Predicting the results of the 16-factor R. Cattell test based on the analysis of text posts of social network users

We investigated the possibility of automating the prediction of the 16-factor personality traits by R. Cattell from text posts of social media users. The proposed new method of automating the evaluation of R. Kettell’s 16-factor personality test traits includes language models and neural networks. Implementation of the method involves several steps. At the first step text posts are extracted from user accounts of social media, pre-processed with language model RuBERT and previously trained over a full-connected neural network. The result of this step is a normalized empirical distribution of the posts by the previously introduced classes for each user. Subsequently, based on the distribution of user posts the evaluation of the expression of psychological features of the user is made with the help of support vector machine, random forest and Naive Bayesian classifier. The final data set for model building and further testing their performance was made up of 183 respondents who took the R. Cattell test, with links to their public social media accounts. Classifiers predicting results for six factors (A, B, F, I, N, Q1) of R. Cattells 16-factor personality test were constructed. The results can be used to create a prototype of automated system for predicting the severity of psychological features of social media users. Results of work are useful in the applied and research systems connected with marketing, psychology and sociology, and also in the field of protection of users from social engineering attacks

Выявление характеристик индивидуального человеческого капитала сотрудников организации по данным самоотчетов о профессиональных навыках и личностным особенностям

В области рекрутинга и менеджмента персонала существует задача автоматизации процесса оценки характеристик человеческого капитала, учитывающего в том числе особенности личности сотрудника. Статья посвящена вопросу выявления характеристик индивидуального человеческого капитала, имеющих наибольший вклад в некоторые показатели эффективности сотрудника организации, таких как карьерный успех, по данным их самоотчетов о профессиональных навыках и ответов на вопросы–утверждения о различных психологических аспектах личности. Предлагается общая структура опросного инструментария, опирающегося на самоотчеты сотрудников, а также формализация предполагаемых методов анализа таких вопросов. Для выявления групп респондентов, обладающих схожими профессиональными навыками, было предложено использовать кластерный анализ, который позволяет сохранить сложную структуру их взаимосвязи. Для выявления личностных особенностей сотрудников из вопросов–утверждений предлагается формировать шкалы и посредством методов современной теории тестирования получить оценки латентной переменной, отражающей личностные особенности. На завершающем этапе исследования предполагается использование аппарата регрессии для оценивания взаимосвязи выявленных кластеров и латентных характеристик личности с тем или иным индикатором успешности сотрудника. Предлагаемый подход представляет собой структуру пилотного исследования, позволяющего выделить характеристики человеческого капитала (профессиональные навыки и особенности личности), обладающие наибольшим вкладом в показатели эффективности сотрудника или организации, и направлен на снижение трудозатрат на последующих этапах более подробного и прицельного исследования. Возможности предложенного подхода продемонстрированы на примере данных, собранных среди государственных гражданских служащих различных структур Российской Федерации. В качестве индикатора эффективности сотрудника рассматривается наиболее доступный к наблюдению аспект карьерного успеха, выраженный фактом наличия руководящей должности

Supramolecular Adduct of γ-Cyclodextrin and [{Re6Q8}(H2O)6]2+ (Q=S, Se)

International audienceSlow evaporation of water solution of [{Re 6 S 8 }(H 2 O) 6 ] 2+ generated in situ from [{Re 6 S 8 }(OH) 6 ] 4-in presence of γ-cyclodextrin (CD) leads to crystallization of {[{Re 6 S 8 }(H 2 O) 6 ]⊂[γ-CD]}(NO 3) 2 ·12H 2 O (1·12H 2 O) supramolecular complex, which was characterized by single-crystal X-ray diffraction crystallography, IR-spectroscopy, thermogravimetric and elemental analyses. X-ray analysis confirms the formation of 1:1 {[{Re 6 S 8 }(H 2 O) 6 ]⊂[γ-CD]} 2+ inclusion compound in the solid state. However, no adduct formation was detected between [{Re 6 S 8 }(H 2 O) 6 ] 2+ and γ-cyclodextrin in solution, according to 1 H NMR spectroscopy. In the case of in situ generated [{Re 6 Se 8 }(H 2 O) 6 ] 2+ the reaction solution with γ-cyclodextrin is unstable and during the crystallization only amorphous precipitate has been obtained

