Journal articles on the topic 'Computer security Taiwan'

Purpose In recent years, the ongoing development and rapid popularization of mobile devices, not only has brought new forms of lifestyle but also has boomed a wide array of service contents, allowing users to engage in entertainment, study and other daily activities, in addition to business transactions. To explore the factors that affect users' continued use of mobile app software, this paper aims to take into account the utilitarian value and privacy, as well as security factors and intends to propose an integrated research model based on the information systems success (ISS) model. Design/methodology/approach The data for this study were collected via an online survey questionnaire. A total of 190 valid responses were used to examine the hypotheses in the research model. The casual model was assessed using partial least squares techniques. Findings The results indicated that the three quality factors (information quality, system quality and service quality) in the ISS model significantly affected satisfaction and utilitarian value. Private and security have significant negative association with utilitarian value. The results also showed that private and security did not significantly affect satisfaction. The findings also provide some directions for further research. Practical implications The results show that user's continued use of mobile app software depends upon the perceived utilitarian value and satisfaction. The quality characteristics are the three critical factors that would affect the perceived utilitarian value and satisfaction. Compared to information quality and service quality, system quality has a higher degree of positive impact, which indicates that users are more concerned about the immediate download ability and ease-of-use provided by the system. Furthermore, the research also finds that privacy and security concerns have a negative influence on the utilitarian value, showing that in the context of task-oriented IS, the perceived risk of privacy and security during the process of using mobile app software services, will negatively affect users’ perception of utilitarian value. The insights provided by this study can help mobile app developers optimize design and marketing strategies. Originality/value This study provides a better understanding of how the factors in the theories influence the continuance usage intention of life style mobile applications.

This study empirically investigates the influence of information security marketing and response cost on employees’ information security intention in the container shipping industry. Survey data were collected from 285 respondents in Taiwan. Exploratory factor analysis was employed to identify all the measures to be summarized in a relative set. Confirmatory factor analysis was utilized to ensure every measure’s construct’s convergent and discriminant validity. Structural equation modeling was carried out to the proposed model in this article. The results indicate that organizational information security marketing has a positive impact on information security intention. Furthermore, this study conducted hierarchical regression to examine the moderating effects of information security awareness and information security climate. In particular, information security awareness significantly influenced the relationships between organizational information security marketing, response cost, and information security intention. Moreover, information security climate moderated the relationship between response cost and information security intention. This article concludes by discussing these theoretical and practical findings and implications.

<p>Residential security is important in today&rsquo;s society. As Taiwan will soon enter a super-aged society, there will be manpower shortages and scheduling problems in the dispatched resident guard service. Hence, how to develop a new security method and business model that uses the techniques of the Internet of Things to improve resident security is a top priority. In addition, in response to the severe global COVID-19 epidemic, residents&rsquo; access to and from residential areas shall be strictly controlled, such as body temperature records and access records, in order to enhance epidemic prevention within communities. Therefore, this paper proposes an improved gated system that combines the techniques of the Internet of Things (IoT) to ensure community security. In terms of access control, a facial recognition system is designed, which integrates with the functions of body temperature measurement, RFID, and QR codes. The QR code function is mainly used to allow guests to enter residential areas. Regarding the COVID-19 epidemic, the information recorded by the system can help to effectively control the contact history and body temperature of community residents. The advantages of this paper, including practicality, residential security, and integration, are explained in the experimental section.</p> <p>&nbsp;</p>

Purpose – The purpose of this paper is to analyze the cause-and-effect relationship and the mutually influential level among information security control items, as well as to provide organizations with a method for analyzing and making systematic decisions for improvement. Design/methodology/approach – This study utilized the Fuzzy DEMATEL to analyze cause-and-effect relationships and mutual influence of the 11 control items of the International Organization for Standardization (ISO) 27001 Information Security Management System (ISMS), which are discussed by seven experts in Taiwan to identify the core control items for developing the improvement strategies. Findings – The study has found that the three core control items of the ISMS are security policy (SC1), access control (SC7) and human resource security (SC4). This study provides organizations with a direction to develop improvement strategies and effectively manage the ISMS of the organization. Originality/value – The value of this study is for an organization to effectively dedicate resources to core control items, such that other control items are driven toward positive change by analyzing the cause-and-effect relation and the mutual influential level among information security control items, through a cause-and-effect matrix and a systematic diagram.

