Search results

This paper aimed to explain why individuals still tend to disclose their privacy information even when privacy risks are high and whether individuals disclose or withhold information following the same logic.

This study develops a configurational decision tree model (CDTM) for precisely understanding individuals' decision-making process of privacy disclosure. A survey of location-based social network service (LBSNS) users was conducted to collect data, and fuzzy-set qualitative comparative analysis (fsQCA) was adopted to validate the hypotheses.

This paper identified two configurations for high and low disclosure, respectively, and found that the benefits and the risks did not function independently but interdependently, and the justice would play a crucial role when both the benefits and the risks were high. Furthermore, the authors found that there were asymmetric mechanisms for high disclosure and low disclosure, and males focused more on perceived usefulness, while females concerned more about perceived enjoyment, privacy risks and perceived justice.

This paper further extends privacy calculus model (PCM) and deepens the understanding of the privacy calculus process from a configurational perspective. In addition, this study also provides guidance for future research on how to adopt the configurational approach with qualitative comparative analysis (QCA) to revise and improve relevant theories for information systems (IS) behavioral research.

A ‘flipped’ or ‘inverted’ teaching approach (Lage et al., 2000) reverses the traditional use of in- and out-ofclass time, delivering instructional input to students before class and devoting classroom time to applying this input in small group tasks. This study investigates the use of videoed lectures and attitudes to in-class activities among undergraduate students in first year Calculus classes using either a lecture-based or a ‘flipped classroom’ approach. Survey results indicate that while the majority of the students embrace the flipped experience and more specifically the in-class group work activities, they lacked the confidence in their self-learning abilities to completely part with an instructor-led class. This finding and its impact on implementing a flipped classroom supports concerns found in the literature that first- and second-year students may need more guidance from their professors before they can truly benefit from the flipped learning model of instruction.

بلقي جهنم سيردتلا " بولقملا " وأ " سوكعملا ) " جيل ،هئﻼمزو 2000 ( فيظوتلا يديلقتلا تقولل لخاد فصلا هجراخو ذإ دوزي بلاطلا داوملاب ةيميلعتلا لبق ءدب فصلا صصخيو تقو ءاقللا يفصلا قيبطتل ام هملعت بلاطلا كلذو نمض تاعومجم مّ ل عت ةريغص ةفداه . لوانتت هذه ةساردلا فيظوت تارضاحم ويديفلا فقاومو ةبلطلا نم ةطشنﻷا ةيفصلا نيب بﻼط ةنسلا ةيعماجلا ىلوﻷا نيقحتلملا تاقاسمب باسح لضافتلا لماكتلاو ) سلوكلاك ( ، كلذو اقﻼطنا نم جهنم دمتعي امإ تارضاحملا وأ فوفصلا ةبولقملا . ريشتو جئاتن حسملا ىلإ هنأ يف نيح لبقي بلغأ بﻼطلا ىلع ةبرجت فصلا ،بولقملا ىلعو هجو ديدحتلا ةطشنأ لمعلا يعامجلا لخاد ،فصلا ريغ مهنأ نورقتفي ىلإ ةقثلا يف مهتاردق ىلع ملعتلا يتاذلا ىلإ دح مهلعجي ريغ نيرداق ىلع يلختلا امامت نع فص هروحم ذاتسﻷا . دناستو هذه ةجيتنلا اهريثأتو ىلع ذيفنت فوفص ةيسارد ةبولقم فواخملا ةدوجوملا يف تايبدﻷا اهدافمو نأ بﻼط ةنسلا ىلوﻷا ةيناثلاو دق نوجاتحي ىلإ ديزم نم هيجوتلا نم مهتذتاسأ لبق نأ اونكمتي نم ةدافتسﻻا اقح نم جذومن ملعتلا بولقملا يف سيردتلا .

Understanding the privacy concerns of individuals in the adoption of contact tracing apps is critical for the successful control of pandemics like COVID-19. This paper explores the privacy paradox in the adoption of contact tracing apps in Australia.

A comprehensive review of the related literature has been conducted, leading to the development of a conceptual model based on the privacy calculus theory and the antecedent-privacy concern-outcome framework. Such a model is then tested and validated using structural equation modelling on the survey data collected in Australia.