Identification of Deterioration caused by AHF, MADS or CE by RR and QT Data Classification

A sharp deterioration of the patient’s condition against the backdrop of the development of life-threatening arrhythmias with symptoms of acute heart failure (AHF), multiple organ dysfunction syndrome (MODS) or cerebral edema (CE) can lead to the death of the patient. Since the known methods of automated diagnostics currently cannot accurately and promptly determine that the patient is in a life-threatening condition leading to the fatal outcome caused by AHF, MODS or CE, there is a need to develop appropriate methods. One of the ways to identify predictors of such a state is to apply machine learning methods to the collected datasets. In this article, we consider using data analysis methods to test the hypothesis that there is a predictor of death risk assessment, which can be derived from the previously obtained values of the ECG intervals, which gives a statistically significant difference for the ECG of the two groups of patients: those who suffered deterioration leading to the fatal outcome caused be MODS, AHF or CE, and those with favorable outcome. A method for unifying ECG data was proposed, which allow, based on the sequence of RR and QT intervals, to the construct of a number that is a characteristic of the patient's heart condition. Based on this characteristic, the patients are classified into groups: the main (patients with fatal outcome) and control (patients with favorable outcome). The resulting classification method lays the potential for the development of methods for identifying the patient's health condition, which will automate the detection of its deterioration. The novelty of the result lies in the confirmation of the hypothesis stated above, as well as the proposed classification criteria that allow solving the urgent problem of an automatic detection of the deterioration of the patient's condition

Automation of complex text CAPTCHA recognition using conditional generative adversarial networks

With the rapid development of Internet technologies, the problems of network security continue to worsen. So, one of the most common methods of maintaining security and preventing malicious attacks is CAPTCHA (fully automated public Turing test). CAPTCHA most often consists of some kind of security code, to bypass which it is necessary to perform a simple task, such as entering a word displayed in an image, solving a basic arithmetic equation, etc. However, the most widely used type of CAPTCHA is still the text type. In the recent years, the development of computer vision and, in particular, neural networks has contributed to a decrease in the resistance to hacking of text CAPTCHA. However, the security and resistance to recognition of complex CAPTCHA containing a lot of noise and distortion is still insufficiently studied. This study examines CAPTCHA, the distinctive feature of which is the use of a large number of different distortions, and each individual image uses its own different set of distortions, that is why even the human eye cannot always recognize what is depicted in the photo. The purpose of this work is to assess the security of sites using the CAPTCHA text type by testing their resistance to an automated solution. This testing will be used for the subsequent development of recommendations for improving the effectiveness of protection mechanisms. The result of the work is an implemented synthetic generator and discriminator of the CGAN architecture, as well as a decoder program, which is a trained convolutional neural network that solves this type of CAPTCHA. The recognition accuracy of the model constructed in the article was 63 % on an initially very limited data set, which shows the information security risks that sites using a similar type of CAPTCHA can carry

Social Influence on the User in Social Network: Types of Communications in Assessment of the Behavioral Risks connected with the Socio-engineering Attacks

