EMITTER - International Journal of Engineering Technology
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    261 research outputs found

    A Simplified Sounding System for Finding NVIS Channel Availability to Support Government Radio Networks in Indonesia

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    Mostly  natural disasters in Java Island such as landslides are within the vicinity of not more than 200 Km from the district capital. Cellular communications require complex systems and rather vulnerable  to cope with disasters. NVIS mode is considered as a simple radio link during disaster mitigation initiation process. It needs a valid estimation to figure out the condition of the ionosphere. There are two purposes of this study, the first of which is an attempt to find out a fact the existences of authorized HF users who still work in the band of 3 MHz – 10 MHz.  The second is to integrate low cost HF radio communication, commonly available small single board computer hardware, and opensource software, to build a sounding system to evaluate the quality of NVIS channels. Prediction system such VOACAP give hourly prediction data, however it has an inherent limitation because of   nature the underlying databases is monthly average based, therefore, the estimation could not be made in a daily bases. However, a real-time channel evaluation (RTCE)  able to purify maximum observed frequency (MOF) estimation, and consequently, its able to select the best available frequency for short term  and real time operation. In this study, we used WSPR to perform a simple RTCE technique. Furthermore, we also reviewed the current regulatory status regarding  the availability of sub-10 MHz band for NVIS radio operation. The results show that discrepancies between simulation and measurement are occurred mainly because of sporadic data in the band of 60m and 80m. However, all of the measurement results and simulations almost have the same agreement regarding the quiet period between local midnight and local sunrise. The results of measurements show that 60m band is the most reliable NVIS channel between local sunrise and local midnight. Furthermore, 100 watts is a proper transmitter power to reach the required SNR for reliable voice communication.Â

    Design and Analysis of the Voltage Controller for the Non Isolated Boost DC-DC Convertor

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    In this paper, a controller has been presented by the root locus method based on the state space average model of the boost switching regulator with all of the converter’s parameters and uncertainties. In this model, the load current is unknown and the inductor, capacitor, diode and active switch are non ideal and have an on-state resistance. Furthermore, an on-state voltage drop has been considered for diode and active switch. By neglecting the load current and assuming the ideal elements the simplified model of the regulator has been caddied out. By these complete and simplified models, a step by step method has been proposed to design a single input single output (SISO), second order controller based on roots locus method. In this regard the controller's electronic circuit has been introduced by operational amplifiers. At the end, by simulation of the complete closed-loop system in MATLAB Simulink environment and comparing its results by the results of the regulator and controller circuits in PLECS, the accuracy of the designed controller performance has been shown

    Enhancing the Productivity of Wire Electrical Discharge Machining Toward Sustainable Production by using Artificial Neural Network Modelling

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    Sustainability plays an important role in manufacturing industries through economically-sound processes that able to minimize negative environmental impacts while having the social benefits. In this present study, the modeling of wire electrical discharge machining (WEDM) cutting process using an artificial neural network (ANN) for prediction has been carried out with a focus on sustainable production. The objective was to develop an ANN model for prediction of two sustainable measures which were material removal rate (as an economic aspect) and surface roughness (as a social aspect) of titanium alloy with ten input parameters. By concerning environmental pollution due to its intrinsic characteristics such as liquid wastes, the water-based dielectric fluid has been used in this study which represents an environmental aspect in sustainability. For this purpose, a feed-forward backpropagation ANN was developed and trained using the minimal experimental data. The other empirical modelling techniques (statistics based) are less in flexibility and prediction accuracy. The minimal, vague data and nonlinear complex input-output relationship make this ANN model simple and perfects method in the manufacturing environment as well as in this study. The results showed good agreement with the experimental data confirming the effectiveness of the ANN approach in the modeling of material removal rate and surface roughness of this cutting process

    Medical Image Encryption Using Modified Identity Based Encryption

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    The development of technology and communication also affects the level of security needed for digital image transmission. It is known that digital images now have important meanings in both communication and video conference. In this paper, we propose a security method for medical encryption in the form of images. The proposed method is implemented in the modified Identity-Based Encryption scheme. The encryption algorithm used is Elliptic Curve Cryptography (ECC) to generate key pairs and the Advanced Encryption Standard (AES) to generate symmetric keys and encrypt process. This method has been tested based on computation time, histogram analysis and statistical analysis. The results of the test were obtained that the proposed method was resistant to multiple attacks despite having slower computing time. The proposed compute time error percentage is 1.69% for key generator stages and 0.07% for total compute time at the encrypt-decrypt stage

    A Full-Bridge Bidirectional DC-DC Converter with Fuzzy Logic Voltage Control for Battery Energy Storage System