The study shows that perceived benefit, perceived privacy risk and trust have significant influences on the adoption of contact tracing apps. It reveals that personal innovativeness and trust have significant and negative influences on perceived privacy risk. The study further finds out that personal innovativeness is insignificant to perceived benefit. It states that perceived ease of use has an insignificant influence on perceived privacy risk in the adoption of contact tracing apps.

This study is the first attempt to use the privacy calculus theory and the antecedent–privacy concern–outcome framework for exploring the privacy paradox in adopting contact tracing apps. This leads to a better understanding of the privacy concerns of individuals in the adoption of contact tracing apps. Such an understanding can help formulate targeted strategies and policies for promoting the adoption of contact tracing apps and inform future epidemic control through effective contact tracing for better emergency management.

The main aim of this paper is to design a technique for improving the quality of EEG signal by removing artefacts which is obtained during acquisition. Initially, pre-processing is done on EEG signal for quality improvement. Then, by using wavelet transform (WT) feature extraction is done. The artefacts present in the EEG are removed using deep convLSTM. This deep convLSTM is trained by proposed fractional calculus based flower pollination optimisation algorithm.

Nowadays' EEG signals play vital role in the field of neurophysiologic research. Brain activities of human can be analysed by using EEG signals. These signals are frequently affected by noise during acquisition and other external disturbances, which lead to degrade the signal quality. Denoising of EEG signals is necessary for the effective usage of signals in any application. This paper proposes a new technique named as flower pollination fractional calculus optimisation (FPFCO) algorithm for the removal of artefacts from EEG signal through deep learning scheme. FPFCO algorithm is the integration of flower pollination optimisation and fractional calculus which takes the advantages of both the flower pollination optimisation and fractional calculus which is used to train the deep convLSTM. The existed FPO algorithm is used for solution update through global and local pollinations. In this case, the fractional calculus (FC) method attempts to include the past solution by including the second order derivative. As a result, the suggested FPFCO algorithm approaches the best solution faster than the existing flower pollination optimization (FPO) method. Initially, 5 EEG signals are contaminated by artefacts such as EMG, EOG, EEG and random noise. These contaminated EEG signals are pre-processed to remove baseline and power line noises. Further, feature extraction is done by using WT and extracted features are applied to deep convLSTM, which is trained by proposed fractional calculus based flower pollination optimisation algorithm. FPFCO is used for the effective removal of artefacts from EEG signal. The proposed technique is compared with existing techniques in terms of SNR and MSE.

The proposed technique is compared with existing techniques in terms of SNR, RMSE and MSE.

100%.

The purpose of this article is to give a non‐technical overview of some of the technical progress made recently on tackling three fundamental problems in the area of formal knowledge representation/artificial intelligence. These are the Frame Problem, the Ramification Problem, and the Qualification Problem. The article aims to describe the development of two logic‐based languages, the Event Calculus and Modular‐E, to address various aspects of these issues. The article also aims to set this work in the wider context of contemporary developments in applied logic, non‐monotonic reasoning and formal theories of common sense.

The study applies symbolic logic to model aspects of human knowledge and reasoning.

The article finds that there are fundamental interdependencies between the three problems mentioned above. The conceptual framework shared by the Event Calculus and Modular‐E is appropriate for providing principled solutions to them.

This article provides an overview of an important approach to dealing with three fundamental issues in artificial intelligence.

The purpose of this paper is to discuss the asymptotic models of different parts with a pitting fault in rolling bearings.

For rolling bearings with a pitting fault, the displacement deviation between raceways and rolling elements is usually considered to vary instantaneously. However, the deviation should change gradually. Based on this shortcoming, the variation rule and calculation method of the displacement deviation are explored. Asymptotic models of different parts with a pitting fault are discussed, respectively. Besides, rolling bearing systems have prominent fractional characteristics unconsidered in the traditional models. Therefore, fractional calculus is introduced into the modeling of rolling bearings. New dynamic asymptotic models of different parts with a pitting fault are proposed based on fractional damping. The numerical simulation is performed based on the proposed model, and the dynamic characteristics are analyzed through the bifurcation diagrams, trajectory diagrams and frequency spectrograms.

Compared with the model based on integral calculus, the proposed model can better reflect the periodic characteristics and fault characteristics of rolling bearings. Finally, the proposed model is verified by the experiment. The dynamic characteristics of rolling bearings at different rotating speeds are analyzed. The experimental results are consistent with the simulation results. Therefore, the proposed model is effective.

