Journal articles: 'Wheat – Classification – Computer programs'

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Parsadanova, Tatyana. "MODERN APPROACHES TO CLASSIFICATION OF TELEVISION CONTENT." Scientific and analytical journal Burganov House. The space of culture 16, no. 2 (June 10, 2020): 19–32. http://dx.doi.org/10.36340/2071-6818-2020-16-2-19-32.

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Program classification is an important tool for records and marketing. Accessible, reliable, and internationally comparable data is needed in all aspects of work. And this is not only a matter of program organisation but also a fundamental part of the research of the audience in terms of studying the relationship between the public and the programs. A typology can be created according to the motives and habits, underlying the behavior of the viewer as a buyer with regard to their television preferences. It can be first considered whether the viewer is watching TV carefully or in parallel with other things, constantly changing channels, or watching a selected channel continuously. The demographic approach is formed by derived indicators and estimates, which allows to comprehensively characterize the structure and movement of the population, social, and demographic processes. In the case of studying television audiences, it is more common to deal with indicators of the number of people, gender, age, state of marriage, level of education, profession, social status, income. A TV set, a computer, a tablet, a smartphone - all this is now television. Arranged on the air according to the broadcasting grid, we watch television programs at home; it is called linear viewing. However, we can also request the content we are interested in on any screen at any time, anywhere - this is non-linear viewing. Recently, in connection with the Covid-19 pandemic, even journalists have been broadcasting from home. It used to be just television but nowadays the definition of "big television" has come into use. Television is primarily what it shows - television content that has certain characteristics. The usual division is based on the basic functions of television - informative, entertaining, and educational. However, a lot depends on the idea, thematic focus, genre structure, origin, format, and content. The division is necessary for a greater understanding of what exactly we intend to produce according to the formula: there is an idea, what the manufacturer wants to convey to the audience, after, it is necessary to understand how it can be made and with what content filled directly. This article deals with approaches to the classification of television programs.

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Uzhinskiy, A. V., G. A. Ososkov, P. V. Goncharov, A. V. Nechaevskiy, and A. A. Smetanin. "One-shot learning with triplet loss for vegetation classification tasks." Computer Optics 45, no. 4 (July 2021): 608–14. http://dx.doi.org/10.18287/2412-6179-co-856.

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Triplet loss function is one of the options that can significantly improve the accuracy of the One-shot Learning tasks. Starting from 2015, many projects use Siamese networks and this kind of loss for face recognition and object classification. In our research, we focused on two tasks related to vegetation. The first one is plant disease detection on 25 classes of five crops (grape, cotton, wheat, cucumbers, and corn). This task is motivated because harvest losses due to diseases is a serious problem for both large farming structures and rural families. The second task is the identification of moss species (5 classes). Mosses are natural bioaccumulators of pollutants; therefore, they are used in environmental monitoring programs. The identification of moss species is an important step in the sample preprocessing. In both tasks, we used self-collected image databases. We tried several deep learning architectures and approaches. Our Siamese network architecture with a triplet loss function and MobileNetV2 as a base network showed the most impressive results in both above-mentioned tasks. The average accuracy for plant disease detection amounted to over 97.8% and 97.6% for moss species classification.

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Eagles, H. A., G. J. Hollamby, N. N. Gororo, and R. F. Eastwood. "Estimation and utilisation of glutenin gene effects from the analysis of unbalanced data from wheat breeding programs." Australian Journal of Agricultural Research 53, no. 4 (2002): 367. http://dx.doi.org/10.1071/ar01074.

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Glutenins are a major determinant of dough characteristics in wheat. These proteins are determined by genes at 6 loci (Glu genes), with multiple alleles present in most breeding programs. This study was conducted to determine whether estimates of allele effects for the important dough rheological characters, maximum dough resistance (Rmax) and dough extensibility, could be determined from aggregated data from southern Australian wheat breeding programs using statistical techniques appropriate for unbalanced data. From a 2-stage analysis of 3226 samples of 1926 cultivars and breeding lines, estimates of Rmax and extensibility effects were obtained, first for the lines, and then for 31 glutenin alleles. Glutenin genes did not determine flour protein concentration, and this character was used as a covariate. Rankings of the estimates of Rmax for the alleles were similar to the relative scores for dough strength reported from previous studies, providing strong evidence that the analysis of a large, unbalanced data set from applied wheat breeding programs can provide reliable estimates. All 2-way interactions between loci were present for 18 of the alleles. Analyses including interactions showed that epistasis was important for both Rmax and extensibility, especially between the Glu-B1 locus coding for high molecular weight glutenins and the Glu-A3 and Glu-B3 loci coding for low molecular weight glutenins. Because of the complexity of these interactions, similar values of Rmax and extensibility were predicted for diverse combinations of alleles. This implied that the practical application of glutenin genes in applied wheat breeding would be greatly enhanced by computer software which can predict dough rheology characteristics from glutenin allele classifications.

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Van Zandt, CDR Robert A. "THE OSRO CLASSIFICATION PROGRAM: WHAT IT IS AND WHAT IT IS NOT." International Oil Spill Conference Proceedings 1997, no. 1 (April 1, 1997): 453–57. http://dx.doi.org/10.7901/2169-3358-1997-1-453.

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ABSTRACT The Coast Guard's oil spill removal organization (OSRO) classification process underwent significant revision in late 1995. The revision was necessary to strengthen the program into a more credible and useful tool for facilitating preparation and review of vessel and facility response plans. The revised process is more closely linked to the response planning criteria that vessel and facility owners and operators are required to meet under the Oil Pollution Act of 1990. As a result, the process provides a better indication of an OSRO's capacity and potential to respond to and recover oil spills of various sizes. Data provided by each OSRO are being included in the computer-based national Response Resource Inventory (RRI). The paper describes the important features and limitations of the revised classification process and gives an interpretation of what the new classifications mean to response plan holders and reviewers. It also describes the method by which plan holders can use the computer-based RRI as a tool to conduct their own analysis of an OSRO's capacity to meet their specific planning requirements.

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Uhl, Joan E., William E. Wilkinson, and Connie S. Wilkinson. "Aching Backs? A Glimpse into the Hazards of Nursing." AAOHN Journal 35, no. 1 (January 1987): 13–17. http://dx.doi.org/10.1177/216507998703500103.

