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29,939 Article Results

Implementation of a personalized food recommendation system based on collaborative filtering and knapsack method

10.11591/ijece.v12i1.pp630-638
Nattaporn Thongsri , Pattaraporn Warintarawej , Santi Chotkaew , Wanida Saetang
Food recommendation system is one of the most interesting recommendation problems since it provides data for decision-making to users on selection of foods that meets individual preference of each user. Personalized recommender system has been used to recommend foods or menus to respond to requirements and restrictions of each user in a better way. This research study aimed to develop a personalized healthy food recommendation system based on collaborative filtering and knapsack method. Assessment results found that users were satisfied with the personalized healthy food recommendation system based on collaborative filtering and knapsack problem algorithm which included ability of operating system, screen design, and efficiency of operating system. The average satisfaction score overall was 4.20 implying that users had an excellent level of satisfaction.
Volume: 12
Issue: 1
Page: 630-638
Publish at: 2022-02-01

Two-dimensional satellite image compression using compressive sensing

10.11591/ijece.v12i1.pp311-319
Gunasheela Keragodu Shivanna , Haranahalli Shreenivasamurthy Prasantha
Compressive sensing is receiving a lot of attention from the image processing research community as a promising technique for image recovery from very few samples. The modality of compressive sensing technique is very useful in the applications where it is not feasible to acquire many samples. It is also prominently useful in satellite imaging applications since it drastically reduces the number of input samples thereby reducing the storage and communication bandwidth required to store and transmit the data into the ground station. In this paper, an interior point-based method is used to recover the entire satellite image from compressive sensing samples. The compression results obtained are compared with the compression results from conventional satellite image compression algorithms. The results demonstrate the increase in reconstruction accuracy as well as higher compression rate in case of compressive sensing-based compression technique.
Volume: 12
Issue: 1
Page: 311-319
Publish at: 2022-02-01

Comparison of cascade P-PI controller tuning methods for PMDC motor based on intelligence techniques

10.11591/ijece.v12i1.pp1-11
Kareem Ghazi Abdulhussein , Naseer Majeed Yasin , Ihsan Jabbar Hasan
In this paper, there are two contributions: The first contribution is to design a robust cascade P-PI controller to control the speed and position of the permanent magnet DC motor (PMDC). The second contribution is to use three methods to tuning the parameter values for this cascade controller by making a comparison between them to obtain the best results to ensure accurate tracking trajectory on the axis to reach the desired position. These methods are the classical method (CM) and it requires some assumptions, the genetic algorithm (GA), and the particle swarm optimization algorithm (PSO). The simulation results show the system becomes unstable after applying the load when using the classical method because it assumes cancellation of the load effect. Also, an overshoot of about 3.763% is observed, and a deviation from the desired position of about 12.03 degrees is observed when using the GA algorithm, while no deviation or overshoot is observed when using the PSO algorithm. Therefore, the PSO algorithm has superiority as compared to the other two methods in improving the performance of the PMDC motor by extracting the best parameters for the cascade P-PI controller to reach the desired position at a regular speed.
Volume: 12
Issue: 1
Page: 1-11
Publish at: 2022-02-01

Audio steganography based on least significant bits algorithm with 4D grid multi-wing hyper-chaotic system

10.11591/ijece.v12i1.pp320-330
Hussein Abdulameer Abdulkadhim , Jinan Nsaif Shehab
Although variety in hiding methods used to protect data and information transmitted via channels but still need more robustness and difficulty to improve protection level of the secret messages from hacking or attacking. Moreover, hiding several medias in one media to reduce the transmission time and band of channel is the important task and define as a gain channel. This calls to find other ways to be more complexity in detecting the secret message. Therefore, this paper proposes cryptography/steganography method to hide an audio/voice message (secret message) in two different cover medias: audio and video. This method is use least significant bits (LSB) algorithm combined with 4D grid multi-wing hyper-chaotic (GMWH) system. Shuffling of an audio using key generated by GMWH system and then hiding message using LSB algorithm will provide more difficulty of extracting the original audio by hackers or attackers. According to analyses of obtained results in the receiver using peak signal-to-noise ratio (PSNR)/mean square error (MSE) and sensitivity of encryption key, the proposed method has more security level and robustness. Finally, this work will provide extra security to the mixture base of crypto-steganographic methods.
Volume: 12
Issue: 1
Page: 320-330
Publish at: 2022-02-01

