Collusion-free for Cloud Verification toward the View of Game Theory

At present, clients can outsource lots of complex and abundant computation, e.g., Internet of things (IoT), tasks to clouds by the “pay as you go” model. Outsourcing computation can save costs for clients and fully utilize the existing cloud infrastructures. However, it is hard for clients to trust the clouds even if blockchain is used as the trusted platform. In this article, we utilize the verification method as SETI@home by only two rational clouds, who hope to maximize their utilities. Utilities are defined as the incomes of clouds when they provide computation results to clients. More specifically, one client outsources two jobs to two clouds and each job contains n tasks, which include k identical sentinels. Two clouds can either honestly compute each task or collude on the identical sentinel tasks by agreeing on random values. If the results of identical sentinels are identical, then client regards the jobs as correctly computed without verification. Obviously, rational clouds have incentives to deviate by collusion and provide identical random results for a higher income. We discuss how to prevent collusion by using deposits, e.g., bit-coins. Furthermore, utilities for each cloud can be automatically assigned by a smart contract. We prove that, given proper parameters, two rational clouds will honestly send correct results to the client without collusion.

A Vibration Similarity Model of Converter Transformers and Its Verification Method

According to the vibration characteristics of converter transformers, considering the Maxwell equation, magnetostrictive effect, Lorentz force and structural mechanics, the similarity criterion suitable for converter transformers is deduced in this paper. Using the finite element simulation platform, the multi physical field coupling model of converter transformers is constructed, and the scale coefficient is 0.1. The magnetic flux density distribution, stress distribution, shape variable and vibration characteristics of the model before and after the similarity are analyzed. The results show that the variation law of the model before and after the similarity conforms to the similarity criterion, and the correctness of the similarity criterion is verified. The converter transformer vibration similarity model and its verification method can effectively reduce the unnecessary waste of resources before the preparation of converter transformers and have important reference value for the analysis and improvement of converter transformer vibration characteristics.

Dark Matter - Are They Insulators to Electromagnetic Radiation?

The detection of Dark Matter is the greatest outstanding problem in modern cosmology. Several attempts have been taken for this without any remarkable success. To find out a suitable way of detection we need to understand its nature comprehensively. In the present article, a hypothesis is described considering Dark Matter as a normal matter. Its peculiar behavior is explained considering its existence in BEC state in the coolest part of the universe that makes it an electromagnetic insulator. Depending upon this hypothesis an experimental verification method is proposed.

The Role of Theory of Truth in Countering Hoaxes Regarding Covid-19

Indonesia is one of the countries experiencing the COVID-19 pandemic. This causes anxiety for the Indonesian people which makes information about COVID-19 becomes crucial. Objective: This research was conducted with the aim of studying philosophical theories that can play a role in the process of testing information in warding off hoaxes about COVID-19. Researchers want to know whether the theory of philosophy of science can be of assistance to the public in recognizing and rejecting hoax news about COVID-19. Methods: The research was conducted using a descriptive verification method with a qualitative approach. The data from this study were taken from interviews and secondary data was taken by studying the literature. Interview data were taken with the target respondents, namely people in Surabaya with an age range of 25-40 years or what is often referred to as generation Y or millennials. The criteria for determining the number of respondents were taken until the researcher found a saturated sample. Meanwhile, the literature study data consists of 2 books, 37 articles, 1 website, and 1 report on the results of a national survey. Results: This study found 5 types of theory of truth, namely coherence theory, correspondence theory, pragmatic theory, consensus theory, and performative theory, each of which has a use in identifying hoaxes around COVID-19. Research Recommendation: Further research needs to be conducted which can test the actual practice of applying truth theories in countering hoaxes in the community at a certain scale. Limitations: This research has little chance of being applied by some Indonesians, given their low level of digital literacy and willingness to seek information.

Probabilistic Forecast of the Extended Range Heatwave Over Eastern China

Several probabilistic forecast methods for heatwave (HW) in extended-range scales over China are constructed using four models (ECMWF, CMA, UKMO, and NCEP) from the Subseasonal-to-Seasonal (S2S) database. The methods include four single-model ensembles (SME; ECMWF, CMA, UKMO, and NCEP), multi-model ensemble (MME), and Bayesian model averaging (BMA). The construction and verification of reforecasts are implemented by a defined heat wave index (HWI) which is not only able to reflect the actual occurrence of heatwaves, but also to facilitate forecast and verification. The performance is measured by traditional verification method at each grid point of the 105°E to 132°E; 20°N to 45°N domain for the July, August, and September (JAS) of 1999–2010. For deterministic evaluations of HWI forecast, BMA shows a better pattern correlation coefficient than SME and MME and comparable equitable threat score (ETS) with ECMWF and MME. The good performance of ECMWF and MME take advantage of setting the percentile thresholds for forecasting HW. For the probabilistic forecast, the Brier score of BMA is comparable (superior) to that of MME and ECMWF at short (long) lead-time. BMA also demonstrates an improvement on the reliability of probabilistic forecast, indicating that BMA method is a useful tool for an extended-range forecast of HW. Meanwhile, in the real-time extended-range probabilistic forecast, the beginning date, end date, and probability of HW event can be predicted by the HWI probabilistic forecast of BMA.

