Similar Description Research Articles

New approach to the identification of the easy expression recognition system by robust techniques (SIFT, PCA-SIFT, ASIFT and SURF)

In recent years, facial recognition has been a major problem in the field of computer vision, which has attracted lots of interest in previous years because of its use in different applications by different domains and image analysis. Which is based on the extraction of facial descriptors, it is a very important step in facial recognition. In this article, we compared robust methods (SIFT, PCA-SIFT, ASIFT and SURF) to extract relevant facial information with different facial posture variations (open and unopened mouth, glasses and no glasses, open and closed eyes). The simulation results show that the detector (SURF) is better than others at finding the similarity descriptor and calculation time. Our method is based on the normalization of vector descriptors and combined with the RANSAC algorithm to cancel outliers in order to calculate the Hessian matrix with the objective of reducing the calculation time. To validate our experience, we tested four facial images databases containing several modifications. The results of the simulation show that our method is more efficient than other detectors in terms of speed of recognition and determination of similar points between two images of the same face, one belonging to the base of the text and the other one to the base driven by different modifications. This method, which can be applied on a mobile platform to analyze the content of simple images, for example, to detect driver fatigue, human-machine interaction, human-robot. Using descriptors with properties important for good accuracy and real-time response.

Relative Distribution Entropy Loss Function in CNN Image Retrieval.

Convolutional neural networks (CNN) is the most mainstream solution in the field of image retrieval. Deep metric learning is introduced into the field of image retrieval, focusing on the construction of pair-based loss function. However, most pair-based loss functions of metric learning merely take common vector similarity (such as Euclidean distance) of the final image descriptors into consideration, while neglecting other distribution characters of these descriptors. In this work, we propose relative distribution entropy (RDE) to describe the internal distribution attributes of image descriptors. We combine relative distribution entropy with the Euclidean distance to obtain the relative distribution entropy weighted distance (RDE-distance). Moreover, the RDE-distance is fused with the contrastive loss and triplet loss to build the relative distributed entropy loss functions. The experimental results demonstrate that our method attains the state-of-the-art performance on most image retrieval benchmarks.

NOVEL KORUPSI KARYA PRAMOEDYA ANANTA TOER DAN KORUPSI KARYA TAHAR BEN JELLOUN SERTA KESESUAIANNYA SEBAGAI BAHAN PEMBELAJARAN SASTRA DI SEKOLAH

Pramoedya Ananta Toer’s Korupsi and Tahar Ben Jelloun’s Korupsi are two literary works of world writers who have similarities in terms of titles and themes. This study aims to find out and describe the structure, describe the similarities and differences, and knowing and describing the suitability between Pramoedya Ananta Toer’s Korupsi and Tahar Ben Jelloun’s Korupsi as material for literary learning at school. The object of this research is Pramoedya Ananta Toer’s Korupsi and Tahar Ben Jelloun’s Korupsi. Through the qualitative research paradigm, this research was conducted using descriptive methods of comparative analysis and objective approaches based on the literature itself. The data collection technique of this study uses library research. In connection with the comparative literary work step, research applies structural analysis by applying Robert Stanton's structuralism theory to reveal the similarities and differences contained in the two novels. Based on the results of comparative analysis of textual structures, we obtain a description of differences and similarities from two data sources so that it can be concluded that the Pramoedya Ananta Toer’s Korupsi influences to Tahar Ben Jelloun’s Korupsi as indicated by the use of titles, themes, characters and characterizations. The results of a comparative study of the Pramoedya Ananta Toer’s Korupsi and Tahar Ben Jelloun’s Korupsi are used as recommendations for literary learning in schools. The Corruption novel by Pramooedya Ananta Toer is suitable as a literary learning material in schools, while the Corruption novel Tahar Ben Jelloun is not appropriate because it does not meet 3 criteria and aspects of the selection of teaching materials, namely aspects of language, culture, and psychology.

