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A survey on security and privacy issues in IoV

10.11591/ijece.v10i5.pp5409-5419
Tanvi Garg , Navid Kagalwalla , Prathamesh Churi , Ambika Pawar , Sanjay Deshmukh
As an up-and-coming branch of the internet of things, internet of vehicles (IoV) is imagined to fill in as a fundamental information detecting and processing platform for astute transportation frameworks. Today, vehicles are progressively being associated with the internet of things which empower them to give pervasive access to data to drivers and travelers while moving. Be that as it may, as the quantity of associated vehicles continues expanding, new prerequisites, (for example, consistent, secure, vigorous, versatile data trade among vehicles, people, and side of the road frameworks) of vehicular systems are developing. Right now, the unique idea of vehicular specially appointed systems is being changed into another idea called the internet of vehicles (IoV). We talk about the issues faced in implementing a secure IoV architecture. We examine the various challenges in implementing security and privacy in IoV by reviewing past papers along with pointing out research gaps and possible future work and putting forth our on inferences relating to each paper.
Volume: 10
Issue: 5
Page: 5409-5419
Publish at: 2020-10-01

ICT-supported for participatory engagement within E-learning community

10.11591/ijeecs.v20.i1.pp492-499
Noor Hida Natrah Aziz , Haryani Haron , Afdallyna Fathiyah Harun
This paper presents ICT-supported for participatory engagement learning within the e-learning community. Effectively tools in e-Learning facilitate interactive learning and the achievement of desired learning outcomes for learners. However, the intensity of its usage is not very remarkable; there is a need to understand ICT- supported for learners from the perspectives of participatory engagement. Therefore, integrating suitable technology into e-learning is expected to strengthen learner's engagement within the e-learning community. The objective of the study is to identify technology that could effectively support learners' engagement. This study analyzes the available technology in the market to integrate into e-learning using the technology evaluation process. Interview sessions with experts were held to validated and suggested other technology uses in e-learning. This research is carrying out with three experts (academic staff) of the e-technologies within the University. This study uses semi-structured interviews to captured expert suggestions, knowledge, and expertise about technologies. Understanding learner's requirements toward technology are essential to ensure learners can reap the benefits of technology usage.  This study uses a thematical analysis to identify and organize key themes from qualitative data. The result reveals mobile technology, wireless technology, live streaming technology, authoring tool, summative assessment, cloud computing, gamification and Instagram is suitable technologies that support participatory engagement activities.
Volume: 20
Issue: 1
Page: 492-499
Publish at: 2020-10-01

Object tracking using motion flow projection for pan-tilt configuration

10.11591/ijece.v10i5.pp4687-4694
Luma Issa Abdul-Kreem , Hussam K. Abdul-Ameer
We propose a new object tracking model for two degrees of freedom mechanism. Our model uses a reverse projection from a camera plane to a world plane. Here, the model takes advantage of optic flow technique by re-projecting the flow vectors from the image space into world space. A pan-tilt (PT) mounting system is used to verify the performance of our model and maintain the tracked object within a region of interest (ROI). This system contains two servo motors to enable a webcam rotating along PT axes. The PT rotation angles are estimated based on a rigid transformation of the the optic flow vectors in which an idealized translation matrix followed by two rotational matrices around PT axes are used. Our model was tested and evaluated using different objects with different motions. The results reveal that our model can keep the target object within a certain region in the camera view.
Volume: 10
Issue: 5
Page: 4687-4694
Publish at: 2020-10-01

A new dynamic speech encryption algorithm based on lorenz chaotic map over internet protocol

10.11591/ijece.v10i5.pp4824-4834
Obaida M. Al-hazaimeh
This paper introduces a dynamic speech encryption algorithm based on Lorenz chaotic map over internet protocol to enhance the services of the real-time applications such as increases the security level and reduces latency. The proposed algorithm was divided into two processes: dynamic key generation process using 128-bit hash value to dynamically alter the initial secret keys, and encryption and decryption process using Lorenz system. In the proposed algorithm, the performance evaluation is carried out through efficient simulations and implementations and statistical analysis. In addition, the average time delay in the proposed algorithm and some of the existing algorithms such as AES is compared. The obtained results concluded that, the proposed dynamic speech encryption algorithm is effectually secured against various cryptanalysis attacks and has useful cryptographic properties such as confusion and diffusion for better voice communication in the voice applications field in the Internet.
Volume: 10
Issue: 5
Page: 4824-4834
Publish at: 2020-10-01

