Explore the vast range of titles available.

The pay-and-use approach is the basis for the cloud computing services that are currently popular. Resource management is one of the more difficult tasks since it takes a while to identify requests and determine what kind of resources are needed to satisfy the customer's needs. Resource provisioning's goal is to identify and make available the right resources depending on user workload's QoS needs so that applications may make efficient use of the resources. The CSPs now offer advanced resource reserves for both short- and long-term periods. Cloud brokers are required to manage the on-demand cloud resource and maintain track of the SLA list of resource providers for their individual cloud customers in our suggested algorithm RSCC (Reservation System for Cloud Computing). According to the user's needs and cost, the RSCC algorithm functions as a flexible reservation that can accommodate a variety of services. The numerical findings demonstrated that the suggested long-term resource planning method was able to produce operational costs that were almost ideal.

Parking reservation systems (PRS) are promoted as smart urban parking tools, yet their continued use remains limited because users face both technological uncertainty and schedule-related uncertainty. This study develops a behavioral analysis framework that combines structural equation modeling (SEM), a stated-preference binary logit model, and Random Forest learning. SEM examines how perceived usefulness, perceived ease of use, perceived risk, social influence, and behavioral attitude shape intention to reuse. The binary logit model examines whether users retain their reserved lot under 10 reservation mechanisms and three arrival scenarios. Random Forest is then used to test nonlinear prediction and interaction effects, with intention to reuse measured as the average of the two reuse-intention items and model performance evaluated by the conventional coefficient of determination (R2), mean squared error, and mean absolute error. The results show that perceived risk suppresses perceived usefulness and behavioral attitude, early and especially late arrival sharply reduce reservation retention, and discount intensity is the strongest positive operational lever. Random Forest additionally shows that the effect of perceived risk depends on perceived ease of use: a more intuitive interface buffers the negative effect of risk on predicted reuse intention. These findings indicate that behavioral uncertainty in PRS is simultaneously perceptual, situational, and interactive. PRS design should therefore combine flexible time management, transparent real-time information, and low-friction user interfaces.

A limit on use is often practiced overnight in mountain national parks to reduce users’ environmental impact on campgrounds and cabins or huts, where they spend most of their time. This study aims to propose an appropriate management system to mitigate the problems observed in Daisetsuzan National Park’s unmanaged campsites. We looked into three mountain national parks in Taiwan to learn about an established campground reservation system. We collected information on campgrounds and cabins in these three national parks through a literature review and internet surveys. The distribution of campgrounds and cabins was mapped using ArcMap 10.8.1. They effectively reduced the distance between adjacent campgrounds and controlled each campground’s area. This was done by tolerating some informal sites among online reservable campgrounds. The results of the interview surveys with the three park managers showed that the reservation system helped reduce the crowding problem. Introducing a lenient reservation system, with the support of related stakeholders and park users, would be a promising option to mitigate soil erosion and overuse problems in campsites in Daisetsuzan National Park’s alpine zone and in other campsites in fragile environments worldwide.

SABRE aims to directly measure the annual modulation of the dark matter interaction rate with NaI(Tl) crystals. A modulation compatible with the standard hypothesis, in which our Galaxy is immersed in a dark matter halo, has been measured by the DAMA experiment in the same target material. Other direct detection experiments, using different target materials, seem to exclude the interpretation of such modulation in the simplest scenario of WIMP-nucleon elastic scattering. The SABRE experiment aims to carry out an independent search with sufficient sensitivity to confirm or refute the DAMA claim. The goal of the SABRE experiment is to achieve the lowest background rate for a NaI(Tl) experiment (order of 0.1 cpd/kg/keVee in the energy region of interest for dark matter). This challenging goal could be achievable by operating high-purity crystals inside a liquid scintillator veto for active background rejection. In addition, twin detectors will be located in the northern and southern hemispheres to identify possible contributions to the modulation from seasonal or site-related effects. The SABRE project includes an initial Proof-of-Principle phase at LNGS (Italy), to assess the radio-purity of the crystals and the efficiency of the liquid scintillator veto. This paper describes the general concept of SABRE and the expected sensitivity to WIMP annual modulation.

