Oil price volatility and new evidence from news and Twitter

In this paper, we develop semantic-based sentiment indices through relevant news and Twitter feeds for oil market using a state-of-the-art natural language processing technique. We investigate the predictability of crude oil price volatility using the novel sentiment indices through a hybrid structure consisting of generalized autoregressive conditional heteroskedasticity and bidirectional long short-term memory models. Findings show that media sentiment considerably enhances forecasting quality and the proposed framework outperforms existing benchmark models. More importantly, we compare the predictive power of news stories with Twitter feeds and document the superiority of the news sentiment index over the counterpart. This is an important contribution as this paper is the first study that compares the impact of regular press with that of social media, as an alternative informative medium, on oil market dynamics

Social commerce constructs and consumers' purchase intention from minimalist brands

The social media and online communities have established new platforms for e-commerce by engaging both consumers and corporations in producing new product or services. Moreover, individuals' interaction on the cyberspace has evolved e-commerce towards social commerce. On the other hand, business incorporations have found the use of minimalism application in designing, which removes unnecessary aspects, attracts more audience. Therefore, drawing on literature the authors propound a new adopted model to portray a more transparent vision of social commerce. To examine the relationships among the model constructs, an empirical study was organised for this purpose; a survey was designed. In doing so, structural equation modelling (SEM) methodology has been used with Smart PLS 3 software in order to confirm or reject assumptions in the present study and is employed to gauge the proposed model

An efficacious method to assemble a modern multi-modal robotic team: dilemmas, challenges, possibilities and solutions

A modern multiagent robotic platform consists of a cooperative team of humans which develop a collaborative team of robots. The multi-modal nature of both the system and the team causes a complex problem which needs to be solved for optimum performance. Both the management and the technical aspect of a modern robotic team are explored in this Chapter in the platform of the RoboCup Competition. RoboCup is an example of such an environment where researchers from different disciplines join to develop a robotic team for completion as an evaluation challenge (Robocup, 2011). RoboCup competitions were first proposed by Mackworth in 1993. The main goal of this scientific competition is to exploit, improve and integrate the methods and techniques from robotics, machine vision and artificial intelligence disciplines to create an autonomous team of soccer playing robots(Kitano, 1997a; Kitano, 1997b; Kitano et al., 1997). Such experiment includes several challenges, from inviting an expert of specific field to the team to choosing bolts and nuts for each part of the robots. Usually each challenge has several possible solutions and choosing the best one is often challenging. We have participated in several world wide RoboCup competitions (Abdollahi, Samani et al. 2002, 2003 & 2004) and share our experience as an extensive instruction for setting up a modern robotic team including management and technical issues.Peer ReviewedPostprint (published version

Laser Application in Prevention of Demineralization in Orthodontic Treatment

One common negative side effect of orthodontic treatment with fixed appliances is the development of incipient caries lesions around brackets, particularly in patients with poor oral hygiene. Different methods have been used to prevent demineralization such as fluoride therapy and application of sealant to prevent caries. The recent effort to improve the resistance against the demineralization is by the application of different types of lasers. The purpose of this review article is discussing the effects of laser in prevention of demineralizationin orthodontic patients

The Effect of Investor Sentiment on Betting Against Beta: A SEM Approach Towards Beta Anomaly

Beta anomaly is one of the greatest anomalies in finance literature as CAPM conveys a positive relationship between the beta of a stock and future returns; however, empirical studies do not document this proposition. Branded as betting against beta, this conundrum is known as a controversial subject. Drawing on literature the authors propose new multi-factor models to develop our understanding of betting against beta using investor sentiment as well as Structural Equation Modeling methodology to gauge the models in the presence of the top-down approach. Results indicate that investor sentiment provides a good explanation of the betting against beta. Limitation and future research directions are presented at the end of paper. Keywords: Behavioral finance, Investor sentiment, BAB factor JEL Classifications: G02, G1

Co-optimized bidding strategy of an integrated wind-thermal-photovoltaic system in deregulated electricity market under uncertainties

Clean Energy sources, such as wind and solar, have become an inseparable part of today's power grids. However, the intermittent nature of these sources has become the greatest challenge for their owners, which makes the bidding in the restructured electricity market more challenging. Hence, the main goal of this paper is to propose a novel multi-objective bidding strategy framework for a wind-thermal-photovoltaic system in the deregulated electricity market for the first time. Contrary to the existing bidding models, in the proposed model, two objective functions are taken into account that the first one copes with profit maximization while the second objective function concerns with emission minimization of thermal units. The proposed multi-objective optimization problem is solved using the weighted sum approach. The uncertainties associated with electricity market prices and the output power of renewable energy sources are characterized by a set of scenarios. Ultimately, in order to select the best-compromised solution among the obtained Pareto optimal solutions, two diverse approaches are applied. The proposed bidding strategy problem is being formulated and examined in various modes of joint and disjoint operation of dispatchable and non-dispatchable energy sources. Simulation results illustrate that not only the integrated participation of these resources increases the producer's expected profit, but also decreases the amount of the produced pollution by the thermal units.© 2019 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

Investigating Energy Use, Environment Pollution, and Economic Growth in Developing Countries

Attaining continuous economic growth entails special consideration of energy sector and the environment. Compliance with this purpose may be more intricate in the uncertain milieu of developing countries. The present paper examines the nature of causality between energy consumption, environment pollution, and economic growth in 8 contiguous developing countries, considering GDP per capita, CO2 emissions, energy use, labour force, total population, urban population, capital formation, financial development, and trade openness. The author applied spatial simultaneous equations for random effects panel data to investigate the spatial interactions of adjacent countries over the period from 1998 to 2011. The findings reveal that energy consumption, environment degradation, and economic growth of a country influence those of its neighbours. Additionally, the results document bidirectional causal relationship between economic growth and environment pollution, as well as between environment pollution and energy consumption. Thus, there is a bidirectional relationship between energy use and economic growth. Fossil fuels replacement with renewable energy and usage of tax instruments to reduce greenhouse gas are recommended

An efficacious method to assemble a modern multi-modal robotic team: dilemmas, challenges, possibilities and solutions

A modern multiagent robotic platform consists of a cooperative team of humans which develop a collaborative team of robots. The multi-modal nature of both the system and the team causes a complex problem which needs to be solved for optimum performance. Both the management and the technical aspect of a modern robotic team are explored in this Chapter in the platform of the RoboCup Competition. RoboCup is an example of such an environment where researchers from different disciplines join to develop a robotic team for completion as an evaluation challenge (Robocup, 2011). RoboCup competitions were first proposed by Mackworth in 1993. The main goal of this scientific competition is to exploit, improve and integrate the methods and techniques from robotics, machine vision and artificial intelligence disciplines to create an autonomous team of soccer playing robots(Kitano, 1997a; Kitano, 1997b; Kitano et al., 1997). Such experiment includes several challenges, from inviting an expert of specific field to the team to choosing bolts and nuts for each part of the robots. Usually each challenge has several possible solutions and choosing the best one is often challenging. We have participated in several world wide RoboCup competitions (Abdollahi, Samani et al. 2002, 2003 & 2004) and share our experience as an extensive instruction for setting up a modern robotic team including management and technical issues.Peer Reviewe