The Inspiration of Bauhaus Principles on the Modern Housing in Cyprus

Modern architecture developed more than a century ago to find solutions suitable to solve the new concerns of the industrial revolution that changed the social idea of the world in all aspects. Bauhaus school which established by Walter Gropius in 1919 adopted too many principles and ideas that were totally new to the architecture concept and theory at that time; their principles started from Simplicity, Angularity, Abstraction, Consistency, Unity, Organization, Economy, Subtlety, Continuity, Regularity, and Sharpness. Those principles affected the architectural world and found its way through many applications in different parts of the world. The unlimited space or the International space that had a significant influence on the architecture space and form as well as the introduction of the new material, the anti- decorating, and Platonic forms had worked to reconstruct the architecture in the world. Cyprus as an Island close to the sources of the movement got the influence from the modern movement. The study will concentrate on Efruz Housing which designed by Ahmet Vural, who developed the project in the 60th of the last century. The aim of the research is to find the relationship and effects of Bauhaus school in Cyprus through studying and analyzing some of Ahmet vural works. The methodology will depend on a comparison with the traditional housing that preceded Mr. Vural work and how the Modernism changed the main features of the housing on the Island

A comprehensive review of plus-minus ratings for evaluating individual players in team sports

The increasing availability of data from sports events has led to many new directions of research, and sports analytics can play a role in making better decisions both within a club and at the level of an individual player. The ability to objectively evaluate individual players in team sports is one aspect that may enable better decision making, but such evaluations are not straightforward to obtain. One class of ratings for individual players in team sports, known as plus-minus ratings, attempt to distribute credit for the performance of a team onto the players of that team. Such ratings have a long history, going back at least to the 1950s, but in recent years research on advanced versions of plus-minus ratings has increased noticeably. This paper presents a comprehensive review of contributions to plusminus ratings in later years, pointing out some key developments and showing the richness of the mathematical models developed. One conclusion is that the literature on plus-minus ratings is quite fragmented, but that awareness of past contributions to the field should allow researchers to focus on some of the many open research questions related to the evaluation of individual players in team sports. Keywords: rating system, ranking, regression, regularizationpublishedVersio

Offensive and defensive plus-minus player ratings for soccer

Rating systems play an important part in professional sports, for example, as a source of entertainment for fans, by influencing decisions regarding tournament seedings, by acting as qualification criteria, or as decision support for bookmakers and gamblers. Creating good ratings at a team level is challenging, but even more so is the task of creating ratings for individual players of a team. This paper considers a plus–minus rating for individual players in soccer, where a mathematical model is used to distribute credit for the performance of a team as a whole onto the individual players appearing for the team. The main aim of the work is to examine whether the individual ratings obtained can be split into offensive and defensive contributions, thereby addressing the lack of defensive metrics for soccer players. As a result, insights are gained into how elements such as the effect of player age, the effect of player dismissals, and the home field advantage can be broken down into offensive and defensive consequences. View Full-Text Keywords: association football, linear regression, regularization, rankingpublishedVersio

State Capacity, Internal Conflict and Democratic Breakdown - A Comparative Study of Mali and Ghana.

The two underdeveloped, West-African states, Mali and Ghana, have been praised for their well-established democratic institutions, and have been said to be good role models when it comes to democracy in an African context. However, Mail experienced a sudden democratic breakdown in 2012, after violent rebellion and a military coup. This puzzle" is what this thesis is about, and to unravel the underlying structures and causes, a qualitative case study is conducted to investigate how variations in state capacity and internal conflict can help explain the difference in outcome in Mali and Ghana. There is a clear pattern showing in Mali, where incapacity on a range of indicators of state capacity, and an unresolved conflict in the northern region can be said to have caused the democratic breakdown. A more muted conflict level and a higher degree of state capacity is the trend in Ghana, and stands as the reason for why the breakdown happened in Mali, and not in Ghana.Master i Sammenliknende politikkSAMPOL350MASV-SAP

Ordinal versus nominal regression models and the problem of correctly predicting draws in soccer

