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E. Dhiravidachelvi¹, M.Suresh Kumar², L. D. Vijay Anand³, D. Pritima⁴, Seifedine Kadry⁵, Byeong-Gwon Kang⁶, Yunyoung Nam^7,*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 961-977, 2023, DOI:10.32604/csse.2023.024612 - 15 June 2022
Abstract Human Activity Recognition (HAR) has been made simple in recent years, thanks to recent advancements made in Artificial Intelligence (AI) techniques. These techniques are applied in several areas like security, surveillance, healthcare, human-robot interaction, and entertainment. Since wearable sensor-based HAR system includes in-built sensors, human activities can be categorized based on sensor values. Further, it can also be employed in other applications such as gait diagnosis, observation of children/adult’s cognitive nature, stroke-patient hospital direction, Epilepsy and Parkinson’s disease examination, etc. Recently-developed Artificial Intelligence (AI) techniques, especially Deep Learning (DL) models can be deployed to accomplish… More >

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3019

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1351

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Narendran Sobanapuram Muruganandam, Umamakeswari Arumugam^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 979-989, 2023, DOI:10.32604/csse.2023.024943 - 15 June 2022
Abstract In forecasting real time environmental factors, large data is needed to analyse the pattern behind the data values. Air pollution is a major threat towards developing countries and it is proliferating every year. Many methods in time series prediction and deep learning models to estimate the severity of air pollution. Each independent variable contributing towards pollution is necessary to analyse the trend behind the air pollution in that particular locality. This approach selects multivariate time series and coalesce a real time updatable autoregressive model to forecast Particulate matter (PM) PM2.5. To perform experimental analysis the… More >

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2010

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1232

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Sathit Prasomphan^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 991-1007, 2023, DOI:10.32604/csse.2023.025452 - 15 June 2022
Abstract Establishing a system for measuring plant health and bacterial infection is critical in agriculture. Previously, the farmers themselves, who observed them with their eyes and relied on their experience in analysis, which could have been incorrect. Plant inspection can determine which plants reflect the quantity of green light and near-infrared using infrared light, both visible and eye using a drone. The goal of this study was to create algorithms for assessing bacterial infections in rice using images from unmanned aerial vehicles (UAVs) with an ensemble classification technique. Convolution neural networks in unmanned aerial vehicles image… More >

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1926

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926

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ARTICLE

Mini Prince^1,*, P. M. Joe Prathap²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1009-1024, 2023, DOI:10.32604/csse.2023.024277 - 15 June 2022
Abstract Most modern technologies, such as social media, smart cities, and the internet of things (IoT), rely on big data. When big data is used in the real-world applications, two data challenges such as class overlap and class imbalance arises. When dealing with large datasets, most traditional classifiers are stuck in the local optimum problem. As a result, it’s necessary to look into new methods for dealing with large data collections. Several solutions have been proposed for overcoming this issue. The rapid growth of the available data threatens to limit the usefulness of many traditional methods.… More >

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2051

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1028

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S. R. Sylaja Vallee Narayan^1,*, R. Jemila Rose²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1025-1038, 2023, DOI:10.32604/csse.2023.022564 - 15 June 2022
Abstract Cervical cancer is a disease that develops in the cervix’s tissue. Cervical cancer mortality is being reduced due to the growth of screening programmers. Cervical cancer screening is a big issue because the majority of cervical cancer screening treatments are invasive. Hence, there is apprehension about standard screening procedures, as well as the time it takes to learn the results. There are different methods for detecting problems in the cervix using Pap (Papanicolaou-stained) test, colposcopy, Computed Tomography (CT), Magnetic Resonance Image (MRI) and ultrasound. To obtain a clear sketch of the infected regions, using a… More >

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1684

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1036

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ARTICLE

Hani Al-Mimi^1,*, Yousef Alrabanah², Mosleh M. Abualhaj³, Sumaya N. Al-khatib³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1039-1049, 2023, DOI:10.32604/csse.2023.024338 - 15 June 2022
Abstract The demand for the telecommunication services, such as IP telephony, has increased dramatically during the COVID-19 pandemic lockdown. IP telephony should be enhanced to provide the expected quality. One of the issues that should be investigated in IP telephony is bandwidth utilization. IP telephony produces very small speech samples attached to a large packet header. The header of the IP telephony consumes a considerable share of the bandwidth allotted to the IP telephony. This wastes the network's bandwidth and influences the IP telephony quality. This paper proposes a mechanism (called Smallerize) that reduces the bandwidth More >

