Miracle-dz/UniFAR-FTUs huggingface dataset:
Long Short-Term Memory (LSTM) Deep Learning Method for Intrusion Detection in Network Security

Nowadays, large numbers of people were affected by data infringes and cyber-attacks due to dependency on internet. India is lager country for any resource use or consumer. Over the past ten years, the average cost of a data breach has increased by 12%. Hacking in India is take share of 2.3% of global criminal activity. To prevent such malicious activity, the network requires a system that detects anomaly and inform to the admin or service operator for taking an action according to the alert. System used for intrusion detection (IDS) is software that helps to identify and observes a network or systems for malicious, anomaly or policy violation. Deep learning algorithm techniques is an advanced method for detect intrusion in network. In this paper, intrusion detection model is train and test by NSL-KDD dataset which is enhanced version of KDD99 dataset. Proposed method operations are done by Long Short-Term Memory (LSTM) and detect attack. So admin can take action according to alert for prevent such activity. This method is used for binary and multiclass classification of data for binary classification it gives 99.2% accuracy and for multiclass classification it gives 96.9% accuracy. Keywords— Intrusion detection; Deep Learning Method; LSTM algorithm; Network Security, NSLKDD dataset.
Working-memory prefrontal model for cognitive flexibility in task-switching and selection

We propose a working-memory model inspired by the prefrontal cortex for flexible cognitive tasks. Our neural model categorizes contexts depending on the task features and selects the most appropriate one relative to inputs. Output errors led to a reevaluation of the context confidence level and a shift to another or the creation of a new one. Tests on the Wisconsin card task show the relevance of our model. Impairments of brain parts that regulate the neuromodulators for context evaluation or output selection produces similar prefrontal disorder and degeneration found in the brain literature.
Does Productivity Fall After the Adoption of New Technology?

A number of theoretical models of technology adoption have been proposed that emphasize technological switching, loss of expertise and subsequent technology-specific learning. These models imply that measured productivity may initially fall and then later rise after the adoption of a new technology. This paper investigates whether or not this implication is a feature of plant-level data from the Colombian manufacturing sector. We regress measures of productivity growth at the plant level on a plant-specific measure of technology adoption and its lagged values. We find that . 'Address of the authors: Centro de Investigacion Economica ITAM, Camino Santa Teresa 930, Mexico DE 10700, Mexico. E-mail: huggett©master.ster. itam.mx, ospina@smithshortitam.mx We thank the Central Bank of Colombia for allowing access to the Encuesta Anual Manufacturera.
Usage of Machine-based Translation Methods for Analyzing Open Data in Legal Cases

Deep learning has completely changed approaches to machine translation. The initial ways of building machine translation software were based on rules, the next stage was based on statistics and probability theory. But nowadays, with new researches in the deep learning field has created simple solutions based on machine learning that outperform the best expert systems. This paper overviews the main features of machine translation for analyzing open data in legal cases based on recurrent neural networks. The advantages of systems based on RNN using the sequence-to-sequence model against statistical translation systems are also highlighted in the article. Two machine translation systems based on the sequence-to-sequence model were constructed using Keras and PyTorch machine learning libraries. Based on the obtained results, libraries' analysis was done, and their performance comparison.
A Review on Image Inpainting Techniques

Various factors affect the image that causes image deterioration. The art of restoration of deteriorated parts of image is known as image inpainting. The image inpainting is mainly categorized in 2 sections: Diffusion based and Exemplarbased image inpainting. This paper contains the overview of various techniques of image inpainting its advantages and limitations. Based on the Existing techniques, a new technique is proposed for image inpainting to overcome the drawbacks of
An algorithmic characterization

