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29,939 Article Results

Improving traffic and emergency vehicle clearence at congested intersections using fuzzy inference engine

10.11591/ijece.v11i4.pp3176-3185
Aditi Agrawal , Rajeev Paulus
Traffic signals play an important role in controlling and coordinating the traffic movement in cities especially in urban areas. As the traffic is exponentially increasing in cities and the pre-timed traffic light control is insufficient in effective timing of the traffic lights, it leads to poor traffic clearance and ultimately to heavy traffic congestion at intersections. Even the Emergency vehicles like Ambulance and Fire brigade are struck at such intersections and experience a prolonged waiting time. An adaptive and intelligent approach in design of traffic light signals is desirable and this paper contributes in applying fuzzy logic to control traffic signal of single four-way intersection giving priority to the Emergency vehicle clearance. The proposed control system is composed of two parallel controllers to select the appropriate lane for green signal and also to decide the appropriate green light time as per the real time traffic condition. Performance of the proposed system is evaluated by using simulations and comparing with pre-timed control system in changing traffic flow condition. Simulation results show significant improvement over the pre-timed control in terms of traffic clearance and lowering of Emergency vehicle wait time at the intersection especially when traffic intensity is high.
Volume: 11
Issue: 4
Page: 3176-3185
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

Privacy preserving association rule hiding using border based approach

10.11591/ijeecs.v23.i2.pp1137-1145
Suma B. , Shobha G.
Association rule mining is a well-known data mining technique used for extracting hidden correlations between data items in large databases. In the majority of the situations, data mining results contain sensitive information about individuals and publishing such data will violate individual secrecy. The challenge of association rule mining is to preserve the confidentiality of sensitive rules when releasing the database to external parties. The association rule hiding technique conceals the knowledge extracted by the sensitive association rules by modifying the database. In this paper, we introduce a border-based algorithm for hiding sensitive association rules. The main purpose of this approach is to conceal the sensitive rule set while maintaining the utility of the database and association rule mining results at the highest level. The performance of the algorithm in terms of the side effects is demonstrated using experiments conducted on two real datasets. The results show that the information loss is minimized without sacrificing the accuracy. 
Volume: 23
Issue: 2
Page: 1137-1145
Publish at: 2021-08-01

Cyber physical systems: A smart city perspective

10.11591/ijece.v11i4.pp3609-3616
Firoz Khan , R. Lakshmana Kumar , Seifedine Kadry , Yunyoung Nam , Maytham N. Meqdad
Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed.
Volume: 11
Issue: 4
Page: 3609-3616
Publish at: 2021-08-01

A fully integrated violence detection system using CNN and LSTM

10.11591/ijece.v11i4.pp3374-3380
Sarthak Sharma , B. Sudharsan , Saamaja Naraharisetti , Vimarsh Trehan , Kayalvizhi Jayavel
Recently, the number of violence-related cases in places such as remote roads, pathways, shopping malls, elevators, sports stadiums, and liquor shops, has increased drastically which are unfortunately discovered only after it’s too late. The aim is to create a complete system that can perform real-time video analysis which will help recognize the presence of any violent activities and notify the same to the concerned authority, such as the police department of the corresponding area. Using the deep learning networks CNN and LSTM along with a well-defined system architecture, we have achieved an efficient solution that can be used for real-time analysis of video footage so that the concerned authority can monitor the situation through a mobile application that can notify about an occurrence of a violent event immediately.
Volume: 11
Issue: 4
Page: 3374-3380
Publish at: 2021-08-01

Data security using random dynamic salting and AES based on master-slave keys for Iraqi dam management system

10.11591/ijeecs.v23.i2.pp1018-1029
Hussam J. Ali , Talib M. Jawad , Hiba Zuhair
In the present time, dam management is considered one of the important challenges for e-government in Iraq, becuase it needs information technology infrastructure, data integrity and protection of user privacy against Internet threats that render such vital infrastructure ineffective. This struggle between the proposed dam management system (DMS) and a multi-tier secure model specifically for the Fallujah dam (and generally for all dams) which is addressed in this paper as a case study. To do this, a relational database design will discuss the development of a multi-tier secure model for integration of the dam management framework with its functions. This paper will discusse encryption and decryption of the dam data using the advanced encryption standard (AES) algorithm with derived keys via PBKDF2 and RNG sequences generator and Slave key for salting protection. The experimental results and analysis on the speed of encryption/decryption process, entropy value, plain text sensitivity, key sensitivity, keyspaceanalysis and histogram analysis will prove the the proposed scheme can impede the known attacks like brute force attacks, statistical and differential.Thus, the encryption scheme can be implemented on the proposed DMS and any other information system, as the implementation which will be presented in the results.
Volume: 23
Issue: 2
Page: 1018-1029
Publish at: 2021-08-01

