Generating Semantic Adversarial Examples via Feature Manipulation in Latent Space.

The susceptibility of deep neural networks (DNNs) to adversarial intrusions, exemplified by adversarial examples, is well-documented. Conventional attacks implement unstructured, pixel-wise perturbations to mislead classifiers, which often results in a noticeable departure from natural samples and lacks human-perceptible interpretability. In this work, we present an adversarial attack strategy that implements fine-granularity, semantic-meaning-oriented structural perturbations.

Evaluation of Federated Learning in Phishing Email Detection.

The use of artificial intelligence (AI) to detect phishing emails is primarily dependent on large-scale centralized datasets, which has opened it up to a myriad of privacy, trust, and legal issues. Moreover, organizations have been loath to share emails, given the risk of leaking commercially sensitive information. Consequently, it has been difficult to obtain sufficient emails to train a global AI model efficiently.

Can the Policy of Increasing Retirement Age Raise Pension Revenue in China-A Case Study of Anhui Province.

With gradual progress in the medical field and the rising living standard of people, the life expectancy of people is gradually increasing. Unfortunately, this positive development contributes significantly to the aging of societies and creates huge challenges for pension systems. In order to mitigate the pressure on its pension system in the coming years, China is considering increasing the retirement age, just like many other countries.

Cyber Code Intelligence for Android Malware Detection.

Evolving Android malware poses a severe security threat to mobile users, and machine-learning (ML)-based defense techniques attract active research. Due to the lack of knowledge, many zero-day families' malware may remain undetected until the classifier gains specialized knowledge. The most existing ML-based methods will take a long time to learn new malware families in the latest malware family landscape.

A Comprehensive Survey on Community Detection With Deep Learning.

Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis. However, beyond the classic spectral clustering and statistical inference methods, there have been significant developments with deep learning techniques for community detection in recent years-particularly when it comes to handling high-dimensional network data.

User, Usage and Usability: Redefining Human Centric Cyber Security.

The effectiveness of cyber security measures are often questioned in the wake of hard hitting security events. Despite much work being done in the field of cyber security, most of the focus seems to be concentrated on system usage. In this paper, we survey advancements made in the development and design of the human centric cyber security domain.

Dual-Mediation Paths Linking Corporate Social Responsibility to Employee's Job Performance: A Multilevel Approach.

This study attempts to examine the direct impact of corporate social responsibility (CSR) initiatives on employees' job performance and the indirect relationships between CSR initiatives on employees' job performance industrial relations climate and psychological contract fulfillment. Data were collected from 764 supervisor-subordinate dyads and 271 middle managers from 85 companies. Using a multilevel approach, the results showed that organizational-level CSR was positively related to employees' job performance.

Daedalus: Breaking Nonmaximum Suppression in Object Detection via Adversarial Examples.

This article demonstrates that nonmaximum suppression (NMS), which is commonly used in object detection (OD) tasks to filter redundant detection results, is no longer secure. Considering that NMS has been an integral part of OD systems, thwarting the functionality of NMS can result in unexpected or even lethal consequences for such systems. In this article, an adversarial example attack that triggers malfunctioning of NMS in OD models is proposed.

Can Cultural Intelligence Affect Employee's Innovative Behavior? Evidence From Chinese Migrant Workers in South Korea.

This empirical study explores the effect of cultural intelligence (CQ) on migrant workers' innovative behavior, as well as the mediating role of knowledge sharing on the CQ-innovative behavior relationship. Besides, it also examines the extent to which the mediating process is moderated by climate for inclusion. Using survey data collected from Chinese migrant workers and their supervisors working in South Korea ( = 386), migrant workers' CQ is found to positively impact their innovative behavior through enhanced knowledge sharing.

Impact of At-Home Telemonitoring on Health Services Expenditure and Hospital Admissions in Patients With Chronic Conditions: Before and After Control Intervention Analysis.

Background: Telemonitoring is becoming increasingly important for the management of patients with chronic conditions, especially in countries with large distances such as Australia. However, despite large national investments in health information technology, little policy work has been undertaken in Australia in deploying telehealth in the home as a solution to the increasing demands and costs of managing chronic disease.

Objective: The objective of this trial was to evaluate the impact of introducing at-home telemonitoring to patients living with chronic conditions on health care expenditure, number of admissions to hospital, and length of stay (LOS).

Facilitating Secure Sharing of Personal Health Data in the Cloud.

Background: Internet-based applications are providing new ways of promoting health and reducing the cost of care. Although data can be kept encrypted in servers, the user does not have the ability to decide whom the data are shared with. Technically this is linked to the problem of who owns the data encryption keys required to decrypt the data.

Design of a multi-site multi-state clinical trial of home monitoring of chronic disease in the community in Australia.

Background: Telehealth services based on at-home monitoring of vital signs and the administration of clinical questionnaires are being increasingly used to manage chronic disease in the community, but few statistically robust studies are available in Australia to evaluate a wide range of health and socio-economic outcomes. The objectives of this study are to use robust statistical methods to research the impact of at home telemonitoring on health care outcomes, acceptability of telemonitoring to patients, carers and clinicians and to identify workplace cultural factors and capacity for organisational change management that will impact on large scale national deployment of telehealth services. Additionally, to develop advanced modelling and data analytics tools to risk stratify patients on a daily basis to automatically identify exacerbations of their chronic conditions.

Barriers for delivering telehealth in rural australia: a review based on Australian trials and studies.

Background: Australians in rural and remote areas live with far poorer health outcomes than those in urban areas. Telehealth services have emerged as a promising solution to narrow this health gap, as they improve the level and diversity of health services delivery to rural and remote Australian communities. Although the benefits of telehealth services are well studied and understood, the uptake has been very slow.

A framework for telehealth program evaluation.

Evaluating telehealth programs is a challenging task, yet it is the most sensible first step when embarking on a telehealth study. How can we frame and report on telehealth studies? What are the health services elements to select based on the application needs? What are the appropriate terms to use to refer to such elements? Various frameworks have been proposed in the literature to answer these questions, and each framework is defined by a set of properties covering different aspects of telehealth systems. The most common properties include application, technology, and functionality.