bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Augmented E-Learning Systems for Enhancing Pro-Social Behaviour in Socially Impaired Individuals
Authors: Bishop Jonathan
Published: May 2011

E-learning systems generally rely on good visual and cognitive abilities, making them suitable for individuals with good levels of intelligence in these areas. A group of such individuals are those with non-systemising impairments (NSIs), such as people with autism spectrum conditions (ASCs). These individuals could benefit greatly from technology that allows them to use their abilities to overcome their impairments in social and emotional functioning in order to develop pro-social behaviours. Existing systems such as PARLE and MindReading are discussed, and a new one, the Visual Ontological Imitation System (VOIS), is proposed and discussed. This chapter details an investigation into the acceptability of these systems by those working in social work and advocacy. The study found that VOIS would be well received, although dependency on assistive technology and its impact on how others view NSIs still need to be addressed by society and its institutions.
Virtual Learning Environments
Authors: Trahan Mitzi P. , Adams Nan B. , Dupre Susan
Published: May 2011

The growing experimentation with multi-user virtual environments for educational purposes demands rigorous examination of all aspects of these digital worlds. While their use appears to enhance and expand traditional distance learning, educators acknowledge that barriers to access remain, including a steep learning curve for orienting users to MUVE navigation and functionality. The application of Adams’s Knowledge Development Model for Virtual Learning Environments provides a framework for the design of in-world learning opportunities and activities, many of which tend to mirror pedagogical best-practices in Real Life (RL).
Exploring the Correlation between Online Teacher Dispositions and Practices in Virtual Classrooms and Student Participation and Satisfaction
Authors: Shepherd Carol M. , Alpert Madelon
Published: May 2011

Greater teacher efficacy in online teaching and teaching in a virtual world appears to be positively correlated with certain exhibited dispositions and practices. Inferential measures of dispositions such as friendliness, enthusiasm, active involvement, patience, and tolerance, among others, exhibited by professors in online instruction lead to greater student participation and satisfaction. By analyzing four professors teaching in the virtual world environment, two with positive student reviews and two with negative or mediocre student reviews, certain teacher dispositions and practices emerged. Three areas were studied: instructor participation with students, the tone of communication with students, and the creation of a community of learners in a virtual world. Instructor participation with students was measured by the interaction and guidance in discussion board questions, comments on graded student work, the amount of measured user time of the instructor while teaching online, and student evaluations. The tone of communication with students was measured by professor communications with students in the discussion boards, virtual office responses to student questions, and whole class as well as individual emails. The creation of a community of learners in a virtual environment helps to foster a sense of belonging, and was measured by activities such as informal course announcements, media, emails, and student and professor biographies, indicating that the instructor is interested in each student. There are two perspectives to online instruction: that of the student as well as that of the instructor. In order to provide a valid base for analysis, it is important to consider both. A search of the literature revealed almost no information in the areas of focus of this study. Further research is needed to identify positive behaviors by instructors leading to greater online instructor efficacy when teaching in virtual worlds.
How to Build Effective “Edutainment” Experiences in MUVEs
Authors: Bucciero Alberto , Di Blas Nicoletta , Mainetti Luca , Paolini Paolo , Poggi Caterina
Published: May 2011

This chapter is about how to make an effective use of MUVEs (Multi-Users Virtual Environments) in formal education. It draws on the authors’ experience with four different programs deployed since 2002 involving, so far, more than 9,000 students from 18 European countries including Israel and the USA. The chapter is intended as a set of “lessons learned” on all of the relevant aspects of this kind of enterprise, from design to implementation and actual deployment. It is therefore meant as a short “users” guide for building effective and engaging edutainment experiences in virtual worlds.
Teaching Project Management with Second Life
Authors: Conrad Marc
Published: May 2011

Project Management is a field of intellectual and pragmatic enquiry that is inherently inter-disciplinary. It typically involves the integration of areas such as: project scoping, time, cost, and human resource management, whilst the management of effective inter-team communication, project risk, and procurement aspects are all central to the discipline. To try to cover all of these areas within a single university assignment presents somewhat of a challenge. This chapter demonstrates that the deployment of a Multi User Virtual Environment can indeed encompass these areas in an effective manner, both from learning objectives, realism, and assessment points of view. The chapter has emerged from the experience of three years deployment of Second Life as an integral part of a unit on Project Management, offered as part of both undergraduate and postgraduate courses within the Department of Computer Science and Technology at the University of Bedfordshire. Examples illustrate the work that has been produced by the students of these courses.
Towards Usable Collaborative Virtual Reality Environments for Promoting Listening Comprehension
Authors: Garcia-Ruiz Miguel A. , Edwards Arthur , Aquino-Santos Raul , Tashiro Jay Shiro , Kapralos Bill
Published: May 2011

