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29,922 Article Results

Large-scale image-to-video face retrieval with convolutional neural network features

10.11591/ijai.v9.i1.pp40-45
Imane Hachchane , Abdelmajid Badri , Aïcha Sahel , Yassine Ruichek
Convolutional neural network features are becoming the norm in instance retrieval. This work investigates the relevance of using an of the shelf object detection network, like Faster R-CNN, as a feature extractor for an image-to-video face retrieval pipeline instead of using hand-crafted features. We use the objects proposals learned by a Region Proposal Network (RPN) and their associated representations taken from a CNN for the filtering and the re-ranking steps. Moreover, we study the relevance of features from a finetuned network. In addition to that we explore the use of face detection, fisher vector and bag of visual words with those CNN features. We also test the impact of different similarity metrics. The results obtained are very promising.
Volume: 9
Issue: 1
Page: 40-45
Publish at: 2020-03-01

Application of carbon nanotubes (CNT) on the computer science and electrical engineering: A review

10.11591/ijres.v9.i1.pp61-82
Hossein Kardan Moghaddam , Mohamad Reza Maraki , Amir Rajaei
In recent years, dimensions and sizes of components and parts in the computer and electronic industries have been steadily reducing, as they are now considered very tiny tools and there is always a need to store and process information stronger. Nanotubes have poor magnetic properties. If nanotubes are covered by ferromagnetic nanoparticles, their magnetic properties can be improved and they can be used in the manufacture of nanoelectronic devices in the computer and electronic industries. In addition to reviewing the structure and properties of materials made using different nanomaterials for use in the computer and electronic industries, the present paper aimed to study different applications of nanomaterials, especially carbon nanotubes, in the manufacture of electronic devices. The present study showed that the corporation of nanomaterials into electronic devices is a promising approach for future applications which can revolutionize the computer industry.
Volume: 9
Issue: 1
Page: 61-82
Publish at: 2020-03-01

Surface potential modeling of dual metal gate-graded channel-dual oxide thickness with two dielectric constant different of surrounding gate MOSFET

10.11591/ijres.v9.i1.pp52-60
Hind Jaafar , Abdellah Aouaj , A. Bouziane , Benjamin Iñiguez
An Analytical study for the surface potential, threshold voltage and Subthreshold swing (SS) of Dual-metal Gate Graded channel and Dual Oxide Thickness with two dielectric constant different cylindrical gate surrounding-gate (DMG-GC-DOTTDCD) metal–oxide–semiconductor field-effect transistors (MOSFETs) is proposed to investigate short-channel effects (SCEs). The performance of the modified structure was studied by developing physics-based analytical models for the surface potential, threshold voltage shift, and Subthreshold swing. It is shown that the novel MOSFET could significantly reduce threshold voltage shift and Subthreshold swing, can also provides improved electron transport and reduced short channel effects (SCE). Results reveal that the DMG-GC-DOTTDCD devices with different dielectric constant offer superior characteristics as compared to DMG-GC-DOT devices. The derived analytical models agree well with simulation by ATLAS.
Volume: 9
Issue: 1
Page: 52-60
Publish at: 2020-03-01

A deep learning based technique for plagiarism detection: a comparative study

10.11591/ijai.v9.i1.pp81-90
Hambi El Mostafa , Faouzia Benabbou
The ease of access to the various resources on the web-enabled the democratization of access to information but at the same time allowed the appearance of enormous plagiarism problems. Many techniques of plagiarism were identified in the literature, but the plagiarism of idea steels the foremost troublesome to detect, because it uses different text manipulation at the same time. Indeed, a few strategies have been proposed to perform semantic plagiarism detection, but they are still numerous challenges to overcome. Unlike the existing states of the art, the purpose of this study is to give an overview of different propositions for plagiarism detection based on the deep learning algorithms. The main goal of these approaches is to provide a high quality of worlds or sentences vector representation. In this paper, we propose a comparative study based on a set of criterions like: Vector representation method, Level Treatment, Similarity Method and Dataset. One result of this study is that most of researches are based on world granularity and use the word2vec method for word vector representation, which sometimes is not suitable to keep the meaning of the whole sentences. Each technique has strengths and weaknesses; however, none is quite mature for semantic plagiarism detection.
Volume: 9
Issue: 1
Page: 81-90
Publish at: 2020-03-01