Let K be a field of characteristic zero, d a derivation of K [X; Y1, . , Yn] of the type d = ∂X + ∑n i=1(ai Yi + bi )∂Yi with ai , bi ∈ K [X ] for every i . We characterize the property “d is a simple derivation of K [X; Y1, . , Yn]” in terms of a certain property of d, a property that one can effectively check for whether it is satisfied or not. We apply our algorithm to exhibit families of simple derivations of K [X; Y1, . , Yn] that are very different from what has been known until now. We also show that our algorithm can be traduced into one that determines effectively whether the solutions in the power series ring K [[t]] of the system of algebraic equations { y i (t) = ai (t + α)yi (t) + bi (t + α) }n i=1 , α ∈ K , are algebraically independent over K (t) or not. c © 2007 Elsevier B.V. All rights reserved. MSC: Primary: 13.N. 15; secondary: 13.P.99
Variable-Radius Offset Surface Approximation on the GPU

Variable-radius offset surfaces ﬁnd applications in various ﬁelds, such as variable brush strokes in 2D and 3D sketching and geometric modeling tools. In forensic facial reconstruction the skin surface can be inferred from a given skull by computing a variable-radius offset surface of the skull surface. Thereby, the skull is represented as a two-manifold triangle mesh and the facial soft tissue thickness is speciﬁed for each vertex of the mesh. We present a method to interactively visualize the wanted skin surface by rendering the variable-radius offset surfaces of all triangles of the skull mesh. We have also developed a special shader program which is able to generate a discretized volumetric representation that can be transformed into a skin mesh. In addition, we show the usefulness of our method to calculate classical Minkowski sums and demonstrate its use for packing problems.
Improving Eye Tracking Accuracy by Head Motion History

We focus on eye tracking by head motion. This type of eye tracking does not provide the most accurate results, but it does not require a user to wear cumbersome sensors like cameras on glasses. The approach works for many applications, such as the extraction of human attention by surveillance camera or an intuitive interface for tablet devices. Through a preliminary experiment, we conﬁrmed that head direction is often largely diﬀerent from eye direction. We propose to estimate accurate eye direction by using head motion history. A sequence of head directions and the diﬀerentials provide richer information than head direction at one moment. Using multiple regression analysis (MRA) and dynamic coupled component analysis (DCCA), we examined the relationship between eye direction and head motion history, and reduced the error rate by 7.2% and 0.8% on average.
Transmitted Drug Resistance in Hiv-1 Non-B Subtypes Newly Diagnosed Patient: Case Report

Antiretroviral therapy has a very high efficacy and has substantially changed patients’ quality of life, although it does need an equallyhigh adherence. The widespread use of antiretroviral therapy has significantly reduced the risk of HIV. However, at the same time it has resulted in an increase in HIV-drug resistance, which can be transmitted to newly-infected individuals, thus compromising the efficacy of combination regimens and potentially leading to the their failure. In Europe the overall prevalence of transmitted HIV-drug resistance was 8.3% in 2008-2010 and it is considered rather uncommon in non-B subtypes. In this study we report a case of drug-resistance transmission in a patient with HIV inter recombinant form infection. The transmission occurred heterosexually in a couple of immigrants without stay permit. Phylogenetic analysis was performed. Our report underlines how, even if not very high, the prevalence of HIV primary drug resistance is essential to perform the resistance test, at least of the pol gene in all new HIV diagnoses. Even in countries with high income and almost totalfree diagnosis and treatment, some patient settings are at risk of developing drug-resistant strains. More studies are needed for the proper evaluation of transmitted HIVDR in non-B subtypes of HIV.
Mechanisms of structural plasticity in mature sensory axons: Role of BMP4 in female reproductive tract