This chapter investigates whether an educational virtual environment can be developed to practice listening comprehension skills that meets second language student needs, complies with usability criteria, and is motivating to use. The chapter also investigates whether the usability of virtual reality(VR) technology positively affects language learning listening comprehension. It provides background research and information in Computer Assisted Language Learning (CALL), VR, and second language methodology. It then presents a technical and qualitative description of Realtown, a virtual environment designed to promote listening comprehension. This chapter also describes a usability study of Realtown. Student errors, motivation, and ease of use, among other features, were positively measured on listening comprehension activities in Realtown. Future work includes longitudinal studies on learning issues, first-person, and collaborative experiences in VR, including the impact of VR on learning and knowledge transfer when combined with traditional instruction.
Second Language Teaching in Virtual Worlds
Authors: Frias Paulo , Fernandes Ricardo N. , Cruz Ricardo
Published: May 2011

This project is a proposal for a case study that aims to describe and understand communicative and pedagogical processes involved in Second Life® (SL™) in a context of second language learning, by modelling in-world lessons of Portuguese as a second language for ERASMUS students1 arriving in Portugal. The purpose is to provide examples of situated e-learning driven activities and perceive how an immersive context stimulates learning by involving students in a virtual reality situation, where real life language context situations are provoked and where ‘not possible in real life’ learning routines happen. This will allow experiencing the advantages of this platform compared to physical life teaching and learning contexts, through the inherent characteristics of this medium, such as the synchronous and simultaneous use of voice and text.
Teaching Foreign Languages in a Virtual World
Authors: Kaplan-Rakowski Regina
Published: May 2011

The author uses her teaching experience, gained both in the real world and in virtual worlds, to convey several potential foreign language activities that could be conducted in a virtual environment. The activities are presented in the form of lesson plans, which teachers should find useful for the preparation of their virtual lessons. The lesson plans follow the conventional format that is used in the USA, however, the lessons themselves are hardly conventional. They take advantage of several affordances of virtual worlds and present activities that are difficult, or even impossible, in a traditional classroom (e.g., traveling in time or traveling in space). Teachers are encouraged to use the lessons as examples of possible activities, which they can modify according to their experience, their preferences and their students’ needs.
A Work-Integrated Learning Philosophy and the Educational Imperatives
Authors: Calway Bruce A. , Murphy Gerald A.
Published: May 2011

The chapter explores these WIL findings as: embedded life-long learning, continuing professional development, and the various learning modes that employ the work and learning interface. Further, any understanding of a WIL philosophy must incorporate a learner environment for individual ‘action learning’ and institutional (i.e. educational as well as workplace) ‘active learning’ as an initiative that addresses the specific educational imperatives and models outlined.
Running a Successful Practice School
Authors: Ku Hong-ming , Thonglek Saranya
Published: May 2011

The Chemical Engineering Practice School (ChEPS) at King Mongkut’s University of Technology Thonburi (KMUTT) in Bangkok is a two-year international curriculum modeled after Massachusetts Institute of Technology’s School of Chemical Engineering Practice. The aim of this Master’s program is to produce professional chemical engineers with strong fundamentals, practical experience, and a good command of English. The program’s uniqueness lies in its strong linkage with the industrial sector. This chapter contains a history of ChEPS and details how KMUTT operates the program. The key factors contributing to the success of the program are identified. Moreover, critical analyses gleaned from the faculty, the alumni, and the industrial sponsors are carried out to examine the current strengths of ChEPS and to identify areas for improvement. Key challenges still facing the program are also outlined. Finally, potential solutions to these challenges are recommended.
Work-Integrated Learning in Postgraduate Design Research
Authors: Siu Kin Wai Michael
Published: May 2011

Instead of only staying in the university to carry out research, postgraduate research students nowadays are expected to gain knowledge and experience through work-integrated learning. The advantages of this kind of learning include better support and facilities for research and more comprehensive and in-depth experience in the research area. The learning also provides an opportunity for students to gain other research experience and explore other research interests. However, sometimes such kind of learning opportunity is not available or not the best available locally, therefore work-integrated learning is necessary or better to be carried out in remote regions. Taking regional collaboration of work-integrated learning for postgraduate design research students between the Chinese mainland and Hong Kong as a case study, this chapter discusses the advantages, merits, issues, and problems of regional collaboration. The chapter then identifies possibilities for improvement and directions for further investigation.
Vehicular Networks Security
Authors: Tchepnda Christian , Moustafa Hassnaa , Labiod Houda , Bourdon Gilles
Published: May 2011

This article provides a panorama on the security in vehicular networks’ environments. The special characteristics of these environments are presented and a general classification for the different types of attacks illustrated by some relevant attacks examples is introduced. Consequently, some key security requirements and security challenges are derived, considering Intelligent Transportation System (ITS) or Safety services as well as non-ITS or non-Safety services. Finally, some existing contributions in this subject are presented, and their deployment feasibility is discussed.
Using Ambient Social Reminders to Stay in Touch with Friends
Authors: Shannon Ross , Kenny Eugene , Quigley Aaron
Published: May 2011