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1819

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764

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K. Vignesh^1,*, A. Askarunisa², A. M. Abirami³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1051-1067, 2023, DOI:10.32604/csse.2023.024475 - 15 June 2022
Abstract Crop yield has been predicted using environmental, land, water, and crop characteristics in a prospective research design. When it comes to predicting crop production, there are a number of factors to consider, including weather conditions, soil qualities, water levels and the location of the farm. A broad variety of algorithms based on deep learning are used to extract useful crops for forecasting. The combination of data mining and deep learning creates a whole crop yield prediction system that is able to connect raw data to predicted crop yields. The suggested study uses a Discrete Deep… More >

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1086

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1

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Waqar Hafeez¹, Nazrina Aziz^1,2,*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1069-1079, 2023, DOI:10.32604/csse.2023.022047 - 15 June 2022
Abstract Acceptance sampling is used to decide either the whole lot will be accepted or rejected, based on inspection of randomly sampled items from the same lot. As an alternative to traditional sampling plans, it is possible to use Bayesian approaches using previous knowledge on process variation. This study presents a Bayesian two-sided group chain sampling plan (BTSGChSP) by using various combinations of design parameters. In BTSGChSP, inspection is based on preceding as well as succeeding lots. Poisson function is used to derive the probability of lot acceptance based on defective and non-defective products. Gamma distribution… More >

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1283

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659

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ARTICLE

P. Immaculate Rexi Jenifer^1,*, S. Kannan²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1081-1097, 2023, DOI:10.32604/csse.2023.026128 - 15 June 2022
Abstract Medical image classification becomes a vital part of the design of computer aided diagnosis (CAD) models. The conventional CAD models are majorly dependent upon the shapes, colors, and/or textures that are problem oriented and exhibited complementary in medical images. The recently developed deep learning (DL) approaches pave an efficient method of constructing dedicated models for classification problems. But the maximum resolution of medical images and small datasets, DL models are facing the issues of increased computation cost. In this aspect, this paper presents a deep convolutional neural network with hierarchical spiking neural network (DCNN-HSNN) for… More >

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1816

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990

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ARTICLE

B. Dhiyanesh^1,*, K. Karthick², R. Radha³, Anita Venaik⁴
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1099-1107, 2023, DOI:10.32604/csse.2023.024691 - 15 June 2022
Abstract Cloud computing (CC) is an advanced technology that provides access to predictive resources and data sharing. The cloud environment represents the right type regarding cloud usage model ownership, size, and rights to access. It introduces the scope and nature of cloud computing. In recent times, all processes are fed into the system for which consumer data and cache size are required. One of the most security issues in the cloud environment is Distributed Denial of Service (DDoS) attacks, responsible for cloud server overloading. This proposed system ID3 (Iterative Dichotomiser 3) Maximum Multifactor Dimensionality Posteriori Method… More >

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1531

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831

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Ishani Mishra^1,*, Sanjay Jain², Vivek Maik³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1109-1123, 2023, DOI:10.32604/csse.2023.025999 - 15 June 2022
Abstract In wireless body sensor network (WBSN), the set of electrocardiogram (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. While transmitting these collected data some adversaries may capture and misuse it due to the compromise of security. So, the major aim of this work is to enhance secure transmission of ECG signal in WBSN. To attain this goal, we present Pity Beetle Swarm Optimization Algorithm (PBOA) based Elliptic Galois Cryptography (EGC) with Chaotic Neural Network. To optimize the key generation More >

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1455

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764

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Feslin Anish Mon Solomon^1,*, Godfrey Winster Sathianesan², R. Ramesh³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1125-1142, 2023, DOI:10.32604/csse.2023.024292 - 15 June 2022
Abstract Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This is applied greatly in business enterprises and government sectors for delivering the services to their customers, clients and citizens. But, the interaction is successful only based on the trust that each device has on another. Thus trust is very much essential for a social network. As Internet of Things have access over sensitive information, it urges to many threats that lead data management to risk. This issue is addressed by trust management that help… More >

