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29,922 Article Results

Image encryption based on elliptic curve cryptosystem

10.11591/ijece.v11i2.pp1293-1302
Zahraa Kadhim Obaid , Najlae Falah Hameed Al Saffar
Image encryption based on elliptic curve cryptosystem and reducing its complexity is still being actively researched. Generating matrix for encryption algorithm secret key together with Hilbert matrix will be involved in this study. For a first case we will need not to compute the inverse matrix for the decryption processing cause the matrix that be generated in encryption step was self invertible matrix. While for the second case, computing the inverse matrix will be required. Peak signal to noise ratio (PSNR), and unified average changing intensity (UACI) will be used to assess which case is more efficiency to encryption the grayscale image.
Volume: 11
Issue: 2
Page: 1293-1302
Publish at: 2021-04-01

Performance enhancement of relays used for next generation wireless communication networks

10.11591/ijict.v10i1.pp27-36
Saraju Prasad Padhy , Madhusmita Panda , Srinivas Sethi , Aruna Tripathy
Relaying is one of the latest communication technologies developed for wireless networks like WiMAX, LTE Advanced and 5G Ultra Reliable Low Latency Communication (URLLC) networks to provide coverage extension as well as higher bitrates for cell edge users. Thus they are included in the design of next generation wireless communication systems to provide performance improvement in terms of coverage and capacity over their predecessors. Other promising features of this technology include easy to implement and reduction in deployment cost. The objective of this paper is to analyze both cooperative and non-cooperative relaying techniques in the Infinite Block length regime and findout the benefits of Relay implementation. A single Amplify and Forward (A&F) Relay is used for this purpose. Reduction in power requirement for Simple Relay is shown in comparison to the direct transmission, using experimental analysis with Matlab simulation. SER (Symbol error rate) is calculated at the receiver for no relay, simple Relay and Cooperative Relaying scenario to show the improvements of cooperative Relaying implementation.The performance enhancement of the Relay is then carried out using Particle Swam Optimization (PSO) optimization technique where allocation of power between Base station and Relay Node is effectively distributed for optimum performance.
Volume: 10
Issue: 1
Page: 27-36
Publish at: 2021-04-01

Recently employed engineering techniques to reduce the spread of COVID-19 (corona virus disease 2019): a review study

10.11591/ijeecs.v22.i1.pp277-286
Bander Saman , Mahmoud M. A. Eid , Marwa M. Eid
The main challenges of today’s global health care system are to reach to strong healthcare system, to provide effective methods to eliminate the increase in the number of dead and infected with virus of COVID-19. Therefore, during the last few months, the great importance and efficacy of a variety of engineering techniques that have greatly contributed in curbing the spread of the COVID-19, and evenly help to eliminate it according to recent scientific studies was highly prominent. Among these promising technologies in this field we mention, but not limited to, the use of ultraviolet (UV) rays to disinfection of air and surfaces. In addition, thermal imaging technology, which was employed using infrared radiation for monitoring people in crowded areas and human groups to determine who have abnormal temperatures, so that all preventive measures are taken. Robots have also been used and harnessed to perform many tasks that limit the spread of the virus and maintain the integrity of the human element. Last but not least, facial recognition techniques have also been used to limit the spread of this pandemic. Ultraviolet radiation is one of physical therapy modalities that can be used to increase the efficiency of human immune system to fight the virus. In conclusion UV radiation, infrared thermal imaging, robotics, AFR technologies are now widely used to reduce the spread of this virus and manage the outbreak.
Volume: 22
Issue: 1
Page: 277-286
Publish at: 2021-04-01

Mobility-prediction and energy optimization for multi-channel multi-interface ad hoc networks in the presence of location errors

10.11591/ijeecs.v22.i1.pp315-325
Hassan Faouzi , Mohammed Boutalline
We present a mobility-prediction and energy optimization solution for multi-channel multi-interface (MCMI) ad hoc networks in the presence of location errors. This solution includes routing of the MCMI communication links that adapt to dynamic channel, traffic conditions, interference and mobility of nodes. We start first with implementing a novel cross-layer routing solution in order to share information between network and MAC layer, the benefit of this technique is to collect information about the channel quality and residual energy of the nodes and send them directly to the network layer. Next, we present a mobility-prediction model using Kalman filter to predict accurate locations and enhance routing performance, through estimating link duration and selecting reliable routes. The performance of proposed mechanism is measured using NS2.35 simulations with different scenarios and varying load in a network. Comparative analysis of simulation results shows better performance of our protocol (ME-MCMI AODV) in terms of reducing end-to-end delay, total dropped packets and increasing network lifetime and packet delivery ratio (PDR).
Volume: 22
Issue: 1
Page: 315-325
Publish at: 2021-04-01

