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This paper presents a novel design method for keyboard circuits. The purpose of this study is to enable a single-board computer with fewer pins to recognize a keyboard system consisting of a large number of switches. Through the study of different kinds of keyboard circuits, a general circuit schematic design method is abstracted. Several experiments are conducted to prove the feasibility of the proposed circuit design method.

Conventional circuit schematic diagrams are often limited to two-dimensional planes. Through investigating higher dimensional alternatives, this paper proposes to place components in high-dimensional geometry before connecting all components. A multi-pin switch construction method is proposed to allow the switches to be arranged on the vertices of high-dimensional geometry and be connected sequentially to form the keyboard system. This proposed system can allow a keyboard system consisting of a large number of switches to be recognized by a single-board computer with less available pins.

The design scheme proposed in this paper can read more switch states with limited Input/Output pins. With the increase of the number of Input/Output ports and pins, the number of simultaneously identifiable switches increases exponentially, which is suitable for sensor design of array type.

Compared with the classical keyboard circuits, the circuit designed using the proposed method will lead to a slightly longer recognition time for each key. This can be compensated by a single-board computer with a modestly higher clock speed.

The circuit schematic design method based on high-dimensional geometry is introduced for the first time. The feasibility of the proposed method is verified by the original experiments. The proposed approach is of importance in guiding the design of new analog and digital sensor circuit systems.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

The public sector use of the internet of Things (IoT) technology is an emerging field with a potential for a variety of institutional applications in the fields of information gathering and policy implementation to establish resilience for modern society. In this context, we aim to investigate the success factors which can positively influence the continuous usage intention of IoT service with the mediation effect of perceived public value.

A conceptual model based on the strong literature and theoretical background is tailored to provide factors for IoT services success in the public sector. A quantitative survey was conducted through 381 citizens using IoT services to validate the proposed conceptual model using structural equation modeling approach in order to examine the influence of identified constructs on the continuous usage intention.

The results highlighted that the proposed model successfully accounted for about 59% perceived variance in public value creation and 63% perceived variance in citizens' continuous usage intention. IoT services success is best dignified by the perceptions of citizens who use the services, therefore, this study identifies the positive role of digital society affinity in context of social sustainability and it climaxes that the real value of IoT in public sector comes from establishment of services on top of the service delivery and that's where the public value is going to be created.

The use of IoT technology in public services will fetch much benefit to the citizens as well as to the government. The study findings are significant in identifying good practices for generating public value in digital society affinity.

The integrated conceptual model explores the driving factors of citizens' inclination towards IoT technology in a social context. Through this study, we can analyze the role of perceived public value in enhancing the citizens' engagement with IoT services. The government policymakers and ICT managers take help from this study to designing IoT public services with making the government more responsive to citizens.

This paper aims to provide a well-behaved nonlinear scheme and accelerating iteration for the nonlinear convection diffusion equation with fundamental properties illustrated.

A nonlinear finite difference scheme is studied with fully implicit (FI) discretization used to acquire accurate simulation. A Picard–Newton (PN) iteration with a quadratic convergent ratio is designed to realize fast solution. Theoretical analysis is performed using the discrete function analysis technique. By adopting a novel induction hypothesis reasoning technique, the L^∞ (H¹) convergence of the scheme is proved despite the difficulty because of the combination of conservative diffusion and convection operator. Other properties are established consequently. Furthermore, the algorithm is extended from first-order temporal accuracy to second-order temporal accuracy.

Theoretical analysis shows that each of the two FI schemes is stable, its solution exists uniquely and has second-order spatial and first/second-order temporal accuracy. The corresponding PN iteration has the same order of accuracy and quadratic convergent speed. Numerical tests verify the conclusions and demonstrate the high accuracy and efficiency of the algorithms. Remarkable acceleration is gained.

The numerical method provides theoretical and technical support to accelerate resolving convection diffusion, non-equilibrium radiation diffusion and radiation transport problems.

The FI schemes and iterations for the convection diffusion problem are proposed with their properties rigorously analyzed. The induction hypothesis reasoning method here differs with those for linearization schemes and is applicable to other nonlinear problems.

The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.

Customer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.

When the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.

This study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.

This paper aims to provide details of a study on the widely shared definition of e‐government and to help scholars – especially young scholars – to understand the scope and meaning of the field.

From 1998‐2007, a ten‐year time‐span, 632 articles from the three world‐leading academic databases, including Wiley InterScience, Elsevier ScienceDirect, and SCI Expanded, were retrieved and 324 were analyzed using CATA software (Concordance 3.20), to identify the vocabulary that was used frequently by e‐government scholars. Then the distinct vocabulary was used to construct the widely shared definition of e‐government.