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    Renewable energy sources require an energy storage system because its are fluctuating and electricity producing at certain times, even sometimes not in accordance with the needs of the load. To maintain continuity of electricity, smart battery energy storage system is needed. Therefore, this paper of a full-bridge bidirectional DC-DC Converter (FB-BDC) with Fuzzy Logic Control (FLC) is designed and implemented for battery energy storage application. The FLC has error and delta error of voltage level as input and duty cycle of FB-BDC as output. The FB-BDC is controlled by a microcontroller ARM Cortex-M4F STM32F407VG for voltage mode control. The FB-BDC topology is selected becuase battery storage system needed isolated and need high voltage ratio both for step-up and step-down. The main purpose of FB-BDC to perform bidirectional energy transfer both of DC-Bus and battery. Moreover, FB-BDC controls the DC-Bus voltage according to referenced value. The power flow and voltage on DC-Bus is controlled by FLC with voltage mode control. The experiment result shows the ability of FLC  voltage mode control to control FB-BDC on regulate charging voltage with an error 1% and sharing voltage 1.5% form referenced value

    AI-Josyu: Thinking Support System in Class by Real-time Speech Recognition and Keyword Extraction

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    In this paper, we present a thinking support system, AI-Josyu. This system also operates as a class support system which helps to teachers for lightening their work. AI-Josyu is implemented based on media-driven real-time content management framework. The system links real world media and legacy media contents together. In resent years, it is easier to collect a large amount of various kinds of data which are created with sensors in the real world. The system realizes interconnection and utilization of legacy media contents. The legacy media contents are generated and scattered on the Internet. The framework has four modules, which are called “acquisition,†“extraction,†“selection,†and “retrieval.†The real world media and the legacy media contents are interconnected by these modules. This interconnection includes semantic components. This system records teacher's voice of its lecture in real time and presents retrieved legacy media contents corresponding to subject of the lecture. By this presentation, preparing of the legacy contents is not required. This system automatically retrieves and shows the legacy media contents. This system helps students to understand contents of the lecture. In addition, the system attends to expansion of ideas. We constructed the system and conducted the demonstration in class. It shows that the system is helpful to teacher and students for expansion of thinking

    Wavelet Based Fault Detection and Classification Algorithm for a Real Distribution Feeder

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    As the importance of protection in power systems increase, knowing the type of malfunction occurring in the system has become crucial. Especially in the distribution system where electricity is delivered to the consumer, detecting the right fault type with a short amount of time is important. For this purpose in this study, Akyazı-Düzköy distribution feeder in Trabzon province, where faults commonly occur, is modeled with Digsilent Powerfactory. The model is performed with actual parameters including 465 lines, 243 loads, 233 transformers and 1093 busbars. First, the load flow and short circuit analysis have been carried out for the validation of the model. Then a fault detection and classification algorithm is enhanced using the wavelet transform and the energy of the coefficients. Different types of short circuit faults are created at different points on the model to test the accuracy of the algorithm. The fault inception time and the effect of the fault resistance are also investigated

    GURILEM : A Novel Design of Customer Rating Model using K-Means and RFM

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    A rating system or reviews are generally used to assist in making decisions. Rating system widely used as a technique in the recommendation of one of them used by the customer, as in determining the resort to be used. However, the credibility of the rating looks vague because the rating could only represent some points of service. So that customer preference with each other is very different. Personalized recommendation systems offer more personalized advice, precisely knowing the preferences or tastes of the customers. Especially for customers who have a transaction history or reservation as at their resorts provide good information used by managers to design a recommendation model for their customers. In this study aims to create a model of resort recommendations based on a rating of frequency. This frequency is the number of resort use by the customer within the specified time frame. With the frequency can represent the preferences of customers. The RFM method is used to measure the reservation frequency value of the customer. The K-Means method is used to categorize customer data with its frequency and classify the type of resort. Recommendation resort to the customer based on the dominant use in one of the resort types. The recommended type of resort based on the similarity between the types of resorts used with other types of resorts

    An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator

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    The traveling salesman problem (TSP) is a famous NP-hard problem in the area of combinatorial optimization. It is utilized to locate the shortest possible route that visits every city precisely once and comes back to the beginning point from a given set of cities and distance. This paper proposes an efficient and effective solution for solving such a query. A modified crossover method using Minimal Weight Variable, Order Selection Crossover operator, a modified mutation using local optimization and a modified selection method using KMST is proposed. The crossover operator (MWVOSX) chooses a particular order from multiple orders which have the minimum cost and takes the remaining from the other parent in backward and forward order. Then it creates two new offspring. Further, it selects the least weight new offspring from those two offspring. The efficiency of the proposed algorithm is compared to the classical genetic algorithm. Comparisons show that our proposed algorithm provides much efficient results than the existing classical genetic algorithm

    The Multipath Influence in Real-Time Kinematic of GNSS Observations at Different Antenna Heights

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    Multipath is a dominant error source in Real-Time Kinematic (RTK) applications that reduces the position, time and velocity accuracy. Mitigation of such errors can be achieved by better signal processing and antenna design. This paper attempts to examine the different height of RTK system antenna with regards to the multipath error. The results obtained in this work show height significantly change of multipath in pseudo range (MP1) and multipath in the carrier phase (MP2). Different antenna height does not give the same multipath error result in the tests that we have conducted in this work. The optimal height of the antenna was achieved as two meters in order to obtain a minimum multipath error for   MP1 and MP2. At the end of this work, we experimentally proved that there is an inverse relationship between the height of the antenna and multipath with RTK algorithm

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    EMITTER - International Journal of Engineering Technology
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