Search results for: physical health component and mental health component of QoL
3204 ME/CFS Health Outcomes: The Interaction of Mode of Illness Onset and Psychiatric Comorbidity
Authors: Mary Gloria C. Njoku, Leonard A. Jason, Nicole Porter, Molly Brown
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The objective of this study was to examine the interaction between mode of illness onset and psychiatric comorbidity on the health outcomes of persons with ME/CFS. A total of 114 individuals with ME/CFS participated in this study. Individuals completed a battery of baseline measures including the fatigue severity scale and measures of disability. Findings indicated that those with sudden illness onset had more impaired physical health functioning. In addition, among individuals with sudden onset, those without psychiatric comorbidity had greater fatigue severity and lower overall physical health than those with psychiatric comordibity. In contrast, among individuals with gradual illness onset, those with psychiatric comorbity had higher fatigue severity than those without comorbid psychiatric disorders. The health outcomes of individuals who have ME/CFS with or without psychiatric comorbidity are impacted by the mode of illness onset and this suggest that it is important to examine these factors in future research.Keywords: Health Outcomes, ME/CFS, Mode of Illness Onset, Psychiatric Comorbidity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19983203 A New Traffic Pattern Matching for DDoS Traceback Using Independent Component Analysis
Authors: Yuji Waizumi, Tohru Sato, Yoshiaki Nemoto
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Recently, Denial of Service(DoS) attacks and Distributed DoS(DDoS) attacks which are stronger form of DoS attacks from plural hosts have become security threats on the Internet. It is important to identify the attack source and to block attack traffic as one of the measures against these attacks. In general, it is difficult to identify them because information about the attack source is falsified. Therefore a method of identifying the attack source by tracing the route of the attack traffic is necessary. A traceback method which uses traffic patterns, using changes in the number of packets over time as criteria for the attack traceback has been proposed. The traceback method using the traffic patterns can trace the attack by matching the shapes of input traffic patterns and the shape of output traffic pattern observed at a network branch point such as a router. The traffic pattern is a shapes of traffic and unfalsifiable information. The proposed trace methods proposed till date cannot obtain enough tracing accuracy, because they directly use traffic patterns which are influenced by non-attack traffics. In this paper, a new traffic pattern matching method using Independent Component Analysis(ICA) is proposed.
Keywords: Distributed Denial of Service, Independent Component Analysis, Traffic pattern
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17613202 An ICA Algorithm for Separation of Convolutive Mixture of Speech Signals
Authors: Rajkishore Prasad, Hiroshi Saruwatari, Kiyohiro Shikano
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This paper describes Independent Component Analysis (ICA) based fixed-point algorithm for the blind separation of the convolutive mixture of speech, picked-up by a linear microphone array. The proposed algorithm extracts independent sources by non- Gaussianizing the Time-Frequency Series of Speech (TFSS) in a deflationary way. The degree of non-Gaussianization is measured by negentropy. The relative performances of algorithm under random initialization and Null beamformer (NBF) based initialization are studied. It has been found that an NBF based initial value gives speedy convergence as well as better separation performance
Keywords: Blind signal separation, independent component analysis, negentropy, convolutive mixture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17673201 A Reusability Evaluation Model for OO-Based Software Components
Authors: Parvinder S. Sandhu, Hardeep Singh
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The requirement to improve software productivity has promoted the research on software metric technology. There are metrics for identifying the quality of reusable components but the function that makes use of these metrics to find reusability of software components is still not clear. These metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the component and hence improve the productivity due to probabilistic increase in the reuse level. CK metric suit is most widely used metrics for the objectoriented (OO) software; we critically analyzed the CK metrics, tried to remove the inconsistencies and devised the framework of metrics to obtain the structural analysis of OO-based software components. Neural network can learn new relationships with new input data and can be used to refine fuzzy rules to create fuzzy adaptive system. Hence, Neuro-fuzzy inference engine can be used to evaluate the reusability of OO-based component using its structural attributes as inputs. In this paper, an algorithm has been proposed in which the inputs can be given to Neuro-fuzzy system in form of tuned WMC, DIT, NOC, CBO , LCOM values of the OO software component and output can be obtained in terms of reusability. The developed reusability model has produced high precision results as expected by the human experts.Keywords: CK-Metric, ID3, Neuro-fuzzy, Reusability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18103200 Cosastudio: A Software Architecture Modeling Tool
