Search results for: statistical features

Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

Procedia PDF Downloads 72

Authors: Sobhan Sobhani

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This study examined the behavioral patterns of student and their determinants according to the "symbolic interaction" sociological perspective in the form of 7 hypotheses. Behavioral patterns of students were classified in 8 categories: religious, scientific, political, artistic, sporting, national, parents and teachers. They were evaluated by student opinions by a five-point Likert rating scale. The statistical population included all male and female students of Islamic Azad University, Behabahan branch, among which 600 patients (268 females and 332 males) were selected randomly. The following statistical methods were used: frequency and percentage, mean, t-test, Pearson correlation coefficient and multi-way analysis of variance. The results obtained from statistical analysis showed that: 1-There is a significant difference between male and female students in terms of disposition to religious figures, artists, teachers and parents. 2-There is a significant difference between students of urban and rural areas in terms of assuming behavioral patterns of religious, political, scientific, artistic, national figures and teachers. 3-The most important criterion for selecting behavioral patterns of students is intellectual understanding with the pattern. 4-The most important factor influencing the behavioral patterns of male and female students is parents followed by friends. 5-Boys are affected by teachers, the Internet and satellite programs more than girls. Girls assume behavioral patterns from books more than boys. 6-There is a significant difference between students in human sciences, technical, medical and engineering disciplines in terms of selecting religious and political figures as behavioral patterns. 7-There is a significant difference between students belonging to different subcultures in terms of assuming behavioral patterns of religious, scientific and cultural figures. 8-Between the first and fourth year students in terms of selecting behavioral patterns, there is a significant difference only in selecting religious figures. 9-There is a significant negative correlation between the education level of parents and the selection of religious and political figures and teachers. 10-There is a significant negative correlation between family income and the selection of political and religious figures.

Keywords: behavioral patterns, behavioral patterns, male and female students, Islamic Azad University

Procedia PDF Downloads 365

Authors: Camilo Andres Agudelo-Velez, Lina María Martinez-Sanchez, Natalia Perilla-Hernandez, Maria De Los Angeles Rodriguez-Gazquez, Felipe Hernandez-Restrepo, Dayana Andrea Quintero-Moreno, Camilo Ruiz-Mejia, Isabel Cristina Ortiz-Trujillo, Monica Maria Zuluaga-Quintero

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Chronic obstructive pulmonary disease is common condition, characterized by a persistent blockage of airflow, partially reversible and progressive, that represents 5% of total deaths around the world, and it is expected to become the third leading cause of death by 2030. Objective: To establish the clinical and epidemiological profile of patients with chronic obstructive pulmonary disease in a medical institution from the city of Medellin, Colombia. Methods: A cross-sectional study was performed, with a sample of 50 patients with a diagnosis of chronic obstructive pulmonary disease in a private institution in Medellin, during 2015. The software SPSS vr. 20 was used for the statistical analysis. For the quantitative variables, averages, standard deviations, and maximun and minimun values were calculated, while for ordinal and nominal qualitative variables, proportions were estimated. Results: The average age was 73.5±9.3 years, 52% of the patients were women, 50% of them had retired, 46% ere married and 80% lived in the city of Medellín. The mean time of diagnosis was 7.8±1.3 years and 100% of the patients were treated at the internal medicine service. The most common clinical features were: 36% were classified as class D for the disease, 34% had a FEV1 <30%, 88% had a history of smoking and 52% had oxygen therapy at home. Conclusion: It was found that class D was the most common, and the majority of the patients had a history of smoking, indicating the need to strengthen promotion and prevention strategies in this regard.

