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29,939 Article Results

An improved quasi-Newton equation on the quasi-Newton methods for unconstrained optimizations

10.11591/ijeecs.v22.i2.pp997-1005
Basim Abbas Hassan , Kanikar Muangchoo , Fadhil Alfarag , Abdulkarim Hassan Ibrahim , Auwal Bala Abubakar
Quasi-Newton methods are a class of numerical methods for solving the problem of unconstrained optimization. To improve the overall efficiency of resulting algorithms, we use the quasi-Newton methods which is interesting for quasi-Newton equation. In this manuscript, we present a modified BFGS update formula based on the new quasi-Newton equation, which give a new search direction for solving unconstrained optimizations proplems. We analyse the convergence rate of quasi-Newton method under some mild condition. Numerical experiments are conducted to demonstrate the efficiency of new methods using some test problems. The results indicates that the proposed method is competitive compared to the BFGS methods as it yielded fewer iteration and fewer function evaluations.
Volume: 22
Issue: 2
Page: 997-1005
Publish at: 2021-05-01

Self-diagnostic approach for cell counting biosensor

10.11591/ijeecs.v22.i2.pp688-698
Qais Al-Gayem , Hussain F. Jaafar , Saad S. Hreshee
In this research, a test monitoring strategy for an array of biosensors is proposed. The principle idea of this diagnostic technique is to measure and compare the impedance of each sensor in the array to achieve fully controlled online health monitoring technique at the system level. The work includes implementation of the diagnostic system, system architecture for analogue part, and SNR analysis. The technique has been applied on a cell coulter counting biochip where the design and fabrication of this sensing chip with electrodes make the coulter counter be an effective mean to count and analyses the cells in a blood sample. The experimental results show that the indication factor of the sensing electrodes has increased from 1 to 1.8 gradually depending on the fault level.
Volume: 22
Issue: 2
Page: 688-698
Publish at: 2021-05-01

A robust watermark algorithm for copyright protection by using 5-level DWT and two logos

10.11591/ijeecs.v22.i2.pp842-856
Alaa Rishek Hoshi , Nasharuddin Zainal , Mahamod Ismail , Abd Al-Razak T. Rahem , Salim Muhsin Wadi
Recent growth and development of internet and multimedia technologies have made it significant to upload data; however, in this situation, the protection of intellectual property rights has become a critical issue. Digital media, including videos, audios, and images are readily distributed, reproduced, and manipulated over these networks that will be lost copyright. Also, the development of various data manipulation tools like PDF converter and Photoshop Editor has resulted in digital data copyright issues. So, a digital watermarking technique has emerged as an efficient technique of protecting intellectual property rights by providing digital data copyright authentication and protection. In this technique, a watermarked document was integrated into electronic data to prevent unauthorized access. In this paper, A robust watermark algorithm based on a 5-level DWT and Two Log was proposed to enhance the copyright protection of images in unsecured media. Our lab results validate that our algorithm scheme is robust and forceful against several sets of attacks, and high quality watermarked image was achieved, where the algorithm was assessed by computation of many evaluation metrics such as PSNR, SNR, MAE, and RMSE.
Volume: 22
Issue: 2
Page: 842-856
Publish at: 2021-05-01

A comparative analysis on traditional wired datasets and the need for wireless datasets for IoT wireless intrusion detection

10.11591/ijeecs.v22.i2.pp1165-1176
Teh Boon Seong , Vasaki Ponnusamy , Noor Zaman Jhanjhi , Robithoh Annur , M N Talib
IoT networks mostly rely on wireless mediums for communication, and due to that, they are very susceptible to intrusions. And due to the tiny nature, processing complexity, and limited storage capacities, IoT networks require very reliable intrusion detection systems (IDS). Although there are many IDS types of research available in the literature, most of these systems are suitable for wired network environments, and the benchmark datasets used for these research works are mostly relying on wired datasets such as KDD Cup’99 and NSL-KDD. IoT and wireless networks are distinct in nature as wireless networks give more emphasis on the data link layer and physical layer. These concerns are not given much attention in traditional wired datasets in the body of knowledge. Therefore, in this research, an IDS system is developed using a newly available IoT wireless dataset (NaBIoT) in the literature with the datasets focusing much on the common IoT related attacks, and related layers are taken into consideration. The IDS system developed is evaluated by comparing with various machine learning algorithms in terms of evaluation metrics such as accuracy, F1 score, false positive, and false negative. Moreover, the IoT wireless dataset is compared against the traditional NSL-KDD datasets to evaluate the need for IoT wireless datasets. The NaBIoT datasets show its effectiveness in detecting wireless intrusions. Besides that, the simulation is performed with different combinations of features to conclude that certain features are primary in detecting attacks, and IDS does not require all the features to perform detection. This can reduce the detection time mainly for machine learning and creating the models. This research results have proposed some of the critically important features to be used and eliminating not such important features.   
Volume: 22
Issue: 2
Page: 1165-1176
Publish at: 2021-05-01

