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The research and innovations in the field of wearable auxiliary devices for visually impaired and blind people are playing a vital role towards improving their quality of life. However, in spite of the promisi...
Automatic caption generation with attention mechanisms aims at generating more descriptive captions containing coarser to finer semantic contents in the image. In this work, we use an encoder-decoder framework...
Wireless sensor networks (WSNs) are increasingly being used for data monitoring and collection purposes. Typically, they consist of a large number of sensor nodes that are used remotely to collect data about t...
Depending on the RMSE and sites sharing travel details, enormous reviews have been posted day by day. In order to recognize potential target customers in a quick and effective manner, hotels are necessary to e...
The effectiveness of machine learning models can be significantly averse to redundant and irrelevant features present in the large dataset which can cause drastic performance degradation. This paper proposes I...
The recent evolution of machine learning (ML) algorithms and the high level of expertise required to use them have fuelled the demand for non-experts solutions. The selection of an appropriate algorithm and th...
In an attempt to mitigate emissions and road traffic, a significant interest has been recently noted in expanding the use of shared vehicles to replace private modes of transport. However, one outstanding issu...
Collecting and analyzing data has become crucial for many sectors, including the health care sector, where a hefty amount of data is generated daily. Over time, the amount and complexity of this data increase ...
The purpose of click-through rate (CTR) prediction is to anticipate how likely a person is to click on an advertisement or item. It's required for a lot of internet applications, such online advertising and re...
One of the most common causes of incompleteness is missing data, which occurs when no data value for the variables in observation is stored. An adaptive approach model outperforming other numerical methods in ...
When you make a forex transaction, you sell one currency and buy another. If the currency you buy increases against the currency you sell, you profit, and you do this through a broker as a retail trader on the...
In Machine Learning, prediction quality is usually measured using different techniques and evaluation methods. In the regression models, the goal is to minimize the distance between the actual and predicted va...
Sensing passersby and detecting crowded locations is a growing area of research and development in the last decades. The COVID-19 pandemic compelled authorities and public and private institutions to monitor a...
Training a machine learning algorithm on a class-imbalanced dataset can be a difficult task, a process that could prove even more challenging under conditions of high dimensionality. Feature extraction and dat...
There is an exponential growth in textual content generation every day in today's world. In-app messaging such as Telegram and WhatsApp, social media websites such as Instagram and Facebook, e-commerce website...
Chemical-shift encoded MRI (CSE-MRI) is a widely used technique for the study of body composition and metabolic disorders, where derived fat and water signals enable the quantification of adipose tissue and mu...
Deep learning algorithms provide visual tracking robustness at an unprecedented level, but realizing an acceptable performance is still challenging because of the natural continuous changes in the features of ...
Global climate change is affecting water resources and other aspects of life in many countries. Rainfall is the most significant climate element affecting the livelihood and well-being of the majority of Ethio...
Since mobile food delivery services have become one of the essential issues for the restaurant industry, predicting customer revisits is highlighted as one of the significant academic and research topics. Cons...
A web application is a software system that provides an interface to its users through a web browser on any operating system (OS). Despite their growing popularity, web application security threats have become...
Recent advances in Information and Communication Technologies have a significant impact on all sectors of the economy worldwide. Digital Agriculture appeared as a consequence of the democratisation of digital ...
Anomaly detection is a relevant problem in the area of data analysis. In networked systems, where individual entities interact in pairs, anomalies are observed when pattern of interactions deviates from patter...
Fuzzy clustering is an invaluable data mining technique that allows each data point to belong to more than one cluster with some degree of membership. It is widely employed in exploratory data mining to discov...
Uncommon observations that significantly vary from the norm are referred to as outliers. Outlier detection, which aims to detect unexpected behavior, is a critical topic that has attracted significant attentio...
We propose a novel feature popularity framework, and introduce this new framework to the cybersecurity domain. Feature popularity has not yet been used in machine learning or data mining, and we implement it w...
Today we create and collect more data than we have in the past. All this data comes from different sources, including social media platforms, our phones and computers, healthcare gadgets and wearable technolog...