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1529

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1127

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Kotchaporn Karoon, Yupaporn Areepong^*, Saowanit Sukparungsee
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1143-1160, 2023, DOI:10.32604/csse.2023.025420 - 15 June 2022
Abstract The Extended Exponentially Weighted Moving Average (extended EWMA) control chart is one of the control charts and can be used to quickly detect a small shift. The performance of control charts can be evaluated with the average run length (ARL). Due to the deriving explicit formulas for the ARL on a two-sided extended EWMA control chart for trend autoregressive or trend AR(p) model has not been reported previously. The aim of this study is to derive the explicit formulas for the ARL on a two-sided extended EWMA control chart for the trend AR(p) model as well as… More >

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1308

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640

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ARTICLE

Romany F. Mansour^1,*, Eatedal Alabdulkreem²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1161-1169, 2023, DOI:10.32604/csse.2023.023307 - 15 June 2022
Abstract The analysis of remote sensing image areas is needed for climate detection and management, especially for monitoring flood disasters in critical environments and applications. Satellites are mostly used to detect disasters on Earth, and they have advantages in capturing Earth images. Using the control technique, Earth images can be used to obtain detailed terrain information. Since the acquisition of satellite and aerial imagery, this system has been able to detect floods, and with increasing convenience, flood detection has become more desirable in the last few years. In this paper, a Big Data Set-based Progressive Image More >

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2024

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1030

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ARTICLE

Ligang Yuan^1,*, Jiazhi Jin¹, Yan Xu², Ningning Zhang³, Bing Zhang⁴
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1171-1185, 2023, DOI:10.32604/csse.2023.027221 - 15 June 2022
Abstract Weather is a key factor affecting the control of air traffic. Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air traffic flow management. Current researches mostly use traditional machine learning methods to extract features of weather scenes, and clustering algorithms to divide similar scenes. Inspired by the excellent performance of deep learning in image recognition, this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering (IDCEC), which uses the combination of the encoding layer and the decoding… More >

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1609

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1675

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G. Rajeshkumar^1,*, M. Vinoth Kumar², K. Sailaja Kumar³, Surbhi Bhatia⁴, Arwa Mashat⁵, Pankaj Dadheech⁶
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1187-1200, 2023, DOI:10.32604/csse.2023.026137 - 15 June 2022
Abstract A Mobile Ad hoc Network (MANET) is a group of low-power consumption of wireless mobile nodes that configure a wireless network without the assistance of any existing infrastructure/centralized organization. The primary aim of MANETs is to extend flexibility into the self-directed, mobile, and wireless domain, in which a cluster of autonomous nodes forms a MANET routing system. An Intrusion Detection System (IDS) is a tool that examines a network for malicious behavior/policy violations. A network monitoring system is often used to report/gather any suspicious attacks/violations. An IDS is a software program or hardware system that… More >

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2073

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786

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ARTICLE

Darpan Majumder^1,*, S. Mohan Kumar²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1201-1217, 2023, DOI:10.32604/csse.2023.024868 - 15 June 2022
Abstract Edge computing is a cloud computing extension where physical computers are installed closer to the device to minimize latency. The task of edge data centers is to include a growing abundance of applications with a small capability in comparison to conventional data centers. Under this framework, Federated Learning was suggested to offer distributed data training strategies by the coordination of many mobile devices for the training of a popular Artificial Intelligence (AI) model without actually revealing the underlying data, which is significantly enhanced in terms of privacy. Federated learning (FL) is a recently developed decentralized… More >

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1793

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963

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ARTICLE

Ashit Kumar Dutta^1,*, Manal Al Faraj¹, Yasser Albagory², Mohammad zeid M Alzamil¹, Abdul Rahaman Wahab Sait³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1219-1231, 2023, DOI:10.32604/csse.2023.026467 - 15 June 2022
Abstract A cyber physical energy system (CPES) involves a combination of processing, network, and physical processes. The smart grid plays a vital role in the CPES model where information technology (IT) can be related to the physical system. At the same time, the machine learning (ML) models find useful for the smart grids integrated into the CPES for effective decision making. Also, the smart grids using ML and deep learning (DL) models are anticipated to lessen the requirement of placing many power plants for electricity utilization. In this aspect, this study designs optimal multi-head attention based… More >

