Search results for: equivalent noise level

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 108

Authors: Maha Z. Rizk, Sami A. Fattah, Heba M. Darwish, Sanaa A. Ali, Mai O. Kadry

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The increasing use of nanomaterials in consumer and industrial products has aroused global concern regarding their fate in biological systems resulting in demand for parallel risk assessment. The objective of this study is investigating either the effect of individual or combined doses of idebenone, carnosine and vitamin E on amelioration of some biochemical indices of nano sized titanium dioxide (TiO2 NPS) induced metabolic disorders in mice liver. TiO2-NPS was administered in an oral dose of 150 mg/kg for consecutive 14 days followed by oral daily doses of the aforementioned antioxidants for 1 month. TiO2-NPS induced a significant elevation in serum level of ALT and AST, hepatic inflammatory markers (tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6)) and increased the percent of DNA damage which was assessed by COMET assay in addition to the apoptotic marker Caspase-3. Moreover, mRNA gene expression observed by RT-PCR showed a significant overexpression in nuclear factor relation-2 (Nrf2), nuclear factor kappa beta (NF-Kβ) and the apoptotic factor (bax), and a significant down-regulation in the antiapoptotic factor (bcl2) level. In conclusion, idebenone, carnosine and vitamin E ameliorated the deviated parameters with a variable degree with the most pronounced role in alleviating the hazardous effect of TiO2 NPS toxicity following the combination regimen.

Keywords: idebenone, carnosine, vitamin E, TiO2 NPS, caspase-3, NrF2, NF-KB

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Authors: Fatemeh Keshavarz

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Background: Schizophrenia is a disease of the nervous system, and immune system disorders can affect its pathogenesis. Activation of microglia, proinflammatory cytokines, disruption of the blood-brain barrier (BBB) due to inflammation, activation of autoreactive B cells, and consequently the production of autoantibodies against system antigens are among the immune processes involved in neurological diseases. interleukin 32 (IL-32) a proinflammatory cytokine that important player in the activation of the innate and adaptive immune responses. This study aimed to measure the serum level of IL-32 as well as the frequency of autoantibody positivity against several nervous system antigens in patients with schizophrenia. Material and Methods: This study was conducted on 40 patients with schizophrenia and 40 healthy individuals in the control group. Serum IL-32 levels were measured by ELISA. The frequency of autoantibodies against Hu, Ri, Yo, Tr, CV2, Amphiphysin, SOX1, Zic4, ITPR1, CARP, GAD, Recoverin, Titin, and Ganglioside antigens were measured by indirect immunofluorescence method. Results: Serum IL-32 levels in patients with schizophrenia were significantly higher compared to the control group. Autoantibodies were positive in 8 patients for GAD antigen and 5 patients for Ri antigen, which showed a significant relationship compared to the control group. Autoantibodies were also positive in 2 patients for CV2, in 1 patient for Hu, and in 1 patient for CARP. Negative results were reported for other antigens. Conclusion: Our findings suggest that elevated the serum IL-32 level and autoantibody positivity against several nervous system antigens may be involved in the pathogenesis of schizophrenia.

Keywords: schizophrenia, microglia, autoantibodies, IL-32

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Authors: Nami Takase

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Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

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Authors: Desta Brhanu Gebrehiwot

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The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

Procedia PDF Downloads 86

Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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Authors: Mojtaba Aghajari, Alireza Aghasi

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The first challenge which the current research faced has been the identification or determination of the level of knowledge in Isfahan public transportation corporation, and the second challenge has been the recognition and choice of a proper approach for the instructional system design. Responding these two challenges will present an appropriate model of instructional system design. In order to respond the first challenge or question, Nonaka and Takeuchi KM model has been utilized due to its universality among the 26 models proposed so far. The statistical population of this research included 2200 people, among which 200 persons were chosen as the sample of the research by the use of Morgan’s method. The data gathering has been carried out by the means of a questionnaire based on Nonaka and Takeuchi KM model, analysis of which has been done by SPSS program. The output of this questionnaire, yielding the point of 1.96 (out of 5 points), revealed that the general condition of Isfahan public transportation corporation is weak concerning its being knowledge-centered. After placing this output on Jonassen’s continuum, it was revealed that the appropriate approach for instructional system design is the system (or behavioral) approach. Accordingly, different steps of the general model of ADDIE, which covers all of the ISO10015 standards, were adopted in the act of designing. Such process in Isfahan public transportation corporation was designed and divided into three main steps, including: instructional designing and planning, instructional course planning, determination of the evaluation and the effectiveness of the instructional courses.

Keywords: instructional system design, system approach, knowledge management, employees

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Authors: Wiem Daoud Ben Amor, Luis Martínez López, Hela Moalla Frikha

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Most of the multi-criteria group decision making (MCGDM) problems dealing with qualitative criteria require consideration of the large background of expert information. It is common that experts have different degrees of knowledge for giving their alternative assessments according to criteria. So, it seems logical that they use different evaluation scales to express their judgment, i.e., multi granular linguistic scales. In this context, we propose the extension of the classical additive ratio assessment (ARAS) method to the case of a hierarchical linguistics term for managing multi granular linguistic scales in uncertain contexts where uncertainty is modeled by means in linguistic information. The proposed approach is called the extended hierarchical linguistics-ARAS method (ARAS-ELH). Within the ARAS-ELH approach, the DM can diagnose the results (the ranking of the alternatives) in a decomposed style, i.e., not only at one level of the hierarchy but also at the intermediate ones. Also, the developed approach allows a feedback transformation i.e the collective final results of all experts able to be transformed at any level of the extended linguistic hierarchy that each expert has previously used. Therefore, the ARAS-ELH technique makes it easier for decision-makers to understand the results. Finally, An MCGDM case study is given to illustrate the proposed approach.

Keywords: additive ratio assessment, extended hierarchical linguistic, multi-criteria group decision making problems, multi granular linguistic contexts

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Authors: Szu-Kai Hsu, Po-Ching Lin

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As more and more multi-core processors emerge, traditional sequential programming paradigm no longer suffice. Yet only few modern dynamic programming languages can leverage such advantage. Ruby, for example, despite its wide adoption, only includes threads as a simple parallel primitive. The global virtual machine lock of official Ruby runtime makes it impossible to exploit full parallelism. Though various alternative Ruby implementations do eliminate the global virtual machine lock, they only provide developers dated locking mechanism for data synchronization. However, traditional locking mechanism error-prone by nature. Software Transactional Memory is one of the promising alternatives among others. This paper introduces a new virtual machine: GobiesVM to provide a native software transactional memory based solution for dynamic programming languages to exploit parallelism. We also proposed a simplified variation of Transactional Locking II algorithm. The empirical results of our experiments show that support of STM at virtual machine level enables developers to write straightforward code without compromising parallelism or sacrificing thread safety. Existing source code only requires minimal or even none modi cation, which allows developers to easily switch their legacy codebase to a parallel environment. The performance evaluations of GobiesVM also indicate the difference between sequential and parallel execution is significant.

Keywords: global interpreter lock, ruby, software transactional memory, virtual machine

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Authors: Reina Kawase

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World GHG emissions should be reduced 50% by 2050 compared with 1990 level. CO2 emission reduction from steel sector, an energy-intensive sector, is essential. To estimate CO2 emission from steel sector in the world, estimation of steel production is required. The world steel production by process is estimated during the period of 2005-2050. The world is divided into aggregated 35 regions. For a steel making process, two kinds of processes are considered; basic oxygen furnace (BOF) and electric arc furnace (EAF). Steel production by process in each region is decided based on a current production capacity, supply-demand balance of steel and scrap, technology innovation of steel making, steel consumption projection, and goods trade. World steel production under moderate countermeasure scenario in 2050 increases by 1.3 times compared with that in 2012. When domestic scrap recycling is promoted, steel production in developed regions increases about 1.5 times. The share in developed regions changes from 34 %(2012) to about 40%(2050). This is because developed regions are main suppliers of scrap. 48-57% of world steel production is produced by EAF. Under the scenario which thinks much of supply-demand balance of steel, steel production in developing regions increases is 1.4 times and is larger than that in developed regions. The share in developing regions, however, is not so different from current level. The increase in steel production by EAF is the largest under the scenario in which supply-demand balance of steel is an important factor. The share reaches 65%.

Keywords: global steel production, production distribution scenario, steel making process, supply-demand balance

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Authors: Ayan Giri, Lukaranjan Phukan, Shantanu Karmakar

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Structure and tectonics play a vital role in ore genesis and deposition. The existence of a swelling structure below the current level of a mine leads to the discovery of ores below some permeant developments of the mine. The discovery and the extraction of the ore body are very critical to sustain the business requirement of the mine. The challenge was to extract the ore without hampering the global stability of the mine. In order to do so, different mining options were considered and analysed by numerical modelling in FLAC3d software. The constitutive model prepared for this simulation is the improved unified constitutive model, which can better and more accurately predict the stress-strain relationships in a continuum model. The IUCM employs the Hoek-Brown criterion to determine the instantaneous Mohr-Coulomb parameters cohesion (c) and friction (ɸ) at each level of confining stress. The extra swelled part can be dimensioned as north-south strike width 50m, east-west strike width 50m. On the north side, already a stope (P1) is excavated of the dimension of 25m NS width. The different options considered were (a) Open stoping of extraction of southern part (P0) of 50m to the full extent, (b) Extraction of the southern part of 25m, then filling of both the primaries and extraction of secondary (S0) 25m in between. (c) Extraction of the southern part (P0) completely, preceded by backfill and modify the design of the secondary (S0) for the overall stability of the permanent excavation above the stoping.

Keywords: extraction, IUCM, FLAC 3D, stoping, tectonics

Procedia PDF Downloads 212

Authors: Tahir Mehmood, Pennung Warnitchai

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Simplified static analysis procedures such Nonlinear Static Procedure (NSP) are gaining popularity for the seismic evaluation of buildings. However, these simplified procedures accounts only for the seismic responses of the fundamental vibration mode of the structure. Some other procedures which can take into account the higher modes of vibration, lack in accuracy to determine the component responses. Hence, such procedures are not suitable for evaluating the structures where many vibration modes may participate significantly or where component responses are needed to be evaluated. Moreover, these procedures were found to either computationally expensive or tedious to obtain individual component responses. In this paper, a simplified but accurate procedure is studied. It is called the Uncoupled Modal Response History Analysis (UMRHA) procedure. In this procedure, the nonlinear response of each vibration mode is first computed, and they are later on combined into the total response of the structure. The responses of four tall buildings are computed by this simplified UMRHA procedure and compared with those obtained from the NLRHA procedure. The comparison shows that the UMRHA procedure is able to accurately compute the global responses, i.e., story shears and story overturning moments, floor accelerations and inter-story drifts as well as the component level responses of these tall buildings with heights varying from 20 to 44 stories. The required computational effort is also extremely low compared to that of the Nonlinear Response History Analysis (NLRHA) procedure.

Keywords: higher mode effects, seismic evaluation procedure, tall buildings, component responses

Procedia PDF Downloads 342

Authors: Julien Deborde, Thomas Milcent, Stéphane Glockner, Pierre Lubin

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A fully Eulerian method is developed to solve the problem of fluid-elastic structure interactions based on a 1-fluid method. The interface between the fluid and the elastic structure is captured by a level set function, advected by the fluid velocity and solved with a WENO 5 scheme. The elastic deformations are computed in an Eulerian framework thanks to the backward characteristics. We use the Neo Hookean or Mooney Rivlin hyperelastic models and the elastic forces are incorporated as a source term in the incompressible Navier-Stokes equations. The velocity/pressure coupling is solved with a pressure-correction method and the equations are discretized by finite volume schemes on a Cartesian grid. The main difficulty resides in that large deformations in the fluid cause numerical instabilities. In order to avoid these problems, we use a re-initialization process for the level set and linear extrapolation of the backward characteristics. First, we verify and validate our approach on several test cases, including the benchmark of FSI proposed by Turek. Next, we apply this method to study the wave damping phenomenon which is a mean to reduce the waves impact on the coastline. So far, to our knowledge, only simulations with rigid or one dimensional elastic structure has been studied in the literature. We propose to place elastic structures on the seabed and we present results where 50 % of waves energy is absorbed.

Keywords: damping wave, Eulerian formulation, finite volume, fluid structure interaction, hyperelastic material

Procedia PDF Downloads 323

Authors: Dilek Yalız Solmaz

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Meta-cognition is an important factor for educating conscious individuals who are aware of their cognitive processes. With this respect, the purposes of this article is to find out the perceived metacognition level of Physical Education and Sports School students at Anadolu University and to identify whether metacognition levels display significant differences in terms of various variables. 416 Anadolu University Physical Education and Sports School students were formed the research universe. "The Meta-Cognitions Questionnaire (MCQ-30)" developed by Cartwright-Hatton and Wells and later developed the 30-item short form (MCQ-30) was used. The MCQ-30 which was adapted into Turkish by Tosun and Irak is a four-point agreement scale. In the data analysis, arithmethic mean, standard deviation, t-test and ANOVA were used. There is no statistical difference between mean scores of uncontrollableness and danger, cognitive awareness, cognitive confidence and the positive beliefs of girls and boys students. There is a statistical difference between mean scores of the need to control thinking. There is no statistical difference according to departments of students between mean scores of uncontrollableness and danger, cognitive awareness, cognitive confidence, need to control thinking and the positive beliefs. There is no statistical difference according to grade level of students between mean scores of the positive beliefs, cognitive confidence and need to control thinking. There is a statistical difference between mean scores of uncontrollableness and danger and cognitive awareness.

Keywords: meta cognition, physical education, sports school students, thinking

Procedia PDF Downloads 383

Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Rida Akzar, Risti Permani, Wahida , Wendy Umberger

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Adoption of farm innovations may increase farm productivity, and therefore improve market access and farm incomes. However, most studies that look at the level and drivers of innovation adoption only focus on a specific type of innovation. Farmers may consider multiple innovation options, and constraints such as budget, environment, scarcity of labour supply, and the cost of learning. There have been some studies proposing different methods to combine a broad variety of innovations into a single measurable index. However, little has been done to compare these methods and assess whether they provide similar information about farmer segmentation by their ‘innovativeness’. Using data from a recent survey of 220 dairy farm households in West Java, Indonesia, this study compares and considers different methods of deriving an innovation index, including expert-weighted innovation index; an index derived from the total number of adopted technologies; and an index of the extent of adoption of innovation taking into account both adoption and disadoption of multiple innovations. Second, it examines the distribution of different farming systems taking into account their innovativeness and farm characteristics. Results from this study will inform policy makers and stakeholders in the dairy industry on how to better design, target and deliver programs to improve and encourage farm innovation, and therefore improve farm productivity and the performance of the dairy industry in Indonesia.

Keywords: adoption, dairy, household survey, innovation index, Indonesia, multiple innovations dairy, West Java

Procedia PDF Downloads 336

Authors: Khan R. Rahaman, Quazi K. Hassan

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Global changes in climate, environment, economies, populations, governments, institutions, and cultures converge in localities. Changes at a local scale, in turn, contribute to global changes as well as being affected by them. Our hypothesis is built on a consideration that temperature does vary at local level (i.e., termed as local warming) in comparison to the predicted models at the regional and/or global scale. To date, the bulk of the research relating local places to global climate change has been top-down, from the global toward the local, concentrating on methods of impact analysis that use as a starting point climate change scenarios derived from global models, even though these have little regional or local specificity. Thus, our focus is to understand such trends over the southern Alberta, which will enable decision makers, scientists, researcher community, and local people to adapt their policies based on local level temperature variations and to act accordingly. Specific objectives in this study are: (i) to understand the local warming (temperature in particular) trend in context of temperature normal during the period 1961-2010 at point locations using meteorological data; (ii) to validate the data by using specific yearly data, and (iii) to delineate the spatial extent of the local warming trends and understanding influential factors to adopt situation by local governments. Existing data has brought the evidence of such changes and future research emphasis will be given to validate this hypothesis based on remotely sensed data (i.e. MODIS product by NASA).

Keywords: local warming, climate change, urban area, Alberta, Canada

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Authors: Viacheslav Sushko, Viktor Sushko

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Pre-cancerous breast diseases are pathological changes that precede the appearance of adenocarcinoma. The most common benign breast disease is mastopathy. We examined the life and disease history of 114 women aged 58-69 who were diagnosed with adenocarcinoma of the breast at different stages of development. They filled out the Reeder Scale to determine the level of stress. The results of the study revealed that 62 of them had mastopathy at the age of 30-45 years old. These women refused surgical treatment for mastopathy. Five to six years before their diagnosis of adenocarcinoma of the mammary gland, 84 women had experienced severe stress (death of a beloved close relative, torture accompanied by rape, prolonged stay in extreme conditions (under bombardment and bombardment). In the assessment of data from completed Reeder scales, 114 women had a high level of mental stress, with a score from 1-1.72. The 84 women who suffered from severe stress showed overeating or a significant decrease in food intake, insomnia, apathy, increased irritability and restlessness, loss of interest in sexual relationships, forgetfulness, difficulty in performing routine work, prolonged uncontrollable headaches, unexplained fatigue, heart pain, reduced capacity for work. In conclusion, it is important to provide psychotherapy for breast cancer patients as the diagnosis, and the different stages of treatment are very stressful. It is also advisable to see a psychiatrist at an early stage and prevent distress and treat precancerous breast disease.

Keywords: breast cancer, distress, mastopathy, severe stress

Procedia PDF Downloads 135

Authors: Prataksitorn Chonlakan, Tiparat Wongsilarat

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The traditional clinical practice guideline used at the emergency room at Songkhla Hospital in caring for patients who come in contact with jellyfish venom took a long time for the pain to reduce to the level that patients can cope with. To investigate the effectiveness of clinical practice guidelines by comparing the effectiveness of a newly developed clinical practice guideline with the traditional clinical practice guideline in the following aspects: 1) pain reduction, 2) length of pain, 3) the rate of patient’s re-visit, 4) the rate of severe complications such as anaphylactic shock, and cardiac arrest, and death, and 5) patient satisfaction. This study employed a quasi-experimental research design. Thirty subjects were selected with purposive sampling from jellyfish-sting patients who came for treatment at the Emergency Room of Songkhla Hospital. The subjects were divided using random assignment into two groups of 15 each: an experimental group, and the control group. The control group was treated using the traditional clinical practice guideline consisting of rinsing the affected area with 0.9% normal saline, using a cloth soaked with vinegar to press against the affected area, and controlling pain using tramadol or diclofenac intramuscular injection. The data were analyzed using descriptive statistics and paired t-test at the significance level p < 0.05. The results of the study revealed the following. The pain level in the experimental group was significantly lower than that of the control group (the average pain score of the experimental group was 3.46 while that of the control group was 6.33) (p < 0.05).The length of pain in the experimental group was significantly lower than that of the control group (the average length of pain in the experimental group was 48.67 minutes while that of the control group was 105.35 minutes) (p < 0.05). The rate of re-visit within 12 hours in the experimental group was significantly lower than that of the control group (the rate of re-visit within 12 hours of the experimental group was 0.07 while that of the control group was 0.00) (p < 0.05).No severe complications such as anaphylactic shock, and cardiac arrest were found in the two groups of subjects.The rate of satisfaction among the subjects in the experimental group was significantly higher than that of the control group (the rate of satisfaction among the subjects of the experimental group was 90.00 percent while that among the control group was 66.33 percent) (p < 0.05). The newly develop clinical practice guideline could reduce pain and increase satisfaction among jellyfish-sting patients better than the traditional clinical practice guideline.

Keywords: effectiveness, clinical practice guideline, jellyfish-sting patients, cardiac arrest

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Authors: Yuan-Lin Liu, Ye Li, Tian Xia

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Taxi-calling APPs have been used widely, while brought both benefits and a variety of issues for the taxi market. Many countries do not know whether the benefits are remarkable than the issues or not. This paper established a comparison between the basic scenario (2009-2012) and a taxi-calling software usage scenario (2012-2015) to explain the impact of taxi-calling APPs. The impacts of taxi-calling APPs illustrated by the comparison results are: 1) The supply and demand distribution is more balanced, extending from the city center to the suburb. The availability of taxi service has been improved in low density areas, thin market attribute has also been improved; 2)The ratio of short distance taxi trip decreased, long distance service increased, the utilization of mileage increased, and the rate of empty decreased; 3) The popularity of taxi-calling APPs was able to reduce the average empty distance, cruise time, empty mileage rate and average times of loading passengers, can also enhance the average operating speed, improve the taxi operating level, and reduce social cost although there are some disadvantages. This paper argues that the taxi industry and government can establish an integrated third-party credit information platform based on credit evaluated by the data of the drivers’ driving behaviors to supervise the drivers. Taxi-calling APPs under fully covered supervision in the mobile Internet environment will become a new trend.

Keywords: taxi, taxi-calling APPs, credit, scenario comparison

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Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake

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Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.

Keywords: AFT model, first employment, proportional hazard, survey design, waiting time

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

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Authors: H. Akhloufi, M. Hulscher, J. M. Prins, I. H. Van Der Sijs, D. Melles, A. Verbon

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Background: A timely switch from intravenous to oral antibiotic therapy has many advantages, such as reduced incidence of IV-line related infections, a decreased hospital length of stay and less workload for healthcare professionals with equivalent patient safety. Additionally, numerous studies have demonstrated significant decreases in costs of a timely intravenous to oral antibiotic therapy switch, while maintaining efficacy and safety. However, a considerable variation in iv to oral antibiotic switch therapy criteria has been described in literature. Here, we report the development of a set of iv to oral switch criteria that are generally applicable in all hospitals. Material/methods: A RAND-modified Delphi procedure, which was composed of 3 rounds, was used. This Delphi procedure is a widely used structured process to develop consensus using multiple rounds of questionnaires within a qualified panel of selected experts. The international expert panel was multidisciplinary and composed out of clinical microbiologists, infectious disease consultants and clinical pharmacists. This panel of 19 experts appraised 6 major intravenous to oral antibiotic switch therapy criteria and operationalized these criteria using 41 measurable conditions extracted from the literature. The procedure to select a concise set of iv to oral switch criteria included 2 questionnaire rounds and a face-to-face meeting. Results: The procedure resulted in the selection of 16 measurable conditions, which operationalize 6 major intravenous to oral antibiotic switch therapy criteria. The following 6 major switch therapy criteria were selected: (1) Vital signs should be good or improving when bad. (2) Signs and symptoms related to the infection have to be resolved or improved. (3) The gastrointestinal tract has to be intact and functioning. (4) The oral route should not be compromised. (5) Absence of contra-indicated infections. (6) An oral variant of the antibiotic with good bioavailability has to exist. Conclusions: This systematic stepwise method which combined evidence and expert opinion resulted in a feasible set of 6 major intravenous to oral antibiotic switch therapy criteria operationalized by 16 measurable conditions. This set of early antibiotic iv to oral switch criteria can be used in daily practice in all adult hospital patients. Future use in audits and as rules in computer assisted decision support systems will lead to improvement of antimicrobial steward ship programs.

Keywords: antibiotic resistance, antibiotic stewardship, intravenous to oral, switch therapy

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: Navid P Roodaki, Rochelle Abila, Daisy Evangeline Garcia

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Background and Objective: Respiratory Distress Syndrome (RDS) among premature infants is a major causes of neonatal death. The use of Continuous Positive Airway Pressure (CPAP) has become a standard of care for preterm newborns with RDS hence cost-effective innovations are needed. This study compared a novel low-cost Bubble CPAP (bCPAP) device to ventilator driven CPAP in the treatment of RDS. Methods: This is a single-blind, randomized controlled trial done on May 2022 to October 2022 in a Level III Neonatal Intensive Care Unit in the Philippines. Preterm newborns (<36 weeks) with RDS were randomized to receive Vayu bCPAP device or Ventilator-derived CPAP. Arterial Blood Gases, Oxygen Saturation, administration of surfactant, and CPAP failure rates were measured. Results: Seventy preterm newborns were included. No differences were observed between the Ventilator driven CPAP and Vayu bCPAP on the PaO2 (97.51mmHg vs 97.37mmHg), So2 (97.08% vs 95.60%) levels, amount of surfactant administered between groups. There were no observed differences in CPAP failure rates between Vayu bPCAP (x̄ 3.23 days) and ventilator-driven CPAP (x̄ 2.98 days). However, a significant difference was noted on the CO2 level (40.32mmHg vs 50.70mmHg), which was higher among those hooked to Ventilator-driven CPAP (p 0.004). Conclusion: This study has shown that the novel low-cost bubble CPAP (Vayu bCPAP) can be used as an efficacious alternate non invasive oxygen therapy among preterm neonates with RDS, although the CO2 levels were higher among those hooked to ventilator driven CPAP, other outcome parameters measured showed that both devices are comparable. Recommendation: A multi-center or national study to account for geographic region, which may alter the outcomes of patients connected to different ventilatory support. Cost comparison between devices is also suggested. A mixed-method research assessing the experiences of health care professionals in assembling and utilizing the gadget is a second consideration.

Keywords: bubble CPAP, ventilator-derived CPAP; infant, premature, respiratory distress syndrome

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Authors: Shin Ku Kim, Yun Ah Oh, Eun Hee Seo, Chang Min Dae, Yun Jung Bae

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Objectives: The commonly used PRESS technique in magnetic resonance spectroscopy (MRS) has a limitation of incomplete water suppression. The recently developed sLASER technique is known for its improved effectiveness in suppressing water signal. However, no prior study has compared both sequences in a normal human brain. In this study, we firstly aimed to compare the performances of both techniques in brain MRS. Materials and methods: From January 2023 to July 2023, thirty healthy participants (mean age 38 years, 17 male, 13 female) without underlying neurological diseases were enrolled in this study. All participants underwent single-voxel MRS using both PRESS and sLASER techniques on 3T MRI. Two regions-of-interest were allocated in the left medial thalamus and left parietal white matter (WM) by a single reader. The SpectroView Analysis (SW5, Philips, Netherlands) provided automatic measurements, including signal-to-noise ratio (SNR) and peak_height of water, N-acetylaspartate (NAA)-water/Choline (Cho)-water/Creatine (Cr)-water ratios, and NAA-Cr/Cho-Cr ratios. The measurements from PRESS and sLASER techniques were compared using paired T-tests and Bland-Altman methods, and the variability was assessed using coefficients of variation (CV). Results: SNR and peak_heights of the water were significantly lower with sLASER compared to PRESS (left medial thalamus, sLASER SNR/peak_height 2092±475/328±85 vs. PRESS 2811±549/440±105); left parietal WM, 5422±1016/872±196 vs. 7152±1305/1150±278; all, P<0.001, respectively). Accordingly, NAA-water/Cho-water/Cr-water ratios and NAA-Cr/Cho-Cr ratios were significantly higher with sLASER than with PRESS (all, P< 0.001, respectively). The variabilities of NAA-water/Cho-water/Cr-water ratios and Cho-Cr ratio in the left medial thalamus were lower with sLASER than with PRESS (CV, sLASER vs. PRESS, 19.9 vs. 58.1/19.8 vs. 54.7/20.5 vs. 43.9 and 11.5 vs. 16.2) Conclusion: The sLASER technique demonstrated enhanced background water suppression, resulting in increased signals and reduced variability in brain metabolite measurements of MRS. Therefore, sLASER could offer a more precise and stable method for identifying brain metabolites.

