Neuroinformatics in Functional Neuroimaging

This Ph.D. thesis proposes methods for information retrieval in functional neuroimaging through automatic computerized authority identification, and searching and cleaning in a neuroscience database. Authorities are found through cocitation analysis of the citation pattern among scientific articles. Based on data from a single scientific journal it is shown that multivariate analyses are able to determine group structure that is interpretable as particular “known ” subgroups in functional neuroimaging. Methods for text analysis are suggested that use a combination of content and links, in the form of the terms in scientific documents and scientific citations, respectively. These included context sensitive author ranking and automatic labeling of axes and groups in connection with multivariate analyses of link data. Talairach foci from the BrainMap ™ database are modeled with conditional probability density models useful for exploratory functional volumes modeling. A further application is shown with conditional outlier detection where abnormal entries in the BrainMap ™ database are spotted using kernel density modeling and the redundancy between anatomical labels and spatial Talairach coordinates. This represents a combination of simple term and spatial modeling. The specific outliers that were found in the BrainMap ™ database constituted among others: Entry errors, errors in the article and unusual terminology

Augmented Reality

Augmented Reality (AR) is a natural development from virtual reality (VR), which was developed several decades earlier. AR complements VR in many ways. Due to the advantages of the user being able to see both the real and virtual objects simultaneously, AR is far more intuitive, but it's not completely detached from human factors and other restrictions. AR doesn't consume as much time and effort in the applications because it's not required to construct the entire virtual scene and the environment. In this book, several new and emerging application areas of AR are presented and divided into three sections. The first section contains applications in outdoor and mobile AR, such as construction, restoration, security and surveillance. The second section deals with AR in medical, biological, and human bodies. The third and final section contains a number of new and useful applications in daily living and learning

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Proceedings of the 5th international conference on disability, virtual reality and associated technologies (ICDVRAT 2004)

The proceedings of the conferenc

Assessment of a novel computer aided learning tool in neuroanatomy education

Impaired understanding of intricate neuroanatomical concepts and structural inter-relationships has been associated with a fear of managing neurology patients, called neurophobia, among medical trainees. As technology advances, the role of e-learning pedagogies becomes more important to supplement the traditional dissection / prosection and lecture-based pedagogies for teaching neuroanatomy to undergraduate students. However, despite the availability of a myriad of e-learning resources, the neuro (-anatomy-) phobia – neurophobia nexus prevails. The focus of the PhD was to investigate the difficulties associated with learning neuroanatomy and to develop and assess the efficacy of a novel e-learning tool for teaching neuroanatomy, in the context of the strengths and pitfalls of the currently available e-learning resources. Firstly, we sought to provide direct evidence of the medical and health science students’ perception regarding specific challenges associated with learning neuroanatomy. The initial results showed that neuroanatomy is perceived as a more difficult subject compared to other anatomy topics, with spinal pathways being the most challenging to learn. Participants believed that computer assisted learning and online resources could enhance neuroanatomy understanding and decrease their neurophobia. Next, in the context of the significance of e-learning for supplementing traditional pedagogies, we identified features of neuroanatomy web-resources that were valued by students and educators with regards to learning neuroanatomy of the spinal pathways. Participants identified strengths and weaknesses of existing neuroanatomy web-resources and ranked one resource above the others in terms of information delivery and integration of clinical, physiological and medical imaging correlates. This provides a novel user perspective on the influence of specific elements of neuroanatomy web-resources to improve instructional design and enhance learner performance. Finally, considering the data acquired from students and educators, a novel, interactive, neuroanatomy learning e-resource was developed to support teaching of the neuroanatomy of the spinal pathways. The instructional design included a discussion of the clinical interpretation of basic neuroanatomical facts to aid in neurological localization. The e-learning tool was assessed and evaluated by undergraduate medical and neuroscience students using neuroanatomy knowledge quizzes and Likert-scale perception questionnaires and compared to the previously identified best-ranked neuroanatomy e-resource. Participants’ opinion regarding the usefulness of various components of the tools was also gauged. The results showed that usage of the UCC e-resource led to a significant increase in participants’ knowledge of the neuroanatomy of the spinal pathways compared to students’ who did not use e-resources. Moreover, the participants reported a greater interest in learning neuroanatomy with the novel tool, showing a greater appreciation for it while learning clinical neurological correlates compared to those using the best available e-resource identified earlier. In summary, the prevailing problem of neurophobia could be addressed by enhancing student-interest. Technological e-learning pedagogies, with intelligently designed interactive user-interface and clinical correlation of basic neuroanatomical facts can play a pivotal role in helping students learn neuroanatomy and breaking the nexus between neuro (-anatomy-) phobia and neurophobia