Much energy-related construction causes environmental concern. Sometimes the environmental issue is so huge that it is difficult to make a policy decision even with the assistance of traditional valuation techniques. The third natural gas receiving station at Datan, Taiwan, is one example of this. The construction would be beneficial to energy security, economic development, and particulate matter (PM) 2.5 reduction. However, it would destroy a precious algal reef, which is a habitat for endangered species, biodiversity, and a unique ecological system. Thus, we used willingness-to-pay to show the strength of both pro-energy and pro-ecology opinions specifically to help with decision-making. First, respondents were asked to choose between the gas station and the reef. Then they were asked about their willingness to pay for that choice. We then estimated parametric/nonparametric models—traditional probit, structured probit, and Turnbull—to obtain reliable estimates. We found that the per-person value for pro-gas-station respondents was higher than that for pro-reef respondents, while the percentage of pro-reef respondents was higher than the percentage of pro-gas-station respondents. These results together form a clear policy implication for this case.

Recent events concerning the Kaspersky anti-virus software in the UK and the Android operating system in the US have highlighted the significance of the domesticity of digital products for national cybersecurity, and the importance of establishing the origin of digital products has been further brought into focus by the war in Ukraine and China’s military activities around Taiwan. Digital products can contain hardware components, software elements, embedded systems, and data, and determining the country of origin (COO) in these circumstances is problematic. The aim of this research, and its main contribution, is to provide an operational framework for the application of the COO concept to address this problem. Using an inductive research methodology based on semi-structured interviews and an online survey, a 19-parameter framework for assessing the COO of digital products is developed and then applied to the case example of a mobile phone import in Turkey. This article concludes that new processes and policies are urgently required to enhance the cyber and information security for digital products, aid domestic digital technology production, and support the transition to recyclable technologies. Such developments are of significance not only for western nations concerned with data and security issues, but also for developing world countries trying to develop their own domestic digital product manufacturing capabilities. This is also of relevance to the computer end-user, who would benefit from greater clarity on the origin of digital products ahead of a purchase decision.

<p>In this paper, the characteristics of the potential behavior of ships contained in AIS information are con-sidered, in order to ensure the safety of navigation in merchant ships’ fishing areas and reduce the occur-rence of collisions between commercial fishing boats. Based on the DBSCAN density clustering algorithm, the identification model of busy water in fishing areas is developed and applied to Minnan fishery in the Taiwan Strait. In addition, a real ship simulation is performed based on real traffic flow data. The results demonstrate that the proposed model can accurately identify the spatial distribution and scale of busy fishing area, adjust the algorithm parameters according to the merchant ship scale, and generate the target-ed recommended route decision for the fishing area. Finally, the STELLAR EXPRESS is compared with the original route. The obtained results show that the recommended route provides a high safety in the fishing area, while retaining the ship operating costs. The model results can be used as a reference for maritime security departments in order to divide the fishing area warning water, and the identification method provides a novel approach for the safety supervision of maritime department. </p> <p>&nbsp;</p>

