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Journal articles on the topic 'DATA BALANCING TECHNIQUE'

Author: Grafiati

Published: 11 September 2023

Last updated: 31 July 2025

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1

Febi Nur Salisah, Inggih Permana, Sanusi, and Shir Li Wang. "Evaluating the Impact of Data Balancing Techniques on the k-Nearest Neighbors Algorithm for Microarray Data Classification." Jurnal Inotera 10, no. 2 (2025): 261–71. https://doi.org/10.31572/inotera.vol10.iss2.2025.id497.

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Microarray data classification poses significant challenges in bioinformatics due to the nature of the data, which has a very high number of features but a limited number of samples, and an unbalanced class distribution. This condition can cause a decrease in the performance of classification models, including k-Nearest Neighbor (kNN). This study aims to evaluate the performance of the kNN algorithm in classifying unbalanced and balanced data. The balancing techniques used are Random Undersampling (RUS), Random Oversampling (ROS), and Synthetic Minority Over-sampling Technique (SMOTE). The dat

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Leah.W.Chege, Hellen.W.Waititu, and Cornelious.O.Nyakundi. "Comparative Analysis of K-Means and Divisive Clustering Techniques on Balanced Mental Health Data." Asian Journal of Probability and Statistics 26, no. 10 (2024): 64–79. http://dx.doi.org/10.9734/ajpas/2024/v26i10659.

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Effective Clustering of mental health data can provide significant insights into patterns and relationships that are critical for understanding mental health conditions. This study investigated various clustering techniques applied to balanced mental health data to avoid biases associated with an imbalanced data. Clustering of the balanced mental health data was done with respect to the area of Residence feature. Firstly, Random undersampling and SMOTE techniques were incorporated to the imbalanced data set as balancing techniques so as to improve model performance. Random Undersampling Techni

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Pranav, Bhokardankar* Harshal Sharma. "PROPOSED ALGORITHM FOR LOAD BALANCING ON CLOUD DATA CENTER." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 12 (2016): 702–5. https://doi.org/10.5281/zenodo.218895.

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Cloud servers are basically developed for supporting the efficient communication and the computation remotely. Thus a number of different time zone machines are able to find the services of resources and the computation. Thus each and every time these machines are working in order to resolve the end client request. But sometime these machines are loaded more then their capacity and does not perform as desired and some of the available processing units are considered to be free. This results in the performance loss in the computational servers. In order to find the optimum performance there is

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Economou, Nikos, and Antonis Vafidis. "Spectral balancing GPR data using time-variant bandwidth in the t-f domain." GEOPHYSICS 75, no. 3 (2010): J19—J27. http://dx.doi.org/10.1190/1.3374464.

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Ground-penetrating radar (GPR) sections encounter a resolution reduction with depth because, for electromagnetic (EM) waves propagating in the subsurface, attenuation is typically more pronounced at higher frequencies. To correct for these effects, we have applied a spectral balancing technique, using the S-transform (ST). This signal-processing technique avoids the drawbacks of inverse [Formula: see text] filtering techniques, namely, the need for estimation of the attenuation factor [Formula: see text] from the GPR section and instability caused by scattering effects that result from methods

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Pattanapairoj, Sirorat, Danaipong Chetchotsak, and Banchar Arnonkijpanich. "Hybrid Balancing Technique Using GRSOM and Bootstrap Algorithms for Classifiers with Imbalanced Data." Advanced Materials Research 931-932 (May 2014): 1375–81. http://dx.doi.org/10.4028/www.scientific.net/amr.931-932.1375.

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To deal with imbalanced data, this paper proposes a hybrid data balancing technique which incorporates both over and under-sampling approaches. This technique determines how much minority data should be grown as well as how much majority data should be reduced. In this manner, noise introduced to the data due to excessive over-sampling could be avoided. On top of that, the proposed data balancing technique helps to determine the appropriate size of the balanced data and thus computation time required for construction of classifiers would be more efficient. The data balancing technique over sam

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Muszala, S. P., D. A. Connors, J. J. Hack, and G. Alaghband. "The Promise of Load Balancing the Parameterization of Moist Convection Using a Model Data Load Index." Journal of Atmospheric and Oceanic Technology 23, no. 4 (2006): 525–37. http://dx.doi.org/10.1175/jtech1865.1.

