Search results for: subjective probability

Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Daniel Wachira

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The study aims to determine factors contributing to increasing rates of DFU among DM patients attending clinics in Nyahururu County referral hospital, Lakipia County. The study objectives include;- To determine the demographic factors contributing to increased rates of DFU among DM patients, determining the sociocultural factors that contribute to increased rates of DFU among DM patients and determining the health facility factors contributing to increased rates of DFU among DM patients attending DM clinic at Nyahururu county referral hospital, Laikipia County. This study will adopt a descriptive cross-sectional study design. It involves the collection of data at a one-time point without follow-up. This method is fast and inexpensive, there is no loss to follow up as the data is collected at one time point and associations between variables can be determined. The study population includes all DM patients with or without DFU. The sampling technique that will be used is the probability sampling method, a simple random method of sampling will be used. The study will employ the use of questionnaires to collect the required information. Questionnaires will be a research administered questionnaires. The questionnaire developed was done in consultation with other research experts (supervisor) to ensure reliability. The questionnaire designed will be pre-tested by hand delivering them to a sample 10% of the sample size at J.M Kariuki Memorial hospital, Nyandarua county and thereafter collecting them dully filled followed by refining of errors to ensure it is valid for collection of data relevant for this study. Refining of errors on the questionnaires to ensure it was valid for collection of data relevant for this study. Data collection will begin after the approval of the project. Questionnaires will be administered only to the participants who met the selection criteria by the researcher and those who agreed to participate in the study to collect key information with regard to the objectives of the study. The study's authority will be obtained from the National Commission of Science and Technology and Innovation. Permission will also be obtained from the Nyahururu County referral hospital administration staff. The purpose of the study will be explained to the respondents in order to secure informed consent, and no names will be written on the questionnaires. All the information will be treated with maximum confidentiality by not disclosing who the respondent was and the information.

Keywords: diabetes, foot ulcer, social factors, hospital factors

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Authors: Meenalochana Inguva

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The context: The Center for Preparatory study is one of the strongest and most vibrant academic teaching units of the Sultan Qaboos University (SQU). The Foundation Programme English Language (FPEL) is part of a larger foundation programme which was implemented at SQU in fall 2010. The programme has been designed to prepare the students who have been accepted to study in the university in order to achieve the required educational goals (the learning outcomes) that have been designed according to Oman Academic Standards and published by the Omani Authority for Academic Accreditation (OAAA) for the English language component. The curriculum: At the CPS, the English language curriculum is based on the learning outcomes drafted for each level. These learning outcomes guide the students in meeting what is expected of them by the end of each level. These six levels are progressive in nature and are seen as a continuum. The study: A periodic evaluation of language programmes is necessary to improve the quality of the programmes and to meet the set goals of the programmes. An evaluation may be carried out internally or externally depending on the purpose and context. A self-study programme was initiated at the beginning of spring semester 2015 with a team comprising a total of 11 members who worked with-in the assigned course areas (level and programme specific). Only areas specific to FPEL have been included in the study. The study was divided into smaller tasks and members focused on their assigned courses. The self-study primarily focused on analyzing the programme LOs, curriculum planning, materials used and their relevance against the GFP exit standards. The review team also reflected on the assessment methods and procedures followed to reflect on student learning. The team has paid attention to having standard criteria for assessment and transparency in procedures. A special attention was paid to the staging of LOs across levels to determine students’ language and study skills ability to cope with higher level courses. Findings: The findings showed that most of the LOs are met through the materials used for teaching. Students score low on objective tests and high on subjective tests. Motivated students take advantage of academic support activities others do not utilize the student support activities to their advantage. Reading should get more hours. In listening, the format of the listening materials in CT 2 does not match the test format. Some of the course materials need revision. For e.g. APA citation, referencing etc. No specific time is allotted for teaching grammar Conclusion: The findings resulted in taking actions in bridging gaps. It will also help the center to be better prepared for the external review of its FPEL curriculum. It will also provide a useful base to prepare for the self-study portfolio for GFP standards assessment and future audit.

Keywords: curriculum planning, learning outcomes, reflections, self-evaluation

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Authors: Zena F. Mushtaq, Iqbal M. Abbas

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Background: Diabetes mellitus during pregnancy is one of the major medical and social problems with increasing prevalence in last decades and may lead to more vulnerable to dental problems and increased risk for periodontal diseases. Objectives: To assess oral hygiene behaviors among pregnant women with diabetes who attended primary health care centers and find out the relationship between oral hygiene behaviors and studied variables. Methodology: A cross sectional design was conducted from 7 July to 30 September 2014 on non probability (convenient sample) of 150 pregnant women with diabetes was selected from twelve Primary Health Care Centers at Baghdad city. Questionnaire format is tool for data collection which had designed and consisted of three main parts including: socio demographic, reproductive characteristics and items of oral hygiene behaviors among pregnant women with diabetes. Reliability of the questionnaire was determined through internal consistency of correlation coefficient (R= 0.940) and validity of content was determined through reviewing it by (12) experts in different specialties and was determined through pilot study. Descriptive and inferential statistics were used to analyze collected data. Result: Result of study revealed that (35.3%) of study sample was (35-39) years old with mean and SD is (X & SD = 33.57 ± 5.54) years, and (34.7%) of the study sample was graduated from primary school and less, half of the study sample was government employment and self employed, (42.7%) of the study sample had moderate socioeconomic status, the highest percentage (70.0%) of the study sample was nonsmokers, The result indicates that oral hygiene behaviors have moderate mean score in all items. There are no statistical significant association between oral hygiene domain and studied variables. Conclusions: All items related to health behavior concerning oral hygiene is in moderate mean of score, which may expose pregnant women with diabetes to high risk of periodontal diseases. Recommendations: Dental care provider should perform a dental examination at least every three months for each pregnant woman with diabetes, explanation of the effect of DM on periodontal health, oral hygiene instruction, oral prophylaxis, professional cleaning and treatment of periodontal diseases(scaling and root planing) when needed.

