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The purpose of this study is to present the state of the art for fiber Bragg grating (FBG) acceleration sensing technologies from two aspects: the principle of the measurement dimension and the principle of the sensing configuration. Some commercial sensors have also been introduced and future work in this field has also been discussed. This paper could provide an important reference for the research community.

This review is to present the state of the art for FBG acceleration sensing technologies from two aspects: the principle of the measurement dimension (one-dimension and multi-dimension) and the principle of the sensing configuration (beam type, radial vibration type, axial vibration type and other composite structures).

The current research on developing FBG acceleration sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of a new information detection method. This paper hypothesizes that in the future, the following research trends will be strengthened: common single-mode fiber grating of the low cost and high utilization rate; high sensitivity and strength special fiber grating; multi-core fiber grating for measuring single-parameter multi-dimensional information or multi-parameter information; demodulating equipment of low cost, small volume and high sampling frequency.

The principle of the measurement dimension and principle of the sensing configuration for FBG acceleration sensors have been introduced, which could provide an important reference for the research community.

The study focussed on information literacy practices, specifically on how higher education staff managed the transition from established and routinised in-person teaching, learning and working practices to institutionally mandated remote or hybrid working patterns during the COVID-19 pandemic.

The qualitative study forms part of a broader research project, examining how information literacy and information practices unfolded during the COVID-19 pandemic. Phase Three of this project, which forms the subject of this paper, employed semi-structured interviews to explore the impact of COVID-19 on the workplace and, in particular, the role that technology and digital literacy plays in enabling or constraining information literacy practices necessary for the operationalisation of work.

The complexities of the COVID-19 pandemic precipitated a fracturing of workplace information environments and worker information landscapes by disrupting all aspects of academic life. The study recognises that whilst the practice of information literacy is predicated on access to modalities of information, this practice is also shaped by material conditions. This has implications for digital literacy which, in attempting to set itself apart from information literacy practice, has negated the significant role that the body and the corporeal modality play as important sources of information that enable transition to occur. In relation to information resilience, the bridging concept of fracture has enabled the authors to consider the informational impact of crisis and transition on people's information experiences and people's capacity to learn to go on when faced with precarity. The concept of grief is introduced into the analysis.

This study presents original research.

The purpose of this paper is to propose a new method to achieve omni-directional vibration vector signal acquisition, and use this method to improve the accuracy of the underground explosion point localization.

Following an introduction, this paper describes the design principle of a sensor structure, and discusses the rationality of the spherical structure of the sensor through finite element analysis. The sensor prototype is designed according to the above method, and its performance is tested by the sensor calibration experiment. Finally, applications are also discussed.

This paper shows that the method for underground omni-directional vibration signal acquisition is reasonable and feasible. The vibration sensor, designed by this method, of which the triaxial dynamic characteristics are consistent, and the three-dimensional vibration information acquired by this sensor can achieve high-precision localization for an underground explosion point.

The paper describes a new method for omni-directional vibration vector signal acquisition. The vibration sensor is developed based on this method, which has a broad application prospect in the positioning of an underground explosion point, the evaluation of explosive power and other underground projects.

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

The purpose of this study was to uncover representative emergent areas and to examine the research area of marketing, tourism and big data (BD) to assess how these thematic areas have developed over a 27-year time period from 1996 to 2022. This study analyzed 1,152 studies to identify the principal thematic areas and emergent topics, principal theories used, predominant forms of analysis and the most productive authors in terms of research.

The articles for this research were all selected from the Web of Science database. A systematic and quantitative literature review was performed. This study used SciMAT software to extract indicators. Specifically, this study analyzed productivity and produced a science map.

The findings suggest that interest in this area has increased gradually. The outputs also reveal the innovative effort of industry in new technologies for developing models for tourism marketing. Ten research areas were identified: “destination marketing,” “mobility patterns,” “co-creation,” “gastronomy,” “sustainability,” “tourist behavior,” “market segmentation,” “artificial neural networks,” “pricing” and “tourist satisfaction.”

This work is unique in proposing an agenda for future research into tourism marketing research with new technologies such as BD and artificial intelligence techniques. In addition, the results presented here fill the current gap in the research since while there have been literature reviews covering tourism with BD or marketing, these areas have not been studied as a whole.

El objetivo de esta investigación fue descubrir nichos representativos de áreas emergentes y examinar el área de Marketing, Turismo y Big Data, evaluando cómo han evolucionado estas áreas temáticas durante un período de 27 años desde 1996–2022. Analizamos 1.152 investigaciones para identificar las principales áreas temáticas y temas emergentes, las principales teorías utilizadas, las formas de análisis predominantes y los autores más productivos en términos de investigación.

