Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Filter Icon

Filters article

Years

FAQ Arrow
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

29,758 Article Results

Determination of favorable blood glucose target range for stochastic TARgeted (STAR) glycemic control in Malaysia

10.11591/ijeecs.v15.i1.pp133-141
A. Abu-Samah , N. N. A. Razak , A. A. Razak , U. K. Jamaludin , F. M. Suhaimi , A. M. Ralib
Stress-induced hyperglycemia is common in critically ill patients, but there is uncertainty about what constitutes an optimal blood glucose target range for glycemic control. Furthermore, to reduce the rate of hyperglycemic and hypoglycemic events, model-based glycemic control protocols have been introduced, such as the stochastic targeted (STAR) glycemic control protocol. This protocol has been used in the intensive care units of Christchurch and Gyulà Hospital since 2010, and in Malaysia since 2017. In this study, we analyzed the adaptability of the protocol and identified the blood glucose target range most favorable for use in the Malaysian population. Virtual simulation results are presented for two clinical cohorts: one receiving treatment by the STAR protocol itself and the other receiving intensive insulin therapy by the sliding scale method. Performance and safety were analyzed using five clinical target ranges, and best control was simulated at a target range of 6.0–10.0 mmol/L. This target range had the best balance of performance, with the lowest risk of hypoglycemia and the lowest requirement for nursing interventions. The result is encouraging as the STAR protocol is suitable to provide better and safer glycemic control while using a target range that is already widely used in Malaysian intensive care units
Volume: 15
Issue: 1
Page: 133-141
Publish at: 2019-07-01

Review on mathematical models for the prediction of solar radiation

10.11591/ijeecs.v15.i1.pp56-61
Meenal Rajasekaran , A.Immanuel Selvakumar , E. Rajasekaran
Global Solar Radiation (GSR) data is important for all solar energy based applications, mainly to forecast the output power of solar PV system in case of renewable energy integration in to the existing grid. The solar radiation components are measured using pyranometer, solarimeter, pyroheliometer and so on. It is not practically possible to install this radiation measuring instruments at all the locations due to the cost and difficulty in measurements. Hence the availability of solar radiation data is limited to few meteorological stations especially in the developing country like India. Therefore, it is necessary to develop mathematical models to predict the solar radiation to eliminate the costly pyranometer. In this paper, the review of mathematical models using trigonometric functions for the prediction of global solar radiation is presented. The mathematical models are applicable wherever the radiation data is unavailable. From the review results, it is concluded that mathematical model with both sine and cosine wave equation gives good prediction accuracy with correlation coefficient of 0.95
Volume: 15
Issue: 1
Page: 56-61
Publish at: 2019-07-01

Prediction of hypertention drug therapy response using K-NN imputation and SVM algorithm

10.11591/ijeecs.v15.i1.pp460-467
Lailil Muflikhah , Nurul Hidayat , Dimas Joko Hariyanto
Hypertention is a degenerative disease but its healing takes a long time by consuming hypertension drugs until patient’s lifetime. The research is conducted to predict response of drug therapy using bioinformatics approach which is a blend of biological and informatics engineering methods. It is used medical record data of hypertensive patient in drug therapy which has an impact on genetic characteristics. The data is constructed as modelling for learning process. Then, it is implemented as a prediction whether the blood presure is under control or not. However, the amount data have no values, then they are required to be applied preprocessing data. Therefore, this research is proposed K-Nearest Neighbor (K-NN) Imputation algorithm for refining data. After that, it is implemented using Support Vector Machine (SVM) algorithm for prediction.The experiment result is achieved the highest accuracy rate of 90% at the best parameter value λ = 0.9, Σ = 2, C = 0.1, ε = 0.001 in ten times iterations.
Volume: 15
Issue: 1
Page: 460-467
Publish at: 2019-07-01

Crowd behavior analysis using MoDTA approach

10.11591/ijeecs.v15.i1.pp484-494
Savitha C , Dr. Ramesh. D
In order to analyze the behaviors of human, significant extent of work has been carried out in the video surveillance applications. While considering the crowded scenes, the adopted features are crafted manually which have a great side to detect anomaly. It requires prior information and is hard to extract from complex video scenes and also it involves huge computational costs. In this paper, we are proposing multi-observational detection and tracking approach (MoDTA) that is based on observational filter. The MoDTA initially acquires  people location in an image, so that is can detect conviction value at pointed locations which generally increases with respect to people density. In the phase of tracking, MoDTA computes the multiple observed weight values and individual features, also advection particle is used at motion model in order to facilitate the dense scenario tracking. Coefficient of correlation is used as template detector and the function of template detector is to estimate the upcoming object. Our proposed MoDTA is compared with other existing detection and tracking methods in order to evaluate the system performance. 
Volume: 15
Issue: 1
Page: 484-494
Publish at: 2019-07-01

