bluuebunny/crossref_metadata_2025 huggingface dataset:
Розробка хмаро орієнтованого курсу шкільної інформатики
Authors: Зезуль І. В. , Мінтій І. С.
Published: May 2022

Метою роботи є розробка курсу дистанційної підтримки шкільної інформатики з використанням вільно поширюваних і хмаро орієнтованих засобів навчання.
Дистанційний спецкурс "Латинь. Ботанічна термінологія" як засіб становлення професійно-термінологічної компетентності вчителя біології
Authors: Перерва Вікторія Вікторівна
Published: May 2022

Виявлено сутність та переваги дистанційного навчання як однієї з форм організації самостійної роботи у професійній підготовці майбутніх фахівців. Становлення фахової терміносистеми розглядається як передумова формування професійно-термінологічної компетентності майбутнього вчителя. Наведено зміст та структуру дистанційного електронного навчального курсу «Латинь. Ботанічна термінологія» для студентів природничого факультету педагогічних закладів вищої освіти. Вивчення латині не є нормативною дисципліною навчального плану підготовки майбутнього вчителя біології, отже спецкурс покликаний до розуміння семантики та етимології біологічних термінів.
Структура навчально-польової практики підготовки майбутніх учителів біології
Authors: Перерва Вікторія Вікторівна
Published: May 2022

Професійна підготовка є основою для формування професійних умінь і навичок: формування психологічної готовності студентів до професійної діяльності; формування бази спеціальних професійних знань; розвитку практичних вмінь та навичок. Особливістю професії педагога є необхідність становлення системи професійного спілкування та взаємодії, становлення професійно-термінологічної системи. За своєю структурою фахова практика є складно організованою і передбачає різноманітні форми організації навчально-практичної діяльності: лабораторно-практичні заняття, екскурсії, самостійну та групову роботу, фенологічні спостереження, польові та демонстраційні досліди.
Педагогічні умови становлення професійно-термінологічної компетентності майбутнього вчителя біології
Authors: Перерва Вікторія Вікторівна
Published: May 2022

У статті розкрито сутність поняття «умова» та охарактеризовано зміст поняття «педагогічні умови». На основі узагальнення існуючих наукових підходів подано розуміння педагогічних умов формування професійно-термінологічної компетентності майбутніх вчителів біології в ході фахової підготовки. Визначено та обґрунтовано основні педагогічні умови формування професійно-термінологічної компетентності майбутніх вчителів біології. В статье раскрыта сущность понятия «условие» и охарактеризованы содержание понятия «педагогические условия». На основе обобщения существующих научных подходов подано понимание педагогических условий формирования профессионально-терминологической компетентности будущих учителей биологии в ходе профессиональной подготовки. Определены и обоснованы основные педагогические условия формирования профессионально-терминологической компетентности будущих учителей биологии. In the article essence of concept «condition» is exposed and maintenance of concept «pedagogical condition» is described. The generalization of existent scientific approaches the understanding of pedagogical terms of forming of professional and terminology competence of future biology teachers is given in the process of professional preparation. The main aspect of modern pedagogical research of the increasing the efficiency of the educational process problems is the identification, substantiation and verification of pedagogical conditions that ensure the success of the activity. The problem of identifying and substantiating the pedagogical conditions of professional and terminological competence of future biology teachers formation during professional training remained out of the attention of the researchers. The effective pedagogical conditions depend on the clearly determining the structure of methodological support in accordance with the ultimate goal, as well as on the implementation of an interdependent set of conditions. Considering that for the biology teacher, as well as for the doctor, Latin is the basis of professional and terminological competence.
Флористична структура рослинного покриву проммайданчику Інгулецького гірничо-збагачувального комбінату
Authors: Прилипко Вікторія Вікторівна , Перерва Вікторія Вікторівна
Published: May 2022