(1) The above models are idealized, i.e. the local pitting fault is treated as a rectangle. When a component comes into contact with the fault, the displacement deviation between the component and the fault component immediately releases if the component enters the fault area and restores if the component leaves. However, the displacement deviation should change gradually. Only when the component touches the fault bottom, the displacement deviation reaches the maximum. (2) Due to the material's memory and fluid viscoelasticity, rolling bearing systems exhibit significant fractional characteristics. However, the above models are all proposed based on integral calculus. Integral calculus has some local characteristics and is not suitable for describing historical dependent processes. Fractional calculus can better describe the essential characteristics of the system.

The purpose of this paper is to test the capability to properly analyze the electrical circuits of a novel constitutive relation of capacitor.

For ceteris paribus, the constitutive relations of the resistor and inductor have been reformulated by following the novel constitutive relation of capacitor. The responses of RL, RC, LC and RLC circuits defined on the fractal set described by these definitions have been derived by means of the fractal calculus and fractal Laplace transformation. A comparative Hamiltonian formalism-based analysis has been performed where the circuits described by the conventional and the formerly proposed revisited constitutive relations have also been considered.

This study has found that the novel constitutive relations give unreasonable results unlike the conventional ones. Like such previous revisited constitutive relations, an odd Hamiltonian has been obtained. On the other hand, the conventional constitutive relations give a reasonable Hamiltonian.

To the best of the author’s knowledge, for the first time, the analysis of fractal set defined electrical circuits by means of unconventional constitutive relations has been performed where the deficiency of the tested capacitive constitutive relation has been pointed out.

With the increasing demands of industrial applications, it is imperative for robots to accomplish good contact-interaction with dynamic environments. Hence, the purpose of this research is to propose an adaptive fractional-order admittance control scheme to realize a robot–environment contact with high accuracy, small overshoot and fast response.

Fractional calculus is introduced to reconstruct the classical admittance model in this control scheme, which can more accurately describe the complex physical relationship between position and force in the interaction process of the robot–environment. In this control scheme, the pre-PID controller and fuzzy controller are adopted to improve the system force tracking performance in highly dynamic unknown environments, and the fuzzy controller is used to improve the trajectory, transient and steady-state response by adjusting the pre-PID integration gain online. Furthermore, the stability and robustness of this control algorithm are theoretically and experimentally demonstrated.

The excellent force tracking performance of the proposed control algorithm is verified by constructing highly dynamic unstructured environments through simulations and experiments. In simulations and experiments, the proposed control algorithm shows satisfactory force tracking performance with the advantages of fast response speed, little overshoot and strong robustness.

The control scheme is practical and simple in the actual industrial and medical scenarios, which requires accurate force control by the robot.

A new fractional-order admittance controller is proposed and verified by experiments in this research, which achieves excellent force tracking performance in dynamic unknown environments.

The purpose of this study is to explore the negative consequences of human resource analytics applications using the privacy calculus approach.

By using the existing literature and privacy calculus theory, a theoretical model has been developed. This model helps to examine the benefits and risks associated with HR analytics applications. The theoretical model was validated using the partial least square structural equation modeling (PLS-SEM) technique with 315 respondents from different organizations.

HR analytics provides multiple benefits to employees and organizations. But employee privacy may be compromised due to unauthorized access to employee data. There are also security concerns about the uncontrolled use of these applications. Tracking employees without their consent increases the risk. The study suggests that appropriate regulation is necessary for using HR analytics.

This study is based on cross-sectional data from a specific region. A longitudinal study would have provided more comprehensive results. This study considers five predictors, including other boundary conditions that could enhance the model’s explanative power. Also, data from other countries could improve the proposed model.

The proposed model is useful for HR practitioners and other policymakers in organizations. Appropriate regulations are important for HR analytics applications. The study also highlights various employee privacy and security-related issues emerging from HR analytics applications. The study also discusses the role of leadership support for the appropriate usage of HR analytics.

Only a few research studies have explored the issues of HR analytics and its consequences. The proposed theoretical model is the first to consider the negative consequence of HR analytics through privacy calculus theory. In this perspective, the research is considered to be novel.

In this article, the historical victories and shortfalls of calculus and calculus‐based methods are briefly described so that a need of developing the theory of blown‐ups is given. Listed are several challenges of the theory of blown‐ups to the traditional thinking logic of continuity and characteristics of the theory of blown‐ups.