Structural changes in sensory axons are associated with many peripheral nerve disorders. Degenerative loss or excessive sprouting of axons are hallmarks of sensory neuropathies or hyperinnervating pain syndromes respectively. While much is known about mechanisms of developmental axon growth or regenerative outgrowth following nerve injury, there is little information about mechanisms that can induce plasticity in intact adult axons. Lack of model systems, where extensive plasticity can be predictably induced under physiological conditions, has been a fundamental impediment in studying sensory neuroplasticity mechanisms in adult. The female reproductive tract presents a highly tractable model where sensory axons cyclically undergo extensive plasticity under the influence of estrogen. In rat, high estrogen levels induce reduction in vaginal sensory nerve density, and low estrogen conditions promote sprouting leading to hyperinnervation. We used this model to explore potential factors that can initiate spontaneous plasticity in intact sensory axons. We found that estrogen downregulates expression of Bone Morphogenetic Protein 4 (BMP4) in the vaginal submucosal smooth muscle cells which are associated with most innervation in the vagina. Thus under low estrogen conditions BMP4 expression increased in the smooth muscle, and the resulting trophic stimulus induced sprouting in associated nociceptive sensory axons. Activated Smad1 in nuclei of retrogradely labeled dorsal root ganglion neurons innervating the vagina confirmed BMP4 signaling under low estrogen conditions. When BMP4 was overexpressed in the vaginal submucosal smooth muscle by lentiviral transduction, elevated nerve density prevailed even under high blood estrogen levels. To identify the signaling mechanism by which BMP4 regulates sensory plasticity downstream from phospho-Smad1, we used the 50B11 sensory neuronal cell line. Receptor iv expression and outgrowth responses of the 50B11 cells to neurotrophins and growth factors resembled closely that of primary sensory neurons in culture, providing a reliable assay system. BMP4 treatment induced upregulation of Inhibitor of DNA binding 2 (Id2), a known downstream target of Smad1, in 50B11 cells; and Id2 overexpression induced increased neurite outgrowth. However, Id2 knockdown failed to abrogate BMP4-mediated increase of outgrowth in primary neurons, suggesting alternative mechanisms. We identified that BMP4 downregulates methyl CpG-binding protein 2 (MeCP2), a methylated-DNA binding protein and an epigenetic modifier and global transcriptional repressor, which is highly expressed in neurons. MeCP2 downregulation can prompt a global transcriptional upregulation inducing multiple genes, a situation characteristic of axonal growth initiation. Lentiviral knockdown of MeCP2 resulted in significant elevation of outgrowth in primary sensory neurons that matched growth induced by BMP4. …
The Long-Term Consequences of a Golden Nest

We study the role played by the standard of living during childhood on nest leaving. Using data from SHARE, we show empirically that individuals who grew up in a golden nest leave the parental home later and that education only partially mediates this effect. This relationship holds across different cultures, for both males and females, urban and rural residents. We then use a 3-period lifecycle model to show that this behaviour is consistent with standard assumptions on preferences and resources if earnings increase with age, and that habit-forming preferences reinforce the delaying effect of a golden nest on nest leaving.
EFFECTIVE HAMILTONIANS FOR LINEAR ENVIRONMENTS

Understanding the role of an object is not possible if it is only observed in isolation. The effect caused on a degree of freedom through a surrounding multi-mode cavity is highly complex and its calculation often requires numerics or heavy approximations. The attempt of this thesis is to investigate these effects analytically through the example of a qubit represented by an LC-oscillator that is weakly coupled to a transmission line. Especially the dispersive and the resonant case are characterized with the emphasis on accurately understanding the limits of their validity. We find that in the dispersive regime the transmission line acts like a single-mode resonator. However, we also discuss a correction due to the other modes which displays an asymmetry with respect to the detuning. Additionally, we discuss a Caldeira-Leggett Hamiltonian for an arbitrary impedance and present an expansion for two-port networks.
Genetic-Based Trading Rules-A New Tool to Beat the Market With?-Proceedings AFIR 1996-Nürnberg, Germany

