Search results for: classification of factors

Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

Abstract:

With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

Procedia PDF Downloads 149

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

Abstract:

This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

Procedia PDF Downloads 535

Authors: Arianda Jalife Gómez, Claudia Rangel Escareño

Abstract:

The Acropora coral genus, comprising reef-building corals in a global distribution, has been extensively studied due to its critical role as a builder for coral reef formation, along with preservation functions, but that has nonetheless experienced impactful consequences of climate change, especially in terms of population reduction related to limited thermal tolerance. A substantial increase in scientific output, particularly regarding omic studies to answer several questions about Acropora spp. overall biology, developmental factors, symbiosis characterization, environmental interactions, and response to climate change-related environmental factors have been observed; however, comprehensive resources characterizing the existing genetic responses of these corals to aforementioned phenomena are lacking. Thus, this study aims to identify key genes expressed across different developmental stages and conditions of Acropora spp. Highlighted in published studies given the shared tissue and polyp-level characteristics among the species comprising the genus, it is hypothesized that common reproductive, developmental, and stress response mechanisms are conserved. The presented resources, aiming to streamline the genus’ biology, elucidate several key factors of development and stress response that contribute to the understanding of researchers of overall biological responses while providing a genetic framework for potential further studies that might contribute to reef preservation strategies.

Keywords: acropora, development, genes, transcriptomics

Procedia PDF Downloads 2

Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

Procedia PDF Downloads 73

Authors: Natalia Polkanova, Sergey Kazakov

Abstract:

In the research, we proposed the set of factors of tourist destinations attractiveness in Spain and determined the factors that have the greatest impact on the positive perception of the tourist destination by Russian tourists; also, we examined what factors create the willingness for Russians to recommend this tourist destination to their friends and relatives. The tourists' comments on the Russian travel sites have been analyzed in order to determine the frequency of attractiveness characteristics references. Additionally, the study will reflect the relationship of variables.

Keywords: tourism destination, destination attractiveness, destination competitiveness, content analysis, unstructured image

Procedia PDF Downloads 459

Authors: Iniye Irene Wodi, Ibebietei Temple Offor

Abstract:

Adolescence is a transition period from childhood to adulthood and one of the challenges of this period to the adolescent is the choice of a career. Choosing a career can be influenced by various factors some of which could be psychological. The study, therefore, investigated the psychological factors that influence adolescents’ choice of career in the southern part of Nigeria. Adolescents from selected secondary schools were drawn for the study using multi-stage sampling techniques. Motivating factors for adolescent career choice questionnaire (MFACC) was used for the study. The instrument was validated by experts in test and measurement. A reliability coefficient of 0.79 was obtained for the instrument using Pearson Product moment after a test-retest. The findings revealed that students’ occupational needs, interest, self-concept and societal values motivated adolescents career choices. Based on these findings, recommendations were made chief among which was the need for society to place more emphasis on acceptable and beneficial values as this would influence career decisions adolescents make. They also influence the occupational needs and interests of the adolescents.

Keywords: adolescence, career choice, psychological factors, societal values

Procedia PDF Downloads 245

Authors: Yunwei Zhang, Na Li, Yuhong Niu

Abstract:

Bone tissue engineering scaffold was regarded as an important clinical technology of curing bony defect. The patent protection of bone tissue engineering scaffold had been paid more attention and strengthened all over the world. This study analyzed the future development trends of international technologies in the field of bone tissue engineering scaffold and its patent protection. This study used the methods of data classification and classification indexing to analyze 2718 patents retrieved in the patent database. Results showed that the patents coming from United States had a competitive advantage over other countiries in the field of bone tissue engineering scaffold. The number of patent applications by a single company in U.S. was a quarter of that of the world. However, the capability of R&D in China was obviously weaker than global level, patents mainly coming from universities and scientific research institutions. Moreover, it would be predicted that synthetic organic materials as new materials would be gradually replaced by composite materials. The patent technology protections of composite materials would be more strengthened in the future.

