2019 March - 38 articles
Selecting representative objects from a large-scale database is an essential task to understand the database. A skyline query is one of the popular methods for selecting representative objects. It retrieves a set of non-dominated objects. In this pap...
This work addresses the question of explaining changes in the desired timescales of the stock market. Tangled string is a sequence visualization tool wherein a sequence is compared to a string and trends in the sequence are compared to the appearance...
Artificial intelligence is changing the healthcare industry from many perspectives: diagnosis, treatment, and follow-up. A wide range of techniques has been proposed in the literature. In this special issue, 13 selected and peer-reviewed original res...
This paper presents an approach to detect and classify the faults in complex systems with small amounts of available data history. The methodology is based on the model fusion for fault detection and classification. Moreover, the database is enriched...
The total variation (TV) regularization-based methods are proven to be effective in removing random noise. However, these solutions usually have staircase effects. This paper proposes a new image reconstruction method based on TV regularization with...
Recent expansion of intelligent gadgets, such as smartphones and smart watches, familiarizes humans with sensing their activities. We have been developing a road accessibility evaluation system inspired by human sensing technologies. This paper intro...
Due to the high demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the data produced and provide the high availability required. Over the years, this increase in en...
In targeting the low correlation between existing image scaling quality assessment methods and subjective awareness, a content-aware retargeted image quality assessment algorithm is proposed, which is based on the structural similarity index. In this...
Data fragmentation and allocation has for long proven to be an efficient technique for improving the performance of distributed database systems’ (DDBSs). A crucial feature of any successful DDBS design revolves around placing an intrinsic emph...
Metagenomics studies, as well as genomics studies of polyploid species such as wheat, deal with the analysis of high variation data. Such data contain sequences from similar, but distinct genetic chains. This fact presents an obstacle to analysis and...
In the last decade, there has been a growing scientific interest in the analysis of DNA microarray datasets, which have been widely used in basic and translational cancer research. The application fields include both the identification of oncological...
The existing short-term traffic flow prediction models fail to provide precise prediction results and consider the impact of different traffic conditions on the prediction results in an actual traffic network. To solve these problems, a hybrid Long S...
The current paper addresses relevant network security vulnerabilities introduced by network devices within the emerging paradigm of Internet of Things (IoT) as well as the urgent need to mitigate the negative effects of some types of Distributed Deni...
This article addresses the task of inferring elements in the attributes of data. Extracting data related to our interests is a challenging task. Although data on the web can be accessed through free text queries, it is difficult to obtain results tha...
In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing th...
We will sketch the debate on testimony in social epistemology by reference to the contemporary debate on reductionism/anti-reductionism, communitarian epistemology and inferentialism. Testimony is a fundamental source of knowledge we share and it is...
We propose an extended scheme for selecting related stocks for themed mutual funds. This scheme was designed to support fund managers who are building themed mutual funds. In our preliminary experiments, building a themed mutual fund was found to be...
Financial prediction is an important research field in financial data time series mining. There has always been a problem of clustering massive financial time series data. Conventional clustering algorithms are not practical for time series data beca...
The industrial internet of things (IIoT) known as industry 4.0, is the use of internet of things technologies, via the Wireless Sensor Network (WSN), to enhance manufacturing and industrial processes. It incorporates machine learning and big data tec...
Assigning sentiment labels to documents is, at first sight, a standard multi-label classification task. Many approaches have been used for this task, but the current state-of-the-art solutions use deep neural networks (DNNs). As such, it seems likely...
Path planning, as the core of navigation control for mobile robots, has become the focus of research in the field of mobile robots. Various path planning algorithms have been recently proposed. In this paper, in view of the advantages and disadvantag...
Statistical bivariate numerical modeling is a method to infer an empirical relationship between unpaired sets of data based on statistical distributions matching. In the present paper, a novel efficient numerical algorithm is proposed to perform biva...
An ontology-based system can currently logically reason through the Web Ontology Language Description Logic (OWL DL). To perform probabilistic reasoning, the system must use a separate knowledge base, separate processing, or third-party applications....
Recently, the skyline query has attracted interest in a wide range of applications from recommendation systems to computer networks. The skyline query is useful to obtain the dominant data points from the given dataset. In the low-dimensional dataset...
The paper presents a flexible system for extracting features and creating training and test examples for solving the all-words sense disambiguation (WSD) task. The system allows integrating word and sense embeddings as part of an example description....
The application of machine learning models for prediction and prognosis of disease development has become an irrevocable part of cancer studies aimed at improving the subsequent therapy and management of patients. The application of machine learning...
Automatic dialog act recognition is an important step for dialog systems since it reveals the intention behind the words uttered by its conversational partners. Although most approaches on the task use word-level tokenization, there is information at...
The increase in demand for clean, safe, and environmentally friendly renewable energy sources faces several challenges such as system design and reliable operations. DC microgrid (MG) is a promising system due to higher efficiency and natural interfa...
Information systems support and ensure the practical running of the most critical business processes. There exists (or can be reconstructed) a record (log) of the process running in the information system. Computer methods of data mining can be used...
Machine learning algorithms are used in many applications nowadays. Sometimes, we need to describe how the decision models created output, and this may not be an easy task. Information visualization (InfoVis) techniques (e.g., TreeMap, parallel coord...
This article analyzes the available readiness indexes and maturity models applied for trends designated as “4.0”, with a focus on Industry 4.0, primarily within the countries of Europe. Based upon it, the available indexes and maturity mo...
The accurate analysis of periodic surface acoustic wave (SAW) structures by combined finite element method and boundary element method (FEM/BEM) is important for SAW design, especially in the extraction of couple-of-mode (COM) parameters. However, th...
The last decades have witnessed the progressive development of research on Internet topology at the router or autonomous systems (AS) level. Routers are essential components of ASes, which dominate their behaviors. It is important to identify the aff...
Recent advances in deep neural networks, language modeling and language generation have introduced new ideas to the field of conversational agents. As a result, deep neural models such as sequence-to-sequence, memory networks, and the Transformer hav...
The existing traffic light system fails to deal with the increase in vehicular traffic requirements due to fixed time programming. Traffic flow suffers from vehicle delay and congestion. A new networking technology called vehicular ad hoc networking...
The article discusses the problem of detecting network attacks on a web server. The attention is focused on two common types of attacks: “denial of service” and “code injection”. A review and an analysis of various attack dete...
Named data networking (NDN) is an alternative model to the current traditional IP-based Internet by improving content distribution in a network with content name. In NDN, content is sent/received based on its name rather than its address. Forwarding...
With self-provisioning of resources as premise, dew computing aims at providing computing services by minimizing the dependency over existing internetwork back-haul. Mobile devices have a huge potential to contribute to this emerging paradigm, not on...
