to improve automatic diagnostic classification.
Text Mining in Bioinformatics
Authors: Qi Yanliang
Published: May 2010

The biology literatures have been increased in an exponential growth in recent year. The researchers need an effective tool to help them find out the needed information in the databases. Text mining is a powerful tool to solve this problem. In this chapter, we talked about the features of text mining and bioinformatics, text mining applications, research methods in bioinformatics and problems and future path.
Literature Review in Computational Linguistics Issues in the Developing Field of Consumer Informatics
Authors: Lee Ki Jung
Published: May 2010

With the increased use of Internet, a large number of consumers first consult on line resources for their healthcare decisions. The problem of the existing information structure primarily lies in the fact that the vocabulary used in consumer queries is intrinsically different from the vocabulary represented in medical literature. Consequently, the medical information retrieval often provides poor search results. Since consumers make medical decisions based on the search results, building an effective information retrieval system becomes an essential issue. By reviewing the foundational concepts and application components of medical information retrieval, this paper will contribute to a body of research that seeks appropriate answers to a question like “How can we design a medical information retrieval system that can satisfy consumer’s information needs?”
The Cultural History of Medical Classifications
Authors: Surján György
Published: May 2010

This chapter outlines the history of medical classifications in a general cultural context. Classification is a general phenomenon in science and has an outstanding role in the biomedical sciences. Its general principles started to be developed in ancient times, while domain classifications, particularly medical classifications have been constructed from about the 16th-17th century. We demonstrate with several examples that all classifications reflect an underlying theory. The development of the notion of disease during the 17th-19th century essentially influenced disease classifications. Development of classifications currently used in computerised information systems started before the computer era, but computational aspects reshape essentially the whole picture. A new generation of classifications is expected in biomedicine that depends less on human classification effort but uses the power of automated classifiers and reasoners.
A Distributed E-Healthcare System
Authors: Kart Firat
Published: May 2010

In this chapter we describe a distributed e-healthcare system that uses service oriented architecture as a basis for designing, implementing, deploying, invoking and managing healthcare services. The ehealthcare system that we have developed provides support for patients, physicians, nurses, pharmacists and other healthcare professionals, as well as for medical monitoring devices, such as blood pressure monitors. The system transmits e-prescriptions from physicians to pharmacists over the Internet. It offers multimedia input and output, including text, images and speech, to provide a human-friendly interface, with the computers and networks hidden from the user.
Telepsychiatry Within European E-Health
Authors: Mucic Davor
Published: May 2010

In this chapter the author gives the short review over wide range of telepsychiatry applications. Furthermore, describes completely new and innovative approach regarding assessment and/or treatment of asylum seekers, refugees and migrants in Europe. Experiences from both Danish telepsychiatry survey and the first international telepsychiatry collaboration in Europe ever, will be reviewed in this chapter. Numbers of benefits within mental health care systems all over the European Union can be achieved by establishing of an International European Telepsychiatry Network. The chapter ends by suggestions for future development within mental health services in EU.
Clinical and Biomolecular Ontologies for E-Health
Authors: Ceresa Mario
Published: May 2010

This chapter mainly focuses on biomedical knowledge representation and its use in biomedicine. It first illustrates the existent more relevant bioinformatics resources and why they need to be better integrated. Then it describes what the main problems that machines can encounter in processing the factual biomedical knowledge are, what terminologies, classifications and ontologies are, and why they could help in better organizing and exploiting the bioinformatics resources available online. The authors hope that a concise perspective of the field and a list of selected resources, commented with their scope and usability, may help interested people in quickly understanding the main principles of knowledge representation in biomedicine and its high relevance for modern biomedical research and e-health.
Distributed Medical Volume Registration
Authors: Tait Roger , Schaefer Gerald
Published: May 2010

The registration of corresponding patient volumes is often a pre-requisite for medical imaging tasks. Accurate alignment, however, usually results in high computational complexity and can hence take a considerable amount of time. This is particularly true with 3-D volume data which adds another dimension to the registration process. One possibility of keeping registration times feasible is to distribute computation among several processors so that it maybe accomplished in parallel. This chapter provides a short survey of parallel registration approaches which have been proposed together with some recent research adopting a blackboard architecture for distributed high performance image and volume registration purposes.
Telemedicine Consultations in Daily Clinical Practice
Authors: Vladzymyrskyy Anton V.
Published: May 2010

