Search results for: nursing interventions classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4403

Search results for: nursing interventions classification

4253 Use of Interpretable Evolved Search Query Classifiers for Sinhala Documents

Authors: Prasanna Haddela

Abstract:

Document analysis is a well matured yet still active research field, partly as a result of the intricate nature of building computational tools but also due to the inherent problems arising from the variety and complexity of human languages. Breaking down language barriers is vital in enabling access to a number of recent technologies. This paper investigates the application of document classification methods to new Sinhalese datasets. This language is geographically isolated and rich with many of its own unique features. We will examine the interpretability of the classification models with a particular focus on the use of evolved Lucene search queries generated using a Genetic Algorithm (GA) as a method of document classification. We will compare the accuracy and interpretability of these search queries with other popular classifiers. The results are promising and are roughly in line with previous work on English language datasets.

Keywords: evolved search queries, Sinhala document classification, Lucene Sinhala analyzer, interpretable text classification, genetic algorithm

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4252 Behavior and Obesity: The Perception of Healthcare Professionals Concerning the Role of Behavior on Obesity

Authors: Saeed Wahass

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Objective: Obesity is epidemic, affecting all societies and cultures. Most serious medical illnesses are attributed to obesity. For this reason, all healthcare systems worldwide have focused on obesity for both intervention and prevention. However, there is scientific evidence supporting that obesity is treatable through implementing different modalities of interventions. They include biological interventions like medications and bariatric surgeries and behavioral interventions. It seems healthcare professionals may suggest the quick and the easiest interventions for obesity like surgery, ignoring other modesties that might require efforts from their sides and patients as well. Searching on the onset, progression and prevention, behavior plays a major role. As a result, psychological interventions have become increasingly core for intervention and prevention of obesity. They are effective and cost effective in dealing with obesity. Methods: A questionnaire describing the role of behavior on obesity and the way it can be prevented and treated was distributed to a group of health professionals who are dealing with obesity e.g. bariatric surgeons, bariatric physicians, psychologists, health educators, nurses and social workers. Results: 88% of healthcare professionals believed that behavior plays a major role on the onset and progression of obesity, 95% of them recognized that obesity can be prevented with consideration for behavior factors. A major proportion (87%) of the respondents see that psychological interventions are effective and cost effective in treating obesity. Conclusions: It optimistically appears that the majority of healthcare professionals believe that behavior is a key component in understanding, preventing and treating obesity. This outcome may help in developing specific training courses for healthcare professionals, who are dealing with obesity concerning the way they can treat patients behaviorally and, moreover, educating the community.

Keywords: behavior, obesity, healthcare provider, psychological interventions

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4251 Nursing Experience of Providing Nursing Care to a Lung Transplantation Patient by Applying the Self-Efficacy Theory

Authors: Hsin-Yi Huang

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This study mainly discussed the disease-induced and surgery-induced physical, psychological, and spiritual issues faced by a patient who suffered from emphysema and respiratory failure and had underwent a right-lung transplantation surgery. Nursing care was provided from May 21 to May 29. Based on the observations, interviews, physical examinations, and evaluations that were carried out using Roy’s adaptation model, the following nursing issues were identified: risk of infection, lack of knowledge, and anxiety. Active care was provided and a good nursing relationship with the patient and the patient’s family was established. The four strategies of Bandura’s self-efficacy theory (self-transcendence, vicarious experience, verbal persuasion, and biofeedback) were employed. Instructions for the appropriate rehabilitation exercises were given, immunosuppressant concentration was monitored, and special measures were taken to prevent infection. The patient was encouraged to express feelings and was provided with sufficient information to alleviate anxiety. With assistance from nursing personnel and the medical team, the patient was successfully discharged from the hospital and thereafter embarked on the path of postoperative recovery. The patient learned about the importance of home self-care and regular follow-up outpatient visits, and patient management was implemented for discharge preparation services. This nursing case study may serve as a reference to nurses managing similar cases in future.

