Готові списки джерел за темами / MULTIFARIOUS FEATURES

Добірка наукової літератури з теми "MULTIFARIOUS FEATURES"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "MULTIFARIOUS FEATURES"

Fu, H. M., Hai Feng Zhang, H. Wang, Ming Xing Zhang, and Zhuang Qi Hu. "Multifarious Fracture Features of CuZrAlGd(Ag) Bulk Metallic Glasses." Advanced Materials Research 29-30 (November 2007): 47–50. http://dx.doi.org/10.4028/www.scientific.net/amr.29-30.47.

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Multifarious fracture features, such as coarse rive-like, micro holes, rugged and flat fracture surface, were systematically investigated in the monolithic Cu46-xZr45Al7Gd2Agx (x=0, 0.5) bulk metallic glasses. The fracture planes presented different angles with the loading direction. These fracture features were completely different from the typical fracture characteristics of amorphous alloys, i.e. vein-pattern and fracturing approximately along the maximum shear stress plane. On the other hand, some tiny strips with about 50 nm intervals were also detected on the flat fracture plane. The preliminary discussions on the formation mechanisms of these exceptional features were presented.

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Vaijayanthimala, J., and T. Padma. "Synthesis Score Level Fusion Based Multifarious Classifier for Multi-Biometrics Applications." Journal of Medical Imaging and Health Informatics 9, no. 8 (October 1, 2019): 1673–80. http://dx.doi.org/10.1166/jmihi.2019.2762.

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In this paper, we are presenting a face and signature recognition method from a large dataset with the different pose and multiple features. Initially, Face and corresponding signature are detected from devices for further pre-processing. Face recognition is the first stage of a system then the signature verification will be done. The proposed Legion feature based verification method will be developed using four important steps like, (i) feature extraction from face and data glove signals using feature Extraction. The various Features like Local binary pattern, shape and geometrical features of face, then the global and local features of the signatures were extracted. (ii) Score match normalization is used to enhance the recognition accuracy using min–max and median estimations. (iii) Then the match scores are evaluated using synthesis score level fusion based feature matching through Euclidean distance, (iv) Recognition based on the final score. Finally based on the feature library the face image and signature can be recognized. The similarity measurement is done by using Synthesis score level fusion (SSF) based multifarious Neural network (MNN) Classifier with weighted summation formulae where two weights will be optimally found out using Adapted motion search optimization algorithm. Finally SSF-MNN based matching score fusion based decision classifier to determine recognized and non-recognized biometrics. Moreover, in comparative analysis, a proposed technique is compared with the existing method by several performance metrics and the proposed SSF-MNN technique efficiently recognize the face images and corresponding signature from the input databases than the existing technique.

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Xu, Pengcheng, Zhongyuan Guo, Lei Liang, and Xiaohang Xu. "MSF-Net: Multi-Scale Feature Learning Network for Classification of Surface Defects of Multifarious Sizes." Sensors 21, no. 15 (July 29, 2021): 5125. http://dx.doi.org/10.3390/s21155125.

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In the field of surface defect detection, the scale difference of product surface defects is often huge. The existing defect detection methods based on Convolutional Neural Networks (CNNs) are more inclined to express macro and abstract features, and the ability to express local and small defects is insufficient, resulting in an imbalance of feature expression capabilities. In this paper, a Multi-Scale Feature Learning Network (MSF-Net) based on Dual Module Feature (DMF) extractor is proposed. DMF extractor is mainly composed of optimized Concatenated Rectified Linear Units (CReLUs) and optimized Inception feature extraction modules, which increases the diversity of feature receptive fields while reducing the amount of calculation; the feature maps of the middle layer with different sizes of receptive fields are merged to increase the richness of the receptive fields of the last layer of feature maps; the residual shortcut connections, batch normalization layer and average pooling layer are used to replace the fully connected layer to improve training efficiency, and make the multi-scale feature learning ability more balanced at the same time. Two representative multi-scale defect data sets are used for experiments, and the experimental results verify the advancement and effectiveness of the proposed MSF-Net in the detection of surface defects with multi-scale features.