Authors: Adel Smeda, Adel Alti, Mourad Oussalah, Abdallah Boukerram
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A key aspect of the design of any software system is its architecture. An architecture description provides a formal model of the architecture in terms of components and connectors and how they are composed together. COSA (Component-Object based Software Structures), is based on object-oriented modeling and component-based modeling. The model improves the reusability by increasing extensibility, evolvability, and compositionality of the software systems. This paper presents the COSA modelling tool which help architects the possibility to verify the structural coherence of a given system and to validate its semantics with COSA approach.Keywords: Software Architecture, Architecture Description Languages, UML, Components, Connectors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16693199 Tele-Diagnosis System for Rural Thailand
Authors: C. Snae Namahoot, M. Brueckner
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Thailand-s health system is challenged by the rising number of patients and decreasing ratio of medical practitioners/patients, especially in rural areas. This may tempt inexperienced GPs to rush through the process of anamnesis with the risk of incorrect diagnosis. Patients have to travel far to the hospital and wait for a long time presenting their case. Many patients try to cure themselves with traditional Thai medicine. Many countries are making use of the Internet for medical information gathering, distribution and storage. Telemedicine applications are a relatively new field of study in Thailand; the infrastructure of ICT had hampered widespread use of the Internet for using medical information. With recent improvements made health and technology professionals can work out novel applications and systems to help advance telemedicine for the benefit of the people. Here we explore the use of telemedicine for people with health problems in rural areas in Thailand and present a Telemedicine Diagnosis System for Rural Thailand (TEDIST) for diagnosing certain conditions that people with Internet access can use to establish contact with Community Health Centers, e.g. by mobile phone. The system uses a Web-based input method for individual patients- symptoms, which are taken by an expert system for the analysis of conditions and appropriate diseases. The analysis harnesses a knowledge base and a backward chaining component to find out, which health professionals should be presented with the case. Doctors have the opportunity to exchange emails or chat with the patients they are responsible for or other specialists. Patients- data are then stored in a Personal Health Record.Keywords: Biomedical engineering, data acquisition, expert system, information management system, and information retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28123198 Leader-Member Exchange and Affective Commitment: The Moderating Role of Exchange Ideology
Authors: Seung Yeon Son
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In today’s rapidly changing and increasingly complex environment, organizations have relied on their members’ positive attitude toward their employers. In particular, employees’ organizational commitment (primarily, the affective component) has been recognized as an essential component of organizational functioning and success. Hence, identifying the determinants of affective commitment is one of the most important research issues. This study tested the influence of leader-member exchange (LMX) and exchange ideology on employee’s affective commitment. In addition, the interactive effect of LMX and exchange ideology was examined. Data from 198 members of the Korean military supports each of the hypotheses. Lastly, implications for research and directions for future research are discussed.Keywords: Affective commitment, exchange ideology, leader-member exchange, commitment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26133197 Demand and Price Evolution Forecasting as Tools for Facilitating the RoadMapping Process of the Photonic Component Industry
Authors: T. Kamalakis, I. Neokosmidis, D. Varoutas, T. Sphicopoulos
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The photonic component industry is a highly innovative industry with a large value chain. In order to ensure the growth of the industry much effort must be devoted to road mapping activities. In such activities demand and price evolution forecasting tools can prove quite useful in order to help in the roadmap refinement and update process. This paper attempts to provide useful guidelines in roadmapping of optical components and considers two models based on diffusion theory and the extended learning curve for demand and price evolution forecasting.Keywords: Roadmapping, Photonic Components, Forecasting, Diffusion Theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13663196 Determining a Suitable Maintenance Measure for Gentelligent Components Using Case-Based Reasoning
Authors: M. Winkens, P. Nyhuis
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Components with sensory properties such as gentelligent components developed at the Collaborative Research Centre 653 offer a new angle in terms of the full utilization of the remaining service life as well as preventive maintenance. The developed methodology of component status driven maintenance analyzes the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance required in this case. The procedure is derived from the case-based reasoning method and will be explained in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.
