Academic Staff Perceptions of the Value of the Elements of an Online Learning Environment

Based on 276 responses from academic staff in an evaluation of an online learning environment (OLE), this paper identifies those elements of the OLE that were most used and valued by staff, those elements of the OLE that staff most wanted to see improved, and those factors that most contributed to staff perceptions that the use of the OLE enhanced their teaching. The most used and valued elements were core functions, including accessing unit information, accessing lecture/tutorial/lab notes, and reading online discussions. The elements identified as most needing attention related to online assessment: submitting assignments, managing assessment items, and receiving feedback on assignments. Staff felt that using the OLE enhanced their teaching when they were satisfied that their students were able to access and use their learning materials, and when they were satisfied with the professional development they received and were confident with their ability to teach with the OLE.

Extraction in Two-Phase Systems and Some Properties of Laccase from Lentinus polychrous

Extraction of laccase produced by L. polychrous in an aqueous two-phase system, composed of polyethylene glycol and phosphate salt at pH 7.0 and 250C was investigated. The effect of PEG molecular weight, PEG concentration and phosphate concentration was determined. Laccase preferentially partitioned to the top phase. Good extraction of laccase to the top phase was observed with PEG 4000. The optimum system was found in the system containing 12% w/w PEG 4000 and 16% w/w phosphate salt with KE of 88.3, purification factor of 3.0-fold and 99.1% yield. Some properties of the enzyme such as thermal stability, effect of heavy metal ions and kinetic constants were also presented in this work. The thermal stability decreased sharply with high temperature above 60 0C. The enzyme was inhibited by Cd2+, Pb2+, Zn2+ and Cu2+. The Vmax and Km values of the enzyme were 74.70 μmol/min/ml and 9.066 mM respectively.

Density Wave Instability of Supercritical Kerosene in Active Cooling Channels of Scramjets

Experimental investigations were made on the instability of supercritical kerosene flowing in active cooling channels. Two approaches were used to control the pressure in the channel. One is the back-pressure valve while the other is the venturi. In both conditions, a kind of low-frequency oscillation of pressure and temperature is observed. And the oscillation periods are calculated. By comparison with the flow time, it is concluded that the instability occurred in active cooling channels is probably one kind of density wave instability. And its period has no relationship with the cooling channel geometry, nor the pressure, but only depends on the flow time of kerosene in active cooling channels. When the mass flow rate, density and pressure drop couple with each other, the density wave instability will appear.

Teacher Education Reform and InternationalGlobalization Hegemony: Issues and Challengesin Turkish Teacher Education

Educational reforms are focused point of different nations. New reform movements generally claim that something is wrong with the current state of affairs, and that the system is deficient in its goals, its accomplishments and it is accused not being adopted into global changes all over the world. It is the same for Turkish education system. It is considered those recent reforms of teacher education in Turkey and the extent to which they reflect a response to global economic pressures. The paper challenges the view that such imposes are inevitable determinants of educational policy and argues that any country will need to develop its own national approach to modernizing teacher education in light of the global context and its particular circumstances. It draws on the idea of reflexive modernization developed by educators and discusses its implications for teacher education policy. The paper deals with four themes teacher education in last decade policy in Turkey; the shift away from the educational disciplines, the shift towards school-based approaches, and the emergence of more centralized forms of accountability of teacher competence.

A Study of Factors Influencing the Improvement of Technology Business Incubator's Effectiveness: An Explanatory Model

In Both developed and developing countries, governments play a basic role in making policies, programs and instruments which support the development of micro, small and medium enterprises. One of the mechanisms employed to nurture small firms for more than two decades is business incubation. One of the mechanisms employed to nurture small firms for more than two decades is technology business incubation. The main aim of this research was to establish influencing factors in Technology Business Incubator's effectiveness and their explanatory model. Therefore, among 56 Technology Business Incubators in Iran, 32 active incubators were selected and by stratified random sampling, 528 start-ups were chosen. The validity of research questionnaires was determines by expert consensus, item analysis and factor analysis; and their reliability calculated by Cronbach-s alpha. Data analysis was then made through SPSS and LISREL soft wares. Both organizational procedures and entrepreneurial behaviors were the meaningful mediators. Organizational procedures with (P < .01, β =0.45) was stronger mediator for the improvement of Technology Business Incubator's effectiveness comparing to entrepreneurial behavior with (P < .01, β =0.36).

Energy Consumption and Carbon Calculations of Microalgae Biodiesel

At present, the severe oil crisis and greenhouse effect are booming, which is a growing worry for China. Over a long period of study, choosing the development of biological diesel is a feasible way in the desertification region in China. With considering the adaptability of Micro-algae in desertification region and analyzing energy consumption and carbon calculations of Micro-algae biodiesel produced by JJ company , this paper, make the microalgae our optimal choice to develop biological diesel in china's desertification region.

