Search results for: psychological distress prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4164

Search results for: psychological distress prediction

3894 The Effectiveness of a Self-Efficacy Psychoeducational Programme to Enhance Outcomes of Patients with End-Stage Renal Disease

Authors: H. C. Chen, S. W. C. Chan, K. Cheng, A. Vathsala, H. K. Sran, H. He

Abstract:

Background: End-stage renal disease (ESRD) is the last stage of chronic kidney disease. The numbers of patients with ESRD have increased worldwide due to the growing number of aging, diabetes and hypertension populations. Patients with ESRD suffer from physical illness and psychological distress due to complex treatment regimens, which often affect the patients’ social and psychological functioning. As a result, the patients may fail to perform daily self-care and self-management, and consequently experience worsening conditions. Aims: The study aims to examine the effectiveness of a self-efficacy psychoeducational programme on primary outcome (self-efficacy) and secondary outcomes (psychological wellbeing, treatment adherence, and quality of life) in patients with ESRD and haemodialysis in Singapore. Methodology: A randomised controlled, two-group pretest and repeated posttests design will be carried out. A total of 154 participants (n=154) will be recruited. The participants in the control group will receive a routine treatment. The participants in the intervention group will receive a self-efficacy psychoeducational programme in addition to the routine treatment. The programme is a two-session of educational intervention in a week. A booklet, two consecutive sessions of face-to-face individual education, and an abdominal breathing exercise are adopted in the programme. Outcome measurements include Dialysis Specific Self-efficacy Scale, Kidney Disease Quality of Life- 36 Hospital Anxiety and Depression Scale, Renal Adherence Attitudes Questionnaire and Renal Adherence Behaviour Questionnaire. The questionnaires will be used to measure at baseline, 1- and 3- and 6-month follow-up periods. Process evaluation will be conducted with a semi-structured face to face interview. Quantitative data will be analysed using SPSS21.0 software. Qualitative data will be analysed by content analysis. Significance of the study: This study will identify a clinically useful and potentially effective approach to help patients with end-stage renal disease and haemodialysis by enhancing their self-efficacy in self-care behaviour, and therefore improving their psychological well-being, treatment adherence and quality of life. This study will provide information to develop clinical guidelines to improve patients’ disease self-management and to enhance health-related outcomes and it will help reducing disease burden.

Keywords: end-stage renal disease (ESRD), haemodialysis, psychoeducation, self-efficacy

Procedia PDF Downloads 283
3893 Identifying Physical and Psycho-Social Issues Facing Breast Cancer Survivors after Definitive Treatment for Early Breast Cancer: A Nurse-Led Clinic Model

Authors: A. Dean, M. Pitcher, L. Storer, K. Shanahan, I. Rio, B. Mann

Abstract:

Purpose: Breast cancer survivors are at risk of specific physical and psycho-social issues, such as arm swelling, fatigue, and depression. Firstly, we investigate symptoms reported by Australia breast cancer survivors upon completion of definitive treatment. Secondly, we evaluate the appropriateness and effectiveness of a multi-centre pilot program nurse-led clinic to identify these issues and make timely referrals to available services. Methods: Patients post-definitive treatment (excluding ongoing hormonal therapy) for early breast cancer or ductal carcinoma in situ were invited to participate. An hour long appointment with a breast care nurse (BCN) was scheduled. In preparation, patients completed validated quality-of-life surveys (FACT-B, Menopause Rating Scale, Distress Thermometer). During the appointment, issues identified in the surveys were addressed and referrals to appropriate services arranged. Results: 183 of 274 (67%) eligible patients attended a nurse-led clinic. Mean age 56.8 years (range 29-87 years), 181/183 women, 105/183 post-menopausal. 96 (55%) participants reported significant level of distress; 31 (18%) participants reported extreme distress or depression. Distress stemmed from a lack of energy (56/175); poor quality of sleep (50/176); inability to work or participate in household activities (35/172) and problems with sex life (28/89). 166 referrals were offered; 94% of patients accepted the referrals. 65% responded to a follow-up survey: the majority of women either strongly agreed or agreed that the BCN was overwhelmingly supportive, helpful in making referrals, and compassionate towards them. 39% reported making lifestyle changes as a result of the BCN. Conclusion: Breast cancer survivors experience a unique set of challenges, including low mood, difficulty sleeping, problems with sex life and fear of disease recurrence. The nurse-led clinic model is an appropriate and effective method to ensure physical and psycho-social issues are identified and managed in a timely manner. This model empowers breast cancer survivors with information about their diagnosis and available services.