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Abstract The parameterization of physical processes in atmospheric general circulation models contributes to load imbalances among individual processors of message-passing distributed-multiprocessor systems. Load imbalances increase the overall time to completion of a model run and should be eliminated or reduced as much as possible. Presented herein is a new technique that shows promise for load balancing the parameterization of moist convection found in the Community Climate System Model's (CCSM's) Community Atmosphere Model version 3 (CAM3). At the heart of this technique is a load index th

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Chetchotsak, Danaipong, Sirorat Pattanapairoj, and Banchar Arnonkijpanich. "Integrating new data balancing technique with committee networks for imbalanced data: GRSOM approach." Cognitive Neurodynamics 9, no. 6 (2015): 627–38. http://dx.doi.org/10.1007/s11571-015-9350-4.

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Muktar Yahuza, Yamani Idna Bin Idris, Ainuddin Wahid Bin Abdul Wahab, Mahdi A. Musa, and Adamu Abdullahi Garba. "A LIGHTWEIGHT AUTHENTICATION TECHNIQUE FOR SECURE COMMUNICATION OF EDGE/FOG DATA-CENTERS." Science Proceedings Series 2, no. 1 (2020): 76–81. http://dx.doi.org/10.31580/sps.v2i1.1319.

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Edge computing has significantly enhanced the capabilities of cloud computing. Edge data-centres are used for storing data of the end-user devices. Secure communication between the legitimate edge data-centres during the load balancing process has attracted industrial and academic researchers. Recently, Puthal et al. have proposed a technique for authenticating edge datacenters to enable secure load balancing. However, the resource-constraint nature of the edge data-centres is ignored. The scheme is characterized by complex computation and memory intensive cryptographic protocol. It is also vu

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ALANAZI, Fayez, and Aminu SULEIMAN. "Impact of Data Balancing and Feature Engineering on Accident Severity Models." Promet - Traffic&Transportation 37, no. 3 (2025): 665–90. https://doi.org/10.7307/ptt.v37i3.856.

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This study investigates the impacts of feature engineering techniques, including Clustering, Target Encoding and Anomaly Detection, in conjunction with data balancing methods, on the efficacy of machine learning models for predicting road accident severity. Automated Machine Learning (AutoML), Distributed Random Forest (DRF), Boosted Regression Trees (BRT) and Deep Learning models were evaluated on datasets that were balanced using the SMOTE (Synthetic Minority Over-Sampling Technique) and ADASYN (Adaptive Synthetic Sampling) techniques. Evaluation metrics such as Mean Squared Error (MSE), Roo

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Thilagavathi, N., D. Divya Dharani, R. Sasilekha, Vasundhara Suruliandi, and V. Rhymend Uthariaraj. "Energy Efficient Load Balancing in Cloud Data Center Using Clustering Technique." International Journal of Intelligent Information Technologies 15, no. 1 (2019): 84–100. http://dx.doi.org/10.4018/ijiit.2019010104.

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Cloud computing has seen tremendous growth in recent days. As a result of this, there has been a great increase in the growth of data centers all over the world. These data centers consume a lot of energy, resulting in high operating costs. The imbalance in load distribution among the servers in the data center results in increased energy consumption. Server consolidation can be handled by migrating all virtual machines in those underutilized servers. Migration causes performance degradation of the job, based on the migration time and number of migrations. Considering these aspects, the propos

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Tanvir Rahman Akash, Nusrat Jahan Sany, Lamia Akter, and Sanjida Akter Sarna. "Privacy - Preserving Technique in cybersecurity: Balancing Data Protection and User Rights." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 248–63. https://doi.org/10.32996/jcsts.2025.7.3.90.

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Increasing technological complexity of cyber threats creates a major challenge between securing data privacy and maintaining potent cybersecurity practices. The paper examines privacy-protecting security methods in cybersecurity by detailing organizational approaches to defend private information throughout the cyber threat detection and mitigation process. Organizations need to establish the appropriate levels of data security because implementations that limit privacy too much threaten their security capabilities but weak protection measures create vulnerabilities to data breaches. The resea

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Nidhi Ranjan, Et al. "Optimizing Cloud Computing Applications with a Data Center Load Balancing Algorithm." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 320–31. http://dx.doi.org/10.17762/ijritcc.v11i10.8495.