Keywords: anxiety, lung transplantation, Roy's adaptation model, self-efficacy theory

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4250 Classification Systems of Peat Soils Based on Their Geotechnical, Physical and Chemical Properties

Authors: Mohammad Saberian, Reza Porhoseini, Mohammad Ali Rahgozar

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Peat is a partially carbonized vegetable tissue which is formed in wet conditions by decomposition of various plants, mosses and animal remains. This restricted definition, including only materials which are entirely of vegetative origin, conflicts with several established soil classification systems. Peat soils are usually defined as soils having more than 75 percent organic matter. Due to this composition, the structure of peat soil is highly different from the mineral soils such as silt, clay and sand. Peat has high compressibility, high moisture content, low shear strength and low bearing capacity, so it is considered to be in the category of problematic. Since this kind of soil is generally found in many countries and various zones, except for desert and polar zones, recognizing this soil is inevitably significant. The objective of this paper is to review the classification of peats based on various properties of peat soils such as organic contents, water content, color, odor, and decomposition, scholars offer various classification systems which Von Post classification system is one of the most well-known and efficient system.

Keywords: peat soil, degree of decomposition, organic content, water content, Von Post classification

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4249 Current Status and Influencing Factors of Transition Status of Newly Graduated Nurses in China: A Multi-center Cross-sectional Study

Authors: Jia Wang, Wanting Zhang, Yutong Xv, Zihan Guo, Weiguang Ma

Abstract:

Background: Before becoming qualified nurses, newly graduated nurses(NGNs) must experience a painful transition period, even transition shocks. Transition shocks are public health issues. To address the transition issue of NGNs, many programs or interventions have been developed and implemented. However, there are no studies to understand and assess the transition state of newly graduated nurses from work to life, from external abilities to internal emotions. Aims: Assess the transition status of newly graduated nurses in China. Identify the factors influencing the transition status of newly graduated nurses. Methods: The multi-center cross-sectional study design was adopted. From May 2022 to June 2023, 1261 newly graduated nurse in hospitals were surveyed online with the the Demographic Questionnaire and Transition Status Scale for Newly Graduated Nurses. SPSS 26.0 were used for data input and statistical analysis. Statistic description were adopted to evaluate the demographic characteristics and transition status of NGNs. Independent-samples T-test, Analysis of Variance and Multiple regression analysis was used to explore the influencing factors of transition status. Results: The total average score of Transition Status Scale for Newly Graduated Nurses was 4.00(SD = 0.61). Among the various dimensions of Transition Status, the highest dimension was competence for nursing work, while the lowest dimension was balance between work and life. The results showed factors influencing the transition status of NGNs include taught by senior nurses, night shift status, internship department, attribute of working hospital, province of work and residence, educational background, reasons for choosing nursing, types of hospital, and monthly income. Conclusion: At present, the transition status score of new nurses in China is relatively high, and NGNs are more likely to agree with their own transition status, especially the dimension of competence for nursing work. However, they have a poor level of excess in terms of life-work balance. Nursing managers should reasonably arrange the working hours of NGNs, promote their work-life balance, increase the salary and reward mechanism of NGNs, arrange experienced nursing mentors to teach, optimize the level of hospitals, provide suitable positions for NGNs with different educational backgrounds, pay attention to the culture shock of NGNs from other provinces, etc. Optimize human resource management by intervening in these factors that affect the transition of new nurses and promote a better transition of new nurses.

Keywords: newly graduated nurse, transition, humanistic car, nursing management, nursing practice education

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4248 Meta-Analysis of Exercise Interventions for Children and Adolescents Diagnosed with Pediatric Metabolic Syndrome

Authors: James M. Geidner

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Objective: The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on reducing metabolic components in children and/or adolescents diagnosed with Paediatric Metabolic Syndrome. Methods: A computerized search was made from four databases: PubMed, PsycInfo, SPORTDiscus, Cochrane Central Register. The analysis was restricted to children and adolescents with metabolic syndrome examining the effect of exercise interventions on metabolic components. Effect size and 95% confidence interval were calculated and the heterogeneity of the studies was estimated using Cochran’s Q-statistic and I2. Bias was assessed using multiple tools and statistical analyses. Results: Thirteen studies, consisting of 19 separate trials, were selected for the meta-analysis as they fulfilled the inclusion criteria (n=908). Exercise interventions resulted in decreased waist circumference, systolic blood pressure, diastolic blood pressure, fasting glucose, insulin resistance, triglycerides, and High-Density Lipoprotein Cholesterol (HDL-C). Conclusions: This meta-analysis provides insights into the effectiveness of exercise interventions on markers of Paediatric Metabolic Syndrome in children and adolescents.

