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Статті в журналах з теми "Distance-based measure"
Wooil Kim and J. Hansen. "Phonetic Distance Based Confidence Measure." IEEE Signal Processing Letters 17, no. 2 (February 2010): 121–24. http://dx.doi.org/10.1109/lsp.2009.2034551.
Повний текст джерелаSahbudin, Murtadha Arif Bin. "Audio Fingerprint based on Power Spectral Density and Hamming Distance Measure." Journal of Advanced Research in Dynamical and Control Systems 12, no. 04-Special Issue (March 31, 2020): 1533–44. http://dx.doi.org/10.5373/jardcs/v12sp4/20201633.
Повний текст джерелаShen, H. C., C. Y. C. Bie, and D. K. Y. Chiu. "A texture-based distance measure for classification." Pattern Recognition 26, no. 9 (September 1993): 1429–37. http://dx.doi.org/10.1016/0031-3203(93)90148-p.
Повний текст джерелаLiu, Hongbing, Huaping Guo, and Chang-an Wu. "Hyperbox Granular Computing Based on Distance Measure." International Journal of Control and Automation 9, no. 1 (January 31, 2016): 1–10. http://dx.doi.org/10.14257/ijca.2016.9.1.01.
Повний текст джерелаCampana, Bilson J. L., and Eamonn J. Keogh. "A compression-based distance measure for texture." Statistical Analysis and Data Mining 3, no. 6 (October 7, 2010): 381–98. http://dx.doi.org/10.1002/sam.10093.
Повний текст джерелаDeng, Jun, and Qiujun Lu. "Fuzzy Regression Model Based on Fuzzy Distance Measure." Journal of Data Analysis and Information Processing 06, no. 03 (2018): 126–40. http://dx.doi.org/10.4236/jdaip.2018.63008.
Повний текст джерела., S. Selvaraj, and K. Seetharaman. "Color Image Retrieval Based on Chernoff Distance Measure." International Journal of Computer Sciences and Engineering 6, no. 9 (September 30, 2018): 329–33. http://dx.doi.org/10.26438/ijcse/v6i9.329333.
Повний текст джерелаOSARAGI, Toshihiro, and Ayaka MURAKAMI. "DISTANCE MEASURE BASED ON SPATIOTEMPORAL COEXISTENCE OF RESIDENTS." Journal of Architecture and Planning (Transactions of AIJ) 80, no. 715 (2015): 2001–10. http://dx.doi.org/10.3130/aija.80.2001.
Повний текст джерелаTanaka, Katsuyuki, Takuji Kinkyo, and Shigeyuki Hamori. "Asymmetric technological distance measure based on language model." Applied Economics Letters 26, no. 18 (March 2019): 1548–51. http://dx.doi.org/10.1080/13504851.2019.1584364.
Повний текст джерелаChen, Chao, Zhenzhou Lu, and Fei Wang. "New Global Sensitivity Measure Based on Fuzzy Distance." Journal of Engineering Mechanics 143, no. 11 (November 2017): 04017125. http://dx.doi.org/10.1061/(asce)em.1943-7889.0001336.
Повний текст джерелаДисертації з теми "Distance-based measure"
Rogers, Wendy Laurel. "A Mahalanobis-distance-based image segmentation error measure with applications in automated microscopy /." Thesis, McGill University, 1985. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66025.
Повний текст джерелаNordström, Markus. "Automatic Source Code Classification : Classifying Source Code for a Case-Based Reasoning System." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25519.
Повний текст джерелаGashayija, Jean Marie. "Image classification, storage and retrieval system for a 3 u cubesat." Thesis, Cape Peninsula University of Technology, 2014. http://hdl.handle.net/20.500.11838/1189.
