Search results for: data communication
24733 The Link Between Collaboration Interactions and Team Creativity Among Nursing Student Teams in Taiwan: A Moderated Mediation Model
Authors: Hsing Yuan Liu
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Background: Considerable theoretical and empirical work has identified a relationship between collaboration interactions and creativity in an organizational context. The mechanisms underlying this link, however, are not well understood in healthcare education. Objectives: The aims of this study were to explore the impact of collaboration interactions on team creativity and its underlying mechanism and to verify a moderated mediation model. Design, setting, and participants: This study utilized a cross-sectional, quantitative, descriptive design. The survey data were collected from 177 nursing students who enrolled in 18-week capstone courses of small interdisciplinary groups collaborating to design healthcare products in Taiwan during 2018 and 2019. Methods: Questionnaires assessed the nursing students' perceptions about their teams' swift trust (of cognition- and affect-based), conflicts (of task, process, and relationship), interaction behaviors (constructive controversy, helping behaviors, and spontaneous communication), and creativity. This study used descriptive statistics to compare demographics, swift trust scores, conflict scores, interaction behavior scores, and creativity scores for interdisciplinary teams. Data were analyzed using Pearson’s correlation coefficient and simple and hierarchical multiple regression models. Results: Pearson’s correlation analysis showed the cognition-based team swift trust was positively correlated with team creativity. The mediation model indicated constructive controversy fully mediated the effect of cognition-based team swift trust on student teams’ creativity. The moderated mediation model indicated that task conflict negatively moderates the mediating effect of the constructive controversy on the link between cognition-based team swift trust and team creativity. Conclusion: Our findings suggest nursing student teams’ interaction behaviors and task conflict are crucial mediating and moderated mediation variables on the relationship between collaboration interactions and team creativity, respectively. The empirical data confirms the validity of our proposed moderated mediation models of team creativity. Therefore, this study's validated moderated mediation model could provide guidance for nursing educators to improve collaboration interaction outcomes and creativity on nursing student teams.Keywords: team swift trust, team conflict, team interaction behavior, moderated mediating effects, interdisciplinary education, nursing students
Procedia PDF Downloads 17824732 Glycemic Control on Self-Efficacy and Self-Care Behaviors among Omani Adults with Type 2 Diabetes
Authors: Melba Sheila D'Souza, Anandhi Amirtharaj, Shreedevi Balachandran
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Background: Type 2 diabetes has a significant impact on individuals’ health and well-being. Glycemic control may influence self-efficacy and self-care behaviors, and reduce the risk of complications among adults with type 2 diabetes. Type 2 diabetes has substantial morbidity and mortality and 60% of adults’ poor self-care. Glycemic control is associated with reported self-efficacy and self-care behavior. Adults with type 2 diabetes with less information were less likely to take diabetes self-care. Aim: To examine the relationship between glycemic control, demographic factors, clinical factors on self-efficacy, self-care behaviors among Omani adults with type 2 diabetes. Methods: A correlational, descriptive study was used. Omani adults with type 2 diabetes (n=140) were recruited from a public hospital in Oman. The data were collected during January-March 2015. Ethical approval was given by the college research and ethics committee, College of Nursing, and the Hospital, Sultan Qaboos University Data was collected on self-efficacy, self-care behaviors and glycemic control. The study was approved by the Institution Ethics and Research Committee. Bivariate and multivariate analyses were conducted. Results: Most adults had a fasting blood glucose >7.2mmol/L (90.7%), with the majority demonstrating ‘uncontrolled or poor HbA1c of > 8%’ (65%). Variance of self-care behavior (20.6%) and 31.3% of the variance of the self-efficacy was explained by the age, duration of diabetes, medication, HbA1c and prevention of activities of living. Adults with type 2 diabetes with poor glycemic control were more likely to have poor self-efficacy and poor self-care behaviors. Conclusion: This study confirms that self-efficacy model on outcome predicts self-efficacy and self-care behavior. Higher understanding of diabetes, prevention of normal daily activities, higher ability to fit diabetes life in a positive manner and high patient-physician communication were significant with self-efficacy and self-care behaviors. Hence, glycemic control has a high effect on improving self-care behaviors like diet, exercise, medication, foot care and self-efficacy among type 2 diabetes. Implications: Using these findings to improve self-efficacy, individualized self-care management is recommended for better self-efficacy and self-care behaviors among adults with type 2 diabetes.Keywords: self-efficacy, self-care behaviors, self-care management, glycemic control, type 2 diabetes, nurse