Fault Detection and Identification of COSMED K4b2 Based On PCA and Neural Network

COSMED K4b2 is a portable electrical device designed to test pulmonary functions. It is ideal for many applications that need the measurement of the cardio-respiratory response either in the field or in the lab is capable with the capability to delivery real time data to a sink node or a PC base station with storing data in the memory at the same time. But the actual sensor outputs and data received may contain some errors, such as impulsive noise which can be related to sensors, low batteries, environment or disturbance in data acquisition process. These abnormal outputs might cause misinterpretations of exercise or living activities to persons being monitored. In our paper we propose an effective and feasible method to detect and identify errors in applications by principal component analysis (PCA) and a back propagation (BP) neural network.

Tuning a Fractional Order PID Controller with Lead Compensator in Frequency Domain

To achieve the desired specifications of gain and phase margins for plants with time-delay that stabilized with FO-PID controller a lead compensator is designed. At first the range of controlled system stability based on stability boundary criteria is determined. Using stability boundary locus method in frequency domain the fractional order controller parameters are tuned and then with drawing bode diagram in frequency domain accessing to desired gain and phase margin are shown. Numerical examples are given to illustrate the shapes of the stabilizing region and to show the design procedure.

Preliminary Overview of Data Mining Technology for Knowledge Management System in Institutions of Higher Learning

Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. Several concepts from literature are adapted, for proposing the new integrative data mining technology and KMS framework to an IHL.

Heuristics Analysis for Distributed Scheduling using MONARC Simulation Tool

Simulation is a very powerful method used for highperformance and high-quality design in distributed system, and now maybe the only one, considering the heterogeneity, complexity and cost of distributed systems. In Grid environments, foe example, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. In addition, Grid test-beds are limited and creating an adequately-sized test-bed is expensive and time consuming. Scalability, reliability and fault-tolerance become important requirements for distributed systems in order to support distributed computation. A distributed system with such characteristics is called dependable. Large environments, like Cloud, offer unique advantages, such as low cost, dependability and satisfy QoS for all users. Resource management in large environments address performant scheduling algorithm guided by QoS constrains. This paper presents the performance evaluation of scheduling heuristics guided by different optimization criteria. The algorithms for distributed scheduling are analyzed in order to satisfy users constrains considering in the same time independent capabilities of resources. This analysis acts like a profiling step for algorithm calibration. The performance evaluation is based on simulation. The simulator is MONARC, a powerful tool for large scale distributed systems simulation. The novelty of this paper consists in synthetic analysis results that offer guidelines for scheduler service configuration and sustain the empirical-based decision. The results could be used in decisions regarding optimizations to existing Grid DAG Scheduling and for selecting the proper algorithm for DAG scheduling in various actual situations.

The Prospects and Challenges of Open Learning and Distance Education in Malawi

Open and distance learning is a fairly new concept in Malawi. The major public provider, the Malawi College of Distance Education, rolled out its activities only about 40 years ago. Over the years, the demand for distance education has tremendously increased. The present government has displayed positive political will to uplift ODL as outlined in the Malawi Growth and Development Strategy as well as the National Education Sector Plan. A growing national interest in education coupled with political stability and a booming ICT industry also raise hope for success. However, a fragile economy with a GNI per capita of -US$ 200 over the last decade, poor public funding, erratic power supply and lack of expertise put strain on efforts towards the promotion of ODL initiatives. Despite the challenges, the nation appears determined to go flat out and explore all possible avenues that could revolutionise education access and equity through ODL.

A Neural Model of Object Naming

One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.

Reliability-Based Topology Optimization Based on Evolutionary Structural Optimization

This paper presents a Reliability-Based Topology Optimization (RBTO) based on Evolutionary Structural Optimization (ESO). An actual design involves uncertain conditions such as material property, operational load and dimensional variation. Deterministic Topology Optimization (DTO) is obtained without considering of the uncertainties related to the uncertainty parameters. However, RBTO involves evaluation of probabilistic constraints, which can be done in two different ways, the reliability index approach (RIA) and the performance measure approach (PMA). Limit state function is approximated using Monte Carlo Simulation and Central Composite Design for reliability analysis. ESO, one of the topology optimization techniques, is adopted for topology optimization. Numerical examples are presented to compare the DTO with RBTO.

Optimal DG Placement in Distribution systems Using Cost/Worth Analysis

DG application has received increasing attention during recent years. The impact of DG on various aspects of distribution system operation, such as reliability and energy loss, depend highly on DG location in distribution feeder. Optimal DG placement is an important subject which has not been fully discussed yet. This paper presents an optimization method to determine optimal DG placement, based on a cost/worth analysis approach. This method considers technical and economical factors such as energy loss, load point reliability indices and DG costs, and particularly, portability of DG. The proposed method is applied to a test system and the impacts of different parameters such as load growth rate and load forecast uncertainty (LFU) on optimum DG location are studied.

