Search results for: Adult dataset

Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

Procedia PDF Downloads 97

Authors: Patrick M. Stanton, William R. McCumber

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Using a large dataset of more than 2,400 individual microfinance institutions (MFIs) from 120 countries from 1999 to 2016, this study finds that nearly half of the international MFIs operate as for-profit institutions. Formal institutions (business regulatory environment, property rights, social protection, and a developed financial sector) impact the likelihood of MFIs being for-profit across countries. Cultural differences across countries (power distance, individualism, masculinity, and indulgence) seem to be a factor in the legal status of the MFI (non-profit or for-profit). MFIs in countries with stronger formal institutions, a greater degree of power distance, and a higher degree of collectivism experience better financial and social performance.

Keywords: Hofstede cultural dimensions, international finance, microfinance institutions, non-profite

Procedia PDF Downloads 273

Authors: Ayşe Coban, Orhan Coban, Haldun Soydal, Sükrü Sürücü

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While health is a source of prosperity for individuals, it is also one of the most important determinants of economic growth for a country. Health, by increasing the productivity of labor, contributes to economic growth. Therefore, countries should give the necessary emphasis to health services. The primary aim of this study is to analyze the changes occurring in health services in Turkey by examining the developments in the sector. In this scope, the second aim of the study is to reveal the place of health expenditures in the Turkish economy. As a result of the analysis in the dataset, in which the 1999-2013 periods is considered, it was determined that some increase in health expenditures took place and that the increase in the share of health expenditures in GDP was too small. Furthermore, analysis of the results points out that in financing health expenditures, the public sector is prominent compared to the private sector.

Keywords: health, health service, health expenditures, Turkey

Procedia PDF Downloads 368

Authors: Betül Demirbağ, Nesrin Demir

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As a developmental period, early adulthood has a vital role in romantic relationships in young adult's life. lt's known that in this period, satisfaction of individual needs such as affiliation is essential for well-functioning and to be succeeded in sequent developmental task. Romantic relationships have an expected association with attachment style. But it's needed to get more information about indicators of romantic relationships in different cultural backgrounds. in this research it's aimed to investigate whether there is a relationship between romantic relationship beliefs and Ego identity status and also other possible indicators such as gender, age, socioeconomic status. Participants were undergraduate students training in various programs in Education Faculty in Adiyaman University. As data collection tool, Romantic Relationship Beliefs scale and Ego Identity Process Questionnaire which was adapted into Turkish were used. Results were discussed in the relevant literature.

Keywords: ego identity, romantic relationships, university counseling

Procedia PDF Downloads 560

Authors: Ehsan Ahmed Yahia

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Introduction: The nursing role in nutrition screening and assessing hospitalized patients is important. Malnutrition is a common and costly problem, particularly among hospitalized patients, and can have an adverse effect on the healing process. The study's goal is to assess the prevalence of malnutrition among adult hospitalized orthopedic patients and to detect the barriers to the nutrition screening process. Aim of the study: This study aimed to (a) assess the prevalence of malnutrition in hospitalized orthopedic patients and (b) evaluate the relationship between malnutrition and selected clinical outcomes. Material and Methods: This prospective field study was conducted for three months between 03/2022 and 06/2022 in the selected orthopedic departments in a teaching hospital affiliated withCairo University, Egypt. with a total number of one hundred twenty (120) patients. Patients' assessment included checking for malnutrition using the Nutritional Risk Screening Questionnaire. Patients at risk for malnourishment were defined as NRS score ≥ 3. Clinical outcomes under consideration included 1) length of hospitalization, 2) mobilization after surgery and conservative treatment, and 3) rate of adverse events. Results: This study found that malnutrition is a significant problem among patients hospitalized in an orthopedic ward. The prevalence of malnutrition was the highest in patients with lumbar spine and pelvis fractures, followed by the proximal femur and proximal humerus fractures. Patients at risk for malnutrition had significantly prolonged hospitalization, delayed postoperative mobilization, and increased incidence of adverse events.27.8% of the study sample were at risk for malnutrition. The highest prevalence of malnourishment was found in Septic Surgery with 32%, followed by Traumatology with 19.6% and Arthroplasty with 15.3%. A higher prevalence of malnutrition was detected among patients with typical fractures, such as lumbar spine and pelvis (46.7%), proximal femur (34.4%), and proximal humeral (23.7%) fractures. Additionally, patients at risk for malnutrition showed prolonged hospitalization (14.7 ± 11.1 vs. 21.2 ± 11.7 days), delayed postoperative mobilization (2.3 ± 2.9 vs. 4.1 ± 4.9 days), and delayed to mobilize after conservative treatment (1.1 ± 2.7 vs. 1.8 ± 1.9 days). A significant statistical correlation of NRS with individual parameters (Spearman's rank correlation, p < 0.05) was observed. The rate of adverse incidents in patients at risk for malnutrition was significantly higher than that of patients with a regular nutritional status (37.2% vs. 21.1%, p < 0.001). Conclusions: Our results indicate that the prevalence of malnutrition in surgical patients is significant. The nutritional status of patients with typical fractures is especially at risk. Prolonged hospitalization, delayed postoperative mobilization, and delayed mobilization after conservative treatment is significantly associated with malnutrition. In addition, the incidence of adverse events in patients at risk for malnutrition is significantly higher.