Keywords: diabetes, health behavior, pregnant women, oral hygiene

Procedia PDF Downloads 287

Authors: Ireen Manase Kabembo, Patrick Chanda

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Background: Substance use disorders are among the chronic conditions that affect all age groups. Worldwide, there is an increase in young people affected by SUDs, which implies that more family members are transitioning into the caregiver role. Family caregivers play a buffering role in the formal healthcare system due to their involvement in caring for persons with acute and chronic conditions in the home setting. Family carers of youth with problematic alcohol and marijuana use experience myriad challenges in managing daily care for this medically vulnerable group. In addition, the poor health-seeking behaviours of youth with SUDs characterized by eluding treatment and runaway tendencies coupled with the effects of the pandemic made caregiving a daunting task for most family caregivers. Issues such as limited and unavailable psychotropic medications, social stigma and discrimination, financial hurdles, systemic barriers in adolescent and young adult mental healthcare services, and the lack of a perceived vulnerability to Covid-19 by youth with SUDs are experiences of family caretakers. Methods: A qualitative study with 30 family caregivers of youth aged 16-24 explored their lived experiences and subjective meanings using two in-depth semi-structured interviews, a caregiving timeline, and participant observation. Findings: Results indicate that most family caregivers had challenges managing care for treatment elusive youth, let alone having them adhere to Covid-19 regulations. However, youth who utilized healthcare services and adhered to treatment regimens had positive outcomes and sustained recovery. The effects of the pandemic, such as job losses and the closure of businesses, further exacerbated the financial challenges experienced by family caregivers, making it difficult to purchase needed medications and daily necessities for the youth. The unabated stigma and discrimination of families of substance-dependent youth in Zambian communities further isolated family caregivers, leaving them with limited support. Conclusion: Since young people with SUDs have a compromised mental capacity due to the cognitive impairments that come with continued substance abuse, they often have difficulties making sound judgements, including the need to utilize SUD recovery services. Also, their tendency to not adhere to the Covid-19 pandemic requirements places them at a higher risk for adverse health outcomes in the (post) pandemic era. This calls for urgent implementation of robust youth mental health services that address prevention and recovery for these emerging adults grappling with substance use disorders. Support for their family caregivers, often overlooked, cannot be overemphasized.

Keywords: chronic care management, Covid-19 pandemic, family caregivers, youth with substance use disorders

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Authors: Davod Ahmadigheidari, Isabel Alvarez, Kate Sinclair, Marnie Davidson, Patrick Cortbaoui, Hugo Melgar-Quiñonez

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The burden of collecting water tends to disproportionately fall on women and girls in low-income countries. Specifically, women spend between one to eight hours per day fetching water for domestic use in Sub-Saharan Africa. While there has been research done on the global time burden for collecting water, it has been mainly focused on water quality parameters; leaving the relationship between water fetching and health outcomes understudied. There is little available evidence regarding the relationship between water fetching and maternal child care practices. The main objective of this study was to help fill the aforementioned gap in the literature. Data from two surveys in Ethiopia and Malawi conducted by CARE Canada in 2016-2017 were used. Descriptive statistics indicate that women were predominantly responsible for collecting water in both Ethiopia (87%) and Malawi (99%) respectively, with the majority spending more than 30 minutes per day on water collection. With regards to child care practices, in both countries, breastfeeding was relatively high (77% and 82%, respectively); and treatment for malnutrition was low (15% and 8%, respectively). However, the same consistency was not found for weighing; in Ethiopia only 16% took their children for weighting in contrast to 94% in Malawi. These three practices were summed to create one variable for regressions analyses. Unadjusted logistic regression findings showed that only in Ethiopia was time fetching water significantly associated with child care practices. Once adjusted for covariates, this relationship was no longer found to be significant. Adjusted logistic regressions also showed that the factors that did influence child care practices differed slightly between the two countries. In Ethiopia, a lack of access to community water supply (OR= 0.668; P=0.010), poor attitudes towards gender equality (OR= 0.608; P=0.001), no access to land and (OR=0.603; P=0.000), significantly decreased a women’s odd of using positive childcare practices. Notably, being young women between 15-24 years (OR=2.308; P=0.017), and 25-29 (OR=2.065; P=0.028) increased probability of using positive childcare practices. Whereas in Malawi, higher maternal age, low decision-making power, significantly decreased a women’s odd of using positive childcare practices. In conclusion, this study found that even though amount of time spent by women fetching water makes a difference for childcare practices, it is not significantly related to women’s child care practices when controlling the covariates. Importantly, women’s age contributes to child care practices in Ethiopia and Malawi.

Keywords: time fetching water, community water supply, women’s child care practices, Ethiopia, Malawi

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Authors: Shahid Ali

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Leadership and management are essential components of running successful organizations. Both concepts are closely related but serve different purposes in the overall management of a company. Leadership focuses on inspiring and motivating employees towards a common goal, while management involves coordinating and directing resources to achieve organizational objectives efficiently. Objectives of Leadership and Management: Inspiring and motivating employees: A key objective of leadership is to inspire and motivate employees to work towards achieving the organization’s goals. Effective leaders create a vision that employees can align with and provide the necessary motivation to drive performance. Setting goals and objectives: Both leadership and management play a crucial role in setting goals and objectives for the organization. Leaders create a vision for the future, while managers develop plans to achieve specific objectives within the given timeframe. Implementing strategies: Leaders come up with innovative strategies to drive the organization forward, while managers are responsible for implementing these strategies effectively. Together, leadership and management ensure that the organization’s plans are executed efficiently. Contributions of Leadership and Management: Employee Engagement: Effective leadership and management can increase employee engagement and satisfaction. When employees feel motivated and inspired by their leaders, they are more likely to be engaged in their work and contribute to the organization’s success. Organizational Success: Good leadership and management are essential for navigating the challenges and changes that organizations face. By setting clear goals, inspiring employees, and making strategic decisions, leaders and managers can drive organizational success. Talent Development: Leaders and managers are responsible for identifying and developing talent within the organization. By providing feedback, training, and coaching, they can help employees reach their full potential and contribute effectively to the organization. Research Type: The research on leadership and management is typically quantitative and qualitative in nature. Quantitative research involves the collection and analysis of numerical data to understand the impact of leadership and management practices on organizational outcomes. This type of research often uses surveys, questionnaires, and statistical analysis to measure variables such as employee satisfaction, performance, and organizational success. Qualitative research, on the other hand, involves exploring the subjective experiences and perspectives of individuals related to leadership and management. This type of research may include interviews, observations, and case studies to gain a deeper understanding of how leadership and management practices influence organizational behavior and outcomes. In conclusion, leadership and management play a critical role in the success of organizations. Through effective leadership and management practices, organizations can inspire and motivate employees, set goals, and implement strategies to achieve their objectives. Research on leadership and management helps to understand the impact of these practices on organizational outcomes and provides valuable insights for improving leadership and management practices in the future.

Keywords: empowering, leadership, management, adaptability

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Authors: Maggie Hui

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Risk management is not a new concept; however, it is an uncharted area as applied to the translation process and translator training. Risk managers are responsible for managing risk, i.e. adopting strategies with the intention to minimize loss and maximize gains in spite of uncertainty. Which risk strategy to use often depends on the frequency of an event (i.e. probability) and the severity of its outcomes (i.e. impact). This is basically the way translation/localization project managers handle risk management. Although risk management could involve both positive and negative impacts, impact seems to be always negative in professional translators’ management models, e.g. how many days of project time are lost or how many clients are lost. However, for analysis of translation performance, the impact should be possibly positive (e.g. increased readability of the translation) or negative (e.g. loss of source-text information). In other words, the straight business model of risk management is not directly applicable to the study of risk management in the rendition process. This research aims to explore trainee translators’ risk managing while translating in a simulated setting that involves translator-client relations. A two-cycle experiment involving two roles, the translator and the simulated client, was carried out with a class of translation students to test the effects of the main variable of peer-group interaction. The researcher made use of a user-friendly screen-voice recording freeware to record subjects’ screen activities, including every word the translator typed and every change they made to the rendition, the websites they browsed and the reference tools they used, in addition to the verbalization of their thoughts throughout the process. The research observes the translation procedures subjects considered and finally adopted, and looks into the justifications for their procedures, in order to interpret their risk management. The qualitative and quantitative results of this study have some implications for translator training: (a) the experience of being a client seems to reinforce the translator’s risk aversion; (b) there is a wide gap between the translator’s internal risk management and their external presentation of risk; and (c) the use of role-playing simulation can empower students’ learning by enhancing their attitudinal or psycho-physiological competence, interpersonal competence and strategic competence.

Keywords: risk management, role-playing simulation, translation pedagogy, translator-client relations

Procedia PDF Downloads 261

Authors: Mehran Barani Shikhrobat, Roger Flanagan

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The construction planning and scheduling based on using the current tools and techniques is resulted deterministic in nature (Gantt chart, CPM) or applying a very little probability of completion (PERT) for each task. However, every project embodies assumptions and influences and should start with a complete set of clearly defined goals and constraints that remain constant throughout the duration of the project. Construction planners continue to apply the traditional methods and tools of “hard” project management that were developed for “ideal projects,” neglecting the potential influence of complexity on the design and construction process. The aim of this research is to investigate the emergence and growth of complexity in project planning and to provide a model to consider the influence of complexity on the total project duration at the post-contract award pre-construction stage of a project. The literature review showed that complexity originates from different sources of environment, technical, and workflow interactions. They can be divided into two categories of complexity factors, first, project tasks, and second, project organisation management. Project tasks may originate from performance, lack of resources, or environmental changes for a specific task. Complexity factors that relate to organisation and management refer to workflow and interdependence of different parts. The literature review highlighted the ineffectiveness of traditional tools and techniques in planning for complexity. However, this research focus on understanding the fundamental causes of the complexity of construction projects were investigated through a questionnaire with industry experts. The results were used to develop a model that considers the core complexity factors and their interactions. System dynamics were used to investigate the model to consider the influence of complexity on project planning. Feedback from experts revealed 20 major complexity factors that impact project planning. The factors are divided into five categories known as core complexity factors. To understand the weight of each factor in comparison, the Analytical Hierarchy Process (AHP) analysis method is used. The comparison showed that externalities are ranked as the biggest influence across the complexity factors. The research underlines that there are many internal and external factors that impact project activities and the project overall. This research shows the importance of considering the influence of complexity on the project master plan undertaken at the post-contract award pre-construction phase of a project.

Keywords: project planning, project complexity measurement, planning uncertainty management, project risk management, strategic project scheduling

Procedia PDF Downloads 138

Authors: Rayanne Branco Dos Santos Lima, Lorena Pinheiro Barbosa, Kamila Ferreira Lima, Victor Manuel Tegoma Ruiz, Monyka Brito Lima Dos Santos, Maria Wendiane Gueiros Gaspar, Luzia Camila Coelho Ferreira, Leandro Cardozo Dos Santos Brito, Deyse Maria Alves Rocha

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Introduction: The lack of regulation of the baby's sleep-wake pattern in the first years of life affects the health of thousands of women. Maternal sleep deprivation can trigger or aggravate psychosomatic problems such as depression, anxiety and stress that can directly influence maternal safety, with consequences for the baby's and mother's sleep. Such conditions can affect the family's quality of life and child development. Objective: To correlate maternal security with maternal state anxiety scores and the mother's and baby's total sleep time. Method: Cross-sectional study carried out with 96 mothers of babies aged 10 to 24 months, accompanied by nursing professionals linked to a Federal University in Northeast Brazil. Study variables were maternal security, maternal state anxiety scores, infant latency and sleep time, and total nocturnal sleep time of mother and infant. Maternal safety was calculated using a four-point Likert scale (1=not at all safe, 2=somewhat safe, 3=very safe, 4=completely safe). Maternal anxiety was measured by State-Trait Anxiety Inventory, state-anxiety subscale whose scores vary from 20 to 80 points, and the higher the score, the higher the anxiety levels. Scores below 33 are considered mild; from 33 to 49, moderate and above 49, high. As for the total nocturnal sleep time, values between 7-9 hours of sleep were considered adequate for mothers, and values between 9-12 hours for the baby, according to the guidelines of the National Sleep Foundation. For the sleep latency time, a time equal to or less than 20 min was considered adequate. It is noteworthy that the latency time and the time of night sleep of the mother and the baby were obtained by the mother's subjective report. To correlate the data, Spearman's correlation was used in the statistical package R version 3.6.3. Results: 96 women and babies participated, aged 22 to 38 years (mean 30.8) and 10 to 24 months (mean 14.7), respectively. The average of maternal security was 2.89 (unsafe); Mean maternal state anxiety scores were 43.75 (moderate anxiety). The babies' average sleep latency time was 39.6 min (>20 min). The mean sleep times of the mother and baby were, respectively, 6h and 42min and 8h and 19min, both less than the recommended nocturnal sleep time. Maternal security was positively correlated with maternal state anxiety scores (rh=266, p=0.009) and negatively correlated with infant sleep latency (rh= -0.30. P=0.003). Baby sleep time was positively correlated with maternal sleep time. (rh 0.46, p<0.001). Conclusion: The more secure the mothers considered themselves, the higher the anxiety scores and the shorter the baby's sleep latency. Also, the longer the baby sleeps, the longer the mother sleeps. Thus, interventions are needed to promote the quality and efficiency of sleep for both mother and baby.

Keywords: sleep, anxiety, infant, mother-child relations

Procedia PDF Downloads 102

Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Jochen Nelles, Susanne Kohns, Julia Spies, Friederike Schmitz-Buhl, Roland Thietje, Christopher Brandl, Alexander Mertens, Christopher M. Schlick

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Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.

Keywords: assistance robot, human-robot interaction, motion capture, stress-strain-concept, surface electromyography, tetraplegia

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Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

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In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

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Authors: Asowata Osamede

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Optimized gain in respect to output power of stand-alone photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident to its low carbon emission and efficiency. Power failure or outage from commercial providers in general does not promote development to the public and private sector, these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost-effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with MPPT from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0o north, with a corresponding tilt angle of 36 o, 26o and 16o. The load employed in this set-up are three Lead Acid Batteries (LAB). The percentage fully charged, charging and not charging conditions are observed for all three batteries. The results obtained in this research is used to draw the conclusion that would provide a benchmark for researchers and scientist worldwide. This is done so as to have an idea of the best tilt and orientation angles for maximum power point in a basic off-grid PV system. A quantitative analysis would be employed in this research. Quantitative research tends to focus on measurement and proof. Inferential statistics are frequently used to generalize what is found about the study sample to the population as a whole. This would involve: selecting and defining the research question, deciding on a study type, deciding on the data collection tools, selecting the sample and its size, analyzing, interpreting and validating findings Preliminary results which include regression analysis (normal probability plot and residual plot using polynomial 6) showed the maximum power point in the system. The best tilt angle for maximum power point tracking proves that the 36o tilt angle provided the best average on time which in turns put the system into a pulse width modulation stage.

Keywords: power-conversion, meteonorm, PV panels, DC-DC converters

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Authors: Krupali Mukeshkumar, Jinesh Shah

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Background: Bilateral Sagittal Split Osteotomy (BSSO), used for the correction of mandibular deformities, is a common oral and maxillofacial surgical procedure. Inferior alveolar nerve dysfunction is commonly reported post-operatively by patients as paresthesia or anesthesia. The current literature lacks a consensus on the incidence of inferior alveolar nerve dysfunction as patients are not routinely assessed pre and post-operatively with an objective assessment. The range of incidence varies from 9% to 85% of patients, with some authors arguing that 100% of patients experience nerve dysfunction immediately post-surgery. Systematic reviews have shown a difference between incidence rates at different follow-up periods using objective and subjective methods. Aim: To identify the incidence of inferior alveolar nerve dysfunction following BSSO. Gold standard: Nerve dysfunction incidence rates similar or lower than current literature of 83% day one post-operatively and 18.4% at one year follow up. Setting: A retrospective cross-sectional audit of patients treated between 2017-2019 at the Royal Stoke University Hospital, Maxillofacial and Orthodontic departments. Sample: All patients who underwent a BSSO (with or without le fort one osteotomy) between 2017–2019 were identified from the database. Patients with pre-existing neurosensory disturbance, those who had a genioplasty at the same time and those with no follow-up were excluded. The sample consisted of 121 patients, 37 males and 84 females between the ages of 17-50 years at the time of surgery. Methods: Clinical records of 121 cases were reviewed to assess the age, sex, type of mandibular osteotomy, status of the nerve during the surgical procedure, type of bony split and incidence of nerve dysfunction at follow-up appointments. The surgical procedure was carried out by three Maxillo-facial surgeons and follow-up appointments were carried out in the Orthodontic and Oral and Maxillo-facial departments. Results: 120 patients were treated to correct the mandibular facial deformity and 1 patient was treated for sleep apnoea. Seventeen patients had a mandibular setback and 104 patients had mandibular advancement. 68 patients reported inferior alveolar nerve dysfunction at one week following their surgery. Seventy-six patients had temporary paresthesia present between 2 weeks and 12 months post-surgery. 13 patients had persistent nerve dysfunction at 12 months, of which 1 had a bad bony split during the BSSO. The incidence of nerve dysfunction postoperatively was 6.6% after 1 day, 56.1% at 1 week, 62.8% at 2 weeks, 59.5% between 3-6 weeks, 43.0% between 8-16 weeks and 10.7% at 1 year. Conclusions: The results of this audit show a similar incidence rate to the research gold standard at the one-year follow-up. Future Recommendations: No changes to surgical procedure or technique are indicated, but a need for improved documentation and a standardized approach for assessment of post-operative nerve dysfunction would be beneficial.

Keywords: bilateral sagittal split osteotomy, inferior alveolar nerve, mandible, nerve dysfunction

Procedia PDF Downloads 237

Authors: Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii

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Today dairy farm experts and farmers have well recognized the importance of dairy cow Body Condition Score (BCS) since these scores can be used to optimize milk production, managing feeding system and as an indicator for abnormality in health even can be utilized to manage for having healthy calving times and process. In tradition, BCS measures are done by animal experts or trained technicians based on visual observations focusing on pin bones, pin, thurl and hook area, tail heads shapes, hook angles and short and long ribs. Since the traditional technique is very manual and subjective, the results can lead to different scores as well as not cost effective. Thus this paper proposes an algebraic geometric imaging approach for an automatic dairy cow BCS system. The proposed system consists of three functional modules. In the first module, significant landmarks or anatomical points from the cow image region are automatically extracted by using image processing techniques. To be specific, there are 23 anatomical points in the regions of ribs, hook bones, pin bone, thurl and tail head. These points are extracted by using block region based vertical and horizontal histogram methods. According to animal experts, the body condition scores depend mainly on the shape structure these regions. Therefore the second module will investigate some algebraic and geometric properties of the extracted anatomical points. Specifically, the second order polynomial regression is employed to a subset of anatomical points to produce the regression coefficients which are to be utilized as a part of feature vector in scoring process. In addition, the angles at thurl, pin, tail head and hook bone area are computed to extend the feature vector. Finally, in the third module, the extracted feature vectors are trained by using Markov Classification process to assign BCS for individual cows. Then the assigned BCS are revised by using multiple regression method to produce the final BCS score for dairy cows. In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.

Keywords: algebraic geometric imaging approach, body condition score, Markov classification, polynomial regression

Procedia PDF Downloads 158

Authors: Valdir Moura, Raniele dos Anjos de Souza, Fernando Gomes de Souza, Jose Vagner da Silva, Jerry Adriani Johann

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The estimate of the Area of Land to be planted with annual crops and its stratification by the municipality are important variables in crop forecast. Nowadays in Brazil, these information’s are obtained by the Brazilian Institute of Geography and Statistics (IBGE) and published under the report Assessment of the Agricultural Production. Due to the high cloud cover in the main crop growing season (October to March) it is difficult to acquire good orbital images. Thus, one alternative is to work with remote sensing data from dates before the crop growing season. This work presents the use of multitemporal Landsat data gathered on July and September (before the summer growing season) in order to estimate the area of land to be planted with summer crops in an area of São Paulo State, Brazil. Geographic Information Systems (GIS) and digital image processing techniques were applied for the treatment of the available data. Supervised and non-supervised classifications were used for data in digital number and reflectance formats and the multitemporal Normalized Difference Vegetation Index (NDVI) images. The objective was to discriminate the tracts with higher probability to become planted with summer crops. Classification accuracies were evaluated using a sampling system developed basically for this study region. The estimated areas were corrected using the error matrix derived from these evaluations. The classification techniques presented an excellent level according to the kappa index. The proportion of crops stratified by municipalities was derived by a field work during the crop growing season. These proportion coefficients were applied onto the area of land to be planted with summer crops (derived from Landsat data). Thus, it was possible to derive the area of each summer crop by the municipality. The discrepancies between official statistics and our results were attributed to the sampling and the stratification procedures. Nevertheless, this methodology can be improved in order to provide good crop area estimates using remote sensing data, despite the cloud cover during the growing season.

Keywords: area intended for summer culture, estimated area planted, agriculture, Landsat, planting schedule

Procedia PDF Downloads 150

Authors: W. Staiano, S. Marcora

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Introduction: It has been proposed that acute negative effect of mental fatigue (MF) could potentially become a training stimulus for the brain (Brain endurance training (BET)) to adapt and improve its ability to attenuate MF states during sport competitions. Purpose: The aim of this study was to test the efficacy of 6 weeks of BET on cognitive and cycling tests in a group of well-trained subjects. We hypothesised that combination of BET and standard physical training (SPT) would increase cognitive capacity and cycling performance by reducing rating of perceived exertion (RPE) and increase resilience to fatigue more than SPT alone. Methods: In a randomized controlled trial design, 26 well trained participants, after a familiarization session, cycled to exhaustion (TTE) at 80% peak power output (PPO) and, after 90 min rest, at 65% PPO, before and after random allocation to a 6 week BET or active placebo control. Cognitive performance was measured using 30 min of STROOP coloured task performed before cycling performance. During the training, BET group performed a series of cognitive tasks for a total of 30 sessions (5 sessions per week) with duration increasing from 30 to 60 min per session. Placebo engaged in a breathing relaxation training. Both groups were monitored for physical training and were naïve to the purpose of the study. Physiological and perceptual parameters of heart rate, lactate (LA) and RPE were recorded during cycling performances, while subjective workload (NASA TLX scale) was measured during the training. Results: Group (BET vs. Placebo) x Test (Pre-test vs. Post-test) mixed model ANOVA’s revealed significant interaction for performance at 80% PPO (p = .038) or 65% PPO (p = .011). In both tests, groups improved their TTE performance; however, BET group improved significantly more compared to placebo. No significant differences were found for heart rate during the TTE cycling tests. LA did not change significantly at rest in both groups. However, at completion of 65% TTE, it was significantly higher (p = 0.043) in the placebo condition compared to BET. RPE measured at ISO-time in BET was significantly lower (80% PPO, p = 0.041; 65% PPO p= 0.021) compared to placebo. Cognitive results in the STROOP task showed that reaction time in both groups decreased at post-test. However, BET decreased significantly (p = 0.01) more compared to placebo despite no differences accuracy. During training sessions, participants in the BET showed, through NASA TLX questionnaires, constantly significantly higher (p < 0.01) mental demand rates compared to placebo. No significant differences were found for physical demand. Conclusion: The results of this study provide evidences that combining BET and SPT seems to be more effective than SPT alone in increasing cognitive and cycling performance in well trained endurance participants. The cognitive overload produced during the 6-week training of BET can induce a reduction in perception of effort at a specific power, and thus improving cycling performance. Moreover, it provides evidence that including neurocognitive interventions will benefit athletes by increasing their mental resilience, without affecting their physical training load and routine.

Keywords: cognitive training, perception of effort, endurance performance, neuro-performance

Procedia PDF Downloads 120

Authors: Jakob Krause

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Past Financial Crisis has shown that contemporary risk management models provide an unjustified sense of security and fail miserably in situations in which they are needed the most. In this paper, we start from the assumption that risk is a notion that changes over time and therefore past data points only have limited explanatory power for the current situation. Our objective is to derive the optimal amount of representative information by optimizing between the two adverse forces of estimator convergence, incentivizing us to use as much data as possible, and the aforementioned non-representativeness doing the opposite. In this endeavor, the cornerstone assumption of having access to identically distributed random variables is weakened and substituted by the assumption that the law of the data generating process changes over time. Hence, in this paper, we give a quantitative theory on how to perform statistical analysis in non-ergodic systems. As an application, we discuss the impact of a paragraph in the last iteration of proposals by the Basel Committee on Banking Regulation. We start from the premise that the severity of assumptions should correspond to the robustness of the system they describe. Hence, in the formal description of physical systems, the level of assumptions can be much higher. It follows that every concept that is carried over from the natural sciences to economics must be checked for its plausibility in the new surroundings. Most of the probability theory has been developed for the analysis of physical systems and is based on the independent and identically distributed (i.i.d.) assumption. In Economics both parts of the i.i.d. assumption are inappropriate. However, only dependence has, so far, been weakened to a sufficient degree. In this paper, an appropriate class of non-stationary processes is used, and their law is tied to a formal object measuring representativeness. Subsequently, that data set is identified that on average minimizes the estimation error stemming from both, insufficient and non-representative, data. Applications are far reaching in a variety of fields. In the paper itself, we apply the results in order to analyze a paragraph in the Basel 3 framework on banking regulation with severe implications on financial stability. Beyond the realm of finance, other potential applications include the reproducibility crisis in the social sciences (but not in the natural sciences) and modeling limited understanding and learning behavior in economics.

Keywords: banking regulation, non-ergodicity, risk management, semimartingale modeling

