Today, Internet and Web technologies not only provide students opportunities for flexible interactivity with study materials, peers and instructors, but also generate large amounts of usage data that can be processed and reveal behavioral patterns of study and learning. This study analyzed data extracted from a Moodle-based blended learning course, to build a student model that predicts course performance. CART decision tree algorithm was used to classify students and predict those at risk, based on the impact of four online activities: message exchanging, group wiki content creation, course files opening and online quiz taking. The overall percentage of correct classifications was about 99.1%, proving the model sensitive to identify very specific groups at risk.

Quadrotor as one type of UAV (Unmanned Aerial Vehicle) is a system that underactuated. It means that the system has a signal control amount is lower than the degrees of freedom or DOF (Degree Of Freedom). This condition causes the quadrotor have limited mobility. If quadrotor is made to have 6 DOF or more (overactuated system), the motion control system to optimise the flight will be different from before. We need to develop overactuated quadrotor control. Quadtiltrotor as the development of quadrotor has some control signal over its DOF. So we call it as an overactuated system. Based on the type of manoeuvre to do, the transition process when the quad tiltrotor performs a translational motion using the tilting rotor need special treatment. The tilt angle change is intended that the quad tiltrotor can perform translational motion while still maintaining its orientation angle near 0°. This orientation angle can change during the undesirable rotational movement as the effect of the transition process. If additional rotational movements cannot be damped, the quad tiltrotor can experience multi overshoot, steady-state error, or even fall. Because of this matter, we need to develop flight control system to handle it. The flight control system of quad tiltrotor can be designed using a model of the system. Models can be created using quad tiltrotor dynamics by the Newton-Euler approach. Then the model is simulated along with the control system using the method of control. Several control methods can be utilised in a quad tiltrotor flight systems. However, with the implementation of LQG control method and Integrator, optimal translational control of the quad tiltrotor can be achieved.

In this work, the Language Models (LMs) and Acoustic Models (AMs) are developed using the speech recognition toolkit Kaldi for noisy and enhanced speech data to build an Automatic Speech Recognition (ASR) system for Kannada language. The speech data used for the development of ASR models is collected under uncontrolled environment from the farmers of different dialect regions of Karnataka state. The collected speech data is preprocessed by proposing a method for noise elimination in the degraded speech data. The proposed method is a combination of Spectral Subtraction with Voice Activity Detection (SS-VAD) and Minimum Mean Square Error-Spectrum Power Estimator (MMSE-SPZC) based on Zero Crossing. The word level transcription and validation of speech data is done by Indic language transliteration tool (IT3 to UTF-8). The Indian Language Speech Label (ILSL12) set is used for the development of Kannada phoneme set and lexicon. The 75% and 25% of transcribed and validated speech data is used for system training and testing respectively. The LMs are generated by using the Kannada language resources and AMs are developed by using Gaussian Mixture Models (GMM) and Subspace Gaussian Mixture Models (SGMM). The proposed method is studied determinedly and used for enhancing the degraded speech data. The Word Error Rates (WERs) of ASR models for noisy and enhanced speech data are highlighted and discussed in this work. The developed ASR models can be used in spoken query system to access the real time agricultural commodity price and weather information in Kannada language.

In the field of database administration query optimization is one of the refinement processes. In recent years, huge volumes of data are flooded from different resources, which make query optimization, a difficult task for the researchers. In the crowd sourcing, environment query optimization is the biggest problem. The client is simply required to post an SQL-like subject, and the framework assumes the main issue of organizing the inquiry; execution setup is generated and in the crowd sourcing market places the evaluation plan evaluated. In order to retrieve data fast and reduce query processing time, Query optimization is badly required. In order to optimize the queries, Meta heuristic techniques are used. In this proposed paper, preprocessing method is used to mine the information from the Crowd. The Original population based ABC algorithm has low convergence speed. In this paper a novel A-BAT algorithm is proposed, which highly improve convergence speed, accuracy and Latency. This algorithm uses a Random walk phase. The proposed algorithm had better optimization accuracy, convergence rate, and robustness.

The main contribution of this paper is the design of a robust model reference fuzzy sliding mode observation technique to control multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. A fuzzy sliding mode controller was used in this study to control the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, chattering phenomenon, and error convergence under uncertain conditions, the proposed sliding mode observer was applied to the fuzzy sliding mode controller. This theory was applied to a six-degrees-of-freedom (DOF) PUMA robot manipulator to verify the power of the proposed method.

School Bus Routing Problem is an optimization problem which falls under the class of the Vehicle Routing Problem. It involves the use of a fleet of vehicles to efficiently and optimally transport students to and from their schools. To solve this problem, optimal school bus routes are found by minimizing the number of buses, the number of routes and the total distance traversed along all routes. Manual routing of school buses have led to creation of many routes, increased number of buses and several buses navigating the same route, thereby incurring more cost. One of such methods used in solving school bus routing problems is meta-heuristic method which has proven better results in terms of optimal solution and reduced time complexity. In this study, Genetic algorithm is utilized to solve the school bus routing problem because of its simplicity and ability to generate many possible solutions. The algorithm is implemented in C# programming language and tested using secondary data obtained from Ondo State Free-School Bus Shuttle Scheme, Akure, Nigeria. The result shows that of all four nodes (bus stops) used in performance evaluation, Alakure to Oke-Aro junction bus stop presents as the best route which covers a total of 69 nodes with a total distance of 34.5km. This shows that there can be less number of buses in use and reduced number of routes in which the buses are assigned.

Concurrent Multipath Transfer (CMT) uses multi-homing feature of Stream Control Transmission Protocol (SCTP) to transfer data concurrently over the multiple paths. CMT provides bandwidth aggregation, fault tolerance, and reliability in multipath data transfer. In multipath data transmission, each path has different delay and bandwidth. Therefore, destination receives unordered data which causes receiver buffer blocking and unwanted congestion window (cwnd) reduction. Both the problem degrades the CMT performance significantly. Thus, this paper proposes a new delay-based fast retransmission policy to adjust the transmission rate of each path according to path delay. Simulation results show that the proposed approach achieves better throughput, reduces the number of the timeout and improves the cwnd growth. The proposed approach improved throughput up to 16% in variable packet loss and 18% in variable network delay environment.

Due to the global demand for energy saving and reduction of greenhouse gas emissions, utilization of renewable energy sources have increased in electricity networks. The negative aspects of this technology are very complex and not well known which affect reliability and robustness of the grids. Microgrids based on renewable energy sources have gained significant popularity, due to the major benefits it has to offer for solving the increasing energy demand. Harmonic distortion in microgrids caused by the non-linear loads is an essential topic of study necessary for the better understanding of power quality impacts in microgrids. The various control techniques utilized to curtail the power quality impacts on micro grids are reviewed in this paper. Also, Optimization based control techniques utilized for power quality improvement in microgrids is discussed in this review.