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29,939 Article Results

Efficient processing of continuous spatial-textual queries over geo-textual data stream

10.11591/ijeecs.v25.i2.pp1094-1102
Kalpana Vivek Metre , Madan Kharat
Due to the extensive use of social media and mobile devices, unbounded and massive data is generated continuously. The need to process this big data is increasing day by day. The traditional data processing algorithms fail to cater to the need of processing data generated by various applications such as digital geo-based advertising, and recommendation systems. There has been a high demand to process continuous spatial fuzzy textual queries over data stream of spatial-textual objects with high density by present locationbased and social network-based service applications. For the spatialkeyword data stream, the performance plays a vital role as the geo information and keyword description matching is needed for every incoming streaming object. The various continuous geo-keyword query processing methods normally lack the support for fuzzy keyword matching when processing the objects from the geo-textual data stream. The edit distancebased approach with the adaptive partitioning tree index for the queries is used for fuzzy string matching and it outperforms than the existing approaches in storage cost and query performance cost.
Volume: 25
Issue: 2
Page: 1094-1102
Publish at: 2022-02-01

Smart monitoring system using NodeMCU for maintenance of production machines

10.11591/ijeecs.v25.i2.pp788-795
Ignatius Deradjad Pranowo , Dian Artanto
Maintenance is an activity that helps to reduce risk, increase productivity, improve quality, and minimize production costs. The necessity for maintenance actions will increase efficiency and enhance the safety and quality of products and processes. On getting these conditions, it is necessary to implement a monitoring system used to observe machines' conditions from time to time, especially the machine parts that often experience problems. This paper presents a low-cost intelligent monitoring system using NodeMCU to continuously monitor machine conditions and provide warnings in the case of machine failure. Not only does it provide alerts, but this monitoring system also generates historical data on machine conditions to the Google Cloud (Google Sheet), includes which machines were down, downtime, issues occurred, repairs made, and technician handling. The results obtained are machine operators do not need to lose a relatively long time to call the technician. Likewise, the technicians assisted in carrying out machine maintenance activities and online reports so that errors that often occur due to human error do not happen again. The system succeeded in reducing the technician-calling time and maintenance workreporting time up to 50%. The availability of online and real-time maintenance historical data will support further maintenance strategy.
Volume: 25
Issue: 2
Page: 788-795
Publish at: 2022-02-01

A design of a multi-agent recommendation system using ontologies and rule-based reasoning: pandemic context

10.11591/ijece.v12i1.pp515-523
Amina Ouatiq , Kamal ElGuemmat , Khalifa Mansouri , Mohammed Qbadou
Learners attend their courses in remote or hybrid systems find it difficult to follow one size fits all courses. These difficulties have increased with the pandemic, lockdown, and the stress they cause. Hence, the role of adaptive systems to recommend personalized learning resources according to the learner's profile. The purpose of this paper is to design a system for recommending learning objects according learner's condition, including his mental state, his COVID-19 history, as well as his social situation and ability to connect to the e-learning system on a regular basis. In this article, we present an architecture of a recommendation system for personalized learning objects based on ontologies and on rule-based reasoning, and we will also describe the inference rules required for the adaptation of the educational content to the needs of the learners, taking into account the learner’s health and mental state, as well as his social situation. The system designed, and validated using the unified modeling language (UML). It additionally allows teachers to have a holistic view of learners’ progress and situations.
Volume: 12
Issue: 1
Page: 515-523
Publish at: 2022-02-01

Classification of three pathological voices based on specific features groups using support vector machine

10.11591/ijece.v12i1.pp946-956
Muneera Altayeb , Amani Al-Ghraibah
Determining and classifying pathological human sounds are still an interesting area of research in the field of speech processing. This paper explores different methods of voice features extraction, namely: Mel frequency cepstral coefficients (MFCCs), zero-crossing rate (ZCR) and discrete wavelet transform (DWT). A comparison is made between these methods in order to identify their ability in classifying any input sound as a normal or pathological voices using support vector machine (SVM). Firstly, the voice signal is processed and filtered, then vocal features are extracted using the proposed methods and finally six groups of features are used to classify the voice data as healthy, hyperkinetic dysphonia, hypokinetic dysphonia, or reflux laryngitis using separate classification processes. The classification results reach 100% accuracy using the MFCC and kurtosis feature group. While the other classification accuracies range between~60% to~97%. The Wavelet features provide very good classification results in comparison with other common voice features like MFCC and ZCR features. This paper aims to improve the diagnosis of voice disorders without the need for surgical interventions and endoscopic procedures which consumes time and burden the patients. Also, the comparison between the proposed feature extraction methods offers a good reference for further researches in the voice classification area.
Volume: 12
Issue: 1
Page: 946-956
Publish at: 2022-02-01