Background The successful completion of medical practices often relies on information collection and analysis. Government agencies and medical institutions have encouraged people to use medical information technology (MIT) to manage their conditions and promote personal health. In 2014, Taiwan established the first electronic personal health record (PHR) platform, My Health Bank (MHB), which allows people to access and manage their PHRs at any time. In the face of the COVID-19 pandemic in 2020, Taiwan has used MIT to effectively prevent the spread of COVID-19 and undertaken various prevention measures before the onset of the outbreak. Using MHB to purchase masks in an efficient and orderly way and thoroughly implementing personal protection efforts is highly important to contain disease spread. Objective This study aims to understand people’s intention to use the electronic PHR platform MHB and to investigate the factors affecting their intention to use this platform. Methods From March 31 to April 9, 2014, in a promotion via email and Facebook, participants were asked to fill out a structured questionnaire after watching an introductory video about MHB on YouTube. The questionnaire included seven dimensions: perceived usefulness, perceived ease of use, health literacy, privacy and security, computer self-efficacy, attitude toward use, and behavioral intention to use. Each question was measured on a 5-point Likert scale ranging from “strongly disagree” (1 point) to “strongly agree” (5 points). Descriptive statistics and structural equation analysis were performed using SPSS 21 and AMOS 21 software. Results A total of 350 valid questionnaire responses were collected (female: 219/350, 62.6%; age: 21-30 years: 238/350, 68.0%; university-level education: 228/350, 65.1%; occupation as student: 195/350, 56.6%; average monthly income <NT $30,000 [<US $1054.89]: 230/350, 65.7%; residence in northern Taiwan: 236/350, 67.4%; and health status perceived as “good”: 171/350, 48.9%). Five indicators, including chi-square test (X2310=2.63), goodness-of-fit index (0.85), adjusted goodness-of-fit index (0.81), comparative fit index (0.91), and root mean square error of approximation (0.07), were calculated. The results indicated a good fit. Further analysis indicated that the most important factor affecting respondents’ behavioral intention to use MHB was their attitude toward use (0.78), followed by perceived ease of use (0.65), perceived usefulness (0.41), health literacy (0.10), and privacy and security (0.07). Conclusions From the perspective of the populace, this study explored the factors affecting the use of MHB and constructed an interpretation model with a strong goodness of fit. The results of our analysis are consistent with the technology acceptance model. Through the diverse value-added services of MHB, Taiwan's experience in pandemic prevention with smart technology can facilitate future responses to unknown, emerging infectious diseases.

Both at the level of political ideology and in the practical sphere, the American strategy of China’s engagement was a part of a global construction of a new architecture of the world order, based on the liberal-democratic political values but at the same time in line with American leadership. The engagement was in many ways reminiscent of Obama’s strategy of «reset» in relations with Russia, especially in terms of achieving qualitative domestic political changes through dialogue and cooperation. However, the conceptualization of the Trump’s administration China’ policy approaches led to some radical revisions of the American philosophy of international cooperation were made. The objectives of the proposed paper aligned with answering the following research questions: What was wrong with the U.S. engagement strategy toward China evolved over the past decades? What are the implications of the U.S. China policy for Taiwan as well as the world at large (comparing with impact on U.S. policy towards Russia and its regional behavior regarding to Ukraine)? Will engagement be restarted or drastically reevaluated? The methods we employed to do the research: comparative case study that is widely using in International Security studies analyzing issue within a situation or framework. Another method of qualitative methodology approach is a thematic analysis method. The scientific novelty. Assuming that the model of cooperative engagement has largely exhausted itself in terms of the strategic objectives of each party we also emphasize that the model has led to the erosion of the possibility of critical US influence on key regions of the world. Conclusions. It is somewhat paradoxical that a result of US cooperative approaches has brought about greater vulnerability of US formal and informal allies. Chinese and Russian foreign policy strategies have not changed significantly, and have attached even more on the main objects of a kind of historical revenge – Taiwan and Ukraine. Chinese and Russian foreign policy values in terms of waning «Western influences» have grown into offensive political realism. Which, in particular, was generated of sensitivity to the growing US influence in the post-bipolar world.