Keywords: early breast cancer, survivorship, breast care nursing, oncology nursing and cancer care

Procedia PDF Downloads 378
3892 Deadline Missing Prediction for Mobile Robots through the Use of Historical Data

Authors: Edwaldo R. B. Monteiro, Patricia D. M. Plentz, Edson R. De Pieri

Abstract:

Mobile robotics is gaining an increasingly important role in modern society. Several potentially dangerous or laborious tasks for human are assigned to mobile robots, which are increasingly capable. Many of these tasks need to be performed within a specified period, i.e., meet a deadline. Missing the deadline can result in financial and/or material losses. Mechanisms for predicting the missing of deadlines are fundamental because corrective actions can be taken to avoid or minimize the losses resulting from missing the deadline. In this work we propose a simple but reliable deadline missing prediction mechanism for mobile robots through the use of historical data and we use the Pioneer 3-DX robot for experiments and simulations, one of the most popular robots in academia.

Keywords: deadline missing, historical data, mobile robots, prediction mechanism

Procedia PDF Downloads 377
3891 Useful Lifetime Prediction of Rail Pads for High Speed Trains

Authors: Chang Su Woo, Hyun Sung Park

Abstract:

Useful lifetime evaluations of rail-pads were very important in design procedure to assure the safety and reliability. It is, therefore, necessary to establish a suitable criterion for the replacement period of rail pads. In this study, we performed properties and accelerated heat aging tests of rail pads considering degradation factors and all environmental conditions including operation, and then derived a lifetime prediction equation according to changes in hardness, thickness, and static spring constants in the Arrhenius plot to establish how to estimate the aging of rail pads. With the useful lifetime prediction equation, the lifetime of e-clip pads was 2.5 years when the change in hardness was 10% at 25°C; and that of f-clip pads was 1.7 years. When the change in thickness was 10%, the lifetime of e-clip pads and f-clip pads is 2.6 years respectively. The results obtained in this study to estimate the useful lifetime of rail pads for high speed trains can be used for determining the maintenance and replacement schedule for rail pads.

Keywords: rail pads, accelerated test, Arrhenius plot, useful lifetime prediction, mechanical engineering design

Procedia PDF Downloads 295
3890 Navigating Creditors' Interests in the Context of Business Rescue

Authors: Hermanus J. Moolman

Abstract:

The COVID-19 pandemic had a severe impact on the society and companies in South Africa. This raises questions about the position of creditors of companies facing financial distress and the actions that directors should take to cater to the interests of creditors. The extent to which directors owe their duties and consideration to creditors has been the subject of debate. The directors of a solvent company owe their duties to the company in favour of its shareholders. When the company becomes insolvent, creditors are the beneficiaries of the directors’ duties. However, the intermittent phase between solvency and insolvency, otherwise referred to as the realm of insolvency, is not accounted for. The purpose of this paper is to determine whether South African company law appropriately addresses the duties that directors owe to creditors and the extent of consideration given to creditors’ interests when the company is in the realm of insolvency and has started business rescue proceedings. A comparative study on South Africa, the United States of America, the United Kingdom and international instruments was employed to achieve the purpose statement. In the United States of America and the United Kingdom, the focus shifts from shareholders to the best interests of creditors when business recue proceedings commence. Such an approach is not aligned with the purpose of the Companies Act of 2008 that calls for a balance of interests of all persons affected by a company’s financial distress and will not be suitable for the South African context. Business rescue in South Africa is relatively new when compared to the practices of the United States of America and the United Kingdom, and the entrepreneurial landscape in South Africa is still evolving. The interests of creditors are not the only interests at risk when a company is financially distressed. It is recommended that an enlightened creditor value approach is adopted for South Africa, where the interests of creditors, albeit paramount, are balanced with those of other stakeholders. This approach optimises a gradual shift in the duties of directors from shareholders to creditors, without disregarding the interests of shareholders.

Keywords: business rescue, shareholders, creditors, financial distress, balance of interests, alternative remedies, company law

Procedia PDF Downloads 22
3889 A Longitudinal Study of Psychological Capital, Parent-Child Relationships, and Subjective Well-Beings in Economically Disadvantaged Adolescents

Authors: Chang Li-Yu

Abstract:

Purposes: The present research focuses on exploring the latent growth model of psychological capital in disadvantaged adolescents and assessing its relationship with subjective well-being. Methods: Longitudinal study design was utilized and the data was from Taiwan Database of Children and Youth in Poverty (TDCYP), using the student questionnaires from 2009, 2011, and 2013. Data analysis was conducted using both univariate and multivariate latent growth curve models. Results: This study finds that: (1) The initial state and growth rate of individual factors such as parent-child relationships, psychological capital, and subjective wellbeing in economically disadvantaged adolescents have a predictive impact; (2) There are positive interactive effects in the development among factors like parentchild relationships, psychological capital, and subjective well-being in economically disadvantaged adolescents; and (3) The initial state and growth rate of parent-child relationships and psychological capital in economically disadvantaged adolescents positively affect the initial state and growth rate of their subjective well-being. Recommendations: Based on these findings, this study concretely discusses the significance of psychological capital and family cohesion for the mental health of economically disadvantaged youth and offers suggestions for counseling, psychological therapy, and future research.

