Real-Time Wireless Sensor Network-Assisted Smart Tourism Environment Suitability Assessment for Tourism IoT

In this paper, we conduct an in-depth study and analysis of the suitability of real-time wireless sensor network-assisted smart tourism environment for tourism IoT and evaluate its suitability. We use nodes in wireless sensor networks as relays and collaborative transmission using mutual information accumulation. Using riteless codes, nodes can accumulate information in advance to decode out the original text. Due to the mobility of mobile robots, the planned routing paths can fail quickly, so we propose a dynamic mutual information accumulation collaborative transmission algorithm. For both cases of information transmission from the cloud to the robot and from the robot to the cloud, we dynamically acquire routing paths using neighbour search and chance transmission, respectively. Experimental results show that our dynamic mutual information accumulation collaborative transfer algorithm has lower time complexity and latency. We use a cooperative transmission algorithm with mutual information accumulation, because wireless transmission has the nature of broadcasting, and all neighbour nodes can receive part of the information when the sender starts to transmit information. Riteless codes are used in single-hop transmissions to improve the probability of successful transmissions. Since transmission failure requires waiting for the next neighbour to wake up, which consumes a lot of energy and time in a low duty cycle environment, using riteless codes to improve the transmission success rate of single-hop transmissions can effectively improve the global transmission efficiency. Experimental results show that the opportunity routing algorithm using riteless codes has lower delay and energy consumption. The two major systems, surface, and underground are used to quantitatively measure 23 indicators in five subsystems, including geological environment, soil and water environment, sensitive geological bodies, groundwater resources, and mineral resources, to evaluate the two-way grade of underground space development suitability, revealing the comprehensive bearing characteristics of the study area with an overall high bearing capacity of underground space resources and environment and an overall surplus of bearing status.

A Randomness Perspective on Intelligence Processes

We study intelligence processes using a diffusion IRT model with random variability in cognitive model parameters: variability in drift rate (the trend of information accumulation toward a correct or incorrect response) and variability in starting point (from where the information accumulation starts). The random variation concerns randomness across person-item pairs and cannot be accounted for by individual and inter-item differences. Interestingly, the models explain the conditional dependencies between response accuracy and response time that are found in previous studies on cognitive ability tests, leading us to the formulation of a randomness perspective on intelligence processes. For an empirical test, we have analyzed verbal analogies data and matrix reasoning data using diffusion IRT models with different variability assumptions. The results indicate that 1) models with random variability fit better than models without, with implications for the conditional dependencies in both types of tasks; 2) for verbal analogies, random variation in drift rate seems to exist, which can be explained by person-by-item word knowledge differences; and 3) for both types of tasks, the starting point variation was also established, in line with the inductive nature of the tasks, requiring a sequential hypothesis testing process. Finally, the correlation of individual differences in drift rate and SAT suggests a meta-strategic choice of respondents to focus on accuracy rather than speed when they have a higher cognitive capacity and when the task is one for which investing in time pays off. This seems primarily the case for matrix reasoning and less so for verbal analogies.

Social Elements of Agri-Expo Strategies Because of Momentary Fluctuation in Key Family and Network Prosperity Measures in Bangladesh and Pakistan

High-return social information accumulation can encourage improved review, progressively comprehensive detailing, and improved inconstancy catch over a period. In spite of the fact that there are instances of little investigations that catch explicit high recurrence factors in the sociology writing, there is so far no noteworthy exertion to gather a wide scope of high recurrence factors. We tried our first such endeavors with a deliberately fluctuating cell phone-based information accumulation approach the return of the investigation task and the update time frame, which enables one to dissect the general advantage of high recurrence information gathering for different key factors in family unit overviews. This overview of 482 ranchers from northwesterly Bangladesh for roughly 1 year of persistent information on key examination for family unit and network prosperity can be especially valuable in planning and assessing improvement intercessions and strategies. While the information talked about here give a concise review of what is conceivable, we likewise stress their capacity to give interdisciplinary research in family unit agribusiness, rehearses, regular yearning, and so forth., in a low-salary rural society.

Quantifying and analysing the stages of online information dissemination in different enterprise emergencies: The idea of system cybernetics

Previous research on information dissemination in emergencies focus on prediction of the volume via abundant models. However, most of these models did not specify different stages of emergencies, and hence making it difficult for public relations (PR) practitioner to make decisions based on needs of each stage in today’s rapid changing media environments. In this study, we introduce the idea of system cybernetics and the method of system identification into information dissemination perspective. Based on the proposed information accumulation probability distribution continuity (IAPDC) model, we provide a quantitative division of the information accumulation process. The durations of each stage and the time points that each stage begins are stated and defined with a quantitative calculation method. Using empirical data from 83 emergencies in 2016 and 2017 covering Weibo, WeChat Platforms and over 20,000 web media, we verify the effectiveness of this method. Next, we use simulation analysis to demonstrate what effects of parameters have on the dissemination process and how do changes on different stages affect the process. Moreover, we also demonstrate the effects of emergencies’ attributes on the information dissemination process and on each stage. Our study complements the gaps in existing communication discipline and provides insight for PR practitioner when dealing with enterprise emergencies.