The Effectiveness of Dynamically Processed Incremental Descriptions in Human Robot Interaction

We explore the effectiveness of a dynamically processed incremental referring description system using under-specified ambiguous descriptions that are then built upon using linguistic repair statements, which we refer to as a dynamic system. We build a dynamically processed incremental referring description generation system that is able to provide contextual navigational statements to describe an object in a potential real-world situation of nuclear waste sorting and maintenance. In a study of 31 participants, we test the dynamic system in a case where a user is remote operating a robot to sort nuclear waste, with the robot assisting them in identifying the correct barrels to be removed. We compare these against a static non-ambiguous description given in the same scenario. As well as looking at efficiency with time and distance measurements, we also look at user preference. Results show that our dynamic system was a much more efficient method—taking only 62% of the time on average—for finding the correct barrel. Participants also favoured our dynamic system.

CLIMATE JUSTICE: BALANCING THE RIGHT TO DEVELOP AND THE NORM OF SUSTAINABILITY

<p>Climate change presents a global problem that requires collective action. Distributing obligations in relation to this has proven problematic, especially in light of the divide between wealthy and developed states compared to poor and developing states. The norm of sustainability requires states to continue to protect and promote sustainable actions. This comes into direct conflict with the right to develop when considering how to mitigate climate change. The right to develop requires the use of limited resources now, whereas the norm of sustainability argues that these resources must be protected for both environmental protection and intergenerational justice. Intragenerational justice requires us to consider whether actions that protect the future may be causing greater injustice within the present generation. In this thesis, I discuss the important potential distribution principles, with considerations of historic responsibility, uncertainty, and the ability to pay principles. I then use this foundation to explore how a right to develop can fit within the balance of intergenerational and intragenerational justice. I also include the context of non-ideal theory as a means of making the discussion more relevant to the real-world situation we find ourselves in, with the partial and non-compliance of many states. I conclude that, within the context of non-ideal theory, there is a right to develop but currently it ought to be limited to a basic needs threshold if we wish to justly distribute obligations between and across generations.</p>

CLIMATE JUSTICE: BALANCING THE RIGHT TO DEVELOP AND THE NORM OF SUSTAINABILITY

<p>Climate change presents a global problem that requires collective action. Distributing obligations in relation to this has proven problematic, especially in light of the divide between wealthy and developed states compared to poor and developing states. The norm of sustainability requires states to continue to protect and promote sustainable actions. This comes into direct conflict with the right to develop when considering how to mitigate climate change. The right to develop requires the use of limited resources now, whereas the norm of sustainability argues that these resources must be protected for both environmental protection and intergenerational justice. Intragenerational justice requires us to consider whether actions that protect the future may be causing greater injustice within the present generation. In this thesis, I discuss the important potential distribution principles, with considerations of historic responsibility, uncertainty, and the ability to pay principles. I then use this foundation to explore how a right to develop can fit within the balance of intergenerational and intragenerational justice. I also include the context of non-ideal theory as a means of making the discussion more relevant to the real-world situation we find ourselves in, with the partial and non-compliance of many states. I conclude that, within the context of non-ideal theory, there is a right to develop but currently it ought to be limited to a basic needs threshold if we wish to justly distribute obligations between and across generations.</p>

Optimizing Non-Pharmaceutical Intervention Strategies Against COVID-19 Using Artificial Intelligence

One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it became possible to model both the infection trends and intervention costs, transforming the creation of an intervention plan into a computational optimization problem. This paper proposes a framework developed to help policy-makers plan the best combination of non-pharmaceutical interventions and to change them over time. We developed a hybrid machine-learning epidemiological model to forecast the infection trends, aggregated the socio-economic costs from literature and expert knowledge, and used a multi-objective optimization algorithm to find and evaluate various intervention plans. The framework is modular and easily adjustable to a real-world situation, it is trained and tested with data collected from almost all countries of the world, and its proposed intervention plans generally outperform those used in real life in terms of both the number of infections and intervention costs.

How is economic growth correlated to index growth?