Improved Lagrangian relaxation generation decision-support in presence of electric vehicles

10.11591/ijeecs.v22.i1.pp598-608
Hossein Zeynal , Zuhaina Zakaria , Ahmad Kor
Decision making strategies for resources available in macro/micro scales have long been a critical argument. Among existing methods to address such a mixed-binary optimization model, lagrangian relaxation (LR) found universal acceptance by many utilities, offering a fast and accurate answer. This paper aims at retrofitting the solution way of LR algorithm by dint of meta-heuristic cuckoo search algorithm (CSA). When integrating CSA into LR mechanism, a tighter duality gap is catered, representing more accurate feasible solution. The key performance of CSA exhibits a head start over other classical methods such as gradient search (GS) and newton raphson (NR) when dealt with the relative duality gap closure in LR procedure. Further, electric vehicles (EV) with its associated hard constraints are encompassed into model to imperiling the proposed CSA-LR if encountered with nonlinear fluctuation of duality gap. Simulation results show that the proposed CSA-LR model outperforms the solution quality with/without EV as compared with conventional NR-LR method.
Volume: 22
Issue: 1
Page: 598-608
Publish at: 2021-04-01

MTVRep: A movie and TV show reputation system based on fine-grained sentiment and semantic analysis

10.11591/ijece.v11i2.pp1613-1626
Abdessamad Benlahbib , El Habib Nfaoui
Customer reviews are a valuable source of information from which we can extract very useful data about different online shopping experiences. For trendy items (products, movies, TV shows, hotels, services . . . ), the number of available users and customers’ opinions could easily surpass thousands. Therefore, online reputation systems could aid potential customers in making the right decision (buying, renting, booking . . . ) by automatically mining textual reviews and their ratings. This paper presents MTVRep, a movie and TV show reputation system that incorporates fine-grained opinion mining and semantic analysis to generate and visualize reputation toward movies and TV shows. Differently from previous studies on reputation generation that treat the task of sentiment analysis as a binary classification problem (positive, negative), the proposed system identifies the sentiment strength during the phase of sentiment classification by using fine-grained sentiment analysis to separate movie and TV show reviews into five discrete classes: strongly negative, weakly negative, neutral, weakly positive and strongly positive. Besides, it employs embeddings from language models (ELMo) representations to extract semantic relations between reviews. The contribution of this paper is threefold. First, movie and TV show reviews are separated into five groups based on their sentiment orientation. Second, a custom score is computed for each opinion group. Finally, a numerical reputation value is produced toward the target movie or TV show. The efficacy of the proposed system is illustrated by conducting several experiments on a real-world movie and TV show dataset.
Volume: 11
Issue: 2
Page: 1613-1626
Publish at: 2021-04-01

Service landscape for private universities in indonesia based on service oriented architecture and cloud technology

10.11591/ijeecs.v22.i1.pp497-506
Faiza Renaldi , Irma Santikarama , Esmeralda C. Djamal , Agya Java Maulidin
Information technology (IT) has been widely adopted and is believed to improve academic processes’ efficiency and run private universities’ academic functions (PTSs) in Indonesia. Nonetheless, adopting diverse technologies for them will also create many challenges. PTSs are struggling to survive in terms of technological implementation, in the sense that the investment and implementation rate in the PTSs just cannot catch up with the technological advancement rate. Even when more PTSs are trying to transform into digital entities, the next problem will be system integration and flexibility. This study aims to overcome this problem by implementing a framework that can be both integrated and flexible while also serving the efficiency of investments. Many studies already suggested that service oriented architecture (SOA) and cloud technology are the solutions. Nevertheless, none has been able to define what standard services can be applied within those platforms. To determine this, we use the BIAN service landscape, which was translated from the banking industry, offering a comprehensive view of the business domain and business capabilities alongside its service functions. While BIAN offers common services throughout the same platform, we modify the framework using the OASIS model from SOA, which allows the framework to be flexible in complying with many platforms of databases, programming languages, and network infrastructures. We completed our study by defining one business area: academic processes, three business domains, 19 business capabilities, and 84 service functions. We are strongly confident that our findings and study results will act as a reference in creating a cloud-based platform for Indonesia’s higher education academic systems.
Volume: 22
Issue: 1
Page: 497-506
Publish at: 2021-04-01