Sunfa Ata Zuyan machine learning models for moon phase detection: algorithm, prototype and performance comparison

10.12928/telkomnika.v20i1.22338
Ata Jahangir; Jiangxi University of Science and Technology Moshayedi , Zu-yan; Jiangxi University of Science and Technology Chen , Liefa; Jiangxi University of Science and Technology Liao , Shuai; Swansea University Li
The history recorded moon as the most inspiring object in the sky, but it combined with visibility issues to study the phases. This research paper proposes a novel algorithm named Sunfa Ata Zuyan (SAZ), which is meant to extend the shape detection algorithms to aim for lunar phase deceleration and overcome the difficulties encountered by the previous methods to find the moon and determine its phase. The paper sets to investigate two aims. First, propose the add-on algorithm SAZ to determine the lunar phase's data faster. Secondly, evaluate the Raspberry Pi as the main CPU due to its compact size and power as the primary processor based on the idea of a portable designed system. Then to examine the ability of the SAZ algorithm, it's combined with famous algorithms like hue, saturation and value (HSV), Canny, erosion, shape detection, and binarization has been tested on both personal computers (PC) and Raspberry Pi with the same images being compared. The results show that SAZ will help the shape detection algorithm to find the object and disclose the moon phases. Furthermore, the Raspberry Pi, functioning as a CPU, can perform as a hand-to-hand system to determine the lunar phase as a compact portable remote sensing structure.
Volume: 20
Issue: 1
Page: 129-140
Publish at: 2022-02-01

Extending lifetime of heterogeneous wireless sensor networks using spider monkey optimization routing protocol

10.12928/telkomnika.v20i1.20984
Imad; College of Computer Science and Information Technology, University of Basrah S. Alshawi , Zainab Ali; Department of Pathological Analysis Science, College of Science, University of Basrah Abbood , Asaad A.; College of Computer Science and Information Technology, University of Basrah Alhijaj
The nodes of wireless sensor networks (WSN) are severely restricted in terms of computing capabilities, limited communications, and limited power supplies, as it is difficult or impossible to replace or recharge the sensor battery. Consequently, the energy of nodes is one of the most important resources to consider when designing of WSNs. So, most of the routing protocols in WSNs are to assure the saving of energy as a significant aim for improvement. Nevertheless, just providing power is not sufficient to extend the lifetime of WSN. Where unbalance energy depletion in WSNs is a challenging issue often leading to splits the network and reduces its lifetime, also retrogression of its performance. This paper, therefore, uses a powerful routing protocol named spider monkey optimization routing protocol (SMORP) to generate an optimal data routing of the pathway for heterogeneous WSNs (HWSNs). SMORP, here, can compute the best way from a sensor to the sink through the cluster head, inside the intra-cluster, and the inter-cluster respectively. For this purpose and the organization of heterogeneous nodes, this paper uses the clustering partition. The simulation results revealed that SMORP significantly improves in terms of data latency reduction, stabilizing depletion of energy, and maximizing the network lifetime for HWSNs.
Volume: 20
Issue: 1
Page: 212-220
Publish at: 2022-02-01

3D chaos graph deep learning method to encrypt and decrypt digital image

10.11591/ijeecs.v25.i2.pp941-951
Daniah Abdul Qahar Shakir , Ali Jbaeer Dawood
We live in technological age development’s where many important data transmitted electronically from one device to another and in every place. Deep learning algorithms have facilitated the process of encoding and decoding digital images. Chaotic graph systems, on the other hand, are one of the most recent techniques utilized to encode image data based on the methods of cryptography. The chaos maps are divided into two main aspects, first one deals with the 1D map which requires fewer features and can be developed easily, the second one is the high dimensional map which is more complex than the 1D graph and it requires more features, more parameters, and it is relatively hard to develop. In this paper, we present a method for image encoding and decoding electronically using deep learning, the proposed algorithm was developed by using the hybrid technique of 3D chaos map generation, the best case of the proposed technique gave the following results: The average entropy calculation was (7.4838) before image encryption and (7.9896) after image encryption with average number of pixels change rate (NPCR) of (99.7085%) and the unified average changing intensity (UACI) of (33.2030%) which are the best outcomes when compared to other similar works.
Volume: 25
Issue: 2
Page: 941-951
Publish at: 2022-02-01