Procedia PDF Downloads 39724731 A Case Study at PT Bank XYZ on The Role of Compensation, Career Development, and Employee Engagement towards Employee Performance
Authors: Ahmad Badawi Saluy, Novawiguna Kemalasari
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This study aims to examine, analyze and explain the impacts of compensation, career development and employee engagement to employee’s performance partially and simultaneously (Case Study at PT Bank XYZ). The research design used is quantitative descriptive research causality involving 30 respondents. Sources of data are from primary and secondary data, primary data obtained from questionnaires distribution and secondary data obtained from journals and books. Data analysis used model test using smart application PLS 3 that consists of test outer model and inner model. The results showed that compensation, career development and employee engagement partially have a positive impact on employee performance, while they have a positive and significant impact on employee performance simultaneously. The independent variable has the greatest impact is the employee engagement.Keywords: compensation, career development, employee engagement, employee performance
Procedia PDF Downloads 14724730 Electronic Mentoring: How Can It Be Used with Teachers?
Authors: Roberta Gentry
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Electronic mentoring is defined as a relationship between a mentor and a mentee using computer mediated communication (CMC) that is intended to develop and improve mentee’s skills, confidence, and cultural understanding. This session will increase knowledge about electronic mentoring, its uses, and outcomes. The research behind electronic mentoring and descriptions of existing programs will also be shared.Keywords: electronic mentoring, mentoring, beginning special educators, education
Procedia PDF Downloads 24424729 Spectral Anomaly Detection and Clustering in Radiological Search
Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk
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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.Keywords: radiological search, radiological mapping, radioactivity, radiation protection
Procedia PDF Downloads 68824728 Knowledge Engineering Based Smart Healthcare Solution
Authors: Rhaed Khiati, Muhammad Hanif
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In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. In this work, we proposed a smart hospital bed, which mixes the complexity and big data usage of traditional healthcare systems with the comfort found in soft beds while taking certain concerns like data confidentiality, security, and maintaining SLA agreements, etc. into account. This research work potentially provides users, namely patients and doctors, with a seamless interaction with to their respective nurses, as well as faster access to up-to-date personal data, including prescriptions and severity of the condition in contrast to the previous research in the area where there is lack of consideration of such provisions.Keywords: big data, smart healthcare, distributed systems, bioinformatics
Procedia PDF Downloads 19224727 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
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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
Procedia PDF Downloads 24524726 Design of an Instrumentation Setup and Data Acquisition System for a GAS Turbine Engine Using Suitable DAQ Software
Authors: Syed Nauman Bin Asghar Bukhari, Mohtashim Mansoor, Mohammad Nouman
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Engine test-Bed system is a fundamental tool to measure dynamic parameters, economic performance, and reliability of an aircraft Engine, and its automation and accuracy directly influences the precision of acquired and analysed data. In this paper, we present the design of digital Data Acquisition (DAQ) system for a vintage aircraft engine test bed that lacks the capability of displaying all the analyzed parameters at one convenient location (one panel-one screen). Recording such measurements in the vintage test bed is not only time consuming but also prone to human errors. Digitizing such measurement system requires a Data Acquisition (DAQ) system capable of recording these parameters and displaying them on one screen-one panel monitor. The challenge in designing upgrade to the vintage systems arises with a need to build and integrate digital measurement system from scratch with a minimal budget and modifications to the existing vintage system. The proposed design not only displays all the key performance / maintenance parameters of the gas turbine engines for operator as well as quality inspector on separate screens but also records the data for further processing / archiving.Keywords: Gas turbine engine, engine test cell, data acquisition, instrumentation
Procedia PDF Downloads 11924725 Elderly Health Care Process by Community Participation: A Sub-District in the Lower Northern Region of Thailand
Authors: Amaraporn Puraya, Roongtiva Boonpracom, Somsak Thojampa, Sirikanok Klankhajhon, Kittisak Kumpeera
