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Quality of Experience (QOE) Aware Video Attributes Determination for Mobile Streaming Using Hybrid Profiling

10.11591/ijeecs.v8.i3.pp597-609
Muhamad Hanif Jofri , Mohd Farhan Md Fudzee , Mohd Norasri Ismail , SHAHREEN KASIM , Jemal Abawajy
Today, consumers use a smartphone device to display the media contents for work and entertainment purposes, as well as watching online video. Online video streaming is the main cause that consume smartphone’s energy quickly. To overcome this problem, smartphone’s energy management is crucial. Thus, a hybrid energy-aware profiler is proposed. Basically, a profiler will monitor and manage the energy consumption in the smartphone devices. The hybrid energy-aware profiler will set up a protocol preference of both the user and the device. Then, it will estimates the energy consumption in smartphone. However, saving energy alone can contribute to the Quality of Experience (QoE) neglection, thus the proposed solution takes into account the client QoE. Even though there are several existing energy-aware profilers that have been developed to manage energy use in smartphones however, most energy-aware profilers does not consider QoE at the same time. The proposed solution consider both, the performance of the hybrid energy-aware profiler is compared with the baseline energy models against a variation of content adaptation according to the pre-defined variables. Three types of variables were determined; resolution, frame rate and energy consumption in smartphone devices. In this area, QoE subjective methods based on MOS (Mean Opinion Score) are the most commonly used approaches for defining and quantifying real video quality. Nevertheless, although these approaches have been established to consistently quantify users’ amounts of approval, they do not adequately realize which are the criteria of video attribute that important. In this paper, we conducted an experiment with a certain devices to measures user’s QoE and energy usage of video attribute in smartphone devices. Our results demonstrate that the list of possible solution is a relevant and useful video attribute that satify the users.
Volume: 8
Issue: 3
Page: 597-609
Publish at: 2017-12-01

Automatic Data Interpretation in Accounting Information Systems Based On Ontology

10.12928/telkomnika.v15i4.6414
Irvan; Institut Teknologi Bandung, Indonesia Iswandi , Iping Supriana; Institut Teknologi Bandung, Indonesia Suwardi , Nur Ulfa; Institut Teknologi Bandung, Indonesia Maulidevi
Financial transactions recorded into accounting journals based on the evidence of the transaction. There are several kinds of evidence of transactions, such as invoices, receipts, notes, memos and others.  Invoice as one of transaction receipt has many forms that it contains a variety of information.  The information contained in the invoice identified based on rules.  Identifiable information includes: invoice date, supplier name, invoice number, product ID, product name, quantity of product and total price.  In this paper, we proposed accounting ontology and Indonesian accounting dictionary. It can be used in intelligence accounting systems. Accounting ontology provides an overview of account mapping within an organization. The accounting dictionary helps in determining the account names used in accounting journals.  Accounting journal created automatically based on accounting evidence identification.  We have done a simulation of the 160 Indonesian accounting evidences, with the result of precision 86.67%, recall 92.86% and f-measure 89.67%.
Volume: 15
Issue: 4
Page: 1817-1829
Publish at: 2017-12-01

Artificial Neural Network Based Target Recognition for Marine Search

10.11591/ijeecs.v8.i3.pp616-618
Capt. V. Ramachandran
The key point of marine search and rescue is to find out and recognize the distress objects. At present, the visual search method is usually adopted to detect the ships in distress, and this method can only be used at good sea condition and visibility. In this paper, a new target detection and recognition system is proposed. The parameters of radar transmitter and echo graphics and the invariant moments of radar images are extracted as the system’s recognition features, and the system’s target classifier is based on Artificial Neural Networks (ANN). The developed recognition classifier has been tested using three kinds of target Images, the target’s features are used as the inputs of trained ANN and the outputs of networks are target classification. Sea experimental results show that the proposed method is well-clustering and with high classified accuracy.
Volume: 8
Issue: 3
Page: 616-618
Publish at: 2017-12-01

