Determination of Skills Gap between School-Based Learning and Laboratory-Based Learning in Omar Al-Mukhtar University

This paper provides an identification of the existing practical skills gap between school-based learning (SBL) and laboratory based learning (LBL) in the Computing Department within the Faculty of Science at Omar Al-Mukhtar University in Libya. A survey has been conducted and the first author has elicited the responses of two groups of stakeholders, namely the academic teachers and students. The primary goal is to review the main strands of evidence available and argue that there is a gap between laboratory and school-based learning in terms of opportunities for experiment and application of skills. In addition, the nature of experimental work within the laboratory at Omar Al-Mukhtar University needs to be reconsidered. Another goal of our study was to identify the reasons for students’ poor performance in the laboratory and to determine how this poor performance can be eliminated by the modification of teaching methods. Bloom’s taxonomy of learning outcomes has been applied in order to classify questions and problems into categories, and the survey was formulated with reference to third year Computing Department students. Furthermore, to discover students’ opinions with respect to all the issues, an exercise was conducted. The survey provided questions related to what the students had learnt and how well they had learnt. We were also interested in feedback on how to improve the course and the final question provided an opportunity for such feedback.

Genetic Algorithm for In-Theatre Military Logistics Search-and-Delivery Path Planning

Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Smart Cane Assisted Mobility for the Visually Impaired

An efficient reintegration of the disabled people in the family and society should be fulfilled; hence it is strongly needful to assist their diminished functions or to replace the totally lost functions. Assistive technology helps in neutralizing the impairment. Recent advancements in embedded systems have opened up a vast area of research and development for affordable and portable assistive devices for the visually impaired. Granted there are many assistive devices on the market that are able to detect obstacles, and numerous research and development currently in process to alleviate the cause, unfortunately the cost of devices, size of devices, intrusiveness and higher learning curve prevents the visually impaired from taking advantage of available devices. This project aims at the design and implementation of a detachable unit which is robust, low cost and user friendly, thus, trying to aggrandize the functionality of the existing white cane, to concede above-knee obstacle detection. The designed obstruction detector uses ultrasound sensors for detecting the obstructions before direct contact. It bestows haptic feedback to the user in accordance with the position of the obstacle.

State-Space PD Feedback Control

A challenged control problem is when the performance is pushed to the limit. The state-derivative feedback control strategy directly uses acceleration information for feedback and state estimation. The derivative part is concerned with the rateof- change of the error with time. If the measured variable approaches the set point rapidly, then the actuator is backed off early to allow it to coast to the required level. Derivative action makes a control system behave much more intelligently. A sensor measures the variable to be controlled and the measured in formation is fed back to the controller to influence the controlled variable. A high gain problem can be also formulated for proportional plus derivative feedback transformation. Using MATLAB Simulink dynamic simulation tool this paper examines a system with a proportional plus derivative feedback and presents an automatic implementation of finding an acceptable controlled system. Using feedback transformations the system is transformed into another system.

Robust Stability in Multivariable Neural Network Control using Harmonic Analysis

Robust stability and performance are the two most basic features of feedback control systems. The harmonic balance analysis technique enables to analyze the stability of limit cycles arising from a neural network control based system operating over nonlinear plants. In this work a robust stability analysis based on the harmonic balance is presented and applied to a neural based control of a non-linear binary distillation column with unstructured uncertainty. We develop ways to describe uncertainty in the form of neglected nonlinear dynamics and high harmonics for the plant and controller respectively. Finally, conclusions about the performance of the neural control system are discussed using the Nyquist stability margin together with the structured singular values of the uncertainty as a robustness measure.

The Relationship between Students- Socio-Economic Backgrounds and Student Residential Satisfaction

Debates on residential satisfaction topic have been vigorously discussed in family house setting. Nonetheless, less or lack of attention was given to survey on student residential satisfaction in the campus house setting. This study, however, tried to fill in the gap by focusing more on the relationship between students- socio-economic backgrounds and student residential satisfaction with their on-campus student housing facilities. Two-stage cluster sampling method was employed to classify the respondents. Then, self-administered questionnaires were distributed face-to-face to the students. In general, it was confirmed that the students- socioeconomic backgrounds have significantly influence the students- satisfaction with their on-campus student housing facilities. The main influential factors were revealed as the economic status, sense of sharing, and the ethnicity of roommates. Likewise, this study could also provide some useful feedback for the universities administration in order to improve their student housing facilities.

Applications of Prediction and Identification Using Adaptive DCMAC Neural Networks

An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.