Ecological, biomorfical, ecology-coenotic and geographical structure of the plant groups of the industrial areas were studied taking the example of Inguletskiy OreDressing Combine. It was found out that changes of participation of ecological groups in relation to environment of life are caused by features edaphical conditions. Infringements of a vegetation and soil cause formation of groups with specific specter of biomorfs. The basic role in a vegetation of the industrial areas has of species of the ruderal coenoelement of the synantropic floroсоеnotyp
Таксономічна структура рослинних угруповань ландшафтно-техногенних систем Новокриворізького гірничо-збагачувального комбінату
Authors: Прилипко Вікторія Вікторівна , Перерва Вікторія Вікторівна
Published: May 2022

The taxonomical structure of the plant communities of the landscape-technogenic systems were found taking the example Novokryvorizky Ore-Dressing Combine. Taxonomical indexes (ratio member family/genus; family/species; genus/species) were found at the plant communities. The complication of the taxonomical structure was determined by using three entropycal indexes.
Ценотична активність видів в межах ландшафтно-техногенних систем
Authors: Прилипко Вікторія , Перерва Вікторія
Published: May 2022

Проведено аналіз ценотичної активності рослин на прикладі рослинності проммайданчику ВАТ «Новокриворізький ГЗК» (НКГЗК). Виявлено, що флористична активність видів зумовлена специфікою едафічних умов і є проявом генезису фітоценозів.
Макроморфологічні особливості ґрунтів ландшафтнотехногенних систем Південного та Новокриворізького гірничозбагачувальних комбінатів
Authors: Сметана Олексій Миколайович , Нестор Олена Олександрівна , Прилипко Вікторія Вікторівна , Перерва Вікторія Вікторівна
Published: May 2022

Досліджувались макроморфологічні особливості грунтів двох ГЗК. У складі грунтового покриву відмічені техногенні примітивні карботантні грунти. Особливостями їх генезису є формування генетичних горизонтів внаслідок осідання техногенного карбонатного пилу, зміни типу грунтоутворення через трансформацію режиму зволоження.
The Total Content of Macronutrients and Heavy Metals in the Soil on Devastated Lands at Kryvyi Rih Iron Mining & Metallurgical District (Ukraine)
Authors: Савосько Василь Миколайович , Бєлик Юлія Віліївна , Лихолат Юрій Васильович , Хайльмейер Герман , Григорюк Іван Панасович , Хромих Ніна Олександрівна , Лихолат Тетяна Юріївна
Published: May 2022

The relevance of the research is due to the need to develop technologies for phytoremediation of the devastated lands in the mining and metallurgical regions of Ukraine and the world. In this regard, the creation of tree plantations adapted to the ecological conditions of such territories is considered by many experts as the most promising option for innovative technologies. However, the development of artificial woodlands requires knowledge of the pedogeochemical character- istics of devastated lands. The aim of the work was to carry out a comparative analysis of the macronutrients and heavy metals gross forms content in the soils of the devastated lands of the Kryvyi Rih mining and metallurgical region. The field studies focused on five contrasting monitoring sites of the Petrovsky dump (Central Kryvorizhzhya), which has a typical age and composition of rocks for the region. Soil sampling, drying, sieving, and sample preparation (sintering in a muffle furnace) were done in accordance with classical techniques. The concentrations of macronutrients (potassium, sodium, calcium, magnesium, sulfur, and phosphorus) and heavy metals (iron, manganese, zinc, copper, lead, and cadmium) were determined using an Inductively Coupled Plasma Mass Spectrometry (ICP- MS) X-Series 2 (Thermo Fisher Scientific, USA). The analytical part of our research was carried out on the basis of the laboratory of the Institute of Biosciences, Freiberg University of Technology and Mining Academy (Freiberg, Germany). At monitoring sites, significant differences were found in the content of macronutrients gross forms, and their variation relative to the control values as well. Potassium and sodium concentrations generally differed slightly or were close to control levels. The results of determining the content of calcium, magnesium and phosphorus indicate a significant deficiency or excess of these macronutrients in the soils of the devastated lands. An increased sulfur content was found in the soils of all monitoring sites, in some cases 4 times higher than the control level. The measured content of gross forms of iron, manganese, copper, cadmium and, partially, zinc in the soils of different monitoring sites exceeded the control values by 5.5 – 5.9 times. Thus, the analysis of the research results made it possible to establish that the soils of the devastated lands of the Petrovsky dump are characterized by unfavorable properties for the growth of most species of woody plants.
Про деякі важливі педагогічні пам'ятки для сучасного вчителя праці
Authors: Пікельна Валерія Семенівна
Published: May 2022

Висвітлено деякі важливі педагогічні пам'ятки для сучасного вчителя праці.
Технологія управління пізнавальною діяльністю у системі модульного навчання
Authors: Пікельна Валерія Семенівна
Published: May 2022

Висвітлено особливості технології управління пізнавальною діяльністю у системі модульного навчання.
Гуманістична педагогіка і гуманізація навчально-виховного процесу в сучасній школі
Authors: Пікельна Валерія Семенівна
Published: May 2022

У статті розглядаються питання гуманістичної педагогіки та гуманізації навчально-виховного процесу в сучасній школі.
Одвічні мрії про "дитину вільну". Ще раз до проблеми гуманізації
Authors: Пікельна Валерія Семенівна
Published: May 2022

Розглянуто проблеми гуманізації та виховання «вільної особистості».
Настанови здорового способу життя в сучасній екологічній освіті
Authors: Темченко Валентина Максимівна , Шанда Володимир Іванович , Пікельна Валерія Семенівна , Корольська Людмила Романівна
Published: May 2022

У статті розглядаються питання змісту настанови здорового способу життя в сучасній екологічній освіті.
"... Никакая система воспитательных средств не может быть установлена навсегда": о некоторых рекомендациях А. С. Макаренко "педагогическому руководителю"
Authors: Пікельна Валерія Семенівна
Published: May 2022

Висвітлено педагогічні погляди А. С. Макаренка.
Криворізький державний педагогічний університет: вчора, сьогодні і завтра
Authors: Шевченко Павло Іванович
Published: May 2022

Розглянуто питання становлення, розвитку КДПУ, наукової та навчально-педагогічної діяльності.
В. А. Сухомлинский о воспитании духовности у школьника
Authors: Шевченко Павло Іванович
Published: May 2022

Висвітлено питання про виховання духовності у школярів у педагогічних поглядах В. О. Сухомлинського
Трудове виховання в педагогічній спадщині С. Ф. Русової
Authors: Шевченко Павло Іванович
Published: May 2022

Розкрито питання трудового виховання в педагогічній спадщині С. Ф. Русової.
В. О. Сухомлинський про розумове виховання
Authors: Шевченко Павло Іванович
Published: May 2022

Висвітлено педагогічні погляди В. О. Сухомлинського про розумове виховання.
Профільне навчання учнів в 10-12 класах середньої загальноосвітньої школи
Authors: Шевченко Павло Іванович
Published: May 2022

Охарактеризовано особливості профільного навчання учнів в 10-12 класах середньої загальноосвітньої школи.
Джон Локк про трудове виховання
Authors: Шевченко Павло Іванович
Published: May 2022

Висвітлено педагогічні погляди Джона Локка про трудове виховання.
Проблеми виховання духовності в процесі трудової діяльності в педагогічній спадщині В. О. Сухомлинського
Authors: Шевченко Павло Іванович
Published: May 2022

Визначено проблеми виховання духовності в процесі трудової діяльності в педагогічній спадщині В. О. Сухомлинського
INFLUENCE OF HEAT TREATMENT ON DYNAMIC PROPERTIES OF TIN-FREE BRONZE. MULTIFRACTAL PARAMETERIZATION OF THE STRUCTURES OF DESTROYED SAMPLES
Authors: Smakovskiy M.S. , Bragov A.M. , Konstantinov A.Yu. , Kuznetsov A.V. , Lomunov A.K. , Savenkov G.G.
Published: May 2022

