Search results for: nursing interventions classification

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

Procedia PDF Downloads 68

Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

Abstract:

Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

Procedia PDF Downloads 290

Authors: Joy Aworookoroh

Abstract:

Writing is one of the active skills in language learning. Students of English as a foreign language are expected to write efficiently and proficiently in the language; however, there are usually challenges to optimal performance and competence in writing. Errors, on the other hand, in a foreign language learning situation are more positive than negative as they provide the basis for solving the limitations of the students. This paper investigates the situation in the Department of English, Taraba State University Jalingo. Students are administered a descriptive writing test across different levels of study. The target students are multilingual with an L1 of either Kuteb, Hausa or Junkun languages. The essays are accessed to identify the different kinds of errors in them alongside the classification of the order. Errors of correctness, clarity, engagement, and delivery were identified. However, the study identified that the degree of errors reduces alongside the experience and exposure of the students to an EFL classroom.

Keywords: errors, writings, descriptive essay, multilingual

Procedia PDF Downloads 45

Authors: Damiano Omari, Topirian Kerempe, Dibo Sama, Walter Wafula, Sharon Chepkoech, Chrispine Juma, Gilbert Kirui, Simon Mburu, Susan Keino

Abstract:

The One Health concept was officially adopted by the international organizations and scholarly bodies in 1984. It aims at combining human, animal and environmental components to address global health challenges. Using collaborative efforts optimal health to people, animals, and the environment can be achieved. One health approach plays a significant approach role in prevention and control of zoonosis diseases. It has also been noted that 75% of new emerging human infectious diseases are zoonotic. In Kenya, one health has been embraced and strongly advocated for by One Health East and Central Africa (OHCEA). It was inaugurated on 17th of October 2010 at a historic meeting facilitated by USAID with participants from 7 public health schools, seven faculties of veterinary medicine in Eastern Africa and 2 American universities (Tufts and University of Minnesota) in addition to respond project staff. The study was conducted in Loitoktok Sub County, specifically in the Amboseli Ecosystem. The Amboseli ecosystem covers an area of 5,700 square kilometers and stretches between Mt. Kilimanjaro, Chyulu Hills, Tsavo West National park and the Kenya/Tanzania border. The area is arid to semi-arid and is more suitable for pastoralism with a high potential for conservation of wildlife and tourism enterprises. The ecosystem consists of the Amboseli National Park, which is surrounded by six group ranches which include Kimana, Olgulului, Selengei, Mbirikani, Kuku and Rombo in Loitoktok District. The Manyatta of study was Osiram Cultural Manyatta in Mbirikani group ranch. Apart from visiting the Manyatta, we also visited the sub-county hospital, slaughter slab, forest service, Kimana market, and the Amboseli National Park. The aim of the study was to identify the one health issues facing the community. This was done by a conducting a community needs assessment and prioritization. Different methods were used in data collection for the qualitative and numerical data. They include among others; key informant interviews and focus group discussions. We also guided the community members in drawing their Resource Map this helped identify the major resources in their land and also help them identify some of the issues they were facing. Matrix piling, root cause analysis, and force field analysis tools were used to establish the one health related priority issues facing community members. Skits were also used to present to the community interventions to the major one health issues. Some of the prioritized needs among the community were water scarcity and inadequate markets for their beadwork. The group intervened on the various needs of the Manyatta. For water scarcity, we educated the community on water harvesting methods using gutters as well as proper storage by the use of tanks and earth dams. The community was also encouraged to recycle and conserve water. To improve markets; we educated the community to upload their products online, a page was opened for them and uploading the photos was demonstrated to them. They were also encouraged to be innovative to attract more clients.

Keywords: Amboseli ecosystem, community interventions, community needs assessment and prioritization, one health issues

Procedia PDF Downloads 155

Authors: Maeah Stephanie A. Macapaz Abadejos

Abstract:

Covid-19 shook the whole world. Every person on all sides of the world was affected by the pandemic. All the nations and world leaders were searching for a variety of cures and solutions to stop the spread of the virus. In connection with this, this investigative case study aims to show a relationship between COVID-19 vaccinations to the immune system of the seniors and elderly. The seniors and elderly are one of the most vulnerable populations that show high morbidity and mortality in any illnesses and diseases. This study will show lived experiences of the senior’s immune system and health status, how it is being affected by the COVID-19 virus and its vaccines, Risk for COVID-19 Infection, Hospitalization, and Death by Age Group. Participants of this study are from 3 Cebu City Barangays and 2 from Barangays of the Cities of the Cebu Province. To conclude, this study shall serve its purpose of providing clear and concise results in strengthening the evidence of the effects of the COVID-19 virus infection, especially the free vaccinations, on the health and overall well-being of the elderly and seniors.

Keywords: gerontology nursing, vaccination, protection and immunity, seniors and the elderly

Procedia PDF Downloads 3

Authors: H. Analuie, M. Faruque, S. Saha, H. Hashim, M. Muzaimi

Abstract:

Though mental toughness has long been explored in sport psychology, much of our understanding on the topic remains largely unexplored. The concept is used widely, but empirical evidence is required to fully understand the construct and its related variables. This research investigated the correlation between mental toughness and trait anxiety to determine whether mentally tough athletes generally experience more or less anxiety. A sample of 57 men (M age = 25.4 years, s=4.66) and 45 women (M age = 23.5 years, s=5.73) participated in a variety of sports were recruited, where mental toughness was measured using MTQ48. Levels of trait anxiety were assessed using the State-Trait Anxiety Inventory (STAI). Series of Pearson correlations between trait anxiety, overall mental toughness, and the six subscales of mental toughness showed significant (p> .05) relationships. As predicted, greater mental toughness was associated with less reported trait anxiety. Independent t-tests found significant differences (p> .05) in overall mental toughness, the mental toughness subscales or trait anxiety between men and women. More research is required to understand how mentally tough athletes experience less anxiety in comparison to those who are not as mentally tough. Our findings suggest that relationships observed in this study emphasize the need for the inclusion of trait anxiety in mental toughness interventions.

Keywords: mental toughness, trait anxiety, MTQ48, sport psychology

Procedia PDF Downloads 451

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 63

Authors: Marie Bieber, Fabrice Cosson, Olivier Schmitt

Abstract:

Europe's Global Navigation Satellite System, Galileo, provides worldwide positioning and navigation services. The satellites in space are only one part of the Galileo system. An extensive ground infrastructure is essential to oversee the satellites and ensure accurate navigation signals. High reliability and availability of the entire Galileo system are crucial to continuously provide positioning information of high quality to users. Outages are tracked, and operational availability is regularly assessed. A highly flexible and adaptive tool has been developed to automate the Galileo system availability analysis. Not only does it enable a quick availability consolidation, but it also provides first steps towards improving the data quality of maintenance tickets used for the analysis. This includes data import and data preparation, with a focus on processing strings used for classification and identifying faulty data. Furthermore, the tool allows to handle a low amount of data, which is a major constraint when the aim is to provide accurate statistics.

Keywords: availability, data quality, system performance, Galileo, aerospace

Procedia PDF Downloads 146

Authors: Neda Dekamei, Mostafa Sarabzadeh, Masoumeh Bigdeli

Abstract:

Backward running is commonly used in different sports conditioning, motor learning, and neurological purposes, and even more commonly in physical rehabilitation. The present study evaluated the effects of six weeks backward and forward running methods on balance promotion adaptation in students. 12 male and female preseniors with the age range of 45-60 years participated and were randomly classified into two groups of backward running (n: 6) and forward running (n: 6) training interventions. During six weeks, 3 sessions per week, all subjects underwent stated different models of backward and forward running training on treadmill (65-80 of HR max). Pre and post-tests were performed by force plate and electromyogram, two times before and after intervention. Data were analyzed using by T test. On the basis of obtained data, significant differences were recorded on balance and plantar flexion force in backward running (BR) and no difference for forward running (FR). It seems the training model of backward running can generate more stimulus to achieve better plantar flexion force and strengthening ankle protectors which leads to balance improvement in pre aging period. It can be recommended as an effective method to promote seniors life quality especially in balance neuromuscular parameters.

Keywords: backward running, balance, plantar flexion, pre seniors

Procedia PDF Downloads 146

Authors: Paul M. H. J. Roekaerts

Abstract:

In recent years, it became clear that much intensive care (ICU) survivors develop a post-intensive care syndrome (PICS) consisting of psychiatric, cognitive and physical problems for a prolonged period after their ICU stay. Physical inactivity and delirium during the ICU stay are the main determinants of the post-ICU PICS. This presentation will focus on delirium, its epidemiology, prevalence, effect on outcome, risk factors and the current standard of care for managing delirium. Because ICU delirium is a predictor of prolonged length-of-stay in the ICU and of death, the use of a delirium prevention bundle (DPB) becomes mandatory in every ICU. In this presentation, a DPB bundle will be discussed consisting of six components: pain, sedation, sleep, sensory and intellectual stimulation, early mobilization, and hydration. For every of the six components, what to do and what not to do will be discussed. The author will present his own institutional policy on pharmacological and non-pharmacological interventions in the management of delirium. The component ‘early mobilization’ will be discussed more in detail, as this component is extremely important in the prevention of delirium as well as in the prevention of the PICS. The author will conclude his presentation with the remaining areas of uncertainties/work and research to be done.

Keywords: delirium, delirium prevention bundle, early mobilisation in intensive care (ICU), post-intensive care syndrome (PICS)

Procedia PDF Downloads 299

Authors: Karla E. Sanchez-Cazares, Kim H. Parker, Jennifer H. Tweedy

Abstract:

The purpose of this work is to develop a simple compartmental model of cerebral fluid balance including blood and cerebrospinal-fluid (CSF). At the first level the cerebral arteries and veins are modelled as bifurcating trees with constant scaling factors between generations which are connected through a homogeneous microcirculation. The arteries and veins are assumed to be non-rigid and the cross-sectional area, resistance and mean pressure in each generation are determined as a function of blood volume flow rate. From the mean pressure and further assumptions about the variation of wall permeability, the transmural fluid flux can be calculated. The results suggest the next level of modelling where the cerebral vasculature is divided into three compartments; the large arteries, the small arteries, the capillaries and the veins with effective compliances and permeabilities derived from the detailed vascular model. These vascular compartments are then linked to other compartments describing the different CSF spaces, the cerebral ventricles and the subarachnoid space. This compartmental model is used to calculate the distribution of fluid in the cranium. Known volumes and flows for normal conditions are used to determine reasonable parameters for the model, which can then be used to help understand pathological behaviour and suggest clinical interventions.

Keywords: cerebrovascular, compartmental model, CSF model, vascular network

Procedia PDF Downloads 264

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

Procedia PDF Downloads 355

Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

Abstract:

Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

Procedia PDF Downloads 75

Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

Abstract:

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: data mining, knowledge discovery in databases, prediction models, student success

Procedia PDF Downloads 395

Authors: Juan Heredia, Naci Dilekli

Abstract:

The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.

Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing

Procedia PDF Downloads 142

Authors: Juan Carlos Briones Macias

Abstract:

Currently, the Huancavilca City Park in Guayaquil is an abandoned public space that is discovering a growing problem of insecurity, where various problems have been perceived, such as the lack of green areas, deteriorating furniture, insufficient lighting, the use of inadequate cladding materials and very sunny areas due to the lack of planning in the design of green areas. The objective of this scientific article is to redesign Huancavilca Park through public space design strategies for more attractive and comfortable areas, becoming a point of interaction in a safe and accessible way. A mixed methodology (qualitative and quantitative) was applied, obtaining information based on surveys, interviews, field observations, and systematizing the data in the traditional weighting of the structuring aspects of the park. The results were obtained from the methodological design scheme of iterative analysis of public spaces by Jan Güell. It is concluded that the use of urban strategies in the structuring elements of the park, such as vegetation, furniture, generating new activities, and security interventions, will specifically solve all the problems of the Huancavilca Park tested in a Pareto 80/20 Diagram.

Keywords: public space, green areas, vegetation, street furniture, urban analysis

Procedia PDF Downloads 131

Authors: C. Rana, S. K. Jain

Abstract:

The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

Procedia PDF Downloads 396

Authors: Navya Saira George, Patroba Achola Odera

Abstract:

This study aims to determine spatio-temporal expansion of Kochi City, situated on the west coast of Kerala State in India. Remote sensing and GIS techniques have been used to determine land use/cover and urban expansion of the City. Classification of Landsat images of the years 1973, 1988, 2002 and 2018 have been used to reproduce a visual story of the growth of the City over a period of 45 years. Accuracy range of 0.79 ~ 0.86 is achieved with kappa coefficient range of 0.69 ~ 0.80. Results show that the areas covered by vegetation and water bodies decreased progressively from 53.0 ~ 30.1% and 34.1 ~ 26.2% respectively, while built-up areas increased steadily from 12.5 to 42.2% over the entire study period (1973 ~ 2018). The shift in land use from agriculture to non-agriculture may be attributed to the land reforms since 1980s.

Keywords: Geographical Information Systems, Kochi City, Land use/cover, Remote Sensing, Urban Sprawl

Procedia PDF Downloads 119

Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

Procedia PDF Downloads 178

Authors: Melaku Tsehay

Abstract:

The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

Procedia PDF Downloads 85

Authors: Ling Choo Chiew, Yoke Yong Chen, Chuong Hock Ting, Raveca Ak Ridi

Abstract:

Job frustration become a prevalent issue in many occupational settings and is linked to mental state, which affects workers when they face obstacles that block them from meeting professional objectives and/or the organization's mission. This study examined the relationship between job frustration and mental health among healthcare workers. A cross-sectional design using the Compassion Satisfaction and Fatigue test (CSF), Copenhagen Burnout Inventory (CBI), and Psychological Flexibility Questionnaire (PFQ) was employed to collect data from a sample of healthcare workers in Sarawak, Malaysia. The results showed that 44.3 % of the healthcare workers experienced compassion fatigue, 9.7% of the healthcare workers had personal burnt out, 3% were work-related burnt out, and 2% were client-related burnt out. On the other hand, the mean of psychological flexibility was 3.55 (SD = 0.838), which was found to be prevalent in the study sample, with varying degrees of severity. The results also indicated a significant association between compassion fatigue and psychological flexibility, F(₄, ₄₈₉) = 5.45, p<.001. Additionally, demographic factors were associated with higher levels of job frustration and burnout. The implications of these findings for developing targeted interventions and support strategies to promote mental well-being among healthcare workers are discussed.

Keywords: compassion fatigue, healthcare worker, job frustration, psychological flexibility

Procedia PDF Downloads 11

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 58

Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN-EmoRecII is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (mimic reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and mimic annotations.

Keywords: open multimodal emotion corpus, annotated labels, intelligent interaction

Procedia PDF Downloads 399

Authors: A. S. Lourens, B. Du Plooy

Abstract:

Across the world, initiatives have been introduced to encourage women to enter into and remain in engineering fields. However, research has shown that many women leave engineering or suffer a loss of self-esteem and self-confidence compared to their male counterparts. To address this problem, a South African comprehensive university developed a self-leadership intervention pilot study in 2013, aimed at improving the self-efficacy of its female engineering students and increasing retention rates. This paper is a qualitative, descriptive, and interpretive study of the rationale and operational aspects of the Women in Engineering Leadership Association’s (WELA) self-leadership workshop. The objectives of this paper are to provide a framework for the design of a self-leadership workshop and to provide insight into the process of developing such a workshop specifically for women engineering students at a South African university. Finally, the paper proposes an evaluation process for the pilot workshop, which also provides a framework to improve future workshops. It is anticipated that the self-leadership development framework will be applicable to other higher education institutions wishing to improve women engineering student’s feelings of self-efficacy and therefore retention rates of women in engineering.

Keywords: co-curricular interventions, self-efficacy, self-leadership, women in engineering

Procedia PDF Downloads 433

Authors: Matthieu-P. Schapranow

Abstract:

Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

Procedia PDF Downloads 476

Authors: Birmohan Singh, V.K.Jain

Abstract:

Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

Procedia PDF Downloads 472

Authors: Ç. Erdoğan, T. Turan

Abstract:

Pediatric cancer patients experience multiple distressing, challenges, physical symptom such as fatigue, pain, sleep disturbance, and balance impairment that continue years after treatment completion. In recent years, yoga is often used in children with cancer to cope with these symptoms. Yoga practice is defined as a unique physical activity that combines physical practice, breath work and mindfulness/meditation. Yoga is an increasingly popular mind-body practice also characterized as a mindfulness mode of exercise. This study aimed to evaluate the impact of yoga intervention of children with cancer. This article planned searching the literature in this field. It has been determined that individualized yoga is feasible and provides benefits for inpatient children, improves health-related quality of life, physical activity levels, physical fitness. After yoga program, children anxiety score decreases significantly. Additionally, individualized yoga is feasible for inpatient children receiving intensive chemotherapy. As a result, yoga is an alternative and complementary medicine that can be safely used in children with cancer.