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1354

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881

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ARTICLE

R.M. Bhavadharini^1,*, S. Karthik²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1233-1250, 2023, DOI:10.32604/csse.2023.025461 - 15 June 2022
Abstract With recent advancements made in wireless communication techniques, wireless sensors have become an essential component in both data collection as well as tracking applications. Wireless Sensor Network (WSN) is an integral part of Internet of Things (IoT) and it encounters different kinds of security issues. Blockchain is designed as a game changer for highly secure and effective digital society. So, the current research paper focuses on the design of Metaheuristic-based Clustering with Routing Protocol for Blockchain-enabled WSN abbreviated as MCRP-BWSN. The proposed MCRP-BWSN technique aims at deriving a shared memory scheme using blockchain technology and… More >

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1875

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1164

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ARTICLE

S. Rajalakshmi^1,*, K. R. Santha²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1251-1262, 2023, DOI:10.32604/csse.2023.024036 - 15 June 2022
Abstract A recommender system is an approach performed by e-commerce for increasing smooth users’ experience. Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions. This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-commerce. This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system. The feature selection's objective is to pick a feature subset having the least feature similarity as well as highest… More >

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1469

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804

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ARTICLE

Thanh X. Le, An T. Le, Quang H. Nguyen^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1263-1278, 2023, DOI:10.32604/csse.2023.026234 - 15 June 2022
Abstract In recent years, speech synthesis systems have allowed for the production of very high-quality voices. Therefore, research in this domain is now turning to the problem of integrating emotions into speech. However, the method of constructing a speech synthesizer for each emotion has some limitations. First, this method often requires an emotional-speech data set with many sentences. Such data sets are very time-intensive and labor-intensive to complete. Second, training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning. In addition, each model for each… More >

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1977

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773

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ARTICLE

C. Aswini^1,*, M. L. Valarmathi²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1279-1293, 2023, DOI:10.32604/csse.2023.022023 - 15 June 2022
Abstract In a non-static information exchange network, routing is an overly complex task to perform, which has to satisfy all the needs of the network. Software Defined Network (SDN) is the latest and widely used technology in the future communication networks, which would provide smart routing that is visible universally. The various features of routing are supported by the information centric network, which minimizes the congestion in the dataflow in a network and provides the content awareness through its mined mastery. Due to the advantages of the information centric network, the concepts of the information-centric network… More >

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1804

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890

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Sathit Prasomphan^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1295-1307, 2023, DOI:10.32604/csse.2023.025293 - 15 June 2022
Abstract Fine-grained image classification is a challenging research topic because of the high degree of similarity among categories and the high degree of dissimilarity for a specific category caused by different poses and scales. A cultural heritage image is one of the fine-grained images because each image has the same similarity in most cases. Using the classification technique, distinguishing cultural heritage architecture may be difficult. This study proposes a cultural heritage content retrieval method using adaptive deep learning for fine-grained image retrieval. The key contribution of this research was the creation of a retrieval model that… More >

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1888

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1003

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Junaid Rashid¹, Sumera Kanwal², Muhammad Wasif Nisar², Jungeun Kim^1,*, Amir Hussain³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1309-1324, 2023, DOI:10.32604/csse.2023.026018 - 15 June 2022
Abstract In project management, effective cost estimation is one of the most crucial activities to efficiently manage resources by predicting the required cost to fulfill a given task. However, finding the best estimation results in software development is challenging. Thus, accurate estimation of software development efforts is always a concern for many companies. In this paper, we proposed a novel software development effort estimation model based both on constructive cost model II (COCOMO II) and the artificial neural network (ANN). An artificial neural network enhances the COCOMO model, and the value of the baseline effort constant More >

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1822

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1038

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G. Karthikeyan^*, G. Kousalya
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1325-1340, 2023, DOI:10.32604/csse.2023.026356 - 15 June 2022
Abstract Generalized Tonic Clonic Seizure (GTCS) is a form of epileptic seizure in which a patient loses control over their entire body, ultimately leading to loss of consciousness. The Vagus Nerve Stimulator (VNS) is a tool/method for treating epileptic episodes that sends counter-electrical stimulations to the Vagus Nerve in order to mitigate epileptic signals from the brain. The machine is a stand-alone device that depends on human decision-making. The proposed framework uses an IoT and Blockchain oversight mechanism to augment the device's transparency. The system counteracts against false-activation by monitoring the patient's vitals through a smart… More >