Fault Localization and Alarm Correlation in Optical WDM Networks

For several high speed networks, providing resilience against failures is an essential requirement. The main feature for designing next generation optical networks is protecting and restoring high capacity WDM networks from the failures. Quick detection, identification and restoration make networks more strong and consistent even though the failures cannot be avoided. Hence, it is necessary to develop fast, efficient and dependable fault localization or detection mechanisms. In this paper we propose a new fault localization algorithm for WDM networks which can identify the location of a failure on a failed lightpath. Our algorithm detects the failed connection and then attempts to reroute data stream through an alternate path. In addition to this, we develop an algorithm to analyze the information of the alarms generated by the components of an optical network, in the presence of a fault. It uses the alarm correlation in order to reduce the list of suspected components shown to the network operators. By our simulation results, we show that our proposed algorithms achieve less blocking probability and delay while getting higher throughput.

An AHP-Delphi Multi-Criteria Usage Cases Model with Application to Citrogypsum Decisions, Case Study: Kimia Gharb Gostar Industries Company

Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.

Underlying Cognitive Complexity Measure Computation with Combinatorial Rules

Measuring the complexity of software has been an insoluble problem in software engineering. Complexity measures can be used to predict critical information about testability, reliability, and maintainability of software systems from automatic analysis of the source code. During the past few years, many complexity measures have been invented based on the emerging Cognitive Informatics discipline. These software complexity measures, including cognitive functional size, lend themselves to the approach of the total cognitive weights of basic control structures such as loops and branches. This paper shows that the current existing calculation method can generate different results that are algebraically equivalence. However, analysis of the combinatorial meanings of this calculation method shows significant flaw of the measure, which also explains why it does not satisfy Weyuker's properties. Based on the findings, improvement directions, such as measures fusion, and cumulative variable counting scheme are suggested to enhance the effectiveness of cognitive complexity measures.

Protein Graph Partitioning by Mutually Maximization of cycle-distributions

The classification of the protein structure is commonly not performed for the whole protein but for structural domains, i.e., compact functional units preserved during evolution. Hence, a first step to a protein structure classification is the separation of the protein into its domains. We approach the problem of protein domain identification by proposing a novel graph theoretical algorithm. We represent the protein structure as an undirected, unweighted and unlabeled graph which nodes correspond the secondary structure elements of the protein. This graph is call the protein graph. The domains are then identified as partitions of the graph corresponding to vertices sets obtained by the maximization of an objective function, which mutually maximizes the cycle distributions found in the partitions of the graph. Our algorithm does not utilize any other kind of information besides the cycle-distribution to find the partitions. If a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. As stop criterion, we calculate numerically a significance level which indicates the stability of the predicted partition against a random rewiring of the protein graph. Hence, our algorithm terminates automatically its iterative application. We present results for one and two domain proteins and compare our results with the manually assigned domains by the SCOP database and differences are discussed.

Hexavalent Chromium Removal from Aqueous Solutions by Adsorption onto Synthetic Nano Size ZeroValent Iron (nZVI)

The present work was conducted for the synthesis of nano size zerovalent iron (nZVI) and hexavalent chromium (Cr(VI)) removal as a highly toxic pollutant by using this nanoparticles. Batch experiments were performed to investigate the effects of Cr(VI), nZVI concentration, pH of solution and contact time variation on the removal efficiency of Cr(VI). nZVI was synthesized by reduction of ferric chloride using sodium borohydrid. SEM and XRD examinations applied for determination of particle size and characterization of produced nanoparticles. The results showed that the removal efficiency decreased with Cr(VI) concentration and pH of solution and increased with adsorbent dosage and contact time. The Langmuir and Freundlich isotherm models were used for the adsorption equilibrium data and the Langmuir isotherm model was well fitted. Nanoparticle ZVI presented an outstanding ability to remove Cr(VI) due to high surface area, low particle size and high inherent activity.

The Locker Problem with Empty Lockers

We consider a cooperative game played by n players against a referee. The players names are randomly distributed among n lockers, with one name per locker. Each player can open up to half the lockers and each player must find his name. Once the game starts the players may not communicate. It has been previously shown that, quite surprisingly, an optimal strategy exists for which the success probability is never worse than 1 − ln 2 ≈ 0.306. In this paper we consider an extension where the number of lockers is greater than the number of players, so that some lockers are empty. We show that the players may still win with positive probability even if there are a constant k number of empty lockers. We show that for each fixed probability p, there is a constant c so that the players can win with probability at least p if they are allowed to open cn lockers.