Social interactions among a group of friends will typically have a certain recurring rhythm. Most people interact with their own circle of friends at a range of different rates, and through a range of different modalities (by email, phone, instant messaging, face-to-face meetings and so on). When these naturally recurring interactions are maintained effectively, people feel at ease with the quality and stability of their social network. Conversely, when a person has not interacted with one of their friends for a longer time interval than they usually do, a situation can be identified in that relationship which may require action to resolve. Here we discuss the opportunities we see in using ambient information technology to effectively support a user’s social connectedness. We present a social network visualisation which provides a user with occasional recommendations of which of their friends they should contact soon to keep their social network in a healthy state.
Online Remote Control of a Wireless Home Automation Network
Authors: Wade John , Santos Jose , Evans Noel
Published: May 2011

Embedded systems within home appliances are not usually manufactured to operate in a networked environment; connecting supplementary hardware/software systems through a wireless, PC-controlled medium is necessary to enable full, efficient control of their functions from a remote location. Access to the home’s central PC may be gained via a local web server, giving Internet-based control from almost anywhere in the world. The proposed system constitutes a significant improvement over those discussed in the literature to date, and reviewed here. It enables complex-appliance control in a secure and reliable portable-wireless environment, and was developed using ASP.Net. The system was assessed for Received Signal Strength (RSS) in an environment more radio-hostile than that found in a typical household. The minimum RF level found at a transfer rate of 9.6 kbps was 8 dB above the receiver’s quoted sensitivity of -103 dBm; this fading margin will increase in a normal household environment.
Proactive Context-Aware Middleware
Authors: Lee Karen , Lunney Tom , Curran Kevin , Santos Jose
Published: May 2011

Advancements in sensor technology, wireless communications and information technology has enabled the success of new types of dynamic computing systems. However designing systems which are flexible and can adapt to the changing needs of the user remains a major research challenge. Flexibility and adaptability are fundamental requirements for Ambient Intelligent (AmI) systems. The complexity involved in designing applications and devices which change and adapt their behaviour automatically based on their context or situation is well recognised. Providing technology which meets the changing needs of the user is heavily reliant on the appropriate infrastructure design. This work outlines the development of an Ambient Middleware framework for Context-Aware systems. The framework will integrate with sensor technologies, intelligent algorithms and the semantic web.
Intelligent Information Description and Recognition in Biomedical Image Databases
Authors: Djemal Khalifa , Maaref Hichem
Published: May 2011

There is a significant increase in the use of biomedical images in clinical medicine, disease research, and education. While the literature lists several successful methods that were developed and implemented for content-based image retrieval and recognition, they have been unable to make significant inroads in biomedical image recognition domain. The use of computer-aided diagnosis has been increasing. It is based on descriptors extraction and classification approaches. This interest is due to the need for specialized methods, which are specific to each biomedical image type, and also due to the lack of advances in image recognition systems. In this chapter, the authors present intelligent information description techniques and the most used classification methods in an image retrieval and recognition system. A multicriteria classification method applied for sickle cells disease image databases is given. The recognition performance system is illustrated and discussed.
Adaptive Dynamic Programming Applied to a 6DoF Quadrotor
Authors: Stingu Petru Emanuel , Lewis Frank L.
Published: May 2011

This chapter discusses how the principles of Adaptive Dynamic Programming (ADP) can be applied to the control of a quadrotor helicopter platform flying in an uncontrolled environment and subjected to various disturbances and model uncertainties. ADP is based on reinforcement learning. The controller (actor) changes its control policy (action) based on stimuli received in response to its actions by the critic (cost function, reward). There is a cause and effect relationship between action and reward. Reward acts as a reinforcement signal that leads to learning of what actions are likely to generate it. After a number of iterations, the overall actor-critic structure stores information (knowledge) about the system dynamics and the optimal controller that can accomplish the explicit or implicit goal specified in the cost function.
Sigma Tuning of Gaussian Kernels Detection of Ischemia from Magnetocardiograms
Authors: Han Long , Embrechts Mark J. , Szymanski Boleslaw K. , Sternickel Karsten , Ross Alexander
Published: May 2011

This chapter introduces a novel Levenberg-Marquardt like second-order algorithm for tuning the Parzen window s in a Radial Basis Function (Gaussian) kernel. In this case, each attribute has its own sigma parameter associated with it. The values of the optimized s are then used as a gauge for variable selection. In this study, the Kernel Partial Least Squares (K-PLS) model is applied to several benchmark data sets in order to estimate the effectiveness of the second-order sigma tuning procedure for an RBF kernel. The variable subset selection method based on these sigma values is then compared with different feature selection procedures such as random forests and sensitivity analysis. The sigma-tuned RBF kernel model outperforms K-PLS and SVM models with a single sigma value. K-PLS models also compare favorably with Least Squares Support Vector Machines (LS-SVM), epsilon-insensitive Support Vector Regression and traditional PLS. The sigma tuning and variable selection procedure introduced in this chapter is applied to industrial magnetocardiogram data for the detection of ischemic heart disease from measurement of the magnetic field around the heart.
Artificial Neural Network Modelling for Waste
Authors: Rene Eldon R. , López M. Estefanía , Veiga María C. , Kennes Christian
Published: May 2011