Air temperature prediction using different machine learning models

10.11591/ijeecs.v22.i1.pp534-541
Rana Muhammad Adnan , Zhongmin Liang , Alban Kuriqi , Ozgur Kisi , Anurag Malik , Binquan Li , Fatemehsadat Mortazavizadeh
Air temperature is an essential climatic component particularly in water resources management and other agro-hydrological/meteorological activities planning This paper examines the prediction capability of three machine learning models, least square support vector machine (LSSVM), group method and data handling neural network (GMDHNN) and classification and regression trees (CART) in air temperature forecasting using monthly temperature data of Astore and Gilgit climatic stations of Pakistan. The prediction capability of three machine learning models is evaluated using different time lags input combinations with help of root mean square error (RMSE), the mean absolute error (MAE) and coefficient of determination (R2).statistical indicators. The obtained results indicated that the LSSVM model is more accurate in temperature forecasting than GMDHNN and CART models. LSSVM significantly decreases the mean RMSE of the GMHNN and CART models by 1.47-3.12% and 20.01-25.12% for the Chakdara and Kalam Stations, respectively.
Volume: 22
Issue: 1
Page: 534-541
Publish at: 2021-04-01

Searching surveillance video contents using convolutional neural network

10.11591/ijece.v11i2.pp1656-1665
Duaa Mohammad , Inad Aljarrah , Moath Jarrah
Manual video inspection, searching, and analyzing is exhausting and inefficient. This paper presents an intelligent system to search surveillance video contents using deep learning. The proposed system reduced the amount of work that is needed to perform video searching and improved the speed and accuracy. A pre-trained VGG-16 CNNs model is used for dataset training. In addition, key frames of videos were extracted in order to save space, reduce the amount of work, and reduce the execution time. The extracted key frames were processed using the sobel operator edge detector and the max-pooling in order to eliminate redundancy. This increases compaction and avoids similarities between extracted frames. A text file, that contains key frame index, time of occurrence, and the classification of the VGG-16 model, is produced. The text file enables humans to easily search for objects of interest. VIRAT and IVY LAB datasets were used in the experiments. In addition, 128 different classes were identified in the datasets. The classes represent important objects for surveillance systems. However, users can identify other classes and utilize the proposed methodology. Experiments and evaluation showed that the proposed system outperformed existing methods in an order of magnitude. The system achieved the best results in speed while providing a high accuracy in classification.
Volume: 11
Issue: 2
Page: 1656-1665
Publish at: 2021-04-01

Global convergence of new conjugate gradient method with inexact line search

10.11591/ijece.v11i2.pp1469-1475
Chergui Ahmed , Bouali Tahar
In this paper, We propose a new nonlinear conjugate gradient method (FRA) that satisfies a sufficient descent condition and global convergence under the inexact line search of strong wolf powell. Our numerical experiment shaw the efficiency of the new method in solving a set of problems from the CUTEst package, the proposed new formula gives excellent numerical results at CPU time, number of iterations, number of gradient ratings when compared to WYL, DY, PRP, and FR methods.
Volume: 11
Issue: 2
Page: 1469-1475
Publish at: 2021-04-01

Algorithmic TCAM on FPGA with data collision approach

10.11591/ijeecs.v22.i1.pp89-96
Nguyen Trinh , Anh Le Thi Kim , Hung Nguyen , Linh Tran
Content addressable memory (CAM) and ternary content addressable memory (TCAM) are specialized high-speed memories for data searching. CAM and TCAM have many applications in network routing, packet forwarding and Internet data centers. These types of memories have drawbacks on power dissipation and area. As field-programmable gate array (FPGA) is recently being used for network acceleration applications, the demand to integrate TCAM and CAM on FPGA is increasing. Because most FPGAs do not support native TCAM and CAM hardware, methods of implementing algorithmic TCAM using FPGA resources have been proposed through recent years. Algorithmic TCAM on FPGA have the advantages of FPGAs low power consumption and high intergration scalability. This paper proposes a scaleable algorithmic TCAM design on FPGA. The design uses memory blocks to negate power dissipation issue and data collision to save area. The paper also presents a design of a 256 x 104-bit algorithmic TCAM on Intel FPGA Cyclone V, evaluates the performance and application ability of the design on large scale and in future developments.
Volume: 22
Issue: 1
Page: 89-96
Publish at: 2021-04-01