Analyzing and detecting hemorrhagic and ischemic strokebased on bit plane slicing and edge detection algorithms

10.11591/ijeecs.v25.i2.pp1003-1010
Warqaa Shaher Alazawee , Zobeda Hatif Naji , Weaam Talaat Ali
Nowadays, in the medical world, analyzing and diagnosing acute brain stroke and its location is a difficult process. In many hospitals, however, striking symptoms with the use of computed tomography (CT) imaging for patients is an important step in screening and diagnosis. Furthermore, computer-assisted accurate detection of diseased brain regions Because of the several sorts of strokes, their uneven form, and their great intensity and size, aided design is extremely challenging. Using the bit plan slice technique and the canny detector, we created and suggested a novel approach. Our algorithm produces excellent outcomes. The results demonstrate that our proposed algorithm is an accurate and reliable technique. This study also indicates that this system can detect two different types of strokes: hemorrhagic and ischemic strokes. The results of a comparison study of our suggested technique and other methods such as negative and logarithmic transformation methods are also included in this article.
Volume: 25
Issue: 2
Page: 1003-1010
Publish at: 2022-02-01

Thriving information system through business intelligence knowledge management excellence framework

10.11591/ijece.v12i1.pp506-514
Abdul Karim Mohamad , Mailasan Jayakrishnan , Mokhtar Mohd Yusof
In the current digitalization dilemma of an organization, there is a need for the business intelligence and knowledge management element for enhancing a perspective of learning and strategic management. These elements will comprise a significant evolution of learning, insight gained, experiences and knowledge through compelling theoretical impact for practitioners, academicians, and scholars in the pertinent field of interest. This phenomenon occurs due to digitalization transformation towards industry revolution 5.0 and organizational excellence in the information system area. This research focuses on the characteristic of a comprehensive performance measure perspective in an organization that conceives information assessment and key challenges of Business Intelligence and Knowledge Management in perceiving a relevant organizational excellence framework. The dynamic research focusing on the decision-making process and leveraging better knowledge creation. The future of organization excellence seemed to be convergent in determining the holistic performance measure perspective and its factors towards industry revolution 5.0. The research ends up with a typical basic excellence framework that will mash up some characteristics in designing an organizational strategic performance framework. The output is a conceptual performance measure framework for a typical decision-making application for organizational strategic performance management dashboarding.
Volume: 12
Issue: 1
Page: 506-514
Publish at: 2022-02-01

Mitigation of packet loss with end-to-end delay in wireless body area network applications

10.11591/ijece.v12i1.pp460-470
Suha Sahib Oleiwi , Ghassan N. Mohammed , Israa Al_Barazanchi
The wireless body area network (WBAN) has been proposed to offer a solution to the problem of population ageing, shortage in medical facilities and different chronic diseases. The development of this technology has been further fueled by the demand for real-time application for monitoring these cases in networks. The integrity of communication is constrained by the loss of packets during communication affecting the reliability of WBAN. Mitigating the loss of packets and ensuring the performance of the network is a challenging task that has sparked numerous studies over the years. The WBAN technology as a problem of reducing network lifetime; thus, in this paper, we utilize cooperative routing protocol (CRP) to improve package delivery via end-to-end latency and increase the length of the network lifetime. The end-to-end latency was used as a metric to determine the significance of CRP in WBAN routing protocols. The CRP increased the rate of transmission of packets to the sink and mitigate packet loss. The proposed solution has shown that the end-to-end delay in the WBAN is considerably reduced by applying the cooperative routing protocol. The CRP technique attained a delivery ratio of 0.8176 compared to 0.8118 when transmitting packets in WBAN.
Volume: 12
Issue: 1
Page: 460-470
Publish at: 2022-02-01

Efficiency of hybrid algorithm for COVID-19 online screening test based on its symptoms

