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Artykuły w czasopismach na temat "Identity Testing in Number Fields"
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Mérai, László. "Values of rational functions in small subgroups of finite fields and the identity testing problem from powers." International Journal of Number Theory 16, no. 02 (2019): 219–31. http://dx.doi.org/10.1142/s1793042120500128.
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Motivated by some algorithmic problems, we give lower bounds on the size of the multiplicative groups containing rational function images of low-dimensional affine subspaces of a finite field [Formula: see text] considered as a linear space over a subfield [Formula: see text]. We apply this to the recently introduced algorithmic problem of identity testing of “hidden” polynomials [Formula: see text] and [Formula: see text] over a high degree extension of a finite field, given oracle access to [Formula: see text] and [Formula: see text].
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Karpinski, Marek, László Mérai, and Igor E. Shparlinski. "Identity testing and interpolation from high powers of polynomials of large degree over finite fields." Journal of Complexity 49 (December 2018): 74–84. http://dx.doi.org/10.1016/j.jco.2018.07.006.
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MacKenzie, Tyler D. B., Manphool S. Fageria, Xianzhou Nie, and Mathuresh Singh. "Effects of Crop Management Practices on Current-Season Spread of Potato virus Y." Plant Disease 98, no. 2 (2014): 213–22. http://dx.doi.org/10.1094/pdis-04-13-0403-re.
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The current-season spread of Potato virus Y (PVY) was monitored in 19 fields under various management practices in New Brunswick, Canada, through the 2011 and 2012 growing seasons. The focus of this study was to evaluate the role of seedborne PVY inoculum, aphid vector abundance, and the numbers, timing, and types of insecticide and mineral oil sprays, and to confirm the reliability and forecasting capacity of midseason PVY testing. In each field, 100 to 110 virus-free plants were identified shortly after emergence and were assessed four times from early July to early September (after top-kill) with enzyme-linked immunosorbent assay (ELISA) and reverse-transcription polymerase chain reaction (RT-PCR) to track PVY spread. In addition, tubers harvested during development in August and after top-kill were grown-out in the greenhouse for ELISA testing. PVY spread to selected virus-free plants varied widely, ranging from 0 to 76.2% across all studied fields. Of the 19 fields over two seasons, 10 fields were planted with no detectable seedborne PVY, and they showed 0 to 8.7% (mean 2.9%) PVY spread by harvest. The remaining nine study fields with 0.9 to 5.8% seedborne PVY showed 1 to 76.2% (mean 15.2%) PVY spread by harvest. PVY spread was detected in most fields during midseason testing with ELISA and RT-PCR; all tests correlated well with final PVY rates after top-kill, though RT-PCR detection in developing tubers was most sensitive and correlated. Logistic regression modeling was used to identify major factors in PVY spread, including seedborne PVY, early-season aphid abundance, and the numbers of insecticide and mineral oil sprays. The best-fitting model, constructed using these factors as well as a measurement of July PVY incidence (ELISAJuly), strongly explained PVY spread by harvest, with the most significant management factor being the number of mineral oil sprays supplemented with insecticide used during the growing season. A similar model fitted without the ELISAJuly did not adequately predict ultimate PVY spread. The analysis suggests that mineral oil alone was effective at lowering PVY spread, and more effective when combined with insecticide, particularly when used early in the season. No evidence was found for differences in PVY spread across the eight cultivars used or across the range of mineral oil application rates, whereas some evidence was found for differences in the effectiveness of different insecticide types.
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Agussalim, Muliana Djafar, and Andi Syam Rizal. "Analisis Potensi Debit Air Tanah Melalui Pumping Test Metode Step Draw Down pada Sumur Bor Irigasi di Desa Bonto Rannu, Kecamatan Kajang, Kabupaten Bulukumba, Sulawesi Selatan." JFT: Jurnal Fisika dan Terapannya 9, no. 2 (2022): 127–37. http://dx.doi.org/10.24252/jft.v9i2.32277.
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The rice fields in Bonto Rannu Village, Kajang District, Bulukumba Regency are dominated by rainfed rice fields. This species has limitations in the dry season because irrigation/agricultural irrigation completely depends on rainwater. Therefore, it is necessary to identify alternative irrigation sources to sustain farmers' farming activities in Bonto Rannu Village. This study aims to analyze the number of groundwater wells by testing in the form of a pump test (pumping test) with the step draw-down method. The optimum discharge (Qopt) of well 1 is 0.01876 m3/s or 67.53 m3/hour with an optimum Sw of 2.891 m. This shows that groundwater in well one can be pumped at 67.53 m3/hour with a decreased water level of 2.891 m, with the pump condition still technically safe. As for well 2, the optimum discharge (Qopt) is 0.00318 m3/s or 11.45 m3/hour with an optimum Sw of 2.100 m. These data indicate that there are limited groundwater reserves.
