-
A new approach based on the discriminant system of polynomial for robust stability and stabilization of two-dimensional systems J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-09 Xiaoxue Li; Xiaorong Hou
In this paper, we present necessary and sufficient stability and robust stability conditions for two-dimensional (2D) systems described by the Fornasini-Marchesini (FM) second model in terms of the discriminant systems of polynomial. This paper simplifies the traditional method of stability into a tractable method by the fractional linear transformation (FLT). More specifically, we reduce the stability
-
Global output feedback stabilization for a class of nonlinear systems with multiple uncertainties J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-14 Zong-Yao Sun; Kai Zhang; Chih-Chiang Chen; Qian Zhao
This paper investigates the problem of global output feedback stabilization for a class of nonlinear systems with multiple uncertainties. A remarkable feature lies in that the system to be considered is not only involved dynamic and parametric uncertainties but also the measurement output affected by an uncertain continuous function, which leads to the obstacles in the constructions of a state observer
-
Robust active suppression for body-freedom flutter of a flying-wing unmanned aerial vehicle J. Franklin Inst. (IF 4.036) Pub Date : 2021-02-02 Qitong Zou; Xusheng Mu; Hongkun Li; Rui Huang; Haiyan Hu
Flying-wing unmanned aerial vehicles have received extensive attention over the past decade because of their excellent aerodynamic and stealth performance. However, the aeroelastic interaction problems among unsteady aerodynamics, flight dynamics, and structural dynamics, such as the body-freedom flutter, are still open. This paper presents the study of a robust control scheme for active body-freedom
-
Event-triggered control for networked control system via an improved integral inequality J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-28 Feng Hu; Chunting Jiao; Hongbin Chang; Xiaojie Su; Yongcheng Gu
This paper focuses on event-triggered controller design problem for a networked control system via a novel integral inequality based on Lyapounov-Krasovskii functional (LKF). Specifically, a new integral inequality is applied to bound integral term, which produces tighter bounds than some existing ones. First, take into account static quantization, a networked control system model with two successive
-
Dissipative output feedback control for semi-Markovian jump systems under hybrid cyber-attacks J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-28 Huiyan Zhang; Xiuli He; Luis I. Minchala; Peng Shi
In this paper, the dissipativity-based dynamic output feedback controller (DOFC) design for Semi-Markovian jump systems under stochastic cyber-attacks is first proposed. It is assumed that the time-varying uncertainties obey Bernoulli-distribution and transition probability matrix is time-varying and partially accessed. By utilizing the dissipativity-based technique, sufficient conditions for the existence
-
Finite-time unknown observer based coordinated path-following control of unmanned underwater vehicles J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-29 Xiao Liang; Xingru Qu; Yuanhang Hou; Ye Li; Rubo Zhang
In this paper, a coordinated path-following control (CPFC) scheme is proposed for multiple unmanned underwater vehicles (UUVs) under undirected communication links. Each UUV is subject to complex unknowns involving model parameter perturbations and time-varying external disturbances. In light of individual path-following control, the coordinated guidance laws are developed to guide UUV surge velocities
-
Reliable dissipative control for fuzzy singular semi-markovian jump systems with mode-dependent delays and randomly occuring uncertainties J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-28 Xin Li; Xiaowu Mu; Zhe Yang
This article addresses the problem of dissipative control for fuzzy singular semi-Markovian jump systems with actuator faults, mode-dependent delays and randomly occuring uncertainties. Firstly, Takagi-Sugeno fuzzy model is utilized to describe the singular nonlinear semi-Markovian jump delayed systems. Then, a more general actuator fault model is considered and the fuzzy reliable controller is designed
-
Input-to-state stabilization of time-delay systems: An event-triggered hybrid approach with delay-dependent impulses J. Franklin Inst. (IF 4.036) Pub Date : 2021-02-05 Xiang Xie; Haiyang Zhang; Xinzhi Liu; Honglei Xu; Xiaodi Li
This paper studies the input-to-state stabilization problem of nonlinear time-delay systems. A novel event-triggered hybrid controller is proposed, where feedback controller and distributed-delayed impulsive controller are taken into account. By using the Lyapunov-Krasovskii method, sufficient conditions for input-to-state stability are constructed under the designed event-triggered hybrid controller