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This study evaluates a combination of extant and collected data that compute frequency and exposure to back injuries reported by nursing employees at a Northwest Medical Center system. A major problem of interest, and the focus of this study is whether there is objective evidence to support the commonly held belief that lifting patients is the main cause of back injuries experienced by nurses; and whether job classification and worksite unit might be confounded with back injuries reported and what demographic characteristics of the nursing personnel, e.g., sex, age, job classification, and worksite unit, might be confounded with occupations that are high at risk for back injuries. Personnel records and injury report forms provided objective data for 659 registered nurses, licensed practical nurses, and nurse aides. Injury report forms providing data for 123 nursing personnel filed during the most recent consecutive twelve-month period between January 1, 1982 and April 30, 1985, were abstracted, summarized, and analyzed for number of back injuries reported using DataBase III and SPSSx computer programs on an IBM-AT system. In addition, on-site observations of patient lifts were made for ten eight-hour shifts on 15 different occasions and different worksites by a nurse-research analyst. These observation data were compared with self-report questionnaire responses representing over 54% of the total population of nurses within this medical center system. An inverse relationship of reported numbers of patient lift per shift was found for the observation and self-report data. Of the 2.5 females to males reporting back injuries, the average age was 43 years, with greater numbers of those injuries working on surgical and medical units versus lesser numbers injured from psychiatry and long-term care units in decreasing order. The Chi-square test was used to compute associations found not significant between reported high and low numbers of lifts and the incidence of back injuries. The t-test compared data from the observed and self-reported number of patient lifts and provided a significant (t = p <.001) difference in favor of self-report for number of lifts per eight-hour shift. Results of this study will contribute to increasing validity of lifting patients resulting in back injuries and further study of feasible and effective methods for evaluating back injuries and preventive interventions for nursing personnel who are at high risk of developing or sustaining back injury from any cause, while on the job.

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Dawood, Abdul Majeed S., and Saad Salman Awad AL Maeeni. "The role of electronic auditing in verifying the principles and approaches of accounting measurement for financial instruments when adopting international financial reporting standards IFRS." Muthanna Journal of Administrative and Economic Sciences 11, no. 1 (May 5, 2021): 229–47. http://dx.doi.org/10.52113/6/2021-11/229-247.

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The diversity of financial assets owned by Iraqi companies, which are measured and presented in different ways according to the classification of these assets according to international financial reporting standards, and that re-measuring these assets (shares) affects the income statement and the financial position of companies according to the change in the fair value of shares. The auditor uses multiple auditing methods for the purpose of verifying the measurement and presentation of these assets, including the use of electronic means in auditing (computer auditing.(The aim of the research is to clarify what electronic auditing is and to explain and analyse the measurement requirements in accordance with the International Financial Reporting Standard (IFRS - 9), in addition to preparing an electronic audit program that helps the auditor to verify the re measurement and presentation of the companies ’financial assets. Two mixed joint stock companies (Iraqi Company for Manufacturing and Marketing Dates - the National Company for Tourism Investments and Real Estate Projects) are adopted as a field of application by analysing their financial data for the year / 2018 and conducting a simulation of the outcome of the activity and the financial position of the company using an electronic audit program. This is to show the difference between the actual results and the results expected to be shown in light of the measurement principles adopted under international financial reporting standards. The researchers have concluded that the use of electronic means helps the auditor to conduct the audit process for the various financial assets due to their multiplicity and diversity in addition to the diversity of their market values. In addition, this enables the auditor to identify errors and indicate their impact on the income statement and budget and thus reach a final opinion on the financial statements towards the use of electronic means in auditing operations by professional organizations and relevant authorities for the purpose of speed and accuracy in completing auditing operations. Moreover, the necessity to prepare electronic programs for various auditing purposes in line with the activity of the bodies subject for auditing and training auditors in the use of such programs.

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Ion, I., R. Arhire, and M. Macesanu. "Programs complexity: comparative analysis hierarchy, classification." ACM SIGPLAN Notices 22, no. 4 (April 1987): 94–102. http://dx.doi.org/10.1145/24714.24726.

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Shi, Yong, YingJie Tian, XiaoJun Chen, and Peng Zhang. "Regularized multiple criteria linear programs for classification." Science in China Series F: Information Sciences 52, no. 10 (October 2009): 1812–20. http://dx.doi.org/10.1007/s11432-009-0126-5.

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Zhang, Zhengzhi, Sarath Kodagoda, David Ruiz, Jayantha Katupitiya, and Gamini Dissanayake. "Classification of Bidens in wheat farms." International Journal of Computer Applications in Technology 39, no. 1/2/3 (2010): 123. http://dx.doi.org/10.1504/ijcat.2010.034740.

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Verma, Surendra P., and M. Abdelaly Rivera-Gómez. "Computer programs for the classification and nomenclature of igneous rocks." Episodes 36, no. 2 (June 1, 2013): 115–24. http://dx.doi.org/10.18814/epiiugs/2013/v36i2/005.

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Giordana, A., and G. Lo Bello. "Learning Classification Programs: The Genetic Algorithm Approach." Fundamenta Informaticae 35, no. 1-4 (1998): 163–77. http://dx.doi.org/10.3233/fi-1998-35123409.

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Sivapalan, S., L. O'Brien, G. Ortiz-Ferrara, G. J. Hollamby, I. Barclay, and P. J. Martin. "Yield performance and adaptation of some Australian and CIMMYT/ICARDA developed wheat genotypes in the West Asia North Africa (WANA) region." Australian Journal of Agricultural Research 52, no. 6 (2001): 661. http://dx.doi.org/10.1071/ar00115.

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A set of 29 advanced breeding lines and named cultivars from different breeding programs in Australia was compared with 18 genotypes developed by the CIMMYT/ICARDA breeding programs for their adaptation and yield performance using 5 locations in the WANA region for 2 years. Classification analysis identified 13 CIMMYT/ICARDA genotypes that had a pattern in yield performance similar to 2 Australian cultivars, Leichhardt and Hartog. The classification of environments effectively identified trials that experienced heat stress and received supplementary irrigation. Most of the genotypes developed by the CIMMYT/ICARDA breeding programs showed wide adaptation in the WANA region. Genotypes developed for Australian Mediterranean environments failed to show wide adaptation in the WANA region. However, many Australian genotypes showed specific adaptation to heat-stressed environments. Variation among Australian genotypes for disease resistance and heat tolerance couldbe used for wheat improvement in the WANA region.

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Aboneh, Tagel, Abebe Rorissa, Ramasamy Srinivasagan, and Ashenafi Gemechu. "Computer Vision Framework for Wheat Disease Identification and Classification Using Jetson GPU Infrastructure." Technologies 9, no. 3 (July 2, 2021): 47. http://dx.doi.org/10.3390/technologies9030047.

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Diseases have adverse effects on crop production and yield loss. Various diseases such as leaf rust, stem rust, and strip rust can affect yield quality and quantity for a studied area. In addition, manual wheat disease identification and interpretation is time-consuming and cumbersome. Currently, decisions related to plants mainly rely on the level of expertise in the domain. To resolve these challenges and to identify wheat disease as early as possible, we implemented different deep learning models such as Inceptionv3, Resnet50, and VGG16/19. This research was conducted in collaboration with Bishoftu Agricultural Research Institute, Ethiopia. Our main objective was to automate plant-disease identification using advanced deep learning approaches and image data. For the experiment, RGB image data were collected from the Bishoftu area. From the experimental results, the VGG19 model classified wheat disease with 99.38% accuracy.