Keywords: economically disadvantaged adolescents, psychological capital, parent-child relationships, subjective well-beings

Procedia PDF Downloads 21
3888 Job Resource, Personal Resource, Engagement and Performance with Balanced Score Card in the Integrated Textile Companies in Indonesia

Authors: Nurlaila Effendy

Abstract:

Companies in Asia face a number of constraints in tight competitiveness in ASEAN Economic Community 2015 and globalization. An economic capitalism system as an integral part of globalization processing brings broad impacts. They need to improve business performance in globalization and ASEAN Economic Community. Organizational development has quite clearly demonstrated that aligning individual’s personal goals with the goals of the organization translates into measurable and sustained performance improvement. Human capital is a key to achieve company performance. Employee Engagement (EE) creates and expresses themselves physically, cognitively and emotionally to achieve company goals and individual goals. One will experience a total involvement when they undertake their jobs and feel a self integration to their job and organization. A leader plays key role in attaining the goals and objectives of a company/organization. Any Manager in a company needs to have leadership competence and global mindset. As one the of positive organizational behavior developments, psychological capital (PsyCap) is assumed to be one of the most important capitals in the global mindset, in addition to intellectual capital and social capital. Textile companies also need to face a number of constraints in tight competitiveness in regional and global. This research involved 42 managers in two textiles and a spinning companies in a group, in Central Java, Indonesia. It is a quantitative research with Partial Least Squares (PLS) studying job resource (Social Support & Organizational Climate) and Personal Resource (4 dimensions of Psychological Capital & Leadership Competence) as prediction of Employee Engagement, also Employee Engagement and leadership competence as prediction of leader’s performance. The performance of a leader is measured by means of achievement on objective strategies in terms of 4 perspectives (financial and non-financial perspectives) in a Balanced Score Card (BSC). It took one year during a business plan of year 2014, from January to December 2014. The result of this research is there is correlation between Job Resource (coefficient value of Social Support is 0.036 & coefficient value of organizational climate is 0.220) and Personal Resource (coefficient value of PsyCap is 0.513 & coefficient value of Leadership Competence is 0.249) with employee engagement. There is correlation between employee engagement (coefficient value is 0.279) and leadership competence (coefficient value is 0.581) with performance.

Keywords: organizational climate, social support, psychological capital leadership competence, employee engagement, performance, integrated textile companies

Procedia PDF Downloads 411
3887 Fighting Competition Stress by Focusing the Psychological Training on the Vigor-Activity Mood States

Authors: Majid Al-Busafi, Alexe Cristina Ioana, Alexe Dan Iulian

Abstract:

The specific competition and pre-competition stress in professional track and field determined an increasing engagement, from a biological and psychological point of view, of the middle distance and long distance runners, to obtain the top performances that would get them to win in a competition. Under these conditions, if the psychological stress is not properly managed, the negative effects can lead to a total drop in self-confidence, and can affect the value, the talent, and the self-trust, which generates an even higher stress. One of the means at our disposal is the psychological training, specially adapted to the athlete's individual characteristics, to the characteristics of the athletic event, or of the competition. This paper aims to highlight certain original aspects regarding the effects of a specific psychological training program on the mood states characterized by psychological activation, vigor, vitality. The subjects were represented by 12 professional middle distance and long distance runners, subjected to an applicative intervention to which they have participated voluntarily, over the course of 6 months (a competition season). The results indicated that The application of a psychological training program, adapted to the track and field competition system, over a period of time characterized by high competition stress, can determine an increase in the states of vigor and psychological activation, at the same time diminishing those moods that have negative effects on the performance, in the middle distance and long distance running events. This conclusion confirms the hypothesis of this research.

Keywords: competition stress, psychological training, track and field, vigor-activity

Procedia PDF Downloads 426
3886 Using Water Erosion Prediction Project Simulation Model for Studying Some Soil Properties in Egypt

Authors: H. A. Mansour

Abstract:

The objective of this research work is studying the water use prediction, prediction technology for water use by action agencies, and others involved in conservation, planning, and environmental assessment of the Water Erosion Prediction Project (WEPP) simulation model. Models the important physical, processes governing erosion in Egypt (climate, infiltration, runoff, ET, detachment by raindrops, detachment by flowing water, deposition, etc.). Simulation of the non-uniform slope, soils, cropping/management., and Egyptian databases for climate, soils, and crops. The study included important parameters in Egyptian conditions as follows: Water Balance & Percolation, Soil Component (Tillage impacts), Plant Growth & Residue Decomposition, Overland Flow Hydraulics. It could be concluded that we can adapt the WEPP simulation model to determining the previous important parameters under Egyptian conditions.

Keywords: WEPP, adaptation, soil properties, tillage impacts, water balance, soil percolation

Procedia PDF Downloads 266
3885 The Impact of the COVID-19 Pandemic on the Mental Health of Families Dealing with Attention-Deficit Hyperactivity Disorder

Authors: Alexis Winfield, Carly Sugar, Barbara Fenesi

Abstract:

The COVID-19 pandemic uprooted regular routines forcing many children to learn from home, requiring many adults to work from home, and cutting families off from support outside the home. Public health restrictions associated with the pandemic caused widespread psychological distress, including depression and anxiety, increased fear, panic, and stress. These trends are particularly concerning for families raising neuroatypical children, such as those with Attention-Deficit Hyperactivity Disorder (ADHD), as these children are already more likely than their typically developing peers to experience comorbid mental health issues and to experience greater distress when required to stay indoors. Families with children who have ADHD are also at greater risk for experiencing heightened familial stress due to the challenges associated with managing ADHD behavioural symptoms, greater parental discord and divorce, and greater financial difficulties compared to other families. The current study engaged families comprised of at least one child diagnosed with ADHD to elucidate 1) the unique ways that the COVID-19 pandemic affected their mental health and 2) the specific barriers these families faced to maintaining optimal mental wellbeing. A total of 33 participants (15 parent-child dyads) engaged in virtual interviews. Content analysis revealed that the most frequently identified mental health effects for families were increased child anxiety and disconnectedness, as well as deteriorating parental mental health. The most frequently identified barriers to maintaining optimal mental well-being were lack of routine, lack of social interaction and social support, and uncertainty and fear. Findings underscore areas of need during times of large-scale social isolation, bring voice to the families of children with ADHD, and contribute to our understanding of the pandemic’s impact on the wellbeing of vulnerable families. This work contributes to a growing body of research aimed at creating safeguards to support mental wellbeing for vulnerable families during times of crisis.

Keywords: attention-deficit hyperactivity disorder, COVID-19, mental health, vulnerable families

Procedia PDF Downloads 259
3884 The Impact of Solution-Focused Brief Therapy on the Improvement of the Psychological Wellbeing of Family Supervisor Women

Authors: Kaveh Qaderi Bagajan, Osman Khanahmadi, Ziba Mamaghani Chaharborj, Majid Chenaparchi

Abstract:

The purpose of this study is to investigate the efficacy of the solution-focused brief therapy on improving the psychological wellbeing of family supervisor woman. This study has been carried out by semi-experimental method and in the form of pre-test, post-test performance on two groups (experimental and control), so that one sample group of 30 individuals was randomly achieved and were randomly divided in two groups of experimental (n=15) and control (n=15). To collect data, Ryff scale psychological wellbeing was used. After conducting pre-test (RSPWB) for two experimental and control groups, Solution-focused brief therapy interference was conducted on the experimental group during five two-hour sessions. Finally, Ryff scale psychological wellbeing was reused for the two groups as post-test and achieved outcomes that were analyzed using covariance. The results indicated that the significant increase of average marks of the experimental group in psychological wellbeing had better function than that of the control group. Finally, solution-focused brief therapy for improving psychological well-being of family supervisor women has a suitable capability and could be used in this way.

Keywords: solution-focused brief therapy, short-term therapy, family supervisor women, psychological well-being

Procedia PDF Downloads 286
3883 Development of Fuzzy Logic and Neuro-Fuzzy Surface Roughness Prediction Systems Coupled with Cutting Current in Milling Operation

Authors: Joseph C. Chen, Venkata Mohan Kudapa

Abstract:

Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations

Procedia PDF Downloads 117
3882 Field Performance of Cement Treated Bases as a Reflective Crack Mitigation Technique for Flexible Pavements

Authors: Mohammad R. Bhuyan, Mohammad J. Khattak

Abstract:

Deterioration of flexible pavements due to crack reflection from its soil-cement base layer is a major concern around the globe. The service life of flexible pavement diminishes significantly because of the reflective cracks. Highway agencies are struggling for decades to prevent or mitigate these cracks in order to increase pavement service lives. The root cause of reflective cracks is the shrinkage crack which occurs in the soil-cement bases during the cement hydration process. The primary factor that causes the shrinkage is the cement content of the soil-cement mixture. With the increase of cement content, the soil-cement base gains strength and durability, which is necessary to withstand the traffic loads. But at the same time, higher cement content creates more shrinkage resulting in more reflective cracks in pavements. Historically, various states of USA have used the soil-cement bases for constructing flexile pavements. State of Louisiana (USA) had been using 8 to 10 percent of cement content to manufacture the soil-cement bases. Such traditional soil-cement bases yield 2.0 MPa (300 psi) 7-day compressive strength and are termed as cement stabilized design (CSD). As these CSD bases generate significant reflective cracks, another design of soil-cement base has been utilized by adding 4 to 6 percent of cement content called cement treated design (CTD), which yields 1.0 MPa (150 psi) 7-day compressive strength. The reduction of cement content in the CTD base is expected to minimize shrinkage cracks thus increasing pavement service lives. Hence, this research study evaluates the long-term field performance of CTD bases with respect to CSD bases used in flexible pavements. Pavement Management System of the state of Louisiana was utilized to select flexible pavement projects with CSD and CTD bases that had good historical record and time-series distress performance data. It should be noted that the state collects roughness and distress data for 1/10th mile section every 2-year period. In total, 120 CSD and CTD projects were analyzed in this research, where more than 145 miles (CTD) and 175 miles (CSD) of roadways data were accepted for performance evaluation and benefit-cost analyses. Here, the service life extension and area based on distress performance were considered as benefits. It was found that CTD bases increased 1 to 5 years of pavement service lives based on transverse cracking as compared to CSD bases. On the other hand, the service lives based on longitudinal and alligator cracking, rutting and roughness index remain the same. Hence, CTD bases provide some service life extension (2.6 years, on average) to the controlling distress; transverse cracking, but it was inexpensive due to its lesser cement content. Consequently, CTD bases become 20% more cost-effective than the traditional CSD bases, when both bases were compared by net benefit-cost ratio obtained from all distress types.

Keywords: cement treated base, cement stabilized base, reflective cracking , service life, flexible pavement

Procedia PDF Downloads 137
3881 Neural Network Based Approach of Software Maintenance Prediction for Laboratory Information System

Authors: Vuk M. Popovic, Dunja D. Popovic

Abstract:

Software maintenance phase is started once a software project has been developed and delivered. After that, any modification to it corresponds to maintenance. Software maintenance involves modifications to keep a software project usable in a changed or a changing environment, to correct discovered faults, and modifications, and to improve performance or maintainability. Software maintenance and management of software maintenance are recognized as two most important and most expensive processes in a life of a software product. This research is basing the prediction of maintenance, on risks and time evaluation, and using them as data sets for working with neural networks. The aim of this paper is to provide support to project maintenance managers. They will be able to pass the issues planned for the next software-service-patch to the experts, for risk and working time evaluation, and afterward to put all data to neural networks in order to get software maintenance prediction. This process will lead to the more accurate prediction of the working hours needed for the software-service-patch, which will eventually lead to better planning of budget for the software maintenance projects.

Keywords: laboratory information system, maintenance engineering, neural networks, software maintenance, software maintenance costs

Procedia PDF Downloads 324
3880 Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms

Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

Procedia PDF Downloads 250
3879 Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks

Authors: Anne-Lena Kampen, Øivind Kure

Abstract:

Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

Procedia PDF Downloads 121
3878 Investigating Differential Psychological Impact of Translated Movies: An Experimental Design

Authors: Sonakshi Saxena, Moosath Harishankar Vasudevan

Abstract:

The current study seeks to investigate the differences in the psychological impact of movies in their original and translated versions. International cinema is exemplar of the success of globalization. The multitude of languages in the global village does not seem to impede the common cinematic goal of filmmakers across linguistic boundaries. To understand, hence, whether the psychological impact of movies, intentional or otherwise, is preserved when the original is translated into a different language, an experimental design was adopted. Multilingual participants in the age group 18-25 years were recruited for the same. A control group and an experimental group were randomly assigned and the psychological impacts of movies were studied under two conditions- a) watching the movie in its original language, and b) watching the movie in its original language as well as translated version. For the second condition, the experimental group was further divided into two groups randomly to balance order effects. The major aspects of psychological impact assessed were emotional impact and attitude towards the movie. The scores were compared for the two groups. It is further discussed whether the experience is salient across language or do languages inherently possess the ability to alter experiences of the audience.

Keywords: experimental design, movies, psychological impact, translation

Procedia PDF Downloads 364
3877 A Type-2 Fuzzy Model for Link Prediction in Social Network

Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

Abstract:

Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

Procedia PDF Downloads 297
3876 Hypotonia - A Concerning Issue in Neonatal Care

Authors: Eda Jazexhiu-Postoli, Gladiola Hoxha, Ada Simeoni, Sonila Biba

Abstract:

Background Neonatal hypotonia represents a commonly encountered issue in the Neonatal Intensive Care Unit and newborn nursery. The differential diagnosis is broad, encompassing chromosome abnormalities, primary muscular dystrophies, neuropathies and inborn errors of metabolism. Aim of study Our study describes some of the main clinical features of hypotonia in newborns and presents clinical cases of neonatal hypotonia we treated in our Neonatal unit in the last 3 years. Case reports Four neonates born in our hospital presented with hypotonia after birth, one preterm newborn 35-36 weeks of gestational age and three other term newborns (38-39 weeks of gestational age). Prenatal data revealed a decrease in fetal movements in both cases. Intrapartum meconium-stained amniotic fluid was found in 75% of our hypotonic newborns. Clinical features included inability to establish effective respiratory movements and need for resuscitation in the delivery room, respiratory distress syndrome, feeding difficulties and need for oro-gastric tube feeding, dysmorphic features, hoarse voice and moderate to severe muscular hypotonia. The genetic workup revealed the diagnosis of Autosomal Recessive Congenital Myasthenic Syndrome 1-B, Sotos Syndrome, Spinal Muscular Atrophy Type 1 and Transient Hypotonia of the Newborn. Two out of four hypotonic neonates were transferred to the Pediatric Intensive Care Unit and died at the age of three to five months old. Conclusion Hypotonia is a concerning finding in neonatal care and it is suggested by decreased intrauterine fetal movements, failure to establish first breaths, respiratory distress and feeding difficulties in the neonate. Prognosis is determined by its etiology and time of diagnosis and intervention.

Keywords: hypotonic neonate, respiratory distress, feeding difficulties, fetal movements

Procedia PDF Downloads 76
3875 Fast Authentication Using User Path Prediction in Wireless Broadband Networks

Authors: Gunasekaran Raja, Rajakumar Arul, Kottilingam Kottursamy, Ramkumar Jayaraman, Sathya Pavithra, Swaminathan Venkatraman

Abstract:

Wireless Interoperability for Microwave Access (WiMAX) utilizes the IEEE 802.1X mechanism for authentication. However, this mechanism incurs considerable delay during handoffs. This delay during handoffs results in service disruption which becomes a severe bottleneck. To overcome this delay, our article proposes a key caching mechanism based on user path prediction. If the user mobility follows that path, the user bypasses the normal IEEE 802.1X mechanism and establishes the necessary authentication keys directly. Through analytical and simulation modeling, we have proved that our mechanism effectively decreases the handoff delay thereby achieving fast authentication.

Keywords: authentication, authorization, and accounting (AAA), handoff, mobile, user path prediction (UPP) and user pattern

Procedia PDF Downloads 365
3874 Relations between Psychological Adjustment and Perceived Parental, Teacher and Best Friend Acceptance among Bangladeshi Adolescents

Authors: Tariqul Islam, Shaheen Mollah

Abstract:

The study's main objective is to assess the relationship between psychological adjustment and parental acceptance-rejection, teacher acceptance-rejection, and best friend acceptance-rejection among secondary school students. This study was conducted on a sample of 300 (6th through 10th-grade students) recruited from over ten schools in Dhaka. While the schools were selected purposively, the respondents within each school were selected conveniently. The collected data were analyzed using Pearson product-moment correlation, hierarchical regression, and simultaneous regression analysis. The results showed that psychological adjustment is positively correlated with paternal, maternal, teacher, and best friend acceptance. The paternal acceptance was significantly connected with maternal acceptance. The teacher and best friend acceptance are correlated substantially with paternal and maternal acceptance. The hierarchical multiple regressions indicated that maternal, paternal, teacher, and best friend acceptance-rejection contributed significantly to students' psychological adjustment. The results revealed substantial independent contributions of maternal, paternal, teacher, and best friend acceptance on the students' psychological adjustment. The simultaneous regression analysis indicates that the maternal and best friend acceptances (but not paternal acceptance) were significant predictors of psychological adjustments. It showed that 41.7% variability in psychological adjustment could be explained by paternal, maternal, and best friend acceptance. The findings of the present study are exciting. They may contribute to developing insight in parents and best friends for behaving properly with their offspring and friend, respectively, for better psychological adjustment.

Keywords: adjustment, parenting, rejection, acceptance

Procedia PDF Downloads 117
3873 Estimation of Sediment Transport into a Reservoir Dam

Authors: Kiyoumars Roushangar, Saeid Sadaghian

Abstract:

Although accurate sediment load prediction is very important in planning, designing, operating and maintenance of water resources structures, the transport mechanism is complex, and the deterministic transport models are based on simplifying assumptions often lead to large prediction errors. In this research, firstly, two intelligent ANN methods, Radial Basis and General Regression Neural Networks, are adopted to model of total sediment load transport into Madani Dam reservoir (north of Iran) using the measured data and then applicability of the sediment transport methods developed by Engelund and Hansen, Ackers and White, Yang, and Toffaleti for predicting of sediment load discharge are evaluated. Based on comparison of the results, it is found that the GRNN model gives better estimates than the sediment rating curve and mentioned classic methods.

Keywords: sediment transport, dam reservoir, RBF, GRNN, prediction

Procedia PDF Downloads 469
3872 Symptomatic Strategies: Artistic Approaches Resembling Psychiatric Symptoms

Authors: B. Körner

Abstract:

This paper compares deviant behaviour in two different readings: 1) as symptomatic for so-called ‘mental illness’ and 2) as part of artistic creation. It analyses works of performance art in the respective frames of psychiatric evaluation and performance studies. This speculative comparison offers an alternative interpretation of mad behaviour beyond pathologisation. It questions the distinction of psychiatric diagnosis, which can contribute to reducing the stigmatisation of mad people. The stigma associated with madness entails exclusion, prejudice, and systemic oppression. Symptoms of psychiatric diagnoses can be considered as behaviour exceptional to the psychological norm. This deviant behaviour constitutes an outsider role which is also defining for the societal role of ‘the artist’, whose transgressions of the norm are expected and celebrated. The research proposes the term ‘artistic exceptionalism’ for this phenomenon. In this study, a set of performance artworks are analysed within the frame of an art-theoretical interpretation and as if they were the basis of a psychiatric assessment. This critical comparison combines the perspective on ‘mental illness’ of mad studies with methods of interpretation used in performance studies. The research employs auto theory and artistic research; interweaving lived experience with scientific theory building through the double role of the author as both performance artist and survivor researcher. It is a distinctly personal and mad thought experiment. The research proposes three major categories of artistic strategies approaching madness: (a) confronting madness (processing and publicly addressing one's own experiences with mental distress through artistic creation), (b) creating critical conditions (conscious or unconscious, voluntary or involuntary creation of crisis situations in order to create an intense experience for a work of art), and (c) symptomatic strategies. This paper focuses on the last of the three categories: symptomatic strategies. These can be described as artistic methods with parallels to forms of coping with and/or symptoms of ‘mental disorders.’ These include, for example feverish activity, a bleak worldview, additional perceptions, an urge for order, and the intensification of emotional experience. The proposed categories are to be understood as a spectrum of approaches that are not mutually exclusive. This research does not aim to diagnose or pathologise artists or their strategies; disease value is neither sought nor assumed. Neither does it intend to belittle psychological suffering, implying that it cannot be so bad if it is productive for artists. It excludes certain approaches that romanticise and/or exoticise mental distress, for example, artistic portrayal of people in mental crisis (e.g., documentary-observational or exoticising depictions) or the deliberate and exaggerated imitation of their forms of expression and behaviour as ‘authentic’ (e.g., Art Brut). These are based on the othering of the Mad and thus perpetuate the social stigma to which they are subjected. By noting that the same deviant behaviour can be interpreted as the opposite in different contexts, this research offers an alternative approach to madness beyond the confines of psychiatry. It challenges the distinction of psychiatric diagnosis and exposes its social constructedness. Hereby, it aims to empower survivors and reduce the stigmatisation of madness.

Keywords: artistic research, mad studies, mental health, performance art, psychiatric stigma

Procedia PDF Downloads 51
3871 Artificial Neural Networks and Hidden Markov Model in Landslides Prediction

Authors: C. S. Subhashini, H. L. Premaratne

Abstract:

Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

Procedia PDF Downloads 361
3870 Exploring Challenges Faced by People Living with HIV/AIDS After Disclosure in Sub-Saharan Countries

Authors: Veliswa Nonfundo Hoho, Jabulani Gilford Kheswa

Abstract:

HIV/AIDS has been a long-term condition worldwide, which does not only affect physical health but also causes psychological and social challenges in people living with this condition. In Sub-Saharan countries, namely; Nigeria, Uganda, Zimbabwe and South Africa, people living with HIV/AIDS come across different challenges especially after one has disclosed his/her status. They experience stigma and discrimination, isolation, lack of accessing and receiving treatment, lack of support and experience psychological distress. By using the evidence-based systematic review as a form of methodology, journal articles, dissertations, internet, and books were explored. This paper seeks to describe the challenges faced by people living with HIV/AIDS after disclosure, which forms a critical component of HIV/AIDS prevention and treatment interventions. The disclosure process model is used to underpin the study. This theory allows one to understand when and why interpersonal and verbal self-disclosure is beneficial for individuals who live with concealable stigmatized identities such as HIV/AIDS. Literature findings advocate that both negative and positive results were noted after disclosing one’s HIV status and psychosocial well-being of the majority of people living with HIV/AIDS also get affected especially in societies which subscribe HIV/AIDS pandemic to witchcraft. As for the infected homosexuals, research indicates that they suffer in silence and to cover their emotional emptiness due to ostracism, they often report low- self-efficacy with regard to condom use and become susceptible to reinfections which further place their lives at heightened risk for low immune system. In this regard, this paper challenges the policies which protect the dignity of people living with HIV/AIDS and calls for unity and financial support in favour of psychoeducational programmes and support groups aimed at curbing discrimination.

