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The Lanczos vectors and the Ritz vectors have been used for computing the dynamic response of linear structures. Although the procedures of using these two sets of vectors appear similar to the procedure of using the eigenvectors to find an approximate solution, the fundamental mechanisms of the three are different. We compare the three sets of vectors in detail to show some of the important differences in the hope that this comparison will be helpful to the use of the Lanczos vectors or the Ritz vectors for computing dynamic responses.

Alternative education settings (AES; i.e., self-contained alternative schools, therapeutic day treatment and residential schools, and juvenile corrections schools) serve youth with complicated and often serious academic and behavioral needs. The use of evidence-based practices (EBPs) and practices with Best Available Evidence are necessary to increase the likelihood of long-term success for these youth. In this chapter, we define three primary categories of AES and review what we know about the characteristics of youth in these schools. Next, we discuss the current emphasis on identifying and implementing EBPs with regard to both academic interventions (i.e., reading and mathematics) and interventions addressing student behavior. In particular, we consider implementation in AES, where there are often high percentages of youth requiring special education services and who have a significant need for EBPs to succeed academically, behaviorally, and in their transition to adulthood. We focus our discussion on: (a) examining approaches to identifying EBPs; (b) providing a brief review of EBPs and Best Available Evidence in the areas of mathematics, reading, and interventions addressing student behavior for youth in AES; (c) delineating key implementation challenges in AES; and (d) providing recommendations for how to facilitate the use of EBPs in AES.

The detection of an adversary in secret image sharing has been a problematic side in the reconstruction phase. Some of verifiable secret sharing solutions have been proposed to solve the problem. However, there is some computational limitation in the previous schemes. The purpose of this paper is to analyze the importance of consistency for detecting an adversary in a secure reconstruction phase. Strong t-consistency assures the correctness of reconstructed secret as long as participants P ∈ N and n(P) = t. Consistency is a solution for preventing the participant to be absent and helps the dealer to easily detect the adversary without an additional verification step.

This paper focuses on secure reconstruction, and uses two different approaches, namely, single-secret and multi-secret, to experiment the relationship between the given variable (t,m,n) and the adversaries by observing the quality test result, polynomial approach and visualization.

The results show that t and m are inversely proportional to the image quality without respect to the polynomial approach. The reconstruction phase is declared as securely conducted when m = 2t − 1, for both single- and multi-secret approaches.

The application of consistency is a considerable step for securing the secret from an adversary by combining the reconstruction phase and the consistency combination at once, removing the need for additional separate verification steps for decreasing the computational time, especially in secret image sharing.

As library collections increase rapidly, personalized recommender systems have become a very important service for library patrons. The purpose of this paper is to design and implement a personal ontology recommender (PORE) system by building personal ontologies based on patrons' borrowing records.

In the PORE system, the traditional cataloging scheme, classification for Chinese libraries, is used as the reference ontology. This reference ontology is transformed to a unique personal ontology for each user based on the mining results from library borrowing records of that user.

A personal ontology represents a unique user interest on specific subjects. The personal ontology can be used to filter out unsuitable recommendations based only on a keyword matching method. Besides, the recommended books can be organized into the personal ontology, and provide the patron with a user‐friendly interface to access library collections.

The PORE system is currently implemented for Chinese collections. From this paper builds a new version to support English collections by adopting the Library of Congress Classification as the reference ontology.

This paper represents a practical method of building a user's personal ontology and explains the functional use of ontology knowledge.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

This study responded to calls to investigate the behavioural and social antecedents that produce a highly positive response to AI bias in a constrained region, which is characterised by a high share of people with minimal buying power, growing but untapped market opportunities and a high number of related businesses operating in an unregulated market.

Drawing on empirical data from 225 human resource managers from Ghana, data were sourced from senior human resource managers across industries such as banking, insurance, media, telecommunication, oil and gas and manufacturing. Data were analysed using a fussy set qualitative comparative analysis (fsQCA).

The results indicated that managers who regarded their response to AI bias as a personal moral duty felt a strong sense of guilt towards the unintended consequences of AI logic and reasoning. Therefore, managers who perceived the processes that guide AI algorithms' reasoning as discriminating showed a high propensity to address this prejudicial outcome.

As awareness of consequences has to go hand in hand with an ascription of responsibility; organisational heads have to build the capacity of their HR managers to recognise the importance of taking personal responsibility for artificial intelligence algorithm bias because, by failing to nurture the appropriate attitude to reinforce personal norm among managers, no immediate action will be taken.

By integrating the social identity theory, norm activation theory and justice theory, the study improves our understanding of how a collective organisational identity, perception of justice and personal values reinforce a positive reactive response towards AI bias outcomes.

One‐time password systems provide great strengths over conventional password systems: protection against over‐the‐shoulder, eavesdropping, replay, etc. The Grid Data Security authentication system is a server‐challenge‐based system. It has advantages over other one‐time password systems since it does not require pre‐installed software nor special devices to carry on. However, there are some weaknesses. The purpose of this paper is to analyze the weaknesses of the one‐time password system and provide practical guidelines for using the one‐time password system.

This paper statistically analyzes the weakness of the Grid Data Security authentication system and simulates attacks to the system to confirm the discovered weakness. The paper also suggests ways to reduce the discovered vulnerability using mathematical formula and offers practical guideline for using the system. It also identifies the system's strength on access authentication on mobile communication.

The Grid Data Security authentication system which is a server‐challenge‐based one‐time password system has a great weakness when an attacker gains its user‐interface screen and its GridCode. The discovered vulnerability can be improved by changing cardinality of the GridCode. This paper creates a formula that can help a system manager to decide the security level and its required cardinality of GridCode and length of password. It also identifies the system's strengths on mobile communication.

The paper provides a practical tool for security managers to identify requirements of cardinality of GridCode and password length for certain levels of security.

The existing research does not systematically explore customers' option about different payment methods, nor does it analyze how shopping channels and shopping scale affect customers' option about different payment methods. Furthermore, there is a lack of exploration on what the relationship is, and how they are adjusted by customer purchasing experience. The authors’ research questions are: (1) when using different shopping channels in online retailing, whether customers will choose different types of payment methods? (2) Does the purchase amounts affect customers' choice of different payment methods?

This study takes 60,484 customers from JD.com, one of the largest B2C platforms in China, as the research object and collects the purchase data of these customers from October 01, 2012 to December 31, 2013, and analyzes them through panel data models.

Based on their purchase data, the authors find the main results by using panel data model that (1) the use of mobile channel has a positive effect on cash on delivery (COD), implying that when consumers use mobile to purchase, they have a higher possibility to use COD, (2) the order size has a positive effects on COD, that is to say, when the purchase amount increases, the possibility of using COD also increases. (3) Furthermore, when consumers' purchase experience abound, mobile channel's positive effect on COD will be decreased, but it does not affect the positive effect between order size and COD.

From the aspects of shopping channels, product attributes and customer purchase experience, it fills the gaps in the research on the preselection of payment methods and makes research of payment methods a complete research system. Secondly, this study adds COD to the options of payment method selection. Finally, the moderating effect of customer shopping experience from a dynamic perspective elaborates that customers can learn from multiple purchases and overcome the shopping risks brought by shopping channels, thereby reducing the probability of choosing a COD method.