-
Discrete-time command filtered adaptive fuzzy fault-tolerant control for induction motors with unknown load disturbances J. Franklin Inst. (IF 4.036) Pub Date : 2021-02-04 Qixin Lei; Jinpeng Yu; Qing-guo Wang
In this paper, a command filtered fault-tolerant control (CFFTC) approach is investigated for induction motors (IMs) discrete-time system in the presence of actuator faults and unknown load disturbances. Firstly, the IMs system discrete-time model is obtained by Euler method. Then, the fuzzy logic systems (FLSs) is utilized to compensate for unknown actuator faults. Besides, introducing the error compensation
-
Resilient consensus of discrete-time connected vehicle systems with interaction network against cyber-attacks J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-29 Yonggui Liu; Ziyuan Li; Zhiping Shen
This paper concerns the consensus of the second-order discrete-time autonomous connected vehicle system (CVS) in presence of cyber-attacks. First, the necessary and sufficient conditions for the autonomous CVS are derived without a cyber-attack. Then, a virtual system in hidden layer, interconnected with the original CVS in platoon layer through the designed interaction network, is introduced to resist
-
Secure distributed Kalman filter using partially homomorphic encryption J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-22 Ladan Sadeghikhorami; Ali Akbar Safavi
In this paper, we present a secure distributed estimation strategy in networked systems. In particular, we consider distributed Kalman filtering as the estimation method and Paillier encryption, which is a partially homomorphic encryption scheme. The proposed strategy protects the confidentiality of the transmitted data within a network. Moreover, it also secures the state estimation computation process
-
Distributed coordination on state-dependent fuzzy graphs J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-31 Mojeed O. Oyedeji; Magdi S. Mahmoud; Yuanqing Xia
Multiagent systems are increasingly becoming popular among researchers spanning multiple fields of study. However, existing studies only models communication interaction between agents as either fixed or switching topologies described by crisp graphs supported by algebraic graph theories. In this paper, we propose an alternative approach to describing agent interactions using fuzzy graphs. Our approach
-
Theoretical and numerical local null controllability of a quasi-linear parabolic equation in dimensions 2 and 3 J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-30 E. Fernández-Cara; J. Límaco; I. Marín-Gayte
This paper is devoted to the theoretical and numerical analysis of the null controllability of a quasi-linear parabolic equation. First, we establish a local controllability result. The proof relies on an appropriate inverse function argument. Then, we formulate an iterative algorithm for the computation of the null control and we prove a convergence result. Finally, we illustrate the analysis with
-
Robust particle filtering with enhanced outlier resilience and real-time disturbance compensation J. Franklin Inst. (IF 4.036) Pub Date : 2021-01-22 Wenshuo Li; Bo Tian; Xin Liu; Lei Guo
This paper is concerned with the state estimation problem for nonlinear/non-Gaussian systems suffered from both time-varying disturbances (TVD) and measurement outliers. Conventional particle filtering (PF) approach can be used to track the non-Gaussian probability density functions, but its sampling efficiency is degraded in the presence TVD. To address this problem, we propose a disturbance observer
-
Comparison of Two Polynomial Approaches in Performance Analysis for Periodic Piecewise Polynomial Systems J. Franklin Inst. (IF 4.036) Pub Date : 2021-03-03 Xiaochen Xie; Jason J.R. Liu; Chenchen Fan
In this paper, the theory and effectiveness of two polynomial approaches are compared in the analysis of L2−L∞ and H∞ performance for a type of periodic piecewise polynomial systems, where the time-varying subsystems can be characterized in Bernstein polynomials. Using the Bernstein polynomial-based lemma and the existing lemma concerning the negativity/positivity of matrix polynomial functions, sufficient
-
Permutation Entropy based Detection Scheme of Replay Attacks in Industrial Cyber-Physical Systems J. Franklin Inst. (IF 4.036) Pub Date : 2021-03-03 Mei Zhou; Zhengdao Zhang; Linbo Xie
