Search results for: healthcare monitoring
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1098

Search results for: healthcare monitoring

918 Patient Perspectives on Telehealth during the Pandemic in the United States

Authors: Manal Sultan Alhussein, Xiang Michelle Liu

Abstract:

Telehealth is an advanced technology using digital information and telecommunication facilities that provide access to health services from a distance. It slows the transmission factor of COVID-19, especially for elderly patients and patients with chronic diseases during the pandemic. Therefore, understanding patient perspectives on telehealth services and the factors impacting their option of telehealth service will shed light on the measures that healthcare providers can take to improve the quality of telehealth services. This study aimed to evaluate perceptions of telehealth services among different patient groups and explore various aspects of telehealth utilization in the United States during the COVID-19 pandemic. An online survey distributed via social media platforms was used to collect research data. In addition to the descriptive statistics, both correlation and regression analyses were conducted to test research hypotheses. The empirical results highlighted that the factors such as accessibility to telehealth services and the type of specialty clinics that the patients required play important roles in the effectiveness of telehealth services they received. However, the results found that patients’ waiting time to receive telehealth services and their annual income did not significantly influence their desire to select receiving healthcare services via telehealth. The limitations of the study and future research directions are discussed.

Keywords: Telehealth, patient satisfaction, pandemic, healthcare, remote patient monitor.

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917 Fabrication of Microfluidic Device for Quantitative Monitoring of Algal Cell Behavior Using X-ray LIGA Technology

Authors: J. Ruenin, S. Sukprasong, R. Phatthanakun, N. Chomnawang, P. Kuntanawat

Abstract:

In this paper, a simple microfluidic device for monitoring algal cell behavior is proposed. An array of algal microwells is fabricated by PDMS soft-lithography using X-ray LIGA mold, placed on a glass substrate. Two layers of replicated PDMS and substrate are attached by oxygen plasma bonding, creating a microchannel for the microfluidic system. Algal cell are loaded into the microfluidic device, which provides positive charge on the bottom surface of wells. Algal cells, which are negative charged, can be attracted to the bottom of the wells via electrostatic interaction. By varying the concentration of algal cells in the loading suspension, it is possible to obtain wells with a single cell. Liquid medium for cells monitoring are flown continuously over the wells, providing nutrient and waste exchange between the well and the main flow. This device could lead to the uncovering of the quantitative biology of the algae, which is a key to effective and extensive algal utilizations in the field of biotechnology, food industry and bioenergy research and developments.

Keywords: Algal cells, microfluidic device, X-ray LIGA, X-ray lithography, metallic mold, synchrotron light, PDMS

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916 Online Monitoring Rheological Property of Polymer Melt during Injection Molding

Authors: Chung-Chih Lin, Chien-Liang Wu

Abstract:

The detection of the polymer melt state during manufacture process is regarded as an efficient way to control the molded part quality in advance. Online monitoring rheological property of polymer melt during processing procedure provides an approach to understand the melt state immediately. Rheological property reflects the polymer melt state at different processing parameters and is very important in injection molding process especially. An approach that demonstrates how to calculate rheological property of polymer melt through in-process measurement, using injection molding as an example, is proposed in this study. The system consists of two sensors and a data acquisition module can process the measured data, which are used for the calculation of rheological properties of polymer melt. The rheological properties of polymer melt discussed in this study include shear rate and viscosity which are investigated with respect to injection speed and melt temperature. The results show that the effect of injection speed on the rheological properties is apparent, especially for high melt temperature and should be considered for precision molding process.

Keywords: Injection molding, melt viscosity, shear rate, monitoring.

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915 Model based Soft-Sensor for Industrial Crystallization: On-line Mass of Crystals and Solubility Measurement

Authors: Cédric Damour, Michel Benne, Brigitte Grondin-Perez, Jean-Pierre Chabriat

Abstract:

Monitoring and control of cane sugar crystallization processes depend on the stability of the supersaturation (σ ) state. The most widely used information to represent σ is the electrical conductivity κ of the solutions. Nevertheless, previous studies point out the shortcomings of this approach: κ may be regarded as inappropriate to guarantee an accurate estimation of σ in impure solutions. To improve the process control efficiency, additional information is necessary. The mass of crystals in the solution ( c m ) and the solubility (mass ratio of sugar to water / s w m m ) are relevant to complete information. Indeed, c m inherently contains information about the mass balance and / s w m m contains information about the supersaturation state of the solution. The main problem is that c m and / s w m m are not available on-line. In this paper, a model based soft-sensor is presented for a final crystallization stage (C sugar). Simulation results obtained on industrial data show the reliability of this approach, c m and the crystal content ( cc ) being estimated with a sufficient accuracy for achieving on-line monitoring in industry

Keywords: Soft-sensor, on-line monitoring, cane sugarcrystallization.