An Augmented Automatic Choosing Control Designed by Extremizing a Combination of Hamiltonian and Lyapunov Functions for Nonlinear Systems with Constrained Input

In this paper we consider a nonlinear feedback control called augmented automatic choosing control (AACC) for nonlinear systems with constrained input. Constant terms which arise from section wise linearization of a given nonlinear system are treated as coefficients of a stable zero dynamics.Parameters included in the control are suboptimally selectedby extremizing a combination of Hamiltonian and Lyapunov functions with the aid of the genetic algorithm. This approach is applied to a field excitation control problem of power system to demonstrate the splendidness of the AACC. Simulation results show that the new controller can improve performance remarkably well.

A Comparative Study of the Effectiveness of Trained Inspectors in Different Workloads between Feed Forward and Feedback Training

Objective of this study was to study and compare the effectiveness of inspectors who had different workloads for feed forward and feedback training. The visual search task was simulated to search for specified alphabets called defects. These defects were included of four alphabets in Thai and English such as s ภ, ถ, X, and V with different background. These defects were combined in the specified alphabets and were given the different three backgrounds i.e., Thai, English, and mixed English and Thai alphabets. Sixty students were chosen as a sample in this study and test for final selection subject. Finally, five subjects were taken into testing process. They were asked to search for defects after they were provided basic information. Experiment design was used factorial design and subjects were trained for feed forward and the feedback training. The results show that both trainings were affected on mean search time. It was also found that the feedback training can increase the effectiveness of visual inspectors rather than the feed forward training significantly different at the level of .05

On-line Recognition of Isolated Gestures of Flight Deck Officers (FDO)

The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.

The System Identification and PID Lead-lag Control for Two Poles Unstable SOPDT Process by Improved Relay Method

This paper describes identification of the two poles unstable SOPDT process, especially with large time delay. A new modified relay feedback identification method for two poles unstable SOPDT process is proposed. Furthermore, for the two poles unstable SOPDT process, an additional Derivative controller is incorporated parallel with relay to relax the constraint on the ratio of delay to the unstable time constant, so that the exact model parameters of unstable processes can be identified. To cope with measurement noise in practice, a low pass filter is suggested to get denoised output signal toimprove the exactness of model parameter of unstable process. PID Lead-lag tuning formulas are derived for two poles unstable (SOPDT) processes based on IMC principle. Simulation example illustrates the effectiveness and the simplicity of the proposed identification and control method.

A New Proportional - Pursuit Coupled Guidance Law with Actuator Delay Compensation

The aim of this paper is to present a new three-dimensional proportional-pursuit coupled (PP) guidance law to track highly maneuverable aircraft. Utilizing a 3-D polar coordinate frame, the PP guidance law is formed by collecting proportional navigation guidance in Z-R plane and pursuit guidance in X-Y plane. Feedback linearization control method to solve the guidance accelerations is used to implement PP guidance. In order to compensate the actuator time delay, the time delay compensated version of PP guidance law (CPP) was derived and proved the effectiveness of modifying the problem of high acceleration in the final phase of pursuit guidance and improving the weak robustness of proportional navigation. The simulation results for intercepting Max G turn situation show that the proposed proportional-pursuit coupled guidance law guidance law with actuator delay compensation (CPP) possesses satisfactory robustness and performance.

Haptics Enabled Offline AFM Image Analysis

Current advancements in nanotechnology are dependent on the capabilities that can enable nano-scientists to extend their eyes and hands into the nano-world. For this purpose, a haptics (devices capable of recreating tactile or force sensations) based system for AFM (Atomic Force Microscope) is proposed. The system enables the nano-scientists to touch and feel the sample surfaces, viewed through AFM, in order to provide them with better understanding of the physical properties of the surface, such as roughness, stiffness and shape of molecular architecture. At this stage, the proposed work uses of ine images produced using AFM and perform image analysis to create virtual surfaces suitable for haptics force analysis. The research work is in the process of extension from of ine to online process where interaction will be done directly on the material surface for realistic analysis.

A 1.5V,100MS/s,12-bit Current-Mode CMOSS ample-and-Hold Circuit

A high-linearity and high-speed current-mode sampleand- hold circuit is designed and simulated using a 0.25μm CMOS technology. This circuit design is based on low voltage and it utilizes a fully differential circuit. Due to the use of only two switches the switch related noise has been reduced. Signal - dependent -error is completely eliminated by a new zero voltage switching technique. The circuit has a linearity error equal to ±0.05μa, i.e. 12-bit accuracy with a ±160 μa differential output - input signal frequency of 5MHZ, and sampling frequency of 100 MHZ. Third harmonic is equal to –78dB.

A New Approach to Feedback Shift Registers

The pseudorandom number generators based on linear feedback shift registers (LFSRs), are very quick, easy and secure in the implementation of hardware and software. Thus they are very popular and widely used. But LFSRs lead to fairly easy cryptanalysis due to their completely linearity properties. In this paper, we propose a stochastic generator, which is called Random Feedback Shift Register (RFSR), using stochastic transformation (Random block) with one-way and non-linearity properties.

