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Performance evaluation of hierarchical clustering protocols with fuzzy C-means

10.11591/ijece.v11i4.pp3212-3221
Hamid Barkouk , El Mokhtar En-Naimi , Aziz Mahboub
The longevity of the network and the lack of resources are the main problems within the WSN. Minimizing energy dissipation and optimizing the lifespan of the WSN network are real challenges in the design of WSN routing protocols. Load balanced clustering increases the reliability of the system and enhances coordination between different nodes within the network. WSN is one of the main technologies dedicated to the detection, sensing, and monitoring of physical phenomena of the environment. For illustration, detection, and measurement of vibration, pressure, temperature, and sound. The WSN can be integrated into many domains, like street parking systems, smart roads, and industrial. This paper examines the efficiency of our two proposed clustering algorithms: Fuzzy C-means based hierarchical routing approach for homogeneous WSN (F-LEACH) and fuzzy distributed energy efficient clustering algorithm (F-DEEC) through a detailed comparison of WSN performance parameters such as the instability and stability duration, lifetime of the network, number of cluster heads per round and the number of alive nodes. The fuzzy C-means based on hierarchical routing approach is based on fuzzy C-means and low-energy adaptive clustering hierarchy (LEACH) protocol. The fuzzy distributed energy efficient clustering algorithm is based on fuzzy C-means and design of a distributed energy efficient clustering (DEEC) protocol. The technical capability of each protocol is measured according to the studied parameters.
Volume: 11
Issue: 4
Page: 3212-3221
Publish at: 2021-08-01

VANET-Based Traffic Monitoring and Incident Detection System: A Review

10.11591/ijece.v11i4.pp3193-3200
Mustafa Maad Hamdi , Lukman Audah , Sami Abduljabbar Rashid , Sameer Alani
As a component of intelligent transport systems (ITS), vehicular ad hoc network (VANET), which is a subform of manet, has been identified. It is established on the roads based on available vehicles and supporting road infrastructure, such as base stations. An accident can be defined as any activity in the environment that may be harmful to human life or dangerous to human life. In terms of early detection, and broadcast delay. VANET has shown various problems. The available technologies for incident detection and the corresponding algorithms for processing. The present problem and challenges of incident detection in VANET technology are discussed in this paper. The paper also reviews the recently proposed methods for early incident techniques and studies them.
Volume: 11
Issue: 4
Page: 3193-3200
Publish at: 2021-08-01

The future of software engineering: Visions of 2025 and beyond

10.11591/ijece.v11i4.pp3443-3450
Firoz Khan , R. Lakshmana Kumar , Seifedine Kadry , Yunyoung Nam
In the current technological scenario of the industry and businesses, there has been increasing need of software within systems and also an increasing demand being put onto software-intensive systems. This in effect will lead to a significant evolution of software engineering processes over the next twenty years. This is due to the fact of emerging technological advancements like Industry 4.0 and Internet of Things in the IT field, among other new developments. This paper addresses and tries to analyses the key research challenges being faced by the software engineering field and articulates information that is derived from the key research specializations within software engineering. The paper analyses the past and current trends in software engineering. The future of software engineering is also looked with respect to Industry 4.0 which including emerging technological platforms like Internet of Things. The societal impact aspect of future trends in software engineering is also addressed in this paper.
Volume: 11
Issue: 4
Page: 3443-3450
Publish at: 2021-08-01

A transfer learning with deep neural network approach for diabetic retinopathy classification

10.11591/ijece.v11i4.pp3492-3501
Mohammed Al-Smadi , Mahmoud Hammad , Qanita Bani Baker , Sa’ad A. Al-Zboon
Diabetic retinopathy is an eye disease caused by high blood sugar and pressure which damages the blood vessels in the eye. Diabetic retinopathy is the root cause of more than 1% of the blindness worldwide. Early detection of this disease is crucial as it prevents it from progressing to a more severe level. However, the current machine learning-based approaches for detecting the severity level of diabetic retinopathy are either, i) rely on manually extracting features which makes an approach unpractical, or ii) trained on small dataset thus cannot be generalized. In this study, we propose a transfer learning-based approach for detecting the severity level of the diabetic retinopathy with high accuracy. Our model is a deep learning model based on global average pooling (GAP) technique with various pre-trained convolutional neural net- work (CNN) models. The experimental results of our approach, in which our best model achieved 82.4% quadratic weighted kappa (QWK), corroborate the ability of our model to detect the severity level of diabetic retinopathy efficiently.
Volume: 11
Issue: 4
Page: 3492-3501
Publish at: 2021-08-01