Keywords: bone tissue engineering, patent analysis, Scaffold material, patent protection

Procedia PDF Downloads 128

Authors: J. J. M. Trienekens, H. L. Romero, L. Cuenca

Abstract:

While process harmonization is increasingly mentioned and unanimously associated with several benefits, there is a need for more understanding of how it contributes to business process redesign and improvement. This paper presents the application, in an industrial case study, of a conceptual harmonization model on the relationship between drivers and effects of process harmonization. The drivers are called contextual factors which influence harmonization. Assessment of these contextual factors in a particular business domain, clarifies the extent of harmonization that can be achieved, or that should be strived at. The case study shows how the conceptual harmonization model can be made operational and can act as a valuable assessment tool. From both qualitative, as well as some quantitative, assessment results, insights are being discussed on the extent of harmonization that can be achieved, and action plans are being defined for business (process) harmonization.

Keywords: case study, contextual factors, process harmonization, industrial company

Procedia PDF Downloads 383

Authors: Fakieh Alrabai

Abstract:

This paper presents an experimental study designed to explore some of the learner’s individual and interpersonal factors (e.g. persistence, interest, regulation, satisfaction, appreciation, etc.) that Saudi learners experience when learning English as a Foreign Language and how learners’ perceptions of these factors influence various aspects of their motivation to learn English language. As part of the study, a 27-item structured survey was administered to a randomly selected sample of 105 Saudi learners from public schools and universities. Data collected through the survey were subjected to some basic statistical analyses, such as "mean" and "standard deviation". Based on the results from the analysis, a number of generalizations and conclusions are made in relation to how these inherent factors affect Saudi learners’ motivation to learn English as a foreign language. In addition, some recommendations are offered to Saudi academics on how to effectively make use of such factors, which may enable Saudi teachers and learners of English as a foreign language to achieve better learning outcomes in an area widely associated by Saudis with lack of success.

Keywords: persistence, interest, appreciation, satisfaction, SL/FL motivation

Procedia PDF Downloads 408

Authors: Ehsan Samimi, Mohammaa Ali Shahosseeni, Ali Abasltian, Shahriar Shafaghi

Abstract:

Background/Objectives: Voluntary turnover and early retirement request by specialists and experienced people in project-based organizations (PBO) has caused many problems in finding suitable experts to execute the projects. Methods/Statistical analysis: The present study is a descriptive and applied research. Research population consists of KWs in oil and gas PBO. The engineers in these organizations were considered as research sample. Interviews and questionnaire were used to gather information. Interviews with experts were used to identify factors and questionnaires were utilized to identify the importance and prioritization. 72 factors were identified and categorized into 9 groups within organizational and HR initiative levels. Results: Results of the research indicate the priority of each group of factors according to the proposed model in the view of KWs in oil, gas and petrochemical industries. On this basis, the following factors have the highest effect ratio based on the respondents’ point of view: 1. knowledge management 2. Performance appraisal system 3. Communication 4.Training and development 5.Job design and analysis 6. Employment policies 7. Career planning 8. Project/organizational factors 9. Salary and rewards. Additionally, in each group the priority of effective sub-factors has been identified as the result of the research .The results support the definitions of KWs and influence of factors examined and specified by similar studies in retention and development of KWs. The high importance of knowledge management and low rank for salary and rewards can be mentioned as example in this regard. Despite the priority of each group of factors the uniqueness of the result is due to identification of effective factors in the specific industry (oil and gas) and type of organization (PBO). Conclusion/Application: The findings of present study can be used to devise plans for retaining and developing KWs in PBO especially in oil and gas industry.

Keywords: project–based organizations, knowledge workers, HR management, turnover, retaining and developing employees

Procedia PDF Downloads 284

Authors: Hooman Fallah

Abstract:

Seawater injection and produced water re-injection are presently the most commonly used approach to enhanced recovery. The dominant factors for total oil recovery are the reservoir temperature, reservoir pressure, crude oil and water composition. In this study, the production under water injection in Soroosh, one of the southern Iranian heavy oil field has been simulated (the fluid properties are focused). In order to reveal the dominant factors in this production process, the sensitivity analysis has been done for the following effective factors, fluid viscosity, initial water saturation, gravity force and injection well strategy. It is crystal clear that the study of the dominant factors in production processes will help the engineers to design the best production mechanisms in our numerous hydrocarbon reservoirs.

Keywords: water injection, initial water saturation, oil viscosity, gravity force, injection well strategy

Procedia PDF Downloads 404

Authors: Mariem Kchaou, Wiem Khlif, Faiez Gargouri

Abstract:

Modeling business processes is an essential task when evaluating, improving, or documenting existing business processes. To be efficient in such tasks, a business process model (BPM) must have high structural quality and high performance. Evidently, evaluating the performance of a business process model is a necessary step to reduce time, cost, while assessing the structural quality aims to improve the understandability and the modifiability of the BPMN model. To achieve these objectives, a set of structural and performance measures have been proposed. Since the diversity of measures, we propose a framework that integrates both structural and performance aspects for classifying them. Our measure classification is based on business process model perspectives (e.g., informational, functional, organizational, behavioral, and temporal), and the elements (activity, event, actor, etc.) involved in computing the measures. Then, we implement this framework in a tool assisting the structural quality and the performance of a business process. The tool helps the designers to select an appropriate subset of measures associated with the corresponding perspective and to calculate and interpret their values in order to improve the structural quality and the performance of the model.

Keywords: performance, structural quality, perspectives, tool, classification framework, measures

Procedia PDF Downloads 149

Authors: Mefoute Badiang Alphonse, Emile Saker Nkwei

Abstract:

This study examines the factors determining the adoption of online purchases among customers and the influence of cultural variables in an African context. The research is based on a combination of the technology acceptance model (IS/IT). The hypotheses are tested using the structural equation method (PLS) on a sample of 446 individuals. The findings show that: (1) rational perception variables are influential factors affecting users’ intentions to adopt online purchases; (2) it is established that cultural factors have an impact on online purchases in the context of the study. Customers who value physical interaction are more likely to make purchases online, although mostly for hedonic reasons. Additionally, the relationship between utilitarian expectations and purchase intention depends on the level of conformity to the group. Implications and limitations of the research are formulated.

Keywords: Africa, cultural variables, online purchases, rational perception

Procedia PDF Downloads 69

Authors: Nagui A. Abdel-Khalek, Khaled A. Selim, Ahmed Hamdy

Abstract:

Kaolin is naturally occurring ore predominantly containing kaolinite mineral in addition to some gangue minerals. Typical impurities present in kaolin ore are quartz, iron oxides, titanoferrous minerals, mica, feldspar, organic matter, etc. The main coloring impurity, particularly in the ultrafine size range, is titanoferrous minerals. Kaolin is used in many industrial applications such as sanitary ware, table ware, ceramic, paint, and paper industries, each of which should be of certain specifications. For most industrial applications, kaolin should be processed to obtain refined clay so as to match with standard specifications. For example, kaolin used in paper and paint industries need to be of high brightness and low yellowness. Egyptian kaolin is not subjected to any beneficiation process and the Egyptian companies apply selective mining followed by, in some localities, crushing and size reduction only. Such low quality kaolin can be used in refractory and pottery production but not in white ware and paper industries. This paper aims to study the amenability of beneficiation of an Egyptian kaolin ore of El-Teih locality, Sinai, to be suitable for different industrial applications. Attrition scrubbing and classification followed by magnetic separation are applied to remove the associated impurities. Attrition scrubbing and classification are used to separate the coarse silica and feldspars. Wet high intensity magnetic separation was applied to remove colored contaminants such as iron oxide and titanium oxide. Different variables affecting of magnetic separation process such as solid percent, magnetic field, matrix loading capacity, and retention time are studied. The results indicated that substantial decrease in iron oxide (from 1.69% to 0.61% ) and TiO2 (from 3.1% to 0.83%) contents as well as improving iso-brightness (from 63.76% to 75.21% and whiteness (from 79.85% to 86.72%) of the product can be achieved.

Keywords: Kaolin, titanoferrous minerals, beneficiation, magnetic separation, attrition scrubbing, classification

Procedia PDF Downloads 349

Authors: Ali Alsawayeh, Ibrahim Eldanfour

Abstract:

This paper examines the extent of disclosure of oil and gas reserve quantum in annual reports of international oil and gas exploration and production companies, particularly companies in untested international markets, such as Canada, the UK and the US, and seeks to determine the underlying factors that affect the level of disclosure on oil reserve quantum. The study is concerned with the usefulness of disclosure of oil and gas reserves quantum to investors and other users. Given the primacy of the annual report (10-k) as a source of supplemental reserves data about the company and as the channel through which companies disseminate information about their performance, the annual reports for one year (2009) were the central focus of the study. This comparative study seeks to establish whether differences exist between the sample companies, based on new disclosure requirements by the Securities and Exchange Commission (SEC) in respect of reserves classification and definition. The extent of disclosure of reserve is provided and compared among the selected companies. Statistical analysis is performed to determine whether any differences exist in the extent of disclosure of reserve under the determinant variables. This study shows that some factors would affect the extent of disclosure of reserve quantum in the above-mentioned countries, namely: company’s size, leverage and quality of auditor. Companies that provide reserves quantum in detail appear to display higher size. The findings also show that the level of leverage has affected companies’ reserves quantum disclosure. Indeed, companies that provide detailed reserves quantum disclosure tend to employ a ‘high-quality auditor’. In addition, the study found significant independent variable such as Profit Sharing Contracts (PSC). This factor could explain variations in the level of disclosure of oil reserve quantum between the contractor and host governments. The implementation of SEC oil and gas reporting requirements do not enhance companies’ valuation because the new rules are based only on past and present reserves information (proven reserves); hence, future valuation of oil and gas companies is missing for the market.

Keywords: comparison, company characteristics, disclosure, reserve quantum, regulation

Procedia PDF Downloads 398

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

Abstract:

Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

Procedia PDF Downloads 437

Authors: Rodrigo Arnaldo Scarpel

Abstract:

Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

Procedia PDF Downloads 73

Authors: Tanapat Chongkamunkong

Abstract:

The objective of this paper is to present a practical use of Geographic Information System (GIS) to the public health from spatial correlation between multiple factors and dengue fever outbreak. Meteorological factors, demographic factors and environmental factors are compiled using GIS techniques along with the Global Satellite Mapping Remote Sensing (RS) data. We use monthly dengue fever cases, population density, precipitation, Digital Elevation Model (DEM) data. The scope cover study area under climate change of the El Niño–Southern Oscillation (ENSO) indicated by sea surface temperature (SST) and study area in 12 provinces of Thailand as remote sensing (RS) data from January 2007 to December 2014.

Keywords: dengue fever, sea surface temperature, Geographic Information System (GIS), remote sensing

Procedia PDF Downloads 185

Authors: Abdullah Alhomidan

Abstract:

This study is conducted to identify the main factors affecting accuracy of pretender cost estimate in building construction projects in Saudi Arabia from owners’ perspective. 44 factors affecting pretender cost estimate were identified through literature review and discussion with some construction experts. The results show that the top important factors affecting pretender cost estimate accuracy are: level of competitors in the tendering, material price changes, communications with suppliers, communications with client, and estimating method used.

Keywords: cost estimate, accuracy, pretender, estimating, bid estimate

Procedia PDF Downloads 547

Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

Abstract:

This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

Procedia PDF Downloads 163

Authors: V. Davaakhuu, D. Tserendagva, D. Amarsaikhan, T. Altanstetseg

Abstract:

In this study we aimed to detect main risk factors for diabetes in Mongolia and obtain data we used survey modified questionnaire. Survey data were obtained from 634 valid nurses (day work nurses-317, shift work nurses-317). Participants who were pregnant, less than 20 years old and no check for fasting glucose level were excluded from the survey in order to determine the risk factors of diabetes. Our study result shows the main risk factors of diabetes were physical inactivity, overweight and obesity, alcohol and tobacco use and lack of vegetable and fruit consumption. Peripheral blood glucose level was normal in subjects with BMI 26.28 ± 0.56, but 20 % of the subjects with normal blood glucose level were obese. Blood glucose level was higher in subjects with BMI 28.63 ± 2.32 and 36 % of them were obese. According to our study results, 3.62% of the surveyed population were identified having no diabetes risk factors, 52.3% were at risk, 28.8% were in higher risk for diabetes by the WHO criteria. In general, the prevalence of blood glucose were especially higher in shift work nurses.