Knowledge Verification Method Based on Artificial Intelligence-based Knowledge Graph Construction

The knowledge graph connects real-world entities and concepts through their relationships, connects all different types of information to obtain a relationship network, and can analyze “relationship” issues. Creating a knowledge graph is a continuous process, and it needs to continuously learn new knowledge and update existing knowledge in the library as time and events change. However, since the accuracy of the updated new knowledge cannot be guaranteed, the new knowledge must be verified. This paper aims to study the knowledge verification method based on artificial intelligence-based knowledge graph construction. Based on the analysis of the knowledge graph construction process, the knowledge graph construction method and the knowledge verification method, knowledge verification is realized by constructing a probabilistic soft logic model. The experimental results show that the recall rate, F1 value, and AUC value of the candidate knowledge set are verified by the knowledge verification model proposed in this paper. Therefore, it can be inferred that the knowledge verification model proposed in this paper is effective.

‘Alaqat Dilaliyyah baina Alfaz al-Ruh wa al-Nafs wa al-Qalb fi al-Qur’an al-Karim

This research aims to know the verses of using the terms spirit, soul, and heart in the Holy Quran, knowing its lexical and contextual meanings, knowing the relationship of its significance, and knowing the educational inclusion of its significance. This research is based on thinking that the words in the Qur'an have a semantic and contextual relationship and the educational inclusion of the meanings of the words soul, soul and heart in it depends on the science of Islamic education. As for the method used in this research, it is the method for analyzing the content with a semantic analysis, whereby the research is directed to analyzing the meanings of words. As for the entry in this research, it is the qualitative entry. By not researching the writer, we obtained the results from it. In the verses that contain the words of the soul, the soul, the heart and the like there are many, and each of its words has different meanings. The writers found the educational inclusion of the use of the words of soul, soul and title, which includes a method of Islamic education, which is the method of abandonment, sweetening, manifestation and the method of attachment, creation, verification, method of worship and the method of supplication, remembrance.

THE IMPACT OF DIVIDEND POLICY AND CAPITAL STRUCTURE ON FIRM VALUE IN AGRICULTURAL SECTOR

This study aims to determine the effect of Dividend Policy and Capital Structure on Agricultural Sector’s Company Value. The research method used in this study is verification method with quantitative approach. The case study was conducted on agricultural sector companies listed on the Indonesia Stock Exchange in 2015-2019. The sample used is Price Book Value (PBV) and Debt to Equity Ratio (DER) in 14 agricultural sector companies obtained from Financial Statements published on the Indonesia Stock Exchange website: www.idx.co.id for the period 2015-2019. The results showed that the variables of Dividend Policy and Capital Structure had a negative and not significant effect on company value.

A Conceptual Framework Proposal for a Noise Modelling Service for Drones in U-Space Architecture

In recent years, there has been a rapid growth in the development and usage of flying drones due to their diverse capabilities worldwide. Public and private sectors will actively use drone technology in the logistics of goods and transporting passengers in the future. There are concerns regarding privacy and noise exposure in and around the rural and urban environment with the rapid expansion. Further, drone noise could affect human health. European Union has defined a service-orientated architecture to provide air traffic management for drones, called U-space. However, it lacks a noise modelling service (NMS). This paper proposes a conceptual framework for such a noise modelling service for drones with a use case scenario and verification method. The framework is conceptualized based on noise modelling from the aviation sector. The NMS can be used to model the noise to understand the accepted drone noise levels in different scenarios and take measures needed to reduce the noise impact on the community.

Automatic verification method of progressive image model matching information based on machine learning

In order to solve the problems of large error and low performance of traditional progressive image model matching information checking methods, an automatic progressive image model matching information checking method based on machine learning is proposed. The generation method of progressive image is analyzed, and the target image sample is obtained. On this basis, machine learning algorithm is used to segment progressive image samples. In each image segmentation part, crawler technology is used to automatically collect progressive image model matching information, and under the constraint of image model matching information checking standard, automatic checking of progressive image model matching information is realized from geometric structure, image content and other aspects. Experimental results show that the verification error of the design method is reduced by 0.687 Mb, and the quality of progressive image is improved.