Neural KDE Based Behaviour Model for Detecting Intrusions in Network Environment

10.11591/ijai.v6.i4.pp166-173
V. Brindha Devi , K.L. Shunmuganathan
Network intrusion is one of the growing concern throughout the globe about the information stealing and data exfiltration. In recent years this was coupled with the data exfiltration and infiltration through the internal threats. Various security encounters have been taken in order to reduce the intrusion and to prevent intrusion, since the stats reveals that every 4 seconds, at least one intrusion is detected in the detection engines. An external software mechanism is required in order to detect the network intrusions. Based on the above stated problem, here we proposed a new hybrid behaviour model based on Neural KDE and correlation method to detect intrusions. The proposed work is splitted into two phases. Initial phase is setup with the Neural KDE as the learning phase and the basic network parameters are profiled for each hosts, here the neural KDE is generated based on the input and learned parameters of the network. Next phase is the detection phase, here the Neural KDE is computed for the identified parameters and the learned KDE feature value is correlated with the present KDE values and correlated values are calculated using cross correlation method. Experimental results show that the proposed model is robust in detecting the intrusions over the network.
Volume: 6
Issue: 4
Page: 166-173
Publish at: 2017-12-01

Intelligent Bridge Seismic Monitoring System Based on Neuro Genetic Hybrid

10.12928/telkomnika.v15i4.6006
Reni; Universitas Riau, Indonesia Suryanita , Mardiyono; Politeknik Negeri Semarang, Indonesia Mardiyono , Azlan; Universiti Teknologi Malaysia, Malaysia Adnan
The natural disaster and design mistake can damage the bridge structure. The damage caused a severe safety problem to human. The study aims to develop the intelligent system for bridge health monitoring due to earthquake load. The Genetic Algorithm method in Neuro-Genetic hybrid has applied to optimize the acceptable Neural Network weight. The acceleration, displacement and time history of the bridge structural responses are used as the input, while the output is the damage level of the bridge. The system displays the alert warning of decks based on result prediction of Neural Network analysis. The best-predicted rate for the training, testing and validation process is 0.986, 0.99, and 0.975 respectively. The result shows the damage level prediction is agreeable to the damage actual values. Therefore, this method in the bridge monitoring system can help the bridge authorities to predict the health condition of the bridge rapidly at any given time. 
Volume: 15
Issue: 4
Page: 1830-1840
Publish at: 2017-12-01

Pairwise Sequence Alignment between HBV and HCC Using Modified Needleman Wunsch Algorithm

10.12928/telkomnika.v15i4.5813
Lailil; Brawijaya University, Indonesia Muflikhah , Edy; Brawijaya University, Indonesia Santoso
Ths paper aims to find similarity of Hepatitis B virus (HBV) and Hepatocelluler Carcinoma (HCC) DNA sequences.The similarity of sequence allignments indicates that they have similarity of chemical and physical properties. Mutation of the virus DNA in X region has potential role in HCC. It is observed using pairwise sequence alignment of genotype-A in HBV. This paper is to purpose the modified method of Needleman Wunsch algorithm for optimum global DNA sequence alignment. The main idea is to optimize filling matrix and backtracking proccess of DNA components, so that there is reduction of computational time and space complexity. This research is applied to DNA sequence of 858 hepatitis B virus and 12 carcinoma patient. There are 10,296 pairwise of DNA sequences to be aligned globally using the modified method. As a result, it is achieved high similarity of 96.547% and validity of 99.854%. There is reduction of computational time as 34.6% and space complexity as 42.52%
Volume: 15
Issue: 4
Page: 1785-1793
Publish at: 2017-12-01