Keywords: day work nurses, shift work nurses, BMI, WHR

Procedia PDF Downloads 587

Authors: Klara Krizova, Rudolf Hela

Abstract:

The topic of the article focuses on the evaluation of selected technological factors and their influence on resulting elasticity modulus of concrete. A series of various factors enter into the manufacturing process which, more or less, influences the elasticity modulus. This paper presents the results of concrete in which the influence of water coefficient and the size of maximum fraction of the aggregate on the static elasticity modulus were monitored. Part of selected results of the long-term programme was discussed in which a wide scope of various variants of proposals for the composition of concretes was evaluated.

Keywords: mix design, water-cement ratio, aggregate, modulus of elasticity

Procedia PDF Downloads 390

Authors: Julio Lavarello-Salinas, Verónica Kramm-Vergara, Pedro Gil-La Orden

Abstract:

During the COVID-19 pandemic, mental health became a relevant factor in people’s performance within organizations. The aim of this study was to analyze the effects of an organizational intervention program on the psychosocial factors of demands, resources, and the consequences of psychosocial risks in a technology services company during the COVID-19 pandemic. A quasi-experimental study was carried out with 105 employees who took part in an eight-week intervention program divided into two large stages. Pre- and post- measurements were collected using the UNIPSICO Questionnaire, considering its factors of demands, resources, and consequences of psychosocial risks. The Spanish Burnout Inventory (SBI) was also included. The results showed significant improvements in the perception of some psychosocial demand factors, all the resource factors, and all the consequences of psychosocial risks, except the guilt dimension of the SBI. Thus, we can conclude that the program was effective and that the study limitations should be improved in future studies.

Keywords: UNIPSICO questionnaire, occupational health, work stress, work psychosocial risk

Procedia PDF Downloads 98

Authors: Madhuri S. Ghate, Rahul P. Chavhan, Shriya S. Nahar

Abstract:

Learning objective: •To describe Magnetic Resonance Imaging (MRI) imaging appearances of typical and atypical uterine fibroids with emphasis on differentiating it from other similar conditions. •To classify uterine fibroids according to International Federation of Gynecology and Obstetrics (FIGO) Sub-classifications system and emphasis on its clinical significance. •To show cases with atypical imaging appearances atypical fibroids Material and methods: MRI of Pelvis had been performed in symptomatic women of child bearing age group on 1.5T and 3T MRI using T1, T2, STIR, FAT SAT, DWI sequences. Contrast was administered when degeneration was suspected. Imaging appearances of Atypical fibroids and various degenerations in fibroids were studied. Fibroids were classified using FIGO Sub-classification system. Its impact on surgical decision making and clinical outcome were also studied qualitatively. Results: Intramural fibroids were most common (14 patients), subserosal 7 patients, submucosal 5 patients . 6 patients were having multiple fibroids. 7 were having atypical fibroids. (1 hyaline degeneration, 1 cystic degeneration, 1 fatty, 1 necrosis and hemorrhage, 1 red degeneration, 1 calcification, 1 unusual large bilobed growth). Fibroids were classified using FIGO system. In uterus conservative surgeries, the lesser was the degree of myometrial invasion of fibroid, better was the fertility outcome. Conclusion: Relationship of fibroid with mucosal and serosal layers is important in the management of symptomatic fibroid cases. Risk to fertility involved in uterus conservative surgeries in women of child bearing age group depends on the extent of myometrial invasion of fibroids. FIGO system provides better insight into the degree of myometrial invasion. Knowledge about the atypical appearances of fibroids is important to avoid diagnostic confusion and untoward treatment.