10.11591/ijeecs.v25.i1.pp440-449
Mohd Kamir Yusof , Wan Mohd Amir Fazamin Wan Hamzah , Nur Shuhada Md Rusli
The coronavirus COVID-19 is affecting 196 countries and territories around the world. The number of deaths keep on increasing each day because of COVID-19. According to World Health Organization (WHO), infected COVID-19 is slightly increasing day by day and now reach to 570,000. WHO is prefer to conduct a screening COVID-19 test via online system. A suitable approach especially in string matching based on symptoms is required to produce fast and accurate result during retrieving process. Currently, four latest approaches in string matching have been implemented in string matching; characters-based algorithm, hashing algorithm, suffix automation algorithm and hybrid algorithm. Meanwhile, extensible markup language (XML), JavaScript object notation (JSON), asynchronous JavaScript XML (AJAX) and JQuery tehnology has been used widelfy for data transmission, data storage and data retrieval. This paper proposes a combination of algorithm among hybrid, JSON and JQuery in order to produce a fast and accurate results during COVID-19 screening process. A few experiments have been by comparison performance in term of execution time and memory usage using five different collections of datasets. Based on the experiments, the results show hybrid produce better performance compared to JSON and JQuery. Online screening COVID-19 is hopefully can reduce the number of effected and deaths because of COVID.
Volume: 25
Issue: 1
Page: 440-449
Publish at: 2022-01-01

Enhancement of observability using Kubernetes operator

10.11591/ijeecs.v25.i1.pp496-503
Prerana Shenoy S. P. , Sai Vishnu Soudri , Ramakanth Kumar P. , Sahana Bailuguttu
Observability is the ability for us to monitor the state of the system, which involves monitoring standard metrics like central processing unit (CPU) utilization, memory usage, and network bandwidth. The more we can understand the state of the system, the better we can improve the performance by recognizing unwanted behavior, improving the stability and reliability of the system. To achieve this, it is essential to build an automated monitoring system that is easy to use and efficient in its working. To do so, we have built a Kubernetes operator that automates the deployment and monitoring of applications and notifies unwanted behavior in real time. It also enables the visualization of the metrics generated by the application and allows standardizing these visualization dashboards for each type of application. Thus, it improves the system's productivity and vastly saves time and resources in deploying monitored applications, upgrading Kubernetes resources for each application deployed, and migration of applications.
Volume: 25
Issue: 1
Page: 496-503
Publish at: 2022-01-01

A YOLO and convolutional neural network for the detection and classification of leukocytes in leukemia

10.11591/ijeecs.v25.i1.pp200-213
Shakir Mahmood Abas , Adnan Mohsin Abdulazeez , Diyar Qader Zeebaree
The developing of deep learning systems that used for chronic diseases diagnosing is challenge. Furthermore, the localization and identification of objects like white blood cells (WBCs) in leukemia without preprocessing or traditional hand segmentation of cells is a challenging matter due to irregular and distorted of nucleus. This paper proposed a system for computer-aided detection depend completely on deep learning with three models computer-aided detection (CAD3) to detect and classify three types of WBC which is fundamentals of leukemia diagnosing. The system used modified you only look once (YOLO v2) algorithm and convolutional neural network (CNN). The proposed system trained and evaluated on dataset created and prepared specially for the addressed problem without any traditional segmentation or preprocessing on microscopic images. The study proved that dividing of addressed problem into sub-problems will achieve better performance and accuracy. Furthermore, the results show that the CAD3 achieved an average precision (AP) up to 96% in the detection of leukocytes and accuracy 94.3% in leukocytes classification. Moreover, the CAD3 gives report contain a complete information of WBC. Finally, the CAD3 proved its efficiency on the other dataset such as acute lymphoblastic leukemia image database (ALL-IBD1) and blood cell count dataset (BCCD).
Volume: 25
Issue: 1
Page: 200-213
Publish at: 2022-01-01

A comparative study for the assessment of Ikonos satellite image-fusion techniques

10.11591/ijeecs.v25.i1.pp256-264
Javier Medina , Nelson Vera , Erika Upegui
IImage-fusion provide users with detailed information about the urban and rural environment, which is useful for applications such as urban planning and management when higher spatial resolution images are not available. There are different image fusion methods. This paper implements, evaluates, and compares six satellite image-fusion methods, namely wavelet 2D-M transform, gram schmidt, high-frequency modulation, high pass filter (HPF) transform, simple mean value, and PCA. An Ikonos image (Panchromatic-PAN and multispectral-MULTI) showing the northwest of Bogotá (Colombia) is used to generate six fused images: MULTIWavelet 2D-M, MULTIG-S, MULTIMHF, MULTIHPF, MULTISMV, and MULTIPCA. In order to assess the efficiency of the six image-fusion methods, the resulting images were evaluated in terms of both spatial quality and spectral quality. To this end, four metrics were applied, namely the correlation index, erreur relative globale adimensionnelle de synthese (ERGAS), relative average spectral error (RASE) and the Q index. The best results were obtained for the  MULTISMV image, which exhibited spectral correlation higher than 0.85, a Q index of 0.84, and the highest scores in spectral assessment according to ERGAS and RASE, 4.36% and 17.39% respectively.
Volume: 25
Issue: 1
Page: 256-264
Publish at: 2022-01-01