Selective Green Device Discovery for Device-to-Device Communication

10.12928/telkomnika.v15i4.6686
Bhaskara; Telkom University, Indonesia Narottama , Arfianto; Telkom University, Indonesia Fahmi , Rina Pudji; Telkom University, Indonesia Astuti , Desti Madya; Telkom University, Indonesia Saputri , Nur; Telkom University, Indonesia Andini , Hurianti; Telkom University, Indonesia Vidyaningtyas , Patricius Evander; Telkom University, Indonesia Christy , Obed Rhesa; Telkom University, Indonesia Ludwiniananda , Furry; Telkom University, Indonesia Rachmawati
The D2D communication is expected to improve devices’ energy-efficiency, which has become a major requirement of the future wireless network. Before the D2D communication can be performed, the device discovery between devices must be done. The previous works usually only assumed one mode of device discovery, i.e. either use network-assisted (with network supervision) or independent (without network supervision) device. Therefore, we propose a selective device discovery for device-to-device (D2D) communication that can utilize both device discovery modes and maintain devices’ energy-efficiency. Different from previous works, our proposed method selects the best device discovery mode to get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy expectation. Our experiment result indicates that the proposed method provides lowest energy consumption per new accepted device while compared with schemes with full network-assisted and independent device discovery in low numbers of new device arrival (for the number of new devices arrival = 1 ~ 3).
Volume: 15
Issue: 4
Page: 1666-1676
Publish at: 2017-12-01

Computer Aided Diagnosis using Margin and Posterior Acoustic Featuresfor Breast Ultrasound Images

10.12928/telkomnika.v15i4.5021
Hanung Adi; Universitas Gadjah Mada, Indonesia Nugroho , Yuli; Universitas Gadjah Mada Politeknik Caltex Riau, Indonesia Triyani , Made; Universitas Gadjah Mada Politeknik Caltex Riau, Indonesia Rahmawaty , Igi; Universitas Gadjah Mada, Indonesia Ardiyanto
Breast cancer is the most commonly diagnosed cancer among females worldwide. Computer aided diagnosis (CAD) was developed to assist radiologists in detecting and evaluating nodules so it can improve diagnostic accuracy, avoid unnecessary biopsies, reduce anxiety and control costs. This research proposes a method of CAD for breast ultrasound images based on margin and posterior acoustic features. It consists of preprocessing, segmentation using active contour without edge (ACWE) and morphological, feature extraction and classification. Texture and geometry analysis was used to determine the characteristics of the posterior acoustic and margin nodules. Support vector machines (SVM) provided better performance than multilayer perceptron (MLP). The performance of proposed method achieved the accuracy of 91.35%, sensitivity of 92.00%, specificity of 89.66%, PPV of 95.83%, NPV of 81.26% and Kappa of 0.7915. These results indicate that the developed CAD has potential to be implemented for diagnosis of breast cancer using ultrasound images.
Volume: 15
Issue: 4
Page: 1776-1784
Publish at: 2017-12-01

Design and Development of a Shortwave near Infrared Spectroscopy using NIR LEDs and Regression Model

10.11591/ijece.v7i6.pp3070-3075
Kim Seng Chia , Yit Peng Tan
Near infrared (NIR) spectroscopic technology has been getting more attention in various fields. The development of a low cost NIR spectroscopy is crucial to reduce the financial barriers so that more NIR spectroscopic applications will be investigated and developed by means of the NIR spectroscopic technology. This study proposes an alternative to measure shortwave NIR spectrum using one collimating lens, two slits, one NIR transmission grating, one linear array sensor, and one microcontroller. Five high precision narrow bands NIR light emitting diodes (LEDs) were used to calibrate the proposed spectroscopy. The effects of the proposed two slits design, the distance between the grating and linear array sensor, and three different regression models were investigated. The accuracy of the proposed design was cross-validated using leave-one-out cross-validation. Results show that the proposed two slits design was able to eliminate unwanted signals substantially, and the cross-validation was able to estimate the best model with root mean squared error of cross-validation of 3.8932nm. Findings indicate that the cross-validation approach is a good approach to estimate the final model without over-fitting, and the proposed shortwave NIR spectroscopy was able to estimate the peak value of the acquired spectrum from NIR LEDs with RMSE of 1.1616nm.
Volume: 7
Issue: 6
Page: 3070-3075
Publish at: 2017-12-01