Potential key challenges for terahertz communication systems

10.11591/ijece.v11i4.pp3403-3409
Ahmad A. A. Solyman , Ismail A. Elhaty
The vision of 6G communications is an improved performance of the data rate and latency limitations and permit ubiquitous connectivity. In addition, 6G communications will adopt a novel strategy. Terahertz (THz) waves will characterize 6G networks, due to 6G will integrate terrestrial wireless mobile communication, geostationary and medium and low orbit satellite communication and short distance direct communication technologies, as well as integrate communication, computing, and navigation. This study discusses the key challenges of THz waves, including path losses which is considered the main challenge; transceiver architectures and THz signal generators; environment of THz with network architecture and 3D communications; finally, Safety and health issues.
Volume: 11
Issue: 4
Page: 3403-3409
Publish at: 2021-08-01

Image encryption under spatial domain based on modify 2D LSCM chaotic map via dynamic substitution-permutation network

10.11591/ijece.v11i4.pp3070-3083
Rana Saad Mohammed , Khalid Kadhim Jabbar , Hussien Abid Hilal
Image encryption has become an important application aspect of information security. Most attempts are focused on increasing the security aspect, the quality of the resulting image, and the time consumed. On the other hand, dealing with the color image under the spatial domain in this filed is considered as another challenge added to the proposed method that make it sensitivity and difficulty. The proposed method aims to encode a color image by dealing with the main color components of the red (R), green (G), and blue (B) components of a color image to strengthen the dependence of each component by modifying a two dimensional logistic- sine coupling map (2D- LSCM). This is to satisfy the statistical features and reduce time-consumption, and benefit from a mixing step of the second of advanced encryption standard (AES) candidates (serpent block cipher) and modified it to achieve in addition of confusion and diffusion processes. The experimental results showed that our proposed method had the ability to resist against statistical attacks and differential attacks. It also had a uniform histogram, a large key space, complex and faster, closer Shannon entropy to 8, and low correlation values between two adjacent pixels compared with other methods.
Volume: 11
Issue: 4
Page: 3070-3083
Publish at: 2021-08-01

AlGaInP optical source integrated with fiber links and silicon avalanche photo detectors in fiber optic systems

10.11591/ijeecs.v23.i2.pp847-854
Mahmoud M. A. Eid , Shabana Urooj , Norah Muhammad Alwadai , Ahmed Nabih Zaki Rashed
This study has clarified aluminium gallium indium phosphide (AlGaInP) optical source integrated with fiber links and silicon avalanche photodetectors in fiber optic systems. The output spectral power, rise time, signal frequency and resonance frequency for AlGaInP laser diode. The laser diode rise time, output spectral power and resonance/signal frequencies versus injection current and ambient temperatures are sketched. The silica doped germanium fiber link pulse broadening and the signal fiber bandwidth are investigated against temperature variations. The signal per noise ratio is related to Q value and bit error rate (BER) at the receiving point (Si avalanche photodetector (APD)) are sketched with temperature.
Volume: 23
Issue: 2
Page: 847-854
Publish at: 2021-08-01

Reactive power sharing in microgrid using virtual voltage

10.11591/ijece.v11i4.pp2743-2751
Eder A. Molina-Viloria , John E. Candelo Becerra , Fredy E. Hoyos Velasco
The traditional droop control strategy has been applied previously in microgrids (MGs) to share accurately the active power. However, in some cases the result obtained when sharing reactive power is not the best, because of the parameters related to the distances from distributed generators (DGs) to the loads and the power variations. Therefore, this paper proposes a reactive power control strategy for a low voltage MG, where the unequal impedance related to the distances between generators and loads requires adjustments to work with the conventional frequency and voltage droop methods. Thus, an additional coefficient is calculated from parameters of the network that relate the location of elements. The test is perfomed by simulations in the MATLAB-Simulink software, considering a three-node MG with three DGs and a load that can change power at different periods of time. The results show that it is possible to improve reactive power sharing between the DGs located in the MG according to the load changes simulated and to improve voltages with this method.
Volume: 11
Issue: 4
Page: 2743-2751
Publish at: 2021-08-01

