Search results for: propensity score matching logit model
18045 The Relationship between Violence against Women in the Family and Common Mental Disorders in Urban Informal Settlements of Mumbai, India: A Cross-Sectional Study
Authors: Abigail Bentley, Audrey Prost, Nayreen Daruwalla, Apoorwa Gupta, David Osrin
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BACKGROUND: Intimate partner violence (IPV) can impact a woman’s physical, reproductive and mental health, including common mental disorders such as anxiety and depression. However, people other than an intimate partner may also perpetrate violence against women in the family, particularly in India. This study aims to investigate the relationship between experiences of violence perpetrated by the husband and other members of the wider household and symptoms of common mental disorders in women residing in informal settlement (slum) areas of Mumbai. METHODS: Experiences of violence were assessed through a detailed cross-sectional survey of 598 women, including questions about specific acts of emotional, economic, physical and sexual violence across different time points in the woman’s life and the main perpetrator of each act. Symptoms of common mental disorders were assessed using the 12-item General Health Questionnaire (GHQ-12). The GHQ-12 scores were divided into four groups and the relationship between experiences of each type of violence in the last 12 months and GHQ-12 score group was analyzed using ordinal logistic regression, adjusted for the woman’s age and clustering. RESULTS: 482 (81%) women consented to interview. On average, they were 28.5 years old, had completed 7 years of education and had been married 9 years. 88% were Muslim and 47% lived in joint and 53% in nuclear families. 44% of women had experienced at least one act of violence in their lifetime (33% emotional, 22% economic, 23% physical, 12% sexual). 7% had a high GHQ-12 score (6 or above). For violence experiences in the last 12 months, the odds of being in the highest GHQ-12 score group versus the lower groups combined were 13.1 for emotional violence, 6.5 for economic, 5.7 for physical and 6.3 for sexual (p<0.001 for all outcomes). DISCUSSION: The high level of violence reported across the lifetime could be due to the detailed assessment of violent acts at multiple time points and the inclusion of perpetrators within the family other than the husband. Each type of violence was associated with greater odds of a higher GHQ-12 score and therefore more symptoms of common mental disorders. Emotional violence was far more strongly associated with symptoms of common mental disorders than physical or sexual violence. However, it is not possible to attribute causal directionality to the association. Further work to investigate the relationship between differing severity of violence experiences and women’s mental health and the components of emotional violence that make it so strongly associated with symptoms of common mental disorders would be beneficial.Keywords: common mental disorders, family violence, India, informal settlements, mental health, violence against women
Procedia PDF Downloads 35918044 Strengths Profiling: An Alternative Approach to Assessing Character Strengths Based on Personal Construct Psychology
Authors: Sam J. Cooley, Mary L. Quinton, Benjamin J. Parry, Mark J. G. Holland, Richard J. Whiting, Jennifer Cumming
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Practitioners draw attention to people’s character strengths to promote empowerment and well-being. This paper explores the possibility that existing approaches for assessing character strengths (e.g., the Values in Action survey; VIA-IS) could be even more autonomy supportive and empowering when combined with strengths profiling, an ideographic tool informed by personal construct theory (PCT). A PCT approach ensures that: (1) knowledge is co-created (i.e., the practitioner is not seen as the ‘expert’ who leads the process); (2) individuals are not required to ‘fit’ within a prescribed list of characteristics; and (3) individuals are free to use their own terminology and interpretations. A combined Strengths Profiling and VIA approach was used in a sample of homeless youth (aged 16-25) who are commonly perceived as ‘hard-to-engage’ through traditional forms of assessment. Strengths Profiling was completed face-to-face in small groups. Participants (N = 116) began by listing a variety of personally meaningful characteristics. Participants gave each characteristic a score out of ten for how important it was to them (1 = not so important; 10 = very important), their ideal competency, and their current competency (1 = poor; 10 = excellent). A discrepancy score was calculated for each characteristic (discrepancy score = ideal score - current score x importance), whereby a lower discrepancy score indicated greater satisfaction. Strengths Profiling was used at the beginning and end of a 10-week positive youth development programme. Experiences were captured through video diary room entries made by participants and through reflective notes taken by the facilitators. Participants were also asked to complete a pre-and post-programme questionnaire, measuring perceptions of well-being, self-worth, and resilience. All of the young people who attended the strengths profiling session agreed to complete a profile, and the majority became highly engaged in the process. Strengths profiling was found to be an autonomy supportive and empowering experience, with each participant identifying an average of 10 character strengths (M = 10.27, SD = 3.23). In total, 215 different character strengths were identified, each with varying terms and definitions used, which differed greatly between participants and demonstrated the value in soliciting personal constructs. Using the participants’ definitions, 98% of characteristics were categorized deductively into the VIA framework. Bravery, perseverance, and hope were the character strengths that featured most, whilst temperance and courage received the highest discrepancy scores. Discrepancy scores were negatively correlated with well-being, self-worth, and resilience, and meaningful improvements were recorded following the intervention. These findings support the use of strengths profiling as a theoretically-driven and novel way to engage disadvantaged youth in identifying and monitoring character strengths. When young people are given the freedom to express their own characteristics, the resulting terminologies extend beyond the language used in existing frameworks. This added freedom and control over the process of strengths identification encouraged youth to take ownership over their profiles and apply their strengths. In addition, the ability to transform characteristics post hoc into the VIA framework means that strengths profiling can be used to explore aggregated/nomothetic hypotheses, whilst still benefiting from its ideographic roots.Keywords: ideographic, nomothetic, positive youth development, VIA-IS, assessment, homeless youth
