Tipping, as a new model of content monetization, is being adopted widely. Leveraging the policy changes in one of the largest social media platforms, we examined when and how tip-based content monetization incentives work. We adopt framing theory to explain different attitudes toward content monetization incentives between status-framed and benefit-framed users. Our results show that a hierarchical

Previous studies have analyzed the impact of cybersecurity breaches on firm performance, but the impact of the privacy breach on firm performance is less explored. Needless to say, the privacy of the individual's personal information has been a rising concern for organizations over the years. Previous studies, primarily focused on cybersecurity breaches, have used a simple market model (MM) to observe

We examine the impacts of mobile app category assortment of developers’ app portfolios on app performance in terms of quality and popularity. First, using data from the Apple App Store, we find a negative effect of portfolio diversity on developers’ app quality, which is negatively moderated by portfolio size. Second, we uncover spillover effects on app popularity, where existing (new) apps of a developer

This article investigates the neural-network-based adaptive predefined-time tracking control problem for switched nonlinear systems. Neural networks are employed to approximate the unknown part of nonlinear functions. The finite-time differentiators are introduced to estimate the first derivative of the virtual controllers. Then, a novel adaptive predefined-time controller is proposed by utilizing

This article considers the problem of cooperative fault-tolerant output regulation of linear heterogeneous multiagent systems with actuator faults where the exosystem matrix is known by part of the followers. An adaptive dynamic event-triggered scheme is proposed to avoid continuous communication between followers, removing the assumption that global information should be known for controller design

This article studies the adaptive output-feedback consensus control problem of nonlinear multiagent systems (MASs) against denial-of-service (DoS) attacks. The attacks on the edges instead of nodes are considered, where we allow different attack intensities but at least one edge is connected in each attacking interval. Affected by output disturbance, the sensor feedback signal of every agent is inaccurate

Non-negative matrix factorization (NMF) has become a popular method for learning interpretable patterns from data. As one of the variants of standard NMF, convolutive NMF (CNMF) incorporates an extra time dimension to each basis, known as convolutive bases, which is well suited for representing sequential patterns. Previously proposed algorithms for solving CNMF use multiplicative updates which can

Gesture recognition based on surface electromyography (sEMG) has been widely used in the field of human-machine interaction (HMI). However, sEMG has limitations, such as low signal-to-noise ratio and insensitivity to fine finger movements, so we consider adding A-mode ultrasound (AUS) to enhance the recognition impact. To explore the influence of multisource sensing data on gesture recognition and

In this study, we investigated the optimal tracking performance (OTP) of feedback control systems with limited bandwidth and colored noise in a fading channel. For the steady state of the feedback control systems, an equivalent average channel (EAC) model was developed by retaining the effects of the first and second moments of the multiplicative channel output, and on the basis of the coprime decomposition

An increase in the vividness of mental imagery can enhance the persuasive appeal of advertisements. To examine the effects of sensory imagery enriched by smelling (olfactory) and tasting (gustatory) in online video-based advertisements, we adopted multi-method empirical investigations to validate our conceptions. Electroencephalograms (EEGs) and survey data collected from 166 customers provide strong

Establishing an automated defect detection system is a critical task for industrial production, but the current defect detection system still faces great challenges, especially for defects with blurred edges and weak defects in complex backgrounds. To solve these problems, we propose an edge-guided and differential attention network (EGD-Net), which can highlight the defect areas by strengthening edge

As congestive heart failure (CHF) has become an important medical problem facing the world, the detection of the CHF is very important. Internet of medical things (IoMT) has been increasing popularity as its application and function in industry 4.0 era. IoMT systems provide an opportunity for innovations and cross-discipline applications in the medical fields, that can significantly improve the efficiency

While autonomous systems can be used for a variety of beneficial applications, they can also be used for malicious intentions and it is mandatory to disrupt them before they act. So, an accurate trajectory inference algorithm is required for monitoring purposes that allows to take appropriate countermeasures. This article presents a closed-loop output error approach for trajectory inference of a class

The multiobjective optimal control method optimizes the performance indexes of nonlinear systems to obtain setpoints, and designs a controller to track the setpoints. However, the stepwise optimal control method that independently analyzes the optimization process may obtain unfeasible and difficult to track setpoints, which will reduce the operation and control performance of the systems. To solve