Classifying shape of internal pores within AlSi10Mg alloy manufactured by laser powder bed fusion using 3D X-ray micro computed tomography: Influence of processing parameters and heat treatment

Internal porosity of metallic parts manufactured by laser powder bed fusion (LPBF) is governed by processing parameters including laser power, scanning speed, scan spacing and layer thickness. To fully understand the influence of processing parameters it is important to categorise the shape of process defects (pores) in 3D beyond the degree of sphericity alone. In the present paper, AlSi10Mg samples were manufactured using 30 unique LPBF parameter combinations and analysed using high resolution X-ray micro computed tomography (XμCT). The shapes of individual pores are classified and studied using an approach based on the similarity of 3D pore descriptors with simplified artificial objects. Porosity within high as-fabricated densification builds can be reduced to virtually negligible by hot isostatic pressing (HIPping), which was found to fully or partially close (flatten) pores. Subsequent T6 treatment causes pores to reopen and resemble their original shape. The effects of treatment are sensitive to pore size.

Gen Dizilerinde (cDNA Mikroarray) Temel Bileşenler Analizinin Uygulanması

Bu çalışmada, farelerin karaciğerleri üzerine belirli zaman periyotlarında uygulanmış olan, toksikolojik çalışmalardan alınan ve cDNA mikrodizi teknolojisi kullanılarak elde edilen 6675 gen ve 20 dizi içeren verilere temel bileşenler analizi uygulanmıştır. cDNA teknolojisi kullanılarak, birbirine benzer ifade profilleri ile gen gruplarının oluşturulması ve gruplar içerisindeki benzer bileşen (component) yükleri vasıtasıyla birbirleriyle ilişkili genlerin tanımlanması açıklanmıştır. Bunun yanı sıra aynı veri kümesine ait korelasyon matrisinden faktörlerin ayrıştırılması ve yorumu hakkında bilgiler verilmiştir. Kullanılan veri seti içinde, bütün veri yapısın izah edebilecek daha az sayıda bileşene indirgemek için temel bileşen sayısına karar verme yöntemlerinden birkaçı değerlendirilmiştir. Bu yöntemlere göre ilk 9 temel bileşenin bütün yapının varyansını açıklamaya yeterli olduğu düşünülürse bu durumda %20,79 oranında bir varyans kaybı ile 20 temel bileşen yerine 9 temel bileşen ile açıklamanın yeterli olduğu düşünülmektedir.

Multi-scale superpatch matching using dual superpixel descriptors

Over-segmentation into superpixels is a very effective dimensionality reduction strategy, enabling fast dense image processing. The main issue of this approach is the inherent irregularity of the image decomposition compared to standard hierarchical multi-resolution schemes, especially when searching for similar neighboring patterns. Several works have attended to overcome this issue by taking into account the region irregularity into their comparison model. Nevertheless, they remain sub-optimal to provide robust and accurate superpixel neighborhood descriptors, since they only compute features within each region, poorly capturing contour information at superpixel borders. In this work, we address these limitations by introducing the dual superpatch, a novel superpixel neighborhood descriptor. This structure contains features computed in reduced superpixel regions, as well as at the interfaces of multiple superpixels to explicitly capture contour structure information. A fast multi-scale non-local matching framework is also introduced for the search of similar descriptors at different resolution levels in an image dataset. The proposed dual superpatch enables to more accurately capture similar structured patterns at different scales, and we demonstrate the robustness and performance of this new strategy on matching and supervised labeling applications.

Hill’s equation, tire tracks and rolling cones

Louis Poinsot has shown in 1854 that the motion of a rigid body, with one of its points fixed, can be described as the rolling without slipping of one cone, the ‘body cone’, along another, the ‘space cone’, with their common vertex at the fixed point. This description has been further refined by the second author in 1996, relating the geodesic curvatures of the spherical curves formed by intersecting the cones with the unit sphere in Euclidean , thus enabling a reconstruction of the motion of the body from knowledge of the space cone together with the (time dependent) magnitude of the angular velocity vector. In this article we show that a similar description exists for a time dependent family of unimodular matrices in terms of rolling cones in 3-dimensional Minkowski space and the associated ‘pseudo spherical’ curves, in either the hyperbolic plane H2 or its Lorentzian analog H1,1. In particular, this yields an apparently new geometric interpretation of Schrödinger’s (or Hill’s) equation in terms of rolling without slipping of curves in the hyperbolic plane.