CL-SA-OFDM: Cross-layer and smart antenna based OFDM system performance enhancement

10.11591/ijece.v10i5.pp4663-4670
Shivapanchakshari T. G. , H. S. Aravinda
The growing usage of wireless services is lacking in providing high-speed data communication in recent times. Hence, many of the modulation techniques are evolved to attain these communication needs. The recent researches have widely considered OFDM technology as the prominent modulation mechanism to fulfill the futuristic needs of wireless communication. The OFDM can bring effective usage of resources, bandwidth, and system performance enhancement in collaboration with the smart antenna and resource allocation mechanism (adaptive). However, the usage of adaptive beamforming with the OFDM leads to complication in the design of medium access layer and which causes a problem in adaptive resource allocation mechanism (ARAM). Hence, the proposed manuscript intends to design an OFDM system by considering different switched beam smart antenna (SBSA) along with the cross-layer adaptive resource allocation (CLARA) and hybrid adaptive array (HAA). In this, various smart antenna mechanism are considered to analyze the quality of service (QoS) and complexity reduction in the OFDM system. In this paper, various SA schemes are used as per the quality of service (QoS) requirement of the different users. The performance analysis is conducted by considering data traffic reduction, bit-rate reduction, and average delay.
Volume: 10
Issue: 5
Page: 4663-4670
Publish at: 2020-10-01

FIBR-OSS: fault injection model for bug reports in open-source software

10.11591/ijeecs.v20.i1.pp465-474
Sundos Abdulameer Alazawi , Mohammed Najim Al-Salam
For assessment of system dependability, fault injection techniques are used to expedite the presence of an error or failure in the system, which helps evaluate fault tolerance and system failure prediction. Defects classification and prediction is the principal significant advance in the trustworthiness evaluation of complex software systems such as open-source software since it can quickly be affected by the reliability of those systems, improves performance, and lessening the product cost. In this context, a new prototype of the fault injection model is presented, FIBR-OSS (fault injection for bug reports in open-source software). FIBR-OSS can support developers to evaluate the system performance during phase's development for its dependability attributes such as reliability and system dependability means such as fault prediction or forecasting. FIBR-OSS is used for fault speed-up to test the system's failure prediction performance. Some machine learning techniques are implemented on bug reports produced existing by the bug tracking system as datasets for failure prediction techniques, some of those machine learning techniques are used in our approach.
Volume: 20
Issue: 1
Page: 465-474
Publish at: 2020-10-01

An energy optimization with improved QOS approach for adaptive cloud resources

10.11591/ijece.v10i5.pp4881-4891
Danthuluri Sudha , Sanjay Chitnis
In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (ACRR) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model ACRR in terms of average run time, power consumption and average power required than any other state-of-art techniques.
Volume: 10
Issue: 5
Page: 4881-4891
Publish at: 2020-10-01

Design of L-S band broadband power amplifier using microstip lines

10.11591/ijece.v10i5.pp5400-5408
Mohamed Ribate , Rachid Mandry , Jamal Zbitou , Larbi El Abdellaoui , Ahmed Errkik , Mohamed Latrach , Ahmed Lakhssassi
This contribution introduces a novel broadband power amplifier design, operating in the frequency band ranging from 1.5 GHz to 3 GHz which cover the mainstream applications running in L and S bands. Both matching and biasing networks are synthesized by using microstrip transmission lines. In order to provide a wide bandwidth, two broadband matching techniques are deployed for this purpose, the first technique is an approximate transformation of a previously designed lumped elements matching networks into microstrip matching circuits, and the second technique is a binomial multi-sections quarter wave impedance transformer. The proposed work is based on ATF-13786 active device. The simulation results depict a maximum power gain of 16.40 dB with an excellent input and output matching across 1.5 GHz ~ 3 GHz. At 2.2 GHz, the introduced BPA achieves a saturated output power of 16.26 dBm with a PAE of 21.74%, and a 1-dB compression point of 4.5 dBm input power level. The whole circuitry is unconditionally stable over the overall bandwidth. By considering the broadband matching, the proposed design compares positively with the most recently published BPA.
Volume: 10
Issue: 5
Page: 5400-5408
Publish at: 2020-10-01