Повний текст джерелаSmall satellites, such as CubeSats are mainly utilized for space and earth imaging missions. Imaging CubeSats are equipped with high resolution cameras for the capturing of digital images, as well as mass storage devices for storing the images. The captured images are transmitted to the ground station and subsequently stored in a database. The main problem with stored images in a large image database, identified by researchers and developers within the last number of years, is the retrieval of precise, clear images and overcoming the semantic gap. The semantic gap relates to the lack of correlation between the semantic categories the user requires and the low level features that a content-based image retrieval system offers. Clear images are needed to be usable for applications such as mapping, disaster monitoring and town planning. The main objective of this thesis is the design and development of an image classification, storage and retrieval system for a CubeSat. This system enables efficient classification, storing and retrieval of images that are received on a daily basis from an in-orbit CubeSat. In order to propose such a system, a specific research methodology was chosen and adopted. This entails extensive literature reviews on image classification techniques and image feature extraction techniques, to extract content embedded within an image, and include studies on image database systems, data mining techniques and image retrieval techniques. The literature study led to a requirement analysis followed by the analyses of software development models in order to design the system. The proposed design entails classifying images using content embedded in the image and also extracting image metadata such as date and time. Specific features extraction techniques are needed to extract required content and metadata. In order to achieve extraction of information embedded in the image, colour feature (colour histogram), shape feature (Mathematical Morphology) and texture feature (GLCM) techniques were used. Other major contributions of this project include a graphical user interface which enables users to search for similar images against those stored in the database. An automatic image extractor algorithm was also designed to classify images according to date and time, and colour, texture and shape features extractor techniques were proposed. These ensured that when a user wishes to query the database, the shape objects, colour quantities and contrast contained in an image are extracted and compared to those stored in the database. Implementation and test results concluded that the designed system is able to categorize images automatically and at the same time provide efficient and accurate results. The features extracted for each image depend on colour, shape and texture methods. Optimal values were also incorporated in order to reduce retrieval times. The mathematical morphological technique was used to compute shape objects using erosion and dilation operators, and the co-occurrence matrix was used to compute the texture feature of the image.
Suñé, Socias Víctor Manuel. "Failure distance based bounds of dependability measures." Doctoral thesis, Universitat Politècnica de Catalunya, 2000. http://hdl.handle.net/10803/6375.
Повний текст джерелаEls sistemes considerats a la tesi es conceptualitzen com formats per components (hardware o software) que fallen i, en el cas de sistemes reparables, són reparats. Els components s'agrupen en classes de forma que els components d'una mateixa classe són indistingibles. Per tant, un component és considerat com a una instància d'una classe de components i el sistema inclou un bag de classes de components definit sobre un cert domini. L'estat no fallada/fallada del sistema es determina a partir de l'estat no fallada/fallada dels components mitjançant una funció d'estructura coherent que s'especifica amb un arbre de fallades amb classes d'esdeveniments bàsics. (Una classe d'esdeveniment bàsic és la fallada d'un component d'una classe de components.)
La classe de models basats en CMTC considerada a la tesi és força àmplia i permet, per exemple, de modelar el fet que un component pot tenir diversos modes de fallada. També permet de modelar fallades de cobertura mitjançant la introducció de components ficticis que no fallen per ells mateixos i als quals es propaguen les fallades d'altres components. En el cas de sistemes reparables, la classe de models considerada admet polítiques de reparació complexes (per exemple, nombre limitat de reparadors, prioritats, inhibició de reparació) així com reparació en grup (reparació simultània de diversos components). Tanmateix, no és possible de modelar la reparació diferida (és a dir, el fet de diferir la reparació d'un component fins que una certa condició es compleixi).
A la tesi es consideren dues mesures de confiabilitat: la no fiabilitat en un instant de temps donat en el cas de sistemes no reparables i la no disponibilitat en règim estacionari en el cas sistemes reparables.
Els mètodes de fitació desenvolupats a la tesi es basen en el concepte de "distància a la fallada", que es defineix com el nombre mínim de components que han de fallar a més dels que ja han fallat per fer que el sistema falli.