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Hameed, Abdul Zubar, Sakthivel Aravind Raj, Jayakrishna Kandasamy, Majed Abubakr Baghdadi, and Muhammad Atif Shahzad. "Chitosan: A Sustainable Material for Multifarious Applications." Polymers 14, no. 12 (June 9, 2022): 2335. http://dx.doi.org/10.3390/polym14122335.

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Due to the versatility of its features and capabilities, chitosan generated from marine crustacean waste is gaining importance and appeal in a wide variety of applications. It was initially used in pharmaceutical and medical applications due to its antibacterial, biocompatible, and biodegradable properties. However, as the demand for innovative materials with environmentally benign properties has increased, the application range of chitosan has expanded, and it is now used in a variety of everyday applications. The most exciting aspect of the chitosan is its bactericidal properties against pathogens, which are prevalent in contaminated water and cause a variety of human ailments. Apart from antimicrobial and water filtration applications, chitosan is used in dentistry, in water filtration membranes to remove metal ions and some heavy metals from industrial effluents, in microbial fuel cell membranes, and in agriculture to maintain moisture in fruits and leaves. It is also used in skin care products and cosmetics as a moisturizer, in conjunction with fertilizer to boost plant immunity, and as a bi-adhesive for bonding woods and metals. As it has the capacity to increase the life span of food items and raw meat, it is an unavoidable component in food packing and preservation. The numerous applications of chitosan are reviewed in this brief study, as well as the approaches used to incorporate chitosan alongside traditional materials and its effect on the outputs.

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AYUNTS, Anoush. "APPLYING CONTRASTIVE ANALYSIS FOR ELUCIDATING CERTAIN FEATURES OF CULTURAL FOREIGN WORDS." Foreign Languages in Higher Education 20, no. 1-2 (20) (February 28, 2022): 3–9. http://dx.doi.org/10.46991/flhe/2016.20.1-2.003.

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Understanding verbal art is a complicated and multifarious phenomenon. The present paper is devoted to the study of some problems related to certain cases of using cultural foreign words, which are revealed due to the application of the contrastive method of analysis. By the application of the method of linguopoetic confrontation of the original and the translated versions of a work of verbal art an attempt is made to identify transliterations of cultural foreign words not having their equivalents in English or French cultures. The usage of cultural foreign words in a work of fiction ensures a global aesthetic impact on the reader.

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Cosner, Shelby, Lisa Walker, Jason Swanson, Martha Hebert, and Samuel P. Whalen. "Examining the architecture of leadership coaching." Journal of Educational Administration 56, no. 3 (May 9, 2018): 364–80. http://dx.doi.org/10.1108/jea-05-2017-0049.

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Purpose The purpose of this paper is to identify the coaching structures that aspiring principals associate with developmentally consequential coaching interactions; identify structural features/functions/attributes that shape a structure’s developmental utility and use; and consider how a multifarious coaching structure might advantage the learning experiences of aspiring principals. Design/methodology/approach This qualitative study included multiple interviews with two cohorts of aspiring principals (n=20) from one preparation program and with their leadership coaches (n=5) and was framed using the theories of social capital and networks, situated learning, and distributed cognition. Findings The authors identified eight coaching structures that aspirants identified as consequential to their learning and development. The authors identified four structural features/functions/attributes that shape a structure’s developmental utility. The authors identified three factors that contribute to the developmental utility of this multifarious coaching model. Research limitations/implications This study includes a relatively small participant sample –70 percent of the aspiring principals from two cohorts within one preparation program. Data do not include direct observations of coaching interactions within the context of individual coaching structures. Practical implications The findings suggest that the structuring of leadership coaching is a critical consideration for those designing leadership coaching programs. This multifarious structuring of leadership coaching created three developmental affordances. Originality/value This paper generates new knowledge for the field of principal preparation related to the structuring of leadership coaching and ways in which structuring can shape aspirant learning experiences. These findings are likely to also be instructive to those interested in coaching more generally.

