Showing papers in "TELKOMNIKA Telecommunication Computing Electronics and Control in 2011"

Dynamic Model and Robust Control of Flexible Link Robot Manipulator

Abstract: The problems of a flexible link manipulator are uncertainties and parametric nonlinearities. This paper presents design and development of a robust control based on linear quadratic regulator (LQR) for a flexible link manipulator. System performances were evaluated in terms of input tracking capability of hub angular position response, end-point displacement, end-point residual and hub velocity. For the controller of the system, LQR was developed to solve flexible link robustness and input tracking capability of hub angular position. The results achieved by the proposed controller are compared with conventional PID, to substantiate and verify the advantages of the proposed scheme and its promising potential in control of a flexible link manipulator. The robust control presented faster settling time and smaller overshoot responses and tracking performances of the proposed controller compared with PID controllers.

Wireless Sensor Network for Landslide Monitoring in Nusa Tenggara Timur

Abstract: Landslides in many regions constitute serious hazards that cause substantial life and financial losses. To overcome and reduce the damages, efforts to monitor landslides are developed. One such technology utilizes a wireless sensor network (WSN). Results obtained from studies conducted in the Ikanfoti village, Kupang District, Nusa Tenggara Timur (NTT) Province (S 10 o 16’ 21.9” and E 123 o 40’59.8”) as pilot project, give result that the application of WSN can be applied properly. We detect and measure vibrations caused by landslides by vibration sensor (accelerometer) on Micaz devices. The results of this study indicate that changes in accelerometer values ranging from 0.2 g (gravity) to 0.49 g of either the X or Y of accelerometer indicate that soil begins to move but not significantly. Value above 0.5 g is a value that indicating a significant change of ground motion. The value of 1 g and above of ground motion indicates a very strong activity and should be alarmed. It is expected that this research provides the foundation for the application of WSN in various areas in NTT Province and Indonesia in general, for establishing thorough and reliable early warning system (EWS).

Energy Analysis for Air Conditioning System Using Fuzzy Logic Controller

Abstract: Reducing energy consumption and to ensure thermal comfort are two important considerations for the designing an air conditioning system. An alternative approach to reduce energy consumption proposed in this study is to use a variable speed compressor. The control strategy will be proposed using the fuzzy logic controller (FLC). FLC was developed to imitate the performance of human expert operators by encoding their knowledge in the form of linguistic rules. The system is installed on a thermal environmental room with a data acquisition system to monitor the temperature of the room, coefficient of performance (COP), energy consumption and energy saving. The measurements taken during the two hour experimental periods at 5-minutes interval times for temperature setpoints of 20 o C, 22 o C and 24 o C with internal heat loads 0, 500, 700 and 1000 W. The experimental results indicate that the proposed technique can save energy in comparison with On/Off and proportional-integral-derivative (PID) control.

Induction Heating Process Design Using COMSOL ® Multiphysics Software

Abstract: Induction heating is clean environmental heating process due to a non-contact heating process. There is lots of the induction heating type that be used in the home appliance but it is still new technology in Indonesia. The main interesting area of the induction heating design is the efficiency of the usage of energy and choice of the plate material. COMSOL ® Multiphysics Software can be used to simulate and estimate the induction heating process. Therefore, the software can be used to design the induction heating process that will have a optimum efficiency. The properties of the induction heating design were also simulated and analyzed such as effect of inductor’s width, inductor’s distance, and conductive plate material. The result was shown that the good design of induction heating must have a short width and distance inductor and used silicon carbide as material plate with high frequency controller .

An Early Detection Method of Type-2 Diabetes Mellitus in Public Hospital

Abstract: Diabetes is a chronic disease and major problem of morbidity and mortality in developing countries. The International Diabetes Federation estimates that 285 million people around the world have diabetes. This total is expected to rise to 438 million within 20 years. Type-2 diabetes mellitus (T2DM) is the most common type of diabetes and accounts for 90-95% of all diabetes. Detection of T2DM from various factors or symptoms became an issue which was not free from false presumptions accompanied by unpredictable effects. According to this context, data mining and machine learning could be used as an alternative way help us in knowledge discovery from data. We applied several learning methods, such as instance based learners, naive bayes, decision tree, support vector machines, and boosted algorithm acquire information from historical data of patient’s medical records of Mohammad Hoesin public hospital in Southern Sumatera. Rules are extracted from Decision tree to offer decision-making support through early detection of T2DM for clinicians.