A la tesi es desenvolupen quatre mètodes de fitació. El primer mètode dóna fites per a la no fiabilitat de sistemes no reparables emprant distàncies a la fallada exactes. Aquestes distàncies es calculen usant el conjunt de talls mínims de la funció d'estructura del sistema. El conjunt de talls mínims s'obté amb un algorisme desenvolupat a la tesi que obté els talls mínims per a arbres de fallades amb classes d'esdeveniments bàsics. El segon mètode dóna fites per a la no fiabilitat usant fites inferiors per a les distàncies a la fallada. Aquestes fites inferiors s'obtenen analitzant l'arbre de fallades del sistema, no requereixen de conèixer el conjunt de talls mínims i el seu càlcul és poc costós. El tercer mètode dóna fites per a la no disponibilitat en règim estacionari de sistemes reparables emprant distàncies a la fallada exactes. El quart mètode dóna fites per a la no disponibilitat en règim estacionari emprant les fites inferiors per a les distàncies a la fallada.
Finalment, s'il·lustren les prestacions de cada mètode usant diversos exemples. La conclusió és que cada un dels mètodes pot funcionar molt millor que altres mètodes prèviament existents i estendre de forma significativa la complexitat de sistemes tolerants a fallades per als quals és possible de calcular fites ajustades per a la no fiabilitat o la no disponibilitat en règim estacionari.
The subject of this dissertation is the development of bounding methods for a class of continuous-time Markov chain (CTMC) dependability models of fault-tolerant systems.
The systems considered in the dissertation are conceptualized as made up of components (hardware or software) that fail and, for repairable systems, are repaired. Components are grouped into classes, the components of the same class being indistinguishable. Thus, a component is regarded as an instance of some component class and the system includes a bag of component classes defined over a certain domain. The up/down state of the system is determined from the unfailed/failed state of the components through a coherent structure function specified by a fault tree with basic event classes. (A basic event class is the failure of a component of a component class.)
The class of CTMC models considered in the dissertation is quite wide and allows, for instance, to model the fact that a component may have different failure modes. It also allows to model coverage failures by means of introducing fictitious components that do not fail by themselves and to which uncovered failures of other components are propagated. In the case of repairable systems, the considered class of models supports very complex repair policies (e.g., limited repairpersons, priorities, repair preemption) as well as group repair (i.e., simultaneous repair of several components). However, deferred repair (i.e., the deferring of repair until some condition is met) is not allowed.
Two dependability measures are considered in the dissertation: the unreliability at a given time epoch for non-repairable systems and the steady-state unavailability for repairable systems.
The bounding methods developed in the dissertation are based on the concept of "failure distance from a state," which is defined as the minimum number of components that have to fail in addition to those already failed to take the system down.
We develop four bounding methods. The first method gives bounds for the unreliability of non-repairable fault-tolerant systems using (exact) failure distances. Those distances are computed using the set of minimal cuts of the structure function of the system. The set of minimal cuts is obtained using an algorithm developed in the dissertation that obtains the minimal cuts for fault trees with basic event classes. The second method gives bounds for the unreliability using easily computable lower bounds for failure distances. Those lower bounds are obtained analyzing the fault tree of the system and do not require the knowledge of the set of minimal cuts. The third method gives bounds for the steady-state unavailability using (exact) failure distances. The fourth method gives bounds for the steady-state unavailability using the lower bounds for failure distances.
Finally, the performance of each method is illustrated by means of several large examples. We conclude that the methods can outperform significantly previously existing methods and extend significantly the complexity of the fault-tolerant systems for which tight bounds for the unreliability or steady-state unavailability can be computed.
Goussakov, Roma. "Hellinger Distance-based Similarity Measures for Recommender Systems." Thesis, Umeå universitet, Statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172385.
Повний текст джерелаDey, Rajarshi. "Inference for the K-sample problem based on precedence probabilities." Diss., Kansas State University, 2011. http://hdl.handle.net/2097/12000.