Procedia PDF Downloads 148

Authors: Miriam Schiff, Hadas Rosenne, Ran Nir-Paz, Shiri Shinan Altman

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To examine (1) the level, predictors, and subjective perception of professional quality of life (PRoQL), posttraumatic growth, roles, task changes during the pandemic, and perceived preparedness for the next pandemic. These variables were added as part of an international study on social workers in healthcare stress, resilience, and perceived preparedness we took part in, along with Australia, Canada, China, Hong Kong, Singapore, and Taiwan. (2) The extent to which background variables, rate of exposure to the virus, working in COVID wards, profession, personal resilience, and resistance to organizational change predict posttraumatic growth, perceived preparedness, and PRoQL (the latter was examined among social workers only). (3) The teams' perceptions of how the pandemic impacted them at the personal, professional, and organizational levels and what assisted them. Methodologies: Mixed quantitative and qualitative methods were used. 1039 hospital healthcare workers from various professions participated in the quantitative study while 32 participated in in-depth interviews. The same methods were used in six other countries. Findings: The level of PRoQL was moderate, with higher burnout and secondary traumatization level than during routine times. Differences between countries in the level of PRoQL were found as well. Perceived preparedness for the next pandemic at the personal level was moderate and similar among the different health professions. Higher exposure to the virus was associated with lower perceived preparedness of the hospitals. Compared to other professions, doctors and nurses perceived hospitals as significantly less prepared for the next pandemic. The preparedness of the State of Israel for the next pandemic is perceived as low by all healthcare professionals. A moderate level of posttraumatic growth was found. Staff who worked at the COVID ward reported a greater level of growth. Doctors reported the lowest level of growth. The staff's resilience was high, with no differences among professions or levels of exposure. Working in the COVID ward and resilience predicted better preparedness, while resistance to organizational change predicted worse preparedness. Findings from the qualitative part of the study revealed that healthcare workers reported challenges at the personal, professional and organizational level during the different waves of the pandemic. They also report on internal and external resources they either owned or obtained during that period. Conclusion: Exposure to the COVID-19 virus is associated with secondary traumatization on one hand and personal posttraumatic growth on the other hand. Personal and professional discoveries and a sense of mission helped cope with the pandemic that was perceived as a historical event, war, or mass casualty event. Personal resilience, along with the support of colleagues, family, and direct management, were seen as significant components of coping. Hospitals should plan ahead and improve their preparedness to the next pandemic.

Keywords: covid-19, health-care, social workers, burnout, preparedness, international perspective

Procedia PDF Downloads 74

Authors: Venkat Kamavaram, Ravi Pare

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Modern warfighters experience extreme environmental conditions in many of their operational and training activities. In temperatures exceeding 95°F, the body’s temperature regulation can no longer cool through convection and radiation. In this case, the only cooling mechanism is evaporation. However, evaporative cooling is often compromised by excessive humidity. Natural cooling mechanisms can be further compromised by clothing and protective gear, which trap hot air and moisture close to the body. Creating an efficient heat extraction apparel system that is also lightweight without hindering dexterity or mobility of personnel working in extreme temperatures is a difficult technical challenge and one that needs to be addressed to increase the probability for the future success of the US military. To address this challenge, Oceanit Laboratories, Inc. has developed and patented a Liquid Cooled Garment (LCG) more effective than any on the market today. Oceanit’s LCG is a form-fitting garment with a network of thermally conductive tubes that extracts body heat and can be worn under all authorized and chemical/biological protective clothing. Oceanit specifically designed and developed ThermoCore®, a thermally conductive polymer, for use in this apparel, optimizing the product for thermal conductivity, mechanical properties, manufacturability, and performance temperatures. Thermal Manikin tests were conducted in accordance with the ASTM test method, ASTM F2371, Standard Test Method for Measuring the Heat Removal Rate of Personal Cooling Systems Using a Sweating Heated Manikin, in an environmental chamber using a 20-zone sweating thermal manikin. Manikin test results have shown that Oceanit’s LCG provides significantly higher heat extraction under the same environmental conditions than the currently fielded Environmental Control Vest (ECV) while at the same time reducing the weight. Oceanit’s LCG vests performed nearly 30% better in extracting body heat while weighing 15% less than the ECV. There are NO cooling garments in the market that provide the same thermal extraction performance, form-factor, and reduced weight as Oceanit’s LCG. The two cooling garments that are commercially available and most commonly used are the Environmental Control Vest (ECV) and the Microclimate Cooling Garment (MCG).

Keywords: thermally conductive composite, tubing, garment design, form fitting vest, thermocore

Procedia PDF Downloads 115

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

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Predicting the risk of diabetic retinopathy (DR) in Indian type 2 diabetes patients is immensely necessary. India, being the second largest country after China in terms of a number of diabetic patients, to the best of our knowledge not a single risk score for complications has ever been investigated. Diabetic retinopathy is a serious complication and is the topmost reason for visual impairment across countries. Any type or form of DR has been taken as the event of interest, be it mild, back, grade I, II, III, and IV DR. A sample was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of DR. Cox proportional hazard regression is used to design risk scores for the prediction of retinopathy. Model calibration and discrimination are assessed from Hosmer Lemeshow and area under receiver operating characteristic curve (ROC). Overfitting and underfitting of the model are checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Optimal cut off point is chosen by Youden’s index. Five-year probability of DR is predicted by both survival function, and Markov chain two state model and the better technique is concluded. The risk scores developed can be applied by doctors and patients themselves for self evaluation. Furthermore, the five-year probabilities can be applied as well to forecast and maintain the condition of patients. This provides immense benefit in real application of DR prediction in T2DM.

Keywords: Cox proportional hazard regression, diabetic retinopathy, ROC curve, type 2 diabetes mellitus

Procedia PDF Downloads 186

Authors: Stephens Oluyemi Adetunji, Nel Norma Margaret, Naidu Narainsamy

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Empathy has been identified by researchers to be a crucial factor in helping adolescents to refrain from delinquent behavior. Adolescent delinquent behavior is a social problem that has become a source of concern to parents, psychologists, educators, correctional services, researchers as well as governments of nations. Empathy is a social skill that enables an individual to understand and to share another’s emotional state. An individual with a high level of empathy will avoid any act or behavior that will affect another person negatively. The need for this study is predicated on the fact that delinquent adolescent behavior could lead to adult criminality. This, in the long run, has the potential of resulting in an increase in crime rate thereby threatening public safety. It has therefore become imperative to explore the level of empathy of delinquent adolescents who have committed crime and are awaiting trial. It is the conjecture of this study that knowledge of the empathy level of delinquent adolescents will provide an opportunity to design an intervention strategy to remediate the deficit. This study was therefore designed to determine the level of empathy of delinquent adolescents. In addition, this study provides a better understanding of factors that may prevent adolescents from developing delinquent behavior, in this case, delinquents’ empathy levels. In the case of participants who have a low level of empathy, remediation strategies to improve their empathy level would be designed. Two research questions were raised to guide this study. A mixed methods research design was employed for the study. The sample consists of fifteen male adolescents who are between 13-18 years old with a mean age of 16.5 years old. The participants are adolescents who are awaiting trial. The non-probability sampling technique was used to obtain the sample for the quantitative study while purposive sampling was used in the case of the qualitative study. A self–report questionnaire and structured interview were used to assess the level of empathy of participants. The data obtained was analysed using the simple percentages for the quantitative data and transcribing the qualitative data. The result indicates that most of the participants have low level of empathy. It is also revealed that there is a difference in the empathy level on the basis of whether they are from parents living together and those whose parents are separated. Based on the findings of this study, it is recommended that the level of empathy of participants be improved through training and emphasizing the importance of stimulating family environment for children. It is also recommended that programs such as youth mentoring and youth sheltering be established by the government of South Africa to address the menace of delinquent adolescents.

