Fuzzy expert based real time monitoring system for patients with chronic heart failure through IOT

Thesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore UniversityData from the World Health Organization has placed CHF as the number one global killer. It remains the only cardiovascular disease with an increasing hospitalization burden and a continuous drain on health care budgets. Heart failure is a complex clinical syndrome of symptoms that suggest the heart is unable to pump blood efficiently as it should. Heart failure signs and symptoms may include irregular heart rate, blood pressure, fatigue and weakness. The hard reality, with which doctors contend every day, is that the effects of these conditions often manifest too gradually for people to recognize. It falls to the healthcare system to deal with these diseases after they’ve advanced to a serious stage, often at a great financial cost. Effective therapy and treatment in CHF patients require thorough continuous monitoring of patients vitals. Doctors require information on patients; blood pressure, heart electrocardiography activities heart rate and temperature to predict the heart failure attacks and respond swiftly. The typical way to diagnose and monitor CHF patients is by use of bedside patient monitoring systems which requires monitoring within the confines of the hospital. Such monitoring equipment are available in very few hospitals in Kenya and that is an impediment to proper therapy and treatment for CHF patients. The challenges faced in using the existing methods include; lack of flexibility for the patient as there is need for long term monitoring in a hospital setup, financial burden on the patients when they are hospitalized, obtrusive nature of the current monitoring systems making it not suitable for monitoring outdoors. This research applies scrum methodology to design, develop and test a fuzzy based expert system for real time monitoring of chronic heart failure patients through IoT. The IoT architecture contains sensors to capture heart rate, heartbeat, and temperature values from the patients and transmit values from the Arduino board to an IoT server via a GSM communication module. A mobile application will be developed to enable the care givers to monitor the patient remotely. The recommended vital parameters will be keyed to the system to enable it detect anomalies. As a result, patient's doctor and care-givers can see CHF patients vital current health conditions in real-time and get sms alerts in case of anomalies’ to enable them respond swiftly. This model reduce re-hospitalization, enables adjustment of therapy to accommodate change in the patient’s condition and reduces death rates caused by CHF

Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets

Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc

Micro/Nano Manufacturing

Micro- and nano-scale manufacturing has been the subject of ever more research and industrial focus over the past 10 years. Traditional lithography-based technology forms the basis of micro-electro-mechanical systems (MEMS) manufacturing, but also precision manufacturing technologies have been developed to cover micro-scale dimensions and accuracies. Furthermore, these fundamentally different technology platforms are currently combined in order to exploit the strengths of both platforms. One example is the use of lithography-based technologies to establish nanostructures that are subsequently transferred to 3D geometries via injection molding. Manufacturing processes at the micro-scale are the key-enabling technologies to bridge the gap between the nano- and the macro-worlds to increase the accuracy of micro/nano-precision production technologies, and to integrate different dimensional scales in mass-manufacturing processes. Accordingly, this Special Issue seeks to showcase research papers, short communications, and review articles that focus on novel methodological developments in micro- and nano-scale manufacturing, i.e., on novel process chains including process optimization, quality assurance approaches and metrology

Bayesian Methods and Machine Learning in Astrophysics

This thesis is concerned with methods for Bayesian inference and their applications in astrophysics. We principally discuss two related themes: advances in nested sampling (Chapters 3 to 5), and Bayesian sparse reconstruction of signals from noisy data (Chapters 6 and 7). Nested sampling is a popular method for Bayesian computation which is widely used in astrophysics. Following the introduction and background material in Chapters 1 and 2, Chapter 3 analyses the sampling errors in nested sampling parameter estimation and presents a method for estimating them numerically for a single nested sampling calculation. Chapter 4 introduces diagnostic tests for detecting when software has not performed the nested sampling algorithm accurately, for example due to missing a mode in a multimodal posterior. The uncertainty estimates and diagnostics in Chapters 3 and 4 are implemented in the $\texttt{nestcheck}$ software package, and both chapters describe an astronomical application of the techniques introduced. Chapter 5 describes dynamic nested sampling: a generalisation of the nested sampling algorithm which can produce large improvements in computational efficiency compared to standard nested sampling. We have implemented dynamic nested sampling in the $\texttt{dyPolyChord}$ and $\texttt{perfectns}$ software packages. Chapter 6 presents a principled Bayesian framework for signal reconstruction, in which the signal is modelled by basis functions whose number (and form, if required) is determined by the data themselves. This approach is based on a Bayesian interpretation of conventional sparse reconstruction and regularisation techniques, in which sparsity is imposed through priors via Bayesian model selection. We demonstrate our method for noisy 1- and 2-dimensional signals, including examples of processing astronomical images. The numerical implementation uses dynamic nested sampling, and uncertainties are calculated using the methods introduced in Chapters 3 and 4. Chapter 7 applies our Bayesian sparse reconstruction framework to artificial neural networks, where it allows the optimum network architecture to be determined by treating the number of nodes and hidden layers as parameters. We conclude by suggesting possible areas of future research in Chapter 8

Environmental Management: A study of Manufacturing Units working in the Gujarat State

People of India are lucky in the richness of natural resources and diversity of living resources. Uniqueness of our planet earth is the most exiting fact. Earth is the only planet that can support life. The earth is gifted with thousands of rivers that supplies sweet water to quench out thirst, an atmosphere that supplies oxygen for our survival, a natural ozone umbrella that protects us from dangerous ultra violet rays, a green carpet of vegetation that recycles the waste gases like carbon dioxide to oxygen, a large number of attractions like rainbows, lightening and thunders. There are three types of environments including, atmosphere, hydrosphere and biosphere. The nature itself keeps balance among these three layers. Biological wealth on the land includes vegetation, animals, birds, and insects, which are interdependent. The environment in all its facets of biological diversity, the air, soil water, and the forests constitute the essential life support system on which we depend. The main and foremost aims of environment are to study of nature ‘Environment is the sum of all social, economical, biological factors which constitutes the surroundings of man, who is both creator and moulder’. In India, industrial sector plays major role in creation environmental imbalance. Researcher selects this area particularly to study environmental problems in Gujarat State. Samples are selected from five main area of cement, pharmaceutical, textile, chemical VI and fertilizer. Rational of this sample is that Gujarat Industrial Economy majority dependent on these industries. This study has significant utility for decision making authority, industry, academician and researcher