Connection status report generator

10.11591/ijeecs.v22.i2.pp1069-1077
Pratyush Gupta , Somnath Banerjee , Debani Prasad Mishra , Surender Reddy Salkuti
This paper presents “Connection Status Report Generator” which is an auto executable application and it generates a detailed textual and pictorial representation of the network connectivity status of a particular computer and sends the generated reports to the concerned party. The features developed in this paper aim to constantly monitor the network connectivity status as well as ease the troubleshooting process of finding the major cause of call-drops which is a popular problem in every industry. This paper is divided into three major sub-categories of real-time connection status tracker, report generator, and the image viewer interface. The proposed executable application is coded in Java and designed to run as a background application with minimal system prerequisites.
Volume: 22
Issue: 2
Page: 1069-1077
Publish at: 2021-05-01

A survey of distance learning in Morocco during COVID19

10.11591/ijeecs.v22.i2.pp1087-1095
Sara Ouahabi , Kamal El Guemmat , Mohamed Azouazi , Sanaa El Filali
The face-to-face mode is always considered as the normal mode of teaching, and distance education is often understood as a remedy for the lack of material and human resources necessary to conduct training; but to prevent the spread of the coronavirus (COVID19), the distance course system has been launched in different countries to ensure continuity of teaching during the period when courses are stopped. In order to shed light on the role of distance learning during the spread of the coronavirus and its effectiveness in successfully continuing the learning process, an investigation was carried out in the Moroccan context. This survey was launched as a questionnaire with 565 participants; they are students and teachers from primary, secondary, university and professional training. The objective is to answer several research questions concerning the current use of distance education during the COVID19 pandemic. The results of this survey are presented in this article as well as their analysis showing that solutions and alternatives must be adopted in order to improve the teaching and learning process in the event of a situation like COVID19.
Volume: 22
Issue: 2
Page: 1087-1095
Publish at: 2021-05-01

A smart wearable device based on internet of things for the safety of children in online transportation

10.11591/ijeecs.v22.i2.pp708-716
Elsyea Adia Tunggadewi , Eva Inaiyah Agustin , Riky Tri Yunardi
The world needs to pay attention to children who often become victims of violence and cannot escape social problems. Various safety devices that are commonly known as smart wearable devices have been created, but they still have many shortcomings. Thus, in this research a safety device that can be held by children is designed and is equipped with a button that can be pressed, then it will automatically send the location and photo of the scene to the parent's cellphone via the telegram application. It uses the Raspberry Pi Zero W controller, the GNSS HMC5983 SAW LNA GPS Module to determine the location, and the 5MP Raspberry Pi Zero Camera Module to capture the incident. Based on the results, the average time needed to share locations is 0.91 seconds, and the average time needed to capture is 11.57 seconds, if the device and receiving cellphone use the same network. Additionally, the average time needed to share locations is 0.96 seconds, and the average time needed to capture is 12.09 seconds, if the device and receiving cellphone use a different network. Both conditions have 97.5% location accuracy rate and 100% photo accuracy rate.
Volume: 22
Issue: 2
Page: 708-716
Publish at: 2021-05-01

ArSL-CNN a convolutional neural network for Arabic sign language gesture recognition