Keywords: adolescents, behavior, delinquents, empathy

Procedia PDF Downloads 462

Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

Procedia PDF Downloads 330

Authors: M. Zasada, A. Markiewicz, A. Erkiert-Polguj, E. Budzisz

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The epidermis is a keratinized stratified squamous epithelium covered by the hydro-lipid barrier. Therefore, active substances should be able to penetrate through this hydro-lipid coating. L-ascorbic acid is one of the vitamins which plays an important role in stimulation fibroblast to produce collagen type I and in hyperpigmentation lightening. Vitamin C is a water-soluble antioxidant, which protects skin from oxidation damage and rejuvenates photoaged skin. No-needle mesotherapy is a non-invasive rejuvenation technique depending on electric pulses, electroporation, and ultrasounds. These physicals factors result in deeper penetration of cosmetics. It is important to increase the penetration of L-ascorbic acid, thereby increasing the spectrum of its activity. The aim of the work was to assess the effectiveness of pure L-ascorbic acid activity in anti-aging therapy using a needle-free and micro-needling mesotherapy. The study was performed on a group of 35 healthy volunteers in accordance with the Declaration of Helsinki of 1964 and agreement of the Ethics Commissions no RNN/281/16/KE 2017. Women were randomized to mesotherapy or control group. Control group applied topically 2,5 ml serum containing 20% L-ascorbic acid with hydrate from strawberries, every 10 days for a period of 9 weeks. No-needle mesotherapy, on the left half of the face and micro-needling on the right with the same serum, was done in mesotherapy group. The pH of serum was 3.5-4, and the serum was prepared directly prior to the facial treatment. The skin parameters were measured at the beginning and before each treatment. The measurement of the forehead skin was done using Cutometer® (measurement of skin elasticity and firmness), Corneometer® (skin hydration measurement), Mexameter® (skin tone measurement). Also, the photographs were taken by Fotomedicus system. Additionally, the volunteers fulfilled the questionnaire. Serum was tested for microbiological purity and stability after the opening of the cosmetic. During the study, all of the volunteers were taken care of a dermatologist. The regular application of the serum has caused improvement of the skin parameters. Respectively, after 4 and 8 weeks improvement in hydration and elasticity has been seen (Corneometer®, Cutometer® results). Moreover, the number of hyper-pigmentated spots has decreased (Mexameter®). After 8 weeks the volunteers has claimed that the tested product has smoothing and moisturizing features. Subjective opinions indicted significant improvement of skin color and elasticity. The product containing the L-ascorbic acid used with intercellular penetration promoters demonstrates higher anti-aging efficiency than control. In vivo studies confirmed the effectiveness of serum and the impact of the active substance on skin firmness and elasticity, the degree of hydration and skin tone. Mesotherapy with pure L-ascorbic acid provides better diffusion of active substances through the skin.

Keywords: anti-aging, l-ascorbic acid, mesotherapy, promoters

Procedia PDF Downloads 265

Authors: Ji Zhou, Jung Hee Seo, Rajat Mittal

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Fish move in groups for foraging, reproduction, predator protection, and hydrodynamic efficiency. Schooling's predator protection involves the "many eyes" theory, which increases predator detection probability in a group. Reduced visual signature in a group scales with school size, offering per-capita protection. The ‘confusion effect’ makes it hard for predators to target prey in a group. These benefits, however, all focus on vision-based sensing, overlooking sound-based detection. Fish, including predators, possess sophisticated sensory systems for pressure waves and underwater sound. The lateral line system detects acoustic waves, while otolith organs sense infrasound, and sharks use an auditory system for low-frequency sounds. Among sound generation mechanisms of fish, the mechanism of dipole sound relates to hydrodynamic pressure forces on the body surface of the fish and this pressure would be affected by group swimming. Thus, swimming within a group could affect this hydrodynamic noise signature of fish and possibly serve as an additional protection afforded by schooling, but none of the studies to date have explored this effect. BAUVs with fin-like propulsors could reduce acoustic noise without compromising performance, addressing issues of anthropogenic noise pollution in marine environments. Therefore, in this study, we used our in-house immersed-boundary method flow and acoustic solver, ViCar3D, to simulate fish schools consisting of four swimmers in the classic ‘diamond’ configuration and discussed the feasibility of yielding higher swimming efficiency and controlling far-field sound signature of the school. We examine the effects of the relative phase of fin flapping of the swimmers and the simulation results indicate that the phase of the fin flapping is a dominant factor in both thrust enhancement and the total sound radiated into the far-field by a group of swimmers. For fish in the “diamond” configuration, a suitable combination of the relative phase difference between pairs of leading fish and trailing fish can result in better swimming performance with significantly lower hydroacoustic noise.

Keywords: fish schooling, biopropulsion, hydrodynamics, hydroacoustics

Procedia PDF Downloads 61

Authors: Adel A. Ghobbar, Varun Raman

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The Corrective maintenance of components and systems is a problem plaguing almost every industry in the world today. Train operators’ and the maintenance repair and overhaul subsidiary of the Dutch railway company is also facing this problem. A considerable portion of the maintenance activities carried out by the company are unscheduled. This, in turn, severely stresses and stretches the workforce and resources available. One possible solution is to have a robust preventive maintenance plan. The other possible solution is to plan maintenance based on real-time data obtained from sensor-based ‘Health and Usage Monitoring Systems.’ The former has been investigated in this paper. The preventive maintenance model developed for train operator will subsequently be extended, to tackle the unscheduled maintenance problem also affecting the aerospace industry. The extension of the model to the aerospace sector will be dealt with in the second part of the research, and it would, in turn, validate the soundness of the model developed. Thus, there are distinct areas that will be addressed in this paper, including the mathematical modelling of preventive maintenance and optimization based on cost and system availability. The results of this research will help an organization to choose the right maintenance strategy, allowing it to save considerable sums of money as opposed to overspending under the guise of maintaining high asset availability. The concept of delay time modelling was used to address the practical problem of unscheduled maintenance in this paper. The delay time modelling can be used to help with support planning for a given asset. The model was run using MATLAB, and the results are shown that the ideal inspection intervals computed using the extended from a minimal cost perspective were 29 days, and from a minimum downtime, perspective was 14 days. Risk matrix integration was constructed to represent the risk in terms of the probability of a fault leading to breakdown maintenance and its consequences in terms of maintenance cost. Thus, the choice of an optimal inspection interval of 29 days, resulted in a cost of approximately 50 Euros and the corresponding value of b(T) was 0.011. These values ensure that the risk associated with component X being maintained at an inspection interval of 29 days is more than acceptable. Thus, a switch in maintenance frequency from 90 days to 29 days would be optimal from the point of view of cost, downtime and risk.

