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Novel Framework for Navigation using Enhanced Fuzzy Approach with Sliding Mode Controller
No full textThe reliability of any embedded navigator in advanced vehicular system depends upon correct and precise information of navigational data captured and processed to offer trustworthy path. After reviewing the existing system, a significant trade-off is explored between the existing navigational system and present state of controller design on various case studies and applications. The existing design of controller system for navigation using error-prone GPS/INS data doesn’t emphasize on sliding mode controller. Although, there has been good number of studies in sliding mode controller, it is less attempted to optimize the navigational performance of a vehicle. Therefore, this paper presents a novel optimized design of a sliding mode controller that can be effectively deployed on advanced navigational system. The study outcome was found to offer higher speed, optimal control signal, and lower error occurances to prove that proposed system offers reliable and optimized navigational services in contrast to existing system
A novel Neuroglial architecture for modelling Singular Perturbation System
No full textThis work develops a new modular architecture that emulates a recently-discovered biological paradigm. It originates from the human brain where the information flows along two different pathways and is processed along two time scales: one is a fast neural network (NN) and the other is a slow network called the glial network (GN). It was found that the neural network is powered and controlled by the glial network. Based on our biological knowledge of glial cells and the powerful concept of modularity, a novel approach called artificial neuroglial Network(ANGN) was designed and an algorithm based on different concepts of modularity was also developed. The implementation is based on the notion of multi-time scale systems. Validation is performed through an asynchronous machine (ASM) modeled in the standard singularly perturbed form. We apply the geometrical approach, based on Gerschgorin’s circle theorem(GCT), to separate the fast and slow variables, as well as the singular perturbation method (SPM) to determine the reduced models. This new architecture makes it possible to obtain smaller networks with less complexity and better performance.
Wireless Technology for Monitoring Site-Specific Landslide in Vietnam
No full textClimate change has caused an increasing number of landslides, especially in the mountainous provinces of Vietnam, resulting in the destruction of vital transport and other infrastructure. Current monitoring and forecasting systems of the meteorology department cannot deliver accurate and reliable forecasts for weather events and issue timely warnings. This paper describes the development of a simple, low cost, and efficient system for monitoring and warning landslide in real-time. The authors focus on the use of wireless and related technologies in the implementation of a technical solution and some of the problems of the wireless sensor network (WSN) related to power consumption. Promising compressed sensing (CS) based solution for landslide monitoring is discussed and evaluated in the paper
A Novel Approach for grid integration of Cascaded H-bridge Multilevel Inverter Under Partial Shading Condition
No full textA modular cascaded H-bridge PV inverter system is presented in this paper. The modular structure of PV inverter helps in obtaining the maximum output power of PV system along with increase the overall efficiency of the whole system. Moreover to utilize the system up to the best a distributed MPPT controller is attached with each PV panel. As partial shading causes power imbalance at the converter output that leads to imbalance grid current, a control technique called the modulation compensation is adopted in such a way that if three phase unbalanced voltage varies directly according to unbalanced power, the injected zero sequence voltage components make the grid current balanced
Modeling Baseline Energy Using Artificial Neural Network – A Small Dataset Approach
No full textIn this work, baseline energy model development using Artificial Neural Network (ANN) with resampling techniques; Cross Validation (CV) and Bootstrap (BS) are presented. Resampling techniques are used to examine the ability of the ANN model to deal with a small dataset. Working days, class days and Cooling Degree Days (CDD) are used as ANN input meanwhile the ANN output is monthly electricity consumption. The coefficient of correlation (R) is used as performance function to evaluate the model accuracy. For this analysis, R is calculated for the entire data set (R_all) and separately for training set (R_train), validation set (R_valid) dan testing set (R_test). The closer R to 1, the higher similarities between targeted and predicted output. The total of two different models with several number of neurons are developed and compared. It can be concluded that all models are capable to train the network. Artificial Neural Network with Bootstrap Cross Validation technique (ANN-BSCV) outperforms Artificial Neural Network with Cross Validation technique (ANN-CV). The 3-6-1 ANN-BSCV, with R_train = 0.95668, R_valid = 0.97553, R_test = 0.85726 and R_all = 0.94079 is selected as the baseline energy model to predict energy consumption for Option C IPMVP