A Lighting Control System in Buildings based on Fuzzy Logic

Abstract: Lighting generally consumed 25%-50% of total electricity consumption in a building. Nowadays, the building lighting source is dominated by the use of fluorescent lamps. The previous technical papers by other researchers had focused on power density control of incandescent lamps, which is now rarely used, unconsidered national standard as control reference value, and required a high-cost in investment. By these reasons, this paper proposes a building lighting system based on fuzzy logic scheme to automate fluorescent lamps in order to achieve illumination according to Indonesian National Standard (SNI). The input variables were indoor lighting, inference from outdoor lighting, and occupancy. The output variable was the required illumination to achieve the standard. The required illumination determined the number of lamps that had to be turned on. In the experiment result, a classroom illumination of lighting without controller in workdays was about 350 lux, while with the proposed controller it varied between 250‐300 lux close to the SNI, i.e. 250 lux. Meanwhile, with the proposed controller the electricity consumption for a classroom was 75% lower than the lighting without controller.

A Hybrid Genetic Algorithm Approach for Optimal Power Flow

Abstract: This paper puts forward a reformed hybrid genetic algorithm (GA) based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA), adaptive genetic algorithm (AGA), differential evolution (DE), particle swarm optimization (PSO) and music based harmony search (MBHS) on a IEEE30 bus test bed, with a total load of 283.4 MW. It’s found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

Progress in Artificial Intelligence Techniques: from Brain to Emotion

Abstract: Artificial Intelligence (AI) techniques, e.g. expert system (ES), fuzzy logic (FL), artificial neural network (ANN), genetic algorithm (GA), particle swarm optimization (PSO) and biologically inspired (BI) have recently been applied widely in power electronics and motor drives.Each AI method has its own uniqueness and characteristics. Recently, researchers have developed a computational model of emotional learning in mammalian brain, namely brain emotional learning based intelligent controller (BELBIC). The results indicate the ability of BELBIC to control unknown non-linear dynamic systems. Therefore, the BELBIC can be easily adopted for niche mechatronics and industrial applications.

Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision

Abstract: Abstrak Pada paper ini, kami mengusulkan sistem penghindaran halangan ganda (multiple moving obstacles) menggunakan stereo vision untuk service robot yang berada di lingkungan indoor. Kami menganggap model service robot ini digunakan untuk mengirimkan sebuah gelas ke pelanggan yang dikenal dari titik asal ke titik tujuan. Kontribusi dari penelitian ini ialah sebuah metode baru untuk penghindaran multiple moving obstacle dengan pendekatan Bayesian berbasis kamera stereo. Kami telah mengembangkan dan memperkenalkan 3 modul utama untuk mengenal wajah, mengidentifikasi multiple moving obstacles dan untuk manuver robot. Sekelompok orang yang berjalan di depan robot akan ditrack sebagai moving obstacles, serta kecepatan, arah dan jarak dari moving obstacles diestimasi menggunakan kamera stereo agar robot dapat bermanuver untuk menghindari tubrukan. Untuk mengatasi ketidakakuratan dari sensor vision, pendekatan Bayesian digunakan uintuk estimasi keberadaan dan arah moving obstacle. Hasil eksperimen dipaparkan dan kami evaluasi performa dari sistem service robot yang diberi nama Srikandi III. Berdasarkan eksperimen, metode yang kami usulkan berjalan dengan baik serta pendekatan Bayesian terbukti meningkatkan performa estimasi dari keberadaan dan arah halangan. Kata kunci: multiple moving obstacles, obstacle avoidance, service robot, stereo vision

A Thermoelectric Generator Replacing Radiator for Internal Combustion Engine Vehicles

Abstract: We have proposed and developed a low temperature thermoelectric generator (TEG) using engine water coolant of light-duty vehicles. Experimental results from test vehicle, of which engine size is about 2.0 liters, show that fabricated prototype Thermoelectric Generator generates more than 75W for driving condition of 80 km/hour, and output power is about 28W during idle condition. The proposed TEG can replace conventional radiator without additional water pumps or mechanical devices except for basic components of legacy water cooling system of radiator.