This chapter introduces usage of telemedicine consultations in daily clinical practice. Author has describe process of teleconsultation, sample schemes of systems, parties of this process and its roles. Also, main steps of clinical teleconsultation (determination of necessity for teleconsultation, preparation of medical information, observance of ethics and law conditions, preparation of conclusion) are shown. Special part is dedicated to efficiency of teleconsultation – author has propose own complex method for estimation of it. Furthermore, the authors hope that understanding of teleconsultations’ process will make it more accessible and easy-to-use for medical practitioners.
Mobile Health Applications and New Home Care Telecare Systems
Authors: Tafa Žilbert
Published: May 2010

This chapter describes the very actual issues on mobile health (M-H) and home care (H-C) telecare systems, reviewing state of the art as well as theoretical and practical engineering issues crucial for designing these applications. The purpose, advantages and overall information and communication technology (ICT) architectures of M-H and H-C telecare systems are firstly presented. There are several engineering fields involved in the design of modern M-H and H-C applications. Making the optimal application-specific choice in each engineering aspect and achieving the right balance between complementary coupled technological requests are of crucial meaning so the main critical engineering issues (weighted at sensing node’s design and the wireless communications) are presented in details as well. Systematic theoretical review and accentuation of the design and realization problems given in this chapter can contribute in better understanding of crucial engineering issues and challenges on this topic as well as in giving the proper direction lines to approaching the practical realization of M-H and H-C telecare systems.
Case Based Reasoning for Customizing Treatment Processes
Authors: Kaiser Carolin
Published: May 2010

This chapter introduces a case based reasoning (CBR) system for customizing treatment processes. The CBR system enables the generating of inpatient and outpatient treatment processes and the supporting of e-services in heath care networks individually customized to the patients’ needs. According to the CBR paradigm, which solves problems based on past experience, the proposed system uses old treatment processes of similar former patients and modifies them for new patients. In general, CBR is an established and well suited artificial intelligence method to support medical decision making. However, CBR systems capable of planning treatment processes by adapting old treatment processes to fit new patients are rare. The aim of this system is to increase the treatment quality of the patient by providing physicians with valuable treatment propositions and to contribute to the development of medical CBR Systems by introducing procedures enabling the generating of new treatment processes by modifying former treatment processes.
Multimedia Distance Learning Solutions for Surgery
Authors: Vucetic Jelena
Published: May 2010

In the last decade, advances in medicine, telemedicine, computer technologies, information systems, Web applications, robotics and telecommunications have enabled creation of new solutions for training and continued education in various medical disciplines. This chapter presents most recent developments and future trends in distance learning for surgeons, focusing on the following goals: a) Building a comprehensive, world-wide, virtual knowledge base for various disciplines of surgery and telesurgery, including text documents, videos, case studies, expert surgeons’ opinions, and relevant references; b) Building a virtual knowledge base for rare medical cases, conditions and recommended procedures; c) Interactive multimedia simulators for hands-on training in all surgical disciplines; d) Building a worldwide surgical community, which will accelerate the accumulation and sharing of the latest surgical breakthroughs and technological advances throughout the world. Above all these goals, the most important goal is to improve patient health and convenience, and reduce risks of mortality and complications.
Transforming a Pediatrics Lecture Series to Online Instruction
Authors: Koszalka Tiffany A. , Olson Bradley
Published: May 2010

A major issue facing medical education training programs across the USA is the recent advent of universal mandatory duty hour limitations and the time pressure it places on formal face-to-face educational sessions. In response to these mandates and associated issues many medical education programs are exploring the use of online instruction to address issues of accessibility. This chapter describes the instructional development process followed to transform a classroom-based pediatrics residency lecture series into an on-demand, video-enhanced, online instructional environment. An overview of the learning principles and instructional sciences that guided the design process is provided. The phases of the designed solution are then described in the context of enhancing the lecture series as it was transformed into online instruction. Implementation logistics are described followed by an overview of the benefits, barriers, and initial project outcomes. Plans for future enhancements and research projects are also discussed.
Quality of Health Information on the Internet
Authors: Alamantariotou Kleopatra
Published: May 2010