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Apt, Krzysztof R., and Howard A. Blair. "Arithmetic Classification of Perfect Models of Stratified Programs." Fundamenta Informaticae 13, no. 1 (January 1, 1990): 1–17. http://dx.doi.org/10.3233/fi-1990-13103.

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We study here the recursion theoretic complexity of the perfect (Herbrand) models of stratified logic programs. We show that these models lie arbitrarily high in the arithmetic hierarchy. As a byproduct we obtain a similar characterization of the recursion theoretic complexity of the set of consequences in a number of formalisms for non-monotonic reasoning. We show that under some circumstances this complexity can be brought down to recursive enumerability.

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Almajdoub, Abu Llbayda M. ,., Mukhtar O. ,. Agoub, Ali S. Shreidi, and Hassan E. Tantun. "Characterization and Classification of Libyan Bread Wheat Germplasm Collections (Triticum aestivum L)." Journal of Misurata University for Agricultural Sciences 1, no. 2 (June 30, 2020): 450–64. http://dx.doi.org/10.36602/jmuas.2020.v01.02.33.

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A field experiment was carried out on the bread wheat crops under the supplementary irrigation system at Misurata Research Station during the agricultural season 2018/2019. It included forty-three varieties and accessions. Thirty-five of them were obtained in a germplasm collection mission in different Libyan regions in the 2017/2018 season. For comparison, eight additional old and modern local varieties from the gene bank of bread wheat crops being worked on in the breeding program at Misurata Research Station were included. Varieties and accessions were randomly planted according to the Augmented designs. The FAO certified profiling system was used to characterize samples in both the field and laboratory. The results showed that the different varieties and accessions differed greatly in their morphological characteristics, growth habits, adaptability to the environmental conditions of the study area, and resistance of major diseases and pests recorded during the growing season. The results also indicated a large variation in some key plant characteristics such as days to heading, which ranged from 41 to 93 days. A significant amount of genetic diversity was found in the fields cultivated with wheat included in the collection mission in different regions of Libya. Some of these genotypes were identified as well-known local varieties such as Sidi Al-Masry, Al-Mukhtar, Bohot 208, and Sabha. Many other genotypes are unknown and need more research so that their genetic material can be used in future breeding programs.

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Sabanci, Kadir, Ahmet Kayabasi, and Abdurrahim Toktas. "Computer vision-based method for classification of wheat grains using artificial neural network." Journal of the Science of Food and Agriculture 97, no. 8 (November 10, 2016): 2588–93. http://dx.doi.org/10.1002/jsfa.8080.

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Anglano, C., and M. Botta. "NOW G-Net: learning classification programs on networks of workstations." IEEE Transactions on Evolutionary Computation 6, no. 5 (October 2002): 463–80. http://dx.doi.org/10.1109/tevc.2002.800882.

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Ullah, Arif, Nazri Mohd Nawi, Anditya Arifianto, Imran Ahmed, Muhammad Aamir, and Sundas Naqeeb Khan. "Real-Time Wheat Classification System for Selective Herbicides Using Broad Wheat Estimation in Deep Neural Network." International Journal on Advanced Science, Engineering and Information Technology 9, no. 1 (January 17, 2019): 153. http://dx.doi.org/10.18517/ijaseit.9.1.5031.

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McCaig, T. N., R. M. DePauw, and P. C. Williams. "Assessing seed-coat color in a wheat breeding program with a NIR/VIS instrument." Canadian Journal of Plant Science 73, no. 2 (April 1, 1993): 535–39. http://dx.doi.org/10.4141/cjps93-073.

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Red seed-coat can be distinguished from white seed-coat of unground wheat (Triticum spp.) by measurement of the first-derivative of the reflectance spectra at approximately 516 nm. Values around 450 nm distinguish durum (T. turgidum L. var. durum) from common (T. aestivum) white types. Classification accuracy is sufficient for screening purposes to reduce the number of samples requiring further examination. For breeding programs currently using combination near-infrared/visible (NIR/VIS) instruments, the additional time and costs to process the seed-coat information are minimal. Key words: Red, white, wheat, pigment, near-infrared, visible, breeding program

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Sivapalan, S., L. O'Brien, G. Ortiz-Ferrara, G. J. Hollamby, I. Barclay, and P. J. Martin. "An adaptation analysis of Australian and CIMMYT/ICARDA wheat germplasm in Australian production environments." Australian Journal of Agricultural Research 51, no. 7 (2000): 903. http://dx.doi.org/10.1071/ar99188.

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An adaptation analysis was conducted in an attempt to identify adapted germplasm and potential indicator or probe varieties that could be used for more efficient germplasm introduction and evaluation. A set of 39 advanced wheat breeding lines and named varieties from Australian breeding programs and 10 from the CIMMYT/ICARDA programs were tested using 20 environments across the Australian wheatbelt during a period of 3 years. AMMI analysis and classification analysis were performed on grain yield data. Five groups of genotypes with similar patterns in performance within each group were identified, mostly reflecting their origin and pedigree. Most of the genotypes from the CIMMYT/ICARDA programs clustered together as did most of those from the University of Adelaide and Agriculture Western Australia breeding programs. Four groups of environments with similar trends in discriminating genotypes within each group were identified. There was a clear discrimination between subtropical and Mediterranean environments. Subtropical environments with supplementary irrigation showed similar patterns to Mediterranean environments. Basic differences in adaptation and phenotypic stability among genotypes from the CIMMYT/ICARDA programs in relation to genotypes from several breeding programs in Australia were identified. CIMMYT/ICARDA genotypes such as Attila, Nesser, Pfau/Seri//Bow, Genaro 81, and Maya/Nac performed well, especially in subtropical environments. The Australian varieties Hartog and Vulcan showed similar performance and could be used as indicator varieties for assessing introduced germplasm for subtropical regions. University of Adelaide developed genotypes Trident, Spear, Excalibur, and RAC 655, along with the Agriculture Western Australia genotypes Tammin and 82Y:1186, showed wide adaptation to all environments and could be used as indicator varieties for wide adaptation. Similarly, genotypes such as BT Schomburgk, Pelsart, and Sunvale could be used as indicator varieties for the other genotype groups. The results of this study can serve as a basis for identification and introduction of germplasm from the CIMMYT/ICARDA programs for various Australian production environments. It has also provided an understanding of the pattern of discrimination of genotypes across each region of the Australian wheatbelt.