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Lu, Yong-Heng, Yao Wang, Feng Mei, Yi-Jun Chang, Hang Zheng, Suotang Jia, and Xian-Min Jin. "Observing multifarious topological phase transitions with real-space indicator." Nanophotonics 11, no. 1 (November 26, 2021): 153–60. http://dx.doi.org/10.1515/nanoph-2021-0559.

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Abstract First- and second-order topological phases, capable of inherent protection against disorder of materials, have been recently experimentally demonstrated in various artificial materials through observing the topologically protected edge states. Topological phase transition represents a new class of quantum critical phenomena, which is accompanied by the changes related to the bulk topology of energy band structures instead of symmetry. However, it is still a challenge to directly observe the topological phase transitions defined in terms of bulk states. Here, we theoretically and experimentally demonstrate the direct observation of multifarious topological phase transitions with real-space indicator in a single photonic chip, which is formed by integration of 324 × 33 waveguides supporting both first- and second-order topological phases. The trivial-to-first-order, trivial-to-second-order and first-to-second-order topological phase transitions signified by the band gap closure can all be directly detected via photon evolution in the bulk. We further observe the creation and destruction of gapped topological edge states associated with these topological phase transitions. The bulk-state-based route to investigate the high-dimensional and high-order topological features, together with the platform of freely engineering topological materials by three-dimensional laser direct writing in a single photonic chip, opens up a new avenue to explore the mechanisms and applications of artificial devices.

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Kant, Chandra, and G. A. Harmain. "A Model Based Study of Fatigue Life Prediction for Multifarious Loadings." Key Engineering Materials 882 (April 2021): 296–327. http://dx.doi.org/10.4028/www.scientific.net/kem.882.296.

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Loading history makes fatigue crack propagation modelling complex. This article focus on life prediction models which take into consideration the variability of fluctuating loads. In particular it emphases on the comparative studies of prediction models involving the significance of one model’s over another. The paper studies models based on multifarious loadings (constant amplitude load, variable amplitude load, overload/underload etc.). The major parameters of load interaction modelling are plasticity, crack closure, effective stress intensity, effective stress ratio and damage accumulation. For large deformation, elasto-plastic fracture mechanics based models are also included. The complexity of models, their features and focusing on their limitation and strengths are stated with various conditions and also validation of models with experimental data are reported. The paper speculates on the directions the study of crack propagation will take in future.

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Verma, Shyam B., Saumya Panda, Pietro Nenoff, Archana Singal, Shivprakash M. Rudramuruthy, Silke Uhrlass, Anupam Das, Kavita Bisherwal, Dipika Shaw, and Resham Vasani. "The unprecedented epidemic-like scenario of dermatophytosis in India: I. Epidemiology, risk factors and clinical features." Indian Journal of Dermatology, Venereology and Leprology 87 (March 23, 2021): 154–75. http://dx.doi.org/10.25259/ijdvl_301_20.

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Dermatophytosis has attained unprecedented dimensions in recent years in India. Its clinical presentation is now multifarious, often with atypical morphology, severe forms and unusually extensive disease in all age groups. We hesitate to call it an epidemic owing to the lack of population-based prevalence surveys. In this part of the review, we discuss the epidemiology and clinical features of this contemporary problem. While the epidemiology is marked by a stark increase in the number of chronic, relapsing and recurrent cases, the clinical distribution is marked by a disproportionate rise in the number of cases with tinea corporis and cruris, cases presenting with the involvement of extensive areas, and tinea faciei.

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Datta, Sougata, and Santanu Bhattacharya. "Multifarious facets of sugar-derived molecular gels: molecular features, mechanisms of self-assembly and emerging applications." Chemical Society Reviews 44, no. 15 (2015): 5596–637. http://dx.doi.org/10.1039/c5cs00093a.

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Дисертації з теми "MULTIFARIOUS FEATURES"

GUPTA, KHUSHBU. "FACE DETECTION AND TRACKING USING IMPROVED CAMSHIFT." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14452.

