scholarly journals EXPRESS PREDICTION OF EXTERNAL DISTINCTIVE FEATURES OF PERSON USING THE PROGRAM OF DERMATOGLYPHICS FOR PREDICTION

2017 ◽  
Vol 3 ◽  
pp. 26-32
Author(s):  
Natalia Kozan ◽  
Julia Kotsyubinskaya ◽  
Galina Zelenchuk
Keyword(s):  
Neural Networks ◽  
Statistical Processing ◽  
Armed Conflicts ◽  
Forensic Identification ◽  
Phenotypic Traits ◽  
Anthropometric Parameters ◽  
Long Time ◽  
And Gender ◽  
Hands And Feet ◽  
Computer Identification

The aim of our study was to investigate the current state of computer identification applications, such as artificial neural networks. The material of our study were antroposcopic and anthropometric parameters obtained from 180 male and females aged 18–55 years living in the Ivano-Frankivsk region and belonging to Boiko, Lemko or Hutsul ethno-territorial group. Prints of comb pattern of the toes obtained by scanning with Futronic's FS80 USB2.0 Fingerprint Scanner using the program ftrScanApiEx.exe. followed by the transfer of data to a personal computer. For statistical processing of the obtained data we use STATISTICA 12 from the company StatSoft. Construction of neural networks was carried out using Neural Networks. As a result of our research there was carried out the prediction of anthropometric and antroposcopic parameters (ethno-territorial and gender belonging, etc.) through the use of dermatoglyphic parameters of the hands and feet in 180 people living in the Ivano-Frankivsk region. The proposed method allowed to obtain the results with a forecasts probability 73–90 %. The use of above algorithm of actions allowed a 50 % increase of quality of identification of unknown person for using dermatoglyphic method and 67 % facilitatation of the process of identification (of quantitative and qualitative calculations, determining correlations between parameters) in comparison with previously known manner. Therefore, our proposed method can be used as an express diagnostics of common phenotypic traits of the person (ethno-territorial affiliation, gender, etc.) at admission of mass victims (natural disasters, acts of terrorism, armed conflicts, man-made disasters, etc.), it doesn’t not require a long time for conducting, specially trained staff and is inexpensive.Conclusions: The possibility of predicting external-recognizing features of a person such as etno-racial belonging, sex, anthropometric and antroposcopic parameters will allow widely use dermatoglyphic method at the level with other methods in conducting forensic identification of impersonal, fragmented and putrefactive modified corpses.

NEURAL NETWORK METHOD OF ADAPTING THE PARAMETERS OF THE INFORMATION SYSTEMS INTERFACE

2020 ◽  
pp. 26-31
Author(s):  
А.Д. Обухов ◽  
М.Н. Краснянский ◽  
М.С. Николюкин
Keyword(s):  
Neural Networks ◽  
Information System ◽  
Information Systems ◽  
Statistical Processing ◽  
Low Complexity ◽  
User Preferences ◽  
Expert Assessment ◽  
Practical Implementation ◽  
Algorithmic Support ◽  
Interface Parameters

Рассматривается проблема выбора оптимальных параметров интерфейса в информационных системах с целью его персонализации под предпочтения пользователя и возможности его оборудования. В настоящее время для ее решения используется алгоритмическое обеспечение и статистическая обработка предпочтений пользователей, что не обеспечивает достаточной гибкости и точности. Поэтому в данной работе предлагается применение разработанного метода адаптации параметров интерфейса, основанного на анализе и обработке пользовательской информации с помощью нейронных сетей. Научная новизна метода заключается в автоматизации сбора, анализа данных и настройки интерфейса за счет использования и интеграции нейронных сетей в информационную систему. Рассмотрена практическая реализация предлагаемого метода на Python. Экспертная оценка адаптивности интерфейса тестовой информационной системы после внедрения разработанного метода показала его перспективность и эффективность. Разработанный метод показывает лучшую точность и низкую сложность программной реализации относительно классического алгоритмического подхода. Полученные результаты могут использоваться для автоматизации процесса выбора компонентов интерфейса различных информационных систем. Дальнейшие исследования заключаются в развитии и интеграции разработанного метода в рамках фреймворка адаптации информационных систем Here we consider the problem of choosing the optimal parameters of the interface in information systems with the aim of personalizing it for the preferences of the user and the capabilities of his equipment. Currently, algorithmic support and statistical processing of user preferences are used to solve it, which does not provide sufficient flexibility and accuracy. Therefore, in this work, we propose the application of the developed method for adapting interface parameters based on the analysis and processing of user information using neural networks. The scientific novelty of the method is to automate the collection, analysis of data and interface settings through the use and integration of neural networks in the information system. We consider the practical implementation of the proposed method in Python. An expert assessment of the adaptability of the interface of the test information system after the implementation of the developed method showed its availability and efficiency. The developed method shows the best accuracy and low complexity of software implementation relative to the classical algorithmic approach. The results obtained can be used to automate the selection of interface components for various information systems. Further research consists in the development and integration of the developed method within the framework of the information systems adaptation framework