Estimation of water quality index using artificial intelligence approaches and multi-linear regression

10.11591/ijai.v9.i1.pp126-134
Muhammad Sani Gaya , Sani Isah Abba , Aliyu Muhammad Abdu , Abubakar Ibrahim Tukur , Mubarak Auwal Saleh , Parvaneh Esmaili , Norhaliza Abdul Wahab
Water quality index is a measure of water quality at a certain location and over a period of time. High value indicates that the water is unsafe for drinking and inadequate in quality to meet the designated uses. Most of the classical models are unreliable producing unpromising forecasting results. This study presents Artificial Intelligence (AI) techniques and a Multi Linear Regression (MLR) as the classical linear model for estimating the Water Quality Index (WQI) of Palla station of Yamuna river, India. Full-scale data of the river were used in validating the models. Performance measures such as Mean Square Error (MSE), Root Mean Squared Error (RMSE) and Determination Coefficient (DC) were utilized in evaluating the accuracy and performance of the models. The obtained result depicted the superiority of AI models over the MLR model. The results also indicated that, the best model of both ANN and ANFIS proved high improvement in performance accuracy over MLR up to 10% in the verification phase. The difference between ANN and ANFIS accuracy is negligible due to a slight increment in performance accuracy indicating that both ANN and ANFIS could serve as reliable models for the estimation of WQI.
Volume: 9
Issue: 1
Page: 126-134
Publish at: 2020-03-01

6 Transistors and 1 memristor based memory cell

10.11591/ijres.v9.i1.pp42-51
Kazi Fatima Sharif , Satyendra N. Biswas
Area efficient and stable memory design is one of the most important tasks in designing system on chip. This research concentrates in designing a new type of hybrid memory model by using only nMOS transistors and memristor. The proposed memory cell is very stable during successive read operates and comparatively faster and also occupies less amount of silicon area. The stability of the data during successive read operation and noise margin are in the promising range. Extensive simulation results using LTspice and Cadence software tools demonstrate the validity and competency of the proposed model.
Volume: 9
Issue: 1
Page: 42-51
Publish at: 2020-03-01

NAO-Teach: helping kids to learn societal and theoretical knowledge with friendly human-robot interaction

10.11591/ijeecs.v17.i3.pp1657-1664
Ahmad Hoirul Basori
Robotic technology has affected the education field, and even early education involves robot to attract Kids. Technical education is the notion of giving students knowledge of robots and technology. The main contribution of our research is to provide an interactive way of learning for kids through play and fun method. Two approaches proposed here: first, we provide an interactive game by touching robots body parts to teach kids how they were practising their motoric nerve and the listening to the instruction. In this game, kids asked to find some robot parts such as right hand, or left hand, where it equipped with a tactile sensor. The game difficulty can be increased by setting up the time limit for the answer and make kids touch the body parts of the robot very fast. The second learning method is practising number counting and pronunciation with NAO Robots. The robots will do computer vision processing to analyse and pronounce the kids handwriting with an artificial neural network. The result of implementation has obtained more than 75% success rate on recognition part with loss es than 0.6. The system received strong appreciation from kids and their parent, while  This research believed able to attract kids to study in interactive and fun ways.
Volume: 17
Issue: 3
Page: 1657-1664
Publish at: 2020-03-01

