Cypriot and Turkish literatures and cultures

This statement introduces and contextualises my creative writing, academic work and professional career as a poet, author and scholar. It highlights my educational and professional background; the most significant original contribution of my work in the fields of Cypriot and Turkish literatures and cultures; the key events and changes that my publications brought to the professional scene and its impact on the public; the evaluation of my contributions over 27 years; the research methodology I have employed; my other skills, knowledge and practical abilities which have given me an influential authority; the relationships, challenges and valuable impacts of my work in Turkey, both parts of Cyprus, Britain, and other European countries; and the issue of ethics and other related considerations in my creative writing, scholarship and professional life. This information and analysis is supported by appendices which include my curriculum vitae, samples of original publications, other documentation and a full bibliography

Study of the bivariate survival data using frailty models based on Lévy processes

Frailty models allow us to take into account the non-observable inhomogeneity of individual hazard functions. Although models with time-independent frailty have been intensively studied over the last decades and a wide range of applications in survival analysis have been found, the studies based on the models with time-dependent frailty are relatively rare. In this paper, we formulate and prove two propositions related to the identifiability of the bivariate survival models with frailty given by a nonnegative bivariate Lévy process. We discuss parametric and semiparametric procedures for estimating unknown parameters and baseline hazard functions. Numerical experiments with simulated and real data illustrate these procedures. The statements of the propositions can be easily extended to the multivariate case

The Future of Lung Diseases: COPD Model for Slovakia

The initial explorations of bronchial tree pathology can be traced back to the early part of the nineteenth century. Laennec was the first to demonstrate the so-called "catarrh pulmonaire" and its significance to the disease, but the attention of physicians centered upon tuberculosis and pneumonia up until the 1950s. The death of more than 4000 -- mainly older -- people during a catastrophic four-day smog in London (1952) and the realization that chronic bronchitis and its complications were the fatal causes has proved the importance of studying this group of diseases. Intensive research has demonstrated the necessity for a more precise definition of the group of illnesses described under the general term chronic nonspecific lung diseases. Common efforts of specialists from all over the world have culminated in accepted definitions of chronic bronchitis, pulmonary emphysema and bronchial asthma by the World Health Organisation (WHO). Recently, a common term has been used by mostly American authors for all of these diagnostic units: chronic obstructive pulmonary disease (COPD). Numerous studies have shown an undesirable spread of COPD in the developed countries. The high and still growing prevalence of these diseases creates a burden on health-care systems, which leads to an associated growth in health care expenditures and in the number of sick-leave cases and disabled people. It is generally understood that the causes of COPD are largely from within the society itself: life style (smoking), environmental (air) pollution, working conditions, and social and economic circumstances are believed to be responsible for the onsets of these chronic diseases. The growth in COPD prevalence is influenced by recent demographic trends, especially population aging. The large proportion of people with these sicknesses makes a complete registration of all tine cases a practical impossibility. But COPD prevalence must be estimated in some way because of the necessity to forecaste and plan appropriate health care resources. We have developed an appropriate tool for the analysis of possible trends and describe COPD model in this paper. The authors hope that it will be of some help in answering specific questions about COPD development. The model uses data from the Slovak Socialist Republic and allows the user to test several scenarios