scholarly journals The Association of Obesity and Liver Enzyme Activities in a Student Population at Increased Risk for Cardiovascular Disease / Veza Između Gojaznosti I Aktivnosti Jetrenih Enzima U Studentskoj Populaciji Sa Povećanim Rizikom Za Nastanak Kardiovaskularnih Bolesti

2013 ◽  
Vol 32 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Emina Čolak ◽  
Dragana Pap ◽  
Nada Majkić-Singh ◽  
Ivana Obradović
Keyword(s):  
Body Mass Index ◽  
Waist Circumference ◽  
Liver Enzyme ◽  
Body Mass ◽  
Statistical Processing ◽  
The Body ◽  
Control Group ◽  
Anthropometric Parameters ◽  
Nonalcoholic Fatty Liver ◽  
Increased Risk

Summary Background: It has been reported that obesity is associated with metabolic syndrome, insulin resistance, cardiovascular risk but also with nonalcoholic fatty liver disease (NAFLD). The prevalence of obesity in children and adolescents is increasing rapidly all over the world. The aim of this study was to analyze the value of liver enzymes: AST, ALT and γGT in a group of obese students in order to establish their correlation to anthropometric parameters such as: BMI (body mass index), WC (waist circumference), HC (hip circumference), and WHR (waist-to-hip ratio) compared to non-obese students who comprised the control group (CG). Methods: In this study, 238 students from the University of Novi Sad of both sexes (126 men and 112 women) with a mean age of 22.32 ± 1.85 years were included. According to the body mass index (BMI) lower and higher than 25 kg/m2 and waist circumference (WC) lower and higher than 94 cm (80 cm for females) the whole group of 238 students was divided into 2 subgroups: the obese group at increased risk for CVD (Group 1) and the group at lower risk for CVD (Group 2). AST, ALT and γGT activities were determined in fasting blood samples. Results: Statistical processing data revealed significantly higher values of AST, ALT and γGT in the group of students with BMI>25 kg/m2, WC>94 cm for males and WC>80 cm for females, HC>108 cm for males and HC>111 cm for females, and WHR>0.90 for males and WHR>0.80 for females (P<0.001). Significant association was established between anthropometric parameters and liver enzyme levels (P<0.0001). Conclusions: Obese students with higher BMI, WC, HC and WHR values have higher liver enzyme activites and a higher chance to develop NAFLD in the future.

Re-membering Syria’s Traumatic Past: Gender, Poetics, and Loss in Manhal al-Sarrāj’s As a River Should

2021 ◽  
Vol 52 (1-2) ◽  
pp. 202-227
Author(s):  
Linda Istanbulli
Keyword(s):  
Armed Conflict ◽  
Armed Conflicts ◽  
Traumatic Memory ◽  
The Novel ◽  
Historical Interpretation ◽  
The Past ◽  
Traumatic History ◽  
History Of ◽  
And Gender ◽  
The City

Abstract In a system where the state maintains a monopoly over historical interpretation, aesthetic investigations of denied traumatic memory become a space where the past is confronted, articulated, and deemed usable both for understanding the present and imagining the future. This article focuses on Kamā yanbaghī li-nahr (As a river should) by Manhal al-Sarrāj, one of the first Syrian novels to openly break the silence on the “1982 Hama massacre.” Engaging the politics and poetics of trauma remembrance, al-Sarrāj places the traumatic history of the city of Hama within a longer tradition of loss and nostalgia, most notably the poetic genre of rithāʾ (elegy) and the subgenre of rithāʾ al-mudun (city elegy). In doing so, Kamā yanbaghī li-nahr functions as a literary counter-site to official histories of the events of 1982, where threatened memory can be preserved. By investigating the intricate relationship between armed conflict and gender, the novel mourns Hama’s loss while condemning the violence that engendered it. The novel also makes new historical interpretations possible by reproducing the intricate relationship between mourning, violence, and gender, dislocating the binary lines around which official narratives of armed conflicts are typically constructed.