Keywords: pulmonary disease, chronic obstructive, pulmonary medicine, oxygen inhalation therapy

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Authors: Ahmed Saeed, Sadok Sassi, Mohammad Roshun

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Gears are important components with a vital role in many rotating machines. One of the common gear failure causes is tooth fatigue crack; however, its early detection is still a challenging task. The objective of this study is to develop a numerical model that simulates the effect of teeth cracks on the resulting gears vibrations and permits consequently to perform an early fault detection. In contrast to other published papers, this work incorporates the possibility of multiple simultaneous cracks with different depths. As cracks alter significantly the stiffness of the tooth, finite element software is used to determine the stiffness variation with respect to the angular position, for different combinations of crack orientation and depth. A simplified six degrees of freedom nonlinear lumped parameter model of a one-stage spur gear system is proposed to study the vibration with and without cracks. The model developed for calculating the stiffness with the crack permitted to update the physical parameters of the second-degree-of-freedom equations of motions describing the vibration of the gearbox. The vibration simulation results of the gearbox were by obtained using Simulink/Matlab. The effect of one crack with different levels was studied thoroughly. The change in the mesh stiffness and the vibration response were found to be consistent with previously published works. In addition, various statistical time domain parameters were considered. They showed different degrees of sensitivity toward the crack depth. Multiple cracks were also introduced at different locations and the vibration response along with the statistical parameters were obtained again for a general case of degradation (increase in crack depth, crack number and crack locations). It was found that although some parameters increase in value as the deterioration level increases, they show almost no change or even decrease when the number of cracks increases. Therefore, the use of any statistical parameters could be misleading if not considered in an appropriate way.

Keywords: Spur gear, cracked tooth, numerical simulation, time-domain parameters

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Authors: Benu Gupta

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The purpose of the study was to assess the impact of yogic exercise on cardiovascular exercises on selected college students of high altitude. The research was conducted on college students of high altitude in Shimla for their cardiovascular function [Blood Pressure (BP), VO2 Max (TLC) and Pulse Rate (PR)] in respect to yogic exercise. Total 139 students were randomly selected from Himachal University colleges in Shimla. The study was conducted in three phases. The subjects were identified in the first phase of research program then further in next phase they were physiologically tested, and yogic exercise battery was operated in different time frame. The entire subjects were treated with three months yogic exercise. The entire lot of students were again evaluated physiologically [(Cardiovascular measurement: Blood Pressure (BP), VO2 Max (TLC) and Pulse Rate (PR)] with standard equipments. The statistical analyses of the variance (PR, BP (SBP & DBP) and TLC) were done. The result reveals that there was a significant difference in TLC; whereas there was no significant difference in PR. For BP statistical analysis suggests no significant difference were formed. Result showed that the BP of the participants were more inclined towards normal standard BP i.e. 120-80 mmHg.

Keywords: cardiovascular function, college students, high altitude, yogic exercise

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Authors: Roshani Gusain, Deep Sinha, Karan Nayal, Anmol Kumar Mishra, Manav Singh

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In this research paper, we introduce "Mind Care Assistant - Companion App", which is a Flutter and Firebase-based mental health monitor. The app wants to improve and monitor the mental health of its users, it uses noninvasive ways to check for a change in their emotional state. By responding to questions, the app will provide individualized suggestions ᅳ tasks and mindfulness exercises ᅳ for users who are depressed or anxious. The app features a chat-bot that incorporates cognitive behavioural therapy (CBT) principles and combines natural language processing with machine learning to develop personalised responses. The feature of the app that makes it easy for us to choose between iOS and Android is cross-platform, which allows users from both mobile systems to experience almost no changes in their interfaces. With Firebase integration synchronized and real-time data storage, security is easily possible. The paper covers the architecture of the app, how it was developed and some important features. The primary research result presents the promise of a "Mind Care Assistant" in mental health care using new wait-for-health technology, proposing a full stack application to be able to manage depression/anxiety and overall Mental well-being very effectively.

Keywords: mental health, mobile application, flutter, firebase, Depression, Anxiety

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Authors: Rahul Srivastava, Priti Pundir, Y. R. Sood, Rajnish Shrivastava

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For the interpretation of the signatures of sweep frequency response analysis(SFRA) of transformer different types of statistical techniques serves as an effective tool for doing either phase to phase comparison or sister unit comparison. In this paper with the discussion on SFRA several statistics techniques like cross correlation coefficient (CCF), root square error (RSQ), comparative standard deviation (CSD), Absolute difference, mean square error(MSE),Min-Max ratio(MM) are presented through several case studies. These methods require sample data size and spot frequencies of SFRA signatures that are being compared. The techniques used are based on power signal processing tools that can simplify result and limits can be created for the severity of the fault occurring in the transformer due to several short circuit forces or due to ageing. The advantages of using statistics techniques for analyzing of SFRA result are being indicated through several case studies and hence the results are obtained which determines the state of the transformer.

