This book presents a collection of recent research on building diagnosis techniques related to construction pathology, hygrothermal behavior and durability, and diagnostic techniques. It highlights recent advances and new developments in the field of building physics, building anomalies in materials and components, new techniques for improved energy efficiency analysis, and diagnosis techniques such as infrared thermography. This book will be of interest to a wide readership of professionals, scientists, students, practitioners, and lecturers.
Besides their notable historical and cultural significance, heritage buildings crucially contribute to the economy of those countries that rely heavily on the tourism industry. Investigation and monitoring of the origins of deterioration and damage are therefore key to the preservation of architectural heritage. Diagnosis of Heritage Buildings by Non-Destructive Techniques offers an up-to-date overview of state-of-the-art knowledge by collating specialized studies written by an international group of experts in the field, while also examining the value of these non-intrusive methods through a number of real-life case studies which prove NDT techniques' global relevance. The volume is an invaluable reference resource for students, researchers, and practitioners alike. - Helps readers to easily identify the latest advances in non-destructive testing by subdividing the content into sections specific to each assessment approach - Explores the integration of different NDT methodologies, facilitating the interoperability of traditional and advanced technologies - Presents case studies based on real built heritage to show how to correctly implement the measurement techniques described, and to interpret the results
In any business, the essential element for the successful use of data processing is training. This represents the largest expense both at start-up and as CAD impacts design office procedures other than drafting. Training is also the most difficult cost item to quantify. Even more than the equip ment, training - or retraining in the case of professionals in practice - is the key to increased productivity. Recommendations for specific programs of training are beyond the scope of this paper. Once staff has been retrained to work at higher levels of productivity with data processing equipment, they are more valuable. They will be more difficult to replace. Their new capabilities represent a significant invest ment in modernization, both to the individual design office and to the design profession as a whole. There is a shortage of qualified people with both professional and computer skills. Competition among employers for people with these skills already exists and will probably continue into the foreseeable future. At the outset of training, an employment agreement is worth consider ing for the well-being of all parties.
Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.
Provides applications of soft computing techniques related to healthcare systems, such as machine learning, fuzzy logic, and statistical mathematics, play in the advancements of smart healthcare systems Examine descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in enhancing the services to connected healthcare systems Addresses real-time challenges and case studies in the Healthcare industry Presents various soft computing methodologies like fuzzy logic, ANN, and Genetic Algorithms, to help decision making Focuses on data-centric operations in the Healthcare industry