The objective of this editorial is to overview the content of the special issue “Machine Learning for Energy Systems”. This special issue collects innovative contributions addressing the top challenges in energy systems development, including electric power systems, heating and cooling systems, and gas transportation systems. The special attention is paid to the non-standard mathematical methods integrating data-driven black box dynamical models with classic mathematical and mechanical models. The general motivation of this special issue is driven by the considerable interest in the rethinking and improvement of energy systems due to the progress in heterogeneous data acquisition, data fusion, numerical methods, machine learning, and high-performance computing. The editor of this special issue has made an attempt to publish a book containing original contributions addressing theory and various applications of machine learning in energy systems’ operation, monitoring, and design. The response to our call had 27 submissions from 11 countries (Brazil, Canada, China, Denmark, Germany, Russia, Saudi Arabia, South Korea, Taiwan, UK, and USA), of which 12 were accepted and 15 were rejected. This issue contains 11 technical articles, one review, and one editorial. It covers a broad range of topics including reliability of power systems analysis, power quality issues in railway electrification systems, test systems of transformer oil, industrial control problems in metallurgy, power control for wind turbine fatigue balancing, advanced methods for forecasting of PV output power as well as wind speed and power, control of the AC/DC hybrid power systems with renewables and storage systems, electric-gas energy systems’ risk assessment, battery’s degradation status prediction, insulators fault forecasting, and autonomous energy coordination using blockchain-based negotiation model. In addition, review of the blockchain technology for information security of the energy internet is given. We believe that this special issue will be of interest not only to academics and researchers, but also to all the engineers who are seriously concerned about the unsolved problems in contemporary power engineering, multi-energy microgrids modeling.

Abstract. Cloud computing is an important part of the development of smart cities and also the focus of the information and communication technology (ICT) industry. From the concept of cloud computing, people and objects in cities are organized based on their application needs and computed in real time. It is a comprehensive utilization of the new generation of information and communication technology. This paper first introduces the concept of cloud computing, smart city construction in Taiwan, and the information security management standard of cloud computing, then describes the cloud computing security framework from three areas,and summarizes the implementation status of cloud computing in Taiwan, government policies, and measures, reaching the conclusion that information transmission must be fast and reliable and ensure personal privacy and security. Any type of information security problem will bring catastrophic consequences. Therefore, cloud computing also brings severe challenges to the traditional information security system.

In Industry 4.0, the concept of a Smart Factory heralds a new phase in manufacturing; the Smart Factory System (SFS) will have a huge demand in Taiwan. However, the cost of constructing a factory system will be high, and the complexity processes and introduction time must be considered. Thus, it is important to figure out how to grasp the key success factors for Smart Factories to reduce difficulties in the process, deal with the occurrence of problems, and improve the success rate of constructing Smart Factories. This research constructs an SFS recommendation model to make up for past research deficiencies in terms of recommendation. It combines the methodology of the Engel–Kollat–Blackwell Model (EKB Model) and the Modified Delphi Method to derive SFS recommendation indicators. Through analyzing weights, the ELECTRE II was used to obtain the importance of each dimension by calculating the Modified Compound Advantage Matrix. For prototype indicators, it reviewed the past literature to find out deficiencies and examined the world’s four largest manufactories or computer technology corporations to analyze their Smart Factory solutions regarding the SFS function characteristics. The survey ran for several rounds with a group of five experts to amend indicators until a consensus was obtained. It proposed 64 indicators of 8 primary dimensions in total, based on the Updated Information System Success Model, and then added the concepts of SFS Function characteristics, Information Security, Perceived Value, Perceived Risk, and UI Design. According to the indicators, the framework and prototype of this system will provide solutions and references for purchasing SFS, the functions of which include SFS purchase ability analysis, demand analysis of manufacture problems, and raking and scoring of recommendation indicators. It will provide real-time ranking and the best alternative recommendations to suppliers, and will not only be referred to for design and modification but also enable the requirements to be closer to the users’ demands.

