Polarity classification is one of the most fundamental problems in sentiment analysis. In this paper, we propose a novel method, Sound Cosine Similarity Matching, for polarity classification of Twitter messages which incorporates features based on audio data rather than on grammar or other text properties, i.e., eliminates the dependency on external dictionaries. It is useful especially for correctly

Many researchers have studied various visual communication cues (e.g. pointer, sketch, and hand gesture) in Mixed Reality remote collaboration systems for real-world tasks. However, the effect of combining them has not been so well explored. We studied the effect of these cues in four combinations: hand only, hand + pointer, hand + sketch, and hand + pointer + sketch, within the two user studies when

The complete parametrization of orthogonal hexagonally symmetric low-pass filters with \(\sqrt{3}\) refinement is presented for several cases of coefficient supports. Given a symmetric low-pass filter, a method that allows to construct hexagonally symmetric tight wavelet frames is suggested. Also, a framework for the construction of orthogonal hexagonally symmetric wavelets is presented.

In wireless localization systems, location information with respect to anchors will be exposed to untrusted target or third party inevitably leading to location privacy leakage. Differential privacy based techniques can provide theoretical guarantee to privacy preservation, while such privacy preservation will degrade localization accuracy. We note that the quantitative relationship between localization

Sparse arrays give rise to the possibility of miniaturization of sensor arrays for ultrasound imaging. The design of sparse arrays that preserves the full-array beampattern has received much attention in the recent past. Based on the transmit/receive pair array synthesis model proposed by Hoctor and Kassam, issues related to producing effective apertures twice their corresponding physical arrays have

In this letter, we aim to apply Nuttall's power-law processor, for which available data are raised to a power prior to summation, to the detection of variable length transient signals. The available data are often couched in frequency domain, where aggregation of transient signal energy into relatively small number of frequency bins is achieved by matching the DFT size with the transient length. However

We consider the problem of adaptive estimation of a linear functional of an unknown multivariate vector from its observations against white Gaussian noise. As a family of estimators for the functional, we use those generated by projection estimators of the unknown vector, and the main problem is to select the best estimator in this family. The goal of the paper is to explain and mathematically justify

Contraction coefficients are distribution dependent constants that are used to sharpen standard data processing inequalities for f-divergences (or relative f-entropies) and produce so-called “strong” data processing inequalities. For any bivariate joint distribution, i.e., any probability vector and stochastic matrix pair, it is known that contraction coefficients for f-divergences are upper bounded

We consider a hypothesis testing problem where a part of data cannot be observed. Our helper observes the missed data and can send us a limited amount of information about them. What kind of this limited information will allow us to make the best statistical inference? In particular, what is the minimum information sufficient to obtain the same results as if we directly observed all the data? We derive

For cycles of length 8 in a Tanner graph, we propose an identification procedure based on the analysis of paths in a protograph. We formulate and prove a number of theorems that introduce identification rules for cycles and restrict the number of subgraphs to be analyzed. To distinguish between them, we propose a number of parameters that uniquely determine the group of analyzed paths in the protograph

Different approaches were proposed to design deep CNNs for semantic segmentation. Usually, they are built upon an encoder–decoder architecture and require computationally expensive operations on high-resolution activation maps. Since for real-time segmentation the costs are critical, efficient approaches compromise spatial information to achieve real-time segmentation but with a considerable drop in

This paper considers the position and attitude tracking control of a quadrotor with inertia parameter uncertainty. With the aid of the cascade structure of the dynamics of the system, an immersion and invariance observer is proposed to estimate the unknown mass of the system first. Secondly, a saturation controller is designed for the thrust force. Thirdly, a virtual controller is proposed for the

Text simplification and text summarisation are related, but different sub-tasks in Natural Language Generation. Whereas summarisation attempts to reduce the length of a document, whilst keeping the original meaning, simplification attempts to reduce the complexity of a document. In this work, we combine both tasks of summarisation and simplification using a novel hybrid architecture of abstractive

Relation classification is one of the most fundamental tasks in the area of cross-media, which is essential for many practical applications such as information extraction, question&answer system, and knowledge base construction. In the cross-media semantic retrieval task, in order to meet the needs of cross-media uniform representation and semantic analysis, it is necessary to analyze the semantic