Numerical investigation on the behavior of combining open-channel flow

10.11591/ijeecs.v23.i2.pp1110-1119
Nor Azni Shahari , Nor Arif Husaini Norwaza , Iskandar Shah Mohd Zawawi , Nurisha Adrina Mohd Kamarul , Aimi Said
Open-channel flow is known as fluid flow with an open atmospheric surface. It has become an important issue especially when measuring the flow rate and depth of water as part of environmental management schemes. Many efforts have been made by the previous researchers to investigate the behavior of water flow. However, most studies on water flow have only been carried out in a straight prismatic main channel, either in a trapezoidal and rectangular type of channel section with lateral branch of angle of 90o. In this study, the general equations of combining open-channel flow for trapezoidal and V-shaped channels are modified in the form of nonlinear polynomial equations. The proposed equations are solved using Newton-Raphson procedure to determine the upstream flow depth. All the computations and analysis of the behavior of water flow depth influenced by Froude number and flow rate ratio are performed using graphical user interface, which is designed in MATLAB software. Comparative analysis shows that the modified equations agree well with the experimental data as reported in the literature. The trapezoidal channel demonstrates the highest value of flow depth as the Froude number and flow rate ratio increase; thus, it has potential to avoid water overflow.
Volume: 23
Issue: 2
Page: 1110-1119
Publish at: 2021-08-01

A self adaptive new crossover operator to improve the efficiency of the genetic algorithm to find the shortest path

10.11591/ijeecs.v23.i2.pp1011-1017
Mrinmoyee Chattoraj , Udaya Rani Vinayakamurthy
Route planning is an important part of road network. To select an optimized route several factors such as flow of traffic, speed limits of road. are concerned. Total cost of such a network depends on the number of junctions between the source and the destination. Due to the growth of the nodes in the network it becomes a tough job to determine the exact path using deterministic algorithms so in such cases genetic algorithms (GA) plays a vital role to find the optimized route. Crossover is an important operator ingenetic algorithm. The efficiency of thegenetic algorithmis directlyinfluenced by the time of a crossover operation. In this paper a new crossoveroperator closest-node pairing crossover (CNPC) is recommended which is explicitly designed to improve the performance of the genetic algorithm compared to other well-known crossover operators such as point based crossover and order crossover. The distance aspect of the network problem has been exploited in this crossover operator. This proposed technique gives a better result compared to the other crossover operator with the fitness value of 0.0048. The CNPC operator gives better rate of convergence compared to the other crossover operators.
Volume: 23
Issue: 2
Page: 1011-1017
Publish at: 2021-08-01

Using deep learning models for learning semantic text similarity of Arabic questions

10.11591/ijece.v11i4.pp3519-3528
Mahmoud Hammad , Mohammed Al-Smadi , Qanita Bani Baker , Sa’ad A. Al-Zboon
Question-answering platforms serve millions of users seeking knowledge and solutions for their daily life problems. However, many knowledge seekers are facing the challenge to find the right answer among similar answered questions and writer’s responding to asked questions feel like they need to repeat answers many times for similar questions. This research aims at tackling the problem of learning the semantic text similarity among different asked questions by using deep learning. Three models are implemented to address the aforementioned problem: i) a supervised-machine learning model using XGBoost trained with pre-defined features, ii) an adapted Siamese-based deep learning recurrent architecture trained with pre-defined features, and iii) a Pre-trained deep bidirectional transformer based on BERT model. Proposed models were evaluated using a reference Arabic dataset from the mawdoo3.com company. Evaluation results show that the BERT-based model outperforms the other two models with an F1=92.99%, whereas the Siamese-based model comes in the second place with F1=89.048%, and finally, the XGBoost as a baseline model achieved the lowest result of F1=86.086%.
Volume: 11
Issue: 4
Page: 3519-3528
Publish at: 2021-08-01

Increasing life-time of wireless sensor network using energy-efficient and fault tolerance algorithms