Appearance Global and Local Structure Fusion for Face Image Recognition

Abstract: Principal component analysis (PCA) and linear descriminant analysis (LDA) are an extraction method based on appearance with the global structure features. The global structure features have a weakness; that is the local structure features can not be characterized . Whereas locality preserving projection (LPP) and orthogonal laplacianfaces (OLF) methods are an appearance extraction with the local structure features, but the global structure features are ignored. For both the global and the local structure features are very important. Feature extraction by using the global or the local structures is not enough. In this research, it is proposed to fuse the global and the local structure features based on appearance. The extraction results of PCA and LDA methods are fused to the extraction results of LPP. Modelling results were tested on the Olivetty Research Laboratory database face images. The experimental results show that our proposed method has achieved higher recognation rate than PCA, LDA, LPP and OLF Methods .

Coffee Bean Grade Determination Based on Image Parameter

Abstract: Quality standard for coffee as an agriculture commodity in Indonesia uses defect system which is regulated in Standar Nasional Indonesia (SNI) for coffee bean, No: 01-2907-1999. In the Defect System standard, coffee bean is classified into six grades, from grade I to grade VI depending on the number of defect found in the coffee bean. Accuracy of this method heavily depends on the experience and the expertise of the human operators. The objective of the research is to develop a system to determine the coffee bean grading based on SNI No: 01-2907-1999. A visual sensor, a webcam connected to a computer, was used for image acquisition of coffee bean image samples, which were placed under uniform illumination of 414.5+2.9 lux. The computer performs feature extraction from parameters of coffee bean image samples in the term of texture (energy, entropy, contrast, homogeneity) and color (R mean, G mean, and B mean) and determines the grade of coffee bean based on the image parameters by implementing neural network algorithm. The accuracy of system testing for the coffee beans of grade I, II, III, IVA, IVB, V, and VI have the value of 100, 80, 60, 40, 100, 40, and 100%, respectively.

A Fuzzy Topsis Multiple-Attribute Decision Making for Scholarship Selection

Abstract: Biaya pendidikan semakin mahal, banyak mahasiswa mengajukan beasiswa. Ratusan bahkan ribuan formulir pengajuan beasiswa harus diseleksi oleh sponsor. Permasalahan tersebut bertujuan untuk memilih beberapa alternatif terbaik berdasarkan beberapa atribut (kriteria) yang digunakan. Dalam rangka pengambilan keputusan pada permasalahan yang bersifat fuzzy dapat digunakan Fuzzy Multiple Attribute Decision Making (FMADM). Pada penelitian ini dilakukan pemodelan menggunakan Unified Modelling Language (UML) pada FMADM dengan metode TOPSIS dan Weighted Product untuk menyeleksi calon penerima beasiswa akademik dan non akademik di Universitas Islam Negeri Sunan Kalijaga. Data yang digunakan adalah data fuzzy dan crisp. Hasil penelitian menunjukkan bahwa Metode TOPSIS dan Weighted Product pada FMADM dapat digunakan untuk seleksi beasiswa. Hasil seleksi merekomendasikan mahasiswa yang memiliki tingkat kelayakan paling tinggi untuk mendapatkan beasiswa berdasarkan nilai preferensi yang dimiliki. Kata kunci: Fuzzy Multiple Attribute Decision Making, TOPSIS, Weighted Product, Scholarship

Focused Crawler Optimization Using Genetic Algorithm

Abstract: As the size of the Web continues to grow, searching it for useful information has become more difficult. Focused crawler intends to explore the Web conform to a specific topic. This paper discusses the problems caused by local searching algorithms. Crawler can be trapped within a limited Web community and overlook suitable Web pages outside its track. A genetic algorithm as a global searching algorithm is modified to address the problems. The genetic algorithm is used to optimize Web crawling and to select more suitable Web pages to be fetched by the crawler. Several evaluation experiments are conducted to examine the effectiveness of the approach. The crawler delivers collections consist of 3396 Web pages from 5390 links which had been visited, or filtering rate of Roulette-Wheel selection at 63% and precision level at 93% in 5 different categories. The result showed that the utilization of genetic algorithm had empowered focused crawler to traverse the Web comprehensively, despite it relatively small collections. Furthermore, it brought up a great potential for building an exemplary collections compared to traditional focused crawling methods.