Keywords: malnutrition, nutritional risk screening, surgery, nursing, orthopedic nurse

Procedia PDF Downloads 99

Authors: Andrew Kurochkin, Kostiantyn Bokhan

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In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

Procedia PDF Downloads 138

Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

Procedia PDF Downloads 338

Authors: Michael Kenomore, Mohamed Hassan, Amjad Shah, Hom Dhakal

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Shale gas reservoirs have been of greater importance compared to shale oil reservoirs since 2009 and with the current nature of the oil market, understanding the technical and economic performance of shale gas reservoirs is of importance. Using the Barnett shale as a case study, an economic model was developed to quantify the effect of finding and development costs and gas prices on the basins in the Barnett shale using net present value as an evaluation parameter. A rate of return of 20% and a payback period of 60 months or less was used as the investment hurdle in the model. The Barnett was split into four basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bend-arch Basin) with analysis conducted on each of the basin to provide a holistic outlook. The dataset consisted of only horizontal wells that started production from 2008 to at most 2015 with 1835 wells coming from the strawn basin, 137 wells from the Ouachita folded belt, 55 wells from the bend-arch basin and 724 wells from the forth-worth syncline. The data was analyzed initially on Microsoft Excel to determine the estimated ultimate recoverable (EUR). The range of EUR from each basin were loaded in the Palisade Risk software and a log normal distribution typical of Barnett shale wells was fitted to the dataset. Monte Carlo simulation was then carried out over a 1000 iterations to obtain a cumulative distribution plot showing the probabilistic distribution of EUR for each basin. From the cumulative distribution plot, the P10, P50 and P90 EUR values for each basin were used in the economic model. Gas production from an individual well with a EUR similar to the calculated EUR was chosen and rescaled to fit the calculated EUR values for each basin at the respective percentiles i.e. P10, P50 and P90. The rescaled production was entered into the economic model to determine the effect of the finding and development cost and gas price on the net present value (10% discount rate/year) as well as also determine the scenario that satisfied the proposed investment hurdle. The finding and development costs used in this paper (assumed to consist only of the drilling and completion costs) were £1 million, £2 million and £4 million while the gas price was varied from $2/MCF-$13/MCF based on Henry Hub spot prices from 2008-2015. One of the major findings in this study was that wells in the bend-arch basin were least economic, higher gas prices are needed in basins containing non-core counties and 90% of the Barnet shale wells were not economic at all finding and development costs irrespective of the gas price in all the basins. This study helps to determine the percentage of wells that are economic at different range of costs and gas prices, determine the basins that are most economic and the wells that satisfy the investment hurdle.

Keywords: shale gas, Barnett shale, unconventional gas, estimated ultimate recoverable

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Authors: Milind D. Meshram

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Ascarids are the most frequent worm parasite of dogs and cats. There are two species that commonly infect dogs: Toxocara canis and Toxascaris leonina. Adult roundworms live in the stomach and intestines and can grow to 7 inches (18 cm) long. A female may lay 200,000 eggs in a day. The eggs are protected by a hard shell. They are extremely hardy and can live for months or years in the soil. A dog aged about 6 years, from Satara was referred to Teaching Veterinary Clinical Complex (TVCC) with a complaint of abdominal pain, anorexia, loss of condition and dull body coat with mucous pale membrane. The clinical examination revealed Anaemia, palpation of abdomen revealed enlargement of liver, slimy feel of the intestine loop, diarrhea.