We investigate price-based heuristic trading rules for buying and selling shares. This is accompanied by transforming the time series of share prices using Point & Figure (P&F) Chart Analysis. On the basis of the binary representation of those charts we used a genetic-based Machine Learning System to generate trading strategies by the classification of different price formations. We used two different evaluation methods: 1) comparing the return of any considered trading strategy with the corresponding riskless interest rate and the average stock market return, and 2) using its risk-adjusted expected return as a benchmark instead of the average stock market return. The latter is calculated using the Capital Asset Pricing Model (CAPM). The resulting binary example data is iteratively processed by our learning system. We used as input data 1.120. 278 intraday stock prices from the Frankfurt Stock Exchange (FSE). We show to which degree of correctness different price formations ca be classified by our system and how such rules look like. R&Um6 Nous ktudions des prix-bash rkgles de commerce pour acheter et vendre des actions. Nous ferons cela en transformant la drie des prix d’actions en utilisant point & figure chart analyse. De ces dernikres, nous reqwrons des formations, dont nous pouvons crkr des rkgles pour la classification par notre gknktique mkhanique systkme d ’apprentissage. Nous ferons 1 ’evaluation des formations en deux mkthodes: L’un, par comparer les taux de rendement de chaque stratkgie de commerce avec l’int6ret sans risque et le moyen taux de rendement de la bourse, 1 ’autre par comparation avec le risque-adapt6 taux de rendement calculk avec le capital asset price model (CAPM). Les donnks d ’exemple sont process& avec notre systkme d ’apprentissage. Nous avons utilid 1.120. 278 entre-jour prix d’actions du Frankfurt Stock Exchange (FSE). Nous montrons l’exactitude de la classification des prix formations diffkrents et les rkgles correspondants avec ceux.
Textual Evidence for the Perfunctoriness of Independent Medical Reviews

We examine a database of 26 , 361 Independent Medical Reviews (IMRs) for privately insured patients, handled by the California Department of Managed Health Care (DMHC) through a private contractor. IMR processes are meant to provide protection for patients whose doctors prescribe treatments that are denied by their health insurance (either private insurance or the insurance that is part of their worker comp; we focus on private insurance here). Laws requiring IMR were established in California and other states because patients and their doctors were concerned that health insurance plans deny coverage for medically necessary services. We analyze the text of the reviews and compare them closely with a sample of 50000 Yelp reviews [19] and the corpus of 50000 IMDB movie reviews [10]. Despite the fact that the IMDB corpus is twice as large as the IMR corpus, and the Yelp sample contains almost twice as many reviews, we can construct a very good language model for the IMR corpus using inductive sequential transfer learning, specifically ULMFiT [8], as measured by the quality of text generation, as well as low perplexity (11 . 86) and high categorical accuracy (0 . 53) on unseen test data, compared to the larger Yelp and IMDB corpora (perplexity: 40 . 3 and 37, respectively; accuracy: 0 . 29 and 0 . 39). We see similar trends in topic models [17] and classification models predicting binary IMR outcomes and binarized sentiment for Yelp and IMDB reviews. We also examine four other corpora (drug reviews [6], data science job postings [9], legal case summaries [5] and cooking recipes [11]) to show that the IMR re-sults are not typical for specialized-register corpora. These results indicate that movie and restaurant reviews exhibit a much larger variety, more contentful discussion, and greater attention to detail compared to IMR reviews, which points to the possibility that a crucial consumer protection mandated by law fails a sizeable class of highly vulnerable patients.
General psychology, personality psychology, history of psychology 3 A study of personal traits in a typological context

The article points out that the identification of typological human peculiarities is of great practical significance in every sphere of our life. As different types of people are characterised with different specifications, the treatment and claims should be different towards them. The aim of the research consists in identifying personal peculiarities and the state of neuroticism among typical extraverts and introverts. The author of the article combines aggression, self-esteem and locus of control in the state of neuroticism. The article points out that aggression and self-esteem problems are found in each case of psychic disorder, so their role is viewed as special when we are talking about typological neurotisation. The high level of control locus is also connected with neuroticism and psychological problems. That is why the author is interested in the correlation between control locus orientations (external – internal) and types. In case of personal peculiarities, according to this typology, the article pays special attention to social attitudes, how different the evaluations and the intensity of these evaluations towards some topics by extraverts and introverts would be. The author carries out experimental research; the results of this research, presented in the article, reveal some interesting correlations between typological and gender factors. For citation Merabishvili T.G. (2018) A study of personal traits in a typological context. Psikhologiya. Istoriko-kriticheskie obzory i sovremennye issledovaniya [Psychology. Historical-critical Reviews and Current Researches], 7 (4A), pp. 3-11.
Assimilation of meteorological data

Meteorological observation tools (satellites and ground stations) provide a very large amount of meteorological data, which must be processed to establish the state of the atmosphere from the forecast model. It is this processing that is called data assimilation. It must result in a value of each of the atmosphere parameters in each grid cell of the model. This initial step in weather forecasting is crucial because any initial error has the property of spreading and gradually contaminating the entire atmosphere.
Beyond the Rotating Wave Approximation Dynamics of High-Fidelity Quantum Gates

An important aspect for practical quantum computation is the ability to precisely manipulate the fundamental unit of quantum information, the qubit, through coupling the qubit to a drive signal. Closely connected to this is our capability to predict the dynamic behavior of the system qubit-gate accurately. In this thesis, we give an extended review from a different perspective of a framework, presented in [1], for the description of the time evolution of such systems. The methodology applied in [1] relies on a perturbative calculation of an effective Hamiltonian based on the Magnus expansion. We will use this effective Hamiltonian formalism to predict the time evolution of a high fidelity quantum gate for singlet-triplet qubits developed in [2] using a phenomenological model. Finally, we will present a new approach of calculating the effective Hamiltonian. This new approach is aimed at finding a nonrecursive formula for the effective Hamiltonian, thereby reducing the computational cost of determining such effective Hamiltonians. In the process of doing so, we obtain some simplifications as well as motivate new directions for further development of the formalism.
The Relation Between Mental Stubbornness and Sports-Burnout of Injured Athletes at Karadeniz Technical University

Sports-burnout stems from chronic stress. The aim of this study was to investigate the relationship between mental stubbornness and sports-burnout in injured athletes at the Karadeniz Technical University. The present study is a correlational study that is applied in terms of its nature. The statistical population of the present study contains the injured athletes of Karadeniz Technical University, whose number is equal to 39 people. Because of the limited statistical population, we used the total number method. Fuller et al. (2006) Injury Report Form was used to select the injured athletes and the mental stubbornness Questionnaire and Sports disability Questionnaire were used to collect information. To analyze the data, SPSS software version 22 was used, and the Pearson correlation coefficient was used to analyze the relationship between the variables, and finally, the regression coefficient was used to determine and predict the sports-burnout of athletes affected by mental stubbornness. The results show that there is a significant negative relation between confidence (r = -0.51, p < 0.01), sustainability (r = -0.51, p < 0.01), control (r = -0.42, p < 0.01) and a total score of mental strength and sports- burnout of injured athletes (r = -0.47, p < 0.01). We conclude that mental stubbornness reduces the likelihood of athletic impairment in athletes and is a psychological characteristic of a personality that protects athletes from developing athletic impairment.
Crowdsourcing Image-Word Associations to Generate Affective Space Maps for Affective Words

: There has been a growing demand to search for content that matches personal preferences, all while the amount of available media increases constantly. Such demand calls for the necessity to label media with affective words, which describes the emotional impression the images might evoke. On the other hand, Affective Space has been gaining more and more attentions for the quantitative representation of emotion. In this study, we propose to use a crowdsourcing approach to collect all affective words that correspond to a given image from IAPS, a database consisting of images with known Affective Space coordinate. An online game is designed to get users involved in associating affective words with images. As the result, we can not only label IAPS images with affective words, but also consequentially obtain the Affective Space coordinates for affective words through their associated images.
STUDY ON CHEMICAL CONSTITUENTS IN ETHYL ACETATE FRACTION OF ALCOHOLIC EXTRACT FROM THE FLOWER OF BOMBAX MALABARICUM DC.

Chemical constituents in ethyl acetate fraction of alcoholic extract from the flower of Bombax malabaricum DC.were investigated by using GC-MS.Sixty peaks were separated,and 46 compounds were identified.Relative content of the constituents were determined by GC with area normalizing method.The identification ratio was 87.11%. The main chemical components of the fraction are palmitic acid,ethyl palmitate,β-sitosterol,etc.