Adaptive-Fuzzy Controller Based Shunt Active Filter for Power Line Conditioners

Abstract: This paper presents a novel Fuzzy Logic Controller (FLC) in conjunction with Phase Locked Loop (PLL) based shunt active filter for Power Line Conditioners (PLCs) to improve the power quality in the distribution system. The active filter is implemented with current controlled Voltage Source Inverter (VSI) for compensating current harmonics and reactive power at the point of common coupling. The VSI gate control switching pulses are derived from proposed Adaptive-Fuzzy-Hysteresis Current Controller (HCC) and this method calculates the hysteresis bandwidth effectively using fuzzy logic. The bandwidth can be adjusted based on compensation current variation, which is used to optimize the required switching frequency and improves active filter substantially. These shunt active power filter system is investigated and verified under steady and transient-state with non-linear load conditions. This shunt active filter is in compliance with IEEE 519 and IEC 61000-3 recommended harmonic standards.

Neural Network Based Indexing and Recognition of Power Quality Disturbances

Abstract: Abstrak Analisis kualitas daya atau power quality (PQ) telah menjadi keharusan terutama bagi konsumen untuk menghindari biaya besar akibat kualitas daya yang buruk. Pengenalan PQ secara akurat masih merupakan pekerjaan yang menantang sedangkan metode untuk pengindeksannya belum banyak dilakukan. Makalah ini menguraikan sistem yang mencakup pembangkitan pola unik yang disebut tandatanda gangguan PQ menggunakan transformasi wavelet kontinyu atau continuous wavelet transform (CWT) dan pengenalan tanda-tanda menggunakan umpan maju jaringan syaraf tiruan. Hal ini juga dikuatkan bahwa ukuran tanda gangguan PQ bersifat proporsional sehingga fitur ini digunakan untuk indeks tingkat gangguan PQ dalam tiga sub-kelas, yaitu tinggi, sedang, dan rendah. Lebih lanjut, juga dianalisis efek jumlah neuron yang digunakan jaringan syaraf tiruan dalam pengenalan kualitas. Keefektifitasan sistem yang diusulkan memiliki akurasi substansi pengenalan hampir 100%. Kata Kunci : jaringan syaraf tiruan umpan maju, kualitas daya, pengenalan, transformasi wavelet kontinyu

Numerical Design of Ultra-Wideband Printed Antenna for Surface Penetrating Radar Application

Abstract: Surface penetrating radar (SPR) is an imaging device of electromagnetic wave that works by emitting and transmitting a narrow period pulse through the antenna. Due to the use of narrow period pulse, according to the Fourier transform duality, therefore ultra-wideband (UWB) antenna becomes one of the most important needs in SPR system. In this paper, a novel UWB printed antenna is proposed to be used for SPR application. Basically, the proposed antenna is developed from a rectangular microstrip antenna fed by symmetric T-shaped. Some investigation methods such as resistive loading, abrupt transition, and ground plane modification are attempted to achieve required characteristics of bandwidth, radiation efficiency, and compactness needed by the system. To obtain the optimum design, the characteristics of proposed antenna are numerically investigated through the physical parameters of antenna. It is shown that proposed antenna deployed on an FR-4 Epoxy substrate with permittivity of 4.3 and thickness of 1.6mm has a compact size of 72.8mm x 60.0mm and a large bandwidth of 50MHz-5GHz which is suitable for SPR application.

Inverse S-Transform Based Decision Tree for Power System Faults Identification

Abstract: In this paper a decision tree based identification of power system faults has been proposed. The key input values to the decision tree are the performance indices calculated from the maximum values of unfiltered inverse Stockwell transform (MUNIST) technique. A wide range of techniques including Stockwell transform (ST) have been used for the identification of power system faults. However, the signatures produced by these techniques are not unique and sometimes lead to misinterpretation of faults. Consequently, a decision tree based on the inverse Stockwell transform method is proposed in the present paper to automatically identify both the symmetrical and unsymmetrical power system faults. The method is able to determine both sudden and gradual changes in the signal caused by different power system faults. The technique is very accurate and produces unique signatures compared to the existing techniques. The results obtained show the efficacy of the proposed technique.