Improved cloud data transfer security using hybrid encryption algorithm

10.11591/ijeecs.v20.i1.pp521-527
Samar Zaineldeen , Abdelrahim Ate
Cloud computing is a model of sophisticated computing which has a strong effect on data innovation. Cloud computing offers remote access to shared computerized assets in the stored cloud. Operationally cloud servers utilize Web services that give enormus advantage to the user in a variety of applications such as banking and finance, storage, social networking and e-mail. Cloud computing accomplishes many of the features interrelated to elasticity, ease of utility, efficiency and performance with low cost. There are a number of potential concerns related to security and privacy since the requirement to protect cloud computing expanded, the encryption algorithms play the key part in data and information security systems, on side these algorithms consume a considerable quantity of computing resource.This paper,presenting  a new hybrid encryption algorithm emphasising  on AES and enhanced homomorphic cryptosystem (EHC) as a hybrid encryption  to guarantee the secure exchange of data between the user and the cloud server, and compression study for two proficient homomorphic encryption techniques for encoding data encryption standard (DES), advance encryption stander (AES).With The proposed techniques an evaluation has been conducted for those encryption algorithms at diverse file sizes of data, to evaluate time taking for encryption and decryption, throughput, memory consumption and power consumption. The major finding was thats the proposed method has the extremity throughput; memory consumption and our proposed work took advantage of the least time taken in sec for encryption and decryption.
Volume: 20
Issue: 1
Page: 521-527
Publish at: 2020-10-01

Error bounds for wireless localization in NLOS environments

10.11591/ijece.v10i5.pp5535-5545
Omotayo Oshiga , Ali Nyangwarimam Obadiah
An efficient and accurate method to evaluate the fundamental error bounds for wireless sen-sor localization is proposed. While there already exist efficient tools like Cram`er-Rao lower bound (CRLB) and position error bound (PEB) to estimate error limits, in their standard formulation they all need an accurate knowledge of the statistic of the ranging error. This requirement, under Non-Line-of-Sight (NLOS) environments, is impossible to be met a priori. Therefore, it is shown that collecting a small number of samples from each link and applying them to a non-parametric estimator, like the Gaussian kernel (GK), could lead to a quite accurate reconstruction of the error distribution. A proposed Edgeworth Expansion method is employed to reconstruct the error statistic in a much more efficient way with respect to the GK. It is shown that with this method, it is possible to get fundamental error bounds almost as accurate as the theoretical case, i.e. when a priori knowledge of the error distribution is available. Therein, a technique to determine fundamental error limits – CRLB and PEB – onsite without knowledge of the statistics of the ranging errors is proposed.
Volume: 10
Issue: 5
Page: 5535-5545
Publish at: 2020-10-01

Comprehensive learning particle swarm optimization for sizing and placement of distributed generation for network loss reduction

10.11591/ijeecs.v20.i1.pp16-23
Eshan Karunarathne , Jagadeesh Pasupuleti , Janaka Ekanayake , Dilini Almeida
With the technological advancements, distributed generation (DG) has become a common method of overwhelming the issues like power losses and voltage drops which accompanies with the leaf of the feeders of radial distribution networks. Many researchers have used several optimization techniques and tools which could be used to locate and size the DG units in the system. particle swarm optimization (PSO) is one of the famous optimization techniques. However, the premature convergence is identified as a fundamental adverse effect of this optimization technique. Therefore, the optimization problem can direct the objective function to a local minimum. This paper presents a variant of PSO techniques, “comprehensive learning particle swarm optimization (CLPSO)” to determine the optimal placement and sizing of the DGs, which uses a novel learning strategy whereby all other particles’ historical best information and learning probability value are used to update a particle’s velocity. The CLPSO particles learn from one exampler for few iterations, instead of learing from global and personal best values in every iteration in PSO and this technique retains the swarm's variability to avoid premature convergence. A detailed analysis was conducted for the IEEE 33 bus system. The comparison results have revealed a higher convergence and an accuracy than the PSO.
Volume: 20
Issue: 1
Page: 16-23
Publish at: 2020-10-01

