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EMITTER International Journal of Engineering Technology

EMITTER
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Published by Politeknik Elektronika Negeri Surabaya

ISSN : 2355391x EISSN : - DOI : -

Core Subject : Science,

Computer Science & IT

EMITTER International Journal of Engineering Technology is a BI-ANNUAL journal published by Politeknik Elektronika Negeri Surabaya (PENS). It aims to encourage initiatives, to share new ideas, and to publish high-quality articles in the field of engineering technology and available to everybody at no cost. It stimulates researchers to explore their ideas and enhance their innovations in the scientific publication on engineering technology. EMITTER International Journal of Engineering Technology primarily focuses on analyzing, applying, implementing and improving existing and emerging technologies and is aimed to the application of engineering principles and the implementation of technological advances for the benefit of humanity.

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Articles 21 Documents

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Search results for , issue "Vol 7 No 1 (2019)" : 21 Documents clear

FPGA Based Design of Artificial Neural Processor Used for Wireless Sensor Network Azzad Bader Saeed; Sabah Abdul-Hassan Gitaffa
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

In this paper,Â a simulation ofÂ artificial intelligent system has been designed for processingÂ the incoming data ofÂ sensorÂ units and then presenting proper decision. The Back-propagation Neural Network BPNN has been used as the proposedÂ intelligent system for this work, whereas the BPNN is considered as a trained network in conjunction with an optimization method for changing the weights and biases of the overall network. The main two features of theÂ BPNN are: high speed processing, and producingÂ lowest Mean-Square-Error MSE ( cost function ) in few iterations. The proposed BPNN has used the linear activation functions 'Satlins' and 'Satline' for the hidden and output layer respectively, and has used the training function 'Traingda' ( which is gradient descent with adaptive learning rate)Â as a powerful learning method. It is worth to mention, that no previous research used these three functions together for such analysis. The MATLAB software package has been used forÂ designing and testing the proposed system. An optimal result has been obtained in this work, where the value ofÂ Mean-Square-Error has reached to zeroÂ Â in 87 epochs, and the real and desired outputs have been fitted. In fact, there isÂ no previous work has reached to this optimal result.Â The proposed BPNN has been implemented in FPGA, which is fast, and low power tool.

Medical Health Record Protection Using Ciphertext-Policy Attribute-Based Encryption and Elliptic Curve Digital Signature Algorithm Novi Aryani Fitri; M. Udin Harun Al Rasyid; Amang Sudarsono
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Information on medical record is very sensitive data due to the number of confidential information about a patient's condition. Therefore, a secure and reliable storage mechanism is needed so that the data remains original without any changes during it was stored in the data center. The user must go through an authentication process to ensure that not an attacker and verify to ensure the authenticity and accuracy of the data received. In this research, we proposed a solution to secure medical data using the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Elliptic Curve Digital Signature Algorithm (ECDSA) methods. Our system can secure data centers from illegal access because the uploaded data has patient control over access rights based on attributes that have been embedded during the data encryption process. Encrypted data was added to the digital signature to pass the authentication process before being sent to the data center. The results of our experiments serve efficient system security and secure with low overhead. We compare the proposed system performance with the same CP-ABE method but donâ€™t add user revocation to this system and for our computing times are shorter than the previous time for 0.06 seconds and 0.1 seconds to verify the signature. The total time in the system that we propose requires 0.6 seconds.

Enhanced PEGASIS using Dynamic Programming for Data Gathering in Wireless Sensor Network Mohammad Robihul Mufid; M. Udin Harun Al Rasyid; Iwan Syarif
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

A number of routing protocol algorithms such as Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) have been proposed to overcome the problem of energy consumption in Wireless Sensor Network (WSN) technology. PEGASIS is a development of the LEACH protocol, where within PEGASIS all nodes are active during data transfer rounds thus limiting the lifetime of the WSN. This study aims to propose improvements from the previous PEGASIS version by giving the name Enhanced PEGASIS using Dynamic Programming (EPDP). EPDP uses the Dominating Set (DS) concept in selecting a subset of nodes to be activated and using dynamic programming based optimization in forming chains from each node. There are 2 topology nodes that we use, namely random and static. Then for the Base Station (BS), it will also be divided into several scenarios, namely the BS is placed outside the network, in the corner of the network, and in the middle of the network. Whereas to determine the performance between EPDP, PEGASIS and LEACH, an analysis of the number of die nodes, number of alive nodes, and remaining of energy were analyzed. From the experiment result, it was found that the EPDP protocol had better performance compared to the LEACH and PEGASIS protocols in terms of number of die nodes, number of alive nodes, and remaining of energy. Whereas the best BS placement is in the middle of the network and uses static node distribution topologies to save more energy.

Content-Dependent Image Search System for Aggregation of Color, Shape and Texture Features Arvita Agus Kurniasari; Ali Ridho Barakbah; Achmad Basuki
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

The existing image search system often faces difficulty to find a appropriate retrieved image corresponding to an image query. The difficulty is commonly caused by that the usersâ€™ intention for searching image is different with dominant information of the image collected from feature extraction. In this paper we present a new approach for content-dependent image search system. The system utilizes information of color distribution inside an image and detects a cloud of clustered colors as something - supposed as an object. We applies segmentation of image as content-dependent process before feature extraction in order to identify is there any object or not inside an image. The system extracts 3 features, which are color, shape, and texture features and aggregates these features for similarity measurement between an image query and image database. HSV histogram color is used to extract color feature of image. While the shape feature extraction used Connected Component Labeling (CCL) which is calculated the area value, equivalent diameter, extent, convex hull, solidity, eccentricity, and perimeter of each object. The texture feature extraction used Leung Malik (LM)â€™s approach with 15 kernels.Â For applicability of our proposed system, we applied the system with benchmark 1000 image SIMPLIcity dataset consisting of 10 categories namely Africans, beaches, buildings historians, buses, dinosaurs, elephants, roses, horses, mountains, and food. The experimental results performed 62% accuracy rate to detect objects by color feature, 71% by texture feature, 60% by shape feature, 72% by combined color-texture feature, 67% by combined color-shape feature, 72 % combined texture-shape features and 73% combined all features.