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Delivering scalable and on-demand computing resources to users through the usage of the cloud has become a common paradigm. The issues of effective resource utilisation and application performance optimisation, however, become more pressing as the demand for cloud services rises. In order to ensure efficient resource allocation and improve application performance, load balancing techniques are essential in dispersing incoming network traffic over several servers. The workload balancing in the context of cloud computing, particularly in the Infrastructure as a Service (IaaS) model, continues to

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Shivaliya, Shikha, and Vijay Anand. "Design of Load Balancing Technique for Cloud Computing Environment." ECS Transactions 107, no. 1 (2022): 2911–18. http://dx.doi.org/10.1149/10701.2911ecst.

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Cloud computing allows for the provision of IT resources on-demand and has various advantages. Because the majority of firms have shifted their activities to the cloud, data centers are frequently flooded with sporadic loads. When dealing with high network traffic in the cloud, it is necessary to balance the load among servers. This is something that load balancing can help with. The primary goal of load balancing is to distribute demand evenly among all available servers such that no server is under or overloaded. Load balancing is the process of dispersing load among several nodes to make th

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Buribayev, Zholdas, Ainur Yerkos, Saida Shaikalamova, Rustem Imanbek, and Zhibek Zhetpisbay. "IMPROVING MEDICAL DIAGNOSIS WITH A HYBRID BALANCING TECHNIQUE." Journal of Problems in Computer Science and Information Technologies 2, no. 3 (2024): 11–20. http://dx.doi.org/10.26577/jpcsit2024-02i03-02.

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The issue of class imbalance in medical data poses a significant challenge for developing robust machine learning models aimed at medical diagnosis. A characteristic feature of such data is the substantial dominance of instances belonging to majority classes (e.g., healthy patients or those with common diseases) over instances representing rare conditions. This disproportion leads to machine learning models trained on such data being prone to systematic classification errors, predominantly predicting the most frequent class. Consequently, the ability of models to accurately identify rare cases

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Muh., Amsyar, Isnawaty, and Natalis Ransi. "IMPLEMENTASI LOAD BALANCING VIRTUAL ROUTER REDUNDANCY PROTOKOL DENGAN MENGGUNAKAN ALGORITMA ROUND ROBIN PADA LAYANAN DATA." semanTIK 5, no. 2 (2019): 283–94. https://doi.org/10.5281/zenodo.3510187.

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<em>Computer networks are the most important part of communication systems in our lives, without a computer network we cannot communicate with one another. For that we need to maintain the quality level of network services by minimizing the occurrence of failures in a network device, by which it is necessary to have a network device that can take over from the main device. Protocol Virtual VR Redundancy (VRRP) is a protocol that is responsible for running the backup router functions when the master router has a fault condition.</em> <em>Mikrotic is a router that can implement load balanci

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Gui, Chun. "Analysis of imbalanced data set problem: The case of churn prediction for telecommunication." Artificial Intelligence Research 6, no. 2 (2017): 93. http://dx.doi.org/10.5430/air.v6n2p93.

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Class-imbalanced datasets are common in the field of mobile Internet industry. We tested three kinds of feature selection techniques-Random Forest (RF), Relative Weight (RW) and Standardized Regression Coefficients (SRC); three kinds of balance methods-over-sampling (OS), under-sampling (US) and synthetic minority over-sampling (SMOTE); a widely used classification method-RF. The combined models are composed of feature selection techniques, balancing techniques and classification method. The original dataset which has 45 thousand records and 22 features were used to evaluate the performances o

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Ramzan, Bajwa, Kazmi, and Amna. "Challenges in NoSQL-Based Distributed Data Storage: A Systematic Literature Review." Electronics 8, no. 5 (2019): 488. http://dx.doi.org/10.3390/electronics8050488.

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Key-Value stores (KVSs) are the most flexible and simplest model of NoSQL databases, which have become highly popular over the last few years due to their salient features such as availability, portability, reliability, and low operational cost. From the perspective of software engineering, the chief obstacle for KVSs is to achieve software quality attributes (consistency, throughput, latency, security, performance, load balancing, and query processing) to ensure quality. The presented research is a Systematic Literature Review (SLR) to find the state-of-the-art research in the KVS domain, and

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Sapna, P. Fathima, and Dr R. Lal Raja Singh. "Smart Meter Data based Load Analysis Using Clustering Technique." International Academic Journal of Science and Engineering 9, no. 1 (2022): 39–48. http://dx.doi.org/10.9756/iajse/v9i1/iajse0918.