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914 Clustering for Detection of Population Groups at Risk from Anticholinergic Medication

Authors: Amirali Shirazibeheshti, Tarik Radwan, Alireza Ettefaghian, Farbod Khanizadeh, George Wilson, Cristina Luca

Abstract:

Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. This work evaluates the association between the average risk score and measures of socioeconomic status (index of multiple deprivation) and health (index of health and disability). The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, suggesting that females are more at risk from this kind of multiple medication. The risk may be monitored and controlled in a healthcare management system that is well-equipped with tools implementing appropriate techniques of artificial intelligence.

Keywords: Anticholinergic medication, socioeconomic status, deprivation, clustering, risk analysis.

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913 Dynamically Monitoring Production Methods for Identifying Structural Changes relevant to Logistics

Authors: Marco Kennemann, Steffen C. Eickemeyer, Peter Nyhuis

Abstract:

Due to the growing dynamic and complexity within the market environment production enterprises in particular are faced with new logistic challenges. Moreover, it is here in this dynamic environment that the Logistic Operating Curve Theory also reaches its limits as a method for describing the correlations between the logistic objectives. In order to convert this theory into a method for dynamically monitoring productions this paper will introduce methods for reliably and quickly identifying structural changes relevant to logistics.

Keywords: Dynamics, Logistic Operating Curves, Production Logistics, Production Planning and Control

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912 A SAW-less Dual-Band CDMA Diversity and Simultaneous-GPS Zero-IF Receiver

Authors: Bassem Fahs, Philippe Barré, Patrick Ozenne, Eric Chartier, Guillaume Hérault, Sébastien Jacquet, Sébastien Clamagirand

Abstract:

We present a dual-band (Cellular & PCS) dual-path zero-IF receiver for CDMA2000 diversity, monitoring and simultaneous-GPS. The secondary path is a SAW-less diversity CDMA receiver which can be also used for advanced features like monitoring when supported with an additional external VCO. A GPS receiver is integrated with its dedicated VCO allowing simultaneous positioning during a cellular call. The circuit is implemented in a 0.25μm 40GHz-fT BiCMOS process and uses a HVQFN 56-pin package. It consumes a maximum 300mW from a 2.8V supply in dual-modes. The chip area is 12.8mm2.

Keywords: CDMA, diversity, GPS, zero-IF, SAW-less

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911 Reconstitute Information about Discontinued Water Quality Variables in the Nile Delta Monitoring Network Using Two Record Extension Techniques

Authors: Bahaa Khalil, Taha B. M. J. Ouarda, André St-Hilaire

Abstract:

The world economic crises and budget constraints have caused authorities, especially those in developing countries, to rationalize water quality monitoring activities. Rationalization consists of reducing the number of monitoring sites, the number of samples, and/or the number of water quality variables measured. The reduction in water quality variables is usually based on correlation. If two variables exhibit high correlation, it is an indication that some of the information produced may be redundant. Consequently, one variable can be discontinued, and the other continues to be measured. Later, the ordinary least squares (OLS) regression technique is employed to reconstitute information about discontinued variable by using the continuously measured one as an explanatory variable. In this paper, two record extension techniques are employed to reconstitute information about discontinued water quality variables, the OLS and the Line of Organic Correlation (LOC). An empirical experiment is conducted using water quality records from the Nile Delta water quality monitoring network in Egypt. The record extension techniques are compared for their ability to predict different statistical parameters of the discontinued variables. Results show that the OLS is better at estimating individual water quality records. However, results indicate an underestimation of the variance in the extended records. The LOC technique is superior in preserving characteristics of the entire distribution and avoids underestimation of the variance. It is concluded from this study that the OLS can be used for the substitution of missing values, while LOC is preferable for inferring statements about the probability distribution.

Keywords: Record extension, record augmentation, monitoringnetworks, water quality indicators.

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910 Measurement of Temperature, Humidity and Strain Variation Using Bragg Sensor

Authors: Amira Zrelli, Tahar Ezzeddine

Abstract:

Measurement and monitoring of temperature, humidity and strain variation are very requested in great fields and areas such as structural health monitoring (SHM) systems. Currently, the use of fiber Bragg grating sensors (FBGS) is very recommended in SHM systems due to the specifications of these sensors. In this paper, we present the theory of Bragg sensor, therefore we try to measure the efficient variation of strain, temperature and humidity (SV, ST, SH) using Bragg sensor. Thus, we can deduce the fundamental relation between these parameters and the wavelength of Bragg sensor.