scholarly journals Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Aref M. al-Swaidani ◽  
Waed T. Khwies
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Network Architecture ◽  
Supplementary Cementitious Material ◽  
Natural Pozzolans ◽  
Long Time ◽  
Ann Models ◽  
Artificial Neural ◽  
And Performance ◽  
And Training

Numerous volcanic scoria (VS) cones are found in many places worldwide. Many of them have not yet been investigated, although few of which have been used as a supplementary cementitious material (SCM) for a long time. The use of natural pozzolans as cement replacement could be considered as a common practice in the construction industry due to the related economic, ecologic, and performance benefits. In the current paper, the effect of VS on the properties of concrete was investigated. Twenty-one concrete mixes with three w/b ratios (0.5, 0.6, and 0.7) and seven replacement levels of VS (0%, 10%, 15%, 20%, 25%, 30%, and 35%) were produced. The investigated concrete properties were the compressive strength, the water permeability, and the concrete porosity. Artificial neural networks (ANNs) were used for prediction of the investigated properties. Feed-forward backpropagation neural networks have been used. The ANN models have been established by incorporation of the laboratory experimental data and by properly choosing the network architecture and training processes. This study shows that the use of ANN models provided a more accurate tool to capture the effects of five parameters (cement content, volcanic scoria content, water content, superplasticizer content, and curing time) on the investigated properties. This prediction makes it possible to design VS-based concretes for a desired strength, water impermeability, and porosity at any given age and replacement level. Some correlations between the investigated properties were derived from the analysed data. Furthermore, the sensitivity analysis showed that all studied parameters have a strong effect on the investigated properties. The modification of the microstructure of VS-based cement paste has been observed, as well.

Age and Gender Recognition from Speech Using Deep Neural Networks

2020 ◽  
pp. 332-344
Author(s):  
Héctor A. Sánchez-Hevia ◽  
Roberto Gil-Pita ◽  
Manuel Utrilla-Manso ◽  
Manuel Rosa-Zurera
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Gender Recognition ◽  
Age And Gender ◽  
And Gender

scholarly journals Peculiarities of Mental and Behavioral Disorders in Children Released from Iraqi Prison

2019 ◽  
Vol 9 (4) ◽  
pp. 225-235
Author(s):  
N.M. Zakharova ◽  
A.V. Milekhina
Keyword(s):  
Behavioral Disorders ◽  
Dynamic Monitoring ◽  
Islamic State ◽  
Military Conflict ◽  
Psychological Examination ◽  
Terrorist Organization ◽  
Long Time ◽  
And Gender ◽  
Mental And Behavioral Disorders

The article provides data from a survey of 61 children (members of families of militants of the Islamic State terrorist organization) released from an Iraqi prison. Mental, psychological and behavioral disorders identified during clinical and psychological examination are described. The role of multiple psycho-traumatic factors in the construction of mental disorders in children who are forced to stay in a zone of local military conflict for a long time and survived heavy losses is shown. Based on the results, 6 groups were identified, united by similar symptoms and gender-age characteristics. It is noted that such general psychodynamic trends as a delay in psychophysical development and pedagogical neglect come to the fore, accompanied by situationally caused anxiety-depressive reactions provoked by additional psycho-traumatic factors (separation from mother, change of habitual settings and environment). The necessity of taking into account the religious, ethical and ethno-cultural characteristics in the examination and development of a set of rehabilitation measures for these children is shown. Attention is focused on the difficulties of adaptation and rehabilitation of this population in a society which is new for them, constant dynamic monitoring of the examined is justified.

scholarly journals Exploring genetic programming systems with MAP-Elites

2018 ◽  
Author(s):  
Emily Dolson ◽  
Alexander Lalejini ◽  
Charles Ofria
Keyword(s):  
Neural Networks ◽  
Genetic Programming ◽  
Pareto Front ◽  
Underlying Structure ◽  
Phenotypic Traits ◽  
Computation Technique ◽  
Phenotype Space ◽  
Programming Systems ◽  
Insight Into ◽  
Connection Cost

