Self-Reliant and Auto-Directed Learning: Modes, Elements, Fields and Scopes

An exploration of the related literature reveals that all instruction methods aim at training autonomous learners. After the turn of second language pedagogy toward learner-oriented strategies, learners’ needs were more focused. Yet; the historical, social and political aspects of learning were still neglected. The present study investigates the notion of autonomous learning and explains its various facets from a pedagogical point of view. Furthermore; different elements, fields and scopes of autonomous learning will be explored. After exploring different aspects of autonomy, it is postulated that liberatory autonomy is highlighted since it not only covers social autonomy but also reveals learners’ capabilities and human potentials. It is also recommended that learners consider different elements of autonomy such as motivation, knowledge, confidence, and skills.

FEM and Experimental Modal Analysis of Computer Mount

Over the last few decades, oilfield service rolling equipment has significantly increased in weight, primarily because of emissions regulations, which require larger/heavier engines, larger cooling systems, and emissions after-treatment systems, in some cases, etc. Larger engines cause more vibration and shock loads, leading to failure of electronics and control systems. If the vibrating frequency of the engine matches the system frequency, high resonance is observed on structural parts and mounts. One such existing automated control equipment system comprising wire rope mounts used for mounting computers was designed approximately 12 years ago. This includes the use of an industrialgrade computer to control the system operation. The original computer had a smaller, lighter enclosure. After a few years, a newer computer version was introduced, which was 10 lbm heavier. Some failures of internal computer parts have been documented for cases in which the old mounts were used. Because of the added weight, there is a possibility of having the two brackets impact each other under off-road conditions, which causes a high shock input to the computer parts. This added failure mode requires validating the existing mount design to suit the new heavy-weight computer. This paper discusses the modal finite element method (FEM) analysis and experimental modal analysis conducted to study the effects of vibration on the wire rope mounts and the computer. The existing mount was modelled in ANSYS software, and resultant mode shapes and frequencies were obtained. The experimental modal analysis was conducted, and actual frequency responses were observed and recorded. Results clearly revealed that at resonance frequency, the brackets were colliding and potentially causing damage to computer parts. To solve this issue, spring mounts of different stiffness were modeled in ANSYS software, and the resonant frequency was determined. Increasing the stiffness of the system increased the resonant frequency zone away from the frequency window at which the engine showed heavy vibrations or resonance. After multiple iterations in ANSYS software, the stiffness of the spring mount was finalized, which was again experimentally validated.

Applying Multiple Intelligences to Teach Buddhist Doctrines in a Classroom

The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Comparative Analysis of Different Page Ranking Algorithms

Search engine plays an important role in internet, to retrieve the relevant documents among the huge number of web pages. However, it retrieves more number of documents, which are all relevant to your search topics. To retrieve the most meaningful documents related to search topics, ranking algorithm is used in information retrieval technique. One of the issues in data miming is ranking the retrieved document. In information retrieval the ranking is one of the practical problems. This paper includes various Page Ranking algorithms, page segmentation algorithms and compares those algorithms used for Information Retrieval. Diverse Page Rank based algorithms like Page Rank (PR), Weighted Page Rank (WPR), Weight Page Content Rank (WPCR), Hyperlink Induced Topic Selection (HITS), Distance Rank, Eigen Rumor, Distance Rank Time Rank, Tag Rank, Relational Based Page Rank and Query Dependent Ranking algorithms are discussed and compared.

Application of RS and GIS Technique for Identifying Groundwater Potential Zone in Gomukhi Nadhi Sub Basin, South India

India holds 17.5% of the world’s population but has only 2% of the total geographical area of the world where 27.35% of the area is categorized as wasteland due to lack of or less groundwater. So there is a demand for excessive groundwater for agricultural and non agricultural activities to balance its growth rate. With this in mind, an attempt is made to find the groundwater potential zone in Gomukhi Nadhi sub basin of Vellar River basin, TamilNadu, India covering an area of 1146.6 Sq.Km consists of 9 blocks from Peddanaickanpalayam to Virudhachalam in the sub basin. The thematic maps such as Geology, Geomorphology, Lineament, Landuse and Landcover and Drainage are prepared for the study area using IRS P6 data. The collateral data includes rainfall, water level, soil map are collected for analysis and inference. The digital elevation model (DEM) is generated using Shuttle Radar Topographic Mission (SRTM) and the slope of the study area is obtained. ArcGIS 10.1 acts as a powerful spatial analysis tool to find out the ground water potential zones in the study area by means of weighted overlay analysis. Each individual parameter of the thematic maps are ranked and weighted in accordance with their influence to increase the water level in the ground. The potential zones in the study area are classified viz., Very Good, Good, Moderate, Poor with its aerial extent of 15.67, 381.06, 575.38, 174.49 Sq.Km respectively.

The Relative Efficiency of Parameter Estimation in Linear Weighted Regression

A new relative efficiency in linear model in reference is instructed into the linear weighted regression, and its upper and lower bound are proposed. In the linear weighted regression model, for the best linear unbiased estimation of mean matrix respect to the least-squares estimation, two new relative efficiencies are given, and their upper and lower bounds are also studied.