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The objective of this qualitative research was to study the elderly health care process by community participation. Data were collected by quality research methods, including secondary data study, observation, in-depth interviews, and focus group discussions and analyzed by content analysis, reflection and review of information. The research results pointed out that the important elderly health care process by community participation consisted of 2 parts, namely the community participation development process in elderly health care and the outcomes from the participation development process. The community participation development process consisted of 4 steps as follows: 1) Building the leadership team, an important social capital of the community, which started from searching for both formal and informal leaders by giving the opportunity for public participation and creating clear agreements defining roles, duties and responsibilities; 2) investigating the problems and the needs of the community, 3) designing the elderly health care activities under the concept of self-care potential development of the elderly through participation in community forums and meetings to exchange knowledge with common goals, plans and operation and 4) the development process of sustainable health care agreement at the local level, starting from opening communication channels to create awareness and participation in various activities at both individual and group levels as well as pushing activities/projects into the community development plan consistent with the local administration policy. The outcomes from the participation development process were as follows. 1) There was the integration of the elderly for doing the elderly health care activities/projects in the community managed by the elderly themselves. 2) The service system was changed from the passive to the proactive one, focusing on health promotion rather than treating diseases or illnesses. 3) The registered nurses / the public health officers can provide care for the elderly with chronic illnesses through the implementation of activities/projects of elderly health care so that the elderly can access the services more. 4) The local government organization became the main mechanism in driving the elderly health care process by community participation.Keywords: elderly health care process, community participation, elderly, Thailand
Procedia PDF Downloads 20424724 Uderstanding Females' Perspective of Healthy Parental Involvement in Their University's Lives
Authors: Mona Bakry Abdel Meguid Abdelaal
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Despite growing evidence that parental involvement in their adolescents’ lives affects the way they perceive the community around them, little effort has been made to address the importance of this relationship and how it affect the adolescents' interaction with their environment. Adolescents are influenced by their parents while they are growing up and this socialization process services to shape the adolescents sense of self, influencing not only how adolescents feel about themselves, but affecting how they interact with their surroundings. In order to effectively understand this issue, it is important to understand the adolescents’ understanding of healthy parental involvement in their lives, in addition to the obstacles that hinder their communication styles with their parents. Understanding parental involvement in their adolescents’ lives will provide further understanding of the role that social work can perform in this field. The rationale for undertaking this study grew out of the literature on adolescents’ studies in addition to the researchers’ interaction with freshmen female students, who are still in the adolescent stage, in the university. The primary purpose of this study was to understand female adolescents’ awareness of healthy parental involvement in their freshmen year in the university life, as well as obstacles that might hinder that healthy involvement. Using semi-structured interview with a purposive sample of the first year female students in the university, the study managed to determine if the type of parental involvement and parental emotional responsiveness between the adolescents and their parents affects the way they interact with their environment, in addition, to determine the obstacles that hamper the communication between adolescents and their parents.Keywords: adolescents, parental involvement, interaction, university life
Procedia PDF Downloads 25024723 Optimizing Resource Allocation and Indoor Location Using Bluetooth Low Energy
Authors: Néstor Álvarez-Díaz, Pino Caballero-Gil, Héctor Reboso-Morales, Francisco Martín-Fernández
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The recent tendency of "Internet of Things" (IoT) has developed in the last years, causing the emergence of innovative communication methods among multiple devices. The appearance of Bluetooth Low Energy (BLE) has allowed a push to IoT in relation to smartphones. In this moment, a set of new applications related to several topics like entertainment and advertisement has begun to be developed but not much has been done till now to take advantage of the potential that these technologies can offer on many business areas and in everyday tasks. In the present work, the application of BLE technology and smartphones is proposed on some business areas related to the optimization of resource allocation in huge facilities like airports. An indoor location system has been developed through triangulation methods with the use of BLE beacons. The described system can be used to locate all employees inside the building in such a way that any task can be automatically assigned to a group of employees. It should be noted that this system cannot only be used to link needs with employees according to distances, but it also takes into account other factors like occupation level or category. In addition, it has been endowed with a security system to manage business and personnel sensitive data. The efficiency of communications is another essential characteristic that has been taken into account in this work.Keywords: bluetooth low energy, indoor location, resource assignment, smartphones