Procedia PDF Downloads 20118043 Investigation of the Effect of Eye Exercises and Convergence Exercise on Visual Acuity in School-Age Children with Hypermetropia
Authors: Gulay Aras, Isil Kutluturk Karagoz, Z. Candan Algun
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Background: Hypermetropia in school-age is a pathology that responds to treatment. In the literature, there has been no study of exercise practice in hypermetropia treatment. Objective: The purpose of this study was to investigate the effects of eye exercises and convergence exercise on visual acuity in school-age children with hypermetropia. Methods: Forty volunteer school-age children with hypermetropia (30 girls, 30 boys, between 7-17 years of age) were included in the study. Sociodemographic information and clinical characteristics were evaluated. 40 participants were randomly divided into two groups: eye exercises and convergence exercises. Home exercise protocols were given to all groups for six weeks, and regular phone calls were made once a week. Individuals performed eye exercises 10 times, convergence exercises 5 min. for two sessions per day for six weeks. The right and left eyes of all the subjects participating in the study were assessed separately by the eye doctor with a Snellen chart. The participants' quality of life was assessed using Pediatric Quality of Life Inventory Version 4.0. Physical health total score (PHTS) and scale total score (STS), which were obtained by evaluating Psychosocial health total score (PSHTS) school, emotional and social functioning, were calculated separately in the scores. At the end of the exercise program, the assessment tests applied at the beginning of the study were reapplied to all individuals. Results: There was no statistically significant difference between the pre- and post-Snellen chart measurements and quality of life in the eye exercises group (p > 0,05). There was a statistically significant difference in visual acuity of right and left eyes (p=0,004, p=0,014) and quality of life in PHTS, PSHTS and STS in the convergence exercise group (p=0,001, p=0,017, p=0,001). Conclusions: In school-age children, convergence exercises were found to be effective on visual acuity and health-related quality of life. Convergence exercises are recommended for the treatment of school-aged children with hypermetropia.Keywords: convergence exercise, eye exercises, hypermetropia, school-age children
Procedia PDF Downloads 25018042 Crowdfunding for Saudi Arabia Green Projects
Authors: Saleh Komies, Mona Alharbi, Razan Alhayyani, Mozah Almulhim, Roseanne Khawaja, Ahmed Alradhi
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One of the proposed solutions that faces some challenges is encouraging sustainable energy consumption across Saudi Arabia through crowdfunding platforms. To address these challenges, we need to determine the level of awareness of crowdfunding and green projects, as well as the preferences and willingness of Saudis to utilize crowdfunding as an alternative funding source for green projects in Saudi Arabia. In this study, we aim to determine the influence of environmental awareness and concern on the propensity to crowdfund green projects. The survey is being conducted as part of environmental initiatives to assess public perceptions and opinions on crowdfunding green projects in Saudi Arabia. A total of 450 responses to an online questionnaire distributed via convenience and snowball sampling were utilized for data analysis. The survey reveals that Saudis have a low understanding of crowdfunding concepts and a relatively high understanding of implementing green projects. The public is interested in crowdfunding green projects if there is a return on investment.Keywords: crowdfunding, green projects, awareness, Saudi Arabia, energy, solar, wind
Procedia PDF Downloads 9918041 Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information
Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin
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The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.Keywords: frame freezing, mean opinion score, objective assessment, subjective evaluation
Procedia PDF Downloads 49418040 UBCSAND Model Calibration for Generic Liquefaction Triggering Curves
Authors: Jui-Ching Chou
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Numerical simulation is a popular method used to evaluate the effects of soil liquefaction on a structure or the effectiveness of a mitigation plan. Many constitutive models (UBCSAND model, PM4 model, SANISAND model, etc.) were presented to model the liquefaction phenomenon. In general, inputs of a constitutive model need to be calibrated against the soil cyclic resistance before being applied to the numerical simulation model. Then, simulation results can be compared with results from simplified liquefaction potential assessing methods. In this article, inputs of the UBCSAND model, a simple elastic-plastic stress-strain model, are calibrated against several popular generic liquefaction triggering curves of simplified liquefaction potential assessing methods via FLAC program. Calibrated inputs can provide engineers to perform a preliminary evaluation of an existing structure or a new design project.Keywords: calibration, liquefaction, numerical simulation, UBCSAND Model
Procedia PDF Downloads 17418039 Mild Auditory Perception and Cognitive Impairment in mid-Trimester Pregnancy
Authors: Tahamina Begum, Wan Nor Azlen Wan Mohamad, Faruque Reza, Wan Rosilawati Wan Rosli