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1491

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724

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Valliappan Raman¹, Khaled ELKarazle^2,*, Patrick Then²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1341-1355, 2023, DOI:10.32604/csse.2023.026674 - 15 June 2022
Abstract Given the current expansion of the computer vision field, several applications that rely on extracting biometric information like facial gender for access control, security or marketing purposes are becoming more common. A typical gender classifier requires many training samples to learn as many distinguishable features as possible. However, collecting facial images from individuals is usually a sensitive task, and it might violate either an individual's privacy or a specific data privacy law. In order to bridge the gap between privacy and the need for many facial images for deep learning training, an artificially generated dataset… More >

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1762

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872

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3

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Christy James Jose^1,*, M. S. Rajasree²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1357-1372, 2023, DOI:10.32604/csse.2023.025672 - 15 June 2022
Abstract The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like, fingerprint or face. Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’ identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session. However, divergent issues remain unaddressed. This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called, Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s… More >

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1523

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734

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P. Ramadevi^1,*, T. Jayasankar¹, V. Dinesh², M. Dhamodaran³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1373-1385, 2023, DOI:10.32604/csse.2023.026603 - 15 June 2022
Abstract Recently, with the growth of cyber physical systems (CPS), several applications have begun to deploy in the CPS for connecting the cyber space with the physical scale effectively. Besides, the cloud computing (CC) enabled CPS offers huge processing and storage resources for CPS that finds helpful for a range of application areas. At the same time, with the massive development of applications that exist in the CPS environment, the energy utilization of the cloud enabled CPS has gained significant interest. For improving the energy effectiveness of the CC platform, virtualization technologies have been employed for… More >

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1460

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982

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S. Devi Mahalakshmi^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1387-1395, 2023, DOI:10.32604/csse.2023.027610 - 15 June 2022
Abstract The kidney is an important organ of humans to purify the blood. The healthy function of the kidney is always essential to balance the salt, potassium and pH levels in the blood. Recently, the failure of kidneys happens easily to human beings due to their lifestyle, eating habits and diabetes diseases. Early prediction of kidney stones is compulsory for timely treatment. Image processing-based diagnosis approaches provide a greater success rate than other detection approaches. In this work, proposed a kidney stone classification method based on optimized Transfer Learning(TL). The Deep Convolutional Neural Network (DCNN) models More >

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1595

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1129

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Qiuyu Hu¹, Wu Zeng^1,*, Yi Sheng¹, Jian Xu¹, Weihua Ou², Ruochen Tan³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1397-1408, 2023, DOI:10.32604/csse.2023.027980 - 15 June 2022
Abstract Heart rate is an important vital characteristic which indicates physical and mental health status. Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly. Therefore, the study of non-contact heart rate measurement methods is of great importance. Based on the principles of photoelectric volumetric tracing, we use a computer device and camera to capture facial images, accurately detect face regions, and to detect multiple facial images using a multi-target tracking algorithm. Then after the regional segmentation of the facial image, the signal acquisition of the region of interest is More >

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1942

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973

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A. M. Almohaimeed¹, El Amjed Hajlaoui^1,2,*, Ziyad M. Almohaimeed¹
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1409-1417, 2023, DOI:10.32604/csse.2023.025738 - 15 June 2022
Abstract This work demonstrates the design of a single band Electromagnetic Band Gap (EBG) antenna by employing an open stub EBG microstrip of a patch antenna for better achievements in terms of its performance to be utilized in a reconfigurable harvester to operate over a wide input power range. The EBG antenna has been used to gather RF energy and a FET-transistor has been obtainable to determine and control the power flow with the intention to operate at the same time for a different level of input power. The measured data of the EBG antenna shows… More >

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1399

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891

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Ashit Kumar Dutta^1,*, Yasser Albagory², Manal Al Faraj¹, Majed Alsanea³, Abdul Rahaman Wahab Sait⁴
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1419-1432, 2023, DOI:10.32604/csse.2023.027377 - 15 June 2022
Abstract Accurate soil prediction is a vital parameter involved to decide appropriate crop, which is commonly carried out by the farmers. Designing an automated soil prediction tool helps to considerably improve the efficacy of the farmers. At the same time, fuzzy logic (FL) approaches can be used for the design of predictive models, particularly, Fuzzy Cognitive Maps (FCMs) have involved the concept of uncertainty representation and cognitive mapping. In other words, the FCM is an integration of the recurrent neural network (RNN) and FL involved in the knowledge engineering phase. In this aspect, this paper introduces… More >