Keywords: Magnetic resonance spectroscopy, Brain, sLASER, PRESS

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: surface roughness, Taguchi parameter design, CNC turning, CNC milling

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Authors: Meskure Pak, Nihal Buyukuslu

Abstract:

During Ramadan Muslims refrain from eating and drinking from dawn to sunset. Transformation of the eating habits cause profound changes in body composition. This study was performed during Ramadan of June-July 2015 with the regular fasting healthy adults (15 women and 15 men). The participants who were not fasting the whole month, have chronic diseases, pregnant and lactated were excluded. All attendances were informed about study. Written informed consent was taken from the voluntary participants. The work was approved by the Ethics and Research Committee of Istanbul Medipol University, Turkey. A questionnaire was conducted to determine the nutritional status, demographic and anthropometric data at the beginning, in the middle and at the end of Ramadan. Statistical Package for Social Sciences version 18.0 (SPSS, Chicago, IL, USA) was used for analyses. The mean ages of women and men were 34.4±9.45 and 28.9±10.55 years respectively. The BMI values (kg/m2) were slightly increased in men (26.5±3.9 to 26.2±3.7) and decreased in women (22.5±3.5 to 23.3±4.5). However the differences in BMI values between genders were not significant. Waist circumferences (WC) (cm) decreased in both women (80.2±14.6 to 79.4±17.7) and men (98.9±8.4 to 95.2±11.0) through the Ramadan. Fat percentages of women (27.0±71) increased in the middle of Ramadan (28.4±7.8) and decreased at the end of Ramadan (27.8±8.3). The fat percentages of men (21.5±6.3) were not affected in the middle of Ramadan (21.5±6.4) however decreased at the end of Ramadan (20.8±6.2). The total change in fat mass from beginning to end of Ramadan was higher in women than in men. The daily energy intake was higher in men than in women during Ramadan. In the middle of Ramadan energy intake (kcal) was reached to the highest level (2057.8±693.1) and at the end of Ramadan it decreased to the beginning level (1656.7±553.2) for men. However, daily energy intake of women slightly decreased from the beginning (1410.0±359.7) to the end (1409.2±366.7) of Ramadan. The comparison of energy intake between men and women was significant in the middle of Ramadan (p < 0.05). Water consumptions for both groups were increased in Ramadan fasting period. In comparison with the beginning of Ramadan, daily carbohydrate and fat consumptions increased and the consumption of protein decreased for men and for women at the end of Ramadan. The gender comparison resulted in a significant increase for protein and carbohydrate consumption of men in the middle of Ramadan (p < 0.05). In the first two weeks, the daily energy intake, the consumption of carbohydrates and fats seemed to increase for both men and women. However the later days of Ramadan daily fat consumption decreased to the level of beginning consumption levels which may indicate the nutritional adaptation period. In spite of the consumption of protein sources such as meat, poultry and egg increased, the decrease in the total amount of protein consumed in Ramadan may be due to a decrease in the consumption of milk and dairy products. In conclusion, the nutritional habits and preferred foods changed during Ramadan as a result affected the body composition.

Keywords: body composition, fasting, nutritional status, Ramadan

Procedia PDF Downloads 224