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To assess auditory perception and cognitive function during pregnancy is necessary as the pregnant women need extra effort for attention mainly for their executive function to maintain their quality of life. This study aimed to investigate neural correlates of cognitive and behavioral processing during mid trimester pregnancy. Event-Related Potentials (ERPs) were studied by using 128-sensor net and PAS or COWA (controlled Oral Word Association), WCST (Wisconsin Card Sorting Test), RAVLTIM (Rey Auditory Verbal and Learning Test: immediate or interference recall, delayed recall (RAVLT DR) and total score (RAVLT TS) were tested for neuropsychology assessment. In total 18 subjects were recruited (n= 9 in each group; control and pregnant group). All participants of the pregnant group were within 16-27 (mid trimester) weeks gestation. Age and education matched control healthy subjects were recruited in the control group. Participants were given a standardized test of auditory cognitive function as auditory oddball paradigm during ERP study. In this paradigm, two different auditory stimuli (standard and target stimuli) were used where subjects counted silently only target stimuli with giving attention by ignoring standard stimuli. Mean differences between target and standard stimuli were compared across groups. N100 (auditory sensory ERP component) and P300 (auditory cognitive ERP component) were recorded at T3, T4, T5, T6, Cz and Pz electrode sites. An equal number of electrodes showed non-significantly shorter amplitude of N100 component (except significantly shorter at T3, P= 0.05) and non-significant longer latencies (except significantly longer latency at T5, P= 0.008) of N100 component in pregnant group comparing control. In case of P300 component, maximum electrode sites showed non-significantly higher amplitudes and equal number of sites showed non-significant shorter latencies in pregnant group comparing control. Neuropsychology results revealed the non-significant higher score of PAS, lower score of WCST, lower score of RAVLTIM and RAVLTDR in pregnant group comparing control. The results of N100 component and RAVLT scores concluded that auditory perception is mildly impaired and P300 component proved very mild cognitive dysfunction with good executive functions in second trimester of pregnancy.Keywords: auditory perception, pregnancy, stimuli, trimester
Procedia PDF Downloads 38418038 From Text to Data: Sentiment Analysis of Presidential Election Political Forums
Authors: Sergio V Davalos, Alison L. Watkins
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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.Keywords: sentiment analysis, text mining, user generated content, US presidential elections
Procedia PDF Downloads 19218037 Factor Associated with Uncertainty Undergoing Hematopoietic Stem Cell Transplantation
Authors: Sandra Adarve, Jhon Osorio
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Uncertainty has been studied in patients with different types of cancer, except in patients with hematologic cancer and undergoing transplantation. The purpose of this study was to identify factors associated with uncertainty in adults patients with malignant hemato-oncology diseases who are scheduled to undergo hematopoietic stem cell transplantation based on Merle Mishel´s Uncertainty theory. This was a cross-sectional study with an analytical purpose. The study sample included 50 patients with leukemia, myeloma, and lymphoma selected by non-probability sampling by convenience and intention. Sociodemographic and clinical variables were measured. Mishel´s Scale of Uncertainty in Illness was used for the measurement of uncertainty. A bivariate and multivariate analyses were performed to explore the relationships and associations between the different variables and uncertainty level. For this analysis, the distribution of the uncertainty scale values was evaluated through the Shapiro-Wilk normality test to identify statistical tests to be used. A multivariate analysis was conducted through a logistic regression using step-by-step technique. Patients were 18-74 years old, with a mean age of 44.8. Over time, the disease course had a median of 9.5 months, an opportunity was found in the performance of the transplantation of < 20 days for 50% of the patients. Regarding the uncertainty scale, a mean score of 95.46 was identified. When the dimensions of the scale were analyzed, the mean score of the framework of stimuli was 25.6, of cognitive ability was 47.4 and structure providers was 22.8. Age was identified to correlate with the total uncertainty score (p=0.012). Additionally, a statistically significant difference was evidenced between different religious creeds and uncertainty score (p=0.023), education level (p=0.012), family history of cancer (p=0.001), the presence of comorbidities (p=0.023) and previous radiotherapy treatment (p=0.022). After performing logistic regression, previous radiotherapy treatment (OR=0.04 IC95% (0.004-0.48)) and family history of cancer (OR=30.7 IC95% (2.7-349)) were found to be factors associated with the high level of uncertainty. Uncertainty is present in high levels in patients who are going to be subjected to bone marrow transplantation, and it is the responsibility of the nurse to assess the levels of uncertainty and the presence of factors that may contribute to their presence. Once it has been valued, the uncertainty must be intervened from the identified associated factors, especially all those that have to do with the cognitive capacity. This implies the implementation and design of intervention strategies to improve the knowledge related to the disease and the therapeutic procedures to which the patients will be subjected. All interventions should favor the adaptation of these patients to their current experience and contribute to seeing uncertainty as an opportunity for growth and transcendence.Keywords: hematopoietic stem cell transplantation, hematologic diseases, nursing, uncertainty
Procedia PDF Downloads 16618036 Channel Estimation for Orthogonal Frequency Division Multiplexing Systems over Doubly Selective Channels Base on DCS-DCSOMP Algorithm
Authors: Linyu Wang, Furui Huo, Jianhong Xiang
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The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low SNR stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.Keywords: OFDM, doubly selective, channel estimation, compressed sensing
Procedia PDF Downloads 9518035 Voice over IP Quality of Service Evaluation for Mobile Ad Hoc Network in an Indoor Environment for Different Voice Codecs
Authors: Lina Abou Haibeh, Nadir Hakem, Ousama Abu Safia
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In this paper, the performance and quality of Voice over IP (VoIP) calls carried over a Mobile Ad Hoc Network (MANET) which has a number of SIP nodes registered on a SIP Proxy are analyzed. The testing campaigns are carried out in an indoor corridor structure having a well-defined channel’s characteristics and model for the different voice codecs, G.711, G.727 and G.723.1. These voice codecs are commonly used in VoIP technology. The calls’ quality are evaluated using four Quality of Service (QoS) metrics, namely, mean opinion score (MOS), jitter, delay, and packet loss. The relationship between the wireless channel’s parameters and the optimum codec is well-established. According to the experimental results, the voice codec G.711 has the best performance for the proposed MANET topologyKeywords: wireless channel modelling, Voip, MANET, session initiation protocol (SIP), QoS
Procedia PDF Downloads 22818034 Economic and Environmental Life Cycle Analysis of Construction and Demolition Waste Management System
Authors: Yanqing Yi, Maria Cristina Lavagnolo, Alessandro Manzardo
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Construction and demolition waste (C&DW) is a major challenge in the European Union, emphasizing the urgent need for appropriate waste management processes. Selecting these solutions is challenging, as it requires identifying efficient C&DW management techniques that balance acceptable practices, regulatory compliance, resource conservation, economic viability, and environmental concerns. Techniques for analyzing many kinds of criteria allow for the use of multi-criteria analysis in life cycle assessment (LCA). Although LCA is commonly used to analyze environmental effects, the economic factor has not been fully integrated into the LCA approach in C&DW management. The life cycle costing (LCC) approach was designed to assess economic performance in the C&DW management process. The choice of an effective multi-criteria decision-making (MCDM) technique is critical for the C&DW system. This study seeks to propose a model that employs MCDM by considering LCA and LCC results, thereby augmenting both environmental and economic sustainability. A widely used compensatory MCDM technique, TOPSIS, has been chosen to identify the most effective C&DW management scheme by comparing and ranking various scenarios. Four waste management alternatives were examined in the Lombardy region of Italy, namely, (i) landfill; (ii) recycling for concrete production and road construction, incineration with energy recovery; (iii) recycling for road construction; (iv) recycling for concrete production and road construction. We determine that, with the implementation of various scenarios, the most suitable scenario emerges to be recycled for concrete production and road construction, with a score of 0.711/1; recycling for road construction, with a final score of 0.291/1, ranks second; recycling for concrete production and road construction, incineration with energy recovery scores 0.002/1, ranks third; and landfill (scores: 0/1) is the worst choice, indicating it has the highest environmental impact. Finally, suggestions were developed to improve the system's environmental performance.Keywords: life cycle assessment, life cycle costing, construction and demolition waste, multi-criteria decision making
Procedia PDF Downloads 7118033 Sentiment Analysis of Social Media Responses: A Comparative Study of (NDA) and Indian National Developmental Inclusive Alliance (INDIA) during Indian General Elections 2024
Authors: Pankaj Dhiman, Simranjeet Kaur
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This research paper presents a comprehensive sentiment analysis of social media responses to videos on Facebook, YouTube, Twitter, and Instagram during the 2024 Indian general elections. The study focuses on the sentiment patterns of voters towards the National Democratic Alliance (NDA) and The Indian National Developmental Inclusive Alliance (INDIA) on these platforms. The analysis aims to understand the impact of social media on voter sentiment and its correlation with the election outcome. The study employed a mixed-methods approach, combining both quantitative and qualitative methods. With a total of 200 posts analysed during general election-2024 final phase, the sentiment analysis was conducted using natural language processing (NLP) techniques, including sentiment dictionaries and machine learning algorithms. The results show that NDA received significantly more positive sentiment responses across all platforms, with a positive sentiment score of 47% compared to INDIA's score of 38.98 %. The analysis also revealed that Twitter and YouTube were the most influential platforms in shaping voter sentiment, with 60% of the total sentiment score coming from these two platforms. The study's findings suggest that social media sentiment analysis can be a valuable tool for understanding voter sentiment and predicting election outcomes. The results also highlight the importance of social media in shaping public opinion and the need for political parties to engage effectively with voters on these platforms. The study's implications are significant, as they indicate that social media can be a key factor in determining the outcome of elections. The findings also underscore the need for political parties to develop effective social media strategies to engage with voters and shape public opinion.Keywords: Indian Elections-2024, NDA, INDIA, sentiment analysis, social media, democracy
Procedia PDF Downloads 5218032 A Crop Growth Subroutine for Watershed Resources Management (WRM) Model 1: Description
Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu
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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies.Keywords: runoff, roughness coefficient, PAR, WRM model
Procedia PDF Downloads 37818031 Measures of Reliability and Transportation Quality on an Urban Rail Transit Network in Case of Links’ Capacities Loss
Authors: Jie Liu, Jinqu Cheng, Qiyuan Peng, Yong Yin
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Urban rail transit (URT) plays a significant role in dealing with traffic congestion and environmental problems in cities. However, equipment failure and obstruction of links often lead to URT links’ capacities loss in daily operation. It affects the reliability and transport service quality of URT network seriously. In order to measure the influence of links’ capacities loss on reliability and transport service quality of URT network, passengers are divided into three categories in case of links’ capacities loss. Passengers in category 1 are less affected by the loss of links’ capacities. Their travel is reliable since their travel quality is not significantly reduced. Passengers in category 2 are affected by the loss of links’ capacities heavily. Their travel is not reliable since their travel quality is reduced seriously. However, passengers in category 2 still can travel on URT. Passengers in category 3 can not travel on URT because their travel paths’ passenger flow exceeds capacities. Their travel is not reliable. Thus, the proportion of passengers in category 1 whose travel is reliable is defined as reliability indicator of URT network. The transport service quality of URT network is related to passengers’ travel time, passengers’ transfer times and whether seats are available to passengers. The generalized travel cost is a comprehensive reflection of travel time, transfer times and travel comfort. Therefore, passengers’ average generalized travel cost is used as transport service quality indicator of URT network. The impact of links’ capacities loss on transport service quality of URT network is measured with passengers’ relative average generalized travel cost with and without links’ capacities loss. The proportion of the passengers affected by links and betweenness of links are used to determine the important links in URT network. The stochastic user equilibrium distribution model based on the improved logit model is used to determine passengers’ categories and calculate passengers’ generalized travel cost in case of links’ capacities loss, which is solved with method of successive weighted averages algorithm. The reliability and transport service quality indicators of URT network are calculated with the solution result. Taking Wuhan Metro as a case, the reliability and transport service quality of Wuhan metro network is measured with indicators and method proposed in this paper. The result shows that using the proportion of the passengers affected by links can identify important links effectively which have great influence on reliability and transport service quality of URT network; The important links are mostly connected to transfer stations and the passenger flow of important links is high; With the increase of number of failure links and the proportion of capacity loss, the reliability of the network keeps decreasing, the proportion of passengers in category 3 keeps increasing and the proportion of passengers in category 2 increases at first and then decreases; When the number of failure links and the proportion of capacity loss increased to a certain level, the decline of transport service quality is weakened.Keywords: urban rail transit network, reliability, transport service quality, links’ capacities loss, important links
Procedia PDF Downloads 12818030 Effect of Low Calorie Sweeteners on Chemical, Sensory Evaluation and Antidiabetic of Pumpkin Jam Fortified with Soybean
Authors: Amnah M. A. Alsuhaibani, Amal N. Al-Kuraieef
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Introduction: In the recent decades, production of low-calorie jams is needed for diabetics that comprise low calorie fruits and low calorie sweeteners. Object: the research aimed to prepare low calorie formulated pumpkin jams (fructose, stevia and aspartame) incorporated with soy bean and evaluate the jams through chemical analysis and sensory evaluation after storage for six month. Moreover, the possible effect of consumption of low calorie jams on diabetic rats was investigated. Methods: Five formulas of pumpkin jam with different sucrose, fructose, stevia and aspartame sweeteners and soy bean were prepared and stored at 10 oC for six month compared to ordinary pumpkin jam. Chemical composition and sensory evaluation of formulated jams were evaluated at zero time, 3 month and 6 month of storage. The best three acceptable pumpkin jams were taken for biological study on diabetic rats. Rats divided into group (1) served as negative control and streptozotocin induce diabetes four rat groups that were positive diabetic control (group2), rats fed on standard diet with 10% sucrose soybean jam, fructose soybean jam and stevia soybean jam (group 3, 4&5), respectively. Results: The content of protein, fat, ash and fiber were increased but carbohydrate was decreased in low calorie formulated pumpkin jams compared to ordinary jam. Production of aspartame soybean pumpkin jam had lower score of all sensory attributes compared to other jam then followed by stevia soybean Pumpkin jam. Using non nutritive sweeteners (stevia & aspartame) with soybean in processing jam could lower the score of the sensory attributes after storage for 3 and 6 months. The highest score was recorded for sucrose and fructose soybean jams followed by stevia soybean jam while aspartame soybean jam recorded the lowest score significantly. The biological evaluation showed a significant improvement in body weight and FER of rats after six weeks of consumption of standard diet with jams (Group 3,4&5) compared to Group1. Rats consumed 10% low calorie jam with nutrient sweetener (fructose) and non nutrient sweetener (stevia) soybean jam (group 4& 5) showed significant decrease in glucose level, liver function enzymes activity, and liver cholesterol & total lipids in addition of significant increase of insulin and glycogen compared to the levels of group 2. Conclusion: low calorie pumpkin jams can be prepared by low calorie sweeteners and soybean and also storage for 3 months at 10oC without change sensory attributes. Consumption of stevia pumpkin jam fortified with soybean had positive health effects on streptozoticin induced diabetes in rats.Keywords: pumpkin jam, HFCS, aspartame, stevia, storage
Procedia PDF Downloads 18318029 An Intelligent Text Independent Speaker Identification Using VQ-GMM Model Based Multiple Classifier System
Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa
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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)
Procedia PDF Downloads 30918028 Antecedent Factors Affecting Evaluation of Quality of Students at Graduate School
Authors: Terada Pinyo
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This study is a survey research designed to evaluate the quality of graduate students and factors influencing their quality. The sample group consists of 240 students. The data are collected from stratified sampling and are analyzed and calculated by instant computer program. Statistics used are percentage, mean, standard deviation, Pearson correlation coefficient, Cramer’s V and logistic regression analysis. It is found that the graduate students’ opinions regarding their characteristics according to the Thai Qualifications Framework for Higher Education (TQF) are at high score range both overall and specific category. The top categories that received the top score are interpersonal skills and responsibility, ethics and morals, knowledge, cognitive skills, numerical analysis with communication and information technology skills, respectively. On the other hand, factors affecting the quality of graduate students are cognitive skills, numerical analysis with communication and information technology, knowledge, interpersonal skills and responsibility, ethics and morals, and career regarding sales/business, respectively.Keywords: student quality evaluation, Thai qualifications framework for higher education, graduate school, cognitive skills
Procedia PDF Downloads 39518027 Stock Market Prediction by Regression Model with Social Moods
Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome
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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.Keywords: stock market prediction, social moods, regression model, DJIA
Procedia PDF Downloads 54918026 The Effectiveness of Self-Compassion Training: A Field Trial Study
Authors: Esmaeil Sarikhani
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Objectives: Considering the importance of introducing new methods of improving self-compassion and compassion to the others in nursing students, this study intends to evaluate the effect of self-compassion training on nursing students. Methods: This is a field trial study in which 52 nursing interns from Isfahan University of Medical Sciences were selected using convenience sampling method and divided in two experimental and control groups. The sampling was done during two phases: before and after the intervention. The intervention consisted of eight sessions over eight weeks of self-compassion training. The data were collected using the self-compassion standard questionnaire with 26 questions before and after the intervention. Data were then analyzed by the SPSS18 software and independent and paired T-tests, and also Chi-square and Mann-Whitney tests. Results: The results obtained from the independent t-test showed that the mean score of self-compassion and its components in the experimental group was significantly increased compared to the control group (p < 0.001). Comparing the groups, the mean overall score difference of self-compassion and its components had also a statistically significant change after the intervention (p < 0.001). Conclusion: Self-compassion training program, leads to improving nursing students' self-compassion. As it seems, this method can be used as an important training course in order to improve compassion of nursing students to themselves and the others.Keywords: self-compassion, student, nursing students, field trial
Procedia PDF Downloads 28418025 Public Preferences and Willingness to Pay for Social Health Insurance in Iran: A Discrete Choice Experiment
Authors: Mohammad Ranjbar, Mohammad Bazyar, Blake Angell, Thomas Lung, Yibeltal Assefa
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Background: Current health insurance programs in Iran suffer from low enrolment and are not sufficient to attain the country to universal health coverage (UHC). We hypothesize that improving the enrollment rate and moving towards a more sustainable UHC can be achieved by improving the benefits package and providing new incentives. The objective of this study is to assess public preferences and willingness to pay (WTP) for social health insurance (SHI) in Iran. Methods: A discrete choice experiment (DCE) was conducted in 2021, using a self-administered questionnaire on 500 participants to estimate WTP and determine individual preferences for the SHI in Yazd, Iran. Respondents were presented with an eight-choice set and asked to select their preferred one. In each choice set, scenarios were described by eight attributes with varying levels. The conditional logit regression model was used to analyze the participants' preferences. Willingness to pay for each attribute was also calculated. Results: Most included attributes were significant predictors of the choice of a health insurance package. The maximum coverage of hospitalization costs in the private sector, ancillary services such as glasses, canes, etc., as well as coverage for hospitalization costs in the public sector and drug costs, were the most important determining factors for this choice. Coverage of preventive dental care did not significantly influence respondent choices. Estimating WTP showed that individuals are willing to pay more for higher financial protection, particularly against private sector costs; the WTP to increase the coverage of hospitalization costs in the private sector from 50% to 90% is estimated at 362,068 IR, Rials per month. Conclusion: This study identifies the key factors that the population value with regard to health insurance and the tradeoffs they are willing to make between them. Hospitalization, drugs, and ancillary services were the most important determining factors for their choice. The data suggest that additional resources coming into the Iranian health system might best be prioritized to cover hospitalization and drug costs and those associated with ancillary services.Keywords: social health insurance, preferences, discrete choice experiment, willingness to pay
Procedia PDF Downloads 8918024 YOLO-IR: Infrared Small Object Detection in High Noise Images
Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long
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Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion
Procedia PDF Downloads 7318023 Structural Equation Modeling Semiparametric Truncated Spline Using Simulation Data
Authors: Adji Achmad Rinaldo Fernandes
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SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model
Procedia PDF Downloads 4118022 Data-Driven Insights Into Juvenile Recidivism: Leveraging Machine Learning for Rehabilitation Strategies
Authors: Saiakhil Chilaka
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Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.Keywords: juvenile, justice system, data analysis, SHAP
Procedia PDF Downloads 2318021 Method to Assessing Aspect of Sustainable Development-Walkability
Authors: Amna Ali Nasser Al-Saadi, Riken Homma, Kazuhisa Iki
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Need to generate objective communication between researchers, Practitioners and policy makers are top concern of sustainability. Despite the fact that many places have successes in achieving some aspects of sustainable urban development, there are no scientific facts to convince policy makers in the rest of the world to apply their guides and manuals. This is because each of them was developed to fulfill the need of specific city. The question is, how to learn the lesson from each case study? And how distinguish between the potential criteria and negative one? And how quantify their effects in the future development? Walkability has been found as a solution to achieve healthy life style as well as social, environmental and economic sustainability. Moreover, it is complicated as every aspect of sustainable development. This research is stand on quantitative- comparative methodology in order to assess pedestrian oriented development. Three Analyzed Areas (AAs) were selected. One site is located in Oman in which hypotheses as motorized oriented development, while two sites are in Japan where the development is pedestrian friendly. The study used Multi-Criteria Evaluation Method (MCEM). Initially, MCEM stands on Analytic Hierarchy Process (AHP). The later was structured into main goal (walkability), objectives (functions and layout) and attributes (the urban form criteria). Secondly, the GIS were used to evaluate the attributes in multi-criteria maps. Since each criterion has different scale of measurement, all results were standardized by z-score and used to measure the co-relations among cr iteria. Different scenario was generated from each AA. After that, MCEM (AHP- OWA) based on GIS measured the walkability score and determined the priority of criteria development in the non-walker friendly environment. As results, the comparison criteria for z-score presented a measurable distinguished orientation of development. This result has been used to prove that Oman is motorized environment while Japan is walkable. Also, it defined the powerful criteria and week criteria regardless to the AA. This result has been used to generalize the priority for walkable development.Keywords: walkability, sustainable development, multi- criteria evaluation method, gis
Procedia PDF Downloads 45318020 Weighted Risk Scores Method Proposal for Occupational Safety Risk Assessment
Authors: Ulas Cinar, Omer Faruk Ugurlu, Selcuk Cebi
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Occupational safety risk management is the most important element of a safe working environment. Effective risk management can only be possible with accurate analysis and evaluations. Scoring-based risk assessment methods offer considerable ease of application as they convert linguistic expressions into numerical results. It can also be easily adapted to any field. Contrary to all these advantages, important problems in scoring-based methods are frequently discussed. Effective measurability is one of the most critical problems. Existing methods allow experts to choose a score equivalent to each parameter. Therefore, experts prefer the score of the most likely outcome for risk. However, all other possible consequences are neglected. Assessments of the existing methods express the most probable level of risk, not the real risk of the enterprises. In this study, it is aimed to develop a method that will present a more comprehensive evaluation compared to the existing methods by evaluating the probability and severity scores, all sub-parameters, and potential results, and a new scoring-based method is proposed in the literature.Keywords: occupational health and safety, risk assessment, scoring based risk assessment method, underground mining, weighted risk scores
Procedia PDF Downloads 13618019 Comparative Study of Analgesic Efficacy of Ultrasound Guided Femoral Nerve Block Versus Intravenous Fentanyl Injection in Fracture Femur Patients at Emergency Department
Authors: Asmaa Hamdy, Israa Nassar, Tarek Aly
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Introduction: Femoral fractures are the most common presentation in the Emergency Department (ED), and they can present as isolated injuries or as part of a polytrauma situation. To provide optimum pain management care to these patients, practitioners must be well prepared and current with utilizing modern evidence-based knowledge and practices. Management of pain associated with fracture femur in the emergency department has a critical role in the satisfaction of patients and preventing further complications. This study aimed to evaluate the analgesic efficacy of ultrasound-guided femoral nerve block compared with intravenous fentanyl in fractures of the femur in patients presented to the Emergency Department. Patients and Methods: Fifty patients with femur fractures were divided into two groups: Group A: In this group (twenty-five patients) were given intravenous fentanyl 2 micro-grams/kg and re-assessed for pain by Visual Analogue Score (VAS). Group B: In this group (twenty-five patients) underwent ultrasonography-guided femoral nerve block and were re-assessed for pain by VAS. Results: VAS score on the movement of the fractured limb between group A and group B at a 10-minute post-intervention period shows P= 0.043, and hence the difference is significant. VAS score on the movement of the fractured limb between group A and group B during a 10-minute post-intervention period showed a significant difference. Seventeen patients in group A had major PID with a percentage of 63% VS 10 patients in group B with a percentage of 37%. conclusion: both femoral nerve block and intravenous fentanyl are effective in relieving pain in patients with femur fractures. But femoral nerve block provides better and more intense analgesia and major pain intensity difference in less time. Moreover, the use of FNB had fewer side effects and more Hemodynamics stability compared to opioids.Keywords: femur fracture, nerve block, fentanyl, ultrasound guided
Procedia PDF Downloads 10018018 Attitudes of Secondary School Students towards Biology in Birnin Kebbi Metropolis, Kebbi State, Nigeria
Authors: I. A. Libata