Underwater acoustic signature identification has been employed as a technique for detecting underwater vehicles, such as in anti-submarine warfare or harbour security systems. The underwater sound channel, however, has interference due to spatial variations in topography or sea state conditions and temporal variations in water column properties, which cause multipath and scattering in acoustic propagation. Thus, acoustic data quality control can be very challenging. One of challenges for an identification system is how to recognise the same target signature from measurements under different temporal and spatial settings. This paper deals with the above challenges by establishing an identification system composed of feature extraction, classification algorithms, and feature selection with two approaches to recognise the target signature of underwater radiated noise from a research vessel, Ocean Researcher III, with a bottom mounted hydrophone in five cruises in 2016 and 2017. The fundamental frequency and its power spectral density are known as significant features for classification. In feature extraction, we extract the features before deciding which is more significant from the two aforementioned features. The first approach utilises Polynomial Regression (PR) classifiers and feature selection by Taguchi method and analysis of variance under a different combination of factors and levels. The second approach utilises Radial Basis Function Neural Network (RBFNN) selecting the optimised parameters of classifier via genetic algorithm. The real-time classifier of PR model is robust and superior to the RBFNN model in this paper. This suggests that the Automatic Identification System for Vehicles using Acoustic Signature developed here can be carried out by utilising harmonic frequency features extracted from unmasking the frequency bandwidth for ship noises and proves that feature extraction is appropriate for our targets. References Nathan D Merchant, Kurt M Fristrup, Mark P Johnson, Peter L Tyack, Matthew J Witt, Philippe Blondel, and Susan E Parks. Measuring acoustic habitats. Methods in Ecology and Evolution, 6(3):257265, 2015. doi:10.1111/2041-210X.12330. Nathan D Merchant, Philippe Blondel, D Tom Dakin, and John Dorocicz. Averaging underwater noise levels for environmental assessment of shipping. The Journal of the Acoustical Society of America, 132(4):EL343EL349, 2012. doi:10.1121/1.4754429. Chi-Fang Chen, Hsiang-Chih Chan, Ray-I Chang, Tswen-Yung Tang, Sen Jan, Chau-Chang Wang, Ruey-Chang Wei, Yiing-Jang Yang, Lien-Siang Chou, Tzay-Chyn Shin, et al. Data demonstrations on physical oceanography and underwater acoustics from the marine cable hosted observatory (macho). In OCEANS, 2012-Yeosu, pages 16. IEEE, 2012. doi:10.1109/OCEANS-Yeosu.2012.6263639. Sauda Sadaf P Yashaswini, Soumya Halagur, Fazil Khan, and Shanta Rangaswamy. A literature survey on ambient noise analysis for underwater acoustic signals. International Journal of Computer Engineering and Sciences, 1(7):19, 2015. doi:10.26472/ijces.v1i7.37. Shuguang Wang and Xiangyang Zeng. Robust underwater noise targets classification using auditory inspired time-frequency analysis. Applied Acoustics, 78:6876, 2014. doi:10.1016/j.apacoust.2013.11.003. LG Weiss and TL Dixon. Wavelet-based denoising of underwater acoustic signals. The Journal of the Acoustical Society of America, 101(1):377383, 1997. doi:10.1121/1.417983. Timothy Alexis Bodisco, Jason D'Netto, Neil Kelson, Jasmine Banks, Ross Hayward, and Tony Parker. Characterising an ecg signal using statistical modelling: a feasibility study. ANZIAM Journal, 55:3246, 2014. doi:10.21914/anziamj.v55i0.7818. José Ribeiro-Fonseca and Luís Correia. Identification of underwater acoustic noise. In OCEANS'94.'Oceans Engineering for Today's Technology and Tomorrow's Preservation.'Proceedings, volume 2, pages II/597II/602 vol. 2. IEEE. Linus YS Chiu and Hwei-Ruy Chen. Estimation and reduction of effects of sea surface reflection on underwater vertical channel. In Underwater Technology Symposium (UT), 2013 IEEE International, pages 18. IEEE, 2013. doi:10.1109/UT.2013.6519874. G.M. Wenz. Acoustic ambient noise in the ocean: spectra and sources. Thesis, 1962. doi:10.1121/1.1909155. Donald Ross. Mechanics of underwater noise. Elsevier, 2013. doi:10.1121/1.398685. Chris Drummond and Robert C Holte. Exploiting the cost (in) sensitivity of decision tree splitting criteria. In ICML, volume 1, 2000. Charles Elkan. The foundations of cost-sensitive learning. In International joint conference on artificial intelligence, volume 17, pages 