Повний текст джерелаDepartment of Statistics
Paul I. Nelson
Rank based inference using independent random samples to compare K>1 continuous distributions, called the K-sample problem, based on precedence probabilities is developed and explored. There are many parametric and nonparametric approaches, most dealing with hypothesis testing, to this important, classical problem. Most existing tests are designed to detect differences among the location parameters of different distributions. Best known and most widely used of these is the F- test, which assumes normality. A comparable nonparametric test was developed by Kruskal and Wallis (1952). When dealing with location-scale families of distributions, both of these tests can perform poorly if the differences among the distributions are among their scale parameters and not in their location parameters. Overall, existing tests are not effective in detecting changes in both location and scale. In this dissertation, I propose a new class of rank-based, asymptotically distribution- free tests that are effective in detecting changes in both location and scale based on precedence probabilities. Let X_{i} be a random variable with distribution function F_{i} ; Also, let _pi_ be the set of all permutations of the numbers (1,2,...,K) . Then P(X_{i_{1}}<...
Sooful, Jayren Jugpal. "Automated phoneme mapping for cross-language speech recognition." Diss., Pretoria [s.n.], 2004. http://upetd.up.ac.za/thesis/available/etd-01112005-131128.
Повний текст джерелаLin, Chia-Wen, and 林嘉文. "A Novel Content-Based Image Retrieval System Based on Distance Measure Approach." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/4m2xy9.
Повний текст джерела國立臺中科技大學
資訊工程系碩士班
101
For the last two dacades, content-based image retrieval (CBIR) is a very popular topic in image processing area. Researchers aim to extract features of color, texture, shape or position information from an image and then via a distance measure method, they retrieve images most similar to the query image from a particular image database. A lot of content-based image retrieval methods have been proposed and the performance of each mothod has been demonstrated in each proposed paper. In this paper, we proposed a novel distance meature approach (re-rank,shorted as RRK) for CBIR system. First, we get the retrieved images from our simple CBIR system. Then we used these images to set reference feature. Finally, we retrieved again using the referenced feature and obtained more precise result. According to the experimental results, the proposed method is simple and efficient. Furthermore, the proposed method can be applied in other CBIR system easily.
Chiang, Cheng-Yuan, and 江正元. "Speaker Recognition with Independent Corpus Based on RM Distance Measure." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/9zur32.
Повний текст джерела淡江大學
電機工程學系碩士班
104
The speaker recognition is always a hot topic in the research field. Technologies of speaker recognition under white and color noisy environments have been proposed in recent years. Sparse representation algorithm has been introduced into noise filtering for improving the assessments of speech quality, such as SNR, SNRseg, LLR and PESQ, but the cost time is lengthy. So we employ Label Consistent K-SVD sparse coding (LC-KSVD) to de-noise speech data and decrease processing time. Speaker recognition systems almost use Euclidean distance to compute the distance between features, currently. Our goal is to have short corpus and independent corpus, which makes it more difficult to achieve high recognition accuracy. We propose Riemannian distance replace Euclidean distance, but our experimental results show that Euclidean distance is superior than Riemannian distance. We use waveform, MFCC and MFCC smoothing spectrum with RD and ED for speaker recognition experiment in this paper.
Liu, Kuan-Liang, and 劉冠良. "A Subset gene selection method based on clustering analysis and distance measure." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/40328330647012774931.
Повний текст джерела國立成功大學
資訊管理研究所
95
After the Human Genome Project, the next challenge for bio-researchers is to understand the meanings of genes and the inter-relationship between them. As the technique of gene expression microarray stores all the gene expression data in a tiny chip, researchers become able to analyze all expression data of genes simultaneously. Nevertheless, compared to the original statistic data, the huge dimensionality and comparatively few sample amounts of gene expression data are still research obstacles. The objective of this research is to screen a representative set of genes according to a specific problem. Although many gene selection methods have been proposed in recent years, problems, such as gene collinearity, lack of consideration for combination genes, and work complexity, are not thoroughly examined and worked out. The gene selection algorithm of this research is tailored to the problems mentioned above. We first distribute the whole data set of genes using density-based clustering technique and screen out genes that are similar and have comparatively lower individual gene rank values. Then we select and substitute combinative genes according to examination of distance measure value, , and cluster similarity index. Considering the characteristic of gene expression data, we introduce relation-based methods and measure similarity between genes. Coupled with the data of tumor classification, the algorithm proposed in this research is tested and the accuracy rate of classification was improved. The gene set of enhanced can really get a higher accuracy rate of classification. In addition, the accuracy rates of gene sets from our selection algorithm are better than the gene sets from individual gene ranking methods.
