Page 1 of 20
This study introduces a novel deep learning-based approach for classifying poultry audio signals, incorporating a custom Burn Layer to enhance model robustness. The methodology integrates digital audio signal ...
In late 2023, the United Nations conference on climate change (COP28), which was held in Dubai, encouraged a quick move from fossil fuels to renewable energy. Solar energy is one of the most promising forms of...
The frequent usage of computer networks and the Internet has made computer networks vulnerable to numerous attacks, highlighting the critical need to enhance the precision of security mechanisms. One of the mo...
The tumor microenvironment (TME) provides a region for intricate interactions within or between immune and non-immune cells. We aimed to reveal the tissue architecture and comprehensive landscape of cells with...
Diabetic retinopathy (DR) is the most prevalent cause of preventable vision loss worldwide, imposing a significant economic and medical burden on society today, of which early identification is the cornerstone...
The image object recognition and detection technology are widely used in many scenarios. In recent years, big data has become increasingly abundant, and big data-driven artificial intelligence models have attr...
The long-term impacts of COVID-19 on human health are a major concern, yet comprehensive evaluations of its effects on various health conditions are lacking.
This article presents an investment recommender system based on an Adaptive Neuro-Fuzzy Inference System (ANFIS) and pre-trained weights from a Multimodal Neural Network (MNN). The model is designed to support...
Psychiatric disorders are severe health challenges that exert a heavy public burden. Air pollution has been widely reported as related to psychiatric disorder risk, but their casual association and pathologica...
In digital agriculture, accurate crop detection is fundamental to developing automated systems for efficient plantation management. For oil palm, the main challenge lies in developing robust models that perfor...
The question of whether artificial intelligence (AI) can surpass human capabilities is crucial in the application of AI in clinical medicine. To explore this, an interpretable deep learning (DL) model was deve...
Data has evolved into one of the principal resources for contemporary businesses. Moreover, corporations have undergone digitalization; consequently, their supply chains generate substantial amounts of data. T...
In recent years, mobile applications have proliferated across domains such as E-banking, Augmented Reality, E-Transportation, and E-Healthcare. These applications are often built using microservices, an archit...
The success of newly established companies holds significant implications for community development and economic growth. However, startups often grapple with heightened vulnerability to market volatility, whic...
Class imbalance is one of many problems of customer churn datasets. One of the common problems is class overlap, where the data have a similar instance between classes. The prediction task of customer churn be...
Some of the most notable human behavioral palimpsests result from warfare and its durable traces in the form of defensive architecture and strategic infrastructure. For premodern periods, this architecture is ...
Subway button detection is paramount for passenger safety, yet the occurrence of inadvertent touches poses operational threats. Camera-based detection is indispensable for identifying touch occurrences, ascert...
This study investigates the causes and countermeasures of cybercrime vulnerabilities, specifically focusing on selected 16 Ethiopian university websites. This study uses a cybersecurity awareness survey, and a...
Crude oil is an essential energy source that affects international trade, transportation, and manufacturing, highlighting its importance to the economy. Its future price prediction affects consumer prices and ...
U-net, a fully convolutional network-based image segmentation method, has demonstrated widespread adaptability in the crack segmentation task. The combination of the semantically dissimilar features of the enc...
The construction industry substantially contributes to the economic growth of a country. However, it records a large number of workplace injuries and fatalities annually due to its hesitant adoption of automat...
This paper presents a comprehensive approach to harmonizing lunar calendars across different global regions, addressing the long-standing challenge of variations in new crescent Moon sightings that mark the be...
The k-Nearest Neighbors (kNN) method, established in 1951, has since evolved into a pivotal tool in data mining, recommendation systems, and Internet of Things (IoT), among other areas. This paper presents a c...
The maize leaf diseases create severe yield reductions and critical problems. The maize leaf disease should be discovered early, perfectly identified, and precisely diagnosed to make greater yield. This work s...
Aspect level sentiment analysis is a basic task to determine the sentiment bias based on the contextual information near the aspect words. Some sentences contain many confusing feature words due to incomplete ...