A Novel Nano-Scaled SRAM Cell

To help overcome limits to the density of conventional SRAMs and leakage current of SRAM cell in nanoscaled CMOS technology, we have developed a four-transistor SRAM cell. The newly developed CMOS four-transistor SRAM cell uses one word-line and one bit-line during read/write operation. This cell retains its data with leakage current and positive feedback without refresh cycle. The new cell size is 19% smaller than a conventional six-transistor cell using same design rules. Also the leakage current of new cell is 60% smaller than a conventional sixtransistor SRAM cell. Simulation result in 65nm CMOS technology shows new cell has correct operation during read/write operation and idle mode.

Virtual Environments...Vehicle for Pedagogical Advancement

Virtual environments are a hot topic in academia and more importantly in courses offered via distance education. Today-s gaming generation view virtual worlds as strong social and interactive mediums for communicating and socializing. And while institutions of higher education are challenged with increasing enrollment while balancing budget cuts, offering effective courses via distance education become a valid option. Educators can utilize virtual worlds to offer students an enhanced learning environment which has the power to alleviate feelings of isolation through the promotion of communication, interaction, collaboration, teamwork, feedback, engagement and constructivists learning activities. This paper focuses on the use of virtual environments to facilitate interaction in distance education courses so as to produce positive learning outcomes for students. Furthermore, the instructional strategies were reviewed and discussed for use in virtual worlds to enhance learning within a social context.

A Novel Adaptive E-Learning Model Based on Developed Learner's Styles

Adaptive e-learning today gives the student a central role in his own learning process. It allows learners to try things out, participate in courses like never before, and get more out of learning than before. In this paper, an adaptive e-learning model for logic design, simplification of Boolean functions and related fields is presented. Such model presents suitable courses for each student in a dynamic and adaptive manner using existing database and workflow technologies. The main objective of this research work is to provide an adaptive e-learning model based learners' personality using explicit and implicit feedback. To recognize the learner-s, we develop dimensions to decide each individual learning style in order to accommodate different abilities of the users and to develop vital skills. Thus, the proposed model becomes more powerful, user friendly and easy to use and interpret. Finally, it suggests a learning strategy and appropriate electronic media that match the learner-s preference.

Design and Performance of Adaptive Polarized MIMO MC-SS-CDMA System for Downlink Mobile Communications

In this paper, an adaptive polarized Multiple-Input Multiple-Output (MIMO) Multicarrier Spread Spectrum Code Division Multiple Access (MC-SS-CDMA) system is designed for downlink mobile communications. The proposed system will be examined in Frequency Division Duplex (FDD) mode for both macro urban and suburban environments. For the same transmission bandwidth, a performance comparison between both nonoverlapped and orthogonal Frequency Division Multiplexing (FDM) schemes will be presented. Also, the proposed system will be compared with both the closed loop vertical MIMO MC-SS-CDMA system and the synchronous vertical STBC-MIMO MC-SS-CDMA system. As will be shown, the proposed system introduces a significant performance gain as well as reducing the spatial dimensions of the MIMO system and simplifying the receiver implementation. The effect of the polarization diversity characteristics on the BER performance will be discussed. Also, the impact of excluding the cross-polarization MCSS- CDMA blocks in the base station will be investigated. In addition, the system performance will be evaluated under different Feedback Information (FBI) rates for slowly-varying channels. Finally, a performance comparison for vehicular and pedestrian environments will be presented

Controller Design for Euler-Bernoulli Smart Structures Using Robust Decentralized FOS via Reduced Order Modeling

This paper features the modeling and design of a Robust Decentralized Fast Output Sampling (RDFOS) Feedback control technique for the active vibration control of a smart flexible multimodel Euler-Bernoulli cantilever beams for a multivariable (MIMO) case by retaining the first 6 vibratory modes. The beam structure is modeled in state space form using the concept of piezoelectric theory, the Euler-Bernoulli beam theory and the Finite Element Method (FEM) technique by dividing the beam into 4 finite elements and placing the piezoelectric sensor / actuator at two finite element locations (positions 2 and 4) as collocated pairs, i.e., as surface mounted sensor / actuator, thus giving rise to a multivariable model of the smart structure plant with two inputs and two outputs. Five such multivariable models are obtained by varying the dimensions (aspect ratios) of the aluminium beam. Using model order reduction technique, the reduced order model of the higher order system is obtained based on dominant Eigen value retention and the Davison technique. RDFOS feedback controllers are designed for the above 5 multivariable-multimodel plant. The closed loop responses with the RDFOS feedback gain and the magnitudes of the control input are obtained and the performance of the proposed multimodel smart structure system is evaluated for vibration control.