Due to their inherent robustness, artificial neural network models have proven to be successful and have been used extensively in biological wastewater treatment applications. However, only recently, with the scientific advancements made in biological waste gas treatment systems, the application of neural networks have slowly gained the practical momentum for performance monitoring in this field. Simple neural models, after vigorous training and testing, are able to generalize the results of a wide range of operating conditions, with high prediction accuracy. This chapter gives a fundamental insight and overview of the process mechanism of different biological waste gas (biofilters, biotrickling filters, continuous stirred tank bioreactors and monolith bioreactors), and wastewater treatment systems (activated sludge process, trickling filter and sequencing batch reactors). The basic theory of artificial neural networks is explained with a clear understanding of the back propagation algorithm. A generalized neural network modelling procedure for waste treatment applications is outlined, and the role of back propagation algorithm network parameters is discussed. Anew, the application of neural networks for solving specific environmental problems is presented in the form of a literature review.
Data Discovery Approaches for Vague Spatial Data
Authors: Petry Frederick E.
Published: May 2011

This chapter focuses on the application of the discovery of association rules in approaches vague spatial databases. The background of data mining and uncertainty representations using rough set and fuzzy set techniques is provided. The extensions of association rule extraction for uncertain data as represented by rough and fuzzy sets is described. Finally, an example of rule extraction for both types of uncertainty representations is given.
Feature Selection and Ranking
Authors: Igelnik Boris
Published: May 2011

This chapter describes a method of feature selection and ranking based on human expert knowledge and training and testing of a neural network. Being computationally efficient, the method is less sensitive to round-off errors and noise in the data than the traditional methods of feature selection and ranking grounded on the sensitivity analysis. The method may lead to a significant reduction of a search space in the tasks of modeling, optimization, and data fusion.
Modeling the Intellect from a Coordination Perspective
Authors: Taxén Lars
Published: May 2011

Usually, models of the intellect take the individual mind and body as the point of departure and proceed outward towards the social and natural environment in which the individual is immersed. As a consequence, important social dimensions contributing to the epigenetic development of the individual are less articulated. This chapter suggests modeling the intellect from a more balanced perspective that recognizes both social and individual aspects–the coordination of actions. The author argues that coordination is made possible by certain innate dispositions called activity modalities: contextualization, spatialization, temporalization, stabilization, and transition. Consequently, a central task for modeling the intellect is to understand how perceptions received through sensory modalities are related to the activity modalities. To this end, the author proposes a research program for modeling the intellect, based on the concept of “activity” in the Russian Activity Theory and the activity modalities. Provisional arguments for the relevance of these modalities are discussed in three different realms associated with the intellect: the social, conceptual, and neural ones. The chapter is concluded with some preliminary research questions, pertinent for the research program.
Outlier Detection in Linear Regression
Authors: Nurunnabi A. A. M. , Imon A. H. M. Rahmatullah , Ali A. B. M. Shawkat , Nasser Mohammed
Published: May 2011

Regression analysis is one of the most important branches of multivariate statistical techniques. It is widely used in almost every field of research and application in multifactor data, which helps to investigate and to fit an unknown model for quantifying relations among observed variables. Nowadays, it has drawn a large attention to perform the tasks with neural networks, support vector machines, evolutionary algorithms, et cetera. Till today, least squares (LS) is the most popular parameter estimation technique to the practitioners, mainly because of its computational simplicity and underlying optimal properties. It is well-known by now that the method of least squares is a non-resistant fitting process; even a single outlier can spoil the whole estimation procedure. Data contamination by outlier is a practical problem which certainly cannot be avoided. It is very important to be able to detect these outliers. The authors are concerned about the effect outliers have on parameter estimates and on inferences about models and their suitability. In this chapter the authors have made a short discussion of the most well known and efficient outlier detection techniques with numerical demonstrations in linear regression. The chapter will help the people who are interested in exploring and investigating an effective mathematical model. The goal is to make the monograph self-contained maintaining its general accessibility.
A Cognitive Informatics Reference Model of Autonomous Agent Systems (AAS)
Authors: Wang Yingxu
Published: May 2011

Despite the fact that the origin of software agent systems has been rooted in autonomous artificial intelligence and cognitive psychology, their implementations are still based on conventional imperative computing techniques rather than autonomous computational intelligence. This paper presents a cognitive informatics perspective on autonomous agent systems (AAS’s). A hierarchical reference model of AAS’s is developed, which reveals that an autonomous agent possesses intelligent behaviors at three layers known as those of imperative, autonomic, and autonomous from the bottom up. The theoretical framework of AAS’s is described from the facets of cognitive informatics, computational intelligence, and denotational mathematics. According to Wang’s abstract intelligence theory, an autonomous software agent is supposed to be called as an intelligent-ware, shortly, an intelware, parallel to hardware and software in computing, information science, and artificial intelligence.
IPML
Authors: Hu Jun , Feijs Loe
Published: May 2011