The success of online social platforms hinges on their ability to predict and understand user behavior at scale. Here, we present data suggesting that context-aware modeling approaches may offer a holistic yet...
This paper addresses the Graeco-Latin square design (GLSD) under neutrosophic statistics. In this work, we propose a novel approach for analyzing Graeco-Latin square designs using uncertain observations.
With the growing complexity of data structures, which include high-dimensional and multilabel datasets, the significance of feature selection has become more emphasized. Multilabel feature selection endeavors ...
The convergence of artificial intelligence (AI), big data (DB), and Internet of Things (IoT) in Society 5.0, has given rise to Marketing 5.0, revolutionizing personalized customer experiences. In this study, a...
Prediction processes in areas ranging from climate and disease spread to disasters and air pollution rely heavily on spatial–temporal data. Understanding and forecasting the distribution patterns of disease ca...
As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly and accurately is crucial be...
The morphology and distribution of airway tree abnormalities enable diagnosis and disease characterisation across a variety of chronic respiratory conditions. In this regard, airway segmentation plays a critic...
Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Re...
Short-term traffic flow forecasting is a hot issue in the field of intelligent transportation. The research field of traffic forecasting has evolved greatly in past decades. With the rapid development of deep ...
Physical fitness is one of the most important traits a person could have for health longevity. Conducting regular exercise is fundamental to maintaining physical fitness, but with the caveat of occurring injur...
This paper introduces TC-Llama 2, a novel application of large language models (LLMs) in the technology-commercialization field. Traditional methods in this field, reliant on statistical learning and expert kn...
This study was designed to develop and validate a robust predictive model for one-year mortality in elderly coronary heart disease (CHD) patients with anemia using machine learning methods.
Within the Hadoop ecosystem, MapReduce stands as a cornerstone for managing, processing, and mining large-scale datasets. Yet, the absence of efficient solutions for precise estimation of job execution times p...
The detection of hate speech (HS) in online platforms has become extremely important for maintaining a safe and inclusive environment. While significant progress has been made in English-language HS detection,...
Time series similarity matrices (informally, recurrence plots or dot-plots), are useful tools for time series data mining. They can be used to guide data exploration, and various useful features can be derived...
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural language processing. In this work, we present a novel frame...
ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the human motor system. It is a group of progressive diseases that affects the nerve cells in the brain and spinal cord that control ...
Emotions are fundamental to human behaviour. How we feel, individually and collectively, determines how humanity evolves and advances into our shared future. The rapid digitalisation of our personal, social an...
In the current industrial landscape, a significant number of sectors are grappling with the challenges posed by unstructured data, which incurs financial losses amounting to millions annually. If harnessed eff...
Recommendation system is currently attracting the interest of many explorers. Various new businesses have surfaced with the rise of online marketing (E-Commerce) in response to Covid-19 pandemic. This phenomen...
White blood cells (WBCs) are one of the most significant parts of the human immune system, and they play a crucial role in diagnosing the characteristics of pathologists and blood-related diseases. The charact...
The article introduces an innovative approach to global optimization and feature selection (FS) using the RIME algorithm, inspired by RIME-ice formation. The RIME algorithm employs a soft-RIME search strategy ...
Hepatocellular carcinoma (HCC) is a highly prevalent form of liver cancer that necessitates accurate prediction models for early diagnosis and effective treatment. Machine learning algorithms have demonstrated...
The classification of imbalanced datasets is a prominent task in text mining and machine learning. The number of samples in each class is not uniformly distributed; one class contains a large number of samples...
OCR2SEQ represents an innovative advancement in Optical Character Recognition (OCR) technology, leveraging a multi-modal generative augmentation strategy to overcome traditional limitations in OCR systems. Thi...
Citation Impact 2023
Journal Impact Factor: 8.6
5-year Journal Impact Factor: 12.4
Source Normalized Impact per Paper (SNIP): 3.853
SCImago Journal Rank (SJR): 2.068
Speed 2023
Submission to first editorial decision (median days): 56
Submission to acceptance (median days): 205
Usage 2023
Downloads: 2,559,548
Altmetric mentions: 280