Keywords: cancer treatment, children, nursing, yoga

Procedia PDF Downloads 210

Authors: Jill Hanass-Hancock, Bradley Carpenter, Samantha Willan, Kristin Dunkle

Abstract:

Access to quality health care for persons with disabilities is the litmus test in our strive toward universal health coverage. Persons with disabilities experience a variety of health disparities related to increased health risks, greater socioeconomic challenges, and persistent ableism in the provision of health care. In low- and middle-income countries, the support needed to address the diverse needs of persons with disabilities and close the gaps in inclusive and accessible health care can appear overwhelming to staff with little knowledge and tools available. An action-orientated disability inclusion toolkit for health facilities was developed through consensus-building consultations and field testing in South Africa. The co-creation of the toolkit followed a bottom-up approach with healthcare staff and persons with disabilities in two developmental cycles. In cycle one, a disability facility assessment tool was developed to increase awareness of disability accessibility and service delivery gaps in primary healthcare services in a simple and action-orientated way. In cycle two, an intervention menu was created, enabling staff to respond to identified gaps and improve accessibility and inclusion. Each cycle followed five distinct steps of development: a review of needs and existing tools, design of the draft tool, consensus discussion to adapt the tool, pilot-testing and adaptation of the tool, and identification of the next steps. The continued consultations, adaptations, and field-testing allowed the team to discuss and test several adaptations while co-creating a meaningful and feasible toolkit with healthcare staff and persons with disabilities. This approach led to a simplified tool design with ‘key elements’ needed to achieve universal health coverage: universal design of health facilities, reasonable accommodation, health care worker training, and care pathway linkages. The toolkit was adapted for paper or digital data entry, produces automated, instant facility reports, and has easy-to-use training guides and online modules. The cyclic approach enabled the team to respond to emerging needs. The pilot testing of the facility assessment tool revealed that healthcare workers took significant actions to change their facilities after an assessment. However, staff needed information on how to improve disability accessibility and inclusion, where to acquire accredited training, and how to improve disability data collection, referrals, and follow-up. Hence, intervention options were needed for each ‘key element’. In consultation with representatives from the health and disability sectors, tangible and feasible solutions/interventions were identified. This process included the development of immediate/low-cost and long-term solutions. The approach gained buy-in from both sectors, who called for including the toolkit in the standard quality assessments for South Africa’s health care services. Furthermore, the process identified tangible solutions for each ‘key element’ and highlighted where research and development are urgently needed. The cyclic and consultative approach enabled the development of a feasible facility assessment tool and a complementary intervention menu, moving facilities toward universal health coverage for and persons with disabilities in low- or better-resourced contexts while identifying gaps in the availability of interventions.

Keywords: public health, disability, accessibility, inclusive health care, universal health coverage

Procedia PDF Downloads 56

Authors: Bishakha Majumdar, Ranjeet Nambudiri

Abstract:

Considerable dichotomy exists in research regarding the role of optimism and self-efficacy in work and career outcomes. Optimism and self-efficacy are related to performance, commitment and engagement, but also are implicated in seeing opportunities outside the firm and switching jobs. There is absence of research capturing these opposing strands of findings in the same model and providing a holistic understanding of how the expectancy beliefs operate in case of the working professional. We attempt to bridge this gap by proposing that career-decision self-efficacy and career outcome expectations affect intention to quit through the competitive mediation pathways of internal and external marketability. This model provides a holistic picture of the role of career expectancy beliefs on career outcomes, by considering perceived career opportunities both inside and outside one’s present organization. The understanding extends the application of career expectancy beliefs in the context of career decision-making by the employed individual. Further, it is valuable for reconsidering the effectiveness of hiring and retention techniques used by a firm, as selection, rewards and training programs need to be supplemented by interventions that specifically strengthen the stability pathway.

Keywords: career decision self-efficacy, career outcome expectations, marketability, intention to quit, job mobility

Procedia PDF Downloads 618

Authors: Malgorzata Wojcik

Abstract:

Groups are a powerful and significant part of human development. They serve as major emergent microsocial structures in children’s and youth’s ecological system. During middle and secondary school, peer groups become a particularly salient influence. While they promote a range of prosocial and positive emotional and behavioral attributes, they can also elicit negative or antisocial attributes, effectively “bringing out the worst” in some individuals. The grounded theory approach was employed to guide data collection and analysis, as it allows for a deeper understanding of the group processes and students’ perspectives on complex intragroup relations. Students’ perspectives on bullying cases were investigated by observing daily interactions among those involved and interviewing 47 students. The results complement theories of labeling in bullying by showing that all students self-label themselves and find it difficult to break patterns of behaviors related to bullying, such as supporting the bully or not defending the victim. In terms of the practical implications, the findings indicate that it could be beneficial to use non-punitive, restorative anti-bullying interventions that implement peer influence to transform bullying relations by removing behavioral labels.

Keywords: bullying, peer group, victimization, class reputation

Procedia PDF Downloads 100