This paper addresses issues of distributing multimedia presentations in an ambient intelligent environment, examines the existing technologies and proposes IPML, a markup language that extends SMIL for distributed settings. It uses a metaphor of play, with which the timing and mapping issues in distributed presentations are covered in a natural way. A generic architecture for playback systems is also presented, which covers the timing and mapping issues of presenting an IPML script in heterogeneous ambient intelligent environments.
Important Attributes Selection Based on Rough Set for Speech Emotion Recognition
Authors: Zhou Jian , Wang Guoyin , Yang Yong
Published: May 2011

Speech emotion recognition is becoming more and more important in such computer application fields as health care, children education, etc. In order to improve the prediction performance or providing faster and more cost-effective recognition system, an attribute selection is often carried out beforehand to select the important attributes from the input attribute sets. However, it is time-consuming for traditional feature selection method used in speech emotion recognition to determine an optimum or suboptimum feature subset. Rough set theory offers an alternative, formal and methodology that can be employed to reduce the dimensionality of data. The purpose of this study is to investigate the effectiveness of Rough Set Theory in identifying important features in speech emotion recognition system. The experiments on CLDC emotion speech database clearly show this approach can reduce the calculation cost while retaining a suitable high recognition rate.
Adaptive Integrated Control for Omnidirectional Mobile Manipulators Based on Neural-Network
Authors: Tan Xiang-min , Zhao Dongbin , Yi Jianqiang , Xu Dong
Published: May 2011

An omnidirectional mobile manipulator, due to its large-scale mobility and dexterous manipulability, has attracted lots of attention in the last decades. However, modeling and control of such systems are very challenging because of their complicated mechanism. In this paper, an unified dynamic model is developed by Lagrange Formalism. In terms of the proposed model, an adaptive integrated tracking controller, based on the computed torque control (CTC) method and the radial basis function neural-network (RBFNN), is presented subsequently. Although CTC is an effective motion control strategy for mobile manipulators, it requires precise models. To handle the unmodeled dynamics and the external disturbance, a RBFNN, serving as a compensator, is adopted. This proposed controller combines the advantages of CTC and RBFNN. Simulation results show the correctness of the proposed model and the effectiveness of the control approach.
Knowledge Adquisition in a Cooperative and Competitive Framework
Authors: de la Encina Alberto , Hidalgo-Herrero Mercedes , López Natalia
Published: May 2011

In this chapter, we modelize an interchange commerce system basen on the economic concept of utility function. A cognitive agent controls the interchanges of the clients in her market. When interchanges are not possible any more, the agent becomes a client of a higher market, giving place to a hierarchical market system. Now, she behaves according to what she has learned from her clients. Apart from physical resources, intangible goods such as knowledge are also interchanged. This cooperative and competitive structure is formalized via process algebra.
Noise Cancellation in ECG Signals with an Unbiased Adaptive Filter
Authors: Wu Yunfeng , Rangayyan Rangaraj M.
Published: May 2011

The electrocardiographic (ECG) signal is a transthoracic manifestation of the electrical activity of the heart and is widely used in clinical applications. This chapter describes an unbiased linear adaptive filter (ULAF) to attenuate high-frequency random noise present in ECG signals. The ULAF does not contain a bias in its summation unit and the filter coefficients are normalized. During the adaptation process, the normalized coefficients are updated with the steepest-descent algorithm to achieve efficient filtering of noisy ECG signals. A total of 16 ECG signals were tested in the adaptive filtering experiments with the ULAF, the least-mean-square (LMS), and the recursive-least-squares (RLS) adaptive filters. The filtering performance was quantified in terms of the root-mean-squared error (RMSE), normalized correlation coefficient (NCC), and filtered noise entropy (FNE). A template derived from each ECG signal was used as the reference to compute the measures of filtering performance. The results indicated that the ULAF was able to provide noise-free ECG signals with an average RMSE of 0.0287, which was lower than the second-best RMSE obtained with the LMS filter. With respect to waveform fidelity, the ULAF provided the highest average NCC (0.9964) among the three filters studied. In addition, the ULAF effectively removed more noise, measured by FNE, in comparison with the LMS and RLS filters in most of the ECG signals tested. The issues of adaptive filter setting for noise reduction in ECG signals are discussed at the end of this chapter.
Using Agent Based Simulation and Game Theory Analysis to Study Knowledge Flow in Organizations
Authors: Jolly Richard , Wakeland Wayne
Published: May 2011

