1.004   Artículos

 
en línea
Boris Stanoev, Goran Mitrov, Andrea Kulakov, Georgina Mirceva, Petre Lameski and Eftim Zdravevski    
With the exponential growth of data, extracting actionable insights becomes resource-intensive. In many organizations, normalized relational databases store a significant portion of this data, where tables are interconnected through some relations. This ... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Róbert Lakatos, Gergo Bogacsovics, Balázs Harangi, István Lakatos, Attila Tiba, János Tóth, Marianna Szabó and András Hajdu    
The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions. However, some tasks are still challenging, especially when considering specific domains. This... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Falah Amer Abdulazeez, Ismail Taha Ahmed and Baraa Tareq Hammad    
A significant quantity of malware is created on purpose every day. Users of smartphones and computer networks now mostly worry about malware. These days, malware detection is a major concern in the cybersecurity area. Several factors can impact malware d... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Lingqi Kong and Shengquau Liu    
With the development of the Internet, vast amounts of text information are being generated constantly. Methods for extracting the valuable parts from this information have become an important research field. Relation extraction aims to identify entities ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia    
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Harun Bolat and Baha Sen    
In the biomedical field, accessing data by classical methods is getting more difficult day by day, as it is in any other field, due to the data growth rate. Different methods are needed to access the desired data more quickly. In particular, more specifi... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Dacheng Yu, Mingjun Zhang, Feng Yao and Jitao Li    
Variational Mode Decomposition (VMD) has typically been used in weak fault feature extraction in recent years. The problem analyzed in this study is weak fault feature extraction and the enhancement of AUV thrusters based on Artificial Rabbits Optimizati... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Justin J. Delver and Zachary K. Smith    
Camelina sativa is an annual oilseed crop that requires low inputs. Recently, interest in camelina oil for both human use and biofuel production has increased. Camelina oil extraction is performed through two main methods, namely, mechanical expulsion an... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Mihael Gudlin, Miro Hegedic, Matija Golec and Davor Kolar    
In the quest for industrial efficiency, human performance within manufacturing systems remains pivotal. Traditional time study methods, reliant on direct observation and manual video analysis, are increasingly inadequate, given technological advancements... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Lianlian He, Hao Li and Rui Zhang    
Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georeferen... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

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