Vision Based Human Decoy System for Spot Cooling

10.12928/telkomnika.v15i4.7229
Tan; Universiti Tun Hussein Onn Malaysia Chun Hou , Wan; Universiti Tun Hussein Onn Malaysia Nurshazwani Wan Zakaria , Tai; Universiti Tun Hussein Onn Malaysia Sue Jing , Razali; Universiti Tun Hussein Onn Malaysia Tomari , Tee; Universiti Tun Hussein Onn Malaysia Kian Sek , Anis; Universiti Tun Hussein Onn Malaysia Azwani Muhd Suberi
This project aims to reduce the energy consumption of air conditioner usage while maintaining occupant comfort. Cooling down the unoccupied space can be considered as waste of energy. Therefore, a human decoy system is proposed to track any human in the detection area. Image contains depth data in each pixel which can be used to detect the presence of target subject as well as their position. The acquired position data is processed by using MATLAB and subsequently is transmitted to Arduino Mega using serial communication to control stepper motors. The experimental results show that the air conditioner airflow is successfully can be directed to the target human subject with average response of 0.860 seconds per movement within detection area.
Volume: 15
Issue: 4
Page: 1512-1519
Publish at: 2017-12-01

Detection of Infiltrate on Infant Chest X-Ray

10.12928/telkomnika.v15i4.3163
Jufriadif; Universitas Putra Indonesia YPTK, Indonesia Na'am , Johan; Gunadarma University Jakarta, Indonesia Harlan , Gunadi Widi; Universitas Putra Indonesia YPTK Padang, Indonesia Nurcahyo , Syafri; Universitas Putra Indonesia YPTK Padang, Indonesia Arlis , Sahari; Universitas Putra Indonesia YPTK Padang, Indonesia Sahari , Mardison; Universitas Putra Indonesia YPTK Padang, Indonesia Mardison , Larissa Navia; Universitas Putra Indonesia YPTK Padang, Indonesia Rani
Currently, Chest X-ray is still widely used around the world for disease examination. This is due to its low cost, low radiation and a lot of disease information. The commonly detected disease using chest x-rays is lung disease. The characteristic of this disease is infiltrate. However, the accuracy of Chest X-ray observations is still low. Therefore, this research offers a method to perform Chest X-ray image processing in clarifying the information contained therein. This research used Chest X-ray of infant patients who treated at Central Public Hospital (RSUP) Dr. M. Djamil Padang. The total of the images tested were 17 images. In these images, there were some suspected infiltrates after being analyzed by doctors. Software used was Matlab which is conducted by applying image processing method. The method used consisted of 4 parts, that was Cropping, Filtering, Detecting Edge, and Sharpening Edge. The results of the research showed that the method could clarify edge detection of the objects contained in the image, so that the infiltrate could be more easily recognized. With this easiness, it will help the doctor to remove doubts for infiltrate observations in the Infant's lungs.
Volume: 15
Issue: 4
Page: 1938-1946
Publish at: 2017-12-01

The Use of Polymer Based Gas Sensor for Detecting Formalin in Food Using Artificial Neural Network

10.12928/telkomnika.v15i4.6164
Budi; Universitas Muria Kudus, Indonesia Gunawan , Arief; Universitas Jenderal Soedirman Grendeng, Indonesia Sudarmaji
The usage of formalin as preservative substance in food is dangerous and make much threat to public society. Yet, it is difficult to identify the presence of formalin in food sensory. It commonly requires laboratory-based testing to detect the formalin. This work describes a detector system of formalin presence in food which employs a series of polymer-based gas sensor and uses a neural network detection method. The sensors are the polymer-carbon composite which made of the polymer mixed with active carbon. There are four types of polymer used, i.e. Polyethylene Glycol (PEG) 6000, PEG200, PEG20M, and PEG1450. The polymer-carbon composite provided a unique characteristic when it is exposed to vapor of food with or without formalin. The resistance of each polymer is different for each detected vapor. The combination of those sensors gives a pattern of voltage output on the sensors when they are exposed certain gas so that every gas has its unique output pattern. The method of detection uses an algorithm of back-propagation of the neural network. That voltage pattern of sensors serves as input to an artificial intelligence program. The result shows that the system has the accuracy of 75% in detecting formalin in food.
Volume: 15
Issue: 4
Page: 1641-1650
Publish at: 2017-12-01

