A Different Approach to Analyse Data in Road Safety
This is a study to identify the contributing factors of crashes on road curves and understand the effect of various dependencies between these factors on crash severity. Data mining techniques are employed based on the ability to identify patterns and the various dependencies between the contributing factors among vague, uncertain and imprecise data that characterised the insurance incident records. Results are more meaningful when the dependencies between the contributing factors are determined. This technique complements existing statistically based tools approach to analyse road crashes. The data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to design tailored countermeasures.
Revision with unchanged content. In 2004 the World Health Organization declared the incidence of fatalities and injuries due to road collisions as one of the leading epidemics of our time. The United Nations have made a similar declaration for 2007. This book reviews the traditional engineering responses of governments to this road safety problem, including analytical techniques, effectiveness, and shortcomings of the conventional reactive approach. It then describes how to overcome the knowledge gap to a more proactive engineering approach to road safety, including the methodology, development, and use of a new family of reliable empirical tools to do road safety planning, termed macro-level collision prediction models. Several case studies are given, demonstrating that this proactive road safety approach can reap significant sustainability benefits. This book is addressed to professionals and sustainability advocates seeking more sustainable land use and transportation development patterns, like planners, engineers, governments, residents, educators, journalists and Communications Managers. It is also directed towards scientists and researchers in Road Safety, Sustainability, Planning and Engineering.
Providing a single access point to an information system from multiple sources is helpful in many fields. As a case study, this research investigates the potential of applying information fusion techniques in biodiversity area since researchers in this domain desperately need information from different sources to support decision making on tasks like biological identification. Furthermore, there are massive collections in this area and the descriptive materials on the same species (object) are scattered in different places. It is not easy to manually collect information to form a broader and integrated one. This study demonstrates that to a certain extent, this fusion approach is generalizable. The generalizability of this fusion approach is a challenging problem due to the typical domain- and task- oriented nature of the fusion methods. We identified the challenges while applying the approach to different data set.
Analysing Volatility of Indian Stock Markets using EViews
Volatility is an important phenomenon in any market in general and stock markets in particular. Analysing stock market volatility has been subject matter of great concern to policy makers and practioners. The book attempts to analyse nature and pattern of volatility of Indian Stock Markets using ARCH/GARCH classes of models. The book follows a unique approach to analyse the data set using EViews software. It explains step-by-step procedure to carry out the data analysis. This makes the analysis and interpretation easy to understand and follow. Any researcher who wants to perform time series data analysis will certainly find the approach useful.
Revision with unchanged content. A data stream being transmitted over a network channel with capacity less than the data transmission rate of the data stream causes sequential network problems. In this book, we present a new approach for shedding less-informative attribute data from a data stream to maintain the data transmission rate less than the network channel capacity. A scheme for shedding attributes, instead of tuples, becomes imperative in stream data, since shedding a complete tuple would lead to shedding some informative, as well as less-informative, attribute data in the tuple. Since data shed at the source site may be of interest to the user at the destination site, we design a data recovery approach, which maintains the minimal amount of information for data recovery purpose while imposing minimal overhead for data recovery on the source site. Our load shedding and data recovery approach (i) handles wide range of data streams in different application domains, (ii) is dynamic in nature, since each load shedding scheme adjusts the amount of data to be shed according to the current load and network capacity, and (iii) is adoptive, which is appealing in an ever-changing network environment, and (iv) is not based on queries, but works on general data streams instead.
One of the most important features of financial assets is the asset price volatility. Understanding volatility and its modelling has been subject matter of great concern for academicians, policy makers and practitioners. The objective of the book is to analyze and capture volatility using ARCH/GARCH classes of models and suggest the best model which explains volatility and its characteristics in a better way. The unique feature of the book is that it uses open source software R to analyse the data set. It implements various functions in R to carry out analysis. The data codes are given in the book. This will help researcher to analyse his/her data set with little bit of modification in the codes. The approach adopted in the book will facilitate any researcher to perform advanced time series data analysis at ease.