Crossmodal correspondence, a perceptual phenomenon which has been extensively studied in cognitive science, has been shown to play a critical role in people’s information processing performance. However, the evidence has been collected mostly based on strictly-controlled stimuli and displayed in a noise-free environment. In real-world interaction scenarios, background noise may blur crossmodal effects

An experiment is described that tested the possibility to classify wooden, plastic, and metallic objects based on reproduced auditory and vibrotactile stimuli. The results show that recognition rates are considerably above chance level with either unimodal auditory or vibrotactile feedback. Supported by those findings, the possibility to render virtual buttons for professional appliances with different

Intracerebral hemorrhage (ICH) is the most serious type of stroke, which results in a high disability or mortality rate. Therefore, accurate and rapid ICH region segmentation is of great significance for clinical diagnosis and treatment of ICH. In this paper, we focus on deep neural networks to automatically segment ICH regions. Firstly, we propose an encoder-decoder convolutional neural network (ED-Net)

Neural networks provide new possibilities to uncover semantic relationships between words by involving contextual information, and further a way to learn the matching pattern from document-query word contextual similarity matrix, which has brought promising results in IR. However, most neural IR methods rely on the conventional word-word matching framework for finding a relevant document for a query

The proposed work deals with a distinguished application of complex algebraic-geometric structure in nonlinear dynamical components of block ciphers. Due to the complex algebraic structure of the elliptic curves, their application in public-key cryptography has gained immense importance in recent years. The presented study introduces an effective application of elliptic curves in the nonlinear components

Most of the non-linear transceivers, which are based on Tomlinson-Harashima (TH) precoding and have been proposed in the literature for two-way relay systems, assume perfect channel state information (CSI). In this paper, a novel and robust TH precoding scheme has been investigated for two-way relay systems, with multiple antennas at the transceiver and relay nodes. We assume imperfect CSI and the

Quantum network enables quantum communication among quantum nodes and provides advantages that are unavailable in any classical network. Based on rapidly developing science and technology in quantum communication, the studies on quantum network have also made important progresses recent years. In this study, we briefly review the experimental progresses in building quantum network based on optical

Imbalance in data distribution hinders the learning performance of classifiers. To solve this problem, a popular type of methods is based on sampling (including oversampling for minority class and undersampling for majority class) so that the imbalanced data becomes relatively balanced data. However, they usually focus on one sampling technique, oversampling or undersampling. Such strategy makes the

Based on the identity-based encryption (IBE) from lattices by Agrawal et al. (Eurocrypt’10), Micciancio and Peikert (Eurocrypt’12) presented a CCA1-secure public-key encryption (PKE), which has the best known efficiency in the standard model and can be used to obtain a CCA2-secure PKE from lattices by using the generic BCHK transform (SIAM J Comput, 2006) with a cost of introducing extra overheads

Synchronization of complex networks with mixed time-varying coupling delays and stochastic perturbation. We constructed a novel Lyapunov functional with triple integral terms. By applying Jensen’s inequality and Lyapunov stability theory stability conditions are derived to check the asymptotical stability of the concerned system. By employing the stochastic evaluation and Kronecker product delay-dependent

Choosing the right parameter configurations for recurring jobs running on big data analytics platforms is difficult because there can be hundreds of possible parameter configurations to pick from. Even the selection of parameter configurations is based on different types of applications and user requirements. The difference between the best configuration and the worst configuration can have a performance

We explore global verifiability; discovering that voting systems vulnerable to attack can be proven to satisfy that security notion, whereas many secure systems cannot. We conclude that current definitions are unsuitable for the analysis of voting systems, fuelling the exploration for a suitable definition.

