An Original Real Time Expert Model for the Operation and Control of the Water Supply Aqueduct of the Greater Athens Area, using Fuzzy Reasoning and Computer Assisted Learning

Author(s):  
L.S. Vamvakeridou-Lyroudia ◽  
H. Giovanopoulos
2020 ◽  
Vol 2 (2) ◽  
pp. 134-142
Author(s):  
Sharon Anyango Onditi ◽  
Stephen Oloo Ajwang

This study examined the effects of Computer Assisted Learning (CAL) on the mastery of Science concepts by learners in universities. Teaching and learning of Science concepts present learners with numerous challenges. Of critical concern is the negative perception by learners that Science based subjects are difficult, thus contributing to widespread poor performance by the learners in the national examinations and subsequently poor choice of the subject in the universities. Solomon Four Group experimental design was employed for the study. The target population comprised all first-year students taking science subjects in 8 universities in western Kenya. A sample size of 335 students was determined using Krejcie Morgan table (1970). The universities were divided into two forming experimental and control groups.  The study was carried out in 4 months spanning 16 weeks where pretest was administered after the first 8 weeks of conventional teaching and post-test administered after the next 8 weeks of treatment. Pretest and post-test Science Achievements Test (SAT) on two topics, digestive system and light and optics, were designed and administered by the respective lecturers, and scores recorded. Piloting was carried before the use of the instruments, and a reliability coefficient of 0.85 on SAT was recorded.  Data were analyzed using t-test one-way ANOVA. The study found that 171 students taught using CAL achieved significantly higher scores in SAT compared to164 students taught through conventional methods with a mean gain of 2.851. The study demonstrated that CAL enhanced active manipulation of content and promoted interaction with content, and gave reality to abstraction. The study may be significant to educationists, lecturers, researchers, and policy makers as it provides insight on the benefits of applying Computer Assisted Learning in Science Education. 


2011 ◽  
Author(s):  
Peter Kazanzides ◽  
Min Yang Jung ◽  
Anton Deguet ◽  
Balazs Vagvolgyi ◽  
Marcin Balicki ◽  
...  

This paper presents the rationale for the use of a component-based architecture for computer-assisted intervention (CAI) systems, including the ability to reuse components and to easily develop distributed systems. We introduce three additional capabilities, however, that we believe are especially important for research and development of CAI systems. The first is the ability to deploy components among different processes (as conventionally done) or within the same process (for optimal real-time performance), without requiring source-level modifications to the component. This is particularly relevant for real-time video processing, where the use of multiple processes could cause perceptible delays in the video stream. The second key feature is the ability to dynamically reconfigure the system. In a system composed of multiple processes on multiple computers, this allows one process to be restarted (e.g., after correcting a problem) and reconnected to the rest of the system, which is more convenient than restarting the entire distributed application and enables better fault recovery. The third key feature is the availability of run-time tools for data collection, interactive control, and introspection, and offline tools for data analysis and playback. The above features are provided by the open-source cisst software package, which forms the basis for the Surgical Assistant Workstation (SAW) framework. A complex computer-assisted intervention system for retinal microsurgery is presented as an example that relies on these features. This system integrates robotics, stereo microscopy, force sensing, and optical coherence tomography (OCT) imaging to transcend the current limitations of vitreoretinal surgery.


1981 ◽  
Vol 18 (3) ◽  
pp. 197-203
Author(s):  
C. McCorkell ◽  
R. N. Wilson

Attempts to include Computer-Aided Design and Computer-Assisted Learning facilities in a substantial way into undergraduate teaching lead inevitably to a consideration of appropriate (efficient) methods of instruction. A method based on syndication of tasks, used at Ulster Polytechnic, is described. The method has been found particularly useful in teaching System Dynamics and Control.


Author(s):  
R. Rajesh ◽  
R. Droopad ◽  
C. H. Kuo ◽  
R. W. Carpenter ◽  
G. N. Maracas

Knowledge of material pseudodielectric functions at MBE growth temperatures is essential for achieving in-situ, real time growth control. This allows us to accurately monitor and control thicknesses of the layers during growth. Undesired effusion cell temperature fluctuations during growth can thus be compensated for in real-time by spectroscopic ellipsometry. The accuracy in determining pseudodielectric functions is increased if one does not require applying a structure model to correct for the presence of an unknown surface layer such as a native oxide. Performing these measurements in an MBE reactor on as-grown material gives us this advantage. Thus, a simple three phase model (vacuum/thin film/substrate) can be used to obtain thin film data without uncertainties arising from a surface oxide layer of unknown composition and temperature dependence.In this study, we obtain the pseudodielectric functions of MBE-grown AlAs from growth temperature (650°C) to room temperature (30°C). The profile of the wavelength-dependent function from the ellipsometry data indicated a rough surface after growth of 0.5 μm of AlAs at a substrate temperature of 600°C, which is typical for MBE-growth of GaAs.


2009 ◽  
Vol 14 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Ulrich W. Ebner-Priemer ◽  
Timothy J. Trull

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.


1994 ◽  
Vol 33 (01) ◽  
pp. 60-63 ◽  
Author(s):  
E. J. Manders ◽  
D. P. Lindstrom ◽  
B. M. Dawant

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.


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