Keywords: absolute difference (DABS), cross correlation coefficient (CCF), mean square error (MSE), min-max ratio (MM-ratio), root square error (RSQ), standard deviation (CSD), sweep frequency response analysis (SFRA)

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Authors: Mumtaz Ali, Hamzullah Khan, Khalid Khanzada, Shahid Ayub, Aurangzeb Wazir

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Objective: To analyse the death of patients treated in neuro-surgical ICU for severe head injuries from different perspectives. The evaluation of the data so obtained to help improve the health care delivery to this group of patients in ICU. Study Design: It is a descriptive study based on retrospective analysis of patients presenting to neuro-surgical ICU in Lady Reading Hospital, Peshawar. Study Duration: It covered the period between 1st January 2009 to 31st December 2009. Material and Methods: The Clinical record of all the patients presenting with the clinical radiological and surgical features of severe head injuries, who expired in neuro-surgical ICU was collected. A separate proforma which mentioned age, sex, time of arrival and death, causes of head injuries, the radiological features, the clinical parameters, the surgical and non surgical treatment given was used. The average duration of stay and the demographic and domiciliary representation of these patients was noted. The record was analyzed accordingly for discussion and recommendations. Results: Out of the total 112 (n-112) patients who expired in one year in the neuro-surgical ICU the young adults made up the majority 64 (57.14%) followed by children, 34 (30.35%) and then the elderly age group: 10 (8.92%). Road traffic accidents were the major cause of presentation, 75 (66.96%) followed by history of fall; 23 (20.53%) and then the fire arm injuries; 13 (11.60%). The predominant CT scan features of these patients on presentation was cerebral edema, and midline shift (diffuse neuronal injuries). 46 (41.07%) followed by cerebral contusions. 28 (25%). The correctable surgical causes were present only in 18 patients (16.07%) and the majority 94 (83.92%) were given conservative management. Of the 69 (n=69) patients in which CT scan was repeated; 62 (89.85%) showed worsening of the initial CT scan abnormalities while in 7 cases (10.14%) the features were static. Among the non surgical cases both ventilatory therapy in 7 (6.25%) and tracheostomy in 39 (34.82%) failed to change the outcome. The maximum stay in the neuro ICU leading upto the death was 48 hours in 35 (31.25%) cases followed by 31 (27.67%) cases in 24 hours; 24 (21.42%) in one week and 16 (14.28%) in 72 hours. Only 6 (5.35%) patients survived more than a week. Patients were received from almost all the districts of NWFP except. The Hazara division. There were some Afghan refugees as well. Conclusion: Mortality following the head injuries is alarmingly high despite repeated claims about the professional and administrative improvement. Even places like ICU could not change the out come according to the desired aims and objectives in the present set up. A rethinking is needed both at the individual and institutional level among the concerned quarters with a clear aim at the more scientific grounds. Only then one can achieve the desired results.