The purpose of this study is to study the impact of possible types of relationships between users, which are represented in the social network “VKontakte”, on the probability of the spread of a social engineering attack.Methods. To achieve this goal, a survey was developed and a web page was created, which is used to collect responses from respondents. After receiving the data, the obtained results were analyzed using the tools available in Microsoft Excel. In addition, for more in-depth analysis of the results, a C program was developed, which calculates the necessary characteristics and outputs the results to an Excel document.Results. In analyzing the results of the survey, the types of relationships between users were identified, in which they are more likely to respond to the request. It was also revealed that the answers are most often found in which several or even all categories in groups of relationship types between users were assigned the same assessments of the degree of readiness to respond to a request. In addition, it is worth noting that there are often answers in which respondents identified only one of the presented communication options.Conclusion. According to the study, it was hypothesized that the assessments of the degree of readiness to respond to a request to join the community for different groups of relationships are different, but the intragroup assessments differ little. The results obtained, demonstrating the lack of differentiation of values within groups of types of relationships, are significant, but at the same time, a deeper study of the orders that can be traced in the responses of a number of respondents is required

Magnetic Properties of La0.9A0.1MnO3 (A: Li, Na, K) Nanopowders and Nanoceramics

Nanocrystalline La0.9A0.1MnO3 (where A is Li, Na, K) powders were synthesized by a combustion method. The powders used to prepare nanoceramics were fabricated via a high-temperature sintering method. The structure and morphology of all compounds were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM). It was found that the size of the crystallites depended on the type of alkali ions used. The high-pressure sintering method kept the nanosized character of the grains in the ceramics, which had a significant impact on their physical properties. Magnetization studies were performed for both powder and ceramic samples in order to check the impact of the alkali ion dopants as well as the sintering pressure on the magnetization of the compounds. It was found that, by using different dopants, it was possible to strongly change the magnetic characteristics of the manganites

Hemilability of phosphine-thioether ligands coordinated to trinuclear Mo3S4 cluster and its effect on hydrogenation catalysis

Ligand-exchange reactions of [Mo3S4(tu)8(H2O)]Cl44H2O (tu = thiourea) with (PhCH2CH2)2PCH2CH2SR ligands, where R = Ph (PS1), pentyl (PS2) or Pr (PS3) afford new complexes isolated as [Mo3S4Cl3(PS1)3]PF6 ([1]PF6), [Mo3S4Cl3(PS2)3]PF6 ([2]PF6) and [Mo3S4Cl3(PS3)3]PF6 ([3]PF6) salts in 30-50% yields as the major reaction products. The crystal structures of [1]PF6 and [2]PF6 were determined by X-ray diffraction (XRD) analysis. Each of the three phosphine-thioether ligands is coordinated in a bidentate chelating mode to a different molybdenum atom of the Mo3S4 trinuclear cluster, herewith all the phosphorus atoms of the phosphino-thioether ligand are located trans to the capping sulfur (3-S). A second product that forms in the reaction of [Mo3S4(tu)8(H2O)]Cl44H2O with PS1 corresponds to the neutral [Mo3S4Cl4(PS1)2(PS1*)] complex. Its XRD analysis reveals both bidentate (PS1) and monodentate (PS1*) coordinating modes of the same ligand. In the latter mode the phosphinethioether is coordinated to a Mo atom only via the P atom. All compounds were characterized by 1H, 31P{1H} NMR, electrospray-ionization (ESI) mass spectrometry and cyclic voltammetry (CV). Reactions of [1]PF6, [2]PF6 and [3]PF6 with an excess of Bu4NCl in CD2Cl2 were followed by 31P{1H} NMR. The spectra indicate equilibrium between cationic [Mo3S4Cl3(PSn)3] + and neutral [Mo3S4Cl4(PSn)2(PSn*)] (n = 1, 2) species. The equilibrium constants were determined as 2.5 ± 0.2103 , 43 ± 2 М -1 and 30 ± 2 М -1 (at 25°C) for [1]PF6, [2]PF6 and [3]PF6, indicating quantitative differences in hemilabile behavior of the phosphino-thioether ligands, depending on the substituent at sulfur. Clusters [1]PF6, [2]PF6 and [3]PF6 were tested as catalysts in reduction of nitrobenzene to aniline with Ph2SiH2 under mild conditions. Significant differencies in the catalytic activity were observed, which can be attributed to different hemilabile behavior of the PS1 and PS2/PS3 ligands