Keywords: delay time modelling, unscheduled maintenance, reliability, maintainability, availability

Procedia PDF Downloads 132

Authors: Getahun Nigusie Demise

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Background; antiretroviral treatment reduce HIV-related morbidity, and prolonged survival of patients however, there is lack of up-to-date information concerning the treatment long term effect on the survival of HIV positive children especially in the study area. Objective: The aim of this study is to assess the incidence and predictors of mortality among HIV positive children on antiretroviral therapy (ART) in public hospitals of Harer town who were enrolled from 2011 to 2021. Methodology: Institution based retrospective cohort study was conducted among 429 HIV positive children enrolled in ART clinic from January 1st 2011 to December30th 2021. Data were collected from medical cards by using a data extraction form, Descriptive analyses were used to Summarized the results, and life table was used to estimate survival probability at specific point of time after introduction of ART. Kaplan Meier survival curve together with log rank test was used to compare survival between different categories of covariates, and Multivariate Cox-proportional hazard regression model was used to estimate adjusted Hazard rate. Variables with p-values ≤0.25 in bivariable analysis were candidates to the multivariable analysis. Finally, variables with p-values < 0.05 were considered as significant variables. Results: The study participants had followed for a total of 2549.6 child-years (30596 child months) with an overall mortality rate of 1.5 (95% CI: 1.1, 2.04) per 100 child-years. Their median survival time was 112 months (95% CI: 101–117). There were 38 children with unknown outcome, 39 deaths, and 55 children transfer out to different facility. The overall survival at 6, 12, 24, 48 months were 98%, 96%, 95%, 94% respectively. being in WHO clinical Stage four (AHR=4.55, 95% CI:1.36, 15.24), having anemia(AHR=2.56, 95% CI:1.11, 5.93), baseline low absolute CD4 count (AHR=2.95, 95% CI: 1.22, 7.12), stunting (AHR=4.1, 95% CI: 1.11, 15.42), wasting (AHR=4.93, 95% CI: 1.31, 18.76), poor adherence to treatment (AHR=3.37, 95% CI: 1.25, 9.11), having TB infection at enrollment (AHR=3.26, 95% CI: 1.25, 8.49),and no history of change their regimen(AHR=7.1, 95% CI: 2.74, 18.24), were independent predictors of death. Conclusion: more than half of death occurs within 2 years. Prevalent tuberculosis, anemia, wasting, and stunting nutritional status, socioeconomic factors, and baseline opportunistic infection were independent predictors of death. Increasing early screening and managing those predictors are required.

Keywords: human immunodeficiency virus-positive children, anti-retroviral therapy, survival, treatment, Ethiopia

Procedia PDF Downloads 49

Authors: Roseliza Mat Alipiah, David Raffaelli, J. C. R. Smart

Abstract:

This research is a new approach as it integrates information from both environmental and social sciences to inform effective management of the wetlands. A three-stage research framework was developed for modelling the drivers and pressures imposed on the wetlands and their impacts to the ecosystem and the local communities. Firstly, a Bayesian Belief Network (BBN) was used to predict the probability of anthropogenic activities affecting the delivery of different key wetland ecosystem services under different management scenarios. Secondly, Choice Experiments (CEs) were used to quantify the relative preferences which key wetland stakeholder group (aquaculturists) held for delivery of different levels of these key ecosystem services. Thirdly, a Multi-Criteria Decision Analysis (MCDA) was applied to produce an ordinal ranking of the alternative management scenarios accounting for their impacts upon ecosystem service delivery as perceived through the preferences of the aquaculturists. This integrated ecosystem management approach was applied to a wetland ecosystem in Setiu, Terengganu, Malaysia which currently supports a significant level of aquaculture activities. This research has produced clear guidelines to inform policy makers considering alternative wetland management scenarios: Intensive Aquaculture, Conservation or Ecotourism, in addition to the Status Quo. The findings of this research are as follows: The BBN revealed that current aquaculture activity is likely to have significant impacts on water column nutrient enrichment, but trivial impacts on caged fish biomass, especially under the Intensive Aquaculture scenario. Secondly, the best fitting CE models identified several stakeholder sub-groups for aquaculturists, each with distinct sets of preferences for the delivery of key ecosystem services. Thirdly, the MCDA identified Conservation as the most desirable scenario overall based on ordinal ranking in the eyes of most of the stakeholder sub-groups. Ecotourism and Status Quo scenarios were the next most preferred and Intensive Aquaculture was the least desirable scenario. The methodologies developed through this research provide an opportunity for improving planning and decision making processes that aim to deliver sustainable management of wetland ecosystems in Malaysia.

Keywords: Bayesian belief network (BBN), choice experiments (CE), multi-criteria decision analysis (MCDA), aquaculture

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Authors: Siming Xie

Abstract:

In social networks, the term homophily refers to the tendency of agents with similar characteristics to link with one another and is so robustly observed across many contexts and dimensions. The starting point of my research is the observation that the “type” of agents is not a single exogenous variable. Agents, despite their differences in race, religion, and other hard to alter characteristics, may share interests and engage in activities that cut across those predetermined lines. This research aims to capture the interactions of homophily effects in a model where agents have two-dimension characteristics (i.e., race and personal hobbies such as basketball, which one either likes or dislikes) and with biases in meeting opportunities and in favor of same-type friendships. A novel feature of my model is providing a matching process with biased meeting probability on different dimensions, which could help to understand the structuring process in multidimensional networks without missing layer interdependencies. The main contribution of this study is providing a welfare based matching process for agents with multi-dimensional characteristics. In particular, this research shows that the biases in meeting opportunities on one dimension would lead to the emergence of homophily on the other dimension. The objective of this research is to determine the pattern of homophily in network formations, which will shed light on our understanding of segregation and its remedies. By constructing a two-dimension matching process, this study explores a method to describe agents’ homophilous behavior in a social network with multidimension and construct a game in which the minorities and majorities play different strategies in a society. It also shows that the optimal strategy is determined by the relative group size, where society would suffer more from social segregation if the two racial groups have a similar size. The research also has political implications—cultivating the same characteristics among agents helps diminishing social segregation, but only if the minority group is small enough. This research includes both theoretical models and empirical analysis. Providing the friendship formation model, the author first uses MATLAB to perform iteration calculations, then derives corresponding mathematical proof on previous results, and last shows that the model is consistent with empirical evidence from high school friendships. The anonymous data comes from The National Longitudinal Study of Adolescent Health (Add Health).

Keywords: homophily, multidimension, social networks, friendships

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