Keywords: Glasgow Coma Scale, pediatrics, geriatrics, Peshawar

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: V. Bezverbny

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The actuality of the project deals with stable growing of deviant behavior’ statistics among Moscow citizens. During the recent years the socioeconomic health, wealth and life expectation of Moscow residents is regularly growing up, but the limits of crime and drug addiction have grown up seriously. Another serious Moscow problem has been economical stratification of population. The cost of identical residential areas differs at 2.5 times. The project is aimed at complex research and the development of methodology for main factors and reasons evaluation of deviant behavior growing in Moscow. The main project objective is finding out the links between the urban environment quality and dynamics of citizens’ deviant behavior in regional and municipal aspect using the statistical research methods and GIS modeling. The conducted research allowed: 1) to evaluate the dynamics of deviant behavior in Moscow different administrative districts; 2) to describe the reasons of crime increasing, drugs addiction, alcoholism, suicides tendencies among the city population; 3) to develop the city districts classification based on the level of the crime rate; 4) to create the statistical database containing the main indicators of Moscow population deviant behavior in 2010-2015 including information regarding crime level, alcoholism, drug addiction, suicides; 5) to present statistical indicators that characterize the dynamics of Moscow population deviant behavior in condition of expanding the city territory; 6) to analyze the main sociological theories and factors of deviant behavior for concretization the deviation types; 7) to consider the main theoretical statements of the city sociology devoted to the reasons for deviant behavior in megalopolis conditions. To explore the level of deviant behavior’ factors differentiation, the questionnaire was worked out, and sociological survey involved more than 1000 people from different districts of the city was conducted. Sociological survey allowed to study the socio-economical and psychological factors of deviant behavior. It also included the Moscow residents’ open-ended answers regarding the most actual problems in their districts and reasons of wish to leave their place. The results of sociological survey lead to the conclusion that the main factors of deviant behavior in Moscow are high level of social inequality, large number of illegal migrants and bums, nearness of large transport hubs and stations on the territory, ineffective work of police, alcohol availability and drug accessibility, low level of psychological comfort for Moscow citizens, large number of building projects.

Keywords: deviant behavior, megapolis, Moscow, urban environment, social stratification

Procedia PDF Downloads 194

Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

Procedia PDF Downloads 290

Authors: Eleni C. Mazarakioti, Anastasios Zotos, Anna-Akrivi Thomatou, Efthimios Kokkotos, Achilleas Kontogeorgos, Athanasios Ladavos, Angelos Patakas

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“Gigantes Elefantes” is a particularly dynamic crop of giant beans cultivated in western Macedonia (Greece). This variety of large beans growing in this area and specifically in the regions of Prespes and Kastoria is a protected designation of origin (PDO) species with high nutritional quality. Mislabeling of geographical origin and blending with unidentified samples are common fraudulent practices in Greek food market with financial and possible health consequences. In the last decades, multi-elemental composition analysis has been used in identifying the geographical origin of foods and agricultural products. In an attempt to discriminate the authenticity of Greek beans, multi-elemental analysis (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, Ge, K, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, Se, Sr, Ta, Ti, Tl, U, V, W, Zn, Zr) was performed by inductively coupled plasma mass spectrometry (ICP-MS) on 320 samples of beans, originated from Greece (Prespes and Kastoria), China and Poland. All samples were collected during the autumn of 2021. The obtained data were analysed by principal component analysis (PCA), an unsupervised statistical method, which allows for to reduce of the dimensionality of the enormous datasets. Statistical analysis revealed a clear separation of beans that had been cultivated in Greece compared with those from China and Poland. An adequate discrimination of geographical origin between bean samples originating from the two Greece regions, Prespes and Kastoria, was also evident. Our results suggest that multi-elemental analysis combined with the appropriate multivariate statistical method could be a useful tool for bean’s geographical authentication. Acknowledgment: This research has been financed by the Public Investment Programme/General Secretariat for Research and Innovation, under the call “YPOERGO 3, code 2018SE01300000: project title: ‘Elaboration and implementation of methodology for authenticity and geographical origin assessment of agricultural products.

Keywords: geographical origin, authenticity, multi-elemental analysis, beans, ICP-MS, PCA

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

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Authors: Francine Siy, Stephen Buñi