Keywords: Gentelligent Components, Preventive Maintenance, Case based Reasoning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18983195 The Robust Clustering with Reduction Dimension
Authors: Dyah E. Herwindiati
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A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paperKeywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16883194 Development of Active Learning Calculus Course for Biomedical Program
Authors: Mikhail Bouniaev
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The paper reviews design and implementation of a Calculus Course required for the Biomedical Competency Based Program developed as a joint project between The University of Texas Rio Grande Valley, and the University of Texas’ Institute for Transformational Learning, from the theoretical perspective as presented in scholarly work on active learning, formative assessment, and on-line teaching. Following a four stage curriculum development process (objective, content, delivery, and assessment), and theoretical recommendations that guarantee effectiveness and efficiency of assessment in active learning, we discuss the practical recommendations on how to incorporate a strong formative assessment component to address disciplines’ needs, and students’ major needs. In design and implementation of this project, we used Constructivism and Stage-by-Stage Development of Mental Actions Theory recommendations.
Keywords: Active learning, assessment, Calculus, cognitive demand, constructivism, mathematics, Stage-by-Stage Development of Mental Action Theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17043193 RTCoord: A Methodology to Design WSAN Applications
Authors: J. Barbarán, M. Díaz, I. Esteve, D. Garrido, L. Llopis, B. Rubio
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Wireless Sensor and Actor Networks (WSANs) constitute an emerging and pervasive technology that is attracting increasing interest in the research community for a wide range of applications. WSANs have two important requirements: coordination interactions and real-time communication to perform correct and timely actions. This paper introduces a methodology to facilitate the task of the application programmer focusing on the coordination and real-time requirements of WSANs. The methodology proposed in this model uses a real-time component model, UM-RTCOM, which will help us to achieve the design and implementation of applications in WSAN by using the component oriented paradigm. This will help us to develop software components which offer some very interesting features, such as reusability and adaptability which are very suitable for WSANs as they are very dynamic environments with rapidly changing conditions. In addition, a high-level coordination model based on tuple channels (TC-WSAN) is integrated into the methodology by providing a component-based specification of this model in UM-RTCOM; this will allow us to satisfy both sensor-actor and actor-actor coordination requirements in WSANs. Finally, we present in this paper the design and implementation of an application which will help us to show how the methodology can be easily used in order to achieve the development of WSANs applications.Keywords: Sensor networks, real time and embedded systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12883192 Space Telemetry Anomaly Detection Based on Statistical PCA Algorithm
Authors: B. Nassar, W. Hussein, M. Mokhtar
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The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the problem above coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions, and the results show that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.Keywords: Space telemetry monitoring, multivariate analysis, PCA algorithm, space operations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20523191 Job Satisfaction of Midwives Working in Labor Ward of the Lady Dufferin Hospital: A Cross-Sectional Study
Authors: B. Muhammadani
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Health workforce is a fundamental component of health system and plays a significant role in delivering effective health care services. However, there is a crucial shortage of skilled personnel which make them prone to work in stressful conditions. In spite of excessively high workload and burnout among the staff, little attention is given to their job satisfaction level which has serious implications on the productivity and effective performance of staff to achieve organizational goals. Therefore, this study aims to explore the job satisfaction of midwives working in the labor ward of the Lady Dufferin Hospital, Karachi. A cross-sectional survey was conducted. The short version of Minnesota Job Satisfaction Questionnaire was administered on a convenient sample group of 22 midwives to gather information on their job satisfaction. The results demonstrated that midwives were overall satisfied with their job. The level of job satisfaction was however found different in various positions within midwifery cadre. The head of midwives was highly satisfied as compared to midwifery staff who works under the supervision of head. The level of satisfaction of team leaders fall between the head and staff of midwifery. Similar trends were observed for both intrinsic and extrinsic job satisfaction. Such evidences on these issues are essential and useful as it helps explore the attitudes of individuals towards work which has direct implications on access to quality care services. Strategic interventions are required at organizational level to provide motivators and satisfiers to health workers for their work related satisfaction and enhanced motivation.Keywords: Health workforce, job satisfaction, motivation, workload, burnout, midwives, health system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22943190 Improved Pattern Matching Applied to Surface Mounting Devices Components Localization on Automated Optical Inspection
Authors: Pedro M. A. Vitoriano, Tito. G. Amaral
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Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.