Although data integrity attack detections are critical to cyber-physical systems (CPSs), replay attack detection in industrial CPSs, especially data-based detection methods against replay attacks, has not been well-studied. Because it’s difficult to distinguish replayed historical measurements and current measurements, replay attacks are hard to detect. In this paper, we propose a permutation entropy
-
Novel delay-partitioning approaches to stability analysis for uncertain Lur’e systems with time-varying delays J. Franklin Inst. (IF 4.036) Pub Date : 2021-03-03 Liang-Dong Guo; Sheng-Juan Huang; Li-Bing Wu
This work deals with the problem of absolute stability analysis for a class of uncertain Lur’e systems with time-varying delays. Novel delay-partitioning approaches are presented, which are dividing the variation interval of the delay into three subintervals. Some new augment Lyapunov-Krasovskii functionals (LKFs) are defined on each of the obtained subintervals which can efficiently make use of the
-
Finite-time consensus control for a class of multi-agent systems with dead-zone input J. Franklin Inst. (IF 4.036) Pub Date : 2021-03-03 Dajie Yao; Chunxia Dou; Nan Zhao; Tingjun Zhang
This paper investigates a finite-time consensus issue for non-affine pure-feedback multi-agent systems with dead-zone input. Compared with the existing results on multi-agent systems, finite-time consensus problem of non-affine multi-agent systems is proposed for the first time. Based on the backsteppting technique, adaptive finite-time consensus control scheme is presented. With the help of this strategy
-
A meliorated Harris Hawks optimizer for combinatorial unit commitment problem with photovoltaic applications J. Electr. Syst. Inf Technol Pub Date : 2021-03-03 Ayani Nandi; Vikram Kumar Kamboj
Conventional unit commitment problem (UCP) consists of thermal generating units and its participation schedule, which is a stimulating and significant responsibility of assigning produced electricity among the committed generating units matter to frequent limitations over a scheduled period view to achieve the least price of power generation. However, modern power system consists of various integrated
-
Stamantic clustering: Combining statistical and semantic features for clustering of large text datasets Expert Syst. Appl. (IF 5.452) Pub Date : 2021-02-18 Vivek Mehta; Seema Bawa; Jasmeet Singh
Document clustering in text mining is a problem that is heavily researched upon. It is observed that individual approaches based on statistical features and semantic features have been extensively used to solve this problem. However, techniques combining the advantages of both types of features have not been frequently researched upon. Specifically, when the growth in the size of textual data is immense
-
MK-Means: Detecting Evolutionary Communities in Dynamic Networks Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Yi-Cheng Chen; Yen-Liang Chen; Jyun-Yun Lu
K-Means algorithm is probably the most famous and popular clustering algorithm in the world. K-Means algorithm has the advantages of simple structure, easy implementation, high efficiency, fast convergence speed, and good results. It has been widely used in many applications, and many extensions of K-Means have been proposed. Basically, most K-Means variants deal with static data. Recently, the dynamic
-
RSigELU: A nonlinear activation function for deep neural networks Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Serhat Kiliçarslan; Mete Celik
In deep learning models, the inputs to the network are processed using activation functions to generate the output corresponding to these inputs. Deep learning models are of particular importance in analyzing big data with numerous parameters and forecasting and are useful for image processing, natural language processing, object recognition, and financial forecasting. Sigmoid and tangent activation
-
Efficient deep feature extraction and classification for identifying Defective Photovoltaic Module Cells in Electroluminescence Images Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Mustafa Yusuf Demirci; Nurettin Beşli; Abdülkadir Gümüşçü
Electroluminescence (EL) imaging has become the standard test procedure for defect detection throughout the production, installation and operation stages of solar modules. Using this test, defects such as micro cracks, broken cells, and finger interruptions on photovoltaic modules could be easily detected and potential power loss issues could be effectively addressed. Although EL test is a very powerful
-
Optimizing electric vehicle routing problems with mixed backhauls and recharging strategies in multi-dimensional representation network Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Senyan Yang; Lianju Ning; Lu Carol Tong; Pan Shang