Knowledge sharing in organizations, especially the impact of sharing freely versus not sharing, was studied using game theoretic analysis and a Netlogo agent-based simulation model. In both analyses, some agents hoarded knowledge while others shared knowledge freely. As expected, sharing was found to greatly increase the overall amount of knowledge within the organization. Unexpectedly, on average, agents who share acquire more knowledge than hoarders. This is in contradiction to the conclusion from the prisoner’s dilemma analysis. This is due to the synergy that develops between groups of agents who are sharing with each other. The density of the agents is important; as the density increases, the probability increases that an agent with a large amount of knowledge to share happens to be organizationally nearby. The implications are that organizations should actively encourage knowledge sharing, and that agent-based simulation is a useful tool for studying this type of organizational phenomena.
Reaching for the Moon
Authors: Allan Mark B. , Korolis Anthony A. , Griffith Terri L.
Published: May 2011

Transactive memory systems (TMS) support knowledge sharing and coordination in groups. TMS are enabled by the encoding, storage, retrieval, and communication of knowledge by domain experts—knowing who knows what. The NASA Ames Intelligent Robotics Group provides an example of how TMS theoretical boundaries are stretched in actual use. This group is characterized as being highly innovative as they routinely engage in field studies that are inherently difficult due to time and technology resource constraints. We provide an expanded view of TMS that includes the technology support system available to this group, and possible further extensions to NASA’s or other such dynamic groups’ practice.
Organization of Lessons Learned Knowledge
Authors: Iyer Subramanian Rama , Sharda Ramesh , Biros David , Lucca Joyce , Shimp Upton
Published: May 2011

With knowledge management systems (KMS) containing large repositories, a major issue is content organization. The ease of finding relevant information depends on the effectiveness of knowledge organization. Ontology, thesauri, and taxonomy are some of the key words that relate to knowledge organization. In this article we propose a schema for organizing knowledge that represents lessons learned from prior experience. Such knowledge from lessons learned has distinct characteristics so that it can be organized in specific ways for ease of discovery, retrieval, and also possible incorporation in formal learning. The proposed taxonomy includes concepts from domain related hierarchy, sources of lessons learned, formal learning, and collaborative inputs (Web 2.0). We describe the proposed taxonomy for organizing the lessons learned knowledge (also termed as knowledge nuggets) and provide details of a specific implementation of this taxonomy in a military organization. Such approaches to knowledge organization have the potential to be useful in many other knowledge management (KM) projects.
Zooming in on the Effect of National Culture on Knowledge Sharing Behavior
Authors: Li Wei
Published: May 2011

This research project investigates what are the national cultural factors that influence employees’ cross-cultural knowledge sharing in online environments and in what way. The chapter draws on findings from 41 in-depth interviewees conducted with 20 Chinese and 21 American employees who worked for a large multinational corporation. The rich interview data identified three national cultural differences that impacted Chinese and American participants s’ knowledge sharing through an online system, namely, language, differences grounded in collectivism/individualism, and different levels of uncertainty avoidance. English created a barrier for Chinese users to post their ideas but it didn’t seem to stop them from consuming knowledge. Differences grounded in collectivist/individualist values were mainly reflected in these two cultural groups’ different logic regarding the relationship between different working contexts and the need to share. Chinese participants also showed a higher level of uncertainty avoidance than American participants. Together these cultural differences could explain why Chinese shared knowledge less frequently than their American peers. Despite these reported cultural differences, findings from this research suggest that the actual cultural differences were smaller than what literature implies. Possible explanations for fewer cultural differences are explored. Practical implications for knowledge management practitioners are also offered.
Visual Gnosis and Face Perception
Authors: Tobimatsu Shozo
Published: May 2011

There are two major parallel pathways in humans: the parvocellular (P) and magnocellular (M) pathways. The former has excellent spatial resolution with color selectivity, while the latter shows excellent temporal resolution with high contrast sensitivity. Visual stimuli should be tailored to answer specific clinical and/or research questions. This chapter examines the neural mechanisms of face perception using event-related potentials (ERPs). Face stimuli of different spatial frequencies were used to investigate how low-spatial-frequency (LSF) and high-spatial-frequency (HSF) components of the face contribute to the identification and recognition of the face and facial expressions. The P100 component in the occipital area (Oz), the N170 in the posterior temporal region (T5/T6) and late components peaking at 270-390 ms (T5/T6) were analyzed. LSF enhanced P100, while N170 was augmented by HSF irrespective of facial expressions. This suggested that LSF is important for global processing of facial expressions, whereas HSF handles featural processing. There were significant amplitude differences between positive and negative LSF facial expressions in the early time windows of 270-310 ms. Subsequently, the amplitudes among negative HSF facial expressions differed significantly in the later time windows of 330–390 ms. Discrimination between positive and negative facial expressions precedes discrimination among different negative expressions in a sequential manner based on parallel visual channels. Interestingly, patients with schizophrenia showed decreased spatial frequency sensitivities for face processing. Taken together, the spatially filtered face images are useful for exploring face perception and recognition.
Tactile Pattern Delivery Device to Investigate Cognitive Mechanisms for Early Detection of Alzheimer’s Disease
Authors: Yang Jiajia , Ogasa Takashi , Wu Jinglong , Ohta Yasuyuki , Abe Koji
Published: May 2011