Ordinal regression models are frequently used in academic literature to model outcomes of soccer matches, and seem to be preferred over nominal models. One reason is that, obviously, there is a natural hierarchy of outcomes, with victory being preferred to a draw and a draw being preferred to a loss. However, the often used ordinal models have an assumption of proportional odds: the influence of an independent variable on the log odds is the same for each outcome. This paper illustrates how ordinal regression models therefore fail to fully utilize independent variables that contain information about the likelihood of matches ending in a draw. However, in practice, this flaw does not seem to have a substantial effect on the predictive accuracy of an ordered logit regression model when compared to a multinomial logistic regression model. Keywords: association football, forecasting, ordered regressionpublishedVersio

Predicting match outcomes in association football using team ratings and player ratings

The main goal of this article is to compare the performance of team ratings and individual player ratings when trying to forecast match outcomes in association football. The well-known Elo rating system is used to calculate team ratings, whereas a variant of plus-minus ratings is used to rate individual players. For prediction purposes, two covariates are introduced. The first represents the pre-match difference in Elo ratings of the two teams competing, while the second is the average difference in individual ratings for the players in the starting line-ups of the two teams. Two different statistical models are used to generate forecasts. The first type is an ordered logit regression (OLR) model that directly outputs probabilities for each of the three possible match outcomes, namely home win, draw and away win. The second type is based on competing risk modelling and involves the estimation of scoring rates for the two competing teams. These scoring rates are used to derive match outcome probabilities using discrete event simulation. Both types of models can be used to generate pre-game forecasts, whereas the competing risk models can also be used for in-game predictions. Computational experiments indicate that there is no statistical difference in the prediction quality for pre-game forecasts between the OLR models and the competing risk models. It is also found that team ratings and player ratings perform about equally well when predicting match outcomes. However, forecasts made when using both team ratings and player ratings as covariates are significantly better than those based on only one of the ratings. Keywords: Elo rating, competing risk, ordered logit regression, plus-minus rating, survival analysis.acceptedVersio

Beyond bonuses : a case study on bonuses and their impact on work motivation from a Beyond Budgeting perspective

The purpose of this research report is to explore the link between bonuses and motivation in a Beyond Budgeting setting. This has been done through conducting a case study of one of the leading finance corporations in the Nordic countries through defining the following problem statement: (How) do bonuses impact motivation in a dynamic management model? Through the use of qualitative interviews as well as a quantitative survey, the research report takes a holistic view of analyzing the motivational impact of three different bonus schemes on employees across the whole organization, as well exploring if a team-based bonus scheme has a different motivational impact on managers compared to non-managers in the organization

RescUSim and IPython: An environment for offshore emergency preparedness planning

Emergency preparedness is crucial for oil and gas operators. While accidents in this industry are commonly connected to oil spill disasters, helicopter accidents are, in terms of incidence rates, a more grave concern in Norway. A recent helicopter accident near Bergen has brought this subject back into focus. We introduce RescUSim, a simulator for rescue missions after offshore helicopter accidents, which is implemented as an open source library with bindings for the Python language. We discuss the modules in the existing Python ecosystem that are used for data preparation and analysis. We show how RescUSim and the interactive computing environment IPython can join forces to provide a tool for planning rescue preparedness for oil and gas related offshore activities

On the relationship between +/- ratings and event-level performance statistics

This work considers the challenge of identifying and properly assessing the contribution of a single player towards the performance of a team. In particular, we study the use of advanced plus-minus ratings for individual football players, which involves evaluating a player based on the goals scored and conceded with the player appearing on the pitch, while compensating for the quality of the opponents and the teammates as well as other factors. To increase the understanding of plus-minus ratings, event-based data from matches are first used to explain the observed variance of ratings, and then to improve their ability to predict outcomes of football matches. It is found that event-level performance statistics can explain from 22% to 38% of the variance in plus-minus ratings, depending on player positions, while incorporating the event-level statistics only marginally improves the predictive power of plus-minus ratings.publishedVersio

Maximizing performance with an eye on the finances: a chance-constrained model for football transfer market decisions

Composing a team of professional players is among the most crucial decisions in association football. Nevertheless, transfer market decisions are often based on myopic objectives and are questionable from a financial point of view. This paper introduces a chance-constrained model to provide analytic support to club managers during transfer windows. The model seeks a top-performing team while adapting to different budgets and financial-risk profiles. In addition, it provides a new rating system that is able to numerically reflect the on-field performance of football players and thus contribute to an objective assessment of football players. The model and rating system are tested on a case study based on real market data. The data from the case study are available online for the benefit of future research