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Safety plays a significant role in everyone’s life on a day-to-day basis. We wish ourselves and our loved ones their safety as we all venture out on our daily commute. The road is undeniably dangerous and unpredictable, with abundant traffic collisions and pedestrians experiencing various injuries. For bicycle users, the risk of accidents is even more exacerbated, and injuries may be severe. Even when cyclists try their best to be safe and protected, the possibility of encountering danger is always there. Despite being equipped with protective gear, safety is never guaranteed. Cyclists often settle for helmets and standard reflector vests to establish a presence on the road. There are different types of vests available, depending on the profession. However, traditional reflector vests, mostly seen on construction workers and traffic enforcers, were not designed for riders and their protection from injuries. With insufficient protection for riders, they need access to ergonomically designed equipment and accessories that suit the riders and cater to their needs. This research aimed to offer a protective vest with safety features for riders that is comfortable, effective, durable, and intuitive. This sheds light and addresses the safety of the biker population, which continuously grows through the years. The product was designed and developed by gathering data and using the cognitive mapping method to ensure that all qualitative and quantitative data were considered in this study to improve other existing products that do not have the proper design considerations. It is known that available equipment for cyclists is often sold separately or lacks the safety features for cyclists traversing open roads. Each safety feature like the headlights, reflectors, signal or rear lights, zipper pouch, body camera attachment, and wireless remote control all play a particular role in helping cyclists embark on their daily commute. These features aid in illumination, visibility, easy maneuvering, convenience, and security, allowing cyclists to go for a safer ride that is of use throughout the day. The product is designed and produced effectively and inexpensively without sacrificing the quality and purpose of its usage.

Keywords: bicycle accessory, protective gear, safety, transport, visibility

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Authors: Mohammed Habchi, Sidi Mohammed Mesli, Rafik Benallal, Mohammed Kotbi

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On the basis of four partial correlation functions and some geometric constraints obtained from neutron scattering experiments, a Reverse Monte Carlo (RMC) simulation has been performed in the study of the aqueous electrolyte LiCl6H2O at the glassy state. The obtained 3-dimensional model allows computing pair radial and orientational distribution functions in order to explore the structural features of the system. Unrealistic features appeared in some coordination peaks. To remedy to this, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an additional energy constraint in addition to the usual constraints derived from experiments. The energy of the system is calculated using an Environment Dependence Interaction Potential (EDIP). Ions effects is studied by comparing correlations between water molecules in the solution and in pure water at room temperature Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in orientational distribution curves.

Keywords: LiCl6H2O, glassy state, RMC, HRMC

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.

Keywords: feature fusion, memory network, multimodal input, speaker recognition

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Authors: Puntarikorn Rungrattanakasin

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Objectives: To develop the trigger tool to warn about the risk of bleeding as an adverse event from warfarin drug usage during admission in Medical Wards of Chumphae Hospital. Methods: A retrospective study was performed by reviewing the medical records for the patients admitted between June 1st,2020- May 31st, 2021. ADEs were evaluated by Naranjo’s algorithm. The international normalized ratio (INR) and events of bleeding during admissions were collected. Statistical analyses, including Chi-square test and Reciever Operating Characteristic (ROC) curve for optimal INR threshold, were used for the study. Results: Among the 139 admissions, the INR range was found to vary between 0.86-14.91, there was a total of 15 bleeding events, out of which 9 were mild, and 6 were severe. The occurrence of bleeding started whenever the INR was greater than 2.5 and reached the statistical significance (p <0.05), which was in concordance with the ROC curve and yielded 100 % sensitivity and 60% specificity in the detection of a bleeding event. In this regard, the INR greater than 2.5 was considered to be an optimal threshold to alert promptly for bleeding tendency. Conclusions: The INR value of greater than 2.5 (>2.5) would be an appropriate trigger tool to warn of the risk of bleeding for patients taking warfarin in Chumphae Hospital.

Keywords: trigger tool, warfarin, risk of bleeding, medical wards

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Authors: Kenan Saatcioglu, Fatma Koc

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When the immigration is considered, it has been found that communities were continuously influenced by the immigrations from the date of the emergence of mankind until the day. The political, social and economic reasons seen at the various periods caused the communities go to new places from where they have lived before. Immigrations have occurred as a result of unequal opportunities among communities, social exclusion and imposition, compulsory homeland emerging politically, exile and war. Immigration is a social tool that is defined as a geographical relocation of people from a housing unit (city, village etc.) to another to spend all or part of their future lives. Immigrations have an effect on the history of humanity directly or indirectly, revealing new dimensions for communities to evaluate the concept of homeland. With these immigrations, communities carried their cultural values to their new settlements leading to a new interaction process. With this interaction process both migrant and native community cultures were reshaped and richer cultural values emerged. The clothes of these communities are amongst the most important visual evidence of this rich cultural interaction. As a result of these immigrations, communities affected each other culture’s clothing mutually and they started adding features of other cultures to the garments of its own, resulting new clothing cultures in time. The cultural and historical differences between these communities are seem to be the most influential factors of keeping the clothing cultures of the people alive. The most important and tragic of these immigrations took place after the Turkish War of Independence that was fought against Greece in 1922. The concept of forced immigration was a result of Lausanne Peace Treaty, which was signed between Turkish and Greek governments on 30th January 1923. As a result Greek Orthodoxes, who lived in Turkey (Anatolia and Thrace) and Muslim Turks, who lived in Greece were forced to immigrate. In this study, clothing features of Greek Orthodox woman immigrants who emigrated from Turkey to Greece in the period of the ‘1923 Greek-Turkish Population Exchange’ are aimed to be examined. In the study using the descriptive research method, before the ‘1923 Greek-Turkish Population Exchange’, the clothings belong to Greek Orthodox woman immigrants who lived in ‘Konya (Iconium)’ region in the Ottoman Empire, are discussed. In the study that is based on two different clothings belonging to ‘Konya (Iconium)’ region in the clothing collection archive at the ‘National Historical Museum’ in Greece, clothings of the Greek Orthodox woman immigrants are discussed with cultural norms, beliefs, values as well as in terms of form, ornamentation and dressing styles. Technical drawings are provided demonstrating formal features of the clothing parts that formed clothing integrity and their properties are described with the use of related literature in this study. This study is of importance that that it contains Greek Orthodox refugees’ clothings that are found in the clothing collection archive at the ‘National Historical Museum’ in Greece reflecting the cultural identities, providing information and documentation on the clothing features of the ‘1923 Greek-Turkish Population Exchange’.

Keywords: clothing, Greece, Greek Orthodoxes, immigration, national historical museum, Turkey

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Authors: Camilo Andrés Agudelo Vélez, Lina María Martínez Sánchez, Isabel Cristina Ortiz Trujillo, Evert Armando Jiménez Cotes, Natalia Perilla Hernández, María de los Ángeles Rodríguez Gázquez, Daniel Duque Restrepo, Felipe Hernández Restrepo, Dayana Andrea Quintero Moreno, Juan José Builes Gómez, Camilo Ruiz Mejía, Ana Lucia Arango Gómez

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Preeclampsia is a clinical complication during pregnancy with high incidence in Colombia; therefore, it is important to evaluate the influence of external conditions and medical interventions, in order to promote measures that encourage improvements in the quality of life. Objective: Determine clinical and sociodemographic variables in women with preeclampsia. Methods: This cross-sectional study enrolled 50 patients with the diagnosis of preeclampsia, from a private institution in Medellin, during 2015. We used the software SPSS ver.20 for statistical analysis. For the qualitative variables, we calculated the mean and standard deviation, while, for ordinal and nominal levels of quantitative variables, ratios were estimated. Results: The average age was 26.8±5.9 years. The predominant characteristics were socioeconomic stratum 2 (48%), students (55%), mixed race (46%) and middle school as level of education (38%). As for clinical features, 72% of the cases were mild preeclampsia, and 22% were severe forms. The most common clinical manifestations were edema (46%), headache (62%), and proteinuria (55%). As for the Gyneco-obstetric history, 8% reported previous episodes of this disease and it was the first pregnancy for 60% of the patients. Conclusions: Preeclampsia is a frequent condition in young women; on the other hand, headache and edema were the most common reasons for consultation, therefore, doctors need to be aware of these symptoms in pregnant women.