10.11591/ijeecs.v23.i2.pp1093-1099
Sama Hussam Sabah , Muayad Sadik Croock
Energy-efficiency ofwireless sensor networks (WSN) becomes an essential issue in the research area. This is because of the energy constraints in WSN that depend on a battery, which is difficult to replace or recharge; therefore, multiple clustering algorithms were proposed to achieve efficiency in using the available energy as much as possible. This paper proposed energy-efficient and fault-tolerance algorithms that enhance thelow energy adaptive clustering hierarchy (LEACH) protocol by three algorithms. The first focuses on selecting the best cluster head and the second focuses on minimizing the required nodes within the same cluster. Simultaneously, the third fault tolerance algorithm uses software engineering techniques like sleep schedules to increase network lifetime as much as possible. The testing results of the proposed algorithms prove the claim of enhancing the lifetime of WSN. In order to check improvement of lifetime of WSN we have compered the results of the proposed algorithms with standered algorthim. The results show prove the claim of enhancing the life-time of WSN, where the total lifetime of WSN rise from about 550 rounds to reach 4100 when utilized self-checking process and rised up to 5200 after enhance minimum distans.
Volume: 23
Issue: 2
Page: 1093-1099
Publish at: 2021-08-01

Bayesian learning scheme for sparse DOA estimation based on maximum-a-posteriori of hyperparameters

10.11591/ijece.v11i4.pp3049-3058
Raghu K. , Prameela Kumari N.
In this paper, the problem of direction of arrival estimation is addressed by employing Bayesian learning technique in sparse domain. This paper deals with the inference of sparse Bayesian learning (SBL) for both single measurement vector (SMV) and multiple measurement vector (MMV) and its applicability to estimate the arriving signal’s direction at the receiving antenna array; particularly considered to be a uniform linear array. We also derive the hyperparameter updating equations by maximizing the posterior of hyperparameters and exhibit the results for nonzero hyperprior scalars. The results presented in this paper, shows that the resolution and speed of the proposed algorithm is comparatively improved with almost zero failure rate and minimum mean square error of signal’s direction estimate.
Volume: 11
Issue: 4
Page: 3049-3058
Publish at: 2021-08-01

Inter-cell interference mitigation using adaptive reduced power subframes in heterogeneous networks

10.11591/ijece.v11i4.pp3275-3284
Mohammed I. Aal-nouman , Osamah Abdullah , Noor Qusay A. Al Shaikhli
With the remarkable impact and fast growth of the mobile networks, the mobile base stations have been increased too, especially in the high population areas. These base stations will be overloaded by users, for that reason the small cells (like pico cells) were introduced. However, the inter-cell interference will be high in this type of Heterogeneous networks. There are many solutions to mitigate this interference like the inter-cell interference coordination (ICIC), and then the further enhanced ICIC (Fe-ICIC) where the almost blank subframes are used to give priority to the (victim users). But it could be a waste of bandwidth due to the unused subframes. For that reason, in this paper, we proposed an adaptive reduced power subframe that reduces its power ratio according to the user’s signal-to-interference-plus-noise ratio (SINR) in order to get a better throughput and to mitigate the intercell interference. When the user is far from the cell, the case will be considered as an edge user and will get a higher priority to be served first. The results show that the throughput of all users in the macro cells and pico cell will be improved when applying the proposed scheme in term of throughput for the users and the cells.
Volume: 11
Issue: 4
Page: 3275-3284
Publish at: 2021-08-01

Evaluation of a wireless low-energy mote with fuzzy algorithms and neural networks for remote environmental monitoring

10.11591/ijeecs.v23.i2.pp717-724
Ricardo Yauri , Jinmi Lezama , Milton Rios
The devices developed for applications in the internet of things have evolved technologically in the improvement of hardware and software components, in the area of optimization of the life time and to increase the capacity to save energy. This paper shows the development of a fuzzy logic algorithm and a power propagation neural network algorithm in a wireless mote (IoT end device). The fuzzy algorithm changes the transmission frequency according to the battery voltage and solar cell voltage. Moreover,the implementation of algorithms based on neural networks, implied a challenge in the evaluation and study of the energy commitment for the implementation of the algorithm, memory space optimization and low energy consumption.
Volume: 23
Issue: 2
Page: 717-724
Publish at: 2021-08-01
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