A dealer-free and non-interactive dynamic threshold secret sharing scheme has been proposed by Harn and Hsu in Information Processing Letters in 2015. In this scheme, a (t,n) secret sharing scheme in secret sharing phase can turn into a (m,n) scheme in secret reconstruction phase, where m is the number of participating shareholders. It has been claimed that the secrecy of shares and the secrecy of

Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

The papers in this special section focuses on security and privacy in industry. Industries, governments, and scientific communities are increasingly drawing special attention to competitive advantages that Industry 4.0 can bring to business sustainability and economy of a country. The tendency to couple information technologies (ITs) with the existing operational technologies (OTs) adds new opportunities

Previous studies have proven that integrating video signals, as a complementary modality, can facilitate improved performance for speech enhancement (SE). However, video clips usually contain large amounts of data and pose a high cost in terms of computational resources and thus may complicate the SE system. As an alternative source, a bone-conducted speech signal has a moderate data size while manifesting

We propose a cumulant-based algorithm for multiple near-field source localization based on exact source-sensor spatial geometry, where no simplification, such as Fresnel approximation of spatial phase-delay and inconsideration of propagation attenuation is made. We define five cumulant matrices, by which a set of coarse angle-range estimates plus a set of ambiguous angle-range estimates are derived

A consensus based distributed algorithm to compute the spectral radius of a network is proposed. The spectral radius of the graph is the largest eigenvalue of the adjacency matrix, and is a useful characterization of the network graph. Conventionally, centralized methods are used to compute the spectral radius, which involves eigenvalue decomposition of the adjacency matrix of the underlying graph

This letter investigates the performance of energy detector with multiple antennas in cognitive vehicular networks, where the sensing signals of the secondary user are temporally correlated. A novel analytical method, based on new results of confidence interval estimation for auto-correlated matrix in random matrix theory, is proposed to estimate the miss detection probability. The estimate accuracy

In this paper, we investigate the optimization of the monitoring rate for a suspicious multicast communication network with a legitimate full-duplex (FD) monitor, where the FD monitor is proactive to jam suspicious receivers and eavesdrop from the suspicious transmitter simultaneously. To effectively monitor the suspicious communication over multicast networks, we maximize the monitoring rate under

Cloud computing provides distributed computing resources such as servers, storage and applications to the end users through data centers. The data centers are geographically located at different locations. The client applications or requests being serviced by cloud service providers on “pay per use”. So, different pricing models are adapted to compute the cost and revenue of the data centers. The cost

Optical packet switching is a prominent technology proposing not only a reduction in the energy consumption by the elimination of numerous optical–electrical–optical conversions in electronic switches, but also a decrease in network latencies due to the cut-through nature of packet transmission. However, it is adversely affected by packet contention, preventing its deployment. Solutions have been proposed

Optical multi-domain transport networks are often controlled by a hierarchical distributed architecture of controllers. Optimal placement of these controllers is very important for efficient management and control. Traditional SDN controller placement methods focus mostly on controller placement in datacenter networks. But the problem of virtualized controller placement for multi-domain transport networks

Search engine optimization allows for users’ needs to be directly met by result snippets or a “knowledge map” without clicking any results. This behavior is called “good abandonment” and is found to frequently occur during mobile searching. Users exhibit such a behavior when they trust the result that addresses their information need without bothering to click it. Therefore, this study examines how

The spreading of misinformation and disinformation is a great problem on microblogs, leading user evaluation of information credibility a critical issue. This study incorporates two message format factors related to multimedia usage on microblogs (vividness and multimedia diagnosticity) with two well-discussed factors for information credibility (i.e., argument quality and source credibility) as a

In this study, optimum channel estimation in MIMO network is investigated by an integrated computing paradigm using Particle Swarm Optimization (PSO) and Nelder Mead Method (NMM). The efficacy of global optimization is exploited through PSO while for fine-tuning of channel coefficients, the strength of NMM as an efficient local optimization technique is utilized. Hybrid swarm intelligence framework

While the research area of artificial intelligence benefited from increasingly sophisticated machine learning techniques in recent years, the resulting systems suffer from a loss of transparency and comprehensibility, especially for end-users. In this paper, we explore the effects of incorporating virtual agents into explainable artificial intelligence (XAI) designs on the perceived trust of end-users

Interacting with an embodied conversational agent (ECA) in a professional context addresses social considerations to satisfy customer-relationship. This paper presents an experimental study about the perception of virtual intimacy in human-ECA interactions. We explore how an ECA’s multimodal communication affects our perception of virtual intimacy. To this end, we developed a virtual Tourism Information

Augmented reality (AR) technologies provide a shared platform for users to collaborate in a physical context involving both real and virtual content. To enhance the quality of interaction between AR users, researchers have proposed augmenting users’ interpersonal space with embodied cues such as their gaze direction. While beneficial in achieving improved interpersonal spatial communication, such shared