Proceedings of the 2nd European conference on disability, virtual reality and associated technologies (ECDVRAT 1998)

The proceedings of the conferenc

Multiple Heat Exchanger Cooling System for Automotive Applications – Design, Mathematical Modeling, and Experimental Observations

The design of the automotive cooling systems has slowly evolved from engine-driven mechanical to computer-controlled electro-mechanical components. With the addition of computer-controlled variable speed actuators, cooling system architectures have been updated to maximize performance and efficiency. By switching from one large radiator to multiple smaller radiators with individual flow control valves, the heat rejection requirements may be precisely adjusted. The combination of computer regulated thermal management system should reduce power consumption while satisfying temperature control objectives. This research focuses on developing and analyzing a multi-radiator system architecture for implementation in ground transportation applications. The premise is to use a single radiator during low thermal loads and activate the second radiator during high thermal loading scenarios. Ground vehicles frequently use different radiators for each component that needs cooling (e.g., engine blocks, electronics, and motors) since they have different optimal working temperatures. The use of numerous smaller heat exchangers adds more energy-management features and alternative routes for carrying on with operation in the event of a crucial subsystem failure. Moreover, despite cooling systems being designed for maximum thermal loads, most vehicles typically operate at a small fraction of their peak values. To study and examine the planned multi-heat exchanger cooling system concepts, various computer simulations and experimental tests were performed. A nonlinear state space model, featuring input and output heat flow paradigms, was developed using a multi-node resistance-capacitance thermal model. The heat removal rate from the radiator(s) was estimated using the -NTU method as downstream fluid temperatures were not required. The system performance was studied for two driving cycles proposed by the Environmental Protection Agency (EPA) – urban and highway driving schedules. The computer simulation was validated using the laboratory setup in the High Bay Area of Fluor Daniel Engineering Innovation Building. The configuration features computer controlled variable speed electric motor driven coolant pump and independent variable speed fans for each radiator to provide desired fluid flow rates. The pump and fan power consumptions are approximately 0.8-1.2 kW and 0.4-3.2 kW, which corresponds to coolant and air flow rates of 0.2-1.5 kg/s and 0.5-1.75 kg/s, respectively. Two servo motor-controlled gate valves limit the coolant outlet from each radiator. Various thermocouples and a magnetic flow sensor record test data in real time using a dSpace DS1103 data acquisition control system. Designing and analyzing a nonlinear control architecture for the suggested system was the last phase in the study process. A nonlinear controller equipped TMS should offer higher energy efficiency and overall system performance. Three controllers—sliding mode, stateflow, and classical—were designed and implemented in Matlab/Simulink and placed onto the dSpace hardware. The sliding mode controller is recommended for high performance applications since it offers steady temperature tracking, 5oC, an acceptable response time, 120 sec, but suffers from frequent changes in fan speed. The stateflow controller exhibited the fewest fan speed oscillations, the fastest response time, 88 sec, and the smallest temperature offset, 3oC, it is advised for use in common passenger vehicle applications. Both controllers need around six minutes to warm up. The traditional controller, meanwhile, had the quickest warmup, 600 sec, but the slowest response time, 215 sec. Nonlinear cooling systems are essential for maintaining component temperatures which will enable vehicle reliability, and maximize performance given the focus on hybrid and electric vehicles