Real-time human detection for electricity conservation using pruned-SSD and arduino

10.11591/ijece.v11i2.pp1510-1520
Ushasukhanya S. , Jothilakshmi S.
Electricity conservation techniques have gained more importance in recent years. Many smart techniques are invented to save electricity with the help of assisted devices like sensors. Though it saves electricity, it adds an additional sensor cost to the system. This work aims to develop a system that manages the electric power supply, only when it is actually needed i.e., the system enables the power supply when a human is present in the location and disables it otherwise. The system avoids any additional costs by using the closed circuit television, which is installed in most of the places for security reasons. Human detection is done by a Modified-single shot detection with a specific hyperparameter tuning method. Further the model is pruned to reduce the computational cost of the framework which in turn reduces the processing speed of the network drastically. The model yields the output to the Arduino micro-controller to enable the power supply in and around the location only when a human is detected and disables it when the human exits. The model is evaluated on CHOKEPOINT dataset and real-time video surveillance footage. Experimental results have shown an average accuracy of 85.82% with 2.1 seconds of processing time per frame.
Volume: 11
Issue: 2
Page: 1510-1520
Publish at: 2021-04-01

Design of wide band slotted microstrip patch antenna with defective ground structure for ku band

10.11591/ijece.v11i2.pp1337-1345
Akhila John Davuluri , P. Siddaiah
This paper proposes a microstrip patch antenna (MSPA) in the Ku band for satellite applications. The antenna is small in size with dimensions of about 40 mm×48 mm×1.59 mm and is fed with a coaxial cable of 50 Ω impedance. The proposed antenna has a wide bandwidth of 3.03 GHz ranging from 12.8 GHz to 15.8 GHz. To realize the characteristics of wideband the techniques of defective ground structure (DGS) and etching slots on the radiating element are adopted. The antenna is modeled on the FR4 substrate. A basic circular patch is selected for the design of a dual-frequency operation and in the next step DGS is introduced into the basic antenna and enhanced bandwidth is achieved at both the frequencies. To attain wider bandwidth two slots are etched on the radiating element of which one is a square ring slot and the second one is a circular ring slot. The novelty of the proposed antenna is a miniaturized design and unique response within the Ku band region which is applicable for wireless UWB applications with VSWR
Volume: 11
Issue: 2
Page: 1337-1345
Publish at: 2021-04-01

A composite controller based on nonlinear H_∞ and nonlinear disturbance observer for attitude stabilization of a flying robot

10.11591/ijeecs.v22.i1.pp270-276
Vahid Razmavar , Heidar Ali Talebi , Farzaneh Abdollahi
In this article a novel composite control technique is introduced. We added a nonlinear disturbance observer to a nonlinear H_∞ control to form this composite controller. The quadrotor kinematics and dynamics is formulated using euler angles and parameters. After that, this nonlinear robust controller is developed for this flying robot attitude control for the outdoor conditions. Because under these conditions the flying robot, experiences both external disturbance and parametric uncertainty. Stability analysis is also presented to show the global asymptotical stability using a Lyapunov function. The simulation results showed that the suggested composite controller had a better performance in comparison with a nonlinear H_∞ control scheme.
Volume: 22
Issue: 1
Page: 270-276
Publish at: 2021-04-01

A review of remote health monitoring based on internet of things

10.11591/ijeecs.v22.i1.pp297-306
Omar AlShorman , Buthaynah Alshorman , Mahmoud Masadeh , Fahad Alkahtani , Basim Al-Absi
Managing, diagnosis, prognosis, continuous monitoring, early detection, and preventing chronic diseases for patients and elderly people have been gained a crucial role nowadays. However, elderly people with chronic health conditions such as diabetes, cardiovascular disease, and mental diseases, need special health care. With the help of the internet of things (IoT) technologies, remote health monitoring (RHM) helps patients, caregivers, and countries for improving healthcare services, such as medical files services, mobile healthcare (mhealth), telemedicine services, and sensing technology. Moreover, RHM aims to reduce hospitalized demands and costs. The main contribution of the proposed study is to review RHM studies based on IoT technologies. Moreover, the challenges and possible future trends of RMH are highlighted.
Volume: 22
Issue: 1
Page: 297-306
Publish at: 2021-04-01
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