Keywords: AOI, automated optical inspection, SMD, surface mounting devices, pattern matching, parallel execution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10703189 Chilean Wines Classification based only on Aroma Information
Authors: Nicolás H. Beltrán, Manuel A. Duarte-Mermoud, Víctor A. Soto, Sebastián A. Salah, and Matías A. Bustos
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Results of Chilean wine classification based on the information provided by an electronic nose are reported in this paper. The classification scheme consists of two parts; in the first stage, Principal Component Analysis is used as feature extraction method to reduce the dimensionality of the original information. Then, Radial Basis Functions Neural Networks is used as pattern recognition technique to perform the classification. The objective of this study is to classify different Cabernet Sauvignon, Merlot and Carménère wine samples from different years, valleys and vineyards of Chile.Keywords: Feature extraction techniques, Pattern recognitiontechniques, Principal component analysis, Radial basis functionsneural networks, Wine classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15393188 A New Approach for Classifying Large Number of Mixed Variables
Authors: Hashibah Hamid
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The issue of classifying objects into one of predefined groups when the measured variables are mixed with different types of variables has been part of interest among statisticians in many years. Some methods for dealing with such situation have been introduced that include parametric, semi-parametric and nonparametric approaches. This paper attempts to discuss on a problem in classifying a data when the number of measured mixed variables is larger than the size of the sample. A propose idea that integrates a dimensionality reduction technique via principal component analysis and a discriminant function based on the location model is discussed. The study aims in offering practitioners another potential tool in a classification problem that is possible to be considered when the observed variables are mixed and too large.Keywords: classification, location model, mixed variables, principal component analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15463187 Numerical Analysis of Rapid Gas Decompression in Pure Nitrogen using 1D and 3D Transient Mathematical Models of Gas Flow in Pipes
Authors: Evgeniy Burlutskiy
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The paper presents a numerical investigation on the rapid gas decompression in pure nitrogen which is made by using the one-dimensional (1D) and three-dimensional (3D) mathematical models of transient compressible non-isothermal fluid flow in pipes. A 1D transient mathematical model of compressible thermal multicomponent fluid mixture flow in pipes is presented. The set of the mass, momentum and enthalpy conservation equations for gas phase is solved in the model. Thermo-physical properties of multicomponent gas mixture are calculated by solving the Equation of State (EOS) model. The Soave-Redlich-Kwong (SRK-EOS) model is chosen. This model is successfully validated on the experimental data [1] and shows a good agreement with measurements. A 3D transient mathematical model of compressible thermal single-component gas flow in pipes, which is built by using the CFD Fluent code (ANSYS), is presented in the paper. The set of unsteady Reynolds-averaged conservation equations for gas phase is solved. Thermo-physical properties of single-component gas are calculated by solving the Real Gas Equation of State (EOS) model. The simplest case of gas decompression in pure nitrogen is simulated using both 1D and 3D models. The ability of both models to simulate the process of rapid decompression with a high order of agreement with each other is tested. Both, 1D and 3D numerical results show a good agreement between each other. The numerical investigation shows that 3D CFD model is very helpful in order to validate 1D simulation results if the experimental data is absent or limited.Keywords: Mathematical model, Rapid Gas Decompression
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22093186 A New Face Recognition Method using PCA, LDA and Neural Network
Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani
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In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32023185 An Approach to Solving a Permutation Problem of Frequency Domain Independent Component Analysis for Blind Source Separation of Speech Signals
Authors: Masaru Fujieda, Takahiro Murakami, Yoshihisa Ishida
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Independent component analysis (ICA) in the frequency domain is used for solving the problem of blind source separation (BSS). However, this method has some problems. For example, a general ICA algorithm cannot determine the permutation of signals which is important in the frequency domain ICA. In this paper, we propose an approach to the solution for a permutation problem. The idea is to effectively combine two conventional approaches. This approach improves the signal separation performance by exploiting features of the conventional approaches. We show the simulation results using artificial data.Keywords: Blind source separation, Independent componentanalysis, Frequency domain, Permutation ambiguity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17733184 Eradication of Mental Illness through Buddhism
Authors: Deshar Bashu Dev
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In this modern age, most people in developed and developing countries are affected by mental illness. There are many mental illnesses, and their differing symptoms impact peoples’ lives in different ways. These illnesses affect the way people think and feel, as well as how they behave with others. Mental illness results from compound interactions between the mind, body, and environment. New technologies and sciences make the world a better place. These technologies are becoming smarter and are being developed every day to help make daily life easier However, people suffer from mental illness in every part of the world. The philosophy propounded by the Buddha, Buddhism, teaches that all life is connected, from the microcosm to macrocosm. In the 2,500 years that elapsed since the death of the Buddha, his disciples have spread his teachings and developed sophisticated psycho-therapeutic methodologies. We can find many examples in Buddhist texts and in the modern age where Buddhist philosophy modern science could not solve. The Noble Eightfold Path, which is one of the main philosophies of Buddhism; it eradicates hatred and ill will and cultivates good deeds, kindness, and compassion. Buddhism, as a practice of dialectic conversation and mindfulness training, is full of rich therapeutic tools that the mental health community has adopted to help people. Similarly, Buddhist meditation is very necessary; it purifies thoughts and avoids unnecessary thinking. This research aims to study different causes of mental illness; analyzes the different approaches to eradicate mental illness problems and provides conclusions and recommendations present solutions through Buddhism in this modern age.