Blockchain based crowdfunding systems

10.11591/ijeecs.v15.i1.pp409-413
Md Nazmus Saadat , Syed Abdul Halim , Husna Osman , Rasheed Mohammad Nassr , Megat F. Zuhairi
Initially, blockchain is only used as a foundation of cryptocurrency, but today, we can see the rise of this new emerging technology are being implemented in many industries. In the future, most technologies around the world are expected to use blockchain as an efficient way to make online transactions. One of the areas that blockchain technologies can be applied is crowdfunding platforms. The most common problem with current crowdfunding scene in around the world including is that the campaigns are not regulated and some of the crowd-funding campaign turned out to be fraud. Besides, the completion of some projects also was significantly delayed. This project aims to solve these problems by applying Ethereum smart contracts to the crowdfunding site to that the contracts will be fully automatically executed, thus preventing frauds and ensuring that the projects can be delivered within duration given.
Volume: 15
Issue: 1
Page: 409-413
Publish at: 2019-07-01

Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender

10.11591/ijeecs.v15.i1.pp199-210
N. S. Nor Shahrudin , K. A. Sidek , A. Z. Jusoh
Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age and gender will affect unequal amount of stress. Electrocardiogram (ECG) signal is an electrical indicator of the heart that can detect changes of human response which relates to our emotions and reactions. Thus, this research proposed a non-intrusive detector to identify stress level for both gender and different classification of age using the ECG. A total of 30 healthy subjects were involved during the data acquisition stage. Data acquisition which initialize ECG data were divided into two conditions; which are normal and stress states. ECG data for normal state only need the participant to breath in and out normally. In other hand, the participants also need to undergo Stroop Colour word test as a stress inducer to represent ECG in stress state. Then, Sgolay filter was selected in the pre-processing stage to remove artifacts in the signal. The process was followed by feature extraction of the ECG signal and finally classified using RR Interval (RRI), different amplitudes of R peaks and Cardioid graph were used to evaluate the performance of the proposed technique. As a result, Class 5 (age range between 50-59 years old) marks the highest changes of stress level rather than other classes, while women are more affected by stress rather than men by showing tremendous percentage changes between normal and stress level over the proposed classifiers. The result proves that ECG signals can be used as an alternative mechanism to recognize stress more efficiently with the integration of gender and age variabilities.
Volume: 15
Issue: 1
Page: 199-210
Publish at: 2019-07-01

An Important Landmarks Construction for a GIS-Map based on Indexing of Dolly Images

10.11591/ijeecs.v15.i1.pp451-459
Abdulkadhem Abdulkareem Abdulkadhem , Tawfiq A. Al-Assadi
In this paper, we describe the construction of important landmarks of roads in the GIS environment. The system uses the corners between more than two roads as an important landmarks. In this corner points will be saving a number of images, each one represents the movement direction between two segment roads. The objective of our work is to build the geo-database repository depend on the GIS (vector data) and multimedia (raster data) information. This paper considered as a preprocessing step for a roadmap discovery of video film when the input to the system is a dolly video film of roads with absence the GPS locations of frames video, and the output is the pathway (route) on the map inside the GIS environment. This work considered as a starting point for multimedia query inside the GIS environment. That’s mean when query the GIS system about a particular image or video, the GIS system must be able to know and determine the location of this image or video file on the map. Thus, the first step for doing this process needs to building and constructing an appropriate database for matching process later.
Volume: 15
Issue: 1
Page: 451-459
Publish at: 2019-07-01