Procedia PDF Downloads 38524722 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network
Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang
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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.Keywords: deep learning network, smart metering, water end use, water-energy data
Procedia PDF Downloads 30124721 Understanding the Effectiveness of Branding Strategies in Car Rental Service Business in India
Authors: Vrajesh Chokshi
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In last three decades, the global economy is substantially changed. Today, we are living in highly inter-connected world. The global markets are more open and consumers are well informed about products and services. The information technology revolution has broken all barriers in global business. The E-commerce has given opportunities of global trades to corporate. The IT is extensively used in almost all industries. After liberalization in 1992, the Indian economy is also significantly changed. The IT (information technology) and ITES (IT enable services) are extensively used in supply chain management. In India, previously car rental service business was dominated by local organization and operated through local contact. This industry is very lucrative and to catch this opportunity, many new corporate have ventured into e-commerce car rental service business in India. As the market is very competitive, branding is also very important part of marketing strategy. Now, the E-commerce portals those are in car rental business in India have realized the importance of the same and have started usage of all types of communication channel to promote their brand in different Indian markets. At consumer side, the awareness is also being considerably increased due to marketing communication campaign run by these companies. This paper aims to understand effectiveness of branding strategies in car rental business in India and also tries to identify unique promotional strategies to consolidate brand image of this business in different Indian markets.Keywords: branding strategies, car rental business, CRM (customer relationship management), ITES (information technology enabled services)
Procedia PDF Downloads 29524720 Variations in Breast Aesthetic Reconstruction Rates between Asian and Caucasian Patients Post Mastectomy in a UK Tertiary Breast Referral Centre: A Five-Year Institutional Review
Authors: Wisam Ismail, Chole Wright, Elizabeth Baker, Cathy Tait, Mohamed Salhab, Richard Linforth
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Background: Post-mastectomy breast reconstruction is an important treatment option for women with breast cancer with psychosocial, emotional and quality of life benefits. Despite this, Asian patients are one-fifth as likely as Caucasian patients to undergo reconstruction after mastectomy. Aim: This study aimed to assess the difference in breast reconstruction rates between Asian and Caucasian patients treated at Bradford Teaching Hospitals between May 2011 – December 2015.The long-term goal is to equip healthcare professionals to improve breast cancer treatment outcome by increasing breast reconstruction rates in this sub-population. Methods: All patients undergoing mastectomy were identified using a prospectively collected departmental database. Further data was obtained via retrospective electronic case note review. Bradford city population is about 530.000 by the end of 2015, with 67.44% of the city's population was White ethnic groups and 26.83% Asian Ethnic Groups (UK population consensus). The majority of Asian population speaks Urdu, hence an Urdu speaking breast care nurse was appointed to facilitate communications and deliver a better understanding of the reconstruction options and pathways. Statistical analysis was undertaken using the SAS program. Patients were stratified by age, self-reported ethnicity, axillary surgery and reconstruction. Relative odds were calculated using univariate and multivariate logistic regression analyses with adjustment for known confounders. An Urdu speaking breast care nurse was employed throughout this period to facilitate communication and patient decision making. Results: 506 patients underwent Mastectomy over 5 years. 72 (14%) Asian v. 434 (85%) Caucasian. Overall median age is 64 years (SD1.1). Asian median age is 62 (SD0.9), versus Caucasian 65 (SD1.2). Total axillary clearance rate was 30% (42% Asian v.30% Caucasian). Overall reconstruction rate was 126 patients (28.9%).Only 6 of 72 Asian patients (<1%) underwent breast reconstruction versus 121of 434 Caucasian (28%) (p < 0.04), Odds ratio 0.68, (95% confidence interval 0.57-0.79). Conclusions: There is a significant difference in post-mastectomy reconstruction rates between Asian and Caucasian patients. This difference is likely to be multi-factorial. Higher rates of axillary clearance in Asian patients might suggest later disease presentation and/or higher rates of subsequent adjuvant therapy, both of which, can impact on the suitability of breast reconstruction. Strategies aimed at reducing racial disparities in breast reconstruction should include symptom awareness to enable earlier presentation and facilitated communication to ensure informed decision-making.Keywords: aesthetic, Asian, breast, reconstruction