Etymologization as a Case of Pedagogical Lying in Plato

In the Cratylus, Plato criticizes the traditional rendering of Hades’ name as the ‘in-visible’ while in the Phaedo he endorses it. Despite this conflict, in both cases, the etymologies are used to oppose the negative characterization of this god by the tradition, just as prescribed in the Republic. Furthermore, both dialogues convey a similar description of Hades as an intellectual realm. Thus, there is an underlying conceptual coherence and a use of conflicting etymologies serving the same practical prescription. This article will verify if this scenario constitutes an instance of the serviceable lies presented in the Republic. Taking Hades’ different etymologizations as a case study, we will be able to better understand the justification for the pedagogical use of lies based on the complex interaction between souls with true and false beliefs. Two types of pedagogical lies emerge. Syrup lies characterize situations in which some true information is conveyed through an illegitimate but attractive cover such as etymologization or tales. In this way, they can capture the attention of souls who are hostage to false beliefs. Moreover, there is also the case for vaccine lies in which the illegitimate method used to convey some information has in itself a self-eroding element. Thus, those who receive the information are also encouraged to question the method in due course. After these determinations, it will be possible to evaluate how such a conception of lying scores morally.

DeeplyTough: Learning Structural Comparison of Protein Binding Sites.

Protein pocket matching, or binding site comparison, is of importance in drug discovery. Identification of similar binding pockets can help guide efforts for hit-finding, understanding polypharmacology, and characterization of protein function. The design of pocket matching methods has traditionally involved much intuition and has employed a broad variety of algorithms and representations of the input protein structures. We regard the high heterogeneity of past work and the recent availability of large-scale benchmarks as an indicator that a data-driven approach may provide a new perspective. We propose DeeplyTough, a convolutional neural network that encodes a three-dimensional representation of protein pockets into descriptor vectors that may be compared efficiently in an alignment-free manner by computing pairwise Euclidean distances. The network is trained with supervision (i) to provide similar pockets with similar descriptors, (ii) to separate the descriptors of dissimilar pockets by a minimum margin, and (iii) to achieve robustness to nuisance variations. We evaluate our method using three large-scale benchmark datasets, on which it demonstrates excellent performance for held-out data coming from the training distribution and competitive performance when the trained network is required to generalize to datasets constructed independently. DeeplyTough is available at https://github.com/BenevolentAI/DeeplyTough.

New Insights About Aromaticity using Molecular Polarization, Molecular Quantum Similarity and Chemical Reactivity Descriptors Supported in the Density Functional Theory

New Insights About Aromaticity using Molecular Polarization, Molecular Quantum Similarity and Chemical Reactivity Descriptors Supported in the Density Functional Theory

Conduction modeling of multi-track raster scanning of heat over a rectangular surface region