Parking entrance control using license plate detection and recognition

10.11591/ijeecs.v15.i1.pp476-483
Mohamed Sayed Farag , Mostafa Mohamed Mohie El Din , Hassan Ahmed Elshenbary
There is no doubt that car parking is a very challenging and interesting topic of surveillance. In the recent years, a lot of smart systems for parking lot access control were developed to control and register the car data. The aim of this paper is to use image processing methods to control the entrance of a smart parking. The steps of car plate recognition are: preprocessing, License plate detection, character extraction and recognition. In the step of preprocessing, image was enhanced and noise was reduced. After preprocessing stage, color filter was used to detect the plate region. In case of large image size DWT was used for feature extraction and decreased the time of the detection stage. In the stage of character segmentation, the image is converted from grayscale to binary according to a given threshold. Filtering the binary image after using the morphological operation method, the largest objects are determined as the segmented plate characters. Finally, the correlation method was used to recognize the segmented characters. In case of similarity, SVM was used as a good classifier. Experimental results using matlab software, view that the proposed method increase the plate detection and recognition rates. It achieved aver- age 97.8% detection rate, 98% segmentation rate and 97% recognition rate, So it will be a good method for smart parking entrance control.
Volume: 15
Issue: 1
Page: 476-483
Publish at: 2019-07-01

Pipeline architectures of Three-dimensional daubechies wavelet transform using hybrid method

10.11591/ijeecs.v15.i1.pp240-246
Noor Huda Ja’afar , Afandi Ahmad
The application of three-dimensional (3-D) medical image compression systems uses several building blocks for its computationally intensive algorithms to perform matrix transformation operations. Complexity in addressing large medical volumes data has resulted in vast challenges from a hardware implementation perspective. This paper presents an approach towards very-large-scale-integration (VLSI) implementation of 3-D Daubechies wavelet transform for medical image compression. Discrete wavelet transform (DWT) algorithm is used to design the proposed architectures with pipelined direct mapping technique. Hybrid method use a combination of hardware description language (HDL) and G-code, where this method provides an advantage compared to traditional method. The proposed pipelined architectures are deployed for adaptive transformation process of medical image compression applications. The soft IP core design was targeted on to Xilinx field programmable gate array (FPGA) single board RIO (sbRIO 9632). Results obtained for 3-D DWT architecture using Daubechies 4-tap (Daub4) implementation exhibits promising results in terms of area, power consumption and maximum frequency compared to Daubechies 6-tap (Daub6).
Volume: 15
Issue: 1
Page: 240-246
Publish at: 2019-07-01

Improving bearings-only target state estimation tracking problem by using adaptive and nonlinear kalman algorithms

10.11591/ijeecs.v15.i1.pp190-198
Tammam Khadour , Michel Al Saba , Louay Saleh
Finding the best estimate of the process state from noisy data is the main problem in tracking systems, many efforts and researches have been done to remove this noise. More useful information about the target’s state can be extracted from observations by using a more appropriate model for the target’s motion or using additional sensors. In this paper, we will introduce two methods to improve the estimation of bearing-only target tracking problem in two dimensions (2D). The first method is by adding a third sensor and making a good alignment of those sensors, and at the same time an extended Kalman filter (EKF), unscented Kalman filter (UKF) and cubature Kalman filter (CKF) are implemented. The second method is by applying an adaptive nonlinear Kalman filter (ANKF) for two sensors to solve the problem of measurement variance uncertainty.
Volume: 15
Issue: 1
Page: 190-198
Publish at: 2019-07-01

Thermal analysis of a three-phase induction motor based on motor-CAD, flux2D, and matlab

10.11591/ijeecs.v15.i1.pp48-55
Afrah thamer Abdullah , Amer Mejbel Ali
This paper adopted a thermal network method (TNM) based on  Motor-CAD software, and Matlab/SIMULINK, with finite element method (FEM) based on Flux2D software to perform a thermal analysis of a totally enclosed fan-cooled (TEFC), squirrel cage, three-phase induction motor. The thermal analysis is achieved based on a precise knowledge of the test motor geometry, materials, and heat sources (losses). The estimation of heat distribution inside the test motor by this three software is done successfully with a good agreement between its results. The proposed triple-software methodology for this work can be adopted from the motor designer instead of using an experimental test based on a real motor.
Volume: 15
Issue: 1
Page: 48-55
Publish at: 2019-07-01