Optimization of an Intelligent Controller for an Unmanned Underwater Vehicle

Abstract: Underwater environment poses a difficult challenge for autonomous underwater navigation. A standard problem of underwater vehicles is to maintain it position at a certain depth in order to perform desired operations. An effective controller is required for this purpose and hence the design of a depth controller for an unmanned underwater vehicle is described in this paper. The control algorithm is simulated by using the marine guidance navigation and control simulator. The project shows a radial basis function metamodel can be used to tune the scaling factors of a fuzzy logic controller. By using offline optimization approach, a comparison between genetic algorithm and metamodeling has been done to minimize the integral square error between the set point and the measured depth of the underwater vehicle. The results showed that it is possible to obtain a reasonably good error using metamodeling approach in much a shorter time compared to the genetic algorithm approach.

Intelligent Avatar on E-Learning using Facial Expression and Haptic

Abstract: The process of introducing emotion can be improved through three-dimensional (3D) tutoring system. The problem that still not solved is how to provide realistic tutor (avatar) in virtual enviro nment. This paper propose an approach to teach children on understanding emotion sensation through facial expression and sense of touch (haptic).The algorithm is created by calculating constant factor ( f) based on maximum value of RGB and magnitude force then magnitude force range will be associated into particular colour. The Integration process will be started from rendering the facial expression then followed by adjusting the vibration power to emotion value. The result that achieved on experiment, it show around 71% students agree with the classification of magnitude force into emotion representation. Respondents commented that high magnitude force create similar sensation when respondents feel anger, while low magnitude force is more relaxing to respondents. Respondents also said that haptic and facial expression is very interactive and realistic.

Generator Contribution Based Congestion Management using Multiobjective Genetic Algorithm

Abstract: Congestion management is one of the key functions of system operator in the restructured power industry during unexpected contingency. This paper proposes a method for generator contribution based congestion management using multiobjective genetic algorithm. In the algorithm, both real and reactive losses have been optimised using optimal power flow model and the contributions of the generators with those optimised losses are calculated. On second level, the congested lines are identified by the proposed overloading index (OI) during contingency and those lines are relieved with the new contribution of generators, which is the outcome of the developed algorithm. The planned method depicts the information related to congestion management to minimize the investment cost, without installing any external devices and to maximise the consumer welfare by avoiding any load curtailment without affecting the voltage profile of the system as well as the optimised total system loss. IEEE 30 bus system is used to demonstrate the effectiveness of the method.

Efficient JPEG 2000 Image Compression Scheme for Multihop Wireless Networks

Abstract: When using wireless sensor networks for real-time data transmission, some critical points should be considered. Restricted computational power, reduced memory, narrow bandwidth and energy supplied present strong limits in sensor nodes. Therefore, maximizing network lifetime and minimizing energy consumption are always optimization goals. To overcome the computation and energy limitation of individual sensor nodes during image transmission, an energy efficient image transport scheme is proposed, taking advantage of JPEG2000 still image compression standard using MATLAB and C from Jasper. JPEG2000 provides a practical set of features, not necessarily available in the previous standards. These features were achieved using techniques: the discrete wavelet transform (DWT), and embedded block coding with optimized truncation (EBCOT). Performance of the proposed image transport scheme is investigated with respect to image quality and energy consumption. Simulation results are presented and show that the proposed scheme optimizes network lifetime and reduces significantly the amount of required memory by analyzing the functional influence of each parameter of this distributed image compression algorithm.

Maximum Torque per Ampere Control of Permanent Magnet Synchronous Motor Using Genetic Algorithm

Abstract: Permanent magnet synchronous motor (PMSM) drives have many advantages over other drives, i.e. high efficiency and high power density. Particularly, PMSMs are epoch-making and are intensively studied among researchers, scientists and engineers. This paper deals with a novel high performance controller based on genetic algorithm. The scheme allows the motor to be driven with maximum torque per ampere characteristic. In this paper assuming an appropriate fitness function, the optimum values for d-axis current of motor set points at each time are found and then applied to the controller. Simulation results show the successful operation of the proposed controller.