Keywords: metabolic syndrome, syndrome x, pediatric, meta-analysis

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4247 Cultural Boundaries and Mental Health Stigma: A Systemic Review of Interventions to Reduce Opposition of Mental Health Services in Asian American Families

Authors: Tanya L. Patimeteeporn, Murali D. Nair

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There is a wide range of literature that suggests the factors that prevent Asian American families from utilizing mental health services. These factors arise from a combination of cultural perceptions of mental illness, and methods of treating them without the use of a mental health professional. Due to the increased awareness of Asian Americans’ stigmatization to mental health, there has been an effort to create culturally competent interventions for Asian American families that would reduce opposition to mental health services. Assessment of the effectiveness of these interventions reveals practices that integrate traditional healing methods with psychoeducation are more likely to promote receptiveness of mental health services by Asian American families. The documentary in this review, demonstrates these traditional healing methods from various ethnic enclaves in Los Angeles. In addition, mental health professionals who provide these interventions to Asian American families need to consider culture-bound syndromes and the various Asian health philosophies and belief systems in order to provide a culturally sensitive holistic treatment for their clients. However, because the literature on these interventions is limited, there is a need for a larger body of evidence to accurately assess the effectiveness of these culturally competent psychoeducation interventions.

Keywords: Asian American, cultural boundaries, intervention, mental health stigma, psychoeducation, traditional healing

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4246 Comparing Three Complementary Interventions (Mindfulness-Meditation, Gratitude, and Affirmations) in the Context of Stress

Authors: Regina Bowler

Abstract:

Rationale & Aims: Complementary interventions such as mindfulness-meditation, gratitude, and self-affirmation are often used by therapists to treat stress. Many studies have been conducted using these interventions either individually or adjunctively with regard to stress. However, there has been little work comparing these interventions to investigate which of them is the most effective in treating stress. This study aims to compare these interventions and to determine which of them has the strongest perceived and physiological impact on stress. Participants: 120 law students preparing to take the bar exam: 3 experimental groups of 30 individuals, 1 control group of 30 individuals. Methods: One day prior to administering the interventions, baseline salivary cortisol samples will be taken, and the participants will complete the perceived stress scale (Cohen et al., 1983). Thirty days prior to the bar exam, each experimental group will be given an intervention to practice. Interventions will be practiced once in the morning after waking and once at night at bedtime. In group one, each participant will do a recorded three-minute mindfulness meditation. In group two, each participant will practice gratitude by writing down three things he/she/they are grateful for. In group three, each participant will practice affirmation by writing three sentences affirming his/her/their core values. The control group will not have an intervention to practice. Starting experimental day 1, upon waking and prior to practicing the intervention, the participants will take a salivary cortisol sample. Then they will practice their given intervention. Every night, before going to bed, the participants will practice their given intervention for a second time. The participants will practice their interventions and take salivary cortisol samples for 28 days. After each seven-day period (days 7, 14, 21, 28), the participants will fill out a brief questionnaire about the effects their intervention has on their stress, daily life, and relationships with themselves and others. On day 29, the participants will take a final salivary cortisol sample and will fill out the Perceived Stress Scale (Cohen et al., 1983). Applications of findings: Findings from this study would inform therapists of best practices when working with clients with stress. Moreover, therapists will gain knowledge of how individuals perceive these interventions and their impact on stress, daily life, somatic symptoms, and relationships with self and others. Thus, therapists will be able to administer these interventions with more precision to the stress-related contexts and issues their clients bring.

Keywords: stress, mindfulness-meditation, gratitude, affirmations, complementary interventions

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4245 Effect of the Endotracheal Care Nursing Guideline Utilization on the Incidence of Endotracheal Tube Displacement, Oxygen Deficiency after Extubation, Re-intubation, and Nurses Satisfaction

Authors: Rabeab Khunpukdee, Aranya Sukchoui, Nonluk Somgit, Chitima Bunnaul

Abstract:

Endotracheal displacement is a major risk of life threatening among critically ill patients. Standard nursing protocol is needed to minimize this risk and to improve clinical outcomes. To evaluate the effectiveness of the endothacheal care nursing guideline. The incidence rates of endochacheal displacement, oxygen deficiency after extubation, re-intubation, and nurse’s satisfaction on the utilization of the endotracheal care nursing guideline. An evidence-based nursing practice framework was used to develop the endotracheal care nursing guideline. The guideline valid content was review by a 3 panel of experts. The index of item objective (IOC) of the guideline was 0.93. The guideline was implemented in 130 patients (guideline group) and 19 registered nurses at a medicine ward, Had Yai hospital, Thailand. Patient’s outcomes were evaluated by comparison with those 155 patients who received the routine nursing care (routine care group). Descriptive statistics, frequency, percentage, mean, standard deviation and Mann Whitney U-test was analyzed using the computer program. All significantly and better outcomes were found in the guideline group compared to the routine care group. The guideline group has less incidence rates of endotracheal displacement (1.54 % vs 9.03 %, p < 0.05), and none of the guideline group had oxygen deficiency after extubation (0 % vs 83.33%) compared to the routine care group. All of the 2 patients in the guideline group, compared to 6 of 14 patients in the routine care group were re-intubation. The overall rate of re-intubation in the total group (n = 130 vs 155) was seen less in the guideline group than the routine care group (1.54 % vs 3.87). Overall, nurses satisfaction was at high-level (89.50%) on the utilization of the guideline.

Keywords: endotracheal care, nursing guideline, re-intubation, satisfaction

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4244 A Comparative Analysis of Classification Models with Wrapper-Based Feature Selection for Predicting Student Academic Performance

Authors: Abdullah Al Farwan, Ya Zhang

Abstract:

In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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4243 INRAM-3DCNN: Multi-Scale Convolutional Neural Network Based on Residual and Attention Module Combined with Multilayer Perceptron for Hyperspectral Image Classification

Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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4242 Medical and Surgical Nursing Care

Authors: Nassim Salmi

Abstract:

This study aimed to identify the administrative, social, cultural, economic and psychological challenges facing the nursing s ector in the Tebessa Algeria. It also seeks to identify whether there are differences between the opinions of managers in public and private hospitals about these challenges. To achieve the objectives of the study, the descriptive analytical method was adopted. The study also used the questionnaire as a tool for collecting the necessary data and information, which was applied to a sample of directors of public and private hospitals in the Tebessa, which amounted to (114) individuals. The study reached a set of results, including: that there are no statistically significant differences between the opinions of managers in public and private hospitals about the administrative, social, cultural, economic and psychological challenges facing the nursing sector in the Tebessa . The results also showed agreement between the views of managers in private public hospitals that the most important administrative challenges are the lack of training programs that affect the efficiency and performance of nursing work, and that the most important social and cultural challenges are the hospital’s failure to provide suitable nurseries for Saudi female nurses, and that the most important economic challenges are the lack of Availability of medical equipment and devices, and the most important psychological challenge is the tense relationship between the administration and the hospital's nursing staff. The study recommended focusing on the importance of rehabilitation and training together, activating the role of training in the ministry and making it compulsory and a condition of renewal for practicing and continuing the nursing profession, and providing the social and economic needs of the nursing staff.

Keywords: postoperative care, gynecology, nursing documentation, database

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4241 Development of EREC IF Model to Increase Critical Thinking and Creativity Skills of Undergraduate Nursing Students

Authors: Kamolrat Turner, Boontuan Wattanakul

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Critical thinking and creativity are prerequisite skills for working professionals in the 21st century. A survey conducted in 2014 at the Boromarajonani College of Nursing, Chon Buri, Thailand, revealed that these skills within students across all academic years was at a low to moderate level. An action research study was conducted to develop the EREC IF Model, a framework which includes the concepts of experience, reflection, engagement, culture and language, ICT, and flexibility and fun, to guide pedagogic activities for 75 sophomores of the undergraduate nursing science program at the college. The model was applied to all professional nursing courses. Prior to implementation, workshops were held to prepare lecturers and students. Both lecturers and students initially expressed their discomfort and pointed to the difficulties with the model. However, later they felt more comfortable, and by the end of the project they expressed their understanding and appreciation of the model. A survey conducted four and eight months after implementation found that the critical thinking and creativity skills of the sophomores were significantly higher than those recorded in the pretest. It could be concluded that the EREC IF model is efficient for fostering critical thinking and creativity skills in the undergraduate nursing science program. This model should be used for other levels of students.