Indonesian sign language recognition using kinect and dynamic time warping

10.11591/ijeecs.v15.i1.pp495-503
Wijayanti Nurul Khotimah , Nanik Suciati , Tiara Anggita
Sign Language Recognition System (SLRS) is a system to recognise sign language and then translate them into text. This system can be developed by using a sensor-based technique. Some studies have implemented various feature extraction and classification methods to recognise sign language in the different country. However, their systems were user dependent (the accuracy was high when the trained and the tested user were the same people, but it was getting worse when the tested user was different to the trained user). Therefore in this study, we proposed a feature extraction method which is invariant to a user. We used the distance between two users’ skeleton instead of using the users’ skeleton positions because the skeleton distance is independent to the user posture. Finally, forty-five features were extracted in this proposed method. Further, we classified the features by using a classification method that is suitable with sign language gestures characteristic (time-dependent sequence data). The classification method is Dynamic Time Wrapping. For the experiment, we used twenty Indonesian sign languages from different semantic groups (greetings, questions, pronouns, places, family and others) and different gesture characteristic (static gesture and dynamic gesture). Then the system was tested by a different user with the user who did the training. The result was promising, this proposed method produced high accuracy, reach 91% which shows that this proposed method is user independent.
Volume: 15
Issue: 1
Page: 495-503
Publish at: 2019-07-01

Portable heart valve disease screening device using electronic stethoscope

10.11591/ijeecs.v15.i1.pp122-132
Mohd Zubir Suboh , Muhyi Yaakop , Mohd Azlan Abu , Mohd Syazwan Md Yid , Aizat Faiz Ramli , Mohd Yusoff Mashor , Abdul Rahman Mohd Saad , Mohd Shaiful Aziz Rashid Ali
Heart sound analysis has been a popular topic of studies since a few decades ago. Most of the studies are done in PC platform since embedding the complex algorithm into a simple small device such as microcontroller board seems to be very difficult due to limited processing speed and memory. This study classifies normal and abnormal heart sound signal from four categories of Heart Valve Disease. An automated system that consists of segmentation, feature extraction and classification of the heart sound signal is developed in PC and hardware platforms. A multimedia board completed with a single board computer, audio codec and graphic LCD is used to make a portable heart valve disease screening device with electronic stethoscope as the input for the system. Both system recorded 96.3% specificity. However, the portable device has only 77.78% sensitivity and 87.04% accuracy compared to PC platform that have sensitivity and accuracy of more than 90%.
Volume: 15
Issue: 1
Page: 122-132
Publish at: 2019-07-01

Protecting sensitive information utilizing an efficient association representative rule concealing algorithm for imbalance dataset

10.11591/ijeecs.v15.i1.pp527-534
Mylam Chinnappan Babu , Sankaralingam Pushpa
In data mining, discrimination is the detrimental behavior of the people which is extensively studied in human society and economical science. However, there are negative perceptions about the data mining. Discrimination has two categories; one is direct, and another is indirect. The decisions depend on sensitive information attributes are named as direct discrimination, and the decisions which depend on non-sensitive information attributes are called as indirect discrimination which is strongly related with biased sensitive ones. Privacy protection has become another one of the most important problems in data mining investigation.  To overcome the above issues, an Efficient Association Representative Rule Concealing (EARRC) algorithm is proposed to protect sensitive information or knowledge and offer privacy protection with the classification of the sensitive data. Representative rule concealing is one kind of the privacy-preserving mechanisms to hide sensitive association rules. The objective of this paper is to reduce the alternation of the original database and perceive that there is no sensitive association rule is obtained. The proposed method hides the sensitive information by altering the database without modifying the support of the sensitive item. The EARRC is a type of association classification approach which integrates the benefits of both associative classification and rule-based PART (Projective Adaptive Resonance Theory) classification. Based on Experimental computations, proposed EARRC+PART classifier improves 1.06 NMI and 5.66 Accuracy compared than existing methodologies.
Volume: 15
Issue: 1
Page: 527-534
Publish at: 2019-07-01

Design and implement of high gain and low noise neural amplifier using compensation techniques

10.11591/ijres.v8.i2.pp124-129
N. Manikandan , S. Muruganand , K. Karuppasamy
Electroencephalography is refer to record the electrical signal with respect to brain activity and its reliable EEG information, using this to diagnosis disorder and tumors. However the signal is very difficult to capture and processing due to so many parameter. Mainly this signal is very low range that from 0.1 to 100μv in and its bandwidth range from 1Hz to 100 Hz. So the signal has amplified by using linear and accurate digital program amplifier(PGA).This amplifier has been designed by using First stage amplifier with gain of 120dB with low output noise. The PGA is consists of OPAMPs the PGA change from 10 dB to 120dB.Inorde to optimized the linear and gain accuracy a new structure resister array is proposed high gain PGA. Hence the simulated result has shown it is promising to exhibit an amplifier with high performance biomedical application.
Volume: 8
Issue: 2
Page: 124-129
Publish at: 2019-07-01
Show 1273 of 1984

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration