Doubly Robust Crowdsourcing

Large-scale labeled dataset is the indispensable fuel that ignites the AI revolution as we see today. Most such datasets are constructed using crowdsourcing services such as Amazon Mechanical Turk which provides noisy labels from non-experts at a fair price. The sheer size of such datasets mandates that it is only feasible to collect a few labels per data point. We formulate the problem of test-time label aggregation as a statistical estimation problem of inferring the expected voting score. By imitating workers with supervised learners and using them in a doubly robust estimation framework, we prove that the variance of estimation can be substantially reduced, even if the learner is a poor approximation. Synthetic and real-world experiments show that by combining the doubly robust approach with adaptive worker/item selection rules, we often need much lower label cost to achieve nearly the same accuracy as in the ideal world where all workers label all data points.

Effect of Regulation on the Increasing Price of Metals and Minerals to Meet the Challenges in Clean Energy Transitions: A Case Study of China

Considering that the development of science and technology depends on metal support, the EU, USA, and China have issued a critical metal list on the development report. However, the scarce and important mineral deposits on a global scale will not be enough to meet the huge needs of economic development in the future. Many fields such as renewable energy, high-performance computing, and AI all require critical metals as essential supports. A proper price regulation of such important metals will contribute to the fair price power on the international market. In this paper, the pricing history and strategy of critical metal support are fully studied and discussed. Since China has become a major consumer country, China should gain fair price power in the market of important metals.

Sukuk Performance Using Comparison of Return and Risk Through Calculation of Market Price and Fair Price

Sukuk investors’ important information used by investors of Sukuk (proof or claim of ownership on assets) is the market price of the Sukuk issued by the IDX and the fair price of the Sukuk issued by the Indonesian Securities Price Appraiser (PHEI). This is a signal or initial information for investors in considering the decision to invest in Sukuk. The measured performance returns as measured by Holding Period Yield (HPY), Yield To Maturity (YTM), and Sharpe Index, while Risk of Sukuk is measured based on its standard deviation. Corporate Sukuk are classified into financial and non-financial sectors and have short, medium, and long maturities. Comparative analysis is conducted using an Independent Sample t-test and ANOVA. The results showed that the average Sukuk return was calculated at a higher market price than the fair price. Sukuk return results in a pattern of movement that tends to be inversely proportional to the market price or fair price of the Sukuk, while the risk of Sukuk based on price issuing institutions had a movement pattern that tends to be in the same direction as the price. Furthermore, corporate Sukuk in the non-financial sector had a higher average return but was more susceptible to risk than the financial sector. Corporate Sukuk with long maturities had a higher average yield and risk exposure than medium and short-term Sukuk. Hypothesis testing showed a significant difference between the market price and the fair price of corporate Sukuk.

The Empirical Model on The Relationship among Price, Service Quality and Customer Purchasing Decision: The Case of the Dili Tais Market in Timor-Leste.

Price, service quality and purchasing decisions are played important roles in tourism market management. Therefore, many empirical studies have been carried out to enhance customer purchasing decisions through price and service quality. Nonetheless, there is a limited number of studies in emerging tourism destinations and marketing. This study aims to analyse the influence of price and service quality on customers’ purchasing decisions. This research was carried out at the Tais Market, Kolmera, Dili. Data was collected by using questionnaires distributed to 395 respondents using accidental sampling technique, and hypotheses were tested using SMART-PLS 3.0. The results showed that both price and service quality have significant impacts on customers’ purchasing decisions. This study enriches the empirical studies on price, service quality and customers’ purchasing decisions, particularly in emerging tourism destinations and markets. This study implies that to enhance customers’ purchasing decisions, the Tais Market needs to offer products at a reasonable and fair price as well to keep improving the tangible and intangible services.

Social Media Analysis to Understand the Expected Benefits by Plant-Based Meat Alternatives Consumers

The plant-based alternative meat products market has attracted attention in recent years, as the demand for these products has grown worldwide. To meet the needs of this promising market, marketers must pay attention to the expected benefits of consumers and the insights that can be gleaned from comments posted on social media. This article proposed an investigation of the potential of the content analysis of comments posted on the Instagram social network of food companies that manufacture plant-based alternative meat products to understand the expected benefits by end consumers from the perspective of the classic marketing mix variables. The content posted voluntarily by consumers was organized into 13 categories of expected benefits analyzed within a proposal of evidence from the perspective of the marketing mix. The results showed that, among the insights obtained, 63% were related to the place variable, 21% to the product variable, 11% to the price variable, and 5% to the promotion variable. The insights reinforce the notion that marketing mix variables are crucial factors for companies to make products available in the right place, in the right quantity, and at a fair price, in addition to engaging with consumers through social media.

Non-Arbitrage Models of Financial Markets

In the first part of the paper, we construct the models of the complete non-arbitrage financial markets for a wide class of evolutions of risky assets.This construction is based on the observation that for a certain class of risky as set evolutions the martingale measure is invariant with respect to these evolutions. For such a financial market model the only martingale measure being equivalent to an initial measure is built. On such a financial market,formulas for the fair price of contingent liabilities are presented. A multi-parameter model of the financial market is proposed, the martingale measure of which does not depend on the parameters of the model of the evolution of risky assets and is the only one.

Entering a medical clinic on the stock exchange: reflection in accounting and reporting

Medicine in modern Russia is as profitable business as any other. Of course, we are talking about private medicine. Therefore, medical organizations need to be able to plan their income and expenses, as well as be able to manage them. Many Russian private medical organizations adopt foreign experience, transferring to the “medical soil” the idea of “effective management”, which consists in the ability to increase revenues, reduce costs, and generate such a volume of profit that suits the shareholders. According to the market law of capital flow, shareholders who own shares of companies in one industry sell these shares (at the time when this can be done with the maximum possible profit) and acquire shares of companies in another industry that are more attractive for investors. It is possible to sell shares “from hand to hand” — from the previous owner to a new one, but the transaction in this case is carried out at a negotiated price that will not meet the criteria of the so-called fair price. A completely different matter is the sale of shares on an exchange, an observable (transparent) market. The transaction is reflected in the accounting and reporting, the only question is whether the profit from the transaction is reflected on the balance sheet of the medical organization in respect of the shares of which the transaction is being made.

Price Prediction for Pre-Owned Cars Using Ensemble Machine Learning Techniques

The Pre-owned cars or so-called used cars have capacious markets across the globe. Before acquiring a used car, the buyer should be able to decide whether the price affixed for the car is genuine. Several facets including mileage, year, model, make, run and many more are needed to be considered before getting a hold of any pre-owned car. Both the seller and the buyer should have a fair deal. This paper presents a system that has been implemented to predict a fair price for any pre-owned car. The system works well to anticipate the price of used cars for the Mumbai region. Ensemble techniques in machine learning namely Random Forest Algorithm, eXtreme Gradient Boost are deployed to develop models that can predict an appropriate price for the used cars. The techniques are compared so as to determine an optimal one. Both the methods provided comparable performance wherein eXtreme Boost outperformed the random forest algorithm. Root Mean Squared Error of random forest recorded 3.44 whereas eXtreme Boost displayed 0.53.

Blockchain and Internet of Things for Electrical Energy Decentralization: A Review and System Architecture

The decentralization in the electrical power grids has gained increasing importance, especially in the last two decades, since transmission system operators (TSO), distribution system operators (DSO) and consumers are more aware of energy efficiency and energy sustainability issues. Therefore, globally, due to the introduction of energy production technologies near the consumers, in residential and industrial sectors, new scenarios of distributed energy resources (DER) are emerging. In order to guarantee an adequate power management in the electrical power grids, incorporating producers, consumers and producers-consumers (prosumers) together, it is important to adopt intelligent systems and platforms that allow the provision of information on energy consumption and production in real time, as well as for obtaining a fair price for the sale and purchase of energy. In this paper, we analyze the literature to identify the appropriate solutions to implement a decentralized electrical power grid based on sensors, blockchain and smart contracts, evaluating the current state of the art and pilot projects already in place. We also discuss a proposal for a power grid model, with renewable energy production, combining Internet of Things, blockchain and smart contracts.

Flow. A Socially Responsible 3D Printed One-Handed Recorder

The recorder is one of the most common instruments used during primary school in the formal education system in the EU. However, there are a percentage of students with only one functional hand. The existing one-handed recorders available for them to be able to play and perform in the same way as their peers are expensive and difficult to use. This study’s purpose is to document the development of Flow—a low cost one-handed recorder as well as the user’s assessment of the psychosocial benefits of the recorder. The methods used for fabrication were 3D modelling and additive manufacturing (AM) technology or 3D printing using the technique of stereolithography, and for the assessment of the product, the Psychosocial Impact of Assistive Devices Scale (PIADS) questionnaire was distributed to 20 primary school users. The results show that the use of resins and Stereolithography is appropriate for wind instruments providing quality and strength at a fair price. Flow also proved to have a positive impact on the users and their inclusion in school. The main conclusions of this study underscore the adequacy of using AM for adaptations required for people with disabilities and the positive psychosocial benefits generated by the use of Flow in children.