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Research ArticleOpen accessEvery word in the titleDetecting Hornbeam Trees Phenological Characteristics of Mountain ForestSasan Babaei Kafaki, Asadollah Mataji, Seyed Armin HashemiProblem statement: Phenology is the study of the seasonal occurrence of developmental or life cycle events, such as bud break, flowering, or autumn leaf drop. The proposed study attempted to quantify changes in Carpinus betulus L. phenology of deciduous broad leaf forest between the years 2003-2006. Approach: Phenological studies were fulfilled during four years as from January 2003-December 2006 by … …American Journal of Environmental Sciences, Vol. 5, Issue 5 · 31 Oct 2009 · 7,278 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTwigX-Guide: Twig Query Pattern Matching for XML TreesSu-Cheng Haw, Chien-Sing LeeThe growing importance of XML and the lack of efficient solutions for managing and querying XML data have led to the development of hybrid systems. We present a hybrid system, TwigX-Guide; an extension of the well-known DataGuide index and region encoding labeling to support twig query processing. With TwigX-Guide, a complex query can be decomposed into a set of path … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,082 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDeep Learning and Image Analytics for Forest Land Management: Classification, and Object DetectionDevam Dixit, Aditya Bhavsar, Shreyas Jani, Nilesh YadavRapid urbanization and industrialization have contributed to deforestation which has led to a severe degradation of the environment and biodiversity loss. Traditional field survey methods are not applicable in the monitoring of large forest areas due to the fact that such methods are manual, costly and time consuming as well as subject to human error. The current methods of remote … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,602 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalyzing Temperature-Dependent Thermal Properties of Biomaterials Using Machine Learning MethodsArmaghan Shalbaftabar, Kristen Rhinehardt, Dhananjay KumarThis research utilizes machine learning models ANN, Random Forest, and Decision Tree to predict material properties of Ti-based biomaterials, including Young’s modulus, density, thermal conductivity, and specific heat at various temperatures. Data was sourced using web scraping and Plot Digitizer, validated against literature, and analyzed in Excel. The ANN model achieved strong performance, with R² = 0.980874 for TiAl and … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 12 Sep 2025 · 4,640 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBlockchain Integrated Distributed Threshold Elliptic Curve Cryptography Framework for Scalable and Secure Cloud Data StorageNaga Swetha Dhulipudi, Balaji SavadamThe development of cloud computing offers scalable processing capabilities, thereby enabling organizations to store and process sensitive data in the cloud. However, it faces crucial security challenges, as existing cryptographic and blockchain systems suffer from poor scalability and centralized key management, which creates a single point of failure and introduces vulnerabilities to both quantum and classical attacks. This research proposes … …Journal of Computer Science, Vol. 22, Issue 11 · 19 Oct 2026 · 416 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Machine Learning Framework for Strategic Gameplay Optimization in Scrabble Using Reinforcement LearningMohd Kaleem, Kanta Prasad Sharma, Tapsi Nagpal et al.This paper explores and compare various artificial intelligence-based techniques used for playing classic board game Scrabble. As the world is evolving around finding quick and efficient techniques for the solution of each problem using Machine learning, gaming industry is also a flourishing industry and has grown 9.8% compared to previous year and has generated a revenue of 26.14 billion dollars … …Journal of Computer Science, Vol. 22, Issue 9 · 22 Sep 2026 · 682 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,947 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalysis of Student Mental Health Dataset Using Mining TechniquesYemima Monica Geasela, Devi Yurisca Bernanda, Johanes Fernandes Andry et al.This study utilizes a decision tree model in RapidMiner to analyze a dataset from Kaggle, comprising 200 student records. Among these, 70 students reported mental health issues, while 130 did not. Strikingly, a significant majority of 58 out of the 70 students with mental health concerns do not seek assistance from professionals. This study underscores the pressing issue of underutilization … …Journal of Computer Science, Vol. 20, Issue 1 · 22 Dec 2023 · 6,970 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIs Single Scan based Restructuring Always a Suitable Approach to Handle Incremental Frequent Pattern Mining?Shafiul Alom Ahmed, Bhabesh NathIncremental mining of frequent patterns has attracted the attention of researchers in the last two decades. The researchers have explored the frequent pattern mining from incremental database problems by considering that the complete database to be processed can be accommodated in systems’ main memory even after the database gets updated very frequently. The FP-tree-based approaches were able to draw more … …Journal of Computer Science, Vol. 17, Issue 3 · 12 Mar 2021 · 6,926 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,098 accessesView PDFCite