Keywords: Optical fiber, strain, temperature, humidity, measurement, Bragg sensor, SHM.

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909 A Procedure for Post-Earthquake Damage Estimation Based on Detection of High-Frequency Transients

Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner

Abstract:

In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.

Keywords: Acoustic emission, Damage detection, Shaking table test, Structural health monitoring, High-frequency transients.

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908 ICT for Smart Appliances: Current Technology and Identification of Future ICT Trend

Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

Abstract:

Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: Communication technology between appliances, demand response, load monitoring, smart appliances and smart grid.

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907 Two States Mapping Based Neural Network Model for Decreasing of Prediction Residual Error

Authors: Insung Jung, lockjo Koo, Gi-Nam Wang

Abstract:

The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.

Keywords: Neural network, U-healthcare, prediction, timeseries, computer aided prediction.

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906 Adaptive Nonparametric Approach for Guaranteed Real-Time Detection of Targeted Signals in Multichannel Monitoring Systems

Authors: Andrey V. Timofeev

Abstract:

An adaptive nonparametric method is proposed for stable real-time detection of seismoacoustic sources in multichannel C-OTDR systems with a significant number of channels. This method guarantees given upper boundaries for probabilities of Type I and Type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this report.

Keywords: Adaptive detection, change point, interval estimation, guaranteed detection, multichannel monitoring systems.

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905 The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications

Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, Implementation, Multi-Agent, SOA, Autonomous, WCF.

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904 Artificial Neural Networks for Identification and Control of a Lab-Scale Distillation Column Using LABVIEW

Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco

Abstract:

LABVIEW is a graphical programming language that has its roots in automation control and data acquisition. In this paper we have utilized this platform to provide a powerful toolset for process identification and control of nonlinear systems based on artificial neural networks (ANN). This tool has been applied to the monitoring and control of a lab-scale distillation column DELTALAB DC-SP. The proposed control scheme offers high speed of response for changes in set points and null stationary error for dual composition control and shows robustness in presence of externally imposed disturbance.

Keywords: Distillation, neural networks, LABVIEW, monitoring, identification, control.

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903 A Low-Cost Air Quality Monitoring Internet of Things Platform

Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

Abstract:

In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO2 and O3 concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: Distributed sensor system, environmental monitoring, Internet of Things, IoT, Smart Cities.

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902 Automated Process Quality Monitoring with Prediction of Fault Condition Using Measurement Data

Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events is important to improve safety and reliability of machine operations and reduce losses caused by failures. Improper set-ups or aligning of parts often leads to severe problems in many machines. The construction of prediction models for predicting faulty conditions is quite essential in making decisions on when to perform machine maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of machine measurement data. The calibration model is used to predict two faulty conditions from historical reference data. This approach utilizes genetic algorithms (GA) based variable selection, and we evaluate the predictive performance of several prediction methods using real data. The results shows that the calibration model based on supervised probabilistic principal component analysis (SPPCA) yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: Prediction, operation monitoring, on-line data, nonlinear statistical methods, empirical model.

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901 MATLAB-Based Graphical User Interface (GUI) for Data Mining as a Tool for Environment Management

Authors: M. Awawdeh, A. Fedi

Abstract:

The application of data mining to environmental monitoring has become crucial for a number of tasks related to emergency management. Over recent years, many tools have been developed for decision support system (DSS) for emergency management. In this article a graphical user interface (GUI) for environmental monitoring system is presented. This interface allows accomplishing (i) data collection and observation and (ii) extraction for data mining. This tool may be the basis for future development along the line of the open source software paradigm.

Keywords: Data Mining, Environmental data, Mathematical Models, Matlab Graphical User Interface.

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900 Vibration Analysis of Gas Turbine SIEMENS 162MW - V94.2 Related to Iran Power Plant Industry in Fars Province

Authors: Omid A. Zargar

Abstract:

Vibration analysis of most critical equipment is considered as one of the most challenging activities in preventive maintenance. Utilities are heart of the process in big industrial plants like petrochemical zones. Vibration analysis methods and condition monitoring systems of these kinds of equipments are developed too much in recent years. On the other hand, there are too much operation factors like inlet and outlet pressures and temperatures that should be monitored. In this paper, some of the most effective concepts and techniques related to gas turbine vibration analysis are discussed. In addition, a gas turbine SIEMENS 162MW - V94.2 vibration case history related to Iran power industry in Fars province is explained. Vibration monitoring system and machinery technical specification are introduced. Besides, absolute and relative vibration trends, turbine and compressor orbits, Fast Fourier transform (FFT) in absolute vibrations, vibration modal analysis, turbine and compressor start up and shut down conditions, bode diagrams for relative vibrations, Nyquist diagrams and waterfall or three-dimensional FFT diagrams in startup and trip conditions are discussed with relative graphs. Furthermore, Split Resonance in gas turbines is discussed in details. Moreover, some updated vibration monitoring system, blade manufacturing technique and modern damping mechanism are discussed in this paper.