An analytical conduction model is implemented for the multi-track raster scanning of a heat spot over sequential neighboring tracks upon a half-space surface, focusing on maximum temperature rise as a function of subsurface position as its primary example of a thermal response of interest, with simple rectangular surface regions scanned and the non-dimensionalization of the analysis (to heat spot size and power as well as half-space thermal properties) intended to broaden applicability of model output. As baseline, first the case of isolated single passes is studied, as would also approximate cases of long times between sequential passes, with no heating from a prior pass available to affect that during a following pass. Asymptotic behavior is found describing all slow scanning speed conditions as described by low Peclet number Pe ≤ 0.1, where isotherms of maximum temperature rise may be plotted as a function of position through the subsurface cross-section. Similar description for fast-scanning high Peclet conditions Pe ≥ 40 is also achieved, although temperature rise and depth must both additionally be multiplied by Pe before attaining isotherms asymptotically pertinent for all high Pe. Such high Pe cases are those for which the effect of shorter finite times between neighboring passes is further studied here, since for any given practical stroke length the correspondingly higher scanning speed results in reduced time between passes and thus more opportunity for a heat accumulation effect. Indeed, at a fixed Pe, for a given point within the body cross-section located in proximity to a track several passes into the region being scanned, its temperature rise is greater than for a single isolated pass, and that temperature rise increases further with decreasing time between neighboring passes, as would result from a decreased period of the cyclic scanning motion. This heat accumulation effect builds for passes further into the rectangular surface region from the first track scanned at the region’s edge, and stabilizes after some number of tracks in, a number found to decrease with increased track spacing. Likewise, if instead holding scanning period and in turn time between passes constant, maximum temperature rises at any given position are also found to increase with decreasing Pe, when maximum temperature rise and depth position are expressed in their modified high Peclet asymptotic forms as multiplied by Pe. The analysis further suggests that if maximum temperature rises and depths are both expressed in such modified forms, any further effect of Peclet number may instead be combined with that of non-dimensionalized scanning period as a function only of their product L* = Peτ*, the non-dimensional track length. Finally, while maximum temperature rise behavior around the mid-stroke location will be similar regardless of whether scanning is via back&forth or one-way pass motions and furthermore in one-way motions these maximum temperature rises will remain fairly uniform with position along the track length as each possesses the same elapsed time since proximity during the previous adjacent pass, in back&forth motion the time since proximity during the previous pass before turn-around and in turn maximum temperature rise will instead vary with position along the track.

Physical activity types among US adults with mobility disability, Behavioral Risk Factor Surveillance System, 2017

BackgroundThe Physical Activity Guidelines for Americans, second edition, recommend that all adults participate in moderate-intensity equivalent aerobic physical activity at least 150–300 min/week for substantial health benefits and muscle-strengthening activities involving all major muscle groups 2 or more days a week. The prevalence of the general population meeting the Guidelines and the types of physical activity in which they engage have been described elsewhere. Similar descriptions are lacking for individuals with mobility disability whose physical activity profiles may differ from the general population. ObjectiveThis study examined patterns of aerobic and muscle-strengthening physical activity among US adults with mobility disability. MethodsWe used 2017 Behavioral Risk Factor Surveillance System data from 66,635 adults with mobility disability. We estimated the percentage who engaged in any aerobic physical activity, met the aerobic and/or muscle-strengthening guidelines, and who participated in specific activities. ResultsLess than half (45.2%) of US adults with mobility disability reported engaging in aerobic physical activity, and 39.5% met one or both components of the physical activity guidelines. Walking was the most commonly reported activity type (34.0%). ConclusionsWalking is a common activity type among adults with mobility disability. Efforts to make walking or wheelchair rolling a safe, viable option are important to helping decrease barriers that may limit the ability of those with mobility disability to engage in walking or other physical activity types.

Sensory Lexicons and Formation Pathways of Off-Aromas in Dairy Ingredients: A Review.

Consumers are becoming increasingly aware of the health benefits of dairy ingredients. However, products fortified with dairy proteins are experiencing considerable aroma challenges. Practices to improve the flavor quality of dairy proteins require a comprehensive understanding of the nature and origins of off-aroma. Unfortunately, existing information from the literature is fragmentary. This review presents sensory lexicons and chemical structures of off-aromas from major dairy ingredients, and it explores their possible precursors and formation mechanisms. It was found that similar chemical structures often contributed to similar off-aroma descriptors. Lipid degradation and Maillard reaction are two primary pathways that commonly cause aroma dissatisfaction. Traditional and novel flavor chemistry tools are usually adopted for off-aroma measurements in dairy ingredients. Strategies for improving aroma quality in dairy derived products include carefully selecting starting materials for formulations, and actively monitoring and optimizing processing and storage conditions.

Liquid–Liquid Equilibrium for the Ternary Systems Water + 1-Butanol + 1-Hexanol or 1-Octanol at 303.15, 313.15, and 323.15 K

Liquid–liquid equilibrium data (LLE) of ternary systems {water + 1-butanol + 1-hexanol} and {water + 1-butanol + 1-octanol} were investigated at 303.15, 313.15, and 323.15 K at 101.3 kPa. The distribution coefficient (D) and selectivity factor (S) were calculated from experimental LLE data. Meanwhile, the effect of temperature on the two-phase zone of the two systems was discussed. The nonrandom two liquid and universal quasi-chemical activity coefficient models were used to regress experimental data sets and generate the relevant binary interaction parameters. Both thermodynamic models provided similar good descriptions for the studied systems with root mean square deviations between the calculated and experimental values less than 0.3%.

