Finite Element analysis of coating delamination during scratching

Understanding the delamination process in coating systems under scratching scenario is important in various applications, such as in automotive and oil and gas pipeline applications. Modeling delamination in coated systems is essential to understand the interfacial phenomenon occurring specifically at the interface of the coating material and its substrate. This knowledge is greatly desired because it can help avert the costly damage caused by the failure of the coating meant to provide protective barrier for the substrate in various applications. This work focuses on understanding the delamination process in coating system under scratching scenario, using Finite Element Method (FEM) modeling. Both hard coating deposited on soft substrate (HoS), and soft coating deposited on hard substrate (SoH) are modeled. The FEM model is used to simulate the delamination process incurred during scratching and to analyze the stress situation that are responsible for coating delamination. The FEM model is validated using the experimental results obtained from the literature. Effects of coating thickness, coefficient of friction and coating yield strength on the onset of delamination are studied for both HoS and SoH systems. The FEM results show that an increase in coating thickness delays the onset of delamination for both HoS and SoH systems. Also, higher coefficient of friction generally causes an earlier onset of delamination. Contrasting results are observed for the coating yield strength effect on the onset of delamination. Increase in coating yield strength delays the onset of delamination in the HoS system, whereas the SoH system shows an opposite trend. Analyses of stress distribution at the coating-substrate interface reveal the key reasons for coating delamination. The study provides useful guidelines for developing durable coating system

Efficient OLAP query processing in distributed data warehouses

, and Divesh Srivastava 2 1 Aalborg Universit

Constructing GPSJ view graphs

A data warehouse collects and maintains integrated information from heterogeneous data sources for OLAP and decision support. An important task in data warehouse design is the selection of views to materialize, in order to minimize the response time and maintenance cost of generalized project-select-join (GPSJ) queries. We discuss how to construct GPSJ view graphs. GPSJ view graphs are directed acyclic graphs, used to compactly encode and represent different possible ways of evaluating a set of GPSJ queries. Our view graph construction algorithm, GPSJVIEWGRAPHBUILDER, incrementally constructs GPSJ view graphs based on a set of merge rules. We provide a set of merging rules to construct GPSJ view graphs in the presence of duplicate sensitive and insensitive aggregates. The merging algorithm used in GPSJVIEWGRAPH-BUILDER ensures that each node is correctly added to the view graph, and employs the merge rules to ensure that relationships between nodes from different queries are incorporated into the view graph

theta-Constrained multi-dimensional aggregation

The SQL:2003 standard introduced window functions to enhance the analytical processing capabilities of SQL. The key concept of window functions is to sort the input relation and to compute the aggregate results during a scan of the sorted relation. For multi-dimensional OLAP queries with aggregation groups defined by a general θ condition an appropriate ordering does not exist, though, and hence expensive join-based solutions are required.In this paper we introduce θ-constrained multi-dimensional aggregation (θ-MDA), which supports multi-dimensional OLAP queries with aggregation groups defined by inequalities. θ-MDA is not based on an ordering of the data relation. Instead, the tuples that shall be considered for computing an aggregate value can be determined by a general θ condition. This facilitates the formulation of complex queries, such as multi-dimensional cumulative aggregates, which are difficult to express in SQL because no appropriate ordering exists. We present algebraic transformation rules that demonstrate how the θ-MDA interacts with other operators of a multi-set algebra. Various techniques for achieving an efficient evaluation of the θ-MDA are investigated, and we integrate them into concrete evaluation algorithms and provide cost formulas. An empirical evaluation with data from the TPC-H benchmark confirms the scalability of the θ-MDA operator and shows performance improvements of up to one order of magnitude over equivalent SQL implementations.Keywords: OLAP; SQL/OLAP; Window functions; Multi-dimensional aggregatio

Cancer Mortality Pattern in Lagos University Teaching Hospital, Lagos, Nigeria

Background. Cancer is a leading cause of death worldwide and about 70% of all cancer deaths occurred in low- and middle-income countries. The cancer mortality pattern is quite different in Africa compared to other parts of the world. Extensive literature research showed little or no information about the overall deaths attributable to cancer in Nigeria. Aims and Objectives. This study aims at providing data on the patterns of cancer deaths in our center using the hospital and autopsy death registers. Methodology. Demographic, clinical data of patients who died of cancer were extracted from death registers in the wards and mortuary over a period of 14 years (2000–2013). Results. A total of 1436 (4.74%) cancer deaths out of 30287 deaths recorded during the period. The male to female ratio was 1 : 2.2 and the peak age of death was between 51 and 60 years. Overall, breast cancer was responsible for most of the deaths. Conclusion. The study shows that the cancers that accounted for majority of death occurred in organs that were accessible to screening procedures and not necessary for survival. We advise regular screening for precancerous lesions in these organs so as to reduce the mortality rate and burden of cancer

An algebraic framework for temporal attribute characteristics

Most real-world database applications manage temporal data, i.e., data with associated time references that capture a temporal aspect of the data, typically either when the data is valid or when the data is known. Such applications abound in, e.g., the financial, medical, and scientific domains. In contrast to this, current database management systems offer preciously little built-in query language support for temporal data management. This situation persists although an active temporal database research community has demonstrated that application development can be simplified substantially by built-in temporal support. This paper's contribution is motivated by the observation that existing temporal data models and query languages generally make the same rigid assumption about the semantics of the association of data and time, namely that if a subset of the time domain is associated with some data then this implies the association of any further subset with the data. This paper offers a comprehensive, general framework where alternative semantics may co-exist. It supports so-called malleable and atomic temporal associations, in addition to the conventional ones mentioned above, which are termed constant. To demonstrate the utility of the framework, the paper defines a characteristics-enabled temporal algebra, termed CETA, which defines the traditional relational operators in the new framework. This contribution demonstrates that it is possible to provide built-in temporal support while making less rigid assumptions about the data and without jeopardizing the degree of the support. This moves temporal support closer to practical applications