10.11591/ijeecs.v22.i2.pp1096-1107
Ali A. Alani , Georgina Cosma
Sign language (SL) is a visual language means of communication for people who are Deaf or have hearing impairments. In Arabic-speaking countries, there are many Arabic sign languages (ArSL) and these use the same alphabets. This study proposes ArSL-CNN, a deep learning model that is based on a convolutional neural network (CNN) for translating Arabic SL (ArSL). Experiments were performed using a large ArSL dataset (ArSL2018) that contains 54049 images of 32 sign language gestures, collected from forty participants. The results of the first experiments with the ArSL-CNN model returned a train and test accuracy of 98.80% and 96.59%, respectively. The results also revealed the impact of imbalanced data on model accuracy. For the second set of experiments, various re-sampling methods were applied to the dataset. Results revealed that applying the synthetic minority oversampling technique (SMOTE) improved the overall test accuracy from 96.59% to 97.29%, yielding a statistically signicant improvement in test accuracy (p=0.016,  α<0=05). The proposed ArSL-CNN model can be trained on a variety of Arabic sign languages and reduce the communication barriers encountered by Deaf communities in Arabic-speaking countries.
Volume: 22
Issue: 2
Page: 1096-1107
Publish at: 2021-05-01

Design of gas concentration measurement and monitoring system for biogas power plant

10.11591/ijeecs.v22.i2.pp726-732
Iswanto Iswanto , Alfian Ma’arif , Bilah Kebenaran , Prisma Megantoro
Biogas is a gas obtained from the breakdown of organic matter (such as animal waste, human waste, and plants) by methanogenic bacteria in an oxygen-free (anaerobic) state. The biogas produced mainly consists of 50-70% methane, 30-40% carbon dioxide, and other gases in small amounts. The gas produced has a different composition depending on the type of animal that produces it. It is challenging to obtain biogas concentration data because the monitoring equipment is currently minimal. Therefore, this research discusses how to make a monitoring system for biogas reactors. Sensors are installed in the digester tank and storage tank. The installed sensors are the MQ-4 sensor to detect methane gas (CH4), MG-811 sensor to detect carbon dioxide (CO2) gas, MQ-136 sensor to detect sulfide acid gas (H2S), and Thermocouple Type-K to detect temperature. The sensor will send a signal to the control unit in Arduino Mega 2560, then processed and displayed on the liquid crystal display (LCD). The sensor calculation results' accuracy is not much different from the reference based on the sensor readings. The sensor deviation standard is below 5.0, indicating that the sensor is in precision. The sensor's linearity of MQ-4 is 0.7%, the MG-811 is 0.17%, the MQ-136 is 0.29%, and the Type-K Thermocouple is 1.19%. The installed sensor can be used to monitor gas concentration and temperature in a biogas reactor.
Volume: 22
Issue: 2
Page: 726-732
Publish at: 2021-05-01

A comparative study of deep learning based language representation learning models

10.11591/ijeecs.v22.i2.pp1032-1040
Mohammed Boukabous , Mostafa Azizi
Deep learning (DL) approaches use various processing layers to learn hierarchical representations of data. Recently, many methods and designs of natural language processing (NLP) models have shown significant development, especially in text mining and analysis. For learning vector-space representations of text, there are famous models like Word2vec, GloVe, and fastText. In fact, NLP took a big step forward when BERT and recently GTP-3 came out. In this paper, we highlight the most important language representation learning models in NLP and provide an insight of their evolution. We also summarize, compare and contrast these different models on sentiment analysis, and thus discuss their main strengths and limitations. Our obtained results show that BERT is the best language representation learning model.
Volume: 22
Issue: 2
Page: 1032-1040
Publish at: 2021-05-01

Software aging prediction and rejuvenation in cloud computing environment: a new approach

10.11591/ijeecs.v22.i2.pp1006-1012
Shruthi P , Nagaraj G Cholli
Service availability is one of the major requirements for user satisfaction. Several researches were conducted in recent years to find suitable infrastructure to enhance the availability. Even though both hardware and software are to be in good condition, in recent years, software faults are the major concern for service availability. Software aging is a type of software fault. Software aging occurs as a result of errors accumulation in the internal environment of the system leading to performance degradation. To manage software aging, technique used is software rejuvenation. There exist two kinds of approaches for studying software aging and deriving optimal software rejuvenation schedules. The two approaches are measurement based and model based. In model based approach, analytic models are built for capturing system degradation and rejuvenation process. In measurement based approach, attributes are periodically monitored and that may indicate signs of software aging. In this work, a prototype of measurement based model has been developed. The model captures the aging indicator metrics from cloud environment and rejuvenates once the system reaches aged status. The proposed model uses platform independent, non-intrusive technique for capturing metrics. The rejuvenation carried out after analysing the captured metrics, increases the availability of the service.
Volume: 22
Issue: 2
Page: 1006-1012
Publish at: 2021-05-01