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In this study, clustering is investigated as a method for improving energy efficiency based on smart meters for a number of household applications that are both currently available and expected to become available in the near future. These applications include smart thermostats, smart lights, smart water heaters, smart washing machines, and smart refrigerators. We describe a novel approach to load balanced clustering that is founded on the K-means Clustering algorithm. Our algorithm's major goal is to optimize network lifetime while maintaining acceptable sensing coverage in scenarios in which

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Al-Batahari, M., Azlinda Abdul Aziz, and Nur Syufiza Ahmad Shukor. "The Techniques in Enhancing Bandwidth Load Balancing QoS at Local Area Network: A Review Paper." International Journal on Cybernetics & Informatics 12, no. 5 (2023): 23–30. http://dx.doi.org/10.5121/ijci.2023.120503.

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Bandwidth load balancing is a critical technique for improving the quality of service (QoS) in local area networks (LANs). Insufficient load balancing and QoS utilization can lead to network congestion, reduced performance, latency, packet loss, and an overall degradation of network performance. This paper presents an overview of load balancing techniques, load balancing algorithms, QoS parameters, load balancing strategies, and considerations for calculating bandwidth. The challenges of implementing load balancing algorithms and preferences for their implementation are discussed. Accurate net

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V, Priyatharsini1. "Load balancing with multiple cloud services using PSO Techniques." International Journal of Advances In Scientific Research and Engineering (IJASRE) 3, no. 5 (2017): 101–8. https://doi.org/10.5281/zenodo.583822.

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There are various problems occur to choose the best path during critical circumstances. PSO is one of the heuristic technique which can be randomly choose a particle and observe the particle’s position. It can be mainly focused on the rotation of the object. It mainly based on non – batch scheduling algorithms. In this paper, the cloud is the data center to secure user’s individual cloudlet and focus on the security of the user. VM’S allocated based on the no. of cloudlets in the data center. It can be similar via amazon.in, salesforce.com & flipkart.com etc. It can be used for real time a

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Cai, Wenfang, Songyuan Lu, Zhengfeng Wu, Guangyao Ying, and Wenjian Wu. "Strategy and Technique of High Efficiency Balancing in Field for Turbo-Generator Units with Large Capacity." Journal of Physics: Conference Series 2101, no. 1 (2021): 012011. http://dx.doi.org/10.1088/1742-6596/2101/1/012011.

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Abstract Abstract.This paper aims at the high efficiency of field balancing for turbo-generator with large capacity currently, and introduces the strategies and key techniques of the rotor system balancing with practical cases of power plant in field. The acquisition, analysis and former processing of the original vibration data for balance calculation are included. Furthermore, they involve complete measuring points and conditions, accurate judgment for the types of unbalance exciting force and selection of stable vibration data, all these could reduce the blindness of balancing effectively.

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Dr., M. Therasa Aishwarya, Priyadharshini, and Joshna. "PREDICTION OF STOCK PRICE USING DATA SCIENCE TECHNIQUE." IJRSET AUGUST Volume 9 Issue 8 9, no. 8 (2022): 19–24. https://doi.org/10.5281/zenodo.7016803.

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Forecasting the future price of a stock on the stock exchange is a difficult task. Stock exchange is difficult to predict due to stock volatility. The price of a stock is altered throughout time. Stock customers are in high demand when it comes to balancing the stock exchange. Applying all of the regulations provided at any one moment is a huge hurdle in accurately forecasting stock in the future values. The latest speculative strategies used in the stock exchange like System of the Neuro-Fuzzy, Neural Network(Artificial), Nearest Neighbor Classifier, Deep Convolution Network , and the pros an

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Arca, Sevgi, and Rattikorn Hewett. "Analytics on Anonymity for Privacy Retention in Smart Health Data." Future Internet 13, no. 11 (2021): 274. http://dx.doi.org/10.3390/fi13110274.

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Advancements in smart technology, wearable and mobile devices, and Internet of Things, have made smart health an integral part of modern living to better individual healthcare and well-being. By enhancing self-monitoring, data collection and sharing among users and service providers, smart health can increase healthy lifestyles, timely treatments, and save lives. However, as health data become larger and more accessible to multiple parties, they become vulnerable to privacy attacks. One way to safeguard privacy is to increase users’ anonymity as anonymity increases indistinguishability making

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B. K., Prabhakara, Chandrakant Naikodi, and Suresh L. "Ford Fulkerson and Newey West Regression Based Dynamic Load Balancing in Cloud Computing for Data Communication." International Journal of Computer Network and Information Security 15, no. 5 (2023): 81–95. http://dx.doi.org/10.5815/ijcnis.2023.05.08.