Levenberg-Marquardt Recurrent Networks for Long- Term Electricity Peak Load Forecasting

Abstract: Increasing electricity demand in Java-Madura-Bali, Indonesia, must be addressed appropriately to avoid blackout by determining accurate peak load forecasting. Econometric approach may not be sufficient to handle this problem due to limitation in modelling nonlinear interaction of factors involved. To overcome this problem, Elman and Jordan Recurrent Neural Network based on Levenberg-Marquardt learning algorithm is proposed to forecast annual peak load of Java-Madura-Bali interconnection for 20092011. Actual historical regional data which consists of economic, electricity statistic and weather during 1995-2008 are applied as inputs. The networks structure is firstly justified using true historical dat a of 1995-2005 to forecast peak load of 2006-2008. Afterwards, peak load forecasting of 2009-2011 is conducted subsequently using actual historical data of 1995-2008. Overall, the proposed networks shown better performance compared to that obtained by Levenberg-Marquardt-Feedforward network, Double-log Multiple Regression, and with projection by PLN for 2006-2010.

Case Study of a Hybrid (Wind and Solar) Power Plant

Abstract: The paper highlights the urgency of utilizing and promoting use of non conventional sources, particularly the wind and solar energy, so as to control the environmental pollution, such as ozone layer depletion, deforestation, loss of biodiversity, global warming etc. As a case study, the various performance factors of a 10 kW hybrid (wind and solar) power plant, which is having 60:40 power generation share of wind power to solar power were analysed. The study shows that there is mismatch between the designed and actual plant load factor (PLF), as well as the power generation share of the wind and solar power plant. It was also found that the plant utilization factor (PUF) was poor and that there is very less scope for installation of solar tracking system. Based on the detailed analysis of obtained results, certain recommendations were made for streamlining and optimizing the power generation capacity, and also for better utilization of generated power .

Electronic Nose using Gas Chromatography Column and Quartz Crystal Microbalance

Abstract: The conventional electronic nose usually consists of an array of dissimilar chemical sensors such as quartz crystal microbalance (QCM) combined with pattern recognition algorithm such as Neural network. Because of parallel processing, the system needs a huge number of sensors and circuits which may emerge complexity and inter-channel crosstalk problems. In this research, a new type of odor identification which combines between gas chromatography (GC) and electronic nose methods has been developed. The system consists of a GC column and a 10-MHz quartz crystal microbalance sensor producing a unique pattern for an odor in time domain. This method offers advantages of substantially reduced size, interferences and power consumption in comparison to existing odor identification system. Several odors of organic compounds were introduced to evaluate the selectivity of the system. Principle component analysis method was used to visualize the classification of each odor in two-dimensional space. This system could resolve common organic solvents, including molecules of different classes (aromatic from alcohols) as well as those within a particular class (methanol from ethanol) and also fuels (premium from pertamax). The neural network can be taught to recognize the odors tested in the experiment with identification rate of 85 %. It is therefore the system may take the place of human nose, especially for poisonous odor evaluations.

The Digital Microscope and Its Image Processing Utility

Abstract: 3 Abstrak Banyak institusi, termasuk sekolah-sekolah, memiliki sejumlah mikroskop analog atau mikroskop biasa. Mikroskop ini digunakan untuk mengamati obyek-obyek kecil. Sayangnya, pengamatan obyek menggunakan mikroskop biasa memerlukan ketelitian dan ketajaman penglihatan yang tinggi dari penggunanya. Makalah ini membahas pengembangan mikroskop digital resolusi tinggi dari mikroskop analog, termasuk perangkat lunak pemroses citra digitalnya. Perangkat lunak yang dikembangkan memungkinkan pemakai mokroskop digital merekam, menyimpan dan memproses citra digital dari obyek yang sedang diamati. Mikroskop digital ini dibuat dengan material yang mudah didapat di Indonesia. Perangkat lunak pengolah citra digital yang dikembangkan mampu menangkap citra, menyimpan citra, mengubah kecerahan citra, memperbaiki kontras citra, mengekualisasi- histogramkan citra, merubah skala (scaling ) citra dan memotong (cropping ) citra. Mikroskop digital yang diusulkan mempunyai kemampuan memperbesar obyek sampai dengan 1600x dengan resolusi citra yang dapat divariasi dari 320x240 sampai 2592x1944 piksel. Mikroskop yang dibuat diuji dengan dengan berbagai preparat obyek dengan berbagai pembesaran, dan pemrosesan citra digital dilakukan pada citra obyek tersebut. Hasil pengujian menunjukkan bahwa mikroskop digital dengan sistem pengolah citranya mampu dipakai untuk mengamati preparat dan melakukan operasi citra preparat sesuai dengan keperluan pengguna. Mikroskop digital ini telah dapat menggantikan pengamatan langsung secara manual yang memerlukan ketajaman mata yang tinggi yang dilakukan pada mikroskop biasa. Abstract Many institutions, including high schools, own a large number of analog or ordinary microscopes. These microscopes are used to observe small objects. Unfortunately, object observations on the ordinary microscope require precision and visual acuity of the user. This paper discusses the development of a high-resolution digital microscope from an analog microscope, including the image processing utility, which allows the digital microscope users to capture, store and process the digital images of the object being observed. The proposed microscope is constructed from hardware components that can be easily found in Indonesia. The image processing software is capable of performing brightness adjustment, contrast enhancement, histogram equalization, scaling and cropping. The proposed digital microscope has a maximum magnification of 1600x, and image resolution can be varied from 320x240 pixels up to 2592x1944 pixels. The microscope was tested with various objects with a variety of magnification, and image processing was carried out on the image of the object. The results showed that the digital microscope and its image processing system were capable of enhancing the observed object and other operations in accordance with the user need. The digital microscope has eliminated the need for direct observation by human eye as with the traditional microscope.