Todos los artículos para esta investigación fueron seleccionados de la base de datos Web of Science. Realizamos una revisión sistemática y cuantitativa de la literatura. Utilizamos el software SciMAT para extraer indicadores. Específicamente, analizamos la productividad y elaboramos un mapeo científico.

Los hallazgos sugieren que el interés en esta área ha aumentado gradualmente. Los resultados también revelan el esfuerzo innovador de la industria en nuevas tecnologías para desarrollar modelos de marketing turístico. Se identificaron diez áreas de investigación (“marketing de destinos”, “patrones de movilidad”, “co-creación”, “gastronomía”, “sostenibilidad”, “comportamiento turístico”, “segmentación de mercado”, “redes neuronales artificiales”, “precios”, y “satisfacción del turista”).

Este trabajo es único al proponer una agenda para futuras investigaciones en investigación de Marketing Turístico con nuevas tecnologías como Big Data y técnicas de Inteligencia Artificial. Además, los resultados presentados aquí llenan el vacío actual en la investigación ya que si bien se han realizado revisiones de literatura que cubren Turismo con Big Data o Marketing, estas áreas no se han estudiado como un conjunto.

这一特定研究领域的目标是发现具有代表性的新兴领域, 并考察市场营销、旅游和大数据研究领域, 以评估这些主题领域在1996年至2022年的27年间是如何发展的。我们分析了1152项研究, 以确定主要专题领域和新兴主题、使用的主要理论、主要的分析形式以及在研究方面最有成效的作者。

本研究的文章都是从Web of Science数据库中选出的。我们进行了系统化的定量文献审查, 并使用SciMAT软件来提取指标。具体来说, 我们分析了生产力并制作了一个科学研究地图。

研究结果表明, 人们对这一领域的兴趣已经逐渐增加。本文也揭示了工业界在开发旅游营销模式的新技术方面的创新努力。研究确定了十个研究领域：“目的地营销”、“流动模式”、“共同创造”、“美食”、“可持续性”、“游客行为”、“市场细分”、“人工神经网络”、“定价 “和游客满意度”。

这项研究的独特之处在于提出了未来利用大数据和人工智能技术等新技术进行旅游营销研究的议程。此外, 本文的结果填补了目前的研究空白, 因为虽然有文献综述涉及旅游与大数据或市场营销, 但这些领域还没有被作为一个整体来研究。

Really new products (RNP) run the risk not only of technical problems in the development process, but also of problems with customer acceptance. Because market uncertainty in particular is frequently high, many top management teams defer essential management decisions on these products until sufficient information is available to be able to make a sound decision. In many cases, however, the market is already been divided up by that time. The purpose of this paper is to examine how better information about customers can be acquired by providing them with a better offering of information which has been prepared in a variety of forms (“information acceleration”) and how management decisions can be improved as a result.

The paper is based on modern models for decision making under uncertainty that incorporate group decisions, and shows how the measurement of purchasing behavior can be improved by information acceleration in a test studio. This is needed because customers generally cannot draw on mentally established analogies in the case of RNP, so that they are virtually unable to make meaningful statements that would improve strategic management decisions when completing standard customer surveys. A test studio was set up in the form of a Car Clinic for the example of a future electric vehicle as a RNP. 121 customers were to be offered a wide variety of information (about the future urban environment, the design of the vehicle concept and the driver’s experience), partly in order to acquire information about the customers. In particular, the extent to which customers could better evaluate their purchasing probability and willingness to pay certain prices and the extent to which the variance of customer opinions was reduced after attending the Car Clinic were examined, because these factors make it easier to forecast future sales revenue and management decisions can be made more easily.

The results reveal that information acceleration in a test studio can improve the estimation of sales revenue in an early decision-making phase and can have a positive influence on decision-making behavior under uncertainty.

This study provides an empirical, valuable step toward an investigation of management decisions on RNP under uncertainty.

The purpose of this paper is to employ an extended Kalman filter for implementing an AHRS (attitude and heading reference system) with acceleration compensation, thereby improving the reliability of such systems, since this removes the usual restrictive assumption that the vehicle is undergoing a non‐accelerated maneuver.

MARG (magnetic, acceleration and rate gyros) sensors constitute the basic hardware, which are integrated by the Kalman filter. The error dynamics for attitude and gyro biases is obtained in the navigation frame, providing a much simpler approach than usually taken in the literature, since it relies on direct quaternion differentiation. The state vector associated to the error dynamics possesses six components: three are associated to the quaternion error and three concern gyro bias estimates.

The AHRS is implemented in an ARM (Advanced RISC Machine) processor and tested with experimental data. The accelerated case is treated by two complementary approaches: by changing the noise variance in the Kalman filter, and by obtaining an acceleration information from GPS (global positioning system) velocity measurements. Experimental results are presented and the performance is compared with commercial ARHS systems.