Development of Compact Pulse Generator with Adjustable Pulse Width for Pulse Electric Field Treatment Technology
No full textThe pulse generator which has been implemented in the pulse electric field (PEF) treatment system for food processing is worth to be highlighted and improved. It is parallel with the advancement in semiconductor technology, which offers robust and accurate devices. This research is an effort to produce a low cost, compact and reliable pulse generator as well as equipped with a pulse width modulation (PWM) method for wide selection of frequency and duty cycle. The result shows that the simulation process has proven the theoretical concept to be right and yields the desired outcome based on the designed values. Then, the actual printed circuit board (PCB) has been fabricated to obtain practical results which intended to be compared with the simulation outcomes. Concerning the frequency and its duty cycle, both parameters can be altered without affecting each other. It means by changing the frequency, duty cycle remains the same and vice versa. Thus, this proposed pulse generator achieves its objective and fits to be implemented in PEF treatment technology. It also can replace the conventional pulse forming network (PFN) which is bulky and costly
A Novel Control Strategy for Compensation of Voltage Quality Problem in AC Drives
No full textThis paper presents a novel control strategy for the compensation of voltage quality issues in power system networks with AC drives. Voltage quality is one of the key parameter for power engineers and to deliver the power with good quality should be given at most priority. Voltage quality mitigation in power system network is done by employing dynamic voltage restorer (DVR). DVR consists of power switches and power switches are to be controlled. DVR in this paper is controlled using a novel control strategy. A novel control strategy can effectively control DVR by improving voltage quality reducing the adverse effects of voltage sag and voltage swell in power system networks. The paper presents the DVR controlled with novel control strategy for electrical machine (induction motor) drive load application
Improve Security of Cloud Storage by Using Third Parity Authentication, One Time Password and Modified AES Encryption Algorithm
No full textCloud computing is a new term to provide application and hardware as service over the internet. Demand for cloud has increased dramatically in recent years. However, a major drawback for cloud adoption is lack of security so that we will try to solve some security issues related to cloud storage by design and implement a secure system to store privet data in cloud storage. This secure system provide secure login to cloud by using third parity authentication (smart phone) and one time password depend on chaotic system to prevent unauthorized people from get access to cloud and modified AES algorithms to encrypt the data in the cloud storage
An Improved Greedy Parameter Stateless Routing In Vehicular Ad Hoc Network
No full textCongestion problem and packet delivery related issues in the vehicular ad hoc network environment is a widely researched problem in recent years. Many network designers utilize various algorithms for the design of ad hoc networks and compare their results with the existing approaches. The design of efficient network protocol is a major challenge in vehicular ad hoc network which utilizes the value of GPS and other parameters associated with the vehicles. In this paper GPSR protocol is improved and compared with the existing GPSR protocol and AODV protocol on the basis of various performance parameters like throughput of the network, delay and packet delivery ratio. The results also validate the performance of the proposed approach
Quadratic Support Vector Machine For The Bomba Traditional Textile Motif Classification
No full textThe Bomba textile is one of the textile fabrics in Indonesia used in a province called Sulawesi Tengah. Bomba Textile has a unique pattern and has a philosophical meaning in human life in Sulawesi Tengah. Bomba Textile has many motif patterns and varied colors. The problem in this research is the difficulty in classifying every The Bomba textile motif in each class. Data classification is needed to recognize the motif of each Bomba textile pattern and to cluster it into the appropriate class. The features used to classify the Bomba textile motif is the textural feature. Texture features obtained from Gray-Level Co-occurrence matrices (GLCM) method consisting of energy, contrast, homogeneity and correlation with four angles 0°, 45°, 90°, and 135°. This research will implement Quadratic Vector Machine (QSVM) method with texture feature on Bomba textile pattern. The use of a single texture feature with angles 90° has an accuracy of 90.3%. The incorporation of texture features by involving all features at all angles can improve the accuracy of the classification model. This research produces a model of motif classification on the Bomba textile which has the classification accuracy of 94.6% and error rate of 5.4%