Traditional clustering algorithms have some limitations, which are sensitive to noise and mostly applicable to convex data sets. To solve these problems, the paper proposes a novel algorithm combining spectral clustering with feature selection. Specifically, the loss item is marked with a root that can reduce the deviation value then improve the robustness of the model. And in the algorithm optimization

In this paper an adaptive optimized fast blind channel estimation using cyclic prefix supported with Space Time Block Coded Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (STBC-MIMO-OFDM) system is presented. The main aspire of our technique is to support multiple users at the same time over same frequency band based on the Multi-Carrier Code-Division Multiple Access (MC-CDMA)

The study investigates the trajectory estimation problem of a noncooperative gliding flight vehicle with complex and atypical maneuvers. An active switching multiple model (ASMM) method is proposed. This method employs a motion behavior model set (MBMS), a motion behavior recognition algorithm, and an active switching estimation and fusion algorithm. First, a recognizable MBMS, which can capture all

A hexagonal shaped fractal Multiple input Multiple Output (MIMO) antenna resonates to six different frequencies is presented. A dumbbell structure with hexagon shaped defected ground structure (DGS) is created in the ground plane. Two antenna elements sharing a common ground plane are positioned orthogonal to each other for better isolation. The antenna is designed, fabricated using FR4 substrate with

The nature of human/instrument interaction is a long-standing area of study, drawing interest from fields as diverse as philosophy, cognitive sciences, anthropology, human–computer-interaction, and artistic creation. In particular, the case of the interaction between performer and musical instrument provides an enticing framework for studying the instrumental dynamics that allow for embodiment, skill

In wireless sensor networks, the signals received by sensors are usually complex nonlinear single-channel mixed signals. In practical applications, it is necessary to separate the useful signals from the complex nonlinear mixed signals. However, the traditional array signal blind source separation algorithms are difficult to separate the nonlinear signals effectively. Building upon the traditional

Very few people would argue against that today’s business environments are subjected to more and more instability that has its roots not only in a highly competitive business environments where new distributive business models fueled by the increase in technology advances and the broader society adoptions of theses technology advances, but also the subjection to constant change from hostile takeovers

Dynamic routing and wavelength assignment problem in optical networks is a two-step problem that is influenced by the choice of a successful optimal path selection and wavelength assignment. Proper selection techniques reduce the number of wavelengths required in the network and thereby improves traffic grooming. Heuristic algorithms and integer linear programming models help in selection of route

Various kinds of smart sensors are being developed and released with the growth of sensor technology and Internet of Things (IoT) technology. IoT smart service can provide convenience in our daily lives with these smart sensors. However, the increasing number of mobile sensors and amount of data may increase latency. It may cause network congestion on a particular network. Therefore, we propose a Smart

Emerging inter-datacenter applications involving data transferred, processed, and analyzed at multiple datacenters, such as virtual machine migrations, real-time data backup, remote desktop, and virtual datacenters, can be modeled as virtual network requests that share computing and spectrum resources of a common substrate physical inter-datacenter network. Recent advances make elastic optical networks

In this paper, stochastic stability and stabilization problems are investigated for the Markovian switching complex-valued neural networks with mixed delays, where the transition rates (TRs) of the Markov chain are partly unknown, which might reflect more the realistic dynamical behaviors of the neural networks. On the basis of the Lyapunov stability theory and the stochastic analysis method as well

Intelligent transportation system (ITS) is an advance leading edge technology that aims to deliver innovative services to different modes of transport and traffic management. Traffic flow prediction (TFP) is one of the key macroscopic parameters of traffic that supports traffic management in ITS. Growth of the real-time data in transportation from various modern equipments, technology, and other resources

Real-time processing and learning of conflicting data, especially messages coming from different ideas, locations, and time, in a dynamic environment such as Twitter is a challenging task that recently gained lots of attention. This paper introduces a framework for managing, processing, analyzing, detecting, and tracking topics in streaming data. We propose a model selector procedure with a hybrid

Abstract The nature of information (conceptual) systems is studied using a system–object approach. The conclusion is made that the hierarchies of conceptual and material systems are an object-oriented system, whose conceptual systems are external systems (class systems) that determine the properties of specific objects, and objects–material or internal systems (systems–phenomena) that perform real