The distributed optimization problem (DOP) of Takagi-Sugeno (T-S) fuzzy cyber-physical systems is studied under the framework of weight-balanced graphs and quasistrongly connected characteristics. The objective is to drive the outputs of all agents to the optimal solution of a given global objective function regarded as the desired output, based on the partial information of the local objective functions

In this article, the output synchronization of heterogeneous multiagent systems with sensor faults is considered. To detect and tolerate the faults, a number of detection mechanisms and fault-tolerant controllers (FTCs) have been proposed. Whereas, the existing methods require the precise model and they cannot be used when model information is unknown. Moreover, some designed parameters are required

Most of the classical conditioning laws implemented by existing circuits are involved in learning and forgetting between only three neurons, and the problems between multiple neurons are not considered. In this article, a multimode generalization and differentiation circuit for the Pavlov associative memory is proposed based on memristors. The designed circuit is mainly composed of voltage control

This research investigates the stability of discrete-time neural networks (DNNs) with a time-varying delay by using the Lyapunov-Krasovskii functional (LKF) method. Recent researches acquired some less conservatism stability criteria for time-varying delayed systems via some augmented LKFs. However, the forward difference of such LKFs resulted in high-degree time-varying delay-dependent polynomials

COVID-19 created a great deal of personal, social, and economic anxiety in the USA and across the globe and exposed the inadequacy of traditional medical systems in handling large-scale emergencies. While telemedicine and virtual visits have become popular as a result, they end once a visit is over, hence lacking data persistence and continuity in caring for patients. Using the design science research

Surrogate-assisted evolutionary algorithms (SAEAs) have shown promising performance for solving expensive optimization problems (EOPs) whose true evaluations are computationally or physically expensive. However, most existing SAEAs only focus on the problems with low dimensionality and they rarely consider solving large-scale EOPs (LSEOPs). To fill this research gap, this article proposes an ensemble

This paper studies a convincingly secure transmission framework under an allowable outage probability for practical finite-alphabet inputs, where a full-duplex receiver (Bob) is taken into account to emit the artificial noise for deteriorating the eavesdropper’s decoding performance. We develop a secure-reliable mechanism to take the place of prior secrecy rate (SR) maximization strategy, where a closed

Under false data-injection (FDI) attacks, the data of some agents are tampered with by the FDI attackers, which causes that the distributed algorithm cannot estimate the ideal unknown parameter. Due to the concealment of the malicious data tampered with by the FDI attacks, many detection algorithms against FDI attacks often have poor detection results or low detection efficiencies. To solve these problems

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The Ever-Increasing evolution of technologies in communication, artificial intelligence (AI), manufacturing, etc., is promoting a new wave of industrial revolution. Industrial Internet of Things (IIoT) has been considered as a critical stimulator for both science and economics by amounts of countries.

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Soft magnetic miniature robots (SMMRs) have potential biomedical applications due to their flexible size and mobility to access confined environments. However, navigating the robot to a goal site with precise control performance and high repeatability in unstructured environments, especially in flow rate conditions, still remains a challenge. In this study, drawing inspiration from the control requirements

This article investigates the fault-tolerant coordinated tracking control problem for networked fixed-wing unmanned aerial vehicles (UAVs) against faults and communication delays. By supplementing the commonly used Gaussian functions in the fuzzy neural networks (FNNs) with sine-cosine functions and constructing two kinds of recurrent loops within the FNN architecture, double recurrent perturbation

In this article, the optimal control strategy for organism is investigated by using the adaptive dynamic programming (ADP) method under the architecture of nonzero-sum games (NZSGs). First, a tumor model is established to formulate the interaction relationships among normal cells, tumor cells, endothelial cells, and the concentrations of drugs. Then, the ADP-based method of single-critic network architecture

This article investigates the consensus problem of multiagent systems (MASs) with time-varying delays subject to switching topologies. For the purpose of obtaining less conservative consensus conditions, first, a delay-product-type Lyapunov-Krasovskii functional (LKF) based on the auxiliary function-based integral inequality (AFBII) is constructed. Then, the generalized reciprocally convex matrix inequality