Procedia PDF Downloads 27324719 Strategy Management of Soybean (Glycine max L.) for Dealing with Extreme Climate through the Use of Cropsyst Model
Authors: Aminah Muchdar, Nuraeni, Eddy
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The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE
Procedia PDF Downloads 17424718 Newspaper Headlines as Tool for Political Propaganda in Nigeria: Trend Analysis of Implications on Four Presidential Elections
Authors: Muhammed Jamiu Mustapha, Jamiu Folarin, Stephen Obiri Agyei, Rasheed Ademola Adebiyi, Mutiu Iyanda Lasisi
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The role of the media in political discourse cannot be overemphasized as they form an important part of societal development. The media institution is considered the fourth estate of the realm because it serves as a check and balance to the arms of government (Executive, Legislature and Judiciary) especially in a democratic setup, and makes public office holders accountable to the people. They scrutinize the political candidates and conduct a holistic analysis of the achievement of the government in order to make the people’s representative accountable to the electorates. The media in Nigeria play a seminal role in shaping how people vote during elections. Newspaper headlines are catchy phrases that easily capture the attention of the audience and call them (audience) to action. Research conducted on newspaper headlines looks at the linguistic aspect and how the tenses used has a resultant effect on peoples’ attitude and behaviour. Communication scholars have also conducted studies that interrogate whether newspaper headlines influence peoples' voting patterns and decisions. Propaganda and negative stories about political opponents are stapling features in electioneering campaigns. Nigerian newspaper readers have the characteristic of scanning newspaper headlines. And the question is whether politicians effectively have played into this tendency to brand opponents negatively, based on half-truths and inadequate information. This study illustrates major trends in the Nigerian political landscape looking at the past four presidential elections and frames the progress of the research in the extant body of political propaganda research in Africa. The study will use the quantitative content analysis of newspaper headlines from 2007 to 2019 to be able to ascertain whether newspaper headlines had any effect on the election results of the presidential elections during these years. This will be supplemented by Key Informant Interviews of political scientists or experts to draw further inferences from the quantitative data. Drawing on newspaper headlines of selected newspapers in Nigeria that have a political propaganda angle for the presidential elections, the analysis will correspond to and complements extant descriptions of how the field of political propaganda has been developed in Nigeria, providing evidence of four presidential elections that have shaped Nigerian politics. Understanding the development of the behavioural change of the electorates provide useful context for trend analysis in political propaganda communication. The findings will contribute to how newspaper headlines are used partly or wholly to decide the outcome of presidential elections in Nigeria.Keywords: newspaper headlines, political propaganda, presidential elections, trend analysis
Procedia PDF Downloads 22724717 Magnetic Navigation in Underwater Networks
Authors: Kumar Divyendra
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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.Keywords: clustering, deep learning, network backbone, parallel computing
Procedia PDF Downloads 9024716 Nurses' Assessments of Their Work Environments
Authors: Manar Aslan, Selver Gokdemir, Chatitze Chousein
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This research was conducted to evaluate the factors affecting the working environment of nurses working in three state hospitals. A favorable working environment contributes to increased job satisfaction of nurses and improved working conditions that affects the quality of the work done in a positive way. The population of the study was composed the three largest state hospitals in the region of Thrace in Turkey and 931 nurses working in there. In this research was not used any sampling method. The sampling was composed of nurses who accepted to take part in this research from three hospitals. It was used nursing work index-the practice work environment scale (Turkish version) for data collection (Cronbach alpha: 0.94).When the total scale scores of the nurses in the research were examined, it was determined that they evaluated the working environment below the average. It was also determined that the adequacy of human and other resources, dimensions of the physician-nurse communication scores were low. As in every profession group, the working environment in nursing has an importance to provide quality health and nursing care. A favorable working environment will increase nurses' performance and satisfaction with their work. Identifying the factors affecting the working environment and carrying out the remedial work for them will increase the quality of the health service.Keywords: work environment, work index, nursing, hospitals