The proposed AHRS can be implemented with low cost MARG sensors, and GPS aiding, with use for instance in UAV (unmanned aerial vehicle) and small aircrafts' attitude estimation, for navigation and control applications.

Usually the AHRS designs employ as states total gyro bias and Euler angles, or quaternion, and do not consider the accelerated case. Here the state is comprised by gyro bias and quaternion error variables, which attenuates the effect of nonlinearities, and two complementary procedures tackle the accelerated case: acceleration correction by using a GPS derived acceleration signal and change in the output noise covariance used by the Kalman filter.

The article introduces selected theoretical approaches to time and temporality relevant to the field of library and information science, and it briefly introduces the papers gathered in this special issue. A number of issues that could potentially be followed in future research are presented.

The authors review a selection of theoretical and empirical approaches to the study of time that originate in or are of particular relevance to library and information science. Four main themes are identified: (1) information as object in temporal perspectives; (2) time and information as tools of power and control; (3) time in society; and (4) experiencing and practicing time.

The paper advocates a thorough engagement with how time and temporality shape notions of information more broadly. This includes, for example, paying attention to how various dimensions of the late-modern time regime of acceleration feed into the ways in which information is operationalised, how information work is commodified, and how hierarchies of information are established; paying attention to the changing temporal dynamics that networked information systems imply for our understanding of documents or of memory institutions; or how external events such as social and natural crises quickly alter modes, speed, and forms of data production and use, in areas as diverse as information practices, policy, management, representation, and organisation, amongst others.

By foregrounding temporal perspectives in library and information science, the authors advocate dialogue with important perspectives on time that come from other fields. Rather than just including such perspectives in library and information science, however, the authors find that the focus on information and documents that the library and information science field contributes has great potential to advance the understanding of how notions and experiences of time shape late-modern societies and individuals.

The purpose of this paper is to relate to the real-time navigation and tracking of pedestrians in a closed environment. To restrain accumulated error of low-cost microelectromechanical system inertial navigation system and adapt to the real-time navigation of pedestrians at different speeds, the authors proposed an improved inertial navigation system (INS)/pedestrian dead reckoning (PDR)/ultra wideband (UWB) integrated positioning method for indoor foot-mounted pedestrians.

This paper proposes a self-adaptive integrated positioning algorithm that can recognize multi-gait and realize a high accurate pedestrian multi-gait indoor positioning. First, the corresponding gait method is used to detect different gaits of pedestrians at different velocities; second, the INS/PDR/UWB integrated system is used to get the positioning information. Thus, the INS/UWB integrated system is used when the pedestrian moves at normal speed; the PDR/UWB integrated system is used when the pedestrian moves at rapid speed. Finally, the adaptive Kalman filter correction method is adopted to modify system errors and improve the positioning performance of integrated system.

The algorithm presented in this paper improves performance of indoor pedestrian integrated positioning system from three aspects: in the view of different pedestrian gaits at different speeds, the zero velocity detection and stride frequency detection are adopted on the integrated positioning system. Further, the accuracy of inertial positioning systems can be improved; the attitude fusion filter is used to obtain the optimal quaternion and improve the accuracy of INS positioning system and PDR positioning system; because of the errors of adaptive integrated positioning system, the adaptive filter is proposed to correct errors and improve integrated positioning accuracy and stability. The adaptive filtering algorithm can effectively restrain the divergence problem caused by outliers. Compared to the KF algorithm, AKF algorithm can better improve the fault tolerance and precision of integrated positioning system.

The INS/PDR/UWB integrated system is built to track pedestrian position and attitude. Finally, an adaptive Kalman filter is used to improve the accuracy and stability of integrated positioning system.

The purpose of this paper is to present a novel position estimation method to accurately locate an object. An accelerometer-based error correction method is also developed to correct the positioning error caused by signal drift of a wireless network. Finally, the method is also utilized to locate cows in a farm for monitoring the action of standing heat.

The proposed method adopts the received signal strength indicator (RSSI) of a wireless sensor network (WSN) to compute the position of an object. The RSSI signal can be submitted from an endpoint device. A complex environment destabilizes the RSSI value, making the position estimation inaccurate. Therefore, a three-axial accelerometer is adopted to correct the position estimation accuracy. Timer and acceleration are two major factors in computing the error correction value to adjust the position estimate.

The proposed method is tested on a farm management system for positioning dairy cows accurately. Devices with WSN module and three-axial accelerometer are mounted on the cows to monitor their positions and actions.

If cows in a crowded farm are close to each other, then the position estimation method is unable to position each cow correctly because too many close objects cause interference in the wireless network.

Experimental results demonstrate that the proposed method improves the position accuracy, and monitor the heat action of the cows effectively.

No position estimation method has been utilized to locate cows in a farm, especially for monitoring their actions via WSN and accelerometer. The proposed method adopts an accelerometer to efficiently improve the position error caused from the signal drift of WSN.