Keywords: critical thinking, creativity, undergraduate nursing students, EREC IF model

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4240 The Difficulties Male Nurses Facing up Due to the Nurse Degree which has the Meaning of ‘Sister’ in Turkish

Authors: Hacer Erdöl, Merve Aydın, Hacer Kobya Bulut, Kıymet Yeşilçiçek Çalık

Abstract:

Like all occupations, nursing is significantly influenced by the society which it serves and it also affects it. Social structure affects attitudes of nurses, nursing practice, society's attitudes towards nursing and those who have chosen nursing as a profession. People who choose nursing schools take the views of the society’s they live in on nursing to nursing school. Until the 1960s, many nursing schools had not accepted men as students and women had received nursing education and profession had been carried out by women. In our country, in 2007 an amendment to article eight of Nursing Law was passed and with these changes men also began to be able to choose the nursing as a profession. In Turkish, nurse means 'sister'. Hence, in this study to determine the problems that male nursing students likely encounter at the clinic, non-clinical environment and in their private life regarding the title of nurse, among qualitative research methods phenomenological research design was used. Using purpose sampling method, a total of 18 voluntary male students-13 in third grade and 5 in fourth grade at nursing school- were taken to the study. Data were collected through interviews and by the ethical principles much attention was paid to ensure the confidentiality and to protect participants’ identity. During the interviews lasting 30-40 minutes on average, nine pre-configured standard questions were asked and when necessary free questions were also used in order to ensure the clarity of the responses. With pre- configured standard questions, the reasons why students chose the profession, the problems they had in clinical and non-clinical environment and the potential problems they might encounter in their private lives regarding the title of nurse were questioned. Content analysis was performed on data collected and three main themes were obtained. According to the findings of the evaluation of data, it was found that almost all the students preferred the profession due to possible work opportunities, there were students who did not bother nurse title as well as the ones who did bother and as the most important problem they might encounter in their private lives was to feel worried if their kids had to answer "What does your father" question as "my dad is a nurse" and being ridiculed afterwards. The results of this study show that studies should be done to change the social judgment stemmed from the recognition of nursing as a female profession and take advantage of media through creating public spotlight to accomplish this.

Keywords: choice of profession, the title of the profession, title problems, nursing

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4239 Medical Image Classification Using Legendre Multifractal Spectrum Features

Authors: R. Korchiyne, A. Sbihi, S. M. Farssi, R. Touahni, M. Tahiri Alaoui

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Trabecular bone structure is important texture in the study of osteoporosis. Legendre multifractal spectrum can reflect the complex and self-similarity characteristic of structures. The main objective of this paper is to develop a new technique of medical image classification based on Legendre multifractal spectrum. Novel features have been developed from basic geometrical properties of this spectrum in a supervised image classification. The proposed method has been successfully used to classify medical images of bone trabeculations, and could be a useful supplement to the clinical observations for osteoporosis diagnosis. A comparative study with existing data reveals that the results of this approach are concordant.

Keywords: multifractal analysis, medical image, osteoporosis, fractal dimension, Legendre spectrum, supervised classification

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4238 Correlation between Early Government Interventions in the Northeastern United States and COVID-19 Outcomes

Authors: Joel Mintz, Kyle Huntley, Waseem Wahood, Samuel Raine, Farzanna Haffizulla

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The effect of different state government interventions on COVID-19 health outcomes is currently unknown. Stay at home (SAH) orders, all non-essential business closures and school closures in the Northeastern US were examined. A linear correlation between the peak number of new daily COVID-19 positive tests, hospitalizations and deaths per capita and the elapsed time between government issued guidance and a fixed number of COVID-19 deaths in each state was performed. Earlier government interventions were correlated with lower peak healthcare burden. Statewide closures of schools and non-essential businesses showed significantly greater (p<.001) correlation to peak COVID-19 disease burden as compared to a statewide SAH. The implications of these findings require further study to determine the effectiveness of these interventions.

Keywords: Coronavirus, epidemiology, government intervention, public health, social distancing

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4237 Neural Network Approach to Classifying Truck Traffic

Authors: Ren Moses

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The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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4236 Addressing Challenging Behaviours of Individuals with Positive Behaviour Support

Authors: Divi Sharma

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The emergence of positive behaviour support (PBS) is directly linked to applied behaviour analysis that incorporates evidence-based approaches to addressing ethical challenges and improving autonomy, participation, and the overall quality of life of people living and learning in complex social environments. Its features include lifestyle improvement, collaboration with general caregivers, tracking progress with sound steps, comprehensive performance-based interventions, striving for contextual equality, and ensuring entry and implementation. This document aims to summarize its features with the support of case examples such as involving caregivers to play an active role in behavioural interventions, creating effective interventions within natural practices. Additionally, dealing with lifestyle changes, as well as a wide variety of behavioural changes, develop strong strategies which reduce professional dependence.