Investigation of Advanced Engine Cooling Systems - Optimization and Nonlinear Control

Advanced automotive engine cooling systems can positively impact the performance, fuel economy, and reliability of internal combustion engines. A smart engine cooling system typically features multiple real time computer controlled actuators: a three way linear smart valve, a variable speed coolant pump, and electric radiator fan(s). In this dissertation, several innovative comprehensive nonlinear control and optimization operation strategies for the next generation smart cooling application will be analyzed. First, the optimal control has been investigated to minimize the electric energy usage of radiator fan matrix. A detailed mathematical model of the radiator fan(s) matrix operation and the forced convection heat transfer process was developed to establish a mixed integer nonlinear programming problem. An interior points approach was introduced to solve the energy consumption minimization problem. A series of laboratory tests have been conducted with different fan configurations and rotational shaft speed combinations, with the objective to cool a thermal loaded engine. Both the mathematical approach and the laboratory test results demonstrated the effectiveness of similar control strategies. Based on the tests data and mathematical analysis, an optimization control strategy reduced the fan matrix power consumption by up to 67%. Second, a series of experimental laboratory tests were implemented to investigate the contributions of each electro-mechanical device in automotive thermal management system. The test results established a basis for several key operating conclusions. The smart valve and variable speed pump impacted the engine temperature by adjusting the heat transfer rate between the engine and the radiator through coolant redirection and/or coolant flow rate. On the other hand, the radiator fan(s) operation affects the engine\u27s temperature by modifying the heat rejection rate of the radiator which can influence the entire cooling system. In addition, the smart valve\u27s operation changes the engine\u27s temperature magnitude the greatest amount followed by the radiator fan(s) and the coolant pump. Furthermore, from a power consumption aspect, the radiator fan(s) consumes the most engine power in comparison to the two other actuators. Third, a Lyapunov based nonlinear control strategy for the radiator fan matrix was studied to accommodate transient engine temperature tracking at heavy heat load. A reduced order mathematical model established a basis for the closed-loop real time feedback system. Representative numerical and experimental tests demonstrated that the advanced control strategy can regulate the engine temperature tracking error within 0.12°C and compensate the unknown heat load. The nonlinear controller provided superior performance in terms of power consumption and temperature tracking as evident by the reduced magnitude when compared to a classical proportional integral with lookup table based controller and a bang bang controller. Fourth, a nonlinear adaptive multiple-input and multiple-output (NAMIMO) controller to operate the smart valve and radiator fans has been presented. This controller regulates the engine temperature while compensating for unknown wide range heat loads and ram air effects. A nonlinear adaptive backstepping (NAB) control strategy and a state flow (SF) control law were introduced for comparisons. The test results indicated that the NAMIMO successfully regulated the engine temperature to a desired value (tracking error, |e|\u3c0.5°C, at steady state) subject to various working conditions. In contrast, the NAB control law consumes the least radiator fan power but demonstrated a larger average temperature tracking error (40% greater than the NAMIMO controller), a longer response time (34% greater than the NAMIMO controller), and defected when the heat load was low. Lastly, the SF controller, characterized by greater oscillation and electrical power consumption (18.9% greater than the NAMIMO controller), was easy to realize and maintained the engine temperature to within |e|\u3c5°C. An important aspect of engineering research is the knowledge gained from learning materials to fully understand the thermal management. As part of the dissertation, advanced three-dimensional (3D) visualization and virtual reality (VR) technology based engineering education methods has been studied. A series of computer aided design (CAD) models with storyboards have been created to provide a step to step guide for developing the learning modules. The topics include automotive, aerospace, and manufacturing. The center for aviation and automotive technological education using virtual e-schools (CA2VES) at Clemson University has developed a comprehensive e-learning system integrated with eBooks, mini video lectures, 3D virtual reality technologies, and online assessments as supplementary materials to engineering education