Enhancing the Productivity of Wire Electrical Discharge Machining Toward Sustainable Production by using Artificial Neural Network Modelling Muhammad Akmal Mohd Zakaria; Raja Izamshah Raja Abdullah; Mohd Shahir Kasim; Mohamad Halim Ibrahim
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

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.

Design, Analysis and Performance Evaluation of Electrical Power Subsystem based on Triple-Junctions Solar PV Cells and SEPIC for a Conceptual 1u Cubesat Mission Ali Danladi; Mehmet KurtoÄŸlu; Ahmet Mete Vural
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

This study aims to popularize low voltage power supply design especially for space satellite Cubesat mission and other portable consumer electronic devices. In this context, a preliminary design of an electrical power subsystem (EPS) is carried out for a conceptual 1u Cubesat mission in this paper. Mathematical modeling of the basic elements of the EPS is presented. Photovoltaic (PV) power generation system that is selected is made up of triple-junction solar cells, and the battery charging system based on lithium technology as well as the power conditioning converters are selected based on single ended primary inductance converter topology popularly abbreviated as SEPIC. Triple-junction solar PV cell results are verified by comparing with the datasheet values. A maximum power point tracking algorithm which is known as perturb and observe is implemented and proportional-integral controller is used for the SEPIC. All of these are well analyzed, mathematically modeled and simulated. Feasibility of the designed EPS is verified by comparing with similar devices from different manufacturers.

Improvement of Segmentation Performance for Feature Extraction on Whirlwind Cloud-based Satellite Image using DBSCAN Clustering Algorithm Nailus Sa'ada; Tri Harsono; Ahmad Basuki
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Images contain a lot of information that can be used in a variety of areas. One of the images that have much information inside is satellite image. In order to extract the information properly, the image processing step should be performed properly. The segmentation process plays an important role in image processing, especially for feature extraction. Many ways were developed to perform the segmentation image. In this study, we apply DBSCAN clustering to segment images on whirlwind cloud feature extraction problems. DBSCAN is a density-based classifier method which means it is suitable to group a density-based data. While the image used in the segmentation process is the Himawari 8 satellite image which also contains density-based data. It contains various information about clouds condition like cloud type, cloud temperature, cloud humidity, rainfall potential based on cloud temperature, etc. This study uses Himawari 8 satellite images as input where the images taken are images several hours before a wirlwind event in an area, while the cluster method used is the DBSCAN algorithm. Clustering is done to get the extraction features of a wirlwind in the form of centroid points that characterize the movement of a cloud. Segmentation performance was observed based on the number of centroid points as a result of clustering several types of clouds in an area before a wirlwind occurred. Based on segmentation testing using the DBSCAN algorithm for cloud data in an area for several hours before a wirlwind, better segmentation performance was obtained compared to the segmentation results of the Meng hee heng k-means algorithm for the same test data specifications. DBSCAN separates a type of cloud in more detail that makes it easier to record each centroid of each cluster around the scene. It is even able to cluster small groups of clouds independently so that these small groups of clouds can also be detected as features.

AI-Josyu: Thinking Support System in Class by Real-time Speech Recognition and Keyword Extraction Kyohei Matsumoto; Takafumi Nakanishi; Toshitada Sakawa; Kengo Onodera; Shinichiro Orimo; Hiroyuki Kobayashi
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

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 â€œacquisition,â€ â€œextraction,â€ â€œselection,â€ and â€œretrieval.â€ 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.Â 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 Hatice OkumuÅŸ; Fatih Mehmet NUROGLU
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v7i1.382

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, AkyazÄ±-DÃ¼zkÃ¶y 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.

Observation of Fish Dissemination Pattern on Madura Coastal Using Segmentation of Satellite Images Citra Nurina Prabiantissa; Achmad Basuki; Wahjoe Tjatur Sesulihatien
EMITTER International Journal of Engineering Technology Vol 7 No 1 (2019)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Almost traditional fishermen still use manual methods to catch fish that rely on experience in fishing and information among fellow fishermen. This method is not effective for maximizing fish production. A good pattern or strategy is needed to increase fish production. In determining dissemination pattern of fish, it can be predicted from physical parameters such as temperature, salinity, chlorophyll, turbidity, total suspended solids, and colored dissolved organic matter using the Landsat 8 images. Â This research area is on the Island of Madura Coast. The pattern is determined by using Lagrange Interpolation and clustering using K-Means. The results of the study of the pattern of fish dissemination were then validated with data from the Dinas Kelautan dan Perikanan Jawa Timur. The results between fish patterns and validation data in 2015 showed similarities in January, February, March, May, June, July, August, September. In 2016, results between fish patterns and validation data showed that similarities in July, August, September, and December. In 2017, results between fish patterns and validation data showed similarities in November. 2015 has the most similarities between the patterns and validation data and the least similarity are 2017.

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