973978. Lawrence Erlbaum Associates Ltd, 2001. Chris Gillard, Alexei Kouzoubov, Simon Lourey, Alice von Trojan, Binh Nguyen, Shane Wood, and Jimmy Wang. Automatic classification of active sonar echoes for improved target identification. Douglas C Montgomery. Design and analysis of experiments. John wiley and sons, 2017. doi:10.1002/9781118147634. G Taguchi. Off-line and on-line quality control systems. In Proceedings of International Conference on Quality Control, 1978. Sheng-Ju Wu, Sheau-Wen Shiah, and Wei-Lung Yu. Parametric analysis of proton exchange membrane fuel cell performance by using the taguchi method and a neural network. Renewable Energy, 34(1):135144, 2009. doi:10.1016/j.renene.2008.03.006. Genichi Taguchi. Introduction to quality engineering: designing quality into products and processes. Technical report, 1986. doi:10.1002/qre.4680040216. Richard Horvath, Gyula Matyasi, and Agota Dregelyi-Kiss. Optimization of machining parameters for fine turning operations based on the response surface method. ANZIAM Journal, 55:250265, 2014. doi:10.21914/anziamj.v55i0.7865. Chuan-Tien Li, Sheng-Ju Wu, and Wei-Lung Yu. Parameter design on the multi-objectives of pem fuel cell stack using an adaptive neuro-fuzzy inference system and genetic algorithms. International Journal of Hydrogen Energy, 39(9):45024515, 2014. doi:10.1016/j.ijhydene.2014.01.034. Antoine Guisan, Thomas C Edwards Jr, and Trevor Hastie. Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecological modelling, 157(2-3):89100, 2002. doi:10.1016/S0304-3800(02)00204-1. Sheng Chen, Colin FN Cowan, and Peter M Grant. Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on neural networks, 2(2):302309, 1991. doi:10.1109/72.80341. Howard Demuth and Mark Beale. Neural network toolbox for use with matlab-user's guide verion 4.0. 1993. Janice Gaffney, Charles Pearce, and David Green. Binary versus real coding for genetic algorithms: A false dichotomy? ANZIAM Journal, 51:347359, 2010. doi:10.21914/anziamj.v51i0.2776. Daniel May and Muttucumaru Sivakumar. Techniques for predicting total phosphorus in urban stormwater runoff at unmonitored catchments. ANZIAM Journal, 45:296309, 2004. doi:10.21914/anziamj.v45i0.889. Chang-Xue Jack Feng, Zhi-Guang Yu, and Andrew Kusiak. Selection and validation of predictive regression and neural network models based on designed experiments. IIE Transactions, 38(1):1323, 2006. doi:10.1080/07408170500346378. Yin-Ying Fang, Ping-Jung Sung, Kai-An Cheng, Meng Fan Tsai, and Chifang Chen. Underwater radiated noise measurement of ocean researcher 3. In The 29th Taiwan Society of Naval Architects and Marine Engineers Conference, 2017. Yin-Ying Fang, Chi-Fang Chen, and Sheng-Ju Wu. Analysis of vibration and underwater radiated noise of ocean researcher 3. In The 30th Taiwan Society of Naval Architects and Marine Engineers Conference, 2018. Det Norske Veritas. Rules for classification of ships new buildings special equipment and systems additional class part 6 chapter 24 silent class notation. Rules for Classification of ShipsNewbuildings, 2010. Underwater acousticsquantities and procedures for description and measurement of underwater sound from ships-part 1requirements for precision measurements in deep water used for comparison purposes. (ISO 17208-1:2012), 2012. Bureau Veritas. Underwater radiated noise, rule note nr 614 dt r00 e. Bureau Veritas, 2014. R.J. Urick. Principles of underwater sound, volume 3. McGraw-Hill New York, 1983. Lars Burgstahler and Martin Neubauer. New modifications of the exponential moving average algorithm for bandwidth estimation. In Proc. of the 15th ITC Specialist Seminar, 2002. Bishnu Prasad Lamichhane. Removing a mixture of gaussian and impulsive noise using the total variation functional and split bregman iterative method. ANZIAM Journal, 56:5267, 2015. doi:10.21914/anziamj.v56i0.9316. Chao-Ton Su. Quality engineering: off-line methods and applications. CRC press, 2016. Jiju Antony and Mike Kaye. Experimental quality: a strategic approach to achieve and improve quality. Springer Science and Business Media, 2012. Ozkan Kucuk, Tayeb Elfarah, Serkan Islak, and Cihan Ozorak. Optimization by using taguchi method of the production of magnesium-matrix carbide reinforced composites by powder metallurgy method. Metals, 7(9):352, 2017. doi:10.3390/met7090352. G Taguchi. System of experimental design, quality resources. New York, 108, 1987. Gavin C Cawley and Nicola LC Talbot. Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers. Pattern Recognition, 36(11):25852592, 2003. doi:10.1016/S0031-3203(03)00136-5.