Recent statistics show that the World Wide Web has now grown to over 100 million sites: a phenomenal expansion in only 15 years (Mulligan 2007). It has been estimated that there are 100,000 sites offering health related information (Wilson 2002). As the amount of health information increases, the public find it increasingly difficult to decide what to accept and what to reject (Burgess 2007). Searching for information on the internet is both deceptively easy and the same time frustratingly difficult (Kiley 2002). The challenge for consumers is to find high quality, relevant information as quickly as possible. There has been ongoing debate about the quality of information aimed at patients and the general public and opinions differ on how it can be improved (Stepperd 1999). The purpose of this chapter is to provide a brief overview of the different perspectives on information quality and to review the main criteria for assessing the quality of health information on the internet. Pointers are provided to enable both clinicians and patients find high quality information sources. An understanding of these issues should help health professionals and patients to make effective use of the internet.
Organization and Evaluation of Experimental Measurements of Ergophysiological Data with the Method of SF12V2
Authors: Drougas Bill Ag , Sevdali Maria
Published: May 2010

Ergophysiology as a division of the Physiology and helps us today to understand what happens in the human body and movement and how we are able to create models and methodologies to understand these mechanisms especially when we recognize something different and or any disability. Focuses on the human Biokinetics and the ability of the human body to create movement with various mechanisms and methods. These mechanisms are Biological, Chemical and Physical mechanisms and is the most important part of the human body and life. There are many problems today existed from various internal or external conditions and parameters for the human movement. If we’ll recognize these problems we will be able to create methodologies to work in to serious scientific directions to help these people. These problems sometimes are very big and very important for the daily person’s life especially with the existence of various other pathological problems in to the modern environment. Many of these problems give us informations about the personal kinetic ability status of any person. With the application of this statistical method of SF12V2 we are able organize and select a lot of personal information from different persons and to recognize different problems in to their own daily life. There are a numerous of recognized similar problems today about the daily kinetics ability level in to different ages. We can recognize the personal health level and the kinetics ability of different persons with some statistical tools and methods. One of these tools is the SF12V2 statistical method. This is a very important tool to organize the selected data from various individuals and to take informations about their health and kinetics ability level using simply ergophysiological research methodologies. This one helps us to recognize every parameter in to the personal daily life activities and work inside or outside their family life or in to their job.Asking people we can take much information about their kinetic ability and their health level. The importance of this method is that the SF12V2 tool helps us to organize the answers for any similar existed problem and also to organize the experimental measurements of other Ergophysilogical data. SF12V2 helps us to recognize problems in to any level age or to search for individuals with any personal disability or any kinetic problem. In this chapter we analyze the special and newest methods used from the SF12V2 tools as we worked in the last year in Greece to recognize different problems in to many individuals. This Statistical methodology is very simple but still with a lot of different applications such as the Ergophysiology and the different levels of health.
Ubiquitous Risk Analysis of Physiological Data
Authors: Apiletti Daniele
Published: May 2010

Current advances in sensing devices and wireless technologies are providing a high opportunity for improving care quality and reducing the medical costs. This chapter presents the architecture of a mobile healthcare system and provides an overview of mobile health applications. Furthermore, it proposes a framework for patient monitoring that performs real-time stream analysis of data collected by means of non-invasive body sensors. It evaluates a patient’s health conditions by analyzing different physiological signals to identify anomalies and activate alarms in risk situations. A risk function for identifying the instantaneous risk of each physiological parameter has been defined. The performance of the proposed system has been evaluated on public physiological data and promising experimental results are presented. By understanding the challenges and the current solutions of informatics appliances described in this chapter, new research areas can be further investigated to improve mobile healthcare services and design innovative medical applications.
Online Privacy, Vulnerabilities, and Threats
Authors: Sockel Hy , Falk Louis K.
Published: May 2010

There are many potential threats that come with conducting business in an online environment. Management must find a way to neutralize or at least reduce these threats if the organization is going to maintain viability. This chapter is designed to give managers an understanding, as well as the vocabulary needed to have a working knowledge of online privacy, vulnerabilities, and threats. The chapter also highlights techniques that are commonly used to impede attacks and protect the privacy of the organization, its customers, and employees. With the advancements in computing technology, any and all conceivable steps should be taken to protect an organization’s data from outside and inside threats.
Practical Privacy Assessments
Authors: Jansen Thejs Willem
Published: May 2010