The results of experimental studies of the dynamic characteristics of tinless bronze of the BrAZhNMts 9-4-4-1 brand of two types (in cold-rolled and annealed states) at different strain rates are presented. An experimental determination of the dynamic characteristics of bronze was carried out using a modification of the Kolsky method for dynamic tension using a split Hopkinson pressure bar. Tests were carried out with different strain rates up to rupture of the samples. It has been found that for both states, an increase in the strain rate leads to a significant change in the mechanical characteristics. The material after annealing showed a decrease in strength properties compared to the initial state by 20–22%. Compared to the static standard characteristics, the dynamic reduction in area has increased for both types of metal condition, and the dynamic reduction in area in the annealed state is 18–25% higher than the reduction in the cold-rolled state, i.e. in the annealed state, bronze is more ductile, which fits into the traditional theory of heat treatment. After dynamic testing, the fractured specimens were cut along the central tensile axis along the diameter so that the analytical sections (surfaces of the specimens that are ground, polished and chemically etched to reveal the structure or defectiveness of the specimens) were perpendicular to the fractures. The microstructural analysis of the destroyed samples and multifractal parametrization of their structures were carried out. On the basis of multifractal analysis in terms of the latent ordering parameter, it was found that the annealed state is less resistant to structural phase transition than the cold-rolled state. In annealed samples, a larger number of excited local regions appear, in which the hydrodynamic nature of the flow is possible and, as a result, such samples are more plastic.
ON CONTACT PROBLEMS WITH DEFORMABLE STAMP
Authors: Babeshko V.A. , Evdokimova O.V. , Babeshko O.M.
Published: May 2022

This paper presents one of the methods for studying the behavior of deformable stamps on a deformable base. It is based on a new universal modeling method previously published by the authors, used in boundary value problems for systems of partial differential equations. Its advantage is the possibility of avoiding the need to solve complex boundary value problems for systems of differential equations by replacing them with separate differential equations, among which the Helmholtz equations are the simplest. With the help of combinations of solutions of boundary value problems for this equation, it is possible to describe the behavior of complex solutions of multicomponent boundary value problems, including for cracks of a new type formed by objects on a deformable base, and models of nano particles located on deformable multicomponent bases. However, without the ability to solve contact problems for deformable stamps, these models are not built. The mixed problem is reduced to the solution of the Wiener–Hopf integral equation. Two cases are considered: the case of a large-width strip stamp and the case of a semi-infinite stamp. A packed block element is accepted as a deformable stamp, as a solution of the Helmholtz equation in the specified area. Mechanically, it can be imitated as a membrane that is located on a multilayer medium occupying the contact area. A combination of such objects can be used to describe solutions to the contact problem for flat deformable objects of more complex rheology, as well as for three-dimensional ones. Along with the proof of constructing an exact solution to the contact problem under consideration, the appearance of unknown functionals is noted in the course of the study. In problems with an absolutely solid stamp, they do not occur. The paper finds a way to determine them and an analytical representation of them is obtained. It is suggested that their appearance will be typical for solving other contact problems with deformable stamps. The features of the method and the results obtained are discussed.
NUMERICAL SIMULATION OF FATIGUE DURABILITY OF PARTS OF AVIATION GAS TURBINE ENGINES UNDER CYCLIC TWOFREQUENCY LOADING
Authors: Boev E.V.
Published: May 2022

The problem of assessing the resource characteristics of responsible engineering facilities, taking into account the peculiarities of operational loading modes, is discussed. The processes of fatigue durability of polycrystalline structural alloys under cyclic two-frequency loading (with the combined action of mechanisms of low and multi-cycle fatigue) are considered.

A mathematical model describing the processes of cyclic elastoplastic deformation and accumulation of fatigue damage in structural alloys under multiaxial disproportionate modes of combined thermomechanical loading has been developed from the modern positions of damaged medium mechanics and fracture mechanics. The model consists of three interrelated parts: relations determining the cyclic elastic-plastic behavior of the material, taking into account the dependence on the destruction process; evolutionary equations describing the kinetics of fatigue damage accumulation; criteria for the strength of the damaged material.

The variant of the defining elastic-plasticity relations is based on the idea of the yield surface and the principle of gradiency of the velocity vector of plastic deformations to the yield surface at the loading point. This version of the equations of state reflects the main effects of cyclic elastic-plastic deformation of the material for arbitrary folded loading trajectories.

The variant of kinetic equations of fatigue damage accumulation is based on the introduction of a scalar damage parameter, is based on energy principles and takes into account the main effects of formation, growth and fusion of microdefects under arbitrary complex cyclic loading regimes. A joint form of the evolutionary equation of fatigue damage accumulation in the areas of low- and multi-cycle fatigue is proposed.

As a criterion of the strength of the damaged material, the condition of reaching the critical value of the damage value is used.

The results of numerical simulation of fatigue durability of a compact sample (model of the disk deflector of the high pressure turbine of an aviation gas turbine engine) are presented with cyclic two-frequency loading. The results of the comparison of the calculated and experimental data showed that the proposed model qualitatively and with the accuracy necessary for practical calculations quantitatively describes the fatigue life of structural elements under cyclic two-frequency loading.
ANALYSIS OF EXPERIMENTAL DATA TO EQUIP A MATHEMATICAL MODEL OF WOOD WITH DEFORMATION AND STRENGTH PARAMETERS
Authors: Kibets A.I. , Kalinina Yu.A. , Vutcin L.I. , Kruszka L.
Published: May 2022

Wood due to a number of specific properties (relatively low density, relatively high strength, low thermal conductivity, manufacturability) has become widespread not only in construction, but also in some areas of technology. Every year, a huge number of containers with radioactive substances, spent nuclear fuel, ammunition components, etc. are transported in the world. Ensuring the safety of transporting such substances and products by air, road, sea and rail transport is of great importance due to the potential risk of damage during transportation damage to people, the environment and property. The design of the container must withstand, without depressurization and damage to the contents, significant dynamic loads that may occur during an emergency fall of the container from the vehicle or during unloading and loading operations. As one of the damping materials that can mitigate the consequences of such intense dynamic effects on containers and their contents, wood is used, since the property is deformed under compression across the fibers up to 30–40%, and for some species up to 70%, at almost constant stress, limits the load transmitted through it by the value of the tensile strength. In order to reliably calculate the behavior of containers in this case, data are needed on the properties of the wood used under impact, in particular, dynamic deformation diagrams. The purpose of this work is to analyze publications containing the results of an experimental study of wood deformation to identify parameters and subsequent verification of its mathematical model as a unidirectionally reinforced elastoplastic material implemented in the Dynamics-3 computer complex.
An Evaluation of Health Risks of Nano Building Products Used for IAQ Management in Smart Environment
Authors: Bilgin Sezgin , Tuna Taygun Gökçe , Vural S. Müjdem
Published: May 2022

Smart technologies create controlled and sustainable systems to meet rapid urbanisation and various needs arising from this urbanisation throughout the world. Some of these systems are realised with nano-technology. Especially in the construction industry, nano products are used in smart building and smart material applications. Some of the products developed with this technology are also used to control indoor air. However, it is seen that nano-sized materials produced artificially with nano-technology have possible health risks on the environment and human health due to various unknowns. In addition, nanomaterials in the content of nanoproducts, can enter the human body through respiration, ingestion and skin contact due to their very small size. This chapter examined the possible effects of nanomaterials in sensors and healing nanoproducts produced to control indoor air quality on user health. The role of nano-smart materials in sustainable building design was evaluated. With the data obtained in this context, it aims to reveal the positive and negative situations caused by the use of nanoproducts to benefit from their improved properties and allow users to make choices considering this information.
Blast Mitigation Using Crushable Core Systems
Authors: Ousji Hamza , Belkassem Bachir , Pyl Lincy , Lecompte David
Published: May 2022