An internet of things framework for real-time aquatic environment monitoring using an Arduino and sensors

10.11591/ijece.v12i1.pp826-833
Md. Monirul Islam , Mohammad Abul Kashem , Jia Uddin
Aquaculture is the farming of aquatic organisms in natural, controlled marine and freshwater environments. The real-time monitoring of aquatic environmental parameters is very important in fish farming. Internet of things (IoT) can play a vital role in the real-time monitoring. This paper presents an IoT framework for the efficient monitoring and effective control of different aquatic environmental parameters related to the water. The proposed system is implemented as an embedded system using sensors and an Arduino. Different sensors including pH, temperature, and turbidity, ultrasonic are placed in cultivating pond water and each of them is connected to a common microcontroller board built on an Arduino Uno. The sensors read the data from the water and store it as a comma-separated values (CSV) file in an IoT cloud named ThingSpeak through the Arduino microcontroller. To validate the experiment, we collected data from 5 ponds of various sizes and environments. After experimental evaluation, it was observed among 5 ponds, only three ponds were perfect for fish farming, where these 3 ponds only satisfied the standard reference values of pH (6.5-8.5), temperature (16-24 °C), turbidity (below 10 ntu), conductivity (970-1825 μS/cm), and depth (1-4) meter. At the end of this paper, a complete hardware implementation of this proposed IoT framework for a real-time aquatic environment monitoring system is presented.
Volume: 12
Issue: 1
Page: 826-833
Publish at: 2022-02-01

A novel fast-qualitative balance test method of screening for vestibular disorder patients

10.11591/ijeecs.v25.i2.pp910-919
Tran Anh Vu , Hoang Quang Huy , Le Van Tuan , Pham Thi Viet Huong
Body balance test is one of the methods of assessing vestibular level. However, the results are still qualitative, depending on the subjectivity of the doctor. This study proposes a new, low-cost method to quantitatively determine the degree of body imbalance. The proposal includes a low-cost laser source, a proposed rectangular paper frame, a camera, and a computer. The rectangular frame is mounted on the patient. The laser source is fixed and projected onto this rectangular frame. The laser projection point is taken as the origin point to evaluate the movement of the frame, which is also the movement of the patient’s body. This rectangular frame is pre-marked with points to get more accuracy of the position of the laser point. Therefore, this measurement is not affected by the position of the camera during recording. The video is then procecced by computer to determine the position of laser point, it is also presented the movement of the patient’s body. Initial trials were conducted on vestibular and normal patients. The results show that there is a clear difference in the balance of the vestibular and healthy people. The proposed method can be used to support quantitative screening for vestibular disease.
Volume: 25
Issue: 2
Page: 910-919
Publish at: 2022-02-01

Energy harvesting maximization by integration of distributed generation based on economic benefits

10.11591/ijeecs.v25.i2.pp610-625
Tarek A. Boghdady , Samar G. A. Nasser , Essam El-Din Aboul Zahab
The purpose of distributed generation systems (DGS) is to enhance the distribution system (DS) performance to be better known with its benefits in the power sector as installing distributed generation (DG) units into the DS can introduce economic, environmental and technical benefits. Those benefits can be obtained if the DG units' site and size is properly determined. The aim of this paper is studying and reviewing the effect of connecting DG units in the DS on transmission efficiency, reactive power loss and voltage deviation in addition to the economical point of view and considering the interest and inflation rate. Whale optimization algorithm (WOA) is introduced to find the best solution to the distributed generation penetration problem in the DS. The result of WOA is compared with the genetic algorithm (GA), particle swarm optimization (PSO), and grey wolf optimizer (GWO). The proposed solutions methodologies have been tested using MATLAB software on IEEE 33 standard bus system.
Volume: 25
Issue: 2
Page: 610-625
Publish at: 2022-02-01

Low power architecture of logic gates using adiabatic techniques

10.11591/ijeecs.v25.i2.pp805-813
Minakshi Sanadhya , Devendra Kumar Sharma
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
Volume: 25
Issue: 2
Page: 805-813
Publish at: 2022-02-01