Keywords: disclosure, discrimination, homosexuality, self-efficacy

Procedia PDF Downloads 196
3869 The Musician as the Athlete: Psychological Response to Injury

Authors: Shulamit Sternin

Abstract:

Athletes experience injuries that can have both a physical and psychological impact on the individual. In such instances, athletes are able to rely on the established field of sports psychology to facilitate holistic rehabilitation. Musicians, like athletes rely on their bodies to perform in much the same way athletes do and are also susceptible to injury. Due to the similar performative nature of succeeding as an athletes or a musician, these careers share many of the same primary psychological concerns and therefore it is reasonable that athletes and musicians may require similar rehabilitation post-injury. However, musicians face their own unique psychological challenges and understanding the needs of an injured athlete can serve as a foundation for understanding the injured musician but is not enough to fully rehabilitate an injured musician. The current research surrounding musicians and their injuries is primarily focused on physiological aspects of injury and rehabilitation; the psychological aspects have not yet received adequate attention resulting in poor musician rehabilitation post- injury. This review paper uses current models of psychological response to injury in athletes to draw parallels with the psychological response to injury in musicians. Search engines such as Medline and PsycInfo were systematically searched using specific key words, such as psychological response, injury, athlete, and musician. Studies that focused on post-injury psychology of either the musician or the athlete were included. Within the literature there is evidence to support psychological responses, unique to the musician, that are not accounted for by current models of response in athletes. The models of psychological response to injury in athletes are inadequate tools for application to the musician. Future directions for performance arts research that can fill the gaps in our understanding and modeling of musicians’ response to injury are discussed. A better understanding of the psychological impact of injuries on musicians holds significant implications for health care practitioners working with injured musicians. Understanding the unique barriers musicians face post-injury, and how support for this population must be tailored to properly suit musicians’ needs will aid in more holistic rehabilitation and a higher likelihood of musician’s returning to pre-injury performance levels.

Keywords: athlete, injury, musician, psychological response

Procedia PDF Downloads 175
3868 Protein Tertiary Structure Prediction by a Multiobjective Optimization and Neural Network Approach

Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

Abstract:

Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

Procedia PDF Downloads 177
3867 Predicting the Relationship Between the Corona Virus Anxiety and Psychological Hardiness in Staff Working at Hospital in Shiraz Iran

Authors: Gholam Reza Mirzaei, Mehran Roost

Abstract:

This research was conducted with the aim of predicting the relationship between coronavirus anxiety and psychological hardiness in employees working at Shahid Beheshti Hospital in Shiraz. The current research design was descriptive and correlational. The statistical population of the research consisted of all the employees of Shahid Beheshti Hospital in Shiraz in 2021. From among the statistical population, 220 individuals were selected and studied based on available sampling. To collect data, Kobasa's psychological hardiness questionnaire and coronavirus anxiety questionnaire were used. After collecting the data, the scores of the participants were analyzed using Pearson's correlation coefficient multiple regression analysis and SPSS-24 statistical software. The results of Pearson's correlation coefficient showed that there is a significant negative correlation between psychological hardiness and its components (challenge, commitment, and control) with coronavirus anxiety; also, psychological hardiness with a beta coefficient of 0.20 could predict coronavirus anxiety in hospital employees. Based on the results, plans can be made to enhance psychological hardiness through educational workshops to relieve the anxiety of the healthcare staff.

Keywords: the corona virus, commitment, hospital employees, psychological hardiness

Procedia PDF Downloads 31
3866 Review: Wavelet New Tool for Path Loss Prediction

Authors: Danladi Ali, Abdullahi Mukaila

Abstract:

In this work, GSM signal strength (power) was monitored in an indoor environment. Samples of the GSM signal strength was measured on mobile equipment (ME). One-dimensional multilevel wavelet is used to predict the fading phenomenon of the GSM signal measured and neural network clustering to determine the average power received in the study area. The wavelet prediction revealed that the GSM signal is attenuated due to the fast fading phenomenon which fades about 7 times faster than the radio wavelength while the neural network clustering determined that -75dBm appeared more frequently followed by -85dBm. The work revealed that significant part of the signal measured is dominated by weak signal and the signal followed more of Rayleigh than Gaussian distribution. This confirmed the wavelet prediction.

Keywords: decomposition, clustering, propagation, model, wavelet, signal strength and spectral efficiency

Procedia PDF Downloads 422
3865 Artificial Intelligence-Generated Previews of Hyaluronic Acid-Based Treatments

Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

Abstract:

Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

Procedia PDF Downloads 87