Recommender systems nowadays play an important role in providing helpful information for users, especially in ecommerce applications. Many of the proposed models use rating histories of the users in order to predict unknown ratings. Recently, users’ reviews as a valuable source of knowledge have attracted the attention of researchers in this field and a new category denoted as review-based recommender

The concept of smart systems blessed with different technologies can enable many algorithms used in Machine Learning (ML) and the world of the Internet of Things (IoT). In a modern city many different sensors can be used for information collection. Algorithms that are cast-off in Machine Learning improves the capabilities and intelligence of a system when the amount of data collectedincreases. In this

Neighbor discovery is a fundamental task to support many other services in wireless multihop networks (WMN). Most existing related methods in WMN rely heavily on the information of radio waves. To extend the way to the neighbor discovery, this paper introduces another interesting way, visual light communication, to explore its property of linear transmission. We apply light emitting diode (LED) array

Users of cloud computing technology can lease resources instead of spending an excessive charge for their ownership. For service delivery in the infrastructure-as-a-service model of the cloud computing paradigm, virtual machines (VMs) are created by the hypervisor. This software is installed on a bare-metal server, called the host, and acted as a broker between the hardware of the host and its VMs

AbstractIn this paper, we propose the first efficient, reliable and safe snap-stabilizing $m$-$wave$ (multi-initiator wave) algorithm implementing concurrent waves started by multiple initiator processes in tree networks. Unlike its self-stabilizing counterpart and broadcast algorithms, the proposed algorithm is a reliable and safe $m$-wave algorithm, i.e. it implements an $m$-wave such that after

In view of the fact that the existing public opinion propagation aspects are mostly based on single-layer propagation network, these works rarely consider the double-layer network structure and the negative opinion evolution. This paper proposes a new susceptible-infected-vaccinated-susceptible negative opinion information propagation model with preventive vaccination by constructing double-layer network

Many graph query languages rely on composition to navigate graphs and select nodes of interest, even though evaluating compositions of relations can be costly. Often, this need for composition can be reduced by rewriting toward queries using semi-joins instead, resulting in a significant reduction of the query evaluation cost. We study techniques to recognize and apply such rewritings. Concretely,

Twitter is an extensively used micro-blogging site for publishing user’s views on recent happenings. This wide reachability of messages over large audience poses a threat, as the degree of personally identifiable information disclosed might lead to user regrets. The Tweet-Scan-Post system scans the tweets contextually for sensitive messages. The tweet repository was generated using cyber-keywords for

It is a hot spot in the field of computer application to diagnose complex brain diseases such as Asperger syndrome (AS) using machine learning technology. To identify AS patients and detect lesions, this paper proposes a novel clustering-evolutionary random support vector machine (SVM) ensemble (CERSVME) based on graph theory. Firstly, we extract graph theory indexes from the resting-state functional

Medical imaging shows the internal structures hidden in the skin and bone to diagnose the disease. Diabetes mellitus (DM) is a metabolic disorder that causes high blood sugar levels due to the inadequate secretion of insulin or the body does not respond properly to the secreted insulin. This paper proposes a non-invasive method to detect DM at an early stage based on the physiognomy extracted from

The inability to scale is one of the most concerning problems looming in blockchain systems, where every node has to store all contents of the ledger database locally, leading to centralization and higher operation costs. In this paper, we propose a model named virtual block group (VBG), which aims at addressing the node storage scalability problem. Adopting the VBG model, each node only needs to store

With the advent of e-commerce sites and social media, users express their preferences and tastes freely through user-generated content such as reviews and comments. In order to promote cross-selling, e-commerce sites such as eBay and Amazon regularly use such inputs from multiple domains and suggest items with which users may be interested. In this paper, we propose a topic coherence-based cross-domain

This study aims to explain a simple but crucial complex problem often faced by multinational enterprises: why multinational companies choose to enter the markets of certain countries. Accordingly, this study developed an international expansion selection model by using the machine learning method. The priority targets for enterprises’ international expansion and the strategic country groups for classification

Traffic accidents are a common problem in any transportation network. Road traffic accidents are predicted to be the seventh leading cause of deaths by the year 2030. Recently research in the integration of geographical information systems (GIS) for analyzing accidents, road design and safety management has increased considerably. The perpetual use of GIS tools, lead this study to propose the identification

Flying ad hoc networks (FANETs) are a collection of unmanned aerial vehicles that communicate without any predefined infrastructure. FANET, being one of the most researched topics nowadays, finds its scope in many complex applications like drones used for military applications, border surveillance systems and other systems like civil applications in traffic monitoring and disaster management. Quality

AbstractIn this paper, we propose the first efficient, reliable and safe snap-stabilizing $m$-$wave$ (multi-initiator wave) algorithm implementing concurrent waves started by multiple initiator processes in tree networks. Unlike its self-stabilizing counterpart and broadcast algorithms, the proposed algorithm is a reliable and safe $m$-wave algorithm, i.e. it implements an $m$-wave such that after

Modular exponentiation, as a fundamental operation used in many public-key cryptosystems, has always be considered to be very time-consuming. It is difficult for some devices with limited computation capability, such as mobile devices and low-cost radio frequency identification (RFID) tags, to perform large-scale modular exponentiations. In cryptosystems, one typical case of modular exponentiation