Keywords: positive behaviour support, quality of life, performance-based interventions, behavioural changes, participation

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4235 Radar-Based Classification of Pedestrian and Dog Using High-Resolution Raw Range-Doppler Signatures

Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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4234 Clinical Supervisors Experience of Supervising Nursing Students from a Higher Education Institution

Authors: J. Magerman, P. Martin

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Nursing students' clinical abilities is highly dependent on the quality of the clinical experience obtained while placed in the clinical environment. The clinical environment has amongst other, key role players which include the clinical supervisor. The primary role of the clinical supervisor is to guide nursing students to become the best practice nursing professionals. However, globally literature alludes to the failure of educating institutions to deliver competent nursing professionals to meet the needs of patients and deliver quality patient care. At the participating university, this may be due to various factors such as large student numbers and social and environmental challenges experienced by clinical supervisors. The aim of this study was to explore and describe the lived experiences of clinical supervisors who supervise nursing students at a higher education institution. The study employed a qualitative research approach utilizing a descriptive phenomenological design. Purposive sampling was used to select participants, who supervised first and second year nursing studnets at the higher education institution under study. TH esample comprised of eight clinical supervisors who supervise first and secon year nursing studnets at teh institution under study. Data was collected by means of in-depht interviews. Data was analysed using Collaizzi's seven steps method of qualitative analysis. Five major themes identified , focussed on the experiences regarding time a sa constraint to job productivity, the impact of teh organisational culture on the fluidity of support, interpersonal relationships a sa dynamic communication process, impact on the self, and limited resources. Trustworthiness of the data was ensured by means of applying Guba's model of truth value, applicability, consistency and neutrality. Reflexivity was also used by the researcher to further enhance trustworthiness.

Keywords: clinical supervision, clinical supervisors, nursing students, clinical placements

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4233 Classification of Poverty Level Data in Indonesia Using the Naïve Bayes Method

Authors: Anung Style Bukhori, Ani Dijah Rahajoe

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Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

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4232 Drone Classification Using Classification Methods Using Conventional Model With Embedded Audio-Visual Features

Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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4231 Application of Fuzzy Approach to the Vibration Fault Diagnosis

Authors: Jalel Khelil

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In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

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4230 Renovate to nZEB of an Existing Building in the Mediterranean Area: Analysis of the Use of Renewable Energy Sources for the HVAC System

Authors: M. Baratieri, M. Beccali, S. Corradino, B. Di Pietra, C. La Grassa, F. Monteleone, G. Morosinotto, G. Puglisi

Abstract:

The energy renovation of existing buildings represents an important opportunity to increase the decarbonization and the sustainability of urban environments. In this context, the work carried out has the objective of demonstrating the technical and economic feasibility of an energy renovate of a public building destined for offices located on the island of Lampedusa in the Mediterranean Sea. By applying the Italian transpositions of European Directives 2010/31/EU and 2009/28/EC, the building has been renovated from the current energy requirements of 111.7 kWh/m² to 16.4 kWh/m². The result achieved classifies the building as nZEB (nearly Zero Energy Building) according to the Italian national definition. The analysis was carried out using in parallel a quasi-stationary software, normally used in the professional field, and a dynamic simulation model often used in the academic world. The proposed interventions cover the components of the building’s envelope, the heating-cooling system and the supply of energy from renewable sources. In these latter points, the analysis has focused more on assessing two aspects that affect the supply of renewable energy. The first concerns the use of advanced logic control systems for air conditioning units in order to increase photovoltaic self-consumption. With these adjustments, a considerable increase in photovoltaic self-consumption and a decrease in the electricity exported to the Island's electricity grid have been obtained. The second point concerned the evaluation of the building's energy classification considering the real efficiency of the heating-cooling plant. Normally the energy plants have lower operational efficiency than the designed one due to multiple reasons; the decrease in the energy classification of the building for this factor has been quantified. This study represents an important example for the evaluation of the best interventions for the energy renovation of buildings in the Mediterranean Climate and a good description of the correct methodology to evaluate the resulting improvements.