A fuzzy neighborhood rough set method for anomaly detection in large scale data

10.11591/ijai.v9.i1.pp1-10
EL Meziati Marouane , Ziyati Elhoussaine
Mining Outlier in database is to find exceptional objects that deviate from the rest of the datasets. Besides classical outlier analysis algorithms, recent studies have focused on mining local outliers. The outliers that have density distribution significantly different from their neighborhood.  However, the existing outlier detection algorithms suffer the drawbacks that they are inefficient in dealing with large scale datasets. In this paper, we propose a novel approach for outlier detection with voluminous data. This approach involves a neighborhood fuzzy rough set theory to rank outlier according to fuzzy membership function computed in rough approximation space. In order to improve the speed of computation, an efficient parallel computing system based on Map Reduce model is developed
Volume: 9
Issue: 1
Page: 1-10
Publish at: 2020-03-01

Two state-of-the-arts current-mode ternary full adders based on CNTFET Technology

10.11591/ijres.v9.i1.pp19-27
Mona Moradi
Adder core respecting to its various applications in VLSI circuits and systems is considered as the most critical building block in microprocessors, digital signal processors and arithmetic operations. Novel designs of a low power and complexity Current Mode 1-bit Full Adder cell based on CNTFET technology has been presented in this paper. Three major parts construct their structures; 1) the first part that converts current to voltage; 2) threshold detectors (TD); and 3) parallel paths to convey the output currents flow. Adjusting threshold voltages which are significant factor for setting threshold detectors switching point has been achieved by means of CNTFET technology. It would bring significant improvements in adjusting threshold voltages, regarding to its unique characterizations. Simple design, less transistor counts and static power dissipation and better performance comparing previous designs could be considered as some advantages of the novel designs.
Volume: 9
Issue: 1
Page: 19-27
Publish at: 2020-03-01

Preservice Turkish language teachers’ attitudes toward Anatolian dialects

10.11591/ijere.v9i1.20471
İzzet Şeref
This study aimed to reveal preservice Turkish Language teachers' attitudes toward the use of Anatolian dialects in education in terms of their genders and years at university. The participants of the study are 201 preservice teachers who are 1st, 2nd, 3rd and 4th-year students studying at Turkish Language Teaching undergraduate program at Tokat Gaziosmanpasa University in the 2017-2018 academic year. The study is a correlational survey employing a descriptive research method. The data of the study were collected employing a scale named Attitude Scale Toward Anatolian Dialects. Using SPSS 22.0, t-Test for independent samples and One-Way ANOVA for independent samples were employed to analyze the data.  As a result of the study, it is found out that there is a significant difference between the attitudes toward Anatolian dialects in favor of males; and being only between 2nd and 4th-year students, there is a significant difference between the attitudes in favor of 2nd-year students.
Volume: 9
Issue: 1
Page: 93-99
Publish at: 2020-03-01

The multicultural experiences, attitudes and efficacy perceptions among prospective teachers

10.11591/ijere.v9i1.20412
Sıddık Bakır
The purpose of this study is to investigate the concepts of multiculturalism and multicultural education and the multicultural experiences, attitudes and efficacies of prospective teachers of Turkish based on different variables. The study was carried out with a total of 249 prospective teachers of which 77% were female, and 23% were male who were receiving education in the spring semester of the academic year of 2018-2019 at the department of Turkish education of a state university. The study utilized the Multicultural Efficacy Scale. The data were analyzed by utilizing statistics and statistical techniques such as percentages, frequencies, arithmetic means, standard deviations, t-test and one-way analysis of variance. The Cronbach’s Alpha reliability coefficient that was calculated for this study was .868. Based on the findings of the study, it was determined that the prospective Turkish teachers had above-average and positive efficacies towards multicultural education, the saw themselves capable in the “experience, attitude and self-efficacy” dimensions, their perception levels were high, and among different variables, there were significant differences in their multicultural efficacy levels based on the variables of class and place of residence.
Volume: 9
Issue: 1
Page: 212-220
Publish at: 2020-03-01

Evaluation of Firewall and Load balance in Fat-Tree Topology Based on Floodlight Controller