Combinatorial interaction testing (CIT) aims at constructing a covering array (CA) of all value combinations at a specific interaction strength, to detect faults that are caused by the interaction of parameters. CIT has been widely used in different applications, with many algorithms and tools having been proposed to support CA construction. To date, however, there appears to have been no studies comparing

The performance of underwater acoustic communication system is affected seriously by inter-symbol interference caused by multipath effects. Therefore, a novel blind equalization algorithm based on constant modulus algorithm (CMA) and decision-directed least mean square (DD_LMS) is adopted to improve the equalization ability of the system. Firstly, the LMS algorithm is improved by introducing inverse

For the past few years, the automated addressing of changes in remote sensing images plays a significant role. However, the change detection (CD) model often suffers from the issue of speckle noise. More investigations have been proceeded to overcome this obstacle. This paper also considers the same issue and proposes a new CD model in synthetic aperture radar (SAR) images. Here, two SAR images that

Cloud adoption has significantly increased using the infrastructure-as-a-service (IaaS) paradigm, in order to meet the growing demands of computing, storage and networking, in small as well as large enterprises. Different vendors provide their customized solutions for OpenStack deployment on bare metal or virtual infrastructure. Among these many available IaaS solutions, OpenStack stands out as being

Crowd emotion understanding is an interesting research area that assists the security personnel to read the emotion/activity of the crowd in the locality. Most of the traditional methods utilize the low-level visual features to understand the crowd emotions that extend the gap between the low- and the high-level features. With the aim to develop an automatic method for emotion recognition, this paper

The rapid increase in information and technology has led to the increased amount of web pages, which raises the complexity in sticking to relevant web pages, and the visitor suffers due to wastage of time resulting in lack of satisfaction. This paper proposes a web page prediction method using a weighed support and Bhattacharya distance-based (WS-BD) two-level match. The major aim of the proposed method

Vehicular ad hoc networks (VANETs) have emerged as an appropriate class of information propagation technology promising to link us even while moving at high speeds. In VANETs, a piece of information propagates through consecutive connections. In the most previous vehicular connectivity analysis, the provided probability density function of intervehicle distance throughout the wide variety of steady-state

The principle of orthogonal frequency-division multiplexing (OFDM) is to transmit the data through a large number of multiple orthogonal subcarriers. The coherent optical OFDM (CO-OFDM) is OFDM data that are being modulated to light frequency and being detected in coherent manner. CO-OFDM brings to optical communications the combination of two powerful techniques, coherent optical detection and OFDM

We present a silent self-stabilizing distributed algorithm computing a maximal |$\ p$|-star decomposition of the underlying communication network. Under the unfair distributed scheduler, the most general scheduler model, the algorithm converges in at most |$12\Delta m + \mathcal{O}(m+n)$| moves, where |$m$| is the number of edges, |$n$| is the number of nodes and |$\Delta $| is the maximum node degree

This paper proposes a retrievable data perturbation model for overcoming the challenges in cloud computing. Initially, genetic whale optimization algorithm (genetic WOA) is developed by integrating genetic algorithm (GA) and WOA for generating the optimized secret key. Then, the input data and the optimized secret key are given to the Tracy–Singh product-based model for transforming the original database

Wireless-charging technology can utilize a mobile wireless charging vehicle (WCV) to rescue dying nodes by supplementing their remaining energy, and using WCVs in this way forms wireless rechargeable sensor networks (WRSNs). However, a WCV in a WRSN encounters several challenges, collectively called the optimized charging problem. This problem involves a set of sensor nodes randomly distributed on

Electricity is a major cost in running a data centre, and servers are responsible for a significant percentage of the power consumption. Given the widespread use of HTTP, both as a service and a component of other services, it is worthwhile reducing the power consumption of web servers. In this paper we consider how reverse proxies, commonly used to improve the performance of web servers, might be

Underwater wireless sensor network (UWSN) has gained its popularity as a powerful technology for monitoring oceans, sea and river. The sensor node drifting along with ocean current offers 4D (space and time) monitoring for real-time underwater application. However, the main challenge arises from the underwater acoustic communication that results in high propagation delay, packet loss and overhead in

Suffix trees are one of the most versatile data structures in stringology, with many applications in bioinformatics. Their main drawback is their size, which can be tens of times larger than the input sequence. Much effort has been put into reducing the space usage, leading ultimately to compressed suffix trees. These compressed data structures can efficiently simulate the suffix tree, while using

There is considerable evidence that exposure to air pollution is harmful to health. In the U.S., ambient air quality is monitored by Federal and State agencies for regulatory purposes. There are limited options, however, for people to access this data in real-time which hinders an individual's ability to manage their own risks. This paper describes a new software package that models environmental concentrations

Nuclear magnetic resonance (NMR) spectroscopy is an important experimental technique that allows one to study protein structure and dynamics in solution. An important bottleneck in NMR protein structure determination is the assignment of NMR peaks to the corresponding nuclei. Structure-based assignment (SBA) aims to solve this problem with the help of a template protein which is homologous to the target