Evaluation of Biomass Introduction Methods in Coal Co-Gasification

Heightened concerns over the amount of carbon emitted from coal-related processes are generating shifts to the application of biomass. In co-gasification, where coal is gasified along with biomass, the biomass may be fed together with coal (cofeeding) or an independent biomass gasifier needs to be integrated with the coal gasifier. The main aim of this work is to evaluate the biomass introduction methods in coal co-gasification. This includes the evaluation of biomass concentration input (B0 to B100) and its gasification performance. A process model is developed and simulated in Aspen HYSYS, where both coal and biomass are modelled according to its ultimate analysis. It was found that the syngas produced increased with increasing biomass content for both co-feeding and independent schemes. However, the heating values and heat duties decreases with biomass concentration as more CO2 are produced from complete combustion.

Hybrid Artificial Bee Colony and Least Squares Method for Rule-Based Systems Learning

This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

High-Temperature X-Ray Powder Diffraction of Secondary Gypsum

This paper involved the performance of a hightemperature X-Ray powder diffraction analysis (XRD) of a sample of chemical gypsum generated in the production of titanium white; this gypsum originates by neutralizing highly acidic water with limestone suspension. Specifically, it was gypsum formed in the first stage of neutralization when the resulting material contains, apart from gypsum, a number of waste products resulting from the decomposition of ilmenite by sulphuric acid. So it can be described as red titanogypsum. By conducting the experiment using XRD apparatus Bruker D8 Advance with a Cu anode (λkα=1.54184 Å) equipped with high-temperature chamber Anton Paar HTK 16, it was possible to identify clearly in the sample each phase transition in the system of CaSO4·xH2O.

Neural Networks for Distinguishing the Performance of Two Hip Joint Implants on the Basis of Hip Implant Side and Ground Reaction Force

In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

DWT Based Image Steganalysis

‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.

Multiple Intelligence Theory with a View to Designing a Classroom for the Future

The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology is not a cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen-year-old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Design and Analysis of Highly Efficient and Reliable Single-Phase Transformerless Inverter for PV Systems

Most of the PV systems are designed with transformer for safety purpose with galvanic isolation. However, the transformer is big, heavy and expensive. Also, it reduces the overall frequency of the conversion stage. Generally PV inverter with transformer is having efficiency around 92%–94% only. To overcome these problems, transformerless PV system is introduced. It is smaller, lighter, cheaper and higher in efficiency. However, dangerous leakage current will flow between PV array and the grid due to the stray capacitance. There are different types of configurations available for transformerless inverters like H5, H6, HERIC, oH5, and Dual paralleled buck inverter. But each configuration is suffering from its own disadvantages like high conduction losses, shoot-through issues of switches, dead-time requirements at zero crossing instants of grid voltage to avoid grid shoot-through faults and MOSFET reverse recovery issues. The main objective of the proposed transformerless inverter is to address two key issues: One key issue for a transformerless inverter is that it is necessary to achieve high efficiency compared to other existing inverter topologies. Another key issue is that the inverter configuration should not have any shoot-through issues for higher reliability.

Spatial Pattern and GIS-Based Model for Risk Assessment – A Case Study of Dusit District, Bangkok

The objectives of the research are to study patterns of fire location distribution and develop techniques of Geographic Information System application in fire risk assessment for fire planning and management. Fire risk assessment was based on two factors: the vulnerability factor such as building material types, building height, building density and capacity for mitigation factor such as accessibility by road, distance to fire station, distance to hydrants and it was obtained from four groups of stakeholders including firemen, city planners, local government officers and local residents. Factors obtained from all stakeholders were converted into Raster data of GIS and then were superimposed on the data in order to prepare fire risk map of the area showing level of fire risk ranging from high to low. The level of fire risk was obtained from weighted mean of each factor based on the stakeholders. Weighted mean for each factor was obtained by Analytical Hierarchy Analysis.

The Customization of 3D Last Form Design Based On Weighted Blending

When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Implementation of Virtual Reality in the Conceptual Design of a Tractor Trailer

Virtual reality (VR) is a rapidly emerging computer interface that attempts to immerse the user completely within an experimental recreation; thereby, greatly enhancing the overall impact and providing a much more intuitive link between the computer and the human participants. The main objective of this study is to design tractor trailer capable of meeting the customers’ requirements and suitable for rough conditions to be used in combination with a farm tractor in India. The final concept is capable of providing arrangements for attaching the trailer to the tractor easily by pickup hitch, stronger and lighter supporting frame, option of spare tyre etc. Furthermore, the resulting product design can be sent via the Internet to customers for comments or marketing purposes. The virtual prototyping (VP) system therefore facilitates advanced product design and helps reduce product development time and cost significantly.

Weighted Data Replication Strategy for Data Grid Considering Economic Approach

Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Orthogonal Regression for Nonparametric Estimation of Errors-in-Variables Models

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Enhanced Weighted Centroid Localization Algorithm for Indoor Environments

Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.