Smart element aware gate controller for intelligent wheeled robot navigation

10.11591/ijece.v11i4.pp3022-3031
Nadia Adnan Shiltagh Al-Jamali , Mahmood Z. Abdullah
The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.
Volume: 11
Issue: 4
Page: 3022-3031
Publish at: 2021-08-01

A dynamic model of electronic wedge brake: experimental, control and optimization

10.11591/ijeecs.v23.i2.pp740-751
Mohd Hanif Che Hasan , Mohd Khair Hassan , Fauzi Ahmad , Mohammad Hamiruce Marhaban , Sharil Izwan Haris
This paper discusses the process of modelling and parameter selection for the creation of the electronic wedge brake system (EWB). The system involves a permanent magnet DC engine (PMDC) that drives the motor, the gear leadscrew and the brake core. The proposed model is simpler and more flexible which can be used in both the most well-known EWB designs either natural or optimized EWB. The selection of the motor is rendered according to the brake specifications. The wedge angle profile is centred on the derivation of EWB system that consists of brake actuator, wedge mechanism dynamic and wedge characteristic brake factor. Control and optimization are carried out with specific coefficients of friction of the brake pads to maintain operating reliability. A 5th-order brake simulation model of the EWB in a single state-space was derived and a simulation was conducted to verify the distribution of force. The efficiency of the brake clamping force control system was assessed by proportional-integral-derivative (PID) control. The performance of the proposed controller is verified in simulations and experiments using a prototype electronic wedge brake. The research findings indicate, the actuator restriction is deemed to achieve consistent performance against full range braking during the EWB control design.
Volume: 23
Issue: 2
Page: 740-751
Publish at: 2021-08-01

Automated data monitoring of MEMS cleanroom parametric requirements

10.11591/ijeecs.v23.i2.pp701-708
Jean M. Capanang , Jobelle P. Panganiban , Glenn N. Ortiz , Mark Joseph B. Enojas
Cleanroom parameters such as temperature, relative humidity and particle count are vital in maintaining cleanliness. People and machines working inside the cleanroom are main contributors for the sudden changes of the separameters. Measurements and monitoring of these parameters are therefore necessary to reduce rejects and downtime in the production of micro-electro-mechanical systems (MEMS). This paper presents a method of developmentof an automated data monitoring of MEMS cleanroom parametric requirements. The prototype developed uses DHT11 sensor and Sharp dust sensor for measuring the temperature, humidity and particle count respectively which are displayed in an LCD display. These parameters are recorded through a data logger for analysis and control. Additionally, agraphical user interface was also developed using visual studio for the working personnel and for supervisory monitoring and control. As a result, the possible quality compromise in the production of MEMS is detected when the monitored parameters are beyond the range.
Volume: 23
Issue: 2
Page: 701-708
Publish at: 2021-08-01

Implementation of SHE-PWM technique for single-phase inverter based on Arduino

10.11591/ijece.v11i4.pp2907-2915
Laith A. Mohammed , Taha A. Husain , Ahmed M. T. Ibraheem
This paper presents design and practical implementation of single-phase inverter based on selective harmonic elimination-pulse width modulation (SHE-PWM) technique. Microcontroller mega type Arduino used as a controller for producing the gate pulses. The optimized switching angles determination results in wide range of output voltage. Depending on number of switching angles, the lower order harmonics (LOHs) can be eliminated to improve the output voltage waveform. A comparison study using MATLAB/Simulink for sinusoidal-PWM and SHE-PWM techniques, which shows for the same LOH in the output voltage waveform, the SHE-PWM has less number of pulses per half cycle than sinusoidal-PWM strategy. The reduction in number of pulses results less switching losses. The simulation done using ten switching angles to drive R-L load. A prototype of SHE-PWM inverter with R-L load is used to validate the simulation results.
Volume: 11
Issue: 4
Page: 2907-2915
Publish at: 2021-08-01