A New Classification Technique in Mobile Robot Navigation

Abstract: This paper presents a novel pattern recognition algorithm that use weightless neural network (WNNs) technique.This technique plays a role of situation classifier to judge the situation around the mobile robot environment and makes control decision in mobile robot navigation. The WNNs technique is choosen due to significant advantages over conventional neural network, such as they can be easily implemented in hardware using standard RAM, faster in training phase and work with small resources. Using a simple classification algorithm, the similar data will be grouped with each other and it will be possible to attach similar data classes to specific local areas in the mobile robot environment. This strategy is demonstrated in simple mobile robot powered by low cost microcontrollers with 512 bytes of RAM and low cost sensors. Experimental result shows, when number of neuron increases the average environmental recognition ratehas risen from 87.6% to 98.5%.The WNNs technique allows the mobile robot to recognize many and different environmental patterns and avoid obstacles in real time. Moreover, by using proposed WNNstechnique mobile robot has successfully reached the goal in dynamic environment compare to fuzzy logic technique and logic function, capable of dealing with uncertainty in sensor reading, achieving good performance in performing control actions with 0.56% error rate in mobile robot speed.

The Damage of ZnO Arrester Block Due To Multiple Impulse Currents

Abstract: A lightning arrester installed in an electrical power system is designed to protect some electrical equipment against damage due to lightning impulse strike. However, if there is a multiple impulse current striking a lightning arrester, it may damage the lightning arrester itself and then, as a result, it cannot provide lightning protection to the electrical equipment anymore. In this research, three peak values of lightning impulse current,which were 600, 1300, and 2500A, each of which had 5 repetitive impulse current, was applied to a 5000A (1p.u.) ZnO block of a 24kV nominal voltage lightning arrester having seven ZnO block units. The results of research showed that by applying impulse current of the order of 600(0.12), 1300(0.26), dan 2500(0.5) A(p.u.), making the ZnO block damage as much as 26.58, 50, and 100% concecutively. In addition, the damage of the ZnO block appeared as permanen low value of residual voltage as low as more than 5% of the new ZnO block residual voltage. If the ZnO block is still being used in a lightning arrester in electrical power system, it may result in the opening of a circuit breaker and possibly making electrical power outages from a number of electrical power customers.

A Variable Switching Frequency with Boost Power Factor Correction Converter

Abstract: This paper presents single phase Power Factor Correction (PFC) with proposed variable switching frequency (VSF) control technique The increasing of non linear loads such as thyristor rectifiers, switching-mode power supplies, adjustable speed drives, and generate harmonic currents causing various problems to the other equipment connected to the point of common coupling There are several disadvantages in the existing PFC control implementation based on conventional PWM control This system considered uses a unified overcomes such a drawback by converting a voltage source into a fast-acting current source, which is reduce the harmonics in the line current, increases the efficiency and capacity of power system The capacitor and inductor with voltage and current ripple with minimum ripple values was designed to absorb sinusoidal input current and to reduce total harmonic distortion (THD) in the input current with output voltage regulation The principal of operation, theoretical analysis, simulation results on a single phase boost converter are presented