Keywords: Mental illness, Buddhism, mindfulness, Buddhist practices.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18933183 The Experiences of Coronary Heart Disease Patients: Biopsychosocial Perspective
Authors: Christopher C. Anyadubalu
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Biological, psychological and social experiences and perceptions of healthcare services in patients medically diagnosed of coronary heart disease were investigated using a sample of 10 participants whose responses to the in-depth interview questions were analyzed based on inter-and-intra-case analyses. The results obtained revealed that advancing age, single status, divorce and/or death of spouse and the issue of single parenting negatively impacted patients- biopsychosocial experiences. The patients- experiences of physical signs and symptoms, anxiety and depression, past serious medical conditions, use of self-prescribed medications, family history of poor mental/medical or physical health, nutritional problems and insufficient physical activities heightened their risk of coronary attack. Collectivist culture served as a big source of relieve to the patients. Patients- temperament, experience of different chronic life stresses/challenges, mood alteration, regular drinking, smoking/gambling, and family/social impairments compounded their health situation. Patients were satisfied with the biomedical services rendered by the healthcare personnel, whereas their psychological and social needs were not attended to. Effective procedural treatment model, a holistic and multidimensional approach to the treatment of heart disease patients was proposed.Keywords: Biopsychosocial, Coronary Heart Disease, Experience, Patients, Perception, Perspective.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26073182 An Empirical Study Comparing Industry Segments as Regards Organisation Management in Open Innovation - Based on a Questionnaire of the Pharmaceutical Industry and IT Component Industry Segment
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The aim of this research is to clarify the difference by industry segment or product characteristics as regards organisation management for an open innovation to raise R&D performance. In particular, the trait of the pharmaceutical industry is defined in comparison with IT component industry segment. In considering open innovation, both inter-organisational relation and the management in an organisation are important issues. As methodology, a questionnaire was conducted. In conclusion, suitable organisation management according to the difference in industry segment or product characteristics became clear.Keywords: Empirical study, industry segment, open innovation, product-development organisation pattern.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17283181 Online Structural Health Monitoring of Ball Bearings
Authors: Matta S. N. S. Kiran, Manikantadhar Maheswaram, Akshat Upadhyay, Rohit Mishra, Bhagat Singh
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A bearing is a very common and useful component of mechanical systems in order to transfer power from one end to another. Therefore, to ensure the accountability and robustness of the rotating mechanical systems, the bearing part's health condition must be checked at regular intervals, also known as preventive maintenance. This condition may lead to unnecessary higher maintenance costs and later result in higher production costs. These costs can be minimized by diagnosing the faulty bearing in its incipient stage. This paper describes an approach to detect rolling bearing defects based on Empirical Mode Decomposition. The novelty of the proposed methodology is validated experimentally using Case Western Reserve University bearing's data sets. The selected data sets comprise the two vibration signals, i.e., inner race and outer, for healthy and faulty conditions.
Keywords: Ball bearing, denoising, signal processing, statistical indicators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4593180 Designing an Integrated Platform for Real-Time Recommendations Sharing among the Aged and People Living with Cancer
Authors: Adekunle O. Afolabi, Pekka Toivanen
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The world is expected to experience growth in the number of ageing population, and this will bring about high cost of providing care for these valuable citizens. In addition, many of these live with chronic diseases that come with old age. Providing adequate care in the face of rising costs and dwindling personnel can be challenging. However, advances in technologies and emergence of the Internet of Things are providing a way to address these challenges while improving care giving. This study proposes the integration of recommendation systems into homecare to provide real-time recommendations for effective management of people receiving care at home and those living with chronic diseases. Using the simplified Training Logic Concept, stakeholders and requirements were identified. Specific requirements were gathered from people living with cancer. The solution designed has two components namely home and community, to enhance recommendations sharing for effective care giving. The community component of the design was implemented with the development of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). This component has illustrated the possibility of real-time recommendations, improved recommendations sharing among care receivers and between a physician and care receivers. Full implementation will increase access to health data for better care decision making.