AbstractWith the rapid advancement of innovative technology, coupled with IT being a core function in contemporary business, there has been an upward trend of multi-national companies (MNCs) reporting a skill deficit in areas such as data analytics and cybersecurity (Columbus, 2017. IBM predicts demand for data scientists will soar 28% By 2020. Forbes; NeSmith, 2018. The cybersecurity gap is an industry crisis. Forbes). In a recent survey with over 3,000 CIOs, 65% indicated their organizations were unable to maintain par with the progression of technology in areas such as data analytics and security due to a lack of adequate talent (Harvey Nash &amp; KPMG, 2018. CIO survey 2018). Although, organizations have recently started to expand their talent pipeline following a neurological breakthrough: research as well as anecdotal evidence suggests adults with mild forms of autism display above-average intelligence, increased attention focus, and high visual–spatial abilities; a combination in high market demand for roles such as software testing, data analysis, cybersecurity, and engineering due to their uncanny ability with pattern recognition, information processing, analytics, and attention to detail.These auspicious developments come at the helm of an increasing rate of governments around the world implementing provisions to their labour regulations towards equitable hiring of people with disabilities (Myors et al., 2017. Perspectives from 22 countries on the legal environment for selection. Handbook of Employee Selection. 659–677. Research Collection Lee Kong Chian School of Business.). Some, such as France, Japan, Kenya, Korea, and Taiwan, have gone so far as to set quota targets (Myors et al., 2017. Perspectives from 22 countries on the legal environment for selection. Handbook of Employee Selection. 659–677. Research Collection Lee Kong Chian School of Business.). The implication for organizations is that they need to develop disability-inclusive recruitment and selection systems along with work designs and environments that are disability friendly. But what does this mean in practice? What does a disability-inclusive recruitment and selection system look like?Enter DXC Technology (DXC): born out of a merger between global conglomerate Computer Science Corporation and Hewlett Packard Enterprise, generating close to $25 billion annually in revenue, with clients across more than 70 countries, they strategically became a pioneer in the digital transformation that was taking place globally. In the wake of the breakthrough in employment diversity, DXC recognized this as an opportunity to gain a critical edge within the increasingly competitive talent pool market. First, design a program of their own for recruiting and selecting adults with high functioning autism. Next, through a collaboration with various universities including the University of Queensland and Macquarie University, Neurodiversity Hubs were established; an initiative designed to assist neurodivergent students with obtaining work experience and internships. In doing so, they faced the following key challenges: How could they design a recruitment and selection strategy for neurodivergent individuals that was equitable, ethical, and efficient? In particular, where could they find suitable neurodivergent candidates, what criteria should they use to select them, and how should they handle unsuccessful candidates to ensure beneficial outcomes for all stakeholders?