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The present study was carried out to determine the attitudes of Secondary School Students towards Biology in Birnin Kebbi metropolis. The population of the study is 2680 SS 2 Secondary School Students in Birnin Kebbi metropolis. Proportionate random sampling was used in selecting the samples. Oppinnionnaire was the only instrument used in the study. The instrument was subjected to test-retest reliability. The reliability index of the instrument was 0.69. Overall scores of the Students were analyzed and a mean score was determined, the mean score of students was 85. There were no significant differences between the attitudes of male and female students. The results also revealed that there was significant difference between the attitude of science and art students. The results also revealed that there was significant difference between the attitude of public and private school students. The study also reveals that majority of students in Birnin Kebbi Metropolis have positive attitudes towards biology. Based on the findings of this study, the researcher recommended that teachers should motivate students, which they can do through their teaching styles and by showing them the relevance of the learning topics to their everyday lives. Government and the school management should create the learning environment that helps motivate students not only to come to classes but also want to learn and enjoy learning Biology.Keywords: attitudes, students, Birnin-Kebbi, metropolis
Procedia PDF Downloads 40218017 Investigation of the Relationship between Digital Game Playing, Internet Addiction and Perceived Stress Levels in University Students
Authors: Sevim Ugur, Cemile Kutmec Yilmaz, Omer Us, Sevdenur Koksaldi
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Aim: This study aims to investigate the effect of digital game playing and Internet addiction on perceived stress levels in university students. Method: The descriptive study was conducted through face-to-face interview method with a total of 364 university students studying at Aksaray University between November 15 and December 30, 2017. The research data were collected using personal information form, a questionnaire to determine the characteristics of playing digital game, the Internet addiction scale and the perceived stress scale. In the evaluation of the data, Mann-Whitney U test was used for two-group comparison of the sample with non-normal distribution, Kruskal-Wallis H-test was used in the comparison of more than two groups, and the Spearman correlation test was used to determine the relationship between Internet addiction and the perceived stress level. Results: It was determined that the mean age of the students participated in the study was 20.13 ± 1.7 years, 67.6% was female, 35.7% was sophomore, and 62.1% had an income 500 TL or less. It was found that 83.5% of the students use the Internet every day and 70.6% uses the Internet for 5 hours or less per day. Of the students, 12.4% prefers digital games instead of spending time outdoors, 8% plays a game as the first activity in leisure time, 12.4% plays all day, 15.7% feels anger when he/she is prevented from playing, 14.8% prefers playing games to get away from his/her problems, 23.4% had his/her school achievement affected negatively because of game playing, and 8% argues with family members due to the time spent for gaming. Students who play games on the computer for a long time were found to feel back pain (30.8%), headache (28.6%), insomnia (26.9%), dryness and pain in the eyes (26.6%), pain in the wrist (21.2%), feeling excessive tension and anger (16.2%), humpback (12.9), vision loss (9.6%) and pain in the wrist and fingers (7.4%). In our study, students' Internet addiction scale mean score was found to be 45.47 ± 16.1 and mean perceived stress scale score was 28.56 ± 2.7. A significant and negative correlation (p=0.037) was found between the total score of the Internet addiction scale and the total score of the perceived stress scale (r=-0.110). Conclusion: It was found in the study that Internet addiction and perceived stress of the students were at a moderate level and that there was a negative correlation between Internet addiction and perceived stress levels. Internet addiction was found to increase with the increasing perceived stress levels of students, and students were found to have health problems such as back pain, dryness in the eyes, pain, insomnia, headache, and humpback. Therefore, it is recommended to inform students about different coping methods other than spending time on the Internet to cope with the stress they perceive.Keywords: digital game, internet addiction, student, stress level
Procedia PDF Downloads 28818016 Atomic Decomposition Audio Data Compression and Denoising Using Sparse Dictionary Feature Learning
Authors: T. Bryan , V. Kepuska, I. Kostnaic
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A method of data compression and denoising is introduced that is based on atomic decomposition of audio data using “basis vectors” that are learned from the audio data itself. The basis vectors are shown to have higher data compression and better signal-to-noise enhancement than the Gabor and gammatone “seed atoms” that were used to generate them. The basis vectors are the input weights of a Sparse AutoEncoder (SAE) that is trained using “envelope samples” of windowed segments of the audio data. The envelope samples are extracted from the audio data by performing atomic decomposition with Gabor or gammatone seed atoms. This process identifies segments of audio data that are locally coherent with the seed atoms. Envelope samples are extracted by identifying locally coherent audio data segments with Gabor or gammatone seed atoms, found by matching pursuit. The envelope samples are formed by taking the kronecker products of the atomic envelopes with the locally coherent data segments. Oracle signal-to-noise ratio (SNR) verses data compression curves are generated for the seed atoms as well as the basis vectors learned from Gabor and gammatone seed atoms. SNR data compression curves are generated for speech signals as well as early American music recordings. The basis vectors are shown to have higher denoising capability for data compression rates ranging from 90% to 99.84% for speech as well as music. Envelope samples are displayed as images by folding the time series into column vectors. This display method is used to compare of the output of the SAE with the envelope samples that produced them. The basis vectors are also displayed as images. Sparsity is shown to play an important role in producing the highest denoising basis vectors.Keywords: sparse dictionary learning, autoencoder, sparse autoencoder, basis vectors, atomic decomposition, envelope sampling, envelope samples, Gabor, gammatone, matching pursuit
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