The cognitive symptoms in early Alzheimer’s disease (AD) involve problems with learning, memory or planning. Currently, no medical tests are available to conclusively diagnose dementia pre-mortem. Previous studies have demonstrated that the cognitive deficits of AD can be detected during a preclinical period with neuropsychological tests. This chapter’s hypothesis is that cognitive deficit symptoms of AD are detectable using a combination of tactile, kinetic, cognitive, and functional MRI tasks in the earliest stages of the disease. The authors of this chapter offer a novel approach to investigate the early detection of AD with tactile procedures. This chapter introduces the development of two tactile pattern delivery devices. The first delivery device is MRI-compatible and can serve to investigate the underlying neural mechanisms of active and passive tactile pattern discrimination. The second delivery device is designed to investigate the characteristics of passive shape discrimination for psychological experiments. These devices may contribute to the early detection of AD with neuropsychological approaches. The ultimate goal of this research was to confirm the human ability of tactile shape discrimination and determine the differences between age-matched healthy individuals and AD patients.
The Clinical Analysis of Combined Effects of Huperzine A and Memantine for Alzheimer’s Disease
Authors: Zhang Shouzi , Li Qinyun , Gao Maolong
Published: May 2011

The purpose of this study was to evaluate the clinical effects of a combination of Huperzine A and memantine for the treatment of Alzheimer’s disease (AD). Sixty patients (aged 69 ± 4.5), treated in both outpatient and hospital settings, were divided into two groups, the treated group and the control group. Over 24 weeks of clinical therapy, 30 patients received treatment with Huperzine A (0.2 mg/d), and the other 30 patients received a combination of Huperzine A (0.2 mg/d) and memantine (20 mg/d). Mini-mental State Examination (MMSE) was taken as the main value target. Activity of Daily Living Scale (ADL) and Neuropsychiatric Inventory (NPI) were secondary targets. Results: After 24 weeks, the scores from the MMSE, ADL, and NPI of the treatment group were more improved than those of the control group (P=0.05). Combination treatment with Huperzine A and memantine will be more effective for treating AD than treatment with Huperzine A alone.
Aß Monomer, Oligomer and Fibril in Alzheimer's Disease
Authors: Mori Hiroshi
Published: May 2011

Alzheimer’s disease (AD), the most prevalent disease of aged people, is a progressive neurodegenerative disorder with dementia. Amyloid-ß (also known as ß-protein and referred to here as Aß) is a well-established, seminal peptide in AD that is produced from the amyloid precursor protein (APP) by consecutive digestion with the ß secretase of BACE (beta-site amyloid cleaving enzyme) and gamma secretase of the presenilin complex. Abnormal cerebral accumulation of Abeta in the form of insoluble fibrils in senile plaques and cerebral amyloid angiopathy (CAA) is a neuropathological hallmark of AD. In contrast to insoluble fibrillary Aß, a soluble oligomeric complex, ADDL, consists of low-n oligomers of Aß, such as Aß*56. Despite their different names, it is currently proposed that oligomeric Aß is directly involved in synaptic toxicity and cognitive dysfunction in the early stages of AD. This chapter identifies a novel APP mutation (E693delta; referred to as the Osaka mutation) in a pedigree with probable AD, resulting in a variant Aß lacking glutamate at position 22. Based on theoretical predictions and in vitro studies on synthetic mutant Aß peptides, the mutated Aß peptide showed a unique and enhanced oligomerization activity without fibrillization. This was further confirmed by PiB-PET analysis on the proband patient. Collectively, the chapter concludes that the Osaka mutation is the first human evidence for the hypothesis that oligomeric Aß is involved in AD.
The Value of Quantitative EEG Measures in the Early Diagnosis of Alzheimer’s Disease
Authors: Tanaka Hideaki
Published: May 2011

There is growing interest in the discovery of clinically useful, robust biomarkers for Alzheimer’s disease (AD) and pre-AD; the ability to accurately diagnose AD or to predict conversion from a preclinical state to AD would aid in both prevention and early intervention. This study aimed to evaluate the usefulness of a statistical assessment of cortical activity using electroencephalograms (EEGs) with normative data and the ability of such an assessment to contribute to the diagnosis of AD. 15 patients with AD and 8 patients with mild cognitive impairment (MCI) were studied. Eyes-closed resting EEGs were digitally recorded at 200 Hz from 20 electrodes placed according to the international 10/20 system on the scalp, and 20 artifact-free EEG epochs lasting 2.56 ms were selected. Each EEG epoch was down-sampled to 100 Hz and matched to the normal data sets. The selected EEGs from each subject were analyzed by standardized Low Resolution Electromagnetic Tomography (sLORETA) and statistically compared with the age-matched normal data sets at all frequencies. This procedure resulted in cortical z values for each EEG frequency with 0.39 Hz frequency resolution for each subject. Some of the AD and MCI patients presented a peak of negative z value around 20 Hz, revealing hypoactivity of the parahippocampal gyrus and the insula in the sLORETA cortical image. In addition, severe cases of AD showed decreased parietal activation. These results were in agreement with evidence from statistical neuroimaging using MRI/SPECT. Submission of normal EEG data sets to sLORETA might be useful for the detection of diagnostic and predictive markers of AD and MCI in individual patients.
Apraxia
Authors: Hallett Mark
Published: May 2011