On active anti-islanding techniques: survey

10.11591/ijeecs.v22.i2.pp609-618
Yasser Ahmed Elshrief , Sameh Abd-Elhaleem , Belal Abo Zalam , Amin D. Asham
The phenomenon of feeding loads from any distributed generators (DGs) with a total disconnection of utility grid at the point of common coupling is called Islanding. The DGs are usually independently controlled. Hence, when the islanding problem occurs, the electric utility loses the control and supervision over that section of the power grid. Furthermore, prolonged islanding can prevent reconnection to the power grid and may cause damage due to voltage and frequency excursions. Therefore, the islanding detection, which is also called anti-islanding (AI), is one of the most critical aspects of the integration of DG sources into the power grid. In this paper, a comprehensive survey on the local AI techniques is illustrated, especially active type which is used for improving the performance regarding the size of the non-detection zone and detection speed. Extensive comparisons are provided to demonstrate the effectiveness of each technique.
Volume: 22
Issue: 2
Page: 609-618
Publish at: 2021-05-01

Network analysis of Youtube videos based on keyword search with graph centrality approach

10.11591/ijeecs.v22.i2.pp780-786
Edi Surya Negara , Ria Andryani , Riyan Amanda
Youtube is a social media that has billions of users, with this can be used as a promotional media, trends, business, and so forth. This study aims to analyze the correlation between Youtube videos by utilizing hashtags on video using graph theory. Data collection in this study uses scraping techniques taken from the Youtube website in the form of links, titles, keywords, and hashtags. The method used in this research is Social Network Analysis, the measurements used in this study are degree centrality and betweenness centrality. The results of this study indicate that the most popular hashtags with the keyword search for "viruses" are #KidflixPT, #Portugues, and #Mondo with degree centrality values equal to 0.071875. and the correlation between the most closely related videos about #Coronavirus with a value of betweenness centrality of 0.082626.
Volume: 22
Issue: 2
Page: 780-786
Publish at: 2021-05-01

Autonomous path planning through application of rotated two-parameter overrelaxation 9-point Laplacian iteration technique

10.11591/ijeecs.v22.i2.pp1116-1123
W. K. Ling , A'Qilah Ahmad Dahalan , Azali Saudi
Autonomous path navigation is one of the important studies in robotics since a robot’s ability to navigate through an environment brings about many advancements with it. This paper suggests the iteration technique called half-sweep two parameter overrelaxation 9-point laplacian (HSTOR-9P) to be applied on autonomous path navigation and aims to investigate its effectiveness in performing computation for path planning in an indoor static environment. This iteration technique is a harmonic function that solves the Laplace’s equation where the modelling of the environment is based on. The harmonic functions are an appropriate method to be used on autonomous path planning because it satisfies the min-max principle, therefore avoiding the occurrence of local minima which traps robot’s movements, and that it offers complete path planning algorithm. Its performance is tested against its predecessor iteration technique. Results shown that HSTOR-9P iteration technique enables path construction in a lower number of iterations, thus, performs better than its predecessors.
Volume: 22
Issue: 2
Page: 1116-1123
Publish at: 2021-05-01

A review of codebook design methods for sparse code multiple access

10.11591/ijeecs.v22.i2.pp927-935
Syed Aamer Hussain , Norulhusna Ahmad , Ibraheem Shayea , Hazilah Mad Kaidi , Liza Abdul Latiff , Norliza Mohamed , Suriani Mohd Sam
The progressions in telecommunication beyond the 5th generation have created a need to improve research drifts. The current 5G study has an important focus on non-orthogonal multiple access (NOMA) technology. sparse code multiple access (SCMA) is a promising technique within NOMA, enhancing the multi-user handling capability of next-generation communication. In the SCMA sphere, codebook designing and optimisation are essential research matters. This study conversed with different codebook design practises existing in the literature, analysing them for numerous parameters, including bit error rate (BER), an optimisation technique, and channel settings. From the analysis, the paper presents the efficiency of different approaches. The article also discusses the prospects and challenges of SCMA optimisation in practical implementation in various domains.
Volume: 22
Issue: 2
Page: 927-935
Publish at: 2021-05-01
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