Книги з теми "Distance-based measure"
van Onselen, Charles. The Night Trains. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197568651.001.0001.
Повний текст джерелаBove, Vincenzo, Chiara Ruffa, and Andrea Ruggeri. Composing Peace. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198790655.001.0001.
Повний текст джерелаWynn, Jonathan. Country Music and Fan Culture. Edited by Travis D. Stimeling. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190248178.013.10.
Повний текст джерелаSilva, Heloísa Helena Corrêa da, Carolina Cassia Batista Santos, Josiara Reis Pereira, Jefferson William Pereira, and Lucilene Ferreira de Melo. Plano de biossegurança do Departamento de Serviço Social da Universidade Federal do Amazonas – UFAM. Brazil Publishing, 2020. http://dx.doi.org/10.31012/978-65-5861-309-1.
Повний текст джерелаRez, Peter. The Simple Physics of Energy Use. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198802297.001.0001.
Повний текст джерелаJohansen, Bruce, and Adebowale Akande, eds. Nationalism: Past as Prologue. Nova Science Publishers, Inc., 2021. http://dx.doi.org/10.52305/aief3847.
Повний текст джерелаЧастини книг з теми "Distance-based measure"
Spiegel, Stephan, Johannes-Brijnesh Jain, and Sahin Albayrak. "A Recurrence Plot-Based Distance Measure." In Springer Proceedings in Mathematics & Statistics, 1–15. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09531-8_1.
Повний текст джерелаAfify, Yasmine M., Ibrahim F. Moawad, Nagwa L. Badr, and Mohamed F. Tolba. "An Enhanced Distance Based Similarity Measure for User Based Recommendations." In Advances in Intelligent Systems and Computing, 42–52. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48308-5_5.
Повний текст джерелаBrunenberg, Ellen, Remco Duits, Bart ter Haar Romeny, and Bram Platel. "A Sobolev Norm Based Distance Measure for HARDI Clustering." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010, 175–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15705-9_22.
Повний текст джерелаKaushik, Sumit, and Jan Slovak. "DTI Segmentation Using Anisotropy Preserving Quaternion Based Distance Measure." In Lecture Notes in Computer Science, 81–89. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93000-8_10.
Повний текст джерелаHao, Zhinan, Zeshui Xu, and Hua Zhao. "The Decision Making Method Based on the New Distance Measure and Similarity Measure." In Uncertainty and Operations Research, 9–33. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3891-9_2.
Повний текст джерелаShao, Yan, and Zhong Jin. "Trademark Image Retrieval Based on Improved Distance Measure of Moments." In Multimedia and Signal Processing, 154–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35286-7_20.
Повний текст джерелаFushimi, Takayasu, Tetsuji Satoh, Kazumi Saito, Kazuhiro Kazama, and Noriko Kando. "Content Centrality Measure for Networks: Introducing Distance-Based Decay Weights." In Lecture Notes in Computer Science, 40–54. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47874-6_4.
Повний текст джерелаChandra, Subhash, and Priyanka. "Classification of Static Signature Based on Distance Measure Using Feature Selection." In Lecture Notes in Electrical Engineering, 707–17. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5341-7_53.
Повний текст джерелаHwang, Jooyeon, Dongsup Lim, and Doowon Paik. "A Straight Line-Based Distance Measure to Compute Photographic Compositional Dissimilarity." In Future Generation Information Technology, 69–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10509-8_9.
Повний текст джерелаCai, Jie, Shilong Chao, Sheng Yang, Shulin Wang, and Jiawei Luo. "Feature Selection Based on Density Peak Clustering Using Information Distance Measure." In Intelligent Computing Theories and Application, 125–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63312-1_11.
Повний текст джерелаТези доповідей конференцій з теми "Distance-based measure"
Campana, Bilson J. L., and Eamonn J. Keogh. "A Compression Based Distance Measure for Texture." In Proceedings of the 2010 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2010. http://dx.doi.org/10.1137/1.9781611972801.74.