Smoking and Lung Cancer Prevalence: Slovakian Case Study

In the first decade of this century lung cancer was an uncommon tumor. This is in sharp contrast to the late 1970s and early 1980s: -- In 1977 the World Health Organization reported that in many countries death rates were either stationary or declining in both males and females, for cancers other than lung. The USA, Australia, Austria, Canada, Japan, Mexico, Sweden, Switzerland, and others were among the affected countries. -- In 1979 the American Cancer Society reported that the overall incidence of cancer had decreased slightly in the past 25 years and that there was an increased death rate in men, which was mainly the result of lung cancer. -- In 1982 the American Cancer Society reported, "Lung cancer rates are indeed the monster of cancer statistics, causing the overall cancer death rate to increase over 18 years from 157.0 to 169.0 per 100,000 persons". Most industrialized countries have recorded similar increases of over 100% incidence in neoplasms of the lung between 1950 and 1964. As a result of intensive epidemiological research carried out in this field during the last 20 years, it is now generally accepted that cancer of the lung is a disease of modern civilization and, in large part, preventable. The incidence of lung neoplasms correlates directly with population density, urbanization, industrialization, tobacco smoking, and even with the registration of automobiles. All these facts suggest that we are facing a real epidemic of lung cancer. The counteractions of health care systems are well known but we are interested in the future development of this process and how it would affect the population in forthcoming years. How effective could preventive campaigns be, assuming different approaches? Where to concentrate preventive efforts -- in the younger or in the older part of the population? Many scientists are looking for the answers to such questions. To develop a mathematical description of processes in the population suffering from the spread of lung cancer may help answer some of these questions and forecast future development. The descriptive model, being realized on a digital computer, could be of substantial help to health care managers, specialists in epidemiology, other physicians, and even to nonphysicians with interests in this field

Modeling of Public Health: Call for Interdisciplinary Actions

Health care systems today confront a range of diseases for which preventive measures lie outside traditional therapeutic medicine. The variety and multicausality of illness forms are closely related to the differences among people, especially social, economical and other conditions of their lives. The activities of many institutions which are not directly involved in health regulation, influence public health today. These facts apply also to the scale of possible control actions. Joint effects of population heterogeneity and the hierarchical nature of public health regulation seem to have led naturally to the current mix of problems and also seem to indicate that only more holistic approaches will improve the situation. One of the problems, how to overcome interdisciplinary barriers and organize effective preventive measures, may be solved only by joined efforts of social and economical institutions directly or indirectly responsible for the modern pattern of diseases. Workshops with computer modeling seem to be an appropriate instrument for developing interdisciplinary collaboration. The results of an experiment with the Slovakian Ministry of Health suggest that intensive modeling workshops involving health care planners, physicians, and other experts lead to better problem formulation and policy analysis

A frailty model for (interval) censored family survival data, applied to the age at onset of non-physical problems

Family survival data can be used to estimate the degree of genetic and environmental contributions to the age at onset of a disease or of a specific event in life. The data can be modeled with a correlated frailty model in which the frailty variable accounts for the degree of kinship within the family. The heritability (degree of heredity) of the age at a specific event in life (or the onset of a disease) is usually defined as the proportion of variance of the survival age that is associated with genetic effects. If the survival age is (interval) censored, heritability as usually defined cannot be estimated. Instead, it is defined as the proportion of variance of the frailty associated with genetic effects. In this paper we describe a correlated frailty model to estimate the heritability and the degree of environmental effects on the age at which individuals contact a social worker for the first time and to test whether there is a difference between the survival functions of this age for twins and non-twins. © 2009 The Author(s)

MULTI-ABSTRACTIVE CONTEXT INTERPRETATIONS OF NETWORK EVENTS

Hybrid and augmented workflows involving predictions or insights produced by automation tools that are handed over to human operators are known to cause cognitive overload. Generally, cognitive overload occurs when an automated system tries to push too much information to a human operator. When such a push of information is sustained over time, cognitive overload leads to what is known as alert fatigue whereby insights of an automated system are not utilized, which can lead to poor adoption. One type of cognitive overload specific to cognitive systems includes situations in which predictions/insights are not necessarily numerous but rather too complex understand and interpret. The lack of ability to understand reasons behind predictions can be a barrier to a broader adoption of artificial intelligence (AI) operations. Presented herein is a novel technique to derive explanations for predictions using multiple contexts, which can help system users to rapidly estimate the importance of predictions from several angles, thereby leading to greater trust and system adoption, as well as improved reaction time

SYSTEM FOR EXPERT-ASSISTED CAUSAL INFERENCE FOR RANKING EVENTS OF INTEREST IN NETWORKS

Networks have increased in size and complexity such that the number of events occurring each day has grown drastically. Techniques of this proposal provide for the ability to infer candidates for causal relationships—in some cases, with confidence. In particular, a novel machine learning (ML) based system is described that provides for the ability to narrow-down candidate temporal patterns that may potentially explain an event of interest (e.g., a network outage). The system is trainable with a human in the loop and is highly effective even with minimal amount of prior training