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In Cloud Computing (CC) environment, load balancing refers to the process of optimizing resources of virtual machines. Load balancing in the CC environment is one of the analytical approaches utilized to ensure indistinguishable workload distribution and effective utilization of resources. This is because only by ensuring effective balance of dynamic workload results in higher user satisfaction and optimal allocation of resource, therefore improve cloud application performance. Moreover, a paramount objective of load balancing is task scheduling because surges in the number of clients utilizin

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Joko Minardi. "Enhancing Stunting Detection Accuracy in Children Using SVM with Advanced Data Balancing Techniques." Journal of Information Systems Engineering and Management 10, no. 6s (2025): 501–9. https://doi.org/10.52783/jisem.v10i6s.748.

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Stunting is a significant public health concern with enduring effects on children's physical and cognitive development. Traditional stunting classification methods often fail due to the complexity and imbalance of health data. This study proposes a novel technique combining Support Vector Machines (SVM) with Synthetic Minority Oversampling Technique (SMOTE) and Tomek Links to address these challenges. The proposed method was evaluated on a dataset from Kecapi Jepara, focusing on children's nutritional status before and after vitamin intervention. The results showed a significant improvement in

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Singh, Prabhdeep, Rajbir Kaur, Junaid Rashid, et al. "A Fog-Cluster Based Load-Balancing Technique." Sustainability 14, no. 13 (2022): 7961. http://dx.doi.org/10.3390/su14137961.

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The Internet of Things has recently been a popular topic of study for developing smart homes and smart cities. Most IoT applications are very sensitive to delays, and IoT sensors provide a constant stream of data. The cloud-based IoT services that were first employed suffer from increased latency and inefficient resource use. Fog computing is used to address these issues by moving cloud services closer to the edge in a small-scale, dispersed fashion. Fog computing is quickly gaining popularity as an effective paradigm for providing customers with real-time processing, platforms, and software s

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Singh, Jaspreet, Deepali Gupta, and Neha Sharma. "Cloud Load Balancing Algorithms: A Comparative Assessment." Journal of Computational and Theoretical Nanoscience 16, no. 9 (2019): 3989–94. http://dx.doi.org/10.1166/jctn.2019.8282.

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Nowadays, Cloud computing is developing quickly and customers are requesting more administrations and superior outcomes. In the cloud domain, load balancing has turned into an extremely intriguing and crucial research area. Numbers of algorithms were recommended to give proficient mechanism for distributing the cloud user’s requests for accessing pool cloud resources. Also load balancing in cloud should provide notable functional benefits to cloud users and at the same time should prove out to be eminent for cloud services providers. In this paper, the pre-existing load balancing techniques ar

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Ross, Christopher P., and Paul L. Beale. "Seismic offset balancing." GEOPHYSICS 59, no. 1 (1994): 93–101. http://dx.doi.org/10.1190/1.1443538.

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The ability to successfully predict lithology and fluid content from reflection seismic records using AVO techniques is contingent upon accurate pre‐analysis conditioning of the seismic data. However, all too often, residual amplitude effects remain after the many offset‐dependent processing steps are completed. Residual amplitude effects often represent a significant error when compared to the amplitude variation with offset (AVO) response that we are attempting to quantify. We propose a model‐based, offset‐dependent amplitude balancing method that attempts to correct for these residuals and

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Shimada, Ken-ichi, Makoto Hosaka, Kazuyoshi Yamazaki, Shinsuke Onoe, and Tatsuro Ide. "Technique for positioning hologram for balancing large data capacity with fast readout." Japanese Journal of Applied Physics 56, no. 9S (2017): 09NA04. http://dx.doi.org/10.7567/jjap.56.09na04.

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Arshed, Muhammad Asad, Muhammad Abdul Jabbar, Farrukh Liaquat, et al. "Machine Learning with Data Balancing Technique for IoT Attack and Anomalies Detection." Vol 4 Issue 2 4, no. 2 (2022): 490–98. http://dx.doi.org/10.33411/ijist/2022040218.

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Nowadays the significant concern in IoT infrastructure is anomaly and attack detection from IoT devices. Due to the advanced technology, the attack issues are increasing gradually. There are many attacks like Data Type Probing, Denial of Service, Malicious Operation, Malicious Control, Spying, Scan, and Wrong Setup that cause the failure of the IoT-based system. In this paper, several machine learning model performances have been compared to effectively predict the attack and anomaly. The performance of the models is compared with evaluation matrices (Accuracy) and confusion matrix for the fin

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Ratnasari, Dwi, and Dianita Meirini. "PAD, Dana Perimbangan, Belanja Modal, SILPA dan Kinerja Keuangan Pemerintah Daerah di Jawa Timur." E-Jurnal Akuntansi 32, no. 5 (2022): 1189. http://dx.doi.org/10.24843/eja.2022.v32.i05.p06.