Prediction of nodes mobility in 3-D space

10.11591/ijece.v11i4.pp3229-3240
Mohammad Al-Hattab , Nuha Hamada
Recently, mobility prediction researches attracted increasing interests, especially for mobile networks where nodes are free to move in the three-dimensional space. Accurate mobility prediction leads to an efficient data delivery for real time applications and enables the network to plan for future tasks such as route planning and data transmission in an adequate time and a suitable space. In this paper, we proposed, tested and validated an algorithm that predicts the future mobility of mobile networks in three-dimensional space. The prediction technique uses polynomial regression to model the spatial relation of a set of points along the mobile node’s path and then provides a time-space mapping for each of the three components of the node’s location coordinates along the trajectory of the node. The proposed algorithm was tested and validated in MATLAB simulation platform using real and computer generated location data. The algorithm achieved an accurate mobility prediction with minimal error and provides promising results for many applications.
Volume: 11
Issue: 4
Page: 3229-3240
Publish at: 2021-08-01

Impact of sensorless neural direct torque control in a fuel cell traction system

10.11591/ijece.v11i4.pp2725-2732
Benhamou Aissa , Tedjini Hamza , Guettaf yacine , Nour Mohamed
Due to the reliability and relatively low cost and modest maintenance requirement of the induction machine make it one of the most widely used machines in industrial applications. The speed control is one of many problems in the traction system, researchers went to new paths instead the classical controllers as PI controller, they integrated the artificial intelligent for its yield. The classical DTC is a method of speed control by using speed sensor and PI controller, it achieves a decoupled control of the electromagnetic torque and the stator flux in the stationary frame, besides, the use of speed sensors has several drawbacks such as the fragility and the high cost, for this reason, the specialists went to propose an estimators as Kalman filter. The fuel cell is a new renewable energy, it has many applications in the traction systems as train, bus. This paper presents an improved control using DTC by integrate the neural network strategy without use speed sensor (sensorless control) to reduce overtaking and current ripple and static error in the system because the PI controller has some problems like this; and reduce the cost with use a renewable energy as fuel cell.
Volume: 11
Issue: 4
Page: 2725-2732
Publish at: 2021-08-01

Big data traffic management in vehicular ad-hoc network

10.11591/ijece.v11i4.pp3483-3491
Tantaoui Mouad , Laanaoui My Driss , Kabil Mustapha
Today, the world has experienced a new trend with regard to data system management, traditional database management tools have become outdated and they will no longer be able to process the mass of data generated by different systems, that's why big data is there to process this mass of data to bring out crucial information hidden in this data, and without big data technologies the treatment is very difficult to manage; among the domains that uses big data technologies is vehicular ad-hoc network to manage their voluminous data. In this article, we establish in the first step a method that allow to detect anomalies or accidents within the road and compute the time spent in each road section in real time, which permit us to obtain a database having the estimated time spent in all sections in real time, this will serve us to send to the vehicles the right estimated time of arrival all along their journey and the optimal route to attain their destination. This database is useful to utilize it like inputs for machine learning to predict the places and times where the probability of accidents is higher. The experimental results prove that our method permits us to avoid congestions and apportion the load of vehicles in all roads effectively, also it contributes to road safety.
Volume: 11
Issue: 4
Page: 3483-3491
Publish at: 2021-08-01

Advances in lane marking detection algorithms for all-weather conditions

10.11591/ijece.v11i4.pp3365-3373
Hadhrami Ab Ghani , Rosli Besar , Zamani Md Sani , Mohd Nazeri Kamaruddin , Syabeela Syahali , Atiqullah Mohamed Daud , Aerun Martin
Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems.
Volume: 11
Issue: 4
Page: 3365-3373
Publish at: 2021-08-01

Accelerating the update of a DL-based IDS for IoT using deep transfer learning

10.11591/ijeecs.v23.i2.pp1059-1067
Idriss Idrissi , Mostafa Azizi , Omar Moussaoui
Deep learning (DL) models are nowadays broadly applied and have shown outstanding performance in a variety of fields, including our focus topic of "IoTcybersecurity". Deep learning-based intrusion detection system (DL-IDS) models are more fixated and depended on the trained dataset. This poses a problem for these DL-IDS, especially with the known mutation and behavior changes of attacks, which can render them undetected. As a result, the DL-IDShas become outdated. In this work, we present a solution for updating DL-ID Semploying a transfer learning technique that allows us to retrain and fine-tune pre-trained models on small datasets with new attack behaviors. In our experiments, we built CNN-based IDS on the Bot-IoT dataset and updated it on small data from a new dataset named TON-IoT. We obtained promising results in multiple metrics regarding the detection rate and the training between the initial training for the original model and the updated one, in the matter of detecting new attacks behaviors and improving the detection rate for some classes by overcoming the lack of their labeled data.
Volume: 23
Issue: 2
Page: 1059-1067
Publish at: 2021-08-01
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