Keywords: Recommendation systems, healthcare, internet of things, real-time, homecare.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9263179 The Ethics of Instream Flows: Science and Policy in Southern Alberta, Canada
Authors: Jeremy J. Schmidt
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Securing instream flows for aquatic ecosystems is critical for sustainable water management and the promotion of human and environmental health. Using a case study from the semiarid region of southern Alberta (Canada) this paper considers how the determination of instream flow standards requires judgments with respect to: (1) The relationship between instream flow indicators and assessments of overall environmental health; (2) The indicators used to determine adequate instream flows, and; (3) The assumptions underlying efforts to model instream flows given data constraints. It argues that judgments in each of these areas have an inherently ethical component because instream flows have direct effects on the water(s) available to meet obligations to humans and non-humans. The conclusion expands from the case study to generic issues regarding instream flows, the growing water ethics literature and prospects for linking science to policy.Keywords: ethics, instream flows, policy, science, watermanagement
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15363178 Network Anomaly Detection using Soft Computing
Authors: Surat Srinoy, Werasak Kurutach, Witcha Chimphlee, Siriporn Chimphlee
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One main drawback of intrusion detection system is the inability of detecting new attacks which do not have known signatures. In this paper we discuss an intrusion detection method that proposes independent component analysis (ICA) based feature selection heuristics and using rough fuzzy for clustering data. ICA is to separate these independent components (ICs) from the monitored variables. Rough set has to decrease the amount of data and get rid of redundancy and Fuzzy methods allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining- (KDDCup 1999) dataset.Keywords: Network security, intrusion detection, rough set, ICA, anomaly detection, independent component analysis, rough fuzzy .
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19463177 Validation of Contemporary Physical Activity Tracking Technologies through Exercise in a Controlled Environment
Authors: Reem I. Altamimi, Geoff D. Skinner
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Extended periods engaged in sedentary behavior increases the risk of becoming overweight and/or obese which is linked to other health problems. Adding technology to the term ‘active living’ permits its inclusion in promoting and facilitating habitual physical activity. Technology can either act as a barrier to, or facilitate this lifestyle, depending on the chosen technology. Physical Activity Monitoring Technologies (PAMTs) are a popular example of such technologies. Different contemporary PAMTs have been evaluated based on customer reviews; however, there is a lack of published experimental research into the efficacy of PAMTs. This research aims to investigate the reliability of four PAMTs: two wristbands (Fitbit Flex and Jawbone UP), a waist-clip (Fitbit One), and a mobile application (iPhone Health Application) for recording a specific distance walked on a treadmill (1.5km) at constant speed. Physical activity tracking technologies are varied in their recordings, even while performing the same activity. This research demonstrates that Jawbone UP band recorded the most accurate distance compared to Fitbit One, Fitbit Flex, and iPhone Health Application.Keywords: Fitbit, Jawbone UP, mobile tracking applications, physical activity tracking technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15133176 Face Recognition Using Principal Component Analysis, K-Means Clustering, and Convolutional Neural Network
Authors: Zukisa Nante, Wang Zenghui
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Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.
Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4773175 Monotonic and Cyclic J-integral Estimation for Through-Wall Cracked Straight Pipes
Authors: Rohit, S. Vishnuvardhan, P. Gandhi, Nagesh R. Iyer
Abstract:
The evaluation of energy release rate and centre Crack Opening Displacement (COD) for circumferential Through-Wall Cracked (TWC) pipes is an important issue in the assessment of critical crack length for unstable fracture. The ability to predict crack growth continues to be an important component of research for several structural materials. Crack growth predictions can aid the understanding of the useful life of a structural component and the determination of inspection intervals and criteria. In this context, studies were carried out at CSIR-SERC on Nuclear Power Plant (NPP) piping components subjected to monotonic as well as cyclic loading to assess the damage for crack growth due to low-cycle fatigue in circumferentially TWC pipes.Keywords: 304LN stainless steel, cyclic J-integral, Elastic- Plastic Fracture Mechanics, J-integral, Through-wall crack
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2577