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The purpose of the study was to examine the effect of local revenue, balancing funds, capital expenditures and SILPA on the financial performance of local governments as proxied through financial ratios in the form of efficiency ratios. A quantitative approach is used as an approach in this study. Saturated sample for sampling technique. The data analysis technique in this study was a panel data regression test. Based on the results of the T-test, financial performance cannot be affected by local revenue but financial performance can be significantly affected negatively by balancing funds and

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Ul Hassan, Ietezaz, Raja Hashim Ali, Zain Ul Abideen, Talha Ali Khan, and Rand Kouatly. "Significance of Machine Learning for Detection of Malicious Websites on an Unbalanced Dataset." Digital 2, no. 4 (2022): 501–19. http://dx.doi.org/10.3390/digital2040027.

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It is hard to trust any data entry on online websites as some websites may be malicious, and gather data for illegal or unintended use. For example, bank login and credit card information can be misused for financial theft. To make users aware of the digital safety of websites, we have tried to identify and learn the pattern on a dataset consisting of features of malicious and benign websites. We treated the problem of differentiation between malicious and benign websites as a classification problem and applied several machine learning techniques, for example, random forest, decision tree, log

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Wardhani, Muhammad, and Muhammad Taufiq Nuruzzaman. "Analisis Pengaruh Penggunaan Internet Download Manager pada Load Balancing di Mikrotik." Edumatic: Jurnal Pendidikan Informatika 7, no. 2 (2023): 495–504. http://dx.doi.org/10.29408/edumatic.v7i2.24295.

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Internet Download Manager (IDM) is one of the popular applications used by users to download various types of files from the internet. Load balancing is a technique used to increase the efficiency of using network resources by distributing data traffic evenly across several connection lines. This research aims to determine the extent to which IDM influences the effectiveness of load balancing as well as the influence of using Internet Download Manager (IDM) in the context of load balancing using the Policy-based Load Balancing (PCC), Equal Cost Multi-Path (ECMP), and Next-Hop Target methods. (

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Kannan, Rithesh, Hu Ng, Timothy Tzen Vun Yap, et al. "Handling class imbalance in education using data-level and deep learning methods." International Journal of Electrical and Computer Engineering (IJECE) 15, no. 1 (2025): 741. http://dx.doi.org/10.11591/ijece.v15i1.pp741-754.

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In the current field of education, universities must be highly competitive to thrive and grow. Education data mining has helped universities in bringing in new students and retaining old ones. However, there is a major issue in this task, which is the class imbalance between the successful students and at-risk students that causes inaccurate predictions. To address this issue, 12 methods from data-level sampling techniques and 2 methods from deep learning synthesizers were compared against each other and an ideal class balancing method for the dataset was identified. The evaluation was done us

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Mayanda, Deara, Annisa Rizki Amaliah, Muhammad Ridwan Ali Raharja, and Nurbojatmiko Nurbojatmiko. "Load Balancing Techniques for Server Clustering in Cloud Environment: Systematic Literature Review." Journal of Renewable Energy, Electrical, and Computer Engineering 4, no. 2 (2024): 173–79. https://doi.org/10.29103/jreece.v4i2.14906.

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The rapid development of cloud computing has a significant impact on increasing the workload on resources, which is often excessive and a major challenge in computing environments. Load balancing is key to avoid overloading or underloading virtual machines, given the high user demand for service availability. There are several types of load balancing techniques, and this diversity poses its own challenges in selecting the optimal technique to address workload issues. This research presents a systematic literature review with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Ana

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Hafizh, Afrianton Noor, and Wiwin Sulistyo. "Optimalisasi Dua Layanan Jaringan Internet Menggunakan Teknik Load Balancing dengan Metode Peer Connection Classifier (PCC) (Studi Kasus: Jaringan Internet Desa Banyuanyar Boyolali)." Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 8, no. 1 (2024): 10–21. http://dx.doi.org/10.35870/jtik.v8i1.1257.