Keywords: therapeutic management, Toxocara canis, induced hepatitis, dogs

Procedia PDF Downloads 592

Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

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Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

Procedia PDF Downloads 202

Authors: Eugen Dimant, Tim Krieger, Margarete Redlin

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This paper analyzes the impact of migration on destination-country corruption levels. Capitalizing on a comprehensive dataset consisting of annual immigration stocks of OECD coun-tries from 207 countries of origin for the period 1984-2008, we explore different channels through which corruption might migrate. We employ different estimation methods using fixed effects and Tobit regressions in order to validate our findings. What is more, we also address the issue of endogeneity by using the Difference-Generalized Method of Moments (GMM) estimator. Independent of the econometric methodology we consistently find that while general migration has an insignificant effect on the destination country’s corruption level, immigration from corruption-ridden origin countries boosts corruption in the destination country. Our findings provide a more profound understanding of the economic implications associated with migration flows.

Keywords: corruption, migration, impact of migration, destination-country corruption

Procedia PDF Downloads 326

Authors: Austyn Snowden

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Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

Procedia PDF Downloads 466

Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

Procedia PDF Downloads 154

Authors: Mansi Chinchanikar

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Homoeopathy is the second most widely used medical system in the world, yet the homoeopaths of India and around the world are sick of reading or hearing about how homoeopathy is only a placebo effect and cannot cure or even manage any disease. However, individuals making such unfounded claims should explain to the group how a homoeopathic placebo, particularly one for a neurodevelopmental disease like Attention Deficit Hyperactivity Disorder (ADHD), can be effective in children, with studies to back it up their skeptics. This literary review work exhibits how homoeopathy with a multimodal approach may show a considerable proportion of ADHD patients in India and throughout the world successfully manageable and treatable according to growing study evidence, ruling out the hazardous conventional medicines. Indeed, homeopathy can help cure ADHD symptoms either on its own or in combination with other types of integrative systems.

Keywords: ADHD, adult ADHD, homoeopathy, integrative approach

Procedia PDF Downloads 81

Authors: Jeongyeon Park, Yeo Jun Yoon, Jiyoung Seo, In Seok Moon, Hae Jun Lee, Kiwon Song

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Cold Atmospheric Pressure Plasma (CAPP) is defined as a partially ionized gas with electrically charged particles at room temperature and atmospheric pressure. CAPP generates reactive oxygen species (ROS) and reactive nitrogen species (RNS), and has potential as a new apoptosis-promoting cancer therapy. With an annular type dielectric barrier discharge (DBD) CAPP-generating device combined with a helium (He) gas feeding system, we showed that CAPP selectively induced apoptosis in various cancer cells while it promoted proliferation of the adipose tissue-derived stem cell (ASC). The apoptotic effect of CAPP was highly selective toward p53-mutated cancer cells. The intracellular ROS was mainly responsible for apoptotic cell death in CAPP-treated cancer cells. CAPP induced apoptosis even in doxorubicin-resistant cancer cell lines, demonstrating the feasibility of CAPP as a potent cancer therapy. With the same device and exposure conditions to cancer cells, CAPP stimulated proliferation of the ASC, a kind of mesenchymal stem cell that is capable of self-renewing and differentiating into adipocytes, chondrocytes, osteoblasts and neurons. CAPP-treated ASCs expressed the stem cell markers and differentiated into adipocytes as untreated ASCs. The increase of proliferation by CAPP in ASCs was offset by a NO scavenger but was not affected by ROS scavengers, suggesting that NO generated by CAPP is responsible for the activated proliferation in ASCs. Usually, cancer stem cells are reported to be resistant to known cancer therapies. When we applied CAPP of the same device and exposure conditions to cancer cells to liver cancer stem cells (CSCs) that express CD133 and epithelial cell adhesion molecule (EpCAM) cancer stem cell markers, apoptotic cell death was not examined. Apoptotic cell death of liver CSCs was induced by the CAPP generated from a device with an air-based flatten type DBD. An exposure of liver CSCs to CAPP decreased the viability of liver CSCs to a great extent, suggesting plasma be used as a promising anti-cancer treatment. To validate whether CAPP can be a promising anti-cancer treatment or an adjuvant modality to eliminate remnant tumor in cancer surgery of vestibular schwannoma, we applied CAPP to mouse schwannoma cell line SC4 Nf2 ‑/‑ and human schwannoma cell line HEI-193. A CAPP treatment leads to anti-proliferative effect in both cell lines. We are currently studying the molecular mechanisms of differential physiological effect of CAPP; the proliferation of ASCs and apoptosis of various cancer cells and CSCs.

Keywords: cold atmospheric pressure plasma, apoptosis, proliferation, cancer cells, adult stem cells

Procedia PDF Downloads 282

Authors: F. Pagliara, F. Mauriello

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The objective of this paper is to investigate the relationship between the increase of accessibility brought by high speed rail (HSR) systems and the tourism market in Italy. The impacts of HSR projects on tourism can be quantified in different ways. In this manuscript, an empirical analysis has been carried out with the aid of a dataset containing information both on tourism and transport for 99 Italian provinces during the 2006-2016 period. Panel data regression models have been considered, since they allow modelling a wide variety of correlation patterns. Results show that HSR has an impact on the choice of a given destination for Italian tourists while the presence of a second level hub mainly affects foreign tourists. Attraction variables are also significant for both categories and the variables concerning security, such as number of crimes registered in a given destination, have a negative impact on the choice of a destination.

Keywords: tourists, overnights, high speed rail, attractions, security

Procedia PDF Downloads 156

Authors: Ibrahim Musa, Mohammed Abdul-Aziz Mabrouk, Yusuf Tanko

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Introduction: Long term physical training affect the performance of athletes especially the females. Soccer which is a team sport, played in an outdoor field, require adequate oxygen transport system for the maximal aerobic power during exercise in order to complete 90 minutes of competitive play. Suboptimal haematological status has often been recorded in athletes with intensive physical activity. It may be due to the iron depletion caused by hemolysis or haemodilution results from plasma volume expansion. There is lack of data regarding the dynamics of red blood cell variables, in male football players. We hypothesized that, a long competitive season involving frequent matches and intense training could influence red blood cell variables, as a consequence of applying repeated physical loads when compared with sedentary. Methods: This cross sectional study was carried on 40 adult males (20 athletes and 20 non athletes) between 18-25 years of age. The 20 apparently healthy male non athletes were taken as sedentary and 20 male footballers comprise the study group. The university institutional review board (ABUTH/HREC/TRG/36) gave approval for all procedures in accordance with the Declaration of Helsinki. Red blood cell (RBC) concentration, packed cell volume (PCV), and plasma volume were measured in fasting state and immediately after exercise. Statistical analysis was done by using SPSS/ win.20.0 for comparison within and between the groups, using student’s paired and unpaired “t” test respectively. Results: The finding from our study shows that, immediately after termination of exercise, the mean RBC counts and PCV significantly (p<0.005) decreased with significant increased (p<0.005) in plasma volume when compared with pre-exercised values in both group. In addition the post exercise RBC was significantly higher in untrained (261.10±8.5) when compared with trained (255.20±4.5). However, there was no significant differences in the post exercise hematocrit and plasma volume parameters between the sedentary and the footballers. Moreover, beside changes in pre-exercise values among the sedentary and the football players, the resting red blood cell counts and Plasma volume (PV %) was significantly (p < 0.05) higher in the sedentary group (306.30±10.05 x 104 /mm3; 58.40±0.54%) when compared with football players (293.70±4.65 x 104 /mm3; 55.60±1.18%). On the other hand, the sedentary group exhibited significant (p < 0.05) decrease in PCV (41.60±0.54%) when compared with the football players (44.40±1.18%). Conclusions: It is therefore proposed that the acute football exercise induced reduction in RBC and PCV is entirely due to plasma volume expansion, and not of red blood cell hemolysis. In addition, the training status also influenced haematological indices of male football players differently from the sedentary at rest due to adaptive response. This is novel.

Keywords: Haematological Indices, Performance Status, Sedentary, Male Football Players

Procedia PDF Downloads 257

Authors: Li-Fen Wu

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Spiritual well-being is one aspect of quality of life that can significantly improve the quality of life of individuals. However, the reports of older adults’ spiritual well-being that live in aged institutions were few. This study aims to identify the relationship between spiritual well-being and quality of life among older adults residing in aged institutions in Taiwan. The correlative study design is used. Data collected by basic personal information, Spiritual Index of Well-being Scale and EuroQol-5D-3L. Case managers help participants complete the questionnaires. This study uses descriptive statistics and correlation test analysis data. The study finds the positive correlation between spiritual well-being and quality of life. According to the correlation between spiritual well-being and quality-of-life score, awareness of the importance of spiritual well-being in caring for these people is recommended.

Keywords: older adult, spiritual well-being, quality of life, aged institution

Procedia PDF Downloads 258

Authors: Ragea Alqahtani

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The purpose of the study was to measure the effectiveness of the Goldstein’s social skill streaming model based on the special and general pre-service teachers’ knowledge about controlling their emotions in conflict situations. A review of previous pieces of literature guided the design and measurement of the effectiveness of the approach to the control of emotions. The teachers were assessed using the coping strategy, adult anger, and Goldstein’s skill streaming inventories. Lastly, the paper provides various recommendations on the sensitization of the Goldstein’s Social Skill streaming model to both the special and pre-service teachers to promote their knowledge about controlling emotions in conflicts.

Keywords: emotional control, Goldstein social skill streaming model, modeling technique, self- as-a-model, self-efficacy, self-regulation

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Authors: Girum Tedla Assefa

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Background: Granulomatous mycosis fungoides is an extremely rare type of cutaneous T-cell lymphoma (<55 cases reported worldwide). Case report: A 36-year-old female presented with soft tissue atrophy of right lower limb (dermis + hypodermis) of 22 years and plaques over trunk of 3 years duration. Histological examination of a biopsy taken from the atrophied tissue showed a granulomatous reaction with epidermotropic atypical lymphocytes. However, in other areas there were only findings of conventional MF without granuloma. Conclusion: The diagnosis of a granulomatous mycosis fungoides depends exclusively on the histological demonstration of granulomas. Distinct clinical characteristics are not present. This case highlights the importance of thorough investigation of lipoatrophic skin changes in the adult to exclude underlying causes, including MF.

Keywords: cutaneous lymphoma, granulomatous skin lymphoma, mycoses fungoides, skin atrophy

Procedia PDF Downloads 371

Authors: Amrane Meriem, Oukid Salyha

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The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

Procedia PDF Downloads 87

Authors: Peri Ozlem Yuksel-Sokmen, Irfan Cagtay

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Oral languages are destined to disappear rapidly in the absence of interventions aimed at encouraging their usage by young children. The seminal language preservation model proposed by Fishman (1991) stresses the importance of multiple generations using the endangered L1 while engaged in daily routines with younger children. Over the last two decades Fishman (2001) has used his intergenerational transmission model in documenting the revitalization of Basque languages, providing evidence that families are transmitting Euskara as a first language to their children with success. In our study, to motivate usage of Lazuri, we asked caregivers to speak the language while engaged with their toddlers (12 to 48 months) in semi-structured play, and included both parents (N=32) and grandparents (N=30) as play partners. This unnatural prompting to speak only in Lazuri was greeted with reluctance, as 90% of our families indicated that they had stopped using Lazuri with their children. Nevertheless, caregivers followed instructions and produced 67% of their utterances in Lazuri, with another 14% of utterances using a combination of Lazuri and Turkish (Codeswitch). Although children spoke mostly in Turkish (83% of utterances), frequencies of caregiver utterances in Lazuri or Codeswitch predicted the extent to which their children used the minority language in return. This trend suggests that home interventions aimed at encouraging dyads to communicate in a non-preferred, endangered language can effectively increase children’s usage of the language. Alternatively, this result suggests than any use of the minority language on the part of the children will promote its further usage by caregivers. For researchers examining links between play, culture, and child development, structured play has emerged as a critical methodology (e.g., Frost, Wortham, Reifel, 2007, Lilliard et al., 2012; Sutton-Smith, 1986; Gaskins & Miller, 2009), allowing investigation of cultural and individual variation in parenting styles, as well as the role of culture in constraining the affordances of toys. Toy props, as well as picture-books in native languages, can be used as tools in the transmission and preservation of endangered languages by allowing children to explore adult roles through enactment of social routines and conversational patterns modeled by caregivers. Through adult-guided play children not only acquire scripts for culturally significant activities, but also develop skills in expressing themselves in culturally relevant ways that may continue to develop over their lives through community engagement. Further pedagogical tools, such as language games and e-learning, will be discussed in this proposed oral talk.

Keywords: language intervention, pedagogical tools, endangered languages, Lazuri

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Authors: Katsumi Hirata

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Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: environmental sound, bispectrum, spectrogram, slice bispectrogram, convolutional neural network

Procedia PDF Downloads 126

Authors: Kamaljeet Kaur, Vinod Kumari, Jatesh Kathpalia, Bas Kaur

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A gender bias towards girl child is pervasive across the world. It is seen in all the strata of the society and manifests in various forms. However nature and extent of these inequalities are not uniform. Generally these inequalities are more prevalent in patriarchal society. Despite emerging and increasing opportunities for women, there are still inequalities between men and women in each and every sphere like education, health, economy, polity and social sphere. Patriarchal ideology as a cultural norm enforces gender construction which is oriented toward hierarchical relations between the sexes and neglect of women in Indian society. Discrimination to girls may also vary by their age and be restricted to the birth order and sex composition of her elder surviving siblings. The present study was conducted to know the gender discrimination among rural children in India. The respondents were selected from three generations as per AICRP age group viz, 18-30 years (3rd generation), 31-60 years (2nd generation) and above 60 years (1st generation). A total sample size was 600 respondents from different villages of two districts of Haryana state comprising of half males and half females. Data were collected using personal interview schedule and analysed by SPSS software. Among the total births 46.35 per cent were girl child and 53.64 % were male child. Dropout rate was more in female children as compared to male children i.e. near about one third (31.09%) female children dropped school followed by 21.17 % male children. It was quite surprising that near about two-third (61.16%) female children and more than half (59.22%) of the male children dropped school. Cooking was mainly performed by adult female with overall mean scores 2.0 and ranked first which was followed by female child (1.7 mean scores) clearly indicating that cooking was the activity performed mainly by females while activity related to purchase of fruits and vegetable, cereals and pulses was mainly done by adult male. First preference was given to male child for serving of costly and special food. Regarding professional aspiration of children of the respondents’ families, it was observed that 20.10% of the male children wanted to become engineer, whereas only 3.89 % female children wanted to become engineer. Ratio of male children was high in both generations irrespective of the districts. School dropouts were more in case of female in both the 1st and 2 nd generations. The main reasons of school dropout were lack of interest, lack of resources and early marriage in both the generations. Female enrolment was more in faculty of arts, whereas in case of male percentage it was more in faculty of non-medical and medical which showed that female children were getting traditional type of education. It is suggested to provide equal opportunities to girls and boys in home as well as outside the home for smooth functioning of society.

Keywords: gender biasness, male child, female child, education, home

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Authors: Carmela Nardelli, Laura Iaffaldano, Valentina Capobianco, Antonietta Tafuto, Maddalena Ferrigno, Angela Capone, Giuseppe Maria Maruotti, Maddalena Raia, Rosa Di Noto, Luigi Del Vecchio, Pasquale Martinelli, Lucio Pastore, Lucia Sacchetti

Abstract:

Maternal obesity and nutrient excess in utero increase the risk of future metabolic diseases in the adult life. The mechanisms underlying this process are probably based on genetic, epigenetic alterations and changes in foetal nutrient supply. In mammals, the placenta is the main interface between foetus and mother, it regulates intrauterine development, modulates adaptive responses to sub optimal in uterus conditions and it is also an important source of human amniotic mesenchymal stem cells (hA-MSCs). We previously highlighted a specific microRNA (miRNA) profiling in amnion from obese (Ob) pregnant women, here we compared the miRNA expression profile of hA-MSCs isolated from (Ob) and control (Co) women, aimed to search for any alterations in metabolic pathways that could predispose the new-born to the obese phenotype. Methods: We isolated, at delivery, hA-MSCs from amnion of 16 Ob- and 7 Co-women with pre-pregnancy body mass index (mean/SEM) 40.3/1.8 and 22.4/1.0 kg/m2, respectively. hA-MSCs were phenotyped by flow cytometry. Globally, 384 miRNAs were evaluated by the TaqMan Array Human MicroRNA Panel v 1.0 (Applied Biosystems). By the TargetScan program we selected the target genes of the miRNAs differently expressed in Ob- vs Co-hA-MSCs; further, by KEGG database, we selected the statistical significant biological pathways. Results: The immunophenotype characterization confirmed the mesenchymal origin of the isolated hA-MSCs. A large percentage of the tested miRNAs, about 61.4% (232/378), was expressed in hA-MSCs, whereas 38.6% (146/378) was not. Most of the expressed miRNAs (89.2%, 207/232) did not differ between Ob- and Co-hA-MSCs and were not further investigated. Conversely, 4.8% of miRNAs (11/232) was higher and 6.0% (14/232) was lower in Ob- vs Co-hA-MSCs. Interestingly, 7/232 miRNAs were obesity-specific, being expressed only in hA-MSCs isolated from obese women. Bioinformatics showed that these miRNAs significantly regulated (P<0.001) genes belonging to several metabolic pathways, i.e. MAPK signalling, actin cytoskeleton, focal adhesion, axon guidance, insulin signaling, etc. Conclusions: Our preliminary data highlight an altered miRNA profile in Ob- vs Co-hA-MSCs and suggest that an epigenetic miRNA-based mechanism of gene regulation could affect pathways involved in placental growth and function, thereby potentially increasing the newborn’s risk of metabolic diseases in the adult life.

Keywords: hA-MSCs, obesity, miRNA, biosystem

Procedia PDF Downloads 528

Authors: L. Rajaonarivo, M. N. Bessagnet, C. Sallaberry, A. Le Parc Lacayrelle, L. Leveque

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TCVPYR is a European FEDER (European Regional Development Fund) project which aims to promote tourism in the French Pyrenees region by leveraging its cultural heritage. It involves scientists from various domains (geographers, historians, anthropologists, computer scientists...). This paper presents a fully automated process to publish any dataset as Wikipedia articles as well as the corresponding linked information on Wikidata and Wikimedia Commons. We validate this process on a sample of geo-referenced cultural heritage data collected by TCVPYR researchers in different regions of the Pyrenees. The main result concerns the technological prerequisites, which are now in place. Moreover, we demonstrated that we can automatically publish cultural heritage data on Wikimedia.

Keywords: cultural heritage dissemination, digital humanities, open data, Wikimedia automated publishing

Procedia PDF Downloads 127

Authors: Jerry Q. Cheng

Abstract:

Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

Procedia PDF Downloads 166

Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Yufen Qin

Abstract:

Text sentiment transfer is an important branch of text style transfer. The goal is to generate text with another sentiment attribute based on a text with a specific sentiment attribute while maintaining the content and semantic information unrelated to sentiment unchanged in the process. There are currently two main challenges in this field: no parallel corpus and text attribute entanglement. In response to the above problems, this paper proposed a novel solution: Mask-Prompt-Rerank. Use the method of masking the sentiment words and then using prompt regeneration to transfer the sentence sentiment. Experiments on two sentiment benchmark datasets and one formality transfer benchmark dataset show that this approach makes the performance of small pre-trained language models comparable to that of the most advanced large models, while consuming two orders of magnitude less computing and memory.

Keywords: language model, natural language processing, prompt, text sentiment transfer

Procedia PDF Downloads 81

Authors: Chouahda Salima, Soltani Noureddine

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The present study is a part of biological control against mosquitoes. It aims to assess the impact of a selective insect growth regulator: halofenozide in mosquitofish: Gambusia affinis. Acetylcholinesterase (AChE), glutathione S-transferase (GST) and glutathione (GSH) used in assessing of environmental stress were measured in juveniles and adults males and females. The response of these biomarkers reveals an inhibition of AChE specific activity, an induction of GST activity, and decrease of GSH rates in juveniles in the end of experiment and during chronic treatment adult males and females. The effect of these biomarkers is more pronounced in females compared to males and juveniles. These different biomarkers have a similar profile for the duration of exposure.

Keywords: biomarkers, chronic toxicity, insecticide, halofenozide, Gambusia affinis, pollution

Procedia PDF Downloads 342