Crops Diseases Detection and Solution System

10.11591/ijict.v6i3.pp209-217
Md. Abdul Awal , Mohammad Jahangir Alam , Md. Nurul Mustafa
The technology based modern agriculture industries are today’s requirement in every part of agriculture in Bangladesh. In this technology, the disease of plants is precisely controlled. Due to the variable atmospheric circumstances these conditions sometimes the farmer doesn’t know what type of disease on the plant and which type of medicine provide them to avoid diseases. This research developed for crops diseases detection and to provides solution by using image processing techniques. We have used Android Studio to develop the system. The crops diseases detection and solution system is compared the image of affected crops with database of CDDASS (Crops Diseases Detection and Solution system). If CDDASS detect any disease symptom, then provide suggestion so that farmers can take proper decision to provide medicine to the affected crops. The application has developed with user friendly features so that farmers can use it easily.
Volume: 6
Issue: 3
Page: 209-217
Publish at: 2017-12-01

250 MHz Multiphase Delay Locked Loop for Low Power Applications

10.11591/ijece.v7i6.pp3323-3331
Shruti Suman , K. G. Sharma , P. K. Ghosh
Delay locked loop is a critical building block of high speed synchronous circuits. An improved architecture of amixed signaldelay locked loop (DLL) is presented here. In this DLL, delay cell based on single ended differential pair configuration is used for voltage controlled delay line (VCDL) implementation. This delay cell provides a high locking range with less phase noise and jitter due to differential pair configuration.For increasing the acquisition range and locking speed of the DLL, modified true single phase clock (TSPC) based phase frequency detector is used. The proposed design is implemented at 0.18 um CMOS technology and at power supply of 1.8V . It has power consumption of 1.39 mW at 125 MHz center frequency with locking range from 0.5 MHz to 250 MHz.
Volume: 7
Issue: 6
Page: 3323-3331
Publish at: 2017-12-01

Pervasive Device and Service Discovery Protocol in Interoperability XBee-IP Network

10.12928/telkomnika.v15i4.5725
Sabriansyah Rizqika; Brawijaya University, Indonesia Akbar , Helmi; Brawijaya University, Indonesia Nizar , Wijaya; Brawijaya University, Indonesia Kurniawan , Mochammad Hannats; Brawijaya University, Indonesia Hanafi Ichsan , Issa; Brawijaya University, Indonesia Arwani
The Internet of Things (IoT) communication protocol built over IP and non-IP environment. Therefore, a gateway device will be needed to bridge the IP and non-IP network transparently since an IoT user is more likely to concern on the service provided by the IoT device, rather than the complexity of the network or device configuration. Since today ubiquitous computing needs to hide the architectural level from it users, the data & information centric approach was proposed. However, the data & information centric protocol is having several issues and one of them is device and service discovery protocol over IP & non-IP network. This paper proposed a pervasive device and service discovery protocol that able to work in interoperability of the IP and non-IP network. The system environment consists of a smart device with XBee Communication as the non-IP network that will send the device and service description data to the IP network using WebSocket. The gateway will able to recognize the smart device and sent the data to the web-based user application. The user application displayed the discovered devices along the services and able to send the control data to each of the smart devices. Our proposed protocol also enriched with the smart device inoperability detection by using keep-alive tracking from the gateway to each of the smart devices. The result showed that the delay for the user application to detect the smart device in the XBee network is around 10.13 ms delay, and the service average delay requested by the user application to each of the devices is 2.13 ms.
Volume: 15
Issue: 4
Page: 1875-1882
Publish at: 2017-12-01
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