Among several blast mitigation methods, the use of lightweight layers, in particular sacrificial cladding, are investigated. The latter consists of a crushable core sandwiched between a front plate and the structure. This paper presents an optimal sacrificial cladding design required to protect a given structural element against a free-air blast loading. The structure property, the fluid-structure interaction and the blast loading are taken into account.
Automated Exploratory Data Analysis
Authors: Dhillon Hubble
Published: May 2022

This study introduces a novel framework that can be generalized for an automated exploratory data analysis to test a given hypothesis. The current work is about a drug-related trend and also provides a specific model to test a motivation-related hypothesis in the case of COVID-19. With the utilization of the right, appropriate, and optimized solution available to solve a problem, it is significant that the user feels motivated to delve into the solution for the betterment of society.

KEYWORDS: automated exploratory data analysis, motivation-related hypothesis
Integration of Blockchain with Big Data Free Schema
Authors: Naqvi Muhammad Raza , Rana Zahoor Ahmad , Tahir Muhammad Usman
Published: May 2022

Security, immutability, and nature present numerous   difficulties. Big data in monetization is still among the biggest concerns for large of dataset management .Large organizations easily convert unstructured data sets into   structured   data   sets. Still   the problems are faced in smart services in searching of reliable big data solutions. Security   and privacy   are   the   main concerns of cybersecurity.  The main problem of integrating blockchain with big data free schema is how big data can be transferred to the blockchain model with complete assurance of privacy,    security,    and    integrity.    It requires   an   architectural model   that paves the way    to    decentralized, immutable and secure data modeling. Blockchain     is relatively a new technology, guaranteeing integrity and ensuring security in    the    field    of information systems. Its first implementation is bitcoin as a crypto consensus     model in     which the computational evaluation of currency has gained a lot of attention. Blockchain mining     and approving     exchanges comprise a   distributed   system   that contains connections. This article opens new     paths into the blocks     of transactions. Immutability, authentication and distributed consensus are the main characteristics of blockchain.
Computational Techniques and their Usage to Optimize Car Design for Better Performance
Authors: Muhammad Uzair Riaz  , Manzoor Tareq , Muhammad Umair  , Hasan Ali  , Ammar Iqbal
Published: May 2022

This paper describes the use of different computational fluid dynamics (CFD) models and other techniques that can be used to get low coefficient of drag. The upper body of a car is designed using surface modeling in CATIA. It is analyzed using K-epsilon realizable model in ANSYS Fluent. Changes in design are made based on the high coefficient of drag at high speeds. Then, K-epsilon realizable model is used for analysis. To get better accuracy, a refined mesh for the wake region is used. Afterwards, k-omega standard model is used. At the end, the upper body of the passenger car and its tyres are examined to get the final results of the coefficient of drag. The same design with the same meshing conditions is also analyzed in Star CCM+ to verify the results.

INDEX TERMS: ANSYS Fluent, computational fluid dynamics (CFD), coefficient of drag, Star CCM+
ReqSpecOnto: Investigating Explicit Software Requirements Specification
Authors: Ahmed Usman , Amjad Farooq  , Tayyaba Farhat
Published: May 2022

Specification of customer's need as software requirements in natural language create ambiguities in requirements and may also lead to failure of the software project. Generally, customers are unable to define their needs due to lack of domain understanding, technological constraints and knowledge gap between stakeholders and requirements analysts. One of the most effective approaches to minimize these gaps and ambiguities is the usage of ontologies for requirements specification and validation. However, the current approaches are mostly limited only to the translation of ambiguous software requirements. In this paper, we have discussed, analyzed and compared the current usage of these ontologies and found that these approaches are time-consuming and create complexities in the overall development process. We have presented a requirements specification ontology (ReqSpecOnto), bypassing the need for creating an ambiguous Software Requirement Specification (SRS). The upper software requirements ontology is defined in Ontology Web Language (OWL) that can be applied in different software scenarios. A case study of budget and planning system for a state physics lab is selected to specify its requirements as derived ontology from the upper ontology created. Results are validated through HermiT and Pellet reasoners to verify defined relationships and constraints. Finally, SPARQL queries are used to obtain the necessary requirements.
Mandatory vaccinations, the segregation of citizens and promotion of inequality in the modern democracy of Greece and other democratic countries. Is it ethical for the scientific community to "enforce" or silently back-up such policies?
Authors: Mavridis Charalampos , Aidonidis Georgios , Kalogeridis Athanasios
Published: May 2022