Keywords: pre-eclampsia, hypertension, pregnancy complications, pregnancy, abdominal, edema

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Authors: Eyal Boers

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This paper shall demonstrate how films can offer a valuable and innovative approach to the study of images, stereotypes, and national identity. "Black Book" ("Zwartboek", 2006), a World War Two film directed by Paul Verhoeven, tells the story of Rachel Stein, a young Jewish woman who becomes a member of a resistance group in the Netherlands. The main hypothesis in this paper maintains that Rachel's character possesses both features of the Dutch prototype (a white, secular, sexual, freedom-loving individualist who seems "Dutch" enough to be accepted into a Dutch resistance group and even infiltrate the local Nazi headquarters) and features which can be defined as specifically Jewish (a black-haired victim persecuted by the Nazis, transforming herself into a gentile, while remaining loyal to her fellow Jews and ultimately immigrating to Israel and becoming a Hebrew teacher in a Kibbutz). Finally, this paper claims that Rachel's "Dutchness" is symptomatic of Dutch nostalgia in the 21st century for the Jews as "others" who blend into dominant Dutch culture, while Rachel's "Jewish Otherness" reflects a transnational identity – one that is always shifting and traverses cultural and national boundaries. In this sense, a film about Dutch Jews in the Second World War reflects on issues of identity in the 21st Century.

Keywords: Dutch, film, stereotypes, identity

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Authors: Michael Fundator

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Groundbreaking application of biomathematical and biochemical research in neural networks processes to formation of non-canonical bases, islands, and analog bases in DNA and mRNA at or near the transcription that contradicts the long anticipated statistical assumptions for the distribution of bases and analog bases compounds is implemented through statistical and stochastic methods apparatus with addition of quantum principles, where the usual transience of Poisson spike train becomes very instrumental tool for finding even almost periodical type of solutions to Fokker-Plank stochastic differential equation. Present article develops new multidimensional methods of finding solutions to stochastic differential equations based on more rigorous approach to mathematical apparatus through Kolmogorov-Chentsov continuity theorem that allows the stochastic processes with jumps under certain conditions to have γ-Holder continuous modification that is used as basis for finding analogous parallels in dynamics of neutral networks and formation of analog bases and transcription in DNA.

Keywords: Fokker-Plank stochastic differential equation, Kolmogorov-Chentsov continuity theorem, neural networks, translation and transcription

Procedia PDF Downloads 408

Authors: B. Farahani, R. Fadil, A. Aboonabi, B. Hoffmann, J. Loscheider, K. Tavakolian, S. Arzanpour

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Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure mapping systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of flexible sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the users' needs.

Keywords: dynamic cushion, image processing, pressure mapping system, wheelchair

Procedia PDF Downloads 171

Authors: Rajpal Kaur, Pooja Choudhary

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Biometrics, which refers to identifying an individual based on his or her physiological or behavioral characteristics, has the capabilities to the reliably distinguish between an authorized person and an imposter. The Signature recognition systems can categorized as offline (static) and online (dynamic). This paper presents Surf Feature based recognition of offline signatures system that is trained with low-resolution scanned signature images. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However the signatures of human can be handled as an image and recognized using computer vision and HMM techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are multiple techniques are defined to signature recognition with a lot of scope of research. In this paper, (static signature) off-line signature recognition & verification using surf feature with HMM is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified depended on parameters extracted from the signature using various image processing techniques. The Off-line Signature Verification and Recognition is implemented using Mat lab platform. This work has been analyzed or tested and found suitable for its purpose or result. The proposed method performs better than the other recently proposed methods.

Keywords: offline signature verification, offline signature recognition, signatures, SURF features, HMM

Procedia PDF Downloads 385

Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

Procedia PDF Downloads 110

Authors: Kay Thinzar Phu, Lwin Lwin Oo

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In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