Framework for reversible data hiding using cost-effective encoding system for video steganography

10.11591/ijece.v10i5.pp5487-5496
Manjunath Kamath K. , R. Sanjeev Kunte
Importances of reversible data hiding practices are always higher in contrast to any conventional data hiding schemes owing to its capability to generate distortion free cover media. Review of existing approaches on reversible data hiding approaches shows variable scheme mainly focussing on the embedding mechanism; however, such schemes could be furthermore improved using encoding scheme for optimal embedding performance. Therefore, the proposed manuscript discusses about a cost-effective scheme where a novel encoding scheme has been used with larger block sizes which reduces the dependencies over larger number of blocks. Further a gradient-based image registration technique is applied to ensure higher quality of the reconstructed signal over the decoding end. The study outcome shows that proposed data hiding technique is proven better than existing data hiding scheme with good balance between security and restored signal quality upon extraction of data.
Volume: 10
Issue: 5
Page: 5487-5496
Publish at: 2020-10-01

An intrusion detection system for packet and flow based networks using deep neural network approach

10.11591/ijece.v10i5.pp5514-5525
Kaniz Farhana , Maqsudur Rahman , Md. Tofael Ahmed
Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest data set available at online, formatted with packet based, flow based data and some additional metadata. The data set is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multi-class classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.
Volume: 10
Issue: 5
Page: 5514-5525
Publish at: 2020-10-01

A dynamic cruise control system (DCCS) for effective navigation system

10.11591/ijece.v10i5.pp4645-4654
T. Someswari , Anil Kumar Tiwari , Nagraj R
With the fast development of artificial intelligence, robotics, and embedded system along with sensor technologies, the speed control mechanism is required in various other applications such as automatic or self-piloting aircraft, auto-driven vehicles, auto driven lifts and much other robotics based automation plants, etc. For each unpredictable and progressed vehicular framework accompanies a better route that is fit for utilizing the two GPS and INS related sign. There have been a noteworthy number of research works being completed towards creating sliding mode control framework. In case of inaccurate navigational data or no availability of navigational service, the cruise control could also stop working. Hence, there is a need to evolve up with a novel system offering reliable and fault tolerant navigation system in order to minimize the dependencies on GPS-based information and maximize the utilization of INS based information. This manuscript presents a dynamic cruise control system to achieve better navigation under uncertainties. The performance of the system is analyzed by incorporating sliding mode and fuzzy logic and achieves better accuracy in tracking error, computational complexity (28 sec of simulation time) under chattering and switching action operation.
Volume: 10
Issue: 5
Page: 4645-4654
Publish at: 2020-10-01

IOT-Based smart street lighting enhances energy conservation

10.11591/ijeecs.v20.i1.pp528-536
Zakiah Mohd Yusoff , Zuraida Muhammad , Mohd Syafiq Izwan Mohd Razi , Noor Fadzilah Razali , Muhd Hussaini Che Hashim
The electricity generation cost is escalating every year while the electric energy is indispensable and increasing in demand. The resources for energy generation is also depleting due to the increasing demand of power. Thus, a system that can reduce the energy wastage and the massive expenses is essential. Street light system is one of the systems that can reduce energy consumption. The massive energy consumption from the current street light system is not efficient enough to reduce the wasted energy. By implementing an IOT-based smart street light system, the power consumption of the street light will be optimized. This system will also provide the ability to monitor input voltage for Arduino MEGA 2560 microcontroller and control the street light through IOT. The concept of this smart system is to introduce an intelligent system which can decide to switch on or off the street light according to the movement detection by using an infrared sensor module. The data will be sent to Arduino Mega 2560, which is a microcontroller that will decide to turn on or off the street light. The Wi-Fi module ESP-01 is implemented to enable the microcontroller to connect to Blynk software for monitoring and controlling purpose. The result shows that the smart street light system is expected to reduce energy consumption up to 45.48% on weekdays and 32.22% on weekends from the present street light system which uses timer system. The IOT-based Smart Street Light system also shows the condition of the street light system based on the Blynk interfaces for maintenance purpose.
Volume: 20
Issue: 1
Page: 528-536
Publish at: 2020-10-01
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