During the COVID-19 pandemic, Greek authorities enforced a vaccination mandate for healthcare workers (HCWs), and “social occlusion” of the unvaccinated citizens in general. At the same time, multiple concerns have been raised about the epidemiological profile of Greece, the condition of public health, the ethical status of segregation policies and the role that the expert panel should play. We discuss how the policy of putting unvaccinated HCWs on unpaid suspension, the inequality and the segregation of citizens could harm social, physical, mental and spiritual healthcare in civilized societies. We would also like to invite the scientific community to an open and broad discussion and a critical debate based on the questions raised.
YIELD TRAITS OF SOYBEAN CULTIVATED UNDER BRACHIARIA AND MILLET STRAW AND POTASSIUM DOSES
Authors: Firmiano Raquel Silva , Mesquita Glaucia Machado , Rios Anderli Divina , Buso Wilian Henrique Diniz
Published: May 2022

There are many doubts about which straw-supplying species should be cultivated in a no-tillage system and which potassium doses are adequate for the Cerrado soils. Therefore, the current study aimed to evaluate the agronomic traits (plant height, first pod insertion height, and stem diameter); yield traits (number of pods per plant, number of grains per pod, and 100-grain weight), grain yield (kg ha-1) and potassium content in the leaves, in the production of soybean cultivated in different straws and potassium doses in two crop seasons under Cerrado conditions in the region of Ceres, Goiás, Brazil. Two types of straw (Brachiaria and millet) and four potassium doses were evaluated. A randomized complete block design arranged in a 2x2x4 factorial scheme with four repetitions was used. Two crop seasons (2011/2012 and 2012/2013), two types of straw (Millet and Brachiaria), and four potassium doses (0, 30, 60, and 90 kg ha-1 of K2O using KCl as source) were evaluated. Phosphate fertilization was performed using 400 kg ha-1 of simple superphosphate, and the cultivar used was P98Y12. The largest plant height values were obtained by applying 90 kg ha-1 of K2O. The Brachiaria straw promoted a grain yield increase associated with the potassium doses increment. The highest grain yield was 4,353.90 kg ha-1, achieved by applying 65 kg ha-1 of K2O using millet straw. The highest grain yield reached was at the rate of 90 kg ha-1 of K2O, resulting in 5,208 kg ha-1. The greatest K accumulation in the leaf is provided by Brachiaria straw.
Application of the growth regulator “Edagum SM” on winter wheat crops in the Republic of North Ossetia – Alania
Authors: Tedeyeva A. , Tedeyeva V.
Published: May 2022