The ability to cross data from multiple sources represents a competitive advantage for organizations. Yet, the governance of the data lifecycle, from the data sources into valuable insights, is largely perform...
Dynamic changes in epigenetic landscape reflect a critical command of lineage-specific gene expression. In an effort to discern the epigenetic regulatory networks of myogenic differentiation, we have used syst...
Aspect-based sentiment analysis (ABSA) is a textual analysis methodology that defines the polarity of opinions on certain aspects related to specific targets. The majority of research on ABSA is in English, wi...
The present study presents a knowledge-based DSS framework for supporting the decision-maker and handling control decisions related to supply chains.
Social media contains an overabundance of health information relating to people living with different type of diseases. Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with lifelong im...
This study uses transformers architecture of Artificial neural networks to generate artificial business text for a given topic or theme. The implication of the study is to augment the business report writing, ...
As the inter-connectivity in cyberspace continues to increase exponentially, privacy and security have become two of the most concerning issues that need to be tackled in today’s state of technology. Therefore...
Social media services and analytics platforms are rapidly growing. A large number of various events happen mostly every day, and the role of social media monitoring tools is also increasing. Social networks ar...
Goal three of the UN’s Sustainable Development Goal is good health and well-being where it clearly emphasized that non-communicable diseases is emerging challenge. One of the objectives is to reduce premature ...
Monitoring health status requires collecting a large amount of data from the human body. The sensor can be used to collect data from the human body. The sensor transmits data for almost every second across the...
The technical advancements and the availability of massive amounts of data on the Internet draw huge attention from researchers in the areas of decision-making, data sciences, business applications, and govern...
Commercial banks are required to explain the credit evaluation results to their customers. Therefore, banks attempt to improve the performance of their credit scoring models while ensuring the interpretability...
Using an incremental approach to solve the record linkage problem is a relatively new research area. In incremental record linkage, every inserted record is compared with some existing clusters of records base...
The massive influx of text, images, and videos to the internet has recently increased the challenge of computer vision-based tasks in big data. Integrating visual data with natural language to generate video e...
The problem of compliance checking and assessment is to ensure that the design or implementation of a system meets some desired properties and complies with some rules or regularities. This problem is a key issue...
Infinite numbers of real-world applications use Machine Learning (ML) techniques to develop potentially the best data available for the users. Transfer learning (TL), one of the categories under ML, has receiv...
Beyond detecting brain lesions or tumors, comparatively little success has been attained in identifying brain disorders such as Alzheimer’s disease (AD), based on magnetic resonance imaging (MRI). Many machine...
Small Medium Enterprises (SMEs) are vital to the global economy and all societies. However, they face a complex and challenging environment, as in most sectors they are lagging behind in their digital transfor...
Occupational data mining and analysis is an important task in understanding today’s industry and job market. Various machine learning techniques are proposed and gradually deployed to improve companies’ operat...
The existence of class imbalance in a dataset can greatly bias the classifier towards majority classification. This discrepancy can pose a serious problem for deep learning models, which require copious and di...
The variety feature of Big Data, represented by multi-model data, has brought a new dimension of complexity to all aspects of data management. The need to process a set of distinct but interlinked data models is ...
The emergence of automated machine learning or AutoML has raised an interesting trend of no-code and low-code machine learning where most tasks in the machine learning pipeline can possibly be automated withou...
A high-dimensional and incomplete (HDI) matrix is a typical representation of big data. However, advanced HDI data analysis models tend to have many extra parameters. Manual tuning of these parameters, general...
Predictive maintenance employing machine learning techniques and big data analytics is a benefit to the industrial business in the Industry 4.0 era. Companies, on the other hand, have difficulties as they move...
2022 Citation Impact
8.1 - 2-year Impact Factor
5.095 - SNIP (Source Normalized Impact per Paper)
2.714 - SJR (SCImago Journal Rank)
2023 Speed
56 days submission to first editorial decision for all manuscripts (Median)
205 days submission to accept (Median)
2023 Usage
2,559,548 downloads
280 Altmetric mentions