The roadside unit (RSU) is one of the fundamental components in a vehicular ad hoc network (VANET), where a vehicle communicates in infrastructure mode. The RSU has multiple functions, including the sharing of emergency messages and the updating of vehicles about the traffic situation. Deploying and managing a static RSU (sRSU) requires considerable capital and operating expenditures (CAPEX and OPEX), leading to RSUs that are sparsely distributed, continuous handovers amongst RSUs, and, more importantly, frequent RSU interruptions. At present, researchers remain focused on multiple parameters in the sRSU to improve the vehicle-to-infrastructure (V2I) communication; however, in this research, the mobile RSU (mRSU), an emerging concept for sixth-generation (6G) edge computing vehicular ad hoc networks (VANETs), is proposed to improve the connectivity and efficiency of communication among V2I. In addition to this, the mRSU can serve as a computing resource for edge computing applications. This paper proposes a novel energy-efficient reservation technique for edge computing in 6G VANETs that provides an energy-efficient, reservation-based, cost-effective solution by introducing the concept of the mRSU. The simulation outcomes demonstrate that the mRSU exhibits superior performance compared to the sRSU in multiple aspects. The mRSU surpasses the sRSU with a packet delivery ratio improvement of 7.7%, a throughput increase of 5.1%, a reduction in end-to-end delay by 4.4%, and a decrease in hop count by 8.7%. The results are generated across diverse propagation models, employing realistic urban scenarios with varying packet sizes and numbers of vehicles. However, it is important to note that the enhanced performance parameters and improved connectivity with more nodes lead to a significant increase in energy consumption by 2%.

Intro -- Table of Contents -- Trainings -- SME Hotel Sector -- Yield and Revenue Management Systems -- CRM -- Electronic Presence -- International Hotel Chains -- 21st Century Inn System.

User-generated content on social media platforms and product search engines is changing the way consumers shop for goods online. However, current product search engines fail to effectively leverage information created across diverse social media platforms. Moreover, current ranking algorithms in these product search engines tend to induce consumers to focus on one single product characteristic dimension (e.g., price, star rating). This approach largely ignores consumers' multidimensional preferences for products. In this paper, we propose to generate a ranking system that recommends products that provide, on average, the best value for the consumer's money. The key idea is that products that provide a higher surplus should be ranked higher on the screen in response to consumer queries. We use a unique data set of U.S. hotel reservations made over a three-month period through Travelocity, which we supplement with data from various social media sources using techniques from text mining, image classification, social geotagging, human annotations, and geomapping. We propose a random coefficient hybrid structural model, taking into consideration the two sources of consumer heterogeneity the different travel occasions and different hotel characteristics introduce. Based on the estimates from the model, we infer the economic impact of various location and service characteristics of hotels. We then propose a new hotel ranking system based on the average utility gain a consumer receives from staying in a particular hotel. By doing so, we can provide customers with the \"best-value\" hotels early on. Our user studies, using ranking comparisons from several thousand users, validate the superiority of our ranking system relative to existing systems on several travel search engines. On a broader note, this paper illustrates how social media can be mined and incorporated into a demand estimation model in order to generate a new ranking system in product search engines. We thus highlight the tight linkages between user behavior on social media and search engines. Our interdisciplinary approach provides several insights for using machine learning techniques in economics and marketing research.