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Rossinskaya, Elena, and Igor Ryadovskiy. "The Concept of Malware as a Means of Committing Computer Crimes: Classification and Methods of Illegal Use." Russian Journal of Criminology 14, no. 5 (November 20, 2020): 699–709. http://dx.doi.org/10.17150/2500-4255.2020.14(5).699-709.

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The authors analyze problems connected with malware from the standpoint of the doctrine of the methods of computer crimes/offenses as one of the components of the theory of information-computer support of criminalistic work. Most methods of computer crimes are based on the unauthorized access to computer facilities and systems gained through malware that, in fact, acts as a weapon of crime. The authors present a classification of malware based on different parameters: from the standpoint of criminal law and criminology; the standpoint of information technology; the standpoint of the doctrine of computer crimes/offenses. Various grounds for the classification of malware are examined. A general classification, widely used by the developers of antiviral software, includes virus-programs, worm-programs and trojan-programs. In the modern situation of massive digitization, it is not practical to regard masquerading as a legitimate file as a dominant feature of trojan software. On the contrary, criminals try hard to hide from the user the downloading, installation and activity of malware that cannot self-propagate. The key method of propagating trojan programs is sending mass emails with attachments masquerading as useful content. The classification of malware by the way and method of propagation - viruses, worms and trojan programs - is only currently used due to traditions and does not reflect the essence of the process. A different classification of malware into autonomous, semi-autonomous and non-autonomous programs is based on the possibility of their autonomous functioning. At present there is practically no malware whose functions include only one specific type of actions, most of it contains a combination of various types of actions implemented through module architecture, which offers criminals wide opportunities for manipulating information. The key mechanisms of malwares work are described and illustrated through examples. Special attention is paid to harmful encryption software working through stable cryptographic algorithms - ransomware, when criminals demand ransom for restoring data. There is no criminal liability for such theft. The authors outline the problems connected with the possibility of the appearance of new malware that would affect cloud resources.

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Boros, Norbert, Mária Borbélyné Varga, and Zoltán Győri. "Use of extensigraph in the examination of wheat flours." Acta Agraria Debreceniensis, no. 32 (December 21, 2008): 17–23. http://dx.doi.org/10.34101/actaagrar/32/3014.

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The extensograph is widely used in quality control and research laboratories studying wheat flour quality. The most commonly used measurements include Rm, the maximum resistance (maximum height of the curve); R5 the resistance at a constant extension of 5 cm; E, extensibility (total curve length); Rm/E, the ratio of maximum resistance to extension; and A, the area under curve. The extensograph has proved useful in the classification and assessment of flours on the physical dough properties. Another important application is its use in wheat breeding programs. Furthermore, extensograph is an excellent tool to study the effects of a wide range of ingredients on dough properties of wheat flour (like oxidants, enzymes, salt and additives), and it can also be used measure the changes during the frozen storage. In the present study we provide a review of the scientific literature concerning the possible applications of the extensograph.

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ZHANG, MENGJIE, and PHILLIP WONG. "EXPLICITLY SIMPLIFYING EVOLVED GENETIC PROGRAMS DURING EVOLUTION." International Journal of Computational Intelligence and Applications 07, no. 02 (June 2008): 201–32. http://dx.doi.org/10.1142/s1469026808002247.

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The genetic programming (GP) evolutionary process typically introduces a large amount of redundancy and unnecessary complexity into evolved programs. Quick growth of redundant and functionally useless sections of programs can quickly overcome a GP system, exhausting system resources and causing premature termination of the system before an acceptable solution can be found. Rather than implicitly controlling the redundancy and code growth/bloat as in most of the existing approaches, this paper investigates an algebraic simplification algorithm for explicitly removing the redundancy from the genetic programs and simplifying these programs online during the evolutionary process. The new GP system with the simplification is examined and compared with a standard GP system on two regression and three classification problems of varying difficulties. The results show that the GP system employing a simplification component can achieve superior efficiency with comparable or slightly superior effectiveness to the standard GP system on these problems. The programs evolved by the new GP approach with the explicit simplification contain ``hidden patterns'' for a particular problem and are relatively simple and easy to interpret.

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Raman, Harsh, B. J. Stodart, Colin Cavanagh, M. Mackay, Matthew Morell, Andrew Milgate, and Peter Martin. "Molecular diversity and genetic structure of modern and traditional landrace cultivars of wheat (Triticum aestivum L.)." Crop and Pasture Science 61, no. 3 (2010): 222. http://dx.doi.org/10.1071/cp09093.

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Wheat is one of the most important cereal crops of the world. In order to achieve continued genetic gain in wheat improvement programs, an assessment and utilisation of genetic diversity in a wide range of germplasm are required. The Australian Winter Cereal Collection (AWCC, Tamworth) holds over 33 000 accessions of wheat. In this study, we scanned the genome of 1057 accessions of hexaploid common wheat (Triticum aestivum L.) originating from different geographic regions of the world, with 178 polymorphic DArT™ markers. These accessions comprised modern cultivars (MCs), advanced breeding lines (BLs), and landrace cultivars (LCs). Our results indicate that the LCs had higher polymorphic information content (PIC values) than the MCs and BLs. Cluster and principal coordinate analysis based on genetic distance matrices enabled classification of the 1057 accessions into 12 subgroups. The structure of subgroups appeared to be geographically determined and was generally consistent with pedigrees. Molecular analyses revealed that LCs have unique alleles compared with MCs and BLs, which may be useful for the genetic improvement of wheat.

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Figueiredo, Marco A., Clay S. Gloster, Mark Stephens, Corey A. Graves, and Mouna Nakkar. "Implementation of Multispectral Image Classification on a Remote Adaptive Computer." VLSI Design 10, no. 3 (January 1, 2000): 307–19. http://dx.doi.org/10.1155/2000/31983.

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As the demand for higher performance computers for the processing of remote sensing science algorithms increases, the need to investigate new computing paradigms is justified. Field Programmable Gate Arrays enable the implementation of algorithms at the hardware gate level, leading to orders of magnitude performance increase over microprocessor based systems. The automatic classification of spaceborne multispectral images is an example of a computation intensive application that can benefit from implementation on an FPGA-based custom computing machine (adaptive or reconfigurable computer). A probabilistic neural network is used here to classify pixels of a multispectral LANDSAT-2 image. The implementation described utilizes Java client/server application programs to access the adaptive computer from a remote site. Results verify that a remote hardware version of the algorithm (implemented on an adaptive computer) is significantly faster than a local software version of the same algorithm (implemented on a typical general-purpose computer).

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Pronozin, A. Yu, A. A. Paulish, E. A. Zavarzin, A. Yu Prikhodko, N. M. Prokhoshin, Yu V. Kruchinina, N. P. Goncharov, E. G. Komyshev, and M. A. Genaev. "Automatic morphology phenotyping of tetra- and hexaploid wheat spike using computer vision methods." Vavilov Journal of Genetics and Breeding 25, no. 1 (March 16, 2021): 71–81. http://dx.doi.org/10.18699/vj21.009.