10.11591/ijeecs.v17.i3.pp1157-1164
Sarah Hashim Mohammed , Ammar Dawood Jasim
Today it has become important to reconfigure the networks in to new form to be more manageable, scalable, dynamic and programmable. The networks recently are so inflexible and failing to deal with the required changes for the Information Technology. Software Defined Networking (SDN) is a modern paradigm that focused to change the main idea of current network infrastructure (traditional network) by breaking the chain between the data forwarding and the control planes to introduce flexible programmability network. This paper makes comparison between the performance of traditional fat-tree network and SDN fat-tree network, which found that average Round Tripe Time (RTT) in SDN fat-tree topology will decrease by 8.96% than traditional fat-tree topology. Then shows the basic operation of OpenFlow protocol that can be applied on fat-tree topology by using SDN technology and how that can be effect on the performance of network and make it more flexible to enable the SDN module applications, like load balancer and firewall for optimizing the SDN network. In this paper the physical switches are replaced by software switches in a virtual network environment and display the SDN structure in GUI, also Floodlight controller is chosen to use as the network operating system for SDN network.
Volume: 17
Issue: 3
Page: 1157-1164
Publish at: 2020-03-01

A compact model of transconductance and drain conductance for DMG-GC-DOT cylindrical gate MOSFET

10.11591/ijres.v9.i1.pp34-41
Hind Jaafar , Abdellah Aouaj , Benjamin Iñiguez , Ahmed Bouziane
A compact model for dual-material gate graded-channel and dual-oxide thickness with two dielectric constant different cylindrical gate (DMG-GC-DOTTDCD) MOSFET was investigated in terms of transconductance, drain conductance and capacitance. Short channel effects are modeled with simple expressions, and incorporated into the core of the model (at the drain current). The design effectiveness of DMG-GC-DOTTDCD was monitored in comparing with the DMG-GC-DOT transistor, the effect of variations of technology parameters, was presented in terms of gate polarization and drain polarization. The results indicate that the DMG-GC-DOTTDCD devices have characteristics higher than the DMG-GC-DOT MOSFET. To validate the proposed model, we used the results obtained from the simulation of the device with the SILVACO-ATLAS-TCAD software.
Volume: 9
Issue: 1
Page: 34-41
Publish at: 2020-03-01

Filtering and acquisition of serial data frames using xilinx system generator

10.11591/ijres.v9.i1.pp1-11
Adrián Gonzalo Stacul
The main purpose of this paper is the design, development and implementation of a PCM bit-synchronizer based on a System Generator and Simulink model. The entire system will be applied to a ground station with an ad-hoc telemetric data acquisition system to be applied in UAV monitoring and sounding rockets. Based on this information, the ground station will compute the platform trajectories, velocities and attitudes.
Volume: 9
Issue: 1
Page: 1-11
Publish at: 2020-03-01

An efficient quantum multiverse optimization algorithm for solving optimization problems

10.11591/ijaas.v9.i1.pp27-33
Samira Sarvari , Nor Fazlida Mohd. Sani , Zurina Mohd Hanapi , Mohd Taufik Abdullah
Due to the recent trend of technologies to use the network-based systems, detecting them from threats become a crucial issue. Detecting unknown or modified attacks is one of the recent challenges in the field of intrusion detection system (IDS). In this research, a new algorithm called quantum multiverse optimization (QMVO) is investigated and combined with an artificial neural network (ANN) to develop advanced detection approaches for an IDS. QMVO algorithm depends on adopting a quantum representation of the quantum interference and operators in the multiverse optimization to obtain the optimal solution. The QMVO algorithm determining the neural network weights based on the kernel function, which can improve the accuracy and then optimize the training part of the artificial neural network. It is demonstrated 99.98% accuracy with experimental results that the proposed QMVO is significantly improved optimization compared with multiverse optimizer (MVO) algorithms.
Volume: 9
Issue: 1
Page: 27-33
Publish at: 2020-03-01
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