Keywords: Gas turbine, turbine compressor, vibration data collector, utility, condition monitoring, non-contact probe, Relative Vibration, Absolute Vibration, Split Resonance, Time Wave Form (TWF), Fast Fourier transform (FFT).

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899 Workplace Monitoring During Interventional Cardiology Procedures

Authors: N. Todorovic, I. Bikit, J. Nikolov, S. Forkapic, D. Mrdja, S. Todorovic

Abstract:

Interventional cardiologists are at greater risk from radiation exposure as a result of the procedures they undertake than most other medical specialists. A study was performed to evaluate operator dose during interventional cardiology procedures and to establish methods of operator dose reduction with a radiation protective device. Different procedure technique and use of protective tools can explain big difference in the annual equivalent dose received by the professionals. Strategies to prevent and monitor radiation exposure, advanced protective shielding and effective radiation monitoring methods should be applied.

Keywords: absorbed dose rate measurements, annualequivalent dose, protective device.

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898 RFID Logistic Management with Cold Chain Monitoring – Cold Store Case Study

Authors: Mira Trebar

Abstract:

Logistics processes of perishable food in the supply chain include the distribution activities and the real time temperature monitoring to fulfil the cold chain requirements. The paper presents the use of RFID (Radio Frequency Identification) technology as an identification tool of receiving and shipping activities in the cold store. At the same time, the use of RFID data loggers with temperature sensors is presented to observe and store the temperatures for the purpose of analyzing the processes and having the history data available for traceability purposes and efficient recall management.

Keywords: Logistics, warehouse, RFID device, cold chain.

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897 Achievements of Healthcare Services Vis-À-Vis the Millennium Development Goals Targets: Evidence from Pakistan

Authors: Saeeda Batool, Ather Maqsood Ahmed

Abstract:

This study investigates the impact of public healthcare facilities and socio-economic circumstances on the status of child health in Pakistan. The complete analysis is carried out in correspondence with fourth and sixth millennium development goals. Further, the health variables chosen are also inherited from targeted indicators of the mentioned goals (MDGs). Trends in the Human Opportunity Index (HOI) for both health inequalities and coverage are analyzed using the Pakistan Social and Living Standards Measurement (PLSM) data set for 2001-02 to 2012-13 at the national and provincial level. To reveal the relative importance of each circumstance in achieving the targeted values for child health, Shorrocks decomposition is applied on HOI. The annual point average growth rate of HOI is used to simulate the time period for the achievement of target set by MDGs and universal access also. The results indicate an improvement in HOI for a reduction in child mortality rates from 52.1% in 2001-02 to 67.3% in 2012-13, which confirms the availability of healthcare opportunities to a larger segment of society. Similarly, immunization against measles and other diseases such as Diphtheria, Polio, Bacillus Calmette-Guerin (BCG), and Hepatitis has also registered an improvement from 51.6% to 69.9% during the period of study at the national level. On a positive note, no gender disparity has been found for child health indicators and that health outcome is mostly affected by the parental and geographical features and availability of health infrastructure. However, the study finds that this achievement has been uneven across provinces. Pakistan is not only lagging behind in achieving its health goals, disappointingly with the current rate of health care provision, but it will take many additional years to achieve its targets.

Keywords: Socio-economic circumstances, unmet MDGs, public healthcare services, child and infant mortality.

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896 Human Tracking across Heterogeneous Systems Based On Mobile Agent Technologies

Authors: Tappei Yotsumoto, Atsushi Nomura, Kozo Tanigawa, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

Abstract:

In a human tracking system, expanding a monitoring range of one system is complicating the management of devices and increasing its cost. Therefore, we propose a method to realize a wide-range human tracking by connecting small systems. In this paper, we examined an agent deploy method and information contents across the heterogeneous human tracking systems. By implementing the proposed method, we can construct a human tracking system across heterogeneous systems, and the system can track a target continuously between systems.

Keywords: Human tracking system, mobile agent, monitoring.