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1370

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824

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Tariq Mohammed Alqahtani^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1433-1449, 2023, DOI:10.32604/csse.2023.025594 - 15 June 2022
Abstract In recent years, huge volumes of healthcare data are getting generated in various forms. The advancements made in medical imaging are tremendous owing to which biomedical image acquisition has become easier and quicker. Due to such massive generation of big data, the utilization of new methods based on Big Data Analytics (BDA), Machine Learning (ML), and Artificial Intelligence (AI) have become essential. In this aspect, the current research work develops a new Big Data Analytics with Cat Swarm Optimization based deep Learning (BDA-CSODL) technique for medical image classification on Apache Spark environment. The aim of… More >

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1036

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A. Jameer Basha¹, S. Aswini¹, S. Aarthini¹, Yunyoung Nam^2,*, Mohamed Abouhawwash^3,4
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1451-1466, 2023, DOI:10.32604/csse.2023.025503 - 15 June 2022
Abstract Wireless Sensor Network (WSN) technology is the real-time application that is growing rapidly as the result of smart environments. Battery power is one of the most significant resources in WSN. For enhancing a power factor, the clustering techniques are used. During the forward of data in WSN, more power is consumed. In the existing system, it works with Load Balanced Clustering Method (LBCM) and provides the lifespan of the network with scalability and reliability. In the existing system, it does not deal with end-to-end delay and delivery of packets. For overcoming these issues in WSN,… More >

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1547

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832

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A. Alice Blessie^1,*, P. Ramesh²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1467-1484, 2023, DOI:10.32604/csse.2023.025399 - 15 June 2022
Abstract The present progress of visual-based detection of the diseased area of a malady plays an essential part in the medical field. In that case, the image processing is performed to improve the image data, wherein it inhibits unintended distortion of image features or it enhances further processing in various applications and fields. This helps to show better results especially for diagnosing diseases. Of late the early prediction of cancer is necessary to prevent disease-causing problems. This work is proposed to identify lung cancer using lung computed tomography (CT) scan images. It helps to identify cancer… More >

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1353

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853

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Ahmed S. Almasoud^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1485-1498, 2023, DOI:10.32604/csse.2023.025190 - 15 June 2022
Abstract The latest advancements in computer vision and deep learning (DL) techniques pave the way to design novel tools for the detection and monitoring of forest fires. In this view, this paper presents an intelligent wild forest fire detection and alarming system using deep learning (IWFFDA-DL) model. The proposed IWFFDA-DL technique aims to identify forest fires at earlier stages through integrated sensors. The proposed IWFFDA-DL system includes an Integrated sensor system (ISS) combining an array of sensors that acts as the major input source that helps to forecast the fire. Then, the attention based convolution neural More >

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2137

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956

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ARTICLE

Pelin Yildirim Taser^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1499-1516, 2023, DOI:10.32604/csse.2023.028083 - 15 June 2022
Abstract Predictive Maintenance is a type of condition-based maintenance that assesses the equipment's states and estimates its failure probability and when maintenance should be performed. Although machine learning techniques have been frequently implemented in this area, the existing studies disregard to the natural order between the target attribute values of the historical sensor data. Thus, these methods cause losing the inherent order of the data that positively affects the prediction performances. To deal with this problem, a novel approach, named Ordinal Multi-dimensional Classification (OMDC), is proposed for estimating the conditions of a hydraulic system's four components by… More >