Max stable set problem to found the initial centroids in clustering problem

10.11591/ijeecs.v25.i1.pp569-579
Awatif Karim , Chakir Loqman , Youssef Hami , Jaouad Boumhidi
In this paper, we propose a new approach to solve the document-clustering using the K-Means algorithm. The latter is sensitive to the random selection of the k cluster centroids in the initialization phase. To evaluate the quality of K-Means clustering we propose to model the text document clustering problem as the max stable set problem (MSSP) and use continuous Hopfield network to solve the MSSP problem to have initial centroids. The idea is inspired by the fact that MSSP and clustering share the same principle, MSSP consists to find the largest set of nodes completely disconnected in a graph, and in clustering, all objects are divided into disjoint clusters. Simulation results demonstrate that the proposed K-Means improved by MSSP (KM_MSSP) is efficient of large data sets, is much optimized in terms of time, and provides better quality of clustering than other methods.
Volume: 25
Issue: 1
Page: 569-579
Publish at: 2022-01-01

An intelligent irrigation system based on internet of things (IoT) to minimize water loss

10.11591/ijeecs.v25.i1.pp504-510
Samar Amassmir , Said Tkatek , Otman Abdoun , Jaafar Abouchabaka
This paper proposes a comparison of three machine learning algorithms for a better intelligent irrigation system based on internet of things (IoT) for differents products. This work's major contribution is to specify the most accurate algorithm among the three machine learning algorithms (k-nearest neighbors (KNN), support vector machine (SVM), artificial neural network (ANN)). This is achieved by collecting irrigation data of a specific products and split it into training data and test data then compare the accuracy of the three algorithms. To evaluate the performance of our algorithm we built a system of IoT devices. The temperature and humidity sensors are installed in the field interact with the Arduino microcontroller. The Arduino is connected to Raspberry Pi3, which holds the machine learning algorithm. It turned out to be ANN algorithm is the most accurate for such system of irrigation. The ANN algorithm is the best choice for an intelligent system to minimize water loss for some products.
Volume: 25
Issue: 1
Page: 504-510
Publish at: 2022-01-01

Optimal design of CMOS current mode instrumentation amplifier using bio-inspired method for biomedical applications

10.11591/ijeecs.v25.i1.pp120-129
Issa Sabiri , Hamid Bouyghf , Abdelhadi Raihani , Brahim Ouacha
Analog integrated circuits for biomedical applications require good performance. This paper presents an instrumentation amplifier (IA) design based on three complementary metal oxide semiconductor (CMOS) conveyors with an active resistor. This circuit offers the possibility to control the gain by voltage and current. We have designed the IA to minimize the parasitic resistance (Rx) with large bandwidth and high common mode rejection ratio (CMRR) using the artificial bee colony algorithm (ABC). The topology is simulated using 0.35µm CMOS technology parameters. The optimization problem is represented by an objective function that will be implemented using MATLAB script. The results were approved by the simulation using the advanced design system (ADS) tool. The simulation results were compared to the characteristics of some other instrumentation amplifiers exsisting in the literature. The circuit has a higher CMRR than other topologies.
Volume: 25
Issue: 1
Page: 120-129
Publish at: 2022-01-01

Performance evaluation of different configurations of system with DSTATCOM using proposed Icos⁡ϕ technique

10.11591/ijeecs.v25.i1.pp1-13
Atma Ram , Parsh Ram Sharma , Rajesh Kumar Ahuja
The proposed Icos⁡ϕ control technique has been applied for power quality improvement using different configurations of system with distribution static compensator (DSTATCOM). Modeling, design and control of DSTATCOM are analysed in detial. Three phase reference current are extracted with this technique. The proposed technique has been used for power factor enhancement, voltage regulation, harmonic suppression and load balancing under dynamic condition with non-linear load. The proposed control is very effective for three different configurations of system with DSTATCOM for power quality improvement. Results for each configuration of system with DSTATCOM are simulated using MATLAB/Simulink sim power tool box. For teaching the power quality course, these can also be helpful.
Volume: 25
Issue: 1
Page: 1-13
Publish at: 2022-01-01
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