Procedia PDF Downloads 23924715 Comparing Performance of Neural Network and Decision Tree in Prediction of Myocardial Infarction
Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan
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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.Keywords: decision trees, neural network, myocardial infarction, Data Mining
Procedia PDF Downloads 42324714 Strategies in Customer Relationship Management and Customers’ Behavior in Making Decision on Buying Car Insurance of Southeast Insurance Co. Ltd. in Bangkok
Authors: Nattapong Techarattanased, Paweena Sribunrueng
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The objective of this study is to investigate strategies in customer relationship management and customers’ behavior in making decision on buying car insurance of Southeast Insurance Co. Ltd. in Bangkok. Subjects in this study included 400 customers with the age over 20 years old to complete questionnaires. The data were analyzed by arithmetic mean and multiple regressions. The results revealed that the customers’ opinions on the strategies in customer relationship management, i.e. customer relationship, customer feedback, customer follow-up, useful service suggestions, customer communication, and service channels were in moderate level but on the customer retention was in high level. Moreover, the strategy in customer relationship management, i.e. customer relationship, and customer feedback had an influence on customers’ buying decision on buying car insurance. The two factors above can be used for the prediction at the rate of 34%. In addition, the strategy in customer relationship management, i.e. customer retention, customer feedback, and useful service suggestions had an influence on the customers’ buying decision on period of being customers. The three factors could be used for the prediction at the rate of 45%.Keywords: strategies, customer relationship management, behavior in buying decision, car insurance
Procedia PDF Downloads 39624713 Safe and Scalable Framework for Participation of Nodes in Smart Grid Networks in a P2P Exchange of Short-Term Products
Authors: Maciej Jedrzejczyk, Karolina Marzantowicz
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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids
Procedia PDF Downloads 29124712 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning
Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul
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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.Keywords: electrocardiogram, dictionary learning, sparse coding, classification
Procedia PDF Downloads 37524711 A Deletion-Cost Based Fast Compression Algorithm for Linear Vector Data
Authors: Qiuxiao Chen, Yan Hou, Ning Wu
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As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost
Procedia PDF Downloads 24524710 Multimedia Container for Autonomous Car
Authors: Janusz Bobulski, Mariusz Kubanek
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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.Keywords: an autonomous car, image processing, lidar, obstacle detection
Procedia PDF Downloads 21824709 Mobile Crowdsensing Scheme by Predicting Vehicle Mobility Using Deep Learning Algorithm
Authors: Monojit Manna, Arpan Adhikary
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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection
Procedia PDF Downloads 6724708 A Biometric Template Security Approach to Fingerprints Based on Polynomial Transformations
Authors: Ramon Santana
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The use of biometric identifiers in the field of information security, access control to resources, authentication in ATMs and banking among others, are of great concern because of the safety of biometric data. In the general architecture of a biometric system have been detected eight vulnerabilities, six of them allow obtaining minutiae template in plain text. The main consequence of obtaining minutia templates is the loss of biometric identifier for life. To mitigate these vulnerabilities several models to protect minutiae templates have been proposed. Several vulnerabilities in the cryptographic security of these models allow to obtain biometric data in plain text. In order to increase the cryptographic security and ease of reversibility, a minutiae templates protection model is proposed. The model aims to make the cryptographic protection and facilitate the reversibility of data using two levels of security. The first level of security is the data transformation level. In this level generates invariant data to rotation and translation, further transformation is irreversible. The second level of security is the evaluation level, where the encryption key is generated and data is evaluated using a defined evaluation function. The model is aimed at mitigating known vulnerabilities of the proposed models, basing its security on the impossibility of the polynomial reconstruction.Keywords: fingerprint, template protection, bio-cryptography, minutiae protection