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1673

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819

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Ashit Kumar Dutta^1,*, Yasser Albagory², Manal Al Faraj¹, Yasir A. M. Eltahir³, Abdul Rahaman Wahab Sait⁴
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1517-1529, 2023, DOI:10.32604/csse.2023.026482 - 15 June 2022
Abstract The recently developed machine learning (ML) models have the ability to obtain high detection rate using biomedical signals. Therefore, this article develops an Optimal Sparse Autoencoder based Sleep Stage Classification Model on Electroencephalography (EEG) Biomedical Signals, named OSAE-SSCEEG technique. The major intention of the OSAE-SSCEEG technique is to find the sleep stage disorders using the EEG biomedical signals. The OSAE-SSCEEG technique primarily undergoes preprocessing using min-max data normalization approach. Moreover, the classification of sleep stages takes place using the Sparse Autoencoder with Smoothed Regularization (SAE-SR) with softmax (SM) approach. Finally, the parameter optimization of the More >

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786

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N. Krishnammal^1,*, C. Kalaiarasan², A. Bharathi³
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1531-1549, 2023, DOI:10.32604/csse.2023.024251 - 15 June 2022
Abstract Link asymmetry in wireless mesh access networks (WMAN) of Mobile ad-hoc Networks (MANETs) is due mesh routers’ transmission range. It is depicted as significant research challenges that pose during the design of network protocol in wireless networks. Based on the extensive review, it is noted that the substantial link percentage is symmetric, i.e., many links are unidirectional. It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message. Therefore, the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asymmetric links. It paves the way to exploit… More >

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862

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Chin-Feng Lee, Kuo-Chung Chan^*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1551-1566, 2023, DOI:10.32604/csse.2023.026294 - 15 June 2022
Abstract Dual-image reversible data hiding (RDH) is a technique for hiding important messages. This technology can be used to safely deliver secret messages to the recipient through dual images in an open network without being easily noticed. The recipient of the image must receive the two stego-images before the secret message can be completely retrieved. Imperceptibility is one of the main advantages of data hiding technology; to increase the imperceptibility, the quality requirements of the stego-images are relatively important. A dual steganographic image RDH method, called a DS-CF scheme that can achieve a better steganographic image… More >

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862

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R. Gopi¹, R. Sheeba², K. Anguraj³, T. Chelladurai⁴, Haya Mesfer Alshahrani⁵, Nadhem Nemri^6,*, Tarek Lamoudan⁷
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1567-1582, 2023, DOI:10.32604/csse.2023.025216 - 15 June 2022
Abstract Rapid increase in the large quantity of industrial data, Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation, data sensing and collection, real-time data processing, and high request arrival rates. The classical intrusion detection system (IDS) is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity. To resolve these issues, this paper designs a new Chaotic Cuckoo Search Optimization Algorithm (CCSOA) with optimal wavelet kernel extreme learning machine (OWKELM) named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform. The CCSOA-OWKELM technique focuses on the design… More >

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1944

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991

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ARTICLE

P. Rahul^1,*, N. Kanthimathi¹, B. Kaarthick², M. Leeban Moses¹
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1583-1600, 2023, DOI:10.32604/csse.2023.027424 - 15 June 2022
Abstract Recently, the fundamental problem with Hybrid Mobile Ad-hoc Networks (H-MANETs) is to find a suitable and secure way of balancing the load through Internet gateways. Moreover, the selection of the gateway and overload of the network results in packet loss and Delay (DL). For optimal performance, it is important to load balance between different gateways. As a result, a stable load balancing procedure is implemented, which selects gateways based on Fuzzy Logic (FL) and increases the efficiency of the network. In this case, since gateways are selected based on the number of nodes, the Energy More >

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725

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ARTICLE

Ghassan Ahmed Ali¹, Thamer Mitib Ahmad Al Sariera^2,*, Muhammad Akram¹, Adel Sulaiman¹, Fekry Olayah¹
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1601-1616, 2023, DOI:10.32604/csse.2023.026119 - 15 June 2022
Abstract Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the… More >

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709

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ARTICLE

S. Sivanantham^1,*, V. Mohanraj², Y. Suresh², J. Senthilkumar²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1617-1631, 2023, DOI:10.32604/csse.2023.025893 - 15 June 2022
Abstract In the network security system, intrusion detection plays a significant role. The network security system detects the malicious actions in the network and also conforms the availability, integrity and confidentiality of data information resources. Intrusion identification system can easily detect the false positive alerts. If large number of false positive alerts are created then it makes intrusion detection system as difficult to differentiate the false positive alerts from genuine attacks. Many research works have been done. The issues in the existing algorithms are more memory space and need more time to execute the transactions of More >