MAP-Elites is an evolutionary computation technique that has proven valuable for exploring and illuminating the genotype-phenotype space of a computational problem. In MAP-Elites, a population is structured based on phenotypic traits of prospective solutions; each cell represents a distinct combination of traits and maintains only the most fit organism found with those traits. The resulting map of trait combinations allows the user to develop a better understanding of how each trait relates to fitness and how traits interact. While MAP-Elites has not been demonstrated to be competitive for identifying the optimal Pareto front, the insights it provides do allow users to better understand the underlying problem. In particular, MAP-Elites has provided insight into the underlying structure of problem representations, such as the value of connection cost or modularity to evolving neural networks. Here, we extend the use of MAP-Elites to examine genetic programming representations, using aspects of program architecture as traits to explore. We demonstrate that MAP-Elites can generate programs with a much wider range of architectures than other evolutionary algorithms do (even those that are highly successful at maintaining diversity), which is not surprising as this is the purpose of MAP-Elites. Ultimately, we propose that MAP-Elites is a useful tool for understanding why genetic programming representations succeed or fail and we suggest that it should be used to choose selection techniques and tune parameters.

Underwriting Automobile Insurance Using Artificial Neural Networks

2011 ◽  
pp. 3865-3870
Author(s):  
Fred Kitchens
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Statistical Analysis ◽  
Automobile Insurance ◽  
Long Time ◽  
Artificial Neural ◽  
Pencil And Paper

For hundreds of years, actuaries used pencil and paper to perform their statistical analysis It was a long time before they had the help of a mechanical adding machine. Only recently have they had the benefit of computers. As recently as 1981, computers were not considered important to the process of insurance underwriting. Leading experts in insurance underwriting believed that the judgment factor involved in the underwriting process was too complex for any computer to handle as effectively as a human underwriter (Holtom, 1981). Recent research in the application of technology to the underwriting process has shown that Holtom’s statement may no longer hold true (Gaunt, 1972; Kitchens, 2000; Rose, 1986). The time for computers to take on an important role in the insurance underwriting process may be upon us. The author intends to illustrate the applicability of artificial neural networks to the insurance underwriting process.

P901 Left ventricular diastolic and systolic functions are compromised in patients with hypothyroidism

2020 ◽  
Vol 21 (Supplement_1) ◽  
Author(s):  
R Tafarshiku ◽  
M Y Henein ◽  
V Berisha-Muharremi ◽  
I Bytyci ◽  
P Ibrahimi ◽  
...  
Keyword(s):  
Diastolic Function ◽  
Systolic Function ◽  
White Blood Cells ◽  
Left Ventricular ◽  
Blood Analysis ◽  
Lv Function ◽  
Anthropometric Parameters ◽  
Age And Gender ◽  
And Gender ◽  
Lv Diastolic Function

Abstract Background and Aim Long standing hypothyroidism may impair myocardial relaxation, but its effect on systolic myocardial function is still controversial. The aim of this study was to investigate left ventricular (LV) systolic and diastolic function in patients with hypothyroidism. Methods This study included 81 (age 42 ± 13 years, 92% female) patients with hypothyroidism, and 22 age and gender matched controls. All subjects underwent a detailed clinical examination followed by a complete biochemical blood analysis including thyroid function assessment and anthropometric parameters measurements. LV function was assessed by 2 dimensional, M-mode and Tissue-Doppler Doppler echocardiographic examination performed in the same day. Results Patients had lower waist/hip ratio (p &lt; 0.001), higher urea level (p = 0.002) and lower white blood cells (p = 0.011), compared to controls. All other clinical, biochemical and anthropometric data did not differ between the two groups. Patients had impaired LV diastolic function (lower E wave [p &lt; 0.001], higher A wave [p = 0.028], lower E/A ratio [p &lt; 0.001], longer E wave deceleration time [p = 0.01], and higher E/e’ ratio [p &lt; 0.001]), compared with controls. Although LV global systolic function did not differ between groups, LV longitudinal systolic function was compromised in patients (lateral mitral annular plane systolic excursion - MAPSE [p = 0.005], as were lateral and septal TDI s’ [p &lt; 0.001 for both]). Conclusion In patients with hypothyroidism, in addition to compromised LV diastolic function, LV longitudinal systolic function is also impaired compared to healthy subjects of the same age and gender. These findings suggest significant subendocardial function impairment, reflecting potentially micro-circulation disease, that requires optimum management.

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