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Load Balancing is a technique for distributing data traffic so that the workload is distributed evenly on 2 or more networks to maximize resource usage and improve performance. There are two ISPs for internet access services to the Banyuanyar Village Office, Boyolali, both of which have different bandwidths, namely from PT. Telkom has 100Mbps bandwidth and Kominfo has 50Mbps bandwidth. So here there will be dense network traffic if the internet network is not optimized.. In this case, it can be optimized using load balancing techniques on both ISPs by using the Peer Connection Classifier techn

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Belalem, Ghalem, Naima Belayachi, Radjaa Behidji, and Belabbes Yagoubi. "Load Balancing to Increase the Consistency of Replicas in Data Grids." International Journal of Distributed Systems and Technologies 1, no. 4 (2010): 42–57. http://dx.doi.org/10.4018/jdst.2010100104.

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Data grids are current solutions to the needs of large scale systems and provide a set of different geographically distributed resources. Their goal is to offer an important capacity of parallel calculation, ensure a data effective and rapid access, improve the availability, and tolerate the breakdowns. In such systems, however, these advantages are possible only by using the replication technique. The use of this technique raises the problem of maintaining consistency of replicas of the same data set. In order to guarantee replica set reliability, it is necessary to have high coherence. This

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Bura, Deepa, Meeta Singh, and Poonam Nandal. "Analysis and Development of Load Balancing Algorithms in Cloud Computing." International Journal of Information Technology and Web Engineering 13, no. 3 (2018): 35–53. http://dx.doi.org/10.4018/ijitwe.2018070103.

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This article describes how cloud computing utilizes the benefits of web engineering and its applications by improving the performance and reducing the load on cloud providers. As the cloud is one of the emerging technology in the field of computing, it is used to provide various services to the user through the internet. One of the major concerns in cloud computing is accessibility of cloud. For estimating the availability of cloud, various load balancing algorithms are deployed in data centers of the cloud environment. Load balancing is a technique that distributes a signal load across variou

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Saekhu, Ahmad, Berlilana Berlilana, and Dhanar Intan Surya Saputra. "Comparative Analysis of Data Balancing Techniques for Machine Learning Classification on Imbalanced Student Perception Datasets." Jurnal Teknik Informatika (Jutif) 6, no. 2 (2025): 627–40. https://doi.org/10.52436/1.jutif.2025.6.2.4286.

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Class imbalance is a common challenge in machine learning classification tasks, often leading to biased predictions toward the majority class. This study evaluates the effectiveness of various machine learning algorithms combined with advanced data balancing techniques in addressing class imbalance in a dataset collected from Class XI students of SMK Ma'arif 1 Kebumen. The dataset, comprising 300 instances and 36 features, includes textual attributes, demographic information, and sentiment labels categorized as Positive, Neutral, and Negative. Preprocessing steps included text cleaning, target

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Rutherford, Steven R. "Noise‐discriminating, statistical‐amplitude compensation for AVO analysis." GEOPHYSICS 58, no. 12 (1993): 1831–39. http://dx.doi.org/10.1190/1.1443398.

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Statistical amplitude balancing/compensation techniques are widely used in the industry to prepare seismic data for amplitude variation with offset (AVO) processing and analysis. The intent of such statistical techniques is to compensate the data for the average signal decay with offset such that reflectors that are anomalous with respect to this average decay can be detected and analyzed. Statistical amplitude compensation techniques, however, suffer from a serious flaw when applied to data sets having low signal‐to‐noise ratios (S/N) that vary with offset. An artifact of this flaw is often a

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Wen-Hsuan, Liang, Cheng Dun-Wei, Hsu Chih-Wei, et al. "Dynamic Flow Scheduling Technique for Load Balancing in Fat-Tree Data Center Networks." International Journal of Performability Engineering 17, no. 6 (2021): 491. http://dx.doi.org/10.23940/ijpe.21.06.p1.491503.

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Kansal, Nidhi Jain, and Inderveer Chana. "An empirical evaluation of energy-aware load balancing technique for cloud data center." Cluster Computing 21, no. 2 (2017): 1311–29. http://dx.doi.org/10.1007/s10586-017-1166-z.

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de Hollander, J. A. "Application of a metabolic balancing technique to the analysis of microbial fermentation data." Antonie van Leeuwenhoek 60, no. 3-4 (1991): 275–92. http://dx.doi.org/10.1007/bf00430370.

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Subasinghe, G. K. N. S. "A transparent technique for mass balancing and data adjustment of complex metallurgical circuits." Mineral Processing and Extractive Metallurgy 118, no. 3 (2009): 162–67. http://dx.doi.org/10.1179/174328509x431418.