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Intraspecific classification of cultivated plants is necessary for the conservation of biological diversity, study of their origin and their phylogeny. The modern cultivated wheat species originated from three wild diploid ancestors as a result of several rounds of genome doubling and are represented by di-, tetra- and hexaploid species. The identification of wheat ploidy level is one of the main stages of their taxonomy. Such classification is possible based on visual analysis of the wheat spike traits. The aim of this study is to investigate the morphological characteristics of spikes for hexa- and tetraploid wheat species based on the method of high-performance phenotyping. Phenotyping of the quantitative characteristics of the spike of 17 wheat species (595 plants, 3348 images), including eight tetraploids (Triticum aethiopicum, T. dicoccoides, T. dicoccum, T. durum, T. militinae, T. polonicum, T. timopheevii, and T. turgidum) and nine hexaploids (T. compactum, T. aestivum, i:ANK-23 (near-isogenic line of T. aestivum cv. Novosibirskaya 67), T. antiquorum, T. spelta (including cv. Rother Sommer Kolben), T. petropavlovskyi, T. yunnanense, T. macha, T. sphaerococcum, and T. vavilovii), was performed. Wheat spike morphology was described on the basis of nine quantitative traits including shape, size and awns area of the spike. The traits were obtained as a result of image analysis using the WERecognizer program. A cluster analysis of plants according to the characteristics of the spike shape and comparison of their distributions in tetraploid and hexaploid species showed a higher variability of traits in hexaploid species compared to tetraploid ones. At the same time, the species themselves form two clusters in the visual characteristics of the spike. One type is predominantly hexaploid species (with the exception of one tetraploid, T. dicoccoides). The other group includes tetraploid ones (with the exception of three hexaploid ones, T. compactum, T. antiquorum, T. sphaerococcum, and i:ANK-23). Thus, it has been shown that the morphological characteristics of spikes for hexaploid and tetraploid wheat species, obtained on the basis of computer analysis of images, include differences, which are further used to develop methods for plant classifications by ploidy level and their species in an automatic mode.

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Pavlenko, Yevhen, Vladimir Butenko, Vadim Gubin, and Serhii Lubenets. "RESEARCH OF DATA TYPE CLASSIFICATION METHODS WHEN DEVELOPING COMPUTER ENGINEERING SOFTWARE." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 1 (5) (July 12, 2021): 80–85. http://dx.doi.org/10.20998/2079-0023.2021.01.13.

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The paper deals with the problems of increasing the efficiency of software development, in particular, the issue of reducing the time for developing programs and using automated synthesis of programs, which will avoid the revision of the original product. The software should be tested along with other system components in all combinations that may occur. Testing is time-consuming because hidden bugs are revealed through unexpected interactions between software components. With structural analysis, data flow diagrams are not the end result, they are a developer tool. First, diagrams are built, and then mechanisms are developed to ensure the required system behavior. A graphical approach to solving the problem of automation of software development is being developed, based on the involvement of visual forms of program presentation. For any program object, you can select a finite number of states in which it is at each moment of time. The program progress is associated with the transition of an object from one state to another. The graph replaces the textual form of the description of the program algorithm, while the visual representation of the algorithm is realized. The specification of data structures, as well as the setting of intermodular interfaces according to data, is separated from the description of the structure of the algorithm and controls. Basic modules and data types are used. Basic modules are local calculable functions, on the basis of which all other technology objects are generated. Data types describe the syntactic and semantic aspects of constructing data used in base functions. Algorithms for finding routes on directed graphs are considered. When defining routes from the root vertex to the final ones, the properties of the algebra of three-valued logic were used. Based on the considered approach, as well as taking into account its shortcomings, a method for classifying data types was proposed, based on the implementation of a partial enumeration of the routes of the graph of program links and a method for designing software based on it, taking into account minimizing the time and cost of the project. Keywords: software, computer engineering, information systems, components, partial enumeration of graph routes, development costs.

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AHN, JOONSEON, and TAISOOK HAN. "AN ANALYTICAL METHOD FOR PARALLELIZATION OF RECURSIVE FUNCTIONS." Parallel Processing Letters 10, no. 01 (March 2000): 87–98. http://dx.doi.org/10.1142/s012962640000010x.

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Programming with parallel skeletons is an attractive framework because it encourages programmers to develop efficient and portable parallel programs. However, extracting parallelism from sequential specifications and constructing efficient parallel programs using the skeletons are still difficult tasks. In this paper, we propose an analytical approach to transforming recursive functions on general recursive data structures into compositions of parallel skeletons. Using static slicing, we have defined a classification of subexpressions based on their data-parallelism. Then, skeleton-based parallel programs are generated from the classification. To extend the scope of parallelization, we have adopted more general parallel skeletons which do not require the associativity of argument functions. In this way, our analytical method can parallelize recursive functions with complex data flows.

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AHN, JOONSEON, and TAISOOK HAN. "AN ANALYTICAL METHOD FOR PARALLELIZATION OF RECURSIVE FUNCTIONS." Parallel Processing Letters 10, no. 04 (December 2000): 359–70. http://dx.doi.org/10.1142/s0129626400000330.

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Programming with parallel skeletons is an attractive framework because it encourages programmers to develop efficient and portable parallel programs. However, extracting parallelism from sequential specifications and constructing efficient parallel programs using the skeletons are still difficult tasks. In this paper, we propose an analytical approach to transforming recursive functions on general recursive data structures into compositions of parallel skeletons. Using static slicing, we have defined a classification of subexpressions based on their data-parallelism. Then, skeleton-based parallel programs are generated from the classification. To extend the scope of parallelization, we have adopted more general parallel skeletons which do not require the associativity of argument functions. In this way, our analytical method can parallelize recursive functions with complex data flows.

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Kuila, Sumanta, Namrata Dhanda, and Subhankar Joardar. "Feature extraction of electrocardiogram signal using machine learning classification." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (December 1, 2020): 6598. http://dx.doi.org/10.11591/ijece.v10i6.pp6598-6605.

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In this article, we'll introduce ways to build virtual worlds through different computer programs. We will show the method of rectangles for analyzing data obtained from the electroencephalogram. We will demonstrate basic mathematical models for movement prediction in a system of virtual reality. Using this data, the main transformations are possible-change of position and rotation (change of orientation).

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Abreu-Lima, C., P. Arnaud, C. R. Brohet, B. Denis, J. Gehring, I. Graham, G. van Herpen, et al. "Evaluation of ECG Interpretation Results Obtained by Computer and Cardiologists." Methods of Information in Medicine 29, no. 04 (1990): 308–16. http://dx.doi.org/10.1055/s-0038-1634794.