Hybrid scheduling algorithms in cloud computing: a review

10.11591/ijece.v12i1.pp880-895
Neeraj Arora , Rohitash Kumar Banyal
Cloud computing is one of the emerging fields in computer science due to its several advancements like on-demand processing, resource sharing, and pay per use. There are several cloud computing issues like security, quality of service (QoS) management, data center energy consumption, and scaling. Scheduling is one of the several challenging problems in cloud computing, where several tasks need to be assigned to resources to optimize the quality of service parameters. Scheduling is a well-known NP-hard problem in cloud computing. This will require a suitable scheduling algorithm. Several heuristics and meta-heuristics algorithms were proposed for scheduling the user's task to the resources available in cloud computing in an optimal way. Hybrid scheduling algorithms have become popular in cloud computing. In this paper, we reviewed the hybrid algorithms, which are the combinations of two or more algorithms, used for scheduling in cloud computing. The basic idea behind the hybridization of the algorithm is to take useful features of the used algorithms. This article also classifies the hybrid algorithms and analyzes their objectives, quality of service (QoS) parameters, and future directions for hybrid scheduling algorithms.
Volume: 12
Issue: 1
Page: 880-895
Publish at: 2022-02-01

Comparison between P&O and SSO techniques based MPPT algorithm for photovoltaic systems

10.11591/ijece.v12i1.pp32-40
Mohamed Hussein Mohamedy Ali , Mahmoud Mohammed Sayed Mohamed , Ninet Mohamed Ahmed , Mohamed Bayoumy Abdelkader Zahran
Solar photovoltaic (SPV) systems are a renewable source of energy that are environmentally friendly and recyclable nature. When the solar panel is connected directly to the load, the power delivered to the load is not the optimal power. It is therefore important to obtain maximum power from SPV systems for enhancing efficiency. Various maximum power point tracking (MPPT) techniques of SPV systems were proposed. Traditional MPPT techniques are commonly limited to uniform weather conditions. This paper presents a study of MPPT for photovoltaic (PV) systems. The study includes a discussion of different MPPT techniques and performs comparison for the performance of the two MPPT techniques, the P&O algorithm, and salp swarm optimization (SSO) algorithm. MATLAB simulations are performed under step changes in irradiation. The results of SSO show that the search time of maximum power point (MPP) is significantly decreased and the MPP is obtained in the shortest time with high accuracy and minimum oscillations in the generated power when compared with P&O.
Volume: 12
Issue: 1
Page: 32-40
Publish at: 2022-02-01

Reconfigurable of current-mode differentiator and integrator based-on current conveyor transconductance amplifiers

10.11591/ijece.v12i1.pp208-218
Soontorn Srisoontorn , Angkana Charoenmee , Suphaphorn Panikhom , Thitiporn Janda , Suttipong Fungdetch , Khunpan Patimaprakorn , Adirek Jantakun
The reconfigurable of the differentiator and integrator based on current conveyor transconductance amplifiers (CCTAs) have been presented in this paper. The proposed configurations are provided with two CCTAs and grounded elements. The configurations can be operated in the differentiator and integrator by selecting external passive elements. The input and output currents have low and high impedances, respectively; therefore, the configurations can be cascaded without additional current buffer. The proposed configurations can be electronically tuned by external direct current (DC) bias currents, and it also has slight fluctuation with temperature. An application of universal filter is demonstrated to confirm the ability of the proposed configurations. The results of simulation with Pspice program are accordance with the theoretical analysis.
Volume: 12
Issue: 1
Page: 208-218
Publish at: 2022-02-01

Agriculture data visualization and analysis using data mining techniques: application of unsupervised machine learning

10.12928/telkomnika.v20i1.18938
Kunal; IIIT Bhubaneswar, Odisha, India Badapanda , Debani Prasad; IIIT Bhubaneswar, Odisha, India Mishra , Surender Reddy; Woosong University Salkuti
Unsupervised machine learning is one of the accepted platforms for applying a broad data analytics challenge that involves the way to identify secret trends, unexplained associations, and other significant data from a wide dispersed dataset. The precise yield estimate for the various crops involved in the planning is a critical problem for agricultural planning. To achieve realistic and effective solutions to this problem, data mining techniques are an essential approach. Applying distplot combined with kernel density estimate (KDE) in this paper to visualize the probability density of disseminated datasets of vast crop deals for crop planning. This paper focuses on analyzing and segmenting agricultural data and determining optimal parameters to maximize crop yield using data mining techniques such as K-means clustering and principal component analysis (PCA)
Volume: 20
Issue: 1
Page: 98-108
Publish at: 2022-02-01
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