This study will mainly focus on the relation between GDP growth and stock market index growth through various methods like the Pearson product-moment coefficient correlation, comparing the theoretical world to the real-world situation, and finally by looking at consumer sentiments and confidence. This could help various analysts, economists, and even the general public. Through the course of our study, we find out various trends in this study, at some point, the results were contradicting themselves but then our last test made it all clear, which proves that there is no correlation between GDP growth and stock market index growth, but then both of them drives from consumer confidence and consumers future actions.

EMERGING ISSUES IN EDUCATIONAL MEASUREMENT: AUTHENTIC ASSESSMENT

Authentic assessment is a tool of evaluating students learning applicable to real world situation. It is unavoidable tools for modern assessment of learning outcomes. It can be apply as formative or summative assessments or for both assessment types. This paper attempted to examined the concept of assessment and its types, the concept of authentic assessment and its categories, the forms of authentic assessment, the tools used for authentic assessment, methods used in authentic assessment, steps involved in authentic assessment, advantages of authentic assessment, challenges of authentic assessment among others. The paper concludes that it is a high time for authentic assessment to replace traditional methods of assessment in all level of learning. The paper also recommended that the Curriculum Planners should design a curriculum based on types of authentic assessment for all levels of learning, the application of authentic assessment at all levels of learning, time has comes to move from traditional method of assessment to authentic assessment form and required competencies must be possessed by the teacher in order to carry out authentic assessments through proper training.

CONSTRAINTS TO EFFECTIVE CONTINUOUS PROFESSIONAL DEVELOPMENT OF TEACHERS IN GOVERNMENT SECONDARY SCHOOL IN FCT

Authentic assessment is a tool of evaluating students learning applicable to real world situation. It is unavoidable tools for modern assessment of learning outcomes. It can be apply as formative or summative assessments or for both assessment types. This paper attempted to examined the concept of assessment and its types, the concept of authentic assessment and its categories, the forms of authentic assessment, the tools used for authentic assessment, methods used in authentic assessment, steps involved in authentic assessment, advantages of authentic assessment, challenges of authentic assessment among others. The paper concludes that it is a high time for authentic assessment to replace traditional methods of assessment in all level of learning. The paper also recommended that the Curriculum Planners should design a curriculum based on types of authentic assessment for all levels of learning, the application of authentic assessment at all levels of learning, time has comes to move from traditional method of assessment to authentic assessment form and required competencies must be possessed by the teacher in order to carry out authentic assessments through proper training

Saying and shaking ˋNo'

In many instances, the head shake can be used instead of or in addition to verbal ˋNo'. Based on previous work on negation in dialogue, we observe head shaking as answer particles and as responding to an implicit or an exophoric (i.e., real world situation) antecedent. Exophoric head shake, however, seems to come in two flavours: with positive and with negative emotional valuation of the antecedent situation. We provide semantic analyses for all three uses (and a head nod) within an HPSG version which is implemented in Type Theory with Records and the dialogue framewok KoS. In particular, we extend on previous work by grounding ˋˋexophoric negation'' in positive or negative appraisal. Finally, we briefly speculate about differences between verbal ˋNo' and head shaking due to (the lack of) simultaneity.

A New Approach to Predicting Cryptocurrency Returns Based on the Gold Prices with Support Vector Machines during the COVID-19 Pandemic Using Sensor-Related Data

In a real-world situation produced under COVID-19 scenarios, predicting cryptocurrency returns accurately can be challenging. Such a prediction may be helpful to the daily economic and financial market. Unlike forecasting the cryptocurrency returns, we propose a new approach to predict whether the return classification would be in the first, second, third quartile, or any quantile of the gold price the next day. In this paper, we employ the support vector machine (SVM) algorithm for exploring the predictability of financial returns for the six major digital currencies selected from the list of top ten cryptocurrencies based on data collected through sensors. These currencies are Binance Coin, Bitcoin, Cardano, Dogecoin, Ethereum, and Ripple. Our study considers the pre-COVID-19 and ongoing COVID-19 periods. An algorithm that allows updated data analysis, based on the use of a sensor in the database, is also proposed. The results show strong evidence that the SVM is a robust technique for devising profitable trading strategies and can provide accurate results before and during the current pandemic. Our findings may be helpful for different stakeholders in understanding the cryptocurrency dynamics and in making better investment decisions, especially under adverse conditions and during times of uncertain environments such as in the COVID-19 pandemic.