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Cahyani, Ailsa Nurina, Junta Zeniarja, Sri Winarno, Rusyda Tsaniya Eka Putri, and Ahmad Alaik Maulani. "Heart Disease Classification Using Deep Neural Network with SMOTE Technique for Balancing Data." Advance Sustainable Science, Engineering and Technology 6, no. 1 (2023): 0240108. http://dx.doi.org/10.26877/asset.v6i1.17521.

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Heart disease is the leading cause of premature death worldwide. According to the WHO, heart disease causes about 30% of the total 58 million deaths and mostly occurs in individuals who are in their productive age. This condition can occur to anyone, including individuals who do not show symptoms of heart disease. However, heart disease can be prevented with early detection. By understanding the various risk factors that can increase the potential for heart disease. Therefore, this study aims to classify heart disease using Deep Neural Network algorithm and SMOTE technique to overcome data imb

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Ullah, Arif, and Nazri Mohd Nawi. "Enhancing the dynamic load balancing technique for cloud computing using HBATAABC algorithm." International Journal of Modeling, Simulation, and Scientific Computing 11, no. 05 (2020): 2050041. http://dx.doi.org/10.1142/s1793962320500415.

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Cloud computing brings incipient transmutations in different fields of life and consists of different characteristics and virtualization is one of them. Virtual machine (VM) is one of the main elements of virtualization. VM is a process in which physical server changes into the virtual machine and works as a physical server. When a user sends data or request for data in cloud data center, a situation can occur that may cause the virtual machines to underload data or overload data. The aforementioned situation can lead to failure of the system or delay the user task. Therefore, appropriate load

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Mohammed, Rafiq Ahmed, Kok-Wai Wong, Mohd Fairuz Shiratuddin, and Xuequn Wang. "PWIDB: A framework for learning to classify imbalanced data streams with incremental data re-balancing technique." Procedia Computer Science 176 (2020): 818–27. http://dx.doi.org/10.1016/j.procs.2020.09.077.

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Parent, Johan, Katja Verbeeck, Jan Lemeire, Ann Nowe, Kris Steenhaut, and Erik Dirkx. "Adaptive Load Balancing of Parallel Applications with Multi-Agent Reinforcement Learning on Heterogeneous Systems." Scientific Programming 12, no. 2 (2004): 71–79. http://dx.doi.org/10.1155/2004/987356.

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We report on the improvements that can be achieved by applying machine learning techniques, in particular reinforcement learning, for the dynamic load balancing of parallel applications. The applications being considered in this paper are coarse grain data intensive applications. Such applications put high pressure on the interconnect of the hardware. Synchronization and load balancing in complex, heterogeneous networks need fast, flexible, adaptive load balancing algorithms. Viewing a parallel application as a one-state coordination game in the framework of multi-agent reinforcement learning,

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Ramadani, Alkansa Fadila, and Muslimin Muslimin. "Pendapatan Asli Daerah dan Dana Perimbangan terhadap Kinerja Keuangan Pemerintah Daerah." Journal of Management and Bussines (JOMB) 4, no. 1 (2022): 362–72. http://dx.doi.org/10.31539/jomb.v4i1.3710.

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This study aims to determine the effect of PAD and Balancing Funds on the financial performance of local governments. This research method is descriptive quantitative. This research utilizes the Non-Probability Sampling method as well as the saturated sampling technique. The type of data used is secondary data obtained from the 2016-2020 Kediri City Government Budget Realization Report. The data were analyzed using multiple linear regression analysis with the help of SPSS 25 software. The results showed that PAD had a positive effect on local government financial performance. Meanwhile, the Ba

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Mustafa Ibrahim, Muhammad. "REDUCING WORK IN PROCESS (WIP) USING LINE BALANCING TECHNIQUE IN MANUFACTURING INDUSTRY." International Journal of Engineering Applied Sciences and Technology 8, no. 1 (2023): 162–68. http://dx.doi.org/10.33564/ijeast.2023.v08i01.026.

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For organizations looking to increase productivity and efficiency in the manufacturing sector, reducing Work In Process (WIP) is a crucial goal. The deployment of line-balancing techniques to accomplish this goal is the main topic of this research article. The introduction discusses the negative consequences of WIP, including productivity loss, leads times that are too long, and bottlenecks. The application of lean manufacturing principles, workflow optimization, WIP limits establishment, improved communication and collaboration, prioritization and sequencing of work, identification and remova

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