Governments and large companies are increasingly relying on information technology to provide enhanced services to the citizens and customers and reduce their operational costs. This means that an increasing amount of information about ordinary citizens is collected in a growing number of databases. As the amount of collected information grows and the ability to correlate information from many different databases increases, the risk that some or all of this information is disclosed to unauthorised third parties grows as well. Although most people appear unaware or unconcerned about this risk, both governments and large companies have started to worry about the dangers of privacy violations on a major scale. In this chapter, we present a new method of assessing the privacy protection offered by a specific IT system. The operational privacy assessment model, presented here, is based on an evaluation of all the organisational, operational and technical factors that are relevant to the protection of personal data stored and managed in an IT system. The different factors are measured on a simple scale and the results presented in a simple graphical form, which makes it easy to compare two systems to each other or to identify the factors that benefit most from improved privacy enhancing technologies.A standardised assessment of the privacy protection offered by a particular IT system; serve to help system owners understand the privacy risks in their IT system as well as help individuals, whose data is being processed, to understand their personal privacy situation. This will facilitate the development and procurement of IT systems with acceptable privacy levels, but the simple standard assessment result may also provide the basis for a certification scheme, which may help raise the confidence in the IT system’s ability to protect the privacy of the data stored and processed in the system.
Current Measures to Protect E-Consumers' Privacy in Australia
Authors: Ha Huong , Coghill Ken
Published: May 2010

The current measures to protect e-consumers’ privacy in Australia include (i) regulation/legislation; (ii) guidelines; (iii) codes of practice; and (iv) activities of consumer associations and the private sector. However; information about the outcomes of such measures has not been sufficiently reported; whereas privacy incidents have increased. Some policy implications for e-consumer protection are drawn from the analysis. Firstly; national privacy legislation should widen its coverage. Secondly; uniform regulations and guidelines could contribute to providing equal protection to e-consumers. Thirdly; guidelines and codes of practice need to be supported by legislation and a proper compliance regime. Corporate social responsibility by e-retailers is also required for effective adoption of self-regulatory measures. Fourthly; consumer education is important to enhance consumer awareness of online privacy risks and their ability to deal with such incidents. Finally; a combination of legal frameworks; technological; and human-behaviour related measures is more likely to address online privacy issues effectively.
Antecedents of Online Privacy Protection Behavior
Authors: Gurung Anil , Jain Anurag
Published: May 2010

Individuals are generally concerned about their privacy and may withhold from disclosing their personal information while interacting with online vendors. Withholding personal information can prevent online vendors from developing profiles to match needs and wants. Through a literature review of research on online privacy; we develop an integrative framework of online privacy protection.
A Profile of the Demographics, Psychological Predispositions, and Social/Behavioral Patterns of Computer Hacker Insiders and Outsiders
Authors: Schell Bernadette H. , Holt Thomas J.
Published: May 2010

This chapter looks at the literature—myths and realities—surrounding the demographics, psychological predispositions, and social/behavioral patterns of computer hackers, to better understand the harms that can be caused to targeted persons and property by online breaches. The authors suggest that a number of prevailing theories regarding those in the computer underground (CU)—such as those espoused by the psychosexual theorists—may be less accurate than theories based on gender role socialization, given recent empirical studies designed to better understand those in the CU and why they engage in hacking and cracking activities. The authors conclude the chapter by maintaining that online breaches and online concerns regarding privacy, security, and trust will require much more complex solutions than currently exist, and that teams of experts in psychology, criminology, law, and information technology security need to collaborate to bring about more effective real-world solutions for the virtual world.
Online Consumer Privacy and Digital Rights Management Systems
Authors: Chan Tom S.
Published: May 2010

While delivering content via the Internet can be efficient and economical, content owners risk losing control of their intellectual property. Any business that wishes to control access to and use of its intellectual property is a potential user of digital rights management (DRM) technologies. DRM control content delivery and distribution but it may affect users’ privacy rights. Exactly how it should be preserved is a matter of controversy; and the main industry solution is the W3C platform for privacy preferences (P3P) initiative. But, the issue remains unresolved, and industries and consumers are confronted with several incompatible standards.