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Bazanova, E. M., A. V. Gorizontova, N. N. Gribova, T. M. Chikake, and A. V. Samosyuk. "Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions." Vysshee Obrazovanie v Rossii = Higher Education in Russia 32, no. 8-9 (2023): 147–66. http://dx.doi.org/10.31992/0869-3617-2023-32-8-9-147-166.
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The article presents the results of approbation of the intellectual system for testing general language competences (ISTOK) developed by testologists, linguists, specialists in methodology of teaching foreign languages and in artificial intelligence. This system includes a range of tests assessing language ability at levels from A2 to C1 of the Common European Framework of Reference (CEFR), as well as an adaptive placement test. All test materials are calibrated according to the CEFR. ISTOK is an adaptive testing system deployed through neural network solutions and providing assessment of receptive and productive language skills (reading, listening, speaking and writing) by using artificial intelligence and/or neurolinguistic models. The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. The results of various testing cohorts with the total number of test takers exceeding 5,000 demonstrated high reliability and objectified test validity. The new approach to language skills testing can be used for various purposes in higher education institutions, as well and to identify and/or confirm language proficiency of personnel in different organisations and businesses, while the principles of training and practical use of neurolinguistic models will find wide application in various fields of applied research.
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Kotsiubivska, Kateryna, Olena Tymoshenko, Kostiantyn Bulyha, and Ihor Yarokhno. "Application of Pseudo-Random Numbers in System Design." Digital Platform: Information Technologies in Sociocultural Sphere 6, no. 1 (2023): 53–62. http://dx.doi.org/10.31866/2617-796x.6.1.2023.283945.
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The purpose of the article is to study and search for optimal strategies for modelling information systems using pseudo-random numbers to improve the performance of information systems and to determine the optimal parameters of random number distributions; to analyze efficient algorithms for generating pseudo-random numbers. The research methods are based on the application of a systematic approach to analyzing the benefits of using pseudorandom numbers in the design of information systems. Scientific novelty. The article analyses the advantages of stochastic modelling of information systems using different approaches to generating pseudorandom numbers, and for the first time considers the application of a random decision tree forest for modelling queuing systems. Conclusions. The application of pseudorandom numbers in system design is an urgent problem that requires further research and development of methods. The design of efficient algorithms for generating, validating, and using pseudorandom values plays an essential role in many fields of science and technology. This approach allows for optimization and planning in the process of designing the system and is essential for validating and testing the system. By generating random variables, you can create different test scenarios and check how the system reacts to various conditions, which helps to identify potential errors, flaws, and problems in the system and ensures the quality of the design. Thus, the use of pseudo-random numbers in system design allows for randomness, risk analysis, optimization and planning, validation, and testing. This is an important aspect of system development that helps to ensure their reliability, performance, and efficiency.
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Kurbanismailov, Z. M., A. T. Tarlanov, and E. M. Akimov. "The technique of point visualization of the electric field in space and time." Russian Technological Journal 9, no. 3 (2021): 58–65. http://dx.doi.org/10.32362/2500-316x-2021-9-3-58-65.
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Testing of electronic devices is an integral part of the technological process of any manufacturer of such equipment. In this case, an electronic device is understood as an energy-intensive unit such as a mobile phone, data center or spacecraft. One of the key stages of testing is to identify the effect of electric fields on various electronic components of the device. This stage often requires making a mock-up of some part of an unfinished device in order to fix interference with special equipment. This requires time, financial and human resource costs. In order to reduce these costs in the modern world, the use of mathematical modeling tools for testing noise immunity and electromagnetic compatibility is becoming popular. In this paper, it is proposed to use an algorithm for visualizing electric fields in three-dimensional space and time. The algorithm is easily embedded into applications as a component of a mathematical modeling system. The work considered three ways of visualizing the electric field strength: starting from a simple setting of points in space, on the basis of which the electric field will be built, around the source of electric field radiation, to the use of algorithms that make it possible to arrange points equidistantly based on a given number of points in space for the formation of an electric field. The performance and visual implications of these methods were analyzed. The proposed methodology will be useful to the developer community as an embedded solution for point visualization of the electric field in any project in any algorithmic language with the ability to animate in time.
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Fajri, Muhammad. "Penerapan Digital Signature Untuk Identitas File Audio Dengan Metode Snefru." Management of Information System Journal 1, no. 1 (2022): 19–28. http://dx.doi.org/10.47065/mis.v1i1.397.