Apraxia is the inability to perform skilled and/or learned movements, not explainable on the basis of more elemental abnormalities. There are several types of apraxia of which the most commonly recognized are (1) limb kinetic apraxia, the loss of hand and finger dexterity; (2) ideomotor apraxia, deficits in pantomiming tool use and gestures with temporal and spatial errors, but with knowledge of the tasks still present; (3) ideational apraxia, the failure to carry out a series of tasks using multiple objects for an intended purpose; and (4) conceptual apraxia, loss of tool knowledge, when tools and objects are used inappropriately. Apraxia can be a feature of both frontotemporal dementia and Alzheimer disease, and even a rare presenting manifestation of both. How sensitive apraxia measures would be in early detection is not well known.
Neuronal Transcytosis of WGA Conjugated Protein
Authors: Takeuchi Yoshiki , Matsumoto Yoshiki , Miki Takanori , Warita Katsuhiko , Wang Zhi-Yu , Yakura Tomiko , Liu Jun-Qian
Published: May 2011

Neuronal transcytosis was observed at the stage when no neurotransmitter was released after the injection of wheat germ agglutinin-conjugated horseradish peroxidase (WGA-HRP; WGA = 22 kDa, HRP = 40 kDa) into the vagus nerve. The co-injection of Rab3A-siRNA with WGA-HRP into the vagus nerve was performed to further examine this phenomenon. This co-injection resulted in the transcytosis of WGA-HRP, both of the passing type, by which it crossed the synapses, and of the secretion type followed by endocytosis of postsynaptic membranes. These findings raised the possibility in vivo that WGA plays an important role in the transcytosis of protein. Therefore, WGA may be a valuable tool for therapeutic drug targeting via transcytosis. The ability of WGA-conjugated Amyloid ß (WGA-Aß) to decrease amyloid deposits in Alzheimer’s disease was investigated. The conjugation of WGA to amyloid-ß (1-40) (Aß; 5 kDa) was confirmed. WGA-Aß was then shown to move to terminals by axonal flow in vivo as well as WGA-HRP. WGA-Aß was also observed in the nodose ganglion cells and terminals after injections of fluorescent Aß (FAß) into the vagus nerve and fluorescent WGA (FWGA) into the common carotid artery. These studies suggested that WGA-Aß could be localized to solitary neurons via transcytosis.
Functional Optical Hemodynamic Imaging of the Olfactory Cortex in Patients with Parkinson’s Disease
Authors: Karaki Masayuki , Kobayashi Eiji , Kobayashi Ryuichi , Akiyama Kosuke , Toge Tetsuo , Mori Nozomu
Published: May 2011

Olfactory dysfunction is a frequent non-motor symptom in Parkinson’s disease (PD). This symptom is considered to be an early manifestation of the disease. The aim of this study was to establish the cortical basis of olfactory function in patients with PD. This study was conducted on ten healthy, normosmic subjects and seven patients with PD (one with subjective olfactory dysfunction and nine without subjective olfactory dysfunction). We employed a 22-channel near-infrared spectroscopy (NIRS) device with eight light-incident fibers and seven light-detector fibers, each with an inter-optode distance of 2.5 centimeters on the frontal head. Isovaleric acid was used as the odor stimulant. We measured the change in total hemoglobin concentrations (totalHb) from pre-baseline values and compared the results obtained for healthy normosmic subjects and patients with PD. In all healthy normosmic subjects and three patients with PD, isovaleric acid caused remarkable changes in (totalHb), especially in the lower areas of the frontal cortex. However, in four patients with PD, isovaleric acid caused no changes. This result indicates that subjective symptoms are different from objective test results in patients with PD. These activated areas may be related to the orbitofrontal cortex corresponding to the olfactory cortices. This study suggests that normosmic subjects with PD already have damage to their olfactory function.
Basic Study on the Effect of Scent on Arousal Level Using Multi-Channel Near-Infrared Spectroscopy (MNIRS)
Authors: Doi Shun’ichi , Wada Takahiro , Kobayashi Eiji , Karaki Masayuki , Mori Nozomu
Published: May 2011

As a result, it is verified that not only characteristics of the scent but also the driver’s preference and subjective judgment of scent changes affect on the each driving performance. The brain activity change by olfactory stimulation and the brain blood flow change by other stimulation were also investigated. The effects of the functional brain imaging of olfactory activity were measured and the comfortable scent for the individual subject was verified to be effective for maintaining the arousal level.