PurposeIn the last decade, the hospitality sector has undergone numerous changes in the organization and structure of its business models. Specifically, the adoption of new digital technologies has initiated transformative changes toward circular economy and sustainability. The present study aims to analyze whether the use of the digital reservation system in circular entrepreneurship businesses has an impact on entrepreneurs’ satisfaction and trust in the in circular economy.Design/methodology/approachThe data collected via a survey of 317 entrepreneurs who use a circular economy strategy were analyzed using SEM in a proposed model based on circular entrepreneurship businesses and the adoption of digital reservation systems.FindingsThe results showed a positive relationship between usability and perceived ease of use and user satisfaction and trust in using digital reservation systems to boost circular entrepreneurship in hospitality. Therefore, it was identified that adopting a digital reservation system can increase the efficiency of entrepreneur resources, as well as lead to creation of sustainable knowledge, augment the use of new sources of user information, improve prediction of services and demand and, consequently, boost sustainability and circular economy.Research limitations/implicationsFuture research can use the results of the present study to investigate how digital technologies work and affect user trust, satisfaction, and use of these systems in entrepreneurs’ projects in hospitality. In addition, it would be interesting to explore how these factors influence hospitality in different business models that support circular economy in tourism. To this end, researchers can use the variables used in the present study, along with other variables, to extend the proposed model and deepen the authors' research. In summary, this study contributes to the literature on the use of applications in hospitality sector and offer useful insight on how the adoption and use of new technologies can drive the management of knowledge and technology development, decision making and acquisition of new data sources that improve the experience of both entrepreneurs and users that interact with their services to enable circular entrepreneurship.Practical implicationsHospitality entrepreneurs can use the results of the present study to better evaluate how using these applications can affect the communication protocols with their employees and stakeholders. Furthermore, entrepreneurs operating in the hospitality sector can use the results to develop action plans focused on the circular economy, new knowledge creation, as well as development and adoption of new digital technologies that enable circular entrepreneurship. In this way, hospitality companies will be able to effectively combine both more traditional offline channels and new technologies, such as mobile applications or the Internet.Social implicationsThe authors' prediction of a strong positive link between perceived usefulness and user trust was also supported by the results of data analysis. The finding that perceived utility increases user trust in entrepreneurs when making adopting these technologies is also consistent with other similar studies. Finally, the results of this study also confirmed the hypothesized link between the perceived utility of digital technologies and user satisfaction. Taken together, the results also highlight the relevance of analyzing the use of digital reservation systems in the hospitality sector to enable circular entrepreneurship.Originality/valueTaken together, the results highlight the relevance of analyzing the use of digital reservation systems in the hospitality sector to enable circular entrepreneurship and increase the perceived usefulness of new digital technologies so that to improve sustainable actions and the circular economy globally.

The Signal Amplification By Reversible Exchange (SABRE) technique provides enhancement of Nuclear Magnetic Resonance (NMR) signals up to several orders of magnitude using chemical exchange of a substrate and parahydrogen on an iridium complex. Therefore, the availability of such a catalytic complex to a broader community is an absolutely vital step for dissemination of the groundbreaking SABRE methodology. The most common SABRE catalyst, which is activated in situ, is based on Ir-IMes system (IMes = 1,3-Bis(2,4,6-trimethylphenyl)imidazol-2-ylidene). Earlier approaches for the synthesis of this catalyst often relied on specialized equipment and were limited to a comparatively small scale. This, in turn, increased the barrier of entry for new scientists to the area of SABRE hyperpolarization. Here, we present a robust, inexpensive, and easy to reproduce synthetic procedure for the preparation of this SABRE catalyst, which does not require specialized inert atmosphere equipment like a glove box or Schlenk line. The synthesis was validated on the scale of several grams vs. tens of milligrams scale in the reported approaches. The resulting SABRE catalyst, [Ir(IMes)(COD)Cl], was activated in situ and further evaluated in hyperpolarization experiments resulting in signal enhancements comparable to (or higher than) those for the catalyst prepared using Schlenk line equipment.

3D-speckle tracking echocardiography(3D-STE) allows simultaneous assessment of ejection fraction(EF) and multidirectional strains, but its prognostic utility in the general population is unknown. We investigated if 3D-STE strains predicted a composite of major cardiac endpoints(MACE) beyond cardiovascular risk factors(CVDRF), and whether they were superior to 3D-EF. 529 participants in SABRE, a UK-based tri-ethnic general population cohort (69±6y; 76.6% male) with acceptable 3D-STE imaging were studied. Associations between 3D-EF or multidirectional myocardial strains and MACE(coronary heart disease(fatal/non-fatal), heart failure hospitalization, new-onset arrhythmia and cardiovascular mortality) were determined using Cox regression including adjustment for CVDRF and 2D-EF. Whether 3D-EF, global longitudinal strain(3D-GLS) and principle tangential strain(3D-PTS/3D-strain) improved cardiovascular risk stratification over CVDRF was investigated using a likelihood ratio test on a series of nested Cox proportional hazards models and Harrell's C statistics. During follow-up(median, 12y), there were 92 events. 3D-EF, 3D-GLS and 3D-PTS and 3D-RS were associated with MACE in unadjusted and models adjusted for CVDRF but not CVDRF+2D-EF. Compared to 3D-EF, both 3D-GLS and 3D-PTS slightly improved the predictive value over CVDRF for MACE, but the improvement was modest(C statistic increased from 0.698(0.647, 0.749) to 0.715(0.663, 0.766) comparing CVDRF with CVDRF +3D-GLS). 3D-STE-derived LV myocardial strains predicted MACE in a multi-ethnic general population sample of elderly individuals from the UK; however the added prognostic value of 3D-STE myocardial strains was small.