Algorithms Development in Detection of the Gelatinization Process during Enzymatic âDodolâ Processing

Computer vision systems have found wide application in foods processing industry to perform quality evaluation. The systems enable to replace human inspectors for the evaluation of a variety of quality attributes. This paper describes the implementation of the Fast Fourier Transform and Kalman filtering algorithms to detect the glutinous rice flour slurry (GRFS) gelatinization in an enzymatic âdodol. processing. The onset of the GRFS gelatinization is critical in determining the quality of an enzymatic âdodol.. Combinations of these two algorithms were able to detect the gelatinization of the GRFS. The result shows that the gelatinization of the GRFS was at the time range of 11.75 minutes to 14.75 minutes for 24 batches of processing. This paper will highlight the capability of computer vision using our proposed algorithms in monitoring and controlling of an enzymatic âdodol. processing via image processing technology

Machine Vision System for Automatic Weeding Strategy in Oil Palm Plantation using Image Filtering Technique

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Estimation of Voltage Regulator Stable Region Using Radial Basis Function Neural Network

Disturbance to the voltage regulator (VR) output caused by the abrupt change in load current can be compensated using an output capacitor with an internal parasitic element called the equivalent series resistance (ESR). However, the ESR value changes due to aging and temperature change factors, thereby creating a VR stable region in terms of ESR. In practice, time-consuming and high-expertise manual characterization is required to characterize the VR stable region during the design and manufacturing phases. Therefore, this research aims to develop an efficient and effective VR characterization method. In this work, the radial basis function neural network (RBFNN) approach was implemented to estimate the stable region. Results show that the RBFNN approach yields a stable region with higher estimation accuracy and faster characterization time than those of manual characterization. VR characterization using the RBFNN approach can efficiently and effectively estimate the VR stable region

Critical Equivalent Series Resistance Estimation for Voltage Regulator Stability Using Hybrid System Identification and Neural Network

Output capacitor in the voltage regulator (VR) circuit ensures stability especially during fast load transients. However, the capacitor parasitic, namely equivalent series resistance (ESR), may cause unstable VR operation. VR characterization in terms of ESR suggests stable range of capacitor ESR based on the ESR tunnel graph in the VR datasheet. Specifically, the stable ESR range is the critical ESR value, which lies on the failure region boundary of ESR tunnel graph. New or updated ESR tunnel graph through characterization is required for new product development or quality assurance purpose. However, the characterization is typically conducted manually in industry, thereby increases the manufacturing time and cost. Therefore, this work proposed a characterization approach that can reduce the time to determine the ESR tunnel graph based on the hybrid system identification and neural network (SI-NN) approach. This method utilised system identification (SI) to estimate the VR circuit model for certain operating points before predicting the transfer function coefficients for the remaining points using radial basis function neural network (RBFNN). Eventually, the critical ESR of failure region boundary was estimated. This hybrid SI-NN approach able to reduce the number of data that would be acquired manually to 25% compared to manual characterization, while provides critical ESR estimation with error less than 2%

Robust Controller for a Vision Feedback Based Telepointer

Telepointer is a very useful tool for teleconsultation and teleproctoring, whereby a telepointer via teleconferencing is a perfect example of computer-supported cooperative work (CSCW) and digital telepresence. To this end, many telepointers are introduced for digital telepresence. However, there are still concerns regarding the speed of response and robustness of the system. It is rather difficult to model the actual system in order to design the controller. This paper described the development of a telepointer and its controller for a real time communication using vision feedback. The main focus of this study was to control the Laser Pointer (LP) with a discrete time PID (proportional–integral–derivative) controller which was tuned using Ziegler-Nichols (ZN) method. The results indicated that the tuned controller bring about fast response with no overshoot and steady state errors at the output response. The controller was shown to be robust against changes in sampling time and external disturbance

Weed detection utilizing quadratic polynomial and ROI techniques

Machine vision for selective weeding or selective herbicide spraying relies substantially on the ability of the system to analyze weed images and process the extracted knowledge for decision making prior to implementing the identified control action. To control weed, different weed type would require different herbicide formulation. Consequently the weed must be identified and classified accordingly. In this work, weed images were classified as either broad or narrow weed type. A fundamental problem in weed image recognition using planar curve analysis is to detect curve. It is difficult to successfully extract curve from the image of weed edges since the appropriate scale to use for extraction is not known a priori As such, this paper considers a curve detection method based on the quadratic polynomial technique which include the use of the region-of-interests (ROI) technique. The ROI technique creates image subsets by selecting regions of the displayed image. The ROIs are typically used to extract statistics for image operations such as classification. As such, the objective of this paper is to present a novel application of curve detection feature extraction technique in weed classification

Development of 3D Simulation Application for Production Multimedia Subject

The development of 3D simulation applications for Production of Multimedia Subjects is intended to provide exposure and convenience to teachers, especially prospective teachers of Universiti Pendidikan Sultan Idris in exploring the 3D virtual world of the classroom and school environment in the context of learning and facilitate teachers to obtain daily information in finding relevant information. 3D. The objective of this study is to identify the 3D elements needed to build a school environment, design and develop a virtual reality application simulation application program that can be developed and evaluate the function of this 3D simulation application can help teachers teach and learn in schools. In addition, the use of applications such as simulators is basically for research and educational purposes. This study uses the ADDIE model used in the development of a 3D simulation application for this Multimedia Production subject. Simulation is capable of producing a virtual world of the surrounding atmosphere and a real environment. This Multimedia Production subject learning simulation can give students an idea of the learning environment in school. There is no denying that the use of simulation applications is not widespread as most of the available applications mostly focus on skills such as aeroplane piloting. With this, applications such as simulators are developed to give students an experience of the virtual learning environment