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This paper addresses face Detection and multifarious tracking using improved CamShift and texture algorithm. Face is detected by calculating texture information. And Object’s motion is taken into account through location and trajectory. Camshift is used to follow trajectory of the object. The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking. It is a well-established and fundamental algorithm for kernel-based visual object tracking. It adjusts Search window itself in size. It will adjust itself for the size of face as the person moves closer or further from camera. And local binary pattern (LBP) technique is used to extract the texture features. LBP is a non-parametric kernel which summarizes the local spatial structure of an image and it is invariant to monotonic gray-scale transformations and rotation.

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Частини книг з теми "MULTIFARIOUS FEATURES"

Fu, H. M., H. F. Zhang, H. Wang, Ming Xing Zhang, and Zhuang Qi Hu. "Multifarious Fracture Features of CuZrAlGd(Ag) Bulk Metallic Glasses." In Advanced Materials and Processing IV, 47–50. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-466-9.47.

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Özbal, Rana, and Fokke Gerritsen. "Barcın Höyük in Interregional Perspective: An Initial Assessment." In Concluding the Neolithic, 287–305. Lockwood Press, 2019. http://dx.doi.org/10.5913/87913.cn.13.

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Using Barcın Höyük (Bursa province, Turkey), a Late Neolithic settlement that spans six centuries from 6600–6000 BC, as the main case-study, this chapter addresses questions of the northwestern spread of Neolithic communities from the mid-seventh millennium onwards. Presented here is the idea that the inhabitants that settled Barcın Höyük in the earliest levels of habitation were migrant pioneers, although it is too early to be certain about their point of origin. We compare the multifarious lines of data regarding architectural features, faunal data, and pottery styles known from Barcın Höyük to assess the similarities and differences with other published sites. However, rather than providing clarity on these issues, this first assessment mainly aims to draw attention to some parallel developments. Overall, this initial analysis does suggest that within a few centuries of their arrival, the inhabitants of Barcın Höyük participated in multiple spheres of interaction and exchange of knowledge, practices, and ideas.

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Patel, Dimple, and Deepti Thakur. "Managing Open Access (OA) Scholarly Information Resources in a University." In Scholarly Communication and the Publish or Perish Pressures of Academia, 224–55. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1697-2.ch011.

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Open Access (OA) to scholarly information has now become a reality. Due to the efforts of OA supporters worldwide now even commercial publishers have started supporting open access to their content through various open access models. Many public institutions like universities and R&D Labs have realized the importance of OA in developing the society in general. As a result, these institutions have come up with OA repositories, archives and libraries. As with any such proliferation of information, OA resources have increased manifold and can easily overwhelm even an experienced user. Also different repositories may use various digital library software, which presents the problem of multifarious search interfaces and features. The solution can be found in the open community of open source software and open standards. The open source metadata harvesting software PKP-OHS and the open protocol for metadata harvesting i.e. OAI-PMH come to the rescue. This chapter discusses how PKP-OHS was implemented as a pilot study at the Central University of Himachal Pradesh (CUHP).

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Patel, Dimple, and Deepti Thakur. "Managing Open Access (OA) Scholarly Information Resources in a University." In Digital Libraries and Institutional Repositories, 474–99. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2463-3.ch029.

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Kalyani, Palanichamy, Thakku Rangachari Banuprabha, Chinnamayan Sudharsana, and Nazim Anvarsha. "Phytomass-Derived Multifunctional Activated Carbon as a “Wonder-Material”: A Paradigm Shift of Filth-to-Wealth." In Current Topics in Recycling [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.99448.

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Activated carbon (AC) is a wonder-material that finds multifarious applications such as catalytic supports, removal of pollutants, electrodes in energy gadgets, gas storage etc. Surface area, chemical constituents and pore structures are a few traits required in the ACs which largely depend on the source of the precursors and processing methodologies adopted. In this context, the idea of recycling phytomass for producing ACs has attracted researchers seeing that the inexpensive and renewable nature of the phytomass can reduce the overall cost of producing ACs with diversified features and that it does not add CO2 to the atmosphere leading to global warming (plants release only the same amount of CO2 as they consumed while growing). Further, phytomass after their life possess no value but their conversion into ACs would be an economically profitable option leading to inexpensive ACs. As a consequent of these advantages this chapter has been planned and designed to provide certain interesting multifunctional aspects of low-cost phytomass derived ACs. The chapter is expected to provide research insights oriented towards identification of unexplored phytomass or wastes which could lead to carbon with novel properties tunable to the applications. Filth-to-wealth or in other words, recycling of wastes provides a strategy categorized under circular-bioeconomy, which is the want of the hour.