N-короны в разбиениях тора на множества ограниченного остатка

Теория геометрических подстановок Арно-Ито позволяет строить последовательности обобщенных перекладывающихся разбиений d-мерного тора. Эти разбиения состоят из параллелепипедов d + 1 типа, а действие некоторого сдвига тора на разбиении сводится к перекладыванию d+1 центрального параллелепипеда. Более того, множество вершин всех параллелепипедов разбиения представляет собой фрагмент орбиты нуля относительно этого сдвига тора. Рассматриваемые разбиения активно используются в различных задачах теории чисел, комбинаторики и теории динамических систем. В настоящей работе изучается локальная структура разбиений тора, получаемых на основе геометрических подстановок. n-короной параллелепипеда называется множество всех параллелепипедов, отстоящих от данного на расстояние не более n в естественной метрике разбиения. Задача состоит в описании всех возможных типов n-корон. Каждому параллелепипеду разбиения естественным образом присваивается номер – его номер в орбите соответствующего центрального параллелепипеда относительно сдвига тора. Доказано, что множество всех номеров распадается на конечное число полуинтервалов, определяющих возможные типы n-корон. Более того, доказано, что границы соответствующих полуинтервалов определяются номерами параллелепипедов, входящих в n-корону набора из d + 1 центрального параллелепипеда. Показано, что этот результат можно рассматривать как некоторое многомерное обобщение знаменитой теоремы о трех длинах. Ранее аналогичное описание было получено для 1-корон разбиений тора получаемых при помощи одной конкретной геометрической подстановки: подстановки Рози. Кроме того, аналогичные результаты ранее были получены для ряда квазипериодических разбиений плоскости. В заключении сформулирован ряд направлений для дальнейшего исследования.

Computational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical map

Progress in olfactory research is currently hampered by incomplete knowledge about chemical receptive ranges of primary receptors. Moreover, the chemical logic underlying the arrangement of computational units in the olfactory bulb has still not been resolved. We undertook a large-scale approach at characterising molecular receptive ranges (MRRs) of glomeruli in the dorsal olfactory bulb (dOB) innervated by the MOR18-2 olfactory receptor, also known as Olfr78, with human ortholog OR51E2. Guided by an iterative approach that combined biological screening and machine learning, we selected 214 odorants to characterise the response of MOR18-2 and its neighbouring glomeruli. We found that a combination of conventional physico-chemical and vibrational molecular descriptors performed best in predicting glomerular responses using nonlinear Support-Vector Regression. We also discovered several previously unknown odorants activating MOR18-2 glomeruli, and obtained detailed MRRs of MOR18-2 glomeruli and their neighbours. Our results confirm earlier findings that demonstrated tunotopy, that is, glomeruli with similar tuning curves tend to be located in spatial proximity in the dOB. In addition, our results indicate chemotopy, that is, a preference for glomeruli with similar physico-chemical MRR descriptions being located in spatial proximity. Together, these findings suggest the existence of a partial chemical map underlying glomerular arrangement in the dOB. Our methodology that combines machine learning and physiological measurements lights the way towards future high-throughput studies to deorphanise and characterise structure-activity relationships in olfaction.

