Digitalization of all spheres of life has led to the fact that organizations store a large amount of information in various data sources. The process of strategic decision-making may involve an in-depth analysis of data on many items of the organization's production cycle. However, data collection in this case can take weeks. This is quite a long time for prompt decision-making. The object of the study is data stored in the corporate information system of the organization, methods of their analysis for making management decisions. The subject of the study is the automation of work with data within the corporate analytical system, the identification of data analysis patterns, as well as the design of an information analysis system of a university. The presented information analysis system will solve the problem of consolidating disparate data of corporate information systems, as well as operational data of the organization. This is ensured by the creation of a metadatabase and the formation of an information analysis system add-on using PowerBI technologies. The generally accepted design scheme of the information system was modernized demonstrating the place of the metadatabase within the corporate information system of the university. A model of data analysis based on the formation of production rules for building a decision tree on the example of human resources analysis is presented. The results of this study can be useful to analysts, executives and senior managers of large organizations in creating an analysis system for the organization's performance
This paper considers the process of developing a method to recognize the causes of plant growth deviations from normal using the advancements in artificial intelligence. The medicinal plant Aloe arborescens L. was chosen as the object of this research given that this plant had been for decades one of the best-selling new products in the world. Aloe arborescens L. is famous for its medicinal properties used in medicine, cosmetology, and even the food industry. Diagnosing the abnormalities in the plant development in a timely and accurate manner plays an important role in preventing the loss of crop production yields. The current study has built a method for recognizing the causes of abnormalities in the development of Aloe arborescens L. caused by a lack of watering or lighting, based on the use of transfer training of the VGG-16 convolutional neural network (United Kingdom). A given architecture is aimed at recognizing objects in images, which is the main reason for using it to achieve the goal set. The analysis of the quality metrics of the proposed image classification process by specified classes has revealed high recognition reliability (for a normally developing plant, 91 %; for a plant without proper watering, 89 %; and for a plant without proper lighting, 83 %). The analysis of the validity of test sample recognition has demonstrated a similar validity of the plant's classification to one of three classes: 92.6 %; 87.5 %; and 85.5 %, respectively. The results reported here make it possible to supplement the automated systems that control the mode parameters of hydroponic installations by the world's major producers with the main feedback on the deviation of the plant's development from the specified values
Розглядаються питання пiдтримки прийняття рiшень при розробцi плану розвитку вузу. Це важливо, тому що сучаснi тенденцiї розвитку органiзацiї вищої освiти постiйно змiнюються i ускладнюються. Управлiння органiзацiєю в сучасних умовах стає адаптивним, випереджувальним, стратегiчним, що вимагає перегляду iнструментiв управлiння. Основою стратегiчного планування виступає iндикативне планування, яке в свою чергу є формою, вирiшальною проблему недосконалої iнформацiї через показники, що описують об'єкт, процес або явище. Ефективне управлiння дiяльнiстю вищого навчального закладу в рамках планування включає форми i методи формування системи показникiв, що вiдображають картину стану органiзацiї. Процес розробки плану розвитку унiверситету стикається з проблемою вибору i ранжирування показникiв розвитку вищого навчального закладу, охоплює як матерiальнi, так i нематерiальнi сторони i є багатокритерiальної завданням прийняття рiшень. Для вирiшення цього завдання необхiдно вибрати метод для пiдтримки прийняття рiшень для формування системи iндикативних показникiв. Оцiнювання iндикативних показникiв здiйснюється через побудову когнiтивної карти, апрiорного ранжирування i методу аналiзу iєрархiй iз залученням експертiв зi сфери управлiння вищою освiтою. Отриманi результати порiвнюються з урахуванням переваг i недолiкiв обраних методiв. Прийняте рiшення щодо вибору методу формування показникiв полягає в спiльному використаннi методу аналiзу iєрархiй та побудовi когнiтивної карти. При гiбридному застосуваннi методiв враховується взаємний вплив показникiв i вiдповiднiсть показникiв напрямками розвитку унiверситету. Апрiорне ранжування для формування показникiв застосовувати недоцiльно, так як вiдсутнi данi про спiльне вплив один на одного декiлькох дослiджуваних показникiв. Результати дослiдження спрямованi на спрощення процесу прийняття рiшень в плануваннi: облiк вузьких мiсць при розробцi плану розвитку, пiдвищення якостi роботи i навчання, ефективне використання матерiальних i нематерiальних ресурсiв Ключовi слова: оцiнка, система, показник, управлiння, стратегiя, розвиток, iєрархiя, когнiтивна карта, рiшення
One of the important elements of the information infrastructure of educational institutions is the information and educational environment. The information and educational environment of preschool education organizations has its own characteristics, which must be taken into account when building a model for managing information processes. The object of study in this work is the information and educational environment for preschool education organizations. The problem to be solved is the need to develop a model for managing data and information processes, which will allow determining the learning outcomes of preschoolers and adjusting individual work with them. The introduction of the developed model allowed to reduce the time spent on adjusting individual work with students by 30 %. These results are explained by the optimization of information processes, as well as improved monitoring of the formation of skills of preschoolers and a reduction in the time for its implementation. When monitoring for each child, 211 indicators are examined. There are 633 indicators per year for three monitoring, in aggregate, per one child. By default, the data is entered into Microsoft Excel and processed manually. However, a large number of entries slows down the processing of Microsoft Excel data and increases the chance of errors. The use of this model will make it possible to carry out calculations automatically, save data and generate reports for each child or group of children. The developed model can be used in information and educational environments for preschool education organizations in order to improve the efficiency of monitoring and managing educational processes
Testing knowledge is an important part of the pedagogical process, as it helps to improve the quality of professional knowledge, contributes to the effectiveness and efficiency of training. This article discusses the use of several approaches to building a fuzzy diagnostic expert system for knowledge testing. The aim of the research is a comprehensive optimisation of the process of mass test information processing in order to obtain reporting data, consideration of clear and fuzzy tests, drawing the analogy between clear and fuzzy tests, proposal and justification of different schemes of summing up the testingandproposal of one's own prototype of automated expert testing system which covers all stages of the testing process. Generally speaking, testing, as an algorithmic problem, can be represented as a problem of building an expert system to evaluate knowledge of testees. Such systems are used in solving many problems related to effective management, scientific research, and the like, where it is necessary to get the result with a limited amount of reliable information. It is established that the classical theory of tests has a number of controversial assumptions, and the results of its application have serious practical drawbacks. Therefore, the main principle of the approach in the work is the separation of the creation of a bank of test tasks and the process of compiling tests (bank of test material) and testing.
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