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In the era of information technology that is developing very rapidly, the use of signatures has been widely applied digitally through digital signatures. Digital signatures along with the times have led to the need for authentication of data or files that are used digitally. Its use also aims to avoid counterfeiting or interference. Currently, the use of digital signatures has been widely applied to software distribution, financial transactions, file transfers. The crime of falsifying audio files is a serious problem in various fields. Audio authenticity testing is important and significant in all social areas, especially when audio is used as evidence for conclusions in courts, the basis for judicial decision-making, and corporate reports. Forgery of audio files will cause losses that cannot be estimated. One solution to the problems mentioned above is to perform the process of assigning an identity to the audio file, so that it can be seen that the audio cannot be manipulated. The SNEFRU method is a hash function to detect changes in digital audio. SNEFRU has several variants, varying in number of operands and hash size. The supported hash sizes are 128 and 256 bits. The number of passes in the final 2-pass variant source of SNEFRU is two passes, while a more secure 4-pass version is also available. After the previous attack was published, the 8-pass version was introduced as well. This 8-pass version is still considered safe.
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Nuthakki, Siddhartha, Sai Kalyana pranitha buddiga, and Sonika Koganti. "Exploring Deep Learning Models for Image Recognition: A Comparative Review." Signal & Image Processing : An International Journal 15, no. 3 (2024): 01–10. http://dx.doi.org/10.5121/sipij.2024.15301.
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Image recognition, which comes under Artificial Intelligence (AI) is a critical aspect of computer vision, enabling computers or other computing devices to identify and categorize objects within images. Among numerous fields of life, food processing is an important area, in which image processing plays a vital role, both for producers and consumers. This study focuses on the binary classification of strawberries, where images are sorted into one of two categories. We Utilized a dataset of strawberry images for this study; we aim to determine the effectiveness of different models in identifying whether an image contains strawberries. This research has practical applications in fields such as agriculture and quality control. We compared various popular deep learning models, including MobileNetV2, Convolutional Neural Networks (CNN), and DenseNet121, for binary classification of strawberry images. The accuracy achieved by MobileNetV2 is 96.7%, CNN is 99.8%, and DenseNet121 is 93.6%. Through rigorous testing and analysis, our results demonstrate that CNN outperforms the other models in this task. In the future, the deep learning models can be evaluated on a richer and larger number of images (datasets) for better/improved results.
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Martin, R. R., I. E. Tzanetakis, J. E. Barnes, and J. F. Elmhirst. "First Report of Strawberry latent ringspot virus in Strawberry in the United States and Canada." Plant Disease 88, no. 5 (2004): 575. http://dx.doi.org/10.1094/pdis.2004.88.5.575a.
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Strawberries in southern California have shown decline symptoms during the last 2 years. More than 70% of plants tested in California were infected with two newly identified criniviruses that infect strawberry (Strawberry pallidosis and Beet pseudo-yellows). Strawberry cultivars are usually symptomless when infected with one virus, and testing for other strawberry viruses is performed to identify any other viruses that may be involved in the symptomatology. Primers SLRSV F (5′ CCTCTCCAACC-TGCTAGACT 3′) and SLRSV R (5′ AAGCGCATGAAGGTGTAACT 3′) that amplify a 497-bp fragment of RNA 2 of Strawberry latent ringspot virus (SLRSV) were developed and utilized for reverse transcription-polymerase chain reaction (RT-PCR) detection. SLRSV belongs to the family Sequiviridae and is transmitted by nematodes of the genus Xiphinema. The virus has a broad host range (4) and is usually symptomless in strawberries. Strawberry plants from commercial fields in California, Oregon, Washington, and British Columbia, Canada were tested. SLRSV was identified in 17% of plants tested from California and 4% of plants tested from British Columbia, while all samples from Oregon and Washington tested negative. The fragment amplified (GenBank Accession No. AY461735, isolate from British Columbia, Canada) shares 84% nucleotide and 94% amino acid sequence identity with the previously published sequence of SLRSV from strawberry (GenBank Accession No. X77466) (3). The virus was transmitted mechanically from strawberry samples from Canada to Chenopodium quinoa, and the infected C. quinoa plants tested positive for SLRSV with RT-PCR, while no amplicons were obtained from noninoculated control plants. To our knowledge, this is the first report of SLRSV in strawberry in North America, although it has been previously reported in a single cherry tree in Ontario, Canada (1) and in an imported seed lot of parsley in California (2). The number of plants that tested positive as well as the geographic distribution of the virus indicates that the virus is widespread in California, but further testing is needed to identify its distribution in other states. References: (1) W. R. Allen et al. Phytopathology 60:1262, 1970. (2) C. M. Hanson and R. N. Campbell. Plant Dis. Rep. 63:142, 1979. (3) S. Kreiah et al. J. Gen. Virol. 75:2527, 1994. (4) K. Schmelzer. Phytopath. Z. 66:1, 1969.