A Local-to-Global Metric Learning Framework From the Geometric Insight

Metric plays a key role in the description of similarity between samples. An appropriate metric for data can well represent their distribution and further promote the performance of learning tasks. In this paper, to better describe the heterogeneous distributions of data, we propose a semi-supervised local-to-global metric learning framework from the geometric insight. Our contributions can be summarized as: Firstly, to enlarge the application scope of local metric learning, we introduce the unsupervised information as the regularization term into our smoothly glued nonlinear metric model. Secondly, we propose two different nonlinear semi-supervised metric learning models with two different loss terms, and find that the smooth loss performs better than the hinge loss by comparison results. Thirdly, we have established not only two metric learning models, but also a nonlinear metric learning framework based on local metrics, which includes supervised and semi-supervised as well as linear and nonlinear metric learning. Moreover, we present an intrinsic steepest descent algorithm on the positive definite manifold for implementation of our semi-supervised nonlinear metric learning models with smooth triplet constrain loss. Finally, we compare our approaches with several state-of-the-art methods on a variety of datasets. The results validate that the robustness and accuracy of classification are both improved under our metrics.

A Solution of the Two-Capacitor Problem Through its Similarity to Single-Electron Electronics

The purpose of this paper is to investigate the two-capacitor paradox using circuit models developed in the analysis of circuits that include nanoelectronic single-electron tunneling devices. The two-capacitor paradox, in which it seems that energy is not conserved in a simple circuit consisting of two capacitors in parallel separated by an ideal switch, is resolved by applying linear circuit theory utilizing a current—described by a (Dirac) delta function—and stepping voltages across all three elements. Based on a similar description, successfully used for tunneling of electrons through metal junctions in nanoelectronics, the switch is modeled as a device across which—upon closing—the voltage steps down while the current through it is an impulse. The model distinguishes three intervals in describing the ideal switch: t 0. As a consequence, the ideal switch dissipates energy during the switching action at t = 0 in zero time. Although the solution of the two-capacitor problem looks like a theoretical curiosity, the application of nanoelectronic concepts allow a physical explanation based on electron tunneling; it shows that the ideal switch is best described by the tunneling of many electrons. In such a context, some of those electrons loose energy and the v-i characteristic shows Ohm’s law.

Conserved Immunoglobulin Domain Similarities of Higher Plant Proteins

The traces of immunoglobulin domain similarities were searched in sequences of higher plants using bioinformatic tools to look for possible early phylogenic structural relationships. 280 thousand sequence IDs, obtained by sixteen types of primary BLAST searches, were differently processed by seventeen selection procedures and an anti-redundant sequence-related approach using JavaScript, PHP, Windows programs and conserved domain searches by means CDD. The resulting seventeen sets of records describing conserved domain similarities of 1323 different sequence IDs yielded a set of next generation (final set) comprising forty-nine records containing superior (“non-refutable”) conserved immunoglobulin domain similarities. The selected sets and their subsets were mapped and subsequently statistically compared with respect to immunoglobulin-related as well as other reciprocal domain linkages. The list of frequently occurring conserved domain similarities concerned first of all domains important for plant and metazoan immunity, e.g. tyrosine kinases accompanying variable immunoglobulin domains in early Metazoa, toll-like receptors, lectin and leucine-rich repeat domains. Detailed description of immunoglobulin domain similarities occurring in the final set was completed by fold analysis of the restricted segments. The data were then discussed with respect to i) immunoglobulin fold evolution, ii) possible structural importance of domains cd14066 (IRAK) and PLN00113 (LRR-associated kinase) for deep evolution of catalytic serine/threonine/tyrosine kinase domains, iii) interatomic, structural and specificity standpoints and iv) traces of antibody-like phosphorylation sites described in our previous paper.

An Alignment-Independent Platform for Allergenicity Prediction.

A great number of novel proteins have been generated from new sources and genetically modified foods during the last decade. As the allergenicity of these proteins is of particular importance for their safe usage, fast and reliable screening strategies for allergenicity assessment are required. The WHO/FAO guidance directs to structural similarities between the novel proteins and known allergens detected by sequence alignment. However, the allergic response involves conformational IgE epitopes that are undetectable by sequence alignment. Here, we present a protocol for allergenicity prediction based on a platform of three alignment-independent servers developed in our lab: AllerTOP v.1, AllerTOP v.2, and AllergenFP. The servers use similar datasets but different chemical descriptors and methods to derive models for allergenicity prediction. The platform is freely accessible and user-friendly. The protocol is demonstrated stepwise on a randomly chosen query protein.