Abstract. The authors present the results of the use of a growth regulator on winter wheat crops in the conditions of the steppe zone of the Republic of North Ossetia – Alania. The purpose of the work is to study the influence of the growth regulator “Edagum SM” on the growth, development, productivity and quality of grain of promising winter wheat varieties, taking into account ecological and economic efficiency and improving on this basis the resource-saving technology of culture cultivation in the conditions of the steppe zone of the Russian Federation. The novelty lies in the fact that the features of the growth and development of promising winter wheat varieties have been studied depending on the doses of the growth regulator “Edagum SM” and their effect on the photosynthetic activity of plants has been shown. Optimal seeding rates of promising varieties have been established, ensuring high crop productivity and improving the quality indicators of the products obtained. The object of research were high-yielding varieties of winter wheat – Homer and Bagrat, selected by the P. P. Lukyanenko National Research Center. Methods. Records and observations were carried out according to generally accepted methods described in the educational and methodological manual for conducting research in agronomy. Results. As a result of the use of a growth regulator, for Homer and Bagrat varieties, the best option is “Edagum SM” (450 ml/ha), and the optimal seeding rate is 5 mln/ha (Gomer variety) and 4 mln/ha (Bagrat variety). The greatest increase in photosynthetic power was observed during the period of exit into the tube-earing. The net photosynthesis productivity of winter wheat increased from the tillering phase to the exit phase into the tube and the maximum indicators reached during earing-milk ripeness. The crop yield, depending on the dose of the growth regulator, increased by 0.13–0.22 t/ha (Homer variety, seeding rate 3 mln/ha). The grain nature index, depending on the studied variants, varied between 691–722 g/l (Homer variety) and 689–720 g/l (Bagrat variety). The protein content varied in the range of 10.1–13.2 % a. s. v., and gluten – 24–26 %. Profitability ranged from 22–47 %.
Domain Adaptive Scene Text Localization in Night View Images
Authors: Alowaidi Majed , Alshehri Mohammed
Published: May 2022

Scene text localisation in a night is a challenging problem and a less explored problem in the area of robust reading. The day and night images have a different distribution. Hence, a domain shift exists from day to night images. This paper introduces a domain adaptation network (DAN) to learn the domain shift from day images to night images. The proposed sub-network DAN can be attached to any existing state-of-theart text detector to learn the domain shift from day to night. For the training of the DAN, synthetic data generation has been done by utilising the generative adversarial network. The proposed method has been extensively validated on the public as well as on the synthetic datasets. The proposed DAN improves the performance of the underline text localisation model with a margin of 1.4-4.0%, 0.1-1.0%, and 0.1-3.1% on LP Night Dataset, ICDAR2015, and Total-Text benchmarking datasets.
Extracting Sections of Simulated Driving Routes that Elicit Driving Responses Predictive of ADHD via Recursively Constructed Ensembles
Authors: Grethlein David
Published: May 2022

In this paper we introduce a novel algorithm called Iterative Section Reduction (ISR) to automatically identify spatial regions wherein time series were recorded that are predictive of a target classification task. Specifically, using data collected from a driving simulator study, we identify which spatial regions (dubbed sections) along the simulated routes tend to manifest driving behaviors that are predictive of the presence of Attention Deficit Hyperactivity Disorder (ADHD). Identifying these sections is important for two main reasons: (1) to improve predictive accuracy of the trained ADHD screening models by filtering out non-predictive time series data, and (2) to gain insights into which on-road scenarios (dubbed events) elicit distinctly different driving behaviors from patients undergoing treatment for ADHD versus those that are not. Our experimental results show both improved classification performance over prior efforts and good alignment between the predictive sections identified and scripted on-road events in the simulator (negotiating turns and curves).
Class-incremental Learning using a Sequence of Partial Implicitly Regularized Classifiers
Authors: Bobiev Sobirdzhon , Khusainova Albina , Khan Adil , Ahsan Kazmi S.M.
Published: May 2022

In class-incremental learning, the objective is to learn a number of classes sequentially without having access to the whole training data. However, due to a problem known as catastrophic forgetting, neural networks suffer substantial performance drop in such settings. The problem is often approached by experience replay, a method that stores a limited number of samples to be replayed in future steps to reduce forgetting of the learned classes. When using a pretrained network as a feature extractor, we show that instead of training a single classifier incrementally, it is better to train a number of specialized classifiers which do not interfere with each other yet can cooperatively predict a single class. Our experiments on CIFAR100 dataset show that the proposed method improves the performance over SOTA by a large margin.
Tractable Inference for Hybrid Bayesian Networks with NAT-Modeled Dynamic Discretization
Authors: Xiang Yang , Zheng Hanwen
Published: May 2