In this article, evolving and incremental value iteration (VI) frameworks are constructed to address the discrete-time zero-sum game problem. First, the evolving scheme means that the closed-loop system is regulated by using the evolving policy pair. During the control stage, we are committed to establishing the stability criterion in order to guarantee the availability of evolving policy pairs. Second

A zero-sum tax/subsidy approach for stabilizing unstable Nash equilibria in pseudo-gradient-based noncooperative dynamical systems is proposed without the information of agents' personal sensitivity parameters. Specifically, we first present several sufficient conditions for guaranteeing stability of an unstable Nash equilibrium in the face of uncertainty. Furthermore, we develop a framework where

The set covering problem (SCP) is a fundamental NP-hard problem in computer science and has a broad range of important real-world applications. In practice, SCP instances transformed from real-world applications would be of large scale, so it is of significant importance to design effective heuristic algorithms, especially local search ones. However, there exist only few research works on developing

Tensor completion is the problem of estimating the missing values of high-order data from partially observed entries. Data corruption due to prevailing outliers poses major challenges to traditional tensor completion algorithms, which catalyzed the development of robust algorithms that alleviate the effect of outliers. However, existing robust methods largely presume that the corruption is sparse,

We introduce the use of video coding settings for source identification and propose a new approach that incorporates encoding and encapsulation aspects of a video. To this end, a joint representation of the overall file metadata is developed and used in conjunction with a two-level hierarchical classification method. At the first level, our method groups videos into metaclasses considering several

Person re-identification (Re-ID) is a critical technique in the video surveillance system, which has achieved significant success in the supervised setting. However, it is difficult to directly apply the supervised model to arbitrary unseen domains due to the domain gap between the available source domains and unseen target domains. In this paper, we propose a novel label distribution learning (LDL)

We examine the content of the official Facebook pages of 502 Italian municipalities over the period 2016–2018 to empirically infer the motivations of municipalities to use Facebook. Our inference is mostly based on the relationship between the main topics discussed by the municipalities on Facebook and the most related municipal expenses per capita, which are reported by function in municipal financial

This article is concerned with cluster consensus control of multiagent systems (MASs) with the fixed/switching topology under a dynamic event-trigger (DET) mechanism. A refined sampled-data-based DET scheme is proposed by introducing two dynamically adjusting threshold parameters to distinguish the different transmission requirements for neighboring agents intra and outer cluster. Faced with the difficulties

Understanding the feedback loop that links the spatiotemporal spread of infectious diseases and human behavior is an open problem. To study this problem, we develop a multiplex framework that couples epidemic spreading across subpopulations in a metapopulation network (i.e., physical layer) with the spreading of awareness about the epidemic in a communication network (i.e., virtual layer). We explicitly

This article investigates the distributed optimal output consensus problem of heterogeneous linear multiagent systems over weight-unbalanced directed networks. A novel distributed continuous-time state feedback controller is proposed to steer the outputs of all the agents to converge to the optimal solution of the global cost function. Under the standard condition that the unbalanced digraph is strongly

This article is concerned with the bipartite synchronization problem of coupled switching neural networks with cooperative-competitive interactions and reaction-diffusion terms. Different from the existing literature, the networked systems under investigation possess the relationship of cooperation and competition among nodes. Notably, the switching topology is described by a signed graph subject to

This article studies the global prescribed-time stabilization problem for a class of time-delay nonlinear systems with uncertain parameters. First, we design two time-varying gains with special properties, in which one is introduced into virtual controllers to achieve prescribed-time convergence and the other one is used to construct the Lyapunov-Krasovskii (L-K) functional and Lyapunov function to

Fuzzy utility (FU) pattern mining with an advantage in human reasoning has become one of the interesting topics in studies of knowledge discovery. The discovered information in FU pattern mining from real-life quantitative databases with item profits is suitable for interpreting data from a human perspective because it is not expressed using numerical values but linguistic terms which consist of natural

Community microgrids, as an emerging technology, offer resiliency in operation for smart grids. Microgrids are seeing an increased penetration of eco-friendly electric vehicles (EVs) in recent years. However, the uncontrolled charging of EVs can easily overwhelm such electric networks. In this work, we propose an efficient demand response (DR) scheme based on dynamic pricing to enhance the capacity