Many banks are eager to adopt technology solutions to enhance operational efficiency in managing supply chain finance, which involves various participants and complex financial activities. Previous research either focuses on the technology aspect or the optimization of a supply chain; there is little specific guidance on how banks can form a holistic model to evaluate their Fintech strategy for supply chain finance. By using an integrated approach, this study adopted the decision- making trial and evaluation laboratory (DEMATEL) and several analytical methods to construct a hybrid decision model for banks. We concluded four plausible Fintech strategies from previous research and highlighted the advantages of the blockchain-based strategy. We used a domestic bank in Taiwan as a case study during the evaluation phase and implemented crisp and confidence-based fuzzy assessments. The result indicates that the blockchain-based leading strategy would be ideal for this bank. The hybrid decision model also unveils the complicated relationships among those evaluation factors, which sheds light on banks pursuing their innovation in financial services. The findings contribute to banks developing their Fintech-based supply chain financing business, and the supply chain participants may also benefit from securing efficient loans to expedite their operations.

Hybrid computational intelligent systems that synergize learning-based inference models and route planning strategies have thrived in recent years. In this article, we focus on the non-monotonicity originated from heterogeneous urban data, as well as heuristics based on neural networks, and thereafter formulate the traveling transporter problem (TTP). TTP is a multi-criteria optimization problem and may be applied to the circular route deployment in public transportation. In particular, TTP aims to find an optimized route that maximizes passenger flow according to a neural-network-based inference model and minimizes the length of the route given several constraints, including must-visit stations and the requirement for additional ones. As a variation of the traveling salesman problem (TSP), we propose a framework that first recommends new stations’ location while considering the herding effect between stations, and thereafter combines state-of-the-art TSP solvers and a metaheuristic named Trembling Hand , which is inspired by self-efficacy for solving TTP. Precisely, the proposed Trembling Hand enhances the spatial exploration considering the structural patterns, previous actions, and aging factors. Evaluation conducted on two real-world mass transit systems, Tainan and Chicago, shows that the proposed framework can outperform other state-of-the-art methods by securing the Pareto-optimal toward the objectives of TTP among comparative methods under various constrained settings.

Abstract During the past decade, several misbehaving certificate authorities (CAs) have issued fraudulent TLS certificates allowing man-in-the-middle (MITM) kinds of attacks that result in serious security incidents. In order to avoid such incidents, Yakubov et al. ((2018) A blockchain-based PKI management framework. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, Taipei, Taiwan, April, pp. 16. IEEE) recently proposed a new public key infrastructure (PKI) architecture where CAs issue, revoke and validate X.509 certificates on a public blockchain. However, in their proposal TLS clients are subject to MITM kinds of attacks, and certificate transparency is not fully provided. In this paper, we eliminate the issues of the Yakubov et al.’s scheme and propose a new PKI architecture based on permissioned blockchain with PBFT consensus mechanism where the consensus nodes utilize a dynamic threshold signature scheme to generate signed blocks. In this way, the trust to the intermediary entities can be completely eliminated during certificate validation. Our scheme enjoys the dynamic property of the threshold signature because TLS clients do not have to change the verification key even if the validator set is dynamic. We implement our proposal on private Ethereum network to demonstrate the experimental results. The results show that our proposal has negligible overhead during TLS handshake. The certificate validation duration is less than the duration in the conventional PKI and Yakubov et al.’s scheme.