Electric vehicles are environmental transportation modes that are widely applied in green logistics systems. To guarantee the energy efficiency, the impacts of customer service modes and recharging strategies need to be integrated into the optimization of electric logistics resource. This paper proposes an electric vehicle routing problem with mixed backhauls, time windows, and recharging strategies
-
Dynamic Ticket Pricing of Airlines using Variant Batch Size Interpretable Multi-Variable Long Short-Term Memory Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Ismail Koc; Emel Arslan
Research of airlines shows that seat inventory control and therefore, revenue management is based not on a systematic analysis but more on human judgement. Machine learning models have been developed and applied to support decisions for ticket pricing dynamically. However, conventional models and approaches yield low statistical evaluation scores. In this study, the features used in other studies were
-
Fully Automatic Electrocardiogram Classification System based on Generative Adversarial Network with Auxiliary Classifier Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Zhanhong Zhou; Xiaolong Zhai; Chung Tin
A generative adversarial network (GAN) based fully automatic electrocardiogram (ECG) arrhythmia classification system with high performance is presented in this paper. The generator (G) in our GAN is designed to generate various coupling matrix inputs conditioned on different arrhythmia classes for data augmentation. Our designed discriminator (D) is trained on both real and generated ECG coupling
-
Neural Network Modeling of Consumer Satisfaction in Mobile Commerce: An Empirical Analysis Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Zoran Kalinić; Veljko Marinković; Ljubina Kalinić; Francisco Liébana-Cabanillas
-
An improved bat algorithm hybridized with extremal optimization and Boltzmann selection Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Min-Rong Chen; Yi-Yuan Huang; Guo-Qiang Zeng; Kang-Di Lu; Liu-Qing Yang
As a meta-heuristic algorithm, bat algorithm (BA) is based on the characteristics of bat-based echolocation and has been widely used in various aspects of optimization problems since it appeared. However, the original BA still has many shortcomings, such as insufficient local search ability, lack of diversity and poor performance on high-dimensional optimization problems. To overcome these weaknesses
-
Detecting Abusive Instagram Comments in Turkish Using Convolutional Neural Network and Machine Learning Methods Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Habibe Karayiğit; Çiğdem İnan Aci; Ali Akdağli
Instagram is a free photo-sharing platform where each user has a profile and can upload photos for followers to view, like, and comment. Abusive comments on images can be humiliating and harmful to those who share photos. Developing a comment filter in languages other than English is difficult and time-consuming. This paper proposes a dataset called Abusive Turkish Comments (ATC) to detect abusive
-
Detection of Counterfeit Coins based on 3D Height-Map Image Analysis Expert Syst. Appl. (IF 5.452) Pub Date : 2021-03-03 Saeed Khazaee; Maryam Sharifi Rad; Ching Y. Suen
Detecting a counterfeit coin using 2D image processing is nearly impossible in some cases, especially when the coin is damaged, corroded or worn out. Edge detection is one of the most widely used techniques to extract features from 2D images. However, in 2D images, the height information is missing, losing the hidden characteristics. In this paper, we propose a 3D approach to detect and analyze the
-
Hybrid observer with finite-memory output error correction for linear systems under intrinsic impulsive feedback Nonlinear Anal. Hybrid Syst. (IF 5.881) Pub Date : 2021-03-02 Diana Yamalova; Alexander Medvedev
A novel hybrid observer that estimates the states of an oscillating system composed of a linear chain structure and an intrinsic pulse-modulated feedback is considered. This particular type of plant model appears in e.g. endocrine systems with pulsatile hormone secretion. The observer reconstructs the continuous states of the model as well as the firing times and weights of the feedback impulses. Since
-
Distributed adaptive output feedback containment control for time-delay nonlinear multiagent systems Automatica (IF 5.541) Pub Date : 2021-03-02 Yafeng Li; Ju H. Park; Changchun Hua; Guopin Liu
This paper addresses the distributed adaptive containment control problem for uncertain nonlinear multiagent systems (MASs) with time delays and unmodeled dynamics under fixed directed graph. With outputs information of neighbors, the local reference generator of each agent is constructed to generate corresponding virtual tracking trajectory belonging to the convex hull spanned by dynamic leaders.
-
Stability and stabilization of linear impulsive systems with large impulse-delays: A stabilizing delay perspective Automatica (IF 5.541) Pub Date : 2021-03-02 Shixian Luo; Feiqi Deng; Wu-Hua Chen
This paper deals with the stability and stabilization of linear impulsive systems with large impulse-delays. To explore the stabilizing effect of the time delay in the discrete-time dynamics, a switched impulsive system approach is developed to establish non-conservative stability criteria for linear impulsive systems with periodic impulses and constant delay. Subsequently, sufficient conditions are
-
The Cubature Kalman Filter revisited Automatica (IF 5.541) Pub Date : 2021-03-02 Juan-Carlos Santos-León; Ramón Orive; Daniel Acosta; Leopoldo Acosta
In this paper, the construction and effectiveness of the so-called Cubature Kalman Filter (CKF) is revisited, as well as its extensions for higher degrees of precision. In this sense, some stable (with respect to the dimension) cubature rules with a quasi-optimal number of nodes are built, and their numerical performance is checked in comparison with other known formulas. All these cubature rules are
-
Improvements for research data repositories: The case of text spam J. Inf. Sci. (IF 2.41) Pub Date : 2021-03-02 Ismael Vázquez; María Novo-Lourés; Reyes Pavón; Rosalía Laza; José Ramón Méndez; David Ruano-Ordás
Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for
-
Lora RTT Ranging Characterization and Indoor Positioning System Wirel. Commun. Mob. Comput. (IF 1.819) Pub Date : 2021-03-03 Qiang Liu; XiuJun Bai; Xingli Gan; Shan Yang
In recent years, indoor positioning systems (IPS) are increasingly very important for a smart factory, and the Lora positioning system based on round-trip time (RTT) has been developed. This paper introduces the ranging characterization, RTT measurement, and position estimation method. In particular, a particle filter localization method-aided Lora pseudorange fitting correction is designed to solve
-
Intelligent Recognition System Based on Contour Accentuation for Navigation Marks Wirel. Commun. Mob. Comput. (IF 1.819) Pub Date : 2021-03-03 Yanke Du; Shuo Sun; Shi Qiu; Shaoxi Li; Mingyang Pan; Chi-Hua Chen
Sensing navigational environment represented by navigation marks is an important task for unmanned ships and intelligent navigation systems, and the sensing can be performed by recognizing the images from a camera. In order to improve the image recognition accuracy, this paper combined a contour accentuation algorithm into a multiple scale attention mechanism-based classification model for navigation
-
A Network Selection Scheme Based on the Analytic Hierarchy Process for Marine Internet Wirel. Commun. Mob. Comput. (IF 1.819) Pub Date : 2021-03-03 Liang Zhou; Sheng-Ming Jiang; Tao Yan
The marine Internet technology has been proposed to exploit abundant communication and network resources available in the ocean in order to provide more cost-effective and handy network services therein. Basically, the marine Internet architecture is based on heterogeneous large-scale dynamic wireless, which consists of different types of networks such as satellite networks, coastline networks, and
-
A Survey of Nearest Neighbor Algorithms for Solving the Class Imbalanced Problem Wirel. Commun. Mob. Comput. (IF 1.819) Pub Date : 2021-03-03 Bo Sun; Haiyan Chen
nearest neighbor (NN) is a simple and widely used classifier; it can achieve comparable performance with more complex classifiers including decision tree and artificial neural network. Therefore, NN has been listed as one of the top 10 algorithms in machine learning and data mining. On the other hand, in many classification problems, such as medical diagnosis and intrusion detection, the collected
-
Mining Network Traffic with the -Means Clustering Algorithm for Stepping-Stone Intrusion Detection Wirel. Commun. Mob. Comput. (IF 1.819) Pub Date : 2021-03-03 Lixin Wang; Jianhua Yang; Xiaohua Xu; Peng-Jun Wan
Intruders on the Internet usually launch network attacks through compromised hosts, called stepping stones, in order to reduce the chance of being detected. With stepping-stone intrusions, an attacker uses tools such as SSH to log in several compromised hosts remotely and create an interactive connection chain and then sends attacking packets to a target system. An effective method to detect such an
-
A Routing Algorithm for the Sparse Opportunistic Networks Based on Node Intimacy Wirel. Commun. Mob. Comput. (IF 1.819) Pub Date : 2021-03-03 Gang Xu; Xinyue Wang; Na Zhang; Zhifei Wang; Lin Yu; Liqiang He
Opportunistic networks are becoming more and more important in the Internet of Things. The opportunistic network routing algorithm is a very important algorithm, especially based on the historical encounters of the nodes. Such an algorithm can improve message delivery quality in scenarios where nodes meet regularly. At present, many kinds of opportunistic network routing algorithms based on historical
-
An Adaptive Visible Watermark Embedding Method based on Region Selection Secur. Commun. Netw. (IF 1.288) Pub Date : 2021-03-03 Wenfa Qi; Yuxin Liu; Sirui Guo; Xiang Wang; Zongming Guo
Aiming at the problem that the robustness, visibility, and transparency of the existing visible watermarking technologies are difficult to achieve a balance, this paper proposes an adaptive embedding method for visible watermarking. Firstly, the salient region of the host image is detected based on superpixel detection. Secondly, the flat region with relatively low complexity is selected as the embedding
-
Nowhere to Hide: A Novel Private Protocol Identification Algorithm Secur. Commun. Netw. (IF 1.288) Pub Date : 2021-03-03 Jiantao Shi; Xiangzhan Yu; Zechao Liu
In recent years, with the rapid development of mobile Internet and 5G technology, great changes have been brought to our lives, and human beings have stepped into the era of big data. These new features and techniques in 5G support many different types of mobile applications for users, which makes network security extremely challenging. Among them, more and more applications involve users’ private
-
Process Variation-Resistant Golden-Free Hardware Trojan Detection through a Power Side Channel Secur. Commun. Netw. (IF 1.288) Pub Date : 2021-03-03 Yidong Yuan; Yao Zhang; Yiqiang Zhao; Xige Zhang; Ming Tang
With the globalization of the manufacturing supply chain, the malicious modification existing in the middle of distrust is becoming an important security issue on the chip. These modifications are called hardware Trojan (HT). HT is difficult to detect due to its high concealment and diversity of implementation. HT detection based on the side channel is a relatively effective detection method because
-
Effects of Information Architecture on the Effectiveness and User Experience of Web-Based Patient Education in Middle-Aged and Older Adults: Online Randomized Experiment J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Tessa Dekkers; Marijke Melles; Stephan B W Vehmeijer; Huib de Ridder
Background: Web-based patient education is increasingly offered to improve patients’ ability to learn, remember, and apply health information. Efficient organization, display, and structural design, that is, information architecture (IA), can support patients’ ability to independently use web-based patient education. However, the role of IA in the context of web-based patient education has not been
-
Compliance With Mobile Ecological Momentary Assessment of Self-Reported Health-Related Behaviors and Psychological Constructs in Adults: Systematic Review and Meta-analysis J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Marie T Williams; Hayley Lewthwaite; François Fraysse; Alexandra Gajewska; Jordan Ignatavicius; Katia Ferrar
Background: Mobile ecological momentary assessment (mEMA) permits real-time capture of self-reported participant behaviors and perceptual experiences. Reporting of mEMA protocols and compliance has been identified as problematic within systematic reviews of children, youth, and specific clinical populations of adults. Objective: This study aimed to describe the use of mEMA for self-reported behaviors
-
Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Owain T Jones; Natalia Calanzani; Smiji Saji; Stephen W Duffy; Jon Emery; Willie Hamilton; Hardeep Singh; Niek J de Wit; Fiona M Walter
Background: More than 17 million people worldwide, including 360,000 people in the United Kingdom, were diagnosed with cancer in 2018. Cancer prognosis and disease burden are highly dependent on the disease stage at diagnosis. Most people diagnosed with cancer first present in primary care settings, where improved assessment of the (often vague) presenting symptoms of cancer could lead to earlier detection
-
A Clinical Communication Tool (Loop) for Team-Based Care in Pediatric and Adult Care Settings: Hybrid Mixed Methods Implementation Study J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Amna Husain; Eyal Cohen; Raluca Dubrowski; Trevor Jamieson; Allison Miyoshi Kurahashi; Bhadra Lokuge; Adam Rapoport; Stephanie Saunders; Elaine Stasiulis; Jennifer Stinson; Saranjah Subramaniam; Pete Wegier; Melanie Barwick
Background: Communication within the circle of care is central to coordinated, safe, and effective care; yet patients, caregivers, and health care providers often experience poor communication and fragmented care. Through a sequential program of research, the Loop Research Collaborative developed a web-based, asynchronous clinical communication system for team-based care. Loop assembles the circle
-
Health Care Students’ Knowledge of and Attitudes, Beliefs, and Practices Toward the French COVID-19 App: Cross-sectional Questionnaire Study J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Ilaria Montagni; Nicolas Roussel; Rodolphe Thiébaut; Christophe Tzourio
Background: Many countries worldwide have developed mobile phone apps capable of supporting instantaneous contact tracing to control the COVID-19 pandemic. In France, a few people have downloaded and are using the StopCovid contact tracing app. Students in the health domain are of particular concern in terms of app uptake. Exploring their use and opinions about the app can inform improvements and diffusion
-
Cost-effectiveness of a Telemonitoring Program for Patients With Heart Failure During the COVID-19 Pandemic in Hong Kong: Model Development and Data Analysis J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Xinchan Jiang; Jiaqi Yao; Joyce Hoi-Sze You
Background: The COVID-19 pandemic has caused patients to avoid seeking medical care. Provision of telemonitoring programs in addition to usual care has demonstrated improved effectiveness in managing patients with heart failure (HF). Objective: We aimed to examine the potential clinical and health economic outcomes of a telemonitoring program for management of patients with HF during the COVID-19 pandemic
-
Correction: Measurement of Digital Literacy Among Older Adults: Systematic Review J. Med. Internet Res. (IF 5.034) Pub Date : 2021-03-03 Sarah Soyeon Oh; Kyoung-A Kim; Minsu Kim; Jaeuk Oh; Sang Hui Chu; JiYeon Choi
-
Adaptive Asymptotic Tracking Fault-tolerant Control of Uncertain Nonlinear Systems with Actuator Failures and Event-triggered Inputs Int. J. Control Autom. Syst. (IF 2.733) Pub Date : 2021-03-03 Yan Yan; Libing Wu; Nannan Zhao; Ruiyan Zhang
This paper is concerned with the problem of adaptive asymptotic tracking fault-tolerant control (FTC) for uncertain nonlinear systems with actuator faults and event-triggered inputs. Firstly, fault-tolerant controller is designed to effectively compensate the unknown actuator failures by constructing the proper parameter updated laws. Then, the event-triggered strategy based on the relative threshold
-
Sleep Pattern Study with Respect to Binaural Beats Using Sensors and Mobile Application Wireless Pers. Commun. (IF 1.061) Pub Date : 2021-03-03 R. Rishika; Aditya Gupta; Sakshi Sinha; S. Sofana Reka
Sleep disorders are common among people in the present lifestyle and this may occur due to irregular sleep patterns. The disordered sleep pattens arise due to various reasons and can be prevented by ensuring a relaxed and deep sleep for everyone. Binaural beats are the stimuli that are set to a particular rhythm and generated to get the required audio frequency to synchronize with the brainwaves. This