This article investigates the event-driven fault-tolerance (ETFT) consensus problem for general linear multiagent systems (MASs) with partial loss of effectiveness (PLOE) and bias faults of actuators in leader-follower networks. Each agent's controller is only updated relatively infrequently at its event moments. A desirable feature of this article is that the proposed event-driven algorithm is fully

The present research on the multi-sensor information fusion technology of mobile robots aims to better understand the outdoor scene and improve the robot's perception of the environment. Firstly, a conversion algorithm is proposed based on two point-cloud-to-image algorithms, including the point cloud plane fitting and point cloud projection transformation. Moreover, the elevation map is constructed

Compared to text, photos are more conspicuous and suited for self-presentation. Although other motivations, such as helping others, partly account for photo sharing in online reviews, we emphasize a model of social status in which a conspicuous display of distant tourism products is used as a signal of an individual's status. Drawing on self-enhancement theory, we test hypotheses concerning exhibitionistic

Quantum blockchain is expected to offer an alternative to classical blockchain to resist malicious attacks laughed by future quantum computers. Although a few quantum blockchain schemes have been constructed, their efficiency is low and unable to meet application requirements due to the fact that they lack of a suitable consensus mechanism. To tackle this issue, a consensus mechanism called quantum

In this paper, we investigate the optimal probabilistic constellation shaping design for covert communication systems from a practical view. Different from conventional covert communications with equiprobable constellations modulation, we propose non-equiprobable constellations modulation schemes to further enhance the covert rate. Specifically, we derive covert rate expressions for practical discrete

Typical deep neural network (DNN) backdoor attacks are based on triggers embedded in inputs. Existing imperceptible triggers are computationally expensive or low in attack success. In this paper, we propose a new backdoor trigger, which is easy to generate, imperceptible, and highly effective. The new trigger is a uniformly randomly generated three-dimensional (3D) binary pattern that can be horizontally

Big data are a prominent source of value capable of generating competitive advantage and superior business performance. This paper represents the first empirical investigation of the theoretical model proposed by Grover et al. (2018), considering the mediating effects of four value creation mechanisms on the relationship between big data analytics capabilities (BDAC) and four value targets. The four

In this article, we consider the optimal sensor scheduling for remote state estimation in cyber-physical systems (CPSs). Different from the existing works concerning the time-invariant channel state in the wireless communication network, our work considers the time-varying channel state modeled by a finite-state Markov channel (FSMC). We focus on the problem of how to schedule the transmission of the

In this paper, we study the secrecy performance of non-orthogonal multiple access (NOMA) enabled visible light communication (VLC) broadcast channels in the presence of an active eavesdropper (Eve). The considered VLC system consists of multiple separately distributed light-emitting diodes arrays and multiple randomly located users (UEs) in an indoor room. User clustering is conducted to reduce the

Published in Journal of Management Information Systems (Vol. 39, No. 3, 2022)

ABSTRACT If managers assume a normal or near-normal distribution of Information Technology (IT) project cost overruns, as is common, and cost overruns can be shown to follow a power-law distribution, managers may be unwittingly exposing their organizations to extreme risk by severely underestimating the probability of large cost overruns. In this research, we collect and analyze a large sample comprised

ABSTRACT Project escalation involves the continued, persistent commitment to a failing project. Through a qualitative meta-analysis of 15 published cases of large information systems (IS) projects in escalation situations, we develop an institutional perspective on IS projects in escalation situations. This perspective describes how project persistence emerges from a plurality of legitimizing institutional

ABSTRACT Social media firestorms (SMF) are commonly seen as destructive forces of toxic comments hurled at a target for perceived wrongdoing. Yet some research suggests that SMF can provide beneficial outcomes for the target. In two studies, we qualitatively examine SMF comments (in terms of purpose and tone) and quantitatively examine users’ motivations for making different types of comments. Results

ABSTRACT Firms and investors often react to financial news on social media. However, how they react to news of different nature and whether their reactions influence the stock market is far from clear. Employing data on financial news, tweets posted by firms and investors, and daily stock prices, we find that firms are more responsive to news with positive sentiment and low uncertainty, whereas investors