Procedia PDF Downloads 313

Authors: Catherine Mary Abou-Zaid

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This quantitative study discusses the concerns with the self-directed learning (SDL) skills of the undergraduate nursing students in a medical university in Bahrain. The nursing undergraduate student SDL study was conducted taking all 4 years and compiling data collected from the students themselves by survey questionnaire. The aim of the study is to understand and change the attitudes of self-directed learning among the undergraduate students. The SDL of the undergraduate student nurses has been noticed to be lacking and motivation to actually perform without supervision while out-with classrooms are very low. Their use of the resources available on the virtual learning environment and also within the university is not as good as it should be for a university student at this level. They do not use them to their own advantage. They are not prepared for the transition from high school to an academic environment such as a university or college. For some students it is the first time in their academic lives that they have faced sharing a classroom with the opposite sex. For some this is a major issue and we as academics need to be aware of all issues that they come to higher education with. Design Methodology: The design methodology that was chosen was a quantitative design using convenience sampling of the students who would be asked to complete survey questionnaire. This sampling method was chosen because of the time constraint. This was completed by the undergraduate students themselves while in class. The questionnaire was analyzed by the statistical package for social sciences (SPSS), the results interpreted by the researcher and the findings published in the paper. The analyzed data will also be reported on and from this information we as educators will be able to see the student’s weaknesses regarding self-directed learning. The aims and objectives of the research will be used as recommendations for the improvement of resources for the students to improve their SDL skills. Conclusion: The results will be able to give the educators an insight to how we can change the self-directed learning techniques of the students and enable them to embrace the skills and to focus more on being self-directed in their studies rather than having to be put on to a SDL pathway from the educators themselves. This evidence will come from the analysis of the statistical data. It may even change the way in which the students are selected for the nursing programme. These recommendations will be reported to the head of school and also to the nursing faculty.

Keywords: self-directed learning, undergraduate students, transition, statistical package for social sciences (SPSS), higher education

Procedia PDF Downloads 316

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

Procedia PDF Downloads 236

Authors: Akeel Noori Al-Mulla Hwaish

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The environmental impact, economics, social and cultural factors, and the processes by which people define history and meaning had influenced the dynamic shape and character of the traditional Islamic Arabic city. Therefore, in regard to the period when Islam was at its peak (7th- 13th Centuries), Islamic city wasn’t the highly dynamited at the scale of buildings and city planning that demonstrates a distinguished city as an ‘Islamic’ as appeared after centuries when the function of the buildings and their particular arrangement and planning scheme in relation to one another that defined an Islamic city character. The architectural features of the urban fabric of the traditional Arabic Islamic city are a ‎reflection of the spiritual, social, and cultural characteristics of the people. It is a ‎combination of Islamic values ‘Din’ and life needs ‘Dunia’ as Prophet Muhammad built the first Mosque in ‎Madinah in the 1st year of his migration to it, then the Suq or market on 2nd of Hijrah, attached to ‎the mosque to signify the birth of a new Muslims community which considers both, ‎‎’Din’ and ‘Dunia’ and initiated nucleus for what which called after that as an ‘Islamic’ city. This research will discuss the main characteristics and components of the traditional Arab cities and demonstrate the impact of the Islamic values on shaping the planning layout and general built environment features of the early traditional Arab cities.

Keywords: urban, Islamic, Arabic, city

Procedia PDF Downloads 202

Authors: Ajitesh Pal, Arpan Datta Roy, H. K. Pratihari

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The different illegal firearms crudely made by skilled gunsmith from scrap materials are popularly known as country made firearms. Such firearms along with improvised ammunition are clandestinely marketed at the cheaper price without any license to the extremist group, criminal, poachers and firearm lovers. As per National Crime Records Bureau (NCRB), MHA, Govt of India about 80% firearm cases are committed by country made/improvised firearms. The ballistic division of the laboratory has examined a good number of cases. The analysis of firearm cases received for forensic examination revealed that 7.65mm calibre pistols mostly improvised firearm are commonly used in firearm related crime cases. In the present communication, physical parameters and other characteristics features of some 7.65mm calibre pistols have been discussed in detail. The detailed study on country made (CM) firearm will help to prepare a database related to type of material used, origin of the raw material and tools used for inscription. The study also includes to establish the chemistry of propellants & head stamp pattern. The database will be helpful to the firearm examiners, researchers, students pursuing study on forensic science as reference material.

Keywords: improvised pistol, stringent gun law, working mechanism, parameters, database

Procedia PDF Downloads 71

Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

Procedia PDF Downloads 471