In those 324 articles, 57 words generated from the text analysis formed the basis for imputing a widely shared definition of the field of e‐government. The definition was conceptualized by six elements.

Two limitations of the pool of articles selected may be noted. First, articles were drawn from three leading academic databases in an effort to distinguish e‐government from other fields; but such an approach omitted any consideration of how e‐government definitions varied from different academic fields. Second, because the pool of articles was drawn only from these three, journals excluded by these databases were thus omitted.

The study is unique in that it discusses the definition of e‐government by an exploratory approach. The universal shared definition extracted could serve as either a screen or a magnet for future research. And the methodology could be applied to several academic fields, including administration and management, library and information science, e‐records management, computer science, etc.

It is necessary to implement green supply chains. But green development needs to be gradual and coexist with ordinary products in the market. This paper aims to study the green and ordinary product pricing and green decision-making under chain-to-chain competition.

This paper considers consumers' multiple preferences and takes two competitive supply chains with asymmetric channels as the research object. Through the construction of the game models involving different competitive situations, this paper studies the pricing, green decision-making and the supply chains' profits, and discusses the impact of consumer green preference, channel preference, green investment and competition on the decision-making and performance. Finally, this paper further studies the impact of the decision structure on the environmental and economic benefits of supply chains.

The results show that consumer green preference has an incentive effect on the green supply chain and also provides an opportunity for the regular supply chain to increase revenue. Specifically, consumers' preference for green online channels improves the product greenness, but its impact on the green retailer and regular supply chain depends on the green investment cost. Moreover, competition not only fosters product sustainability, but also improves supply chain performance. This paper also points out that the decentralization of the regular supply chain is conducive to the environmental attributes of the green product, while the environment-friendly structure of the green supply chain is different under different conditions. In addition, the profit of a supply chain under centralized decision is not always higher than that under decentralized decision.

The novelty of this paper is that it investigates the pricing of two heterogeneous alternative products and green decision-making for the green product under the competition between two supply chains with asymmetric channels, in which the green supply chain adopts dual channels and the regular supply chain adopts a single retail channel.

In the modern era, libraries confront significant service challenges. Some challenges are linked to information resource management which includes direct availability of information for immediate decision making. The Internet of Things (IoT) is a recent technological shift that library personnel should be aware of because it has the potential to enhance information resource management. The purpose of the research is to highlight the willingness to adopt IoT technology in libraries.

This study uses a quantitative research design in which a survey of public sector universities in Nanjing, China, is conducted to investigate the determinants of IoT adoption intention in libraries. A total of 389 responses were captured from experienced library personnel. The literature on technology adoption is then used to formulate quantitative theories. For data analysis, partial least squares structural equation modeling using SmartPLS.

The research highlights the various success factors which support the IoT service adoption process. It is concluded that IoT augmented services in academic libraries must be supported through robust management practices and effective utilization of technological resources. Many libraries have made substantial modifications to their structure in terms of technology and design to satisfy the demands of patrons.

This is an empirical paper that looks at IoT adoption intention in libraries using a quantitative approach through surveying library personnel. The library personnel can aid in the understanding of the motivations behind technology adoption in libraries, particularly of IoT services that may bring about advances in the libraries' capability to provide information access services.

Most of the existing ground filtering algorithms are based on the Cartesian coordinate system, which is not compatible with the working principle of mobile light detection and ranging and difficult to obtain good filtering accuracy. The purpose of this paper is to improve the accuracy of ground filtering by making full use of the order information between the point and the point in the spherical coordinate.

First, the cloth simulation (CS) algorithm is modified into a sorting algorithm for scattered point clouds to obtain the adjacent relationship of the point clouds and to generate a matrix containing the adjacent information of the point cloud. Then, according to the adjacent information of the points, a projection distance comparison and local slope analysis are simultaneously performed. These results are integrated to process the point cloud details further and the algorithm is finally used to filter a point cloud in a scene from the KITTI data set.

The results show that the accuracy of KITTI point cloud sorting is 96.3% and the kappa coefficient of the ground filtering result is 0.7978. Compared with other algorithms applied to the same scene, the proposed algorithm has higher processing accuracy.

Steps of the algorithm are parallel computing, which saves time owing to the small amount of computation. In addition, the generality of the algorithm is improved and it could be used for different data sets from urban streets. However, due to the lack of point clouds from the field environment with labeled ground points, the filtering result of this algorithm in the field environment needs further study.

In this study, the point cloud neighboring information was obtained by a modified CS algorithm. The ground filtering algorithm distinguish ground points and off-ground points according to the flatness, continuity and minimality of ground points in point cloud data. In addition, it has little effect on the algorithm results if thresholds were changed.