-
Folded Substrate Integrated Waveguide Based Multiband Filter for Wi-Fi6E Application Wireless Pers. Commun. (IF 1.061) Pub Date : 2021-03-03 Sheelu Kumari; Vibha Rani Gupta; Shweta Srivastava
This paper presents the design and development of a multiband filter using folded substrate integrated waveguide (FSIW) for the Wi-Fi 6E application. The emerging network standard IEEE802.11ax also known as Wi-Fi 6E is the next generation of Wi-Fi, which includes an additional frequency band at 6 GHz and provides improvements over 802.11ac (Wi-Fi 5). The designed filter is based on modification of
-
An Introduction to Neural Networks in SCMA Wireless Pers. Commun. (IF 1.061) Pub Date : 2021-03-03 Madhura Kanzarkar; M. S. S. Rukmini; Rajeshree Raut
Sparse Code Multiple Access (SCMA) has proved to be a fascinating research in order to curtail the complications faced by the wireless communication networks. SCMA being a Non-Orthogonal Multiple Access technique evinces to be an outstanding candidate, to cater the complications faced by 5G communication networks to improve the bit error rate and reduce the complexity of decoding the transmitted signal
-
SBT (Sense Before Transmit) Based LTE Licenced Assisted Access for 5 GHz Unlicensed Spectrum Wireless Pers. Commun. (IF 1.061) Pub Date : 2021-03-03 S. Reddy Vamshidhar Reddy; Sanjay Dhar Roy
Utilization of unlicensed spectrum under licensed assisted access ensuring fair co-existence with Wi-Fi networks is a good solution to address immense usage of mobile data. Radio communication operation of LTE in unlicensed frequency band is referred as LTE-unlicensed (LTE-U) or LTE-licensed assisted access. In this paper, we consider a HGNW in which coverage area of Wireless-Fidelity (Wi-Fi)’s Access
-
Robust Web Data Extraction Based on Weighted Path-layer Similarity J. Comput. Inform. Syst. (IF 1.582) Pub Date : 2021-03-02 Peng Gao; Hao Han
ABSTRACT Web data extraction techniques often focus on accurate and efficient information acquisition from webpages. However, webpage variants cause frequent extraction to fail and result in high maintenance costs. Significant effort is attracted to robust extraction, but most either require complex pre-processing or supplementary files. In this paper, a novel method is proposed to enhance extraction
-
Tapping the Next Purchase: Embracing the Wave of Mobile Payment J. Comput. Inform. Syst. (IF 1.582) Pub Date : 2021-03-02 Hui-Ting Tew; Garry Wei-Han Tan; Xiu-Ming Loh; Voon-Hsien Lee; Wei-Lee Lim; Keng-Boon Ooi
ABSTRACT This paper looks to determine the antecedents of Near Field Communication (NFC) mobile payment from a developing country’s perspective. This was done with the use of a conceptual framework based on the Mobile Technology Acceptance Model (MTAM) that consists of mobile usefulness (MU), mobile ease of use (MEU) while integrating mobile self-efficacy (MSE), and system and service quality (SSQ)
-
Phish Me, Phish Me Not J. Comput. Inform. Syst. (IF 1.582) Pub Date : 2021-03-02 Bartlomiej Hanus; Yu Andy Wu; James Parrish
ABSTRACT While phishing has evolved over the years, it still exploits one of the weakest links in any information system — humans. The present study aims at describing who the potential phishing victims are. We constructed two types of phishing messages that represented two basic categories of phishing e-mails: regular and spear-phishing. In cooperation with the IT management of a municipality in the
-
Big Data in Healthcare Research: A survey study J. Comput. Inform. Syst. (IF 1.582) Pub Date : 2021-03-02 Shah J Miah; Edwin Camilleri; H. Quan Vu
ABSTRACT The purpose of this study is to present a literature review that provides in-depth analytical insight into big data in health care. This was addressed by achieving three things: (a) identifying the key topics addressed in existing big data research in health care, (b) measuring associations between topics in existing studies, and (c) constructing time series profiles for the various topics
Contents have been reproduced by permission of the publishers.