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895 Monitoring of Key Indicators of Sustainable Tourism in the Jalapão State Park/Tocantins: A Case Study of Environmental Indicators

Authors: Veruska C. Dutra, Afonso R. Aquino

Abstract:

Since the 1980s, global tourism activity has consolidated worldwide to become an important economic contributor, and consequently, the sociocultural and environmental impacts are starting to become evidenced. This raises the need of discussing about actions for sustainable tourism that should be linked not only to the economy, but also to the environment and social aspects. The work that is going to be presented is part of a doctoral research project in Sciences undertaken at the Sao Paulo University, Brazil. It aims to analyze whether the monitoring of the tourism sector with a focus on sustainability is applicable or not, through those indicators, put in a case study in the Jalapão State Park (JSP) conservation unit, in the state of Tocantins, Brazil. This is a study of an interdisciplinary nature that had the deductive method as its guide. We concluded that the key points of the sustainable tourism, when analyzed with the focal point in environmental indicators, are an important evaluation and quantification tool of that activity in the study locus. It displayed itself as an adequate tool for monitoring, thus decoding, the main environmental impacts that occur in tourism regions and their intensity, which is made possible through analysis, and has the objective to trace ways to prevent and correct the presented impacts.

Keywords: Economic indicators, tourism, sustainability, Jalapão.

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894 Transformation of the Business Model in an Occupational Health Care Company Embedded in an Emerging Personal Data Ecosystem: A Case Study in Finland

Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

Abstract:

Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: Ecosystem, business model, personal data, preventive healthcare.

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893 Improving the Decision-Making Process and Transparency of Corporate Governance Using XBRL

Authors: Claudiu Brandas

Abstract:

Several recent studies have shown that the transparency of financial reporting have a significant influence on investor-s decisions. Thus, regulation authorities and professional organizations (IFAC) have emphasized the role of XBRL (eXtensible Business Reporting Language) and interactive data as a means of promoting transparency and monitoring corporate reporting. In this context, this paper has as objective the analysis of interactive reporting through XBRL and its use as a support in the process of taking decisions in corporate governance, namely the potential of interactive reports in XBRL to increase the transparency and monitoring process of corporate governance.

Keywords: Corporate Governance, decision, financial reporting, transparency, XBRL.

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892 Sensor Monitoring of the Concentrations of Different Gases Present in Synthesis of Ammonia Based On Multi-Scale Entropy and Multivariate Statistics

Authors: S. Aouabdi, M. Taibi

Abstract:

This paper presents powerful techniques for the development of a new monitoring method based on multi-scale entropy (MSE) in order to characterize the behaviour of the concentrations of different gases present in the synthesis of Ammonia and soft-sensor based on Principal Component Analysis (PCA).

Keywords: Ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivariate statistics.

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891 Eliciting and Confirming Data, Information, Knowledge and Wisdom in a Specialist Health Care Setting: The WICKED Method

Authors: S. Impey, D. Berry, S. Furtado, M. Galvin, L. Grogan, O. Hardiman, L. Hederman, M. Heverin, V. Wade, L. Douris, D. O'Sullivan, G. Stephens

Abstract:

Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: Healthcare, knowledge acquisition, maximal data sets, action design science.

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890 Development and Usability Assessment of a Connected Resistance Exercise Band Application for Strength-Monitoring

Authors: J. A. Batsis, G. G. Boateng, L. M. Seo, C. L. Petersen, K. L. Fortuna, E. V. Wechsler, R. J. Peterson, S. B. Cook, D. Pidgeon, R. S. Dokko, R. J. Halter, D. F. Kotz

Abstract:

Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.

Keywords: Application, mHealth, older adult, resistance exercise band, sarcopenia.

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889 An Intelligent Nondestructive Testing System of Ultrasonic Infrared Thermal Imaging Based on Embedded Linux

Authors: Hao Mi, Ming Yang, Tian-yue Yang

Abstract:

Ultrasonic infrared nondestructive testing is a kind of testing method with high speed, accuracy and localization. However, there are still some problems, such as the detection requires manual real-time field judgment, the methods of result storage and viewing are still primitive. An intelligent non-destructive detection system based on embedded linux is put forward in this paper. The hardware part of the detection system is based on the ARM (Advanced Reduced Instruction Set Computer Machine) core and an embedded linux system is built to realize image processing and defect detection of thermal images. The CLAHE algorithm and the Butterworth filter are used to process the thermal image, and then the boa server and CGI (Common Gateway Interface) technology are used to transmit the test results to the display terminal through the network for real-time monitoring and remote monitoring. The system also liberates labor and eliminates the obstacle of manual judgment. According to the experiment result, the system provides a convenient and quick solution for industrial non-destructive testing.

Keywords: Remote monitoring, non-destructive testing, embedded linux system, image processing.

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