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AbstractIn an international project investigators from 25 institutes are trying to establish a common reference library and evaluation methods for testing the diagnostic performance of various ECG computer programs and of cardiologists, based on ECG-independent clinical information. A first set of 500 validated ECGs was collected and analyzed by fifteen different computer programs and nine cardiologists, seven of who analysed the ECG and five the VCG. A coding scheme was used to map individual diagnostic statements onto a common set. Combined program and referee results were obtained by weighted averaging. Preliminary results indicate that the classification accuracy of several programs can still be improved. However, it was also apparent that the results of the best 12-lead ECG computer programs proved to be almost as accurate as the best of seven cardiologists in classifying seven main disease categories, i.e., normal, left, right and biventricular hypertrophy, anterior, inferior and combined myocardial infarction. Evaluation of rhythm statements and conduction disturbances was not included in the study. The data collection is still being pursued in order to reach over 1,000 cases. In this way a common diagnostic database is being established for comparative testing of diagnostic computer programs. This should lead to consumer protection and improve the accuracy and reliability of computerized electrocardiography.

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le Roux, Marlon-Schylor L., Nicolas Francois V. Burger, Maré Vlok, Karl J. Kunert, Christopher A. Cullis, and Anna-Maria Botha. "EMS Derived Wheat Mutant BIG8-1 (Triticum aestivum L.)—A New Drought Tolerant Mutant Wheat Line." International Journal of Molecular Sciences 22, no. 10 (May 18, 2021): 5314. http://dx.doi.org/10.3390/ijms22105314.

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Drought response in wheat is considered a highly complex process, since it is a multigenic trait; nevertheless, breeding programs are continuously searching for new wheat varieties with characteristics for drought tolerance. In a previous study, we demonstrated the effectiveness of a mutant known as RYNO3936 that could survive 14 days without water. In this study, we reveal another mutant known as BIG8-1 that can endure severe water deficit stress (21 days without water) with superior drought response characteristics. Phenotypically, the mutant plants had broader leaves, including a densely packed fibrous root architecture that was not visible in the WT parent plants. During mild (day 7) drought stress, the mutant could maintain its relative water content, chlorophyll content, maximum quantum yield of PSII (Fv/Fm) and stomatal conductance, with no phenotypic symptoms such as wilting or senescence despite a decrease in soil moisture content. It was only during moderate (day 14) and severe (day 21) water deficit stress that a decline in those variables was evident. Furthermore, the mutant plants also displayed a unique preservation of metabolic activity, which was confirmed by assessing the accumulation of free amino acids and increase of antioxidative enzymes (peroxidases and glutathione S-transferase). Proteome reshuffling was also observed, allowing slow degradation of essential proteins such as RuBisCO during water deficit stress. The LC-MS/MS data revealed a high abundance of proteins involved in energy and photosynthesis under well-watered conditions, particularly Serpin-Z2A and Z2B, SGT1 and Calnexin-like protein. However, after 21 days of water stress, the mutants expressed ABC transporter permeases and xylanase inhibitor protein, which are involved in the transport of amino acids and protecting cells, respectively. This study characterizes a new mutant BIG8-1 with drought-tolerant characteristics suited for breeding programs.

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Dix, Jürgen. "A CLASSIFICATION THEORY OF SEMANTICS OF NORMAL LOGIC PROGRAMS: I. STRONG PROPERTIES." Fundamenta Informaticae 22, no. 3 (1995): 227–55. http://dx.doi.org/10.3233/fi-1995-2233.

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DIX, Jürgen. "A CLASSIFICATION THEORY OF SEMANTICS OF NORMAL LOGIC PROGRAMS: II. WEAK PROPERTIES." Fundamenta Informaticae 22, no. 3 (1995): 257–88. http://dx.doi.org/10.3233/fi-1995-2234.

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Su, Wen-Hao, Jiajing Zhang, Ce Yang, Rae Page, Tamas Szinyei, Cory D. Hirsch, and Brian J. Steffenson. "Automatic Evaluation of Wheat Resistance to Fusarium Head Blight Using Dual Mask-RCNN Deep Learning Frameworks in Computer Vision." Remote Sensing 13, no. 1 (December 23, 2020): 26. http://dx.doi.org/10.3390/rs13010026.

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In many regions of the world, wheat is vulnerable to severe yield and quality losses from the fungus disease of Fusarium head blight (FHB). The development of resistant cultivars is one means of ameliorating the devastating effects of this disease, but the breeding process requires the evaluation of hundreds of lines each year for reaction to the disease. These field evaluations are laborious, expensive, time-consuming, and are prone to rater error. A phenotyping cart that can quickly capture images of the spikes of wheat lines and their level of FHB infection would greatly benefit wheat breeding programs. In this study, mask region convolutional neural network (Mask-RCNN) allowed for reliable identification of the symptom location and the disease severity of wheat spikes. Within a wheat line planted in the field, color images of individual wheat spikes and their corresponding diseased areas were labeled and segmented into sub-images. Images with annotated spikes and sub-images of individual spikes with labeled diseased areas were used as ground truth data to train Mask-RCNN models for automatic image segmentation of wheat spikes and FHB diseased areas, respectively. The feature pyramid network (FPN) based on ResNet-101 network was used as the backbone of Mask-RCNN for constructing the feature pyramid and extracting features. After generating mask images of wheat spikes from full-size images, Mask-RCNN was performed to predict diseased areas on each individual spike. This protocol enabled the rapid recognition of wheat spikes and diseased areas with the detection rates of 77.76% and 98.81%, respectively. The prediction accuracy of 77.19% was achieved by calculating the ratio of the wheat FHB severity value of prediction over ground truth. This study demonstrates the feasibility of rapidly determining levels of FHB in wheat spikes, which will greatly facilitate the breeding of resistant cultivars.

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Cao, Wenguang, G. Scoles, P. Hucl, and R. N. Chibbar. "Phylogenetic relationships of five morphological groups of hexaploid wheat (Triticum aestivum L. em Thell.) based on RAPD analysis." Genome 43, no. 4 (August 1, 2000): 724–27. http://dx.doi.org/10.1139/g00-030.

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The genetic relationships among the five groups of hexaploid wheat: common, spelta, macha, vavilovii, and semi-wild wheat (SWW) are not clear. Random amplified polymorphic DNA (RAPD) analysis was used to assess phylogenetic relationships among these five morphological groups of hexaploid wheat. RAPD data were analyzed using the NTSYS-PC computer program to generate Jaccard genetic similarity coefficients. A dendrogram based on RAPD analysis grouped 15 accessions into five distinct clusters. These results are in agreement with those based on morphological classification, suggesting that common wheat is most closely related to SWW, followed by spelta, vavilovii, and macha.Key words: RAPD, macha, spelta, vavilovii, semi-wild wheat, phylogenetic relationships.