Keywords: heat pumps, HVAC systems, nZEB renovation, renewable energy sources

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4229 MhAGCN: Multi-Head Attention Graph Convolutional Network for Web Services Classification

Authors: Bing Li, Zhi Li, Yilong Yang

Abstract:

Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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4228 Musical Instruments Classification Using Machine Learning Techniques

Authors: Bhalke D. G., Bormane D. S., Kharate G. K.

Abstract:

This paper presents classification of musical instrument using machine learning techniques. The classification has been carried out using temporal, spectral, cepstral and wavelet features. Detail feature analysis is carried out using separate and combined features. Further, instrument model has been developed using K-Nearest Neighbor and Support Vector Machine (SVM). Benchmarked McGill university database has been used to test the performance of the system. Experimental result shows that SVM performs better as compared to KNN classifier.

Keywords: feature extraction, SVM, KNN, musical instruments

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4227 Improved Classification Procedure for Imbalanced and Overlapped Situations

Authors: Hankyu Lee, Seoung Bum Kim

Abstract:

The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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4226 Critical Thinking and Creativity of Undergraduate Nursing Students: Descriptive and Disposition in Academic Levels

Authors: Kamolrat Turner, Chularat Howharn

Abstract:

Critical thinking and creativity are desirable competency for contemporary nurses although there are growing concerns supporting a disturbing paucity in its achievement. Nursing colleges in Thailand have developed teaching strategies and curricula that nurture critical thinking and creativity dispositions according academic levels. Objectives: This descriptive study identified critical thinking and creativity dispositions of Thai nursing students according academic levels. Methods: A cross-sectional questionnaire survey was conducted among 515 nursing students for four academic levels. All are studying at Boromarajonani College of Nursing Chon Buri, Thailand. Descriptive and univariate general linear model analysis were applied. Results: The scores on critical thinking disposition gradually increased as academic level is rising from the junior year throughout the senior year, but its scores are neutral. Scores on creativity skill is neutral and constant thorough the four academic years. The fourth grade students had slightly higher scores on creativity when compared to others. A significant relationship between critical thinking and creativity was also found. Conclusions: The scores on critical thinking disposition gradually improved which greatly increased in the senior year. However, creativity has neutrally progressed. The findings suggest the importance of targeting the development of curriculum and teaching strategies for all grades of nursing students to increase their critical thinking and creativity skills.

Keywords: critical thinking, creativity, undergraduate nursing students, competency

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4225 Assessment of Planet Image for Land Cover Mapping Using Soft and Hard Classifiers

Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

Abstract:

Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.

Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers

Procedia PDF Downloads 153
4224 Self-Reliant Peer Learning for Nursing Students

Authors: U.-B. Schaer, M. Wehr, R. Hodler

Abstract:

Background: Most nursing students require more training time for necessary nursing skills than defined by nursing schools curriculum to acquire basic nursing skills. Given skills training lessons are too brief to enable effective student learning, meaning in-depth skills practice and repetition various learning steps. This increases stress levels and the pressure to succeed for a nursing student with slower learning capabilities. Another possible consequence is that nursing students are less prepared in the required skills for future clinical practice. Intervention: The Bern College of Higher Education of Nursing, Switzerland, started the independent peer practice learning program in 2012. A concept was developed which defines specific aims and content as well as student’s rights and obligations. Students enlist beforehand and order the required materials. They organize themselves and train in small groups in allocated training location in the area of Learning Training and Transfer (LTT). During the peer practice, skills and knowledge can be repeatedly trained and reflected in the peer groups without the presence of a tutor. All invasive skills are practiced only on teaching dummies. This allows students to use all their potential. The students may access learning materials as literature and their own student notes. This allows nursing students to practice their skills and to deepen their knowledge on corresponding with their own learning rate. Results: Peer group discussions during the independent peer practice learning support the students in gaining certainty and confidence in their knowledge and skills. This may improve patient safety in future daily care practice. Descriptive statics show that the number of students who take advantage of the independent peer practice learning increased continuously (2012-2018). It has to be mentioned that in 2012, solely students of the first semester attended the independent peer practice learning program, while in 2018 over one-third of the participating students were in their fifth semester and final study year. It is clearly visible that the demand for independent peer practice learning is increasing. This has to be considered in the development of future teaching curricula.

Keywords: learning program, nursing students, peer learning, skill training

Procedia PDF Downloads 95