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1

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ARTICLE

Qiang Wu¹, Zhaoyang Han², Ghulam Mohiuddin³, Yongjun Ren^1,*
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1633-1646, 2023, DOI:10.32604/csse.2023.030646 - 15 June 2022
Abstract In the data communication system, the real-time information interaction of communication device increases the risk of privacy sensitive data being tampered with. Therefore, maintaining data security is one of the most important issues in network data communication. Because the timestamp is the most important way to authenticate data in information interaction, it is very necessary to provide timestamp service in the data communication system. However, the existing centralized timestamp mechanism is difficult to provide credible timestamp service, and users can conspire with timestamping servers to forge timestamps. Therefore, this paper designs a distributed timestamp mechanism… More >

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753

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2

Open Access

ARTICLE

M. Usharani^1,*, B. Sakthivel², S. Gayathri Priya³, T. Nagalakshmi⁴, J. Shirisha⁵
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1647-1657, 2023, DOI:10.32604/csse.2023.027744 - 15 June 2022
Abstract Approximate computing is a popular field for low power consumption that is used in several applications like image processing, video processing, multimedia and data mining. This Approximate computing is majorly performed with an arithmetic circuit particular with a multiplier. The multiplier is the most essential element used for approximate computing where the power consumption is majorly based on its performance. There are several researchers are worked on the approximate multiplier for power reduction for a few decades, but the design of low power approximate multiplier is not so easy. This seems a bigger challenge for… More >

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837

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Joseph Sathiadhas Esra^1,*, Y. Sukhi²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1659-1678, 2023, DOI:10.32604/csse.2023.025969 - 15 June 2022
Abstract In the design of hearing aids (HA), the real-time speech-enhancement is done. The digital hearing aids should provide high signal-to-noise ratio, gain improvement and should eliminate feedback. In generic hearing aids the performance towards different frequencies varies and non uniform. Existing noise cancellation and speech separation methods drops the voice magnitude under the noise environment. The performance of the HA for frequency response is non uniform. Existing noise suppression methods reduce the required signal strength also. So, the performance of uniform sub band analysis is poor when hearing aid is concern. In this paper, a More >

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915

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Abdullah Alshehri^1,*, Nayeem Khan¹, Ali Alowayr¹, Mohammed Yahya Alghamdi²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1679-1689, 2023, DOI:10.32604/csse.2023.026526 - 15 June 2022
Abstract This paper proposes a novel framework to detect cyber-attacks using Machine Learning coupled with User Behavior Analytics. The framework models the user behavior as sequences of events representing the user activities at such a network. The represented sequences are then fitted into a recurrent neural network model to extract features that draw distinctive behavior for individual users. Thus, the model can recognize frequencies of regular behavior to profile the user manner in the network. The subsequent procedure is that the recurrent neural network would detect abnormal behavior by classifying unknown behavior to either regular or… More >

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953

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ARTICLE

K. Saraswathi^1,*, V. Mohanraj², Y. Suresh², J. Senthilkumar²
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1691-1702, 2023, DOI:10.32604/csse.2023.027987 - 15 June 2022
Abstract Nowadays, review systems have been developed with social media Recommendation systems (RS). Although research on RS social media is increasing year by year, the comprehensive literature review and classification of this RS research is limited and needs to be improved. The previous method did not find any user reviews within a time, so it gets poor accuracy and doesn’t filter the irrelevant comments efficiently. The Recursive Neural Network-based Trust Recommender System (RNN-TRS) is proposed to overcome this method’s problem. So it is efficient to analyse the trust comment and remove the irrelevant sentence appropriately. The… More >

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1968

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1014

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V. Arulalan^*, Dhananjay Kumar
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1703-1717, 2023, DOI:10.32604/csse.2023.026744 - 15 June 2022
Abstract Object detection and classification are the trending research topics in the field of computer vision because of their applications like visual surveillance. However, the vision-based objects detection and classification methods still suffer from detecting smaller objects and dense objects in the complex dynamic environment with high accuracy and precision. The present paper proposes a novel enhanced method to detect and classify objects using Hyperbolic Tangent based You Only Look Once V4 with a Modified Manta-Ray Foraging Optimization-based Convolution Neural Network. Initially, in the pre-processing, the video data was converted into image sequences and Polynomial Adaptive… More >

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1495