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Charytanowicz, Małgorzata, Piotr Kulczycki, Piotr A. Kowalski, Szymon Łukasik, and Róża Czabak-Garbacz. "An evaluation of utilizing geometric features for wheat grain classification using X-ray images." Computers and Electronics in Agriculture 144 (January 2018): 260–68. http://dx.doi.org/10.1016/j.compag.2017.12.004.

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Neethirajan, S., C. Karunakaran, S. Symons, and D. S. Jayas. "Classification of vitreousness in durum wheat using soft X-rays and transmitted light images." Computers and Electronics in Agriculture 53, no. 1 (August 2006): 71–78. http://dx.doi.org/10.1016/j.compag.2006.03.001.

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Romero, José R., Pablo F. Roncallo, Pavan C. Akkiraju, Ignacio Ponzoni, Viviana C. Echenique, and Jessica A. Carballido. "Using classification algorithms for predicting durum wheat yield in the province of Buenos Aires." Computers and Electronics in Agriculture 96 (August 2013): 173–79. http://dx.doi.org/10.1016/j.compag.2013.05.006.

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ZHU, JINGBO, MATTHEW Y. MA, JINHONG K. GUO, and ZHENXING WANG. "CONTENT CLASSIFICATION AND RECOMMENDATION TECHNIQUES FOR VIEWING ELECTRONIC PROGRAMMING GUIDE ON A PORTABLE DEVICE." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 02 (March 2007): 375–95. http://dx.doi.org/10.1142/s0218001407005399.

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With the merge of digital television (DTV) and the exponential growth of broadcasting network, an overwhelmingly amount of information has been made available to a consumer's home. Therefore, how to provide consumers with the right amount of information becomes a challenging problem. In this paper, we propose an electronic programming guide (EPG) recommender based on natural language processing techniques, more specifically, text classification. This recommender has been implemented as a service on a home network that facilitates the personalized browsing and recommendation of TV programs on a portable remote device. Evaluations of our Maximum Entropy text classifier were performed on multiple categories of TV programs, and a near 80% retrieval rate is achieved using a small set of training data.

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Heller, I., A. Isakov, S. Blinder-Weiner, and M. Topilsky. "Bayesian Classification of Vasculitis: A Simulation Study." Methods of Information in Medicine 34, no. 03 (May 1995): 259–65. http://dx.doi.org/10.1055/s-0038-1634598.

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Abstract:New classification criteria for vasculitic disorders have recently been proposed by the American College of Rheumatology. These classification criteria have limitations inherent to the method employed in their development. We propose a different approach to the quantitative analysis of the manifestations of vasculitis, which may improve the precision of classification criteria in this domain. Bayesian classifiers were developed for six vasculitides using literature-derived quantitative descriptions of these syndromes. These clinical data were also used in computer programs designed to generate simulations of vasculitis and control cases. The performance of Bayesian classifiers of vasculitis was then compared to that of the American College of Rheumatology criteria, using series of computer-simulated vasculitis cases. Bayesian classifiers identified simulated vasculitis cases with greater accuracy than those of the corresponding American College of Rheumatology 1990 vasculitis criteria in all six diseases studied. As predicted by theoretical considerations, Bayesian classifiers have the potential to identify vasculitis cases more accurately than the proposed American College of Rheumatology 1990 criteria.

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Janse, Pooja Vinod, and Ratnadeep R. Deshmukh. "Crop Discrimination using Non-Imaging Hyperspectral Data." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 269–73. http://dx.doi.org/10.35940/ijeat.e2802.0610521.

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Crop type discrimination is still very challenging task for researchers using non-imaging hyperspectral data. It is because of spectral reflectance similarity between crops. In this research work we have discriminated between four crops wheat, jowar, bajara and maize. We have tried to overcome the problems which have been faced my researchers. Initially by visual analysis we have selected 22 reflectance band which shows the absorption property of particular molecules and classification techniqueis applied, but it has given us very poor result of classification. We observed only 24% classification accuracy. So we considered nine vegetation indices along with spectral bands and achieved better classification accuracy. ASD FieldSpec 4 Spectroradiometer device is used for capturing spectral reflectance data. We calculated nine different vegetation indices and some selective reflectance bands are used for crop classification. We have used Support Vector Machine (SVM) for classification.

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Josefsson, Martin. "On the classification of convex quadrilaterals." Mathematical Gazette 100, no. 547 (March 2016): 68–85. http://dx.doi.org/10.1017/mag.2016.9.

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We live in a golden age regarding the opportunities to explore Euclidean geometry. The access to dynamic geometry computer programs for everyone has made it very easy to study complex configurations in a way that has never been possible before. This is especially apparent in the study of triangle geometry, where the flow of new problems, properties, and papers is probably the highest it has ever been in the history of mathematics. Even though it has increased a bit in recent years, the interest in quadrilateral geometry is significantly lower. Why are triangles so much more popular than quadrilaterals? In fact, we think it would be more logical if the situation were reversed, since there are so many classes of quadrilaterals to explore. This is the primary reason we think that quadrilaterals are a lot more interesting to study than triangles.

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Narayanan, Barath Narayanan, and Venkata Salini Priyamvada Davuluru. "Ensemble Malware Classification System Using Deep Neural Networks." Electronics 9, no. 5 (April 27, 2020): 721. http://dx.doi.org/10.3390/electronics9050721.

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With the advancement of technology, there is a growing need of classifying malware programs that could potentially harm any computer system and/or smaller devices. In this research, an ensemble classification system comprising convolutional and recurrent neural networks is proposed to distinguish malware programs. Microsoft’s Malware Classification Challenge (BIG 2015) dataset with nine distinct classes is utilized for this study. This dataset contains an assembly file and a compiled file for each malware program. Compiled files are visualized as images and are classified using Convolutional Neural Networks (CNNs). Assembly files consist of machine language opcodes that are distinguished among classes using Long Short-Term Memory (LSTM) networks after converting them into sequences. In addition, features are extracted from these architectures (CNNs and LSTM) and are classified using a support vector machine or logistic regression. An accuracy of 97.2% is achieved using LSTM network for distinguishing assembly files, 99.4% using CNN architecture for classifying compiled files and an overall accuracy of 99.8% using the proposed ensemble approach thereby setting a new benchmark. An independent and automated classification system for assembly and/or compiled files provides the luxury to anti-malware industry experts to choose the type of system depending on their available computational resources.

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Gelesz, A., and A. Reith. "Classification and re-evaluation of double-skin facades." International Review of Applied Sciences and Engineering 2, no. 2 (December 1, 2011): 129–36. http://dx.doi.org/10.1556/irase.2.2011.2.9.