Procedia PDF Downloads 16524707 Bank Internal Controls and Credit Risk in Europe: A Quantitative Measurement Approach
Authors: Ellis Kofi Akwaa-Sekyi, Jordi Moreno Gené
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Managerial actions which negatively profile banks and impair corporate reputation are addressed through effective internal control systems. Disregard for acceptable standards and procedures for granting credit have affected bank loan portfolios and could be cited for the crises in some European countries. The study intends to determine the effectiveness of internal control systems, investigate whether perceived agency problems exist on the part of board members and to establish the relationship between internal controls and credit risk among listed banks in the European Union. Drawing theoretical support from the behavioural compliance and agency theories, about seventeen internal control variables (drawn from the revised COSO framework), bank-specific, country, stock market and macro-economic variables will be involved in the study. A purely quantitative approach will be employed to model internal control variables covering the control environment, risk management, control activities, information and communication and monitoring. Panel data from 2005-2014 on listed banks from 28 European Union countries will be used for the study. Hypotheses will be tested and the Generalized Least Squares (GLS) regression will be run to establish the relationship between dependent and independent variables. The Hausman test will be used to select whether random or fixed effect model will be used. It is expected that listed banks will have sound internal control systems but their effectiveness cannot be confirmed. A perceived agency problem on the part of the board of directors is expected to be confirmed. The study expects significant effect of internal controls on credit risk. The study will uncover another perspective of internal controls as not only an operational risk issue but credit risk too. Banks will be cautious that observing effective internal control systems is an ethical and socially responsible act since the collapse (crisis) of financial institutions as a result of excessive default is a major contagion. This study deviates from the usual primary data approach to measuring internal control variables and rather models internal control variables in a quantitative approach for the panel data. Thus a grey area in approaching the revised COSO framework for internal controls is opened for further research. Most bank failures and crises could be averted if effective internal control systems are religiously adhered to.Keywords: agency theory, credit risk, internal controls, revised COSO framework
Procedia PDF Downloads 30524706 Towards a Successful Implementation of ICT in Education : Analyzing Teacher Practices and Perceptions
Authors: Azzeddine Atibi, Lamalif latifa, Khadija El Kababi, Salim Ahmed, Mohamed Radid
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This study analyzes the integration of Information and Communication Technologies (ICT) in modern education, where these tools have become essential. Due to the rapid emergence of new technologies and their increasing adoption in education, it is important to understand how teachers use and perceive these tools. The study pursues three objectives : examining current teacher practices regarding ICT, evaluating their impact on student skills and engagement, and making recommendations for better integration of ICT in education. The study's methodology is based on a quantitative approach, using a questionnaire administered to a sample of 104 teachers. This questionnaire, rigorously validated to ensure its reliability, gathers representative data on perceptions and challenges related to the use of ICT. The results show widespread adoption of ICT by teachers, with the majority reporting an improvement in student skills due to these technologies. However, opinions diverge on their impact on student engagement : some teachers note an increase in engagement, while others remain skeptical. Persistent challenges include insufficient technological infrastructure and the need for ongoing training. The recommendations highlight the importance of improving infrastructures and supporting the professional development of teachers to optimize the integration of ICT.Keywords: ICT, education, teaching practices, teacher perceptions, continuing education
Procedia PDF Downloads 2324705 A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon
Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba
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In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.Keywords: population, road network, statistical correlations, remote sensing
Procedia PDF Downloads 15224704 A Multicopy Strategy for Improved Security Wireless Sensor Network
Authors: Tuğçe Yücel
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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.Keywords: MIP, sensor, telecommunications, WSN
Procedia PDF Downloads 499