Повний текст джерелаMohd, Wan Rosanisah Wan, and Lazim Abdullah. "Similarity measures of Pythagorean fuzzy sets based on combination of cosine similarity measure and Euclidean distance measure." In PROCEEDING OF THE 25TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM25): Mathematical Sciences as the Core of Intellectual Excellence. Author(s), 2018. http://dx.doi.org/10.1063/1.5041661.
Повний текст джерелаMoosavi, Mohammad Reza, Zahra Yeganehfard, Alireza Kazemi, Mohammad Hadi Sadreddini, and Mansoor Zolghadri Jahromi. "Distance measure adaptation based on local feature weighting." In 2012 6th IEEE International Conference Intelligent Systems (IS). IEEE, 2012. http://dx.doi.org/10.1109/is.2012.6335126.
Повний текст джерелаYu, Yan, Tianjiang Wang, Ying Chen, Jinsheng Li, and Tan Liu. "Image Distance Measure Based on Adaptive Patch Matching." In 2014 7th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2014. http://dx.doi.org/10.1109/iscid.2014.191.
Повний текст джерелаAlaudah, Yazeed, and Ghassan AlRegib. "A curvelet-based distance measure for seismic images." In 2015 IEEE International Conference on Image Processing (ICIP). IEEE, 2015. http://dx.doi.org/10.1109/icip.2015.7351597.
Повний текст джерелаBelcher, Craig, and Yingzi Du. "Information distance based contrast invariant iris quality measure." In SPIE Defense and Security Symposium, edited by Sos S. Agaian and Sabah A. Jassim. SPIE, 2008. http://dx.doi.org/10.1117/12.778111.
Повний текст джерелаMahale, P. Mowlaee Begzade, and A. Sayadiyan. "New Distance Measure for Monaural Model-based Sound Separation." In Communication Technologies: from Theory to Applications (ICTTA). IEEE, 2008. http://dx.doi.org/10.1109/ictta.2008.4530025.
Повний текст джерелаGartner, D., F. Kraft, and T. Schaaf. "An Adaptive Distance Measure for Similarity Based Playlist Generation." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366658.
Повний текст джерелаPark, Alex, and James Glass. "A NOVEL DTW-BASED DISTANCE MEASURE FOR SPEAKER SEGMENTATION." In 2006 IEEE Spoken Language Technology Workshop. IEEE, 2006. http://dx.doi.org/10.1109/slt.2006.326807.
Повний текст джерелаGang Li, Jian Zhuang, Hongning Hou, and Dehong Yu. "A genetic algorithm based clustering using geodesic distance measure." In 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5357846.
Повний текст джерелаЗвіти організацій з теми "Distance-based measure"
Tetzlaff, Sasha, Jinelle Sperry, and Brett DeGregorio. You can go your own way : no evidence for social behavior based on kinship or familiarity in captive juvenile box turtles. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/44923.
Повний текст джерелаRipey, Mariya. NUMBERS IN THE NEWS TEXT (BASED ON MATERIAL OF ONE ISSUE OF NATIONWIDE NEWSPAPER “DAY”). Ivan Franko National University of Lviv, March 2021. http://dx.doi.org/10.30970/vjo.2021.50.11106.
Повний текст джерелаGoetsch, Arthur L., Yoav Aharoni, Arieh Brosh, Ryszard (Richard) Puchala, Terry A. Gipson, Zalman Henkin, Eugene D. Ungar, and Amit Dolev. Energy Expenditure for Activity in Free Ranging Ruminants: A Nutritional Frontier. United States Department of Agriculture, June 2009. http://dx.doi.org/10.32747/2009.7696529.bard.
Повний текст джерелаAlchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7580664.bard.
Повний текст джерелаGur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7600047.bard.
Повний текст джерелаSTUDY ON FIRE RESISTANCE OF BOX-TYPE COMPOSITE WALLS. The Hong Kong Institute of Steel Construction, August 2022. http://dx.doi.org/10.18057/icass2020.p.323.
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