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Abstract The construction of double-skin glass facades in Hungary has mainly design or acoustic motivations. The potential energy savings or risks of double-skin facades are, however, not commonly evident. This fact is not surprising if we notice that there is no widely excepted classification of these constructions. In the following article different facade typologies are compared (Pottgiesser, BBRI, Széll) and an attempt to develop a transparent classification system is made. Subsequently a few chosen facade types, which are expected to perform well in the Hungarian climate, are evaluated through computer simulation programs to serve as a guideline for the design on climates similar to the domestic one.

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Zhang, Shanwen, Wenzhun Huang, and Zuliang Wang. "Combing modified Grabcut, K-means clustering and sparse representation classification for weed recognition in wheat field." Neurocomputing 452 (September 2021): 665–74. http://dx.doi.org/10.1016/j.neucom.2020.06.140.

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M, Vishweshwaran, and . "Linear Genetic Programming, Naïve Bayes algorithm - Their Applications in Geotechnical Engineering." International Journal of Engineering & Technology 7, no. 3.12 (July 20, 2018): 925. http://dx.doi.org/10.14419/ijet.v7i3.12.16562.

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Modeling soil and rock pose challenges due to uncertainties in their complex behavior. In the present study, linear genetic programming and Naïve Bayes are used in classification of liquefied and non-liquefied data. Soil and seismic parameters influencing the soil liquefaction potential are used to develop the models. Genetic Programming is the automatic creation of computer programs to perform a selected task using Darwinian natural selection. Linear genetic programming forms a peculiar subset of genetic programming where computer programs in a population are constituted as successive repetition of instructions from imperative programming language. Naive Bayes methods are supervised learning algorithms by applying Bayes’ theorem with the “naive” assumption of independence among all the sets of the features. Accuracy of results of classification for linear genetic programming, Naïve Bayes were found to be 94.12% and 90.59% respectively.

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Xi, Wei, Zongxiang Tang, Shuyao Tang, Zujun Yang, Jie Luo, and Shulan Fu. "New ND-FISH-Positive Oligo Probes for Identifying Thinopyrum Chromosomes in Wheat Backgrounds." International Journal of Molecular Sciences 20, no. 8 (April 25, 2019): 2031. http://dx.doi.org/10.3390/ijms20082031.

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Thinopyrum has been widely used to improve wheat (Triticum aestivum L.) cultivars. Non-denaturing fluorescence in situ hybridization (ND-FISH) technology using oligonucleotides (oligo) as probes provides a convenient and efficient way to identify alien chromosomes in wheat backgrounds. However, suitable ND-FISH-positive oligo probes for distinguishing Thinopyrum chromosomes from wheat are lacking. Two oligo probes, Oligo-B11 and Oligo-pThp3.93, were designed according to the published Thinopyrum ponticum (Th. ponticum)-specific repetitive sequences. Both Oligo-B11 and Oligo-pThp3.93 can be used for ND-FISH analysis and can replace conventional GISH and FISH to discriminate some chromosomes of Th. elongatum, Th. intermedium, and Th. ponticum in wheat backgrounds. The two oligo probes provide a convenient way for the utilization of Thinopyrum germplasms in future wheat breeding programs.

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Atia, Mohamed A. M., Eman A. El-Khateeb, Reem M. Abd El-Maksoud, Mohamed A. Abou-Zeid, Arwa Salah, and Amal M. E. Abdel-Hamid. "Mining of Leaf Rust Resistance Genes Content in Egyptian Bread Wheat Collection." Plants 10, no. 7 (July 5, 2021): 1378. http://dx.doi.org/10.3390/plants10071378.

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Wheat is a major nutritional cereal crop that has economic and strategic value worldwide. The sustainability of this extraordinary crop is facing critical challenges globally, particularly leaf rust disease, which causes endless problems for wheat farmers and countries and negatively affects humanity’s food security. Developing effective marker-assisted selection programs for leaf rust resistance in wheat mainly depends on the availability of deep mining of resistance genes within the germplasm collections. This is the first study that evaluated the leaf rust resistance of 50 Egyptian wheat varieties at the adult plant stage for two successive seasons and identified the absence/presence of 28 leaf rust resistance (Lr) genes within the studied wheat collection. The field evaluation results indicated that most of these varieties demonstrated high to moderate leaf rust resistance levels except Gemmeiza 1, Gemmeiza 9, Giza162, Giza 163, Giza 164, Giza 165, Sids 1, Sids 2, Sids 3, Sakha 62, Sakha 69, Sohag 3 and Bany Swif 4, which showed fast rusting behavior. On the other hand, out of these 28 Lr genes tested against the wheat collection, 21 Lr genes were successfully identified. Out of 15 Lr genes reported conferring the adult plant resistant or slow rusting behavior in wheat, only five genes (Lr13, Lr22a, Lr34, Lr37, and Lr67) were detected within the Egyptian collection. Remarkedly, the genes Lr13, Lr19, Lr20, Lr22a, Lr28, Lr29, Lr32, Lr34, Lr36, Lr47, and Lr60, were found to be the most predominant Lr genes across the 50 Egyptian wheat varieties. The molecular phylogeny results also inferred the same classification of field evaluation, through grouping genotypes characterized by high to moderate leaf rust resistance in one cluster while being highly susceptible in a separate cluster, with few exceptions.

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HAYASHI, YOSHIHARU, MIME KOBAYASHI, KATSUYOSHI SAKAGUCHI, NAO IWATA, MASAKI KOBAYASHI, YO KIKUCHI, and YOSHIMASA TAKAHASHI. "PROTEIN CLASSIFICATION USING COMPARATIVE MOLECULAR INTERACTION PROFILE ANALYSIS SYSTEM." Journal of Bioinformatics and Computational Biology 02, no. 03 (September 2004): 497–510. http://dx.doi.org/10.1142/s0219720004000703.

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We recently introduced a new molecular description factor, interaction profile Factor (IPF) that is useful for evaluating molecular interactions. IPF is a data set of interaction energies calculated by the Comparative Molecular Interaction Profile Analysis system (CoMIPA). CoMIPA utilizes AutoDock 3.0 docking program, and the system has shown to be a powerful tool in clustering the interacting properties between small molecules and proteins. In this report, we describe the application of CoMIPA for protein clustering. A sample set of 15 proteins that share less than 20% homology and have no common functional motifs in primary structure were chosen. Using CoMIPA, we were able to cluster proteins that bound to the same small molecule. Other structural homology-based clustering programs such as PSI-BLAST or PFAM were unable to achieve the same classification. The results are striking because it is difficult to find any common features in the active sites of these proteins that share the same ligand. CoMIPA adds new dimensions for protein classification and has the potential to be a helpful tool in predicting and analyzing molecular interactions.

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Journal articles on the topic 'Wheat – Classification – Computer programs'

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