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Villas-Boas, Mauro, and Ana Sepulveda De Rezende. "Exploring Structural, Functional, and Kinetic Aspects of Nucleic Acid–Protein Complexes with Pressure: Nucleosomes and RNA Polymerase." In High Pressure Effects in Molecular Biophysics and Enzymology. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195097221.003.0012.

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High pressure has provided us with new insights into two complex DNA-protein systems: nucleosomes and RNA polymerase. In spite of their complexity, we can derive new and useful information about them by coupling high pressure with a variety of other physical techniques and functional assays. These studies have shown clearly that multiple conformations of these large–molecular weight DNA-protein assemblies are present simultaneously in solution, although both molecular assemblies are generally considered to be single structures in most in vitro experiments. Considering the variety of different cellular situations encountered by nucleosomes and RNA polymerases, it is perhaps to be expected that evolution would select structures with flexible and multifarious conformations that possesses sufficient stability, rather than static, rigid, singular, and highly stable structures. The molecular organization in the nucleus of a biological cell is extensive and involves intricate protein-protein and protein–nucleic acid interactions that are changing continually during the cell cycle. These dynamic activities in the nucleus are tightly coordinated with many extranuclear events throughout the cell. Highly organized molecular complexes involving multisubunit proteins (and higher order protein assemblies) interacting with the nucleic acid components are the rule rather than the exception in the nucleus (Alberts et al., 1983; Darnell et al., 1990; Lewin, 1994). For instance, chromosomes are organized in a structural hierarchy culminating in the metaphase state in which they are packed tightly together with proteins in a highly specific and economical manner that still largely eludes our understanding; the DNA of a eukaryotic cell is replicated with the help of a complex assembly of proteins; and information coded within the DNA sequence is transcribed with the assistance of multisubunit DNA-binding proteins, some acting as enzymes and others serving mainly as organizational and structural assistants to the catalytic process. Many important features of protein-nucleic acid (DNA and RNA) interactions have been elucidated in the last decade (Pabo & Sauer, 1992; Steitz, 1990), and exciting results have been obtained for singleprotein molecules and dimers binding to DNA. Although we are a long way from understanding these interactions completely, enough aspects are known so that structural predictions are sometimes possible simply from the amino acid sequence.

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Player, Mark. "Parallax Historiography and Metareference." In The Moving Form of Film, 47–62. Oxford University Press, 2023. http://dx.doi.org/10.1093/oso/9780197621707.003.0005.

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Abstract This chapter considers the extent to which intermediality can read cinema and its complex media-historical development by applying the concepts of “parallax historiography” and “metareference” to the work of Japanese filmmaker Nagasaki Shun’ichi. Nagasaki’s Heart, Beating in the Dark—New Version (2005) marks a complex return to his seminal Super 8 feature Heart, Beating in the Dark (1982), acting as a sequel to and remake of the original, while also documenting its own production via fictionalised “behind-the-scenes” sequences. By using conceptual tools that self-reflexively address film’s past and present specificities, this chapter demonstrates how Heart, Beating in the Dark—New Version not only fulfils intermediality’s political potential by abolishing “the schism between art and life” but also conjures a peculiar kind of “intramediality,” absorbed by its own media archaeology, legacy, and specificities. As such, multifarious passages open up between the real and fictional histories of Nagasaki’s Heart, Beating in the Dark diptych, which are presented in blurred parallel.

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Тези доповідей конференцій з теми "MULTIFARIOUS FEATURES"

Zhao, Chengshuai, Shuai Liu, Feng Huang, Shichao Liu, and Wen Zhang. "CSGNN: Contrastive Self-Supervised Graph Neural Network for Molecular Interaction Prediction." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/517.

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Molecular interactions are significant resources for analyzing sophisticated biological systems. Identification of multifarious molecular interactions attracts increasing attention in biomedicine, bioinformatics, and human healthcare communities. Recently, a plethora of methods have been proposed to reveal molecular interactions in one specific domain. However, existing methods heavily rely on features or structures involving molecules, which limits the capacity of transferring the models to other tasks. Therefore, generalized models for the multifarious molecular interaction prediction (MIP) are in demand. In this paper, we propose a contrastive self-supervised graph neural network (CSGNN) to predict molecular interactions. CSGNN injects a mix-hop neighborhood aggregator into a graph neural network (GNN) to capture high-order dependency in the molecular interaction networks and leverages a contrastive self-supervised learning task as a regularizer within a multi-task learning paradigm to enhance the generalization ability. Experiments on seven molecular interaction networks show that CSGNN outperforms classic and state-of-the-art models. Comprehensive experiments indicate that the mix-hop aggregator and the self-supervised regularizer can effectively facilitate the link inference in multifarious molecular networks.

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Edara, Deepak Chowdary, Venkataramaphanikumar S, and Venkata Krishna Kishore Kolli. "Deep Sentient network with multifarious features and inter-mutual attention mechanism for target-specific sentiment classification." In 2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). IEEE, 2022. http://dx.doi.org/10.1109/iatmsi56455.2022.10119248.

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Tang, Guozhi, Lele Xie, Lianwen Jin, Jiapeng Wang, Jingdong Chen, Zhen Xu, Qianying Wang, Yaqiang Wu, and Hui Li. "MatchVIE: Exploiting Match Relevancy between Entities for Visual Information Extraction." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/144.

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Visual Information Extraction (VIE) task aims to extract key information from multifarious document images (e.g., invoices and purchase receipts). Most previous methods treat the VIE task simply as a sequence labeling problem or classification problem, which requires models to carefully identify each kind of semantics by introducing multimodal features, such as font, color, layout. But simply introducing multimodal features can't work well when faced with numeric semantic categories or some ambiguous texts. To address this issue, in this paper we propose a novel key-value matching model based on a graph neural network for VIE (MatchVIE). Through key-value matching based on relevancy evaluation, the proposed MatchVIE can bypass the recognitions to various semantics, and simply focuses on the strong relevancy between entities. Besides, we introduce a simple but effective operation, Num2Vec, to tackle the instability of encoded values, which helps model converge more smoothly. Comprehensive experiments demonstrate that the proposed MatchVIE can significantly outperform previous methods. Notably, to the best of our knowledge, MatchVIE may be the first attempt to tackle the VIE task by modeling the relevancy between keys and values and it is a good complement to the existing methods.

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Temel, Dogancan, Jinsol Lee, and Ghassan AlRegib. "Object Recognition Under Multifarious Conditions: A Reliability Analysis and a Feature Similarity-Based Performance Estimation." In 2019 IEEE International Conference on Image Processing (ICIP). IEEE, 2019. http://dx.doi.org/10.1109/icip.2019.8803317.

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Cui, Yuning, Yi Tao, Luoxi Jing, and Alois Knoll. "Strip Attention for Image Restoration." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/72.

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As a long-standing task, image restoration aims to recover the latent sharp image from its degraded counterpart. In recent years, owing to the strong ability of self-attention in capturing long-range dependencies, Transformer based methods have achieved promising performance on multifarious image restoration tasks. However, the canonical self-attention leads to quadratic complexity with respect to input size, hindering its further applications in image restoration. In this paper, we propose a Strip Attention Network (SANet) for image restoration to integrate information in a more efficient and effective manner. Specifically, a strip attention unit is proposed to harvest the contextual information for each pixel from its adjacent pixels in the same row or column. By employing this operation in different directions, each location can perceive information from an expanded region. Furthermore, we apply various receptive fields in different feature groups to enhance representation learning. Incorporating these designs into a U-shaped backbone, our SANet performs favorably against state-of-the-art algorithms on several image restoration tasks. The code is available at https://github.com/c-yn/SANet.

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