Keywords: degeneration, FIGO sub-classification, MRI pelvis, uterine fibroids

Procedia PDF Downloads 78

Authors: Avhasei Dorothy Rasifudi, Josephine Mandizha

Abstract:

Cardiovascular risk factors continue to be the leading cause of death in the majority of developed and developing countries. In 2011, the World Health Organization reported that every year an estimated 17 million people globally die of CVD, representing 30% of all global deaths, particularly caused by heart attacks and strokes. The purpose of the study was to determine and describe the prevalence of selected cardiovascular risk factors among university of Venda staff. A cross-sectional study was conducted among 100 staff aged 20-65 years. The anthropometric measurements were conducted in accordance to and with standardized procedures advocated by the International Society for the Advanced Kinanthropometry. Weight, Height, waist circumference and hip circumference were measured for calculation of body mass index and waist-hip ratio. Blood pressure was measured using a Heine cuff and sphygmomanometer. Questionnaire was administered to gather demographic details and cardiovascular risk factors of hypertension and obesity. Data were analyzed using mean and standard deviation. The parameter t-test was applied to test significance level at p ≤ 0.05 between sexes. The statistical significance was set at p ≤ 0.05. The prevalence of hypertension was 23% with the highest prevalence amongst those aged 40 years and above. Factors found to be to be significantly associated with hypertension were gender, age, physical inactivity and family history. Prevalence of obesity was 43%, with the highest prevalence among those aged 40 years. The factors associated with obesity were diet, age and physical activity. The prevalence of hypertension and obesity in the study were high.

Keywords: cardiovascular, prevalence, risk factors, staff

Procedia PDF Downloads 283

Authors: Khadija Mushtaq, Muhammad Umar

Abstract:

The research aims to study the association between job satisfaction, motivation and the five factors of organizational citizenship behavior (i.e. Altruism, Conscientiousness, Sportsmanship, Courtesy and Civic virtue) among Public Sector Employees in Pakistan.In this research Structure Equation Modeling with confirmatory factor analysis was used to test the relationship between two independent and five dependent variables. Data was collected through questionnaire survey from 152 Public Servants Working in Gujrat District-Pakistan in different capacities. Stratified Random Sampling Technique was used to conduct this survey. The results of the study indicate that five factors of OCB have positive significant relation with both motivation and job satisfaction except the relationship of Civic Virtue with Motivation.The research findings implicate that factors other than motivation and job satisfaction may also affect OCB. Likewise, all the five factors of OCB may not be present in all populations. Thus, Managers must concentrate on increasing motivation and job satisfaction to increase OCB. Furthermore, the present research gives a direction to future researchers to use more independent variables (e.g. Culture, leadership, workplace environment, various job attitudes, types of motivation, etc.) on different types of populations with larger sample size in order to find the reasons behind insignificant relationship of civic virtue with Motivation in the research in hand and to generalize the tested model.

Keywords: five factors of organizational citizenship behavior (OCB), motivation, job satisfaction, public sector employees in Pakistan

Procedia PDF Downloads 332

Authors: Goutom K. Pall

Abstract:

At the very heart of the power system, power transmission (PT) acts as an essential link between power generation and distribution. Timely completion of PT infrastructures is therefore crucial to support the development of power system as a whole. Yet despite the importance, studies on PT infrastructure development projects are embryonic and, hence, PT projects undergoing widespread delays worldwide. These delay factors are idiosyncratic and identifying the critical delay factors is essential if the PT industry professionals are to complete their projects efficiently and within the expected timeframes. This study identifies and categorizes 46 causes of PT project delay under ten major groups using six sector expert’s recommendations studied by a preliminary questionnaire survey. Based on the experts’ strong recommendations, two new groups are introduced in the final questionnaire survey: sector specific factors (SSF) and general factors (GF). SSF pertain to delay factors applicable only to the PT projects, while GF represents less biased samples with shared responsibilities of all project parties involved in a project. The study then uses 112 data samples from the contractors to rank the delay factors using relative importance index (RII). The results reveal that SSF, GF and external factors are the most critical groups, while the highest ranked delay factors include the right of way (RoW) problems of transmission lines (TL), delay in payments, frequent changes in TL routes, poor communication and coordination among the project parties and accessibility to TL tower locations. Finally, recommendations are made to minimize the identified delay. The findings are expected to be of substantial benefit to professionals in minimizing time overrun in PT projects implementation, as well as power generation, power distribution, and non-power linear construction projects worldwide.

Keywords: delay, project delay, power transmission projects, time-overruns

Procedia PDF Downloads 173

Authors: Enes Furkan Erkan, Özer Uygun, Halil Ibrahim Demir, Zeynep Demir

Abstract:

Companies require increase in quality perception level of their products due to competitive conditions. As a result, the tendency to quality and researches to develop the quality are increasing day by day. Cost and time constraints are the biggest problems that companies face in their quality improvement efforts. In this study, factors that affect the porosity of ceramic products are determined and analyzed in a factory producing ceramic tiles. Then, Taguchi method is used in the design phase in order to decrease the number of tests to be performed by means of orthogonal sequences. The most important factors affecting the porosity of ceramic tiles are determined using Taguchi and ANOVA analysis. Based on the analyses, the most affecting factors are determined to be used in the fuzzy implementation stage. Then, the fuzzy rules were established with the factors affecting porosity by the experts’ opinion. Thus, porosity result could be obtained not only for the specified factor levels but also for intermediate values. In this way, it has been provided convenience to the factory in terms of cost and quality improvement.

Keywords: fuzzy, porosity, Taguchi Method, Taguchi-Fuzzy

Procedia PDF Downloads 424

Authors: Guilhermina Torrao

Abstract:

An extensive number of studies have been conducted to determine the factors which influence crash injury risk (CIR); however, uncertainties inherent to selected variables have been neglected. A review of existing literature is required to not only obtain an overview of the variables and measures but also ascertain the implications when comparing studies without a systematic view of variable taxonomy. Therefore, the aim of this literature review is to examine and report on peer-reviewed studies in the field of crash analysis and to understand the implications of broad variations in variable selection in CIR analysis. The objective of this study is to demonstrate the variance in variable selection and classification when modeling injury risk involving occupants of light vehicles by presenting an analytical review of the literature. Based on data collected from 64 journal publications reported over the past 21 years, the analytical review discusses the variables selected by each study across an organized list of predictors for CIR analysis and provides a better understanding of the contribution of accident and vehicle factors to injuries acquired by occupants of light vehicles. A cross-comparison analysis demonstrates that almost half the studies (48%) did not consider vehicle design specifications (e.g., vehicle weight), whereas, for those that did, the vehicle age/model year was the most selected explanatory variable used by 41% of the literature studies. For those studies that included speed risk factor in their analyses, the majority (64%) used the legal speed limit data as a ‘proxy’ of vehicle speed at the moment of a crash, imposing limitations for CIR analysis and modeling. Despite the proven efficiency of airbags in minimizing injury impact following a crash, only 22% of studies included airbag deployment data. A major contribution of this study is to highlight the uncertainty linked to explanatory variable selection and identify opportunities for improvements when performing future studies in the field of road injuries.

Keywords: crash, exploratory, injury, risk, variables, vehicle

Procedia PDF Downloads 121

Authors: Awad A. Younis, Elise Stronberg, Shifa Noor

Abstract:

Malware attacks due to end-user vulnerabilities have been noticeably increased in the past few years. Investigating the factors that make an end-user vulnerable to those attacks is critical because they can be utilized to set up proactive strategies such as awareness and education to mitigate the impacts of those attacks. Some existing studies investigated demographic, behavioral, and cultural factors that make an end-user susceptible to malware attacks. However, it has been challenging to draw more general conclusions from individual studies due to the varieties in the type of end-users and different types of malware. Therefore, we conducted a systematic literature review (SLR) of the existing research for end-user susceptibility factors to malware attacks. The results showed while some demographic factors are mostly associated with malware infection regardless of the end users' type, age, and gender are not consistent among the same and different types of end-users. Besides, the association of culture and personality factors with malware infection are consistent in most of the selected studies and for all type of end-users. Moreover, malware infection varies based on age, geographic location, and host types. We propose that future studies should carefully take into consideration the type of end-users because different end users may be exposed to different threats or be targeted based on their user domains’ characteristics. Additionally, as different types of malware use different tactics to trick end-users, taking the malware types into consideration is important.

Keywords: cybersecurity, malware, end-users, demographics, personality, culture, systematic literature review

Procedia PDF Downloads 220