Road traffic crashes are a global problem resulting in deaths, injury and property damage. The World Health Organisation statistics indicate that almost 1.26 million people are killed in road crashes each year globally, representing 25 per cent of all deaths caused by injuries and additional 50 million people are estimated to be injured. The situation is different country to country based on a country's development level, road safety systems and experiences. Amidst the many regulations in the form of driver education and training, road system and vehicle engineering and road safety regulation enforcement to reduce traffic crashes and its associated casualties, the fight is far from over especially in developing countries like Ghana. This book identifies the underlying causes of this problem especially pertaining to Ghana and also recommends measures to reduce crash occurance if not halt it completely
This book provides an advanced novel approach to solving a sensor data fusion problem. It provides a solution to fusing sensory data of different and same type. Moreover, it proposes sensory data pre-processing method to satisfy certain level of input quality prior to fusion. The proved concepts in this book can be utilized in several real life appliations that range from security to battlefield analysis and a lot more where fusion and decision making are needed.
Building a Soil Information System for Multi-Source Data Integration
This study was aimed at the design of a Soil Geographic Database (SGDB) as part of a Soil Information System (SIS), for the improved management of soil and land resource data relevant to an area around Lake Naivasha in Kenya. Emphasis has been given to the rescue of existing data available in different formats from a variety of sources and to the improvement of user access to adequate soil information for multiple purposes. The methods adopted for SGDB data modelling and for SIS development are the relational data model and the iterative structured information system development method, respectively. Two components of the SIS were designed: a relational database structure having twelve relations, and a prototype information system architecture consisting of four subsystems. The study proposes a working approach for multi-source data integration and standardisation in a common database structure. Correlation tables have been developed to handle the multi-category issues when dealing with different soil survey approaches and soil classification systems. A nested database design approach is applied to integrate data resulting from surveys at different levels of detail and map scale.
Data and Information Security using Hylemetric Approach
Security and secure authentication is nowadays a spreading market. Biometry is today the more valuable way to identify and authenticate physical person. The same approach could be followed to authenticate valuable objects, such as banknotes, artworks and drugs packaging. This book wants to present the object authentication problem, the state of the art in object security and how a biometric approach can be used to increase security in object authentication processes. In particular the usage of intrinsic object characteristic inside a biometric paradigm has been called Hylemetry. The proposed approach will be demonstrated for a large set of different objects, starting from banknotes, the more counterfeited object in the world, since artworks of different natures, and eventually, with drug packaging, the emerging new frontier of counterfeiting.
Road Traffic Crashes on Rural Highways in the Ashanti Region of Ghana
Crash Prediction Models (CPMs) have been used in the developed countries as a useful tool by road Engineers and Planners. There is however a limited literature on the prediction of road traffic crashes in Low and Middle Income Countries (LMICs) including Ghana. This book studies crash data and develops a prediction model for injury road traffic crashes occurring on rural highways in the Ashanti Region of Ghana. Data was collected from rural highway sections of varying lengths. Data collected for each segment comprised injury crash data, traffic flow and speed data, and roadway characteristics and road geometry data. The Generalised Linear Model (GLM) with Negative Binomial (NB) error structure was used to estimate the model parameters. Crash rates were initially related to each explanatory variable in turn to ascertain if any relationships existed. Two types of models, the ‘core'' model which included key exposure variables only and the ‘full'' model which included a wider range of variables were developed and interpretations given. Road and Traffic Engineers and Planners can apply the crash prediction model as a tool in safety improvement works and in the design of safer roads.
Many researchers have suggested the atomic data type approach to maintaining data consistency in a system. In this approach, atomicity is ensured by the data objects that are shared by concurrent activities. By using the semantics of the operations of the shared objects,greater concurrency among activities can be permitted. In addition, by encapsulating synchronisation and recovery in the implementation of the shared objects,modularity can be enhanced. Existing systems support user-defined atomic data types in an explicit approach. They either permit limited semantics to be presented thus providing less concurrency, or permit a high level of semantics to be presented but in an encapsulated way,thus resulting in a complicated implementation. The result of this research makes the implementation of user-defined atomic data types simple, efficient, while still permitting great concurrency. It lessens the programmer's burden by supporting an implicit approach for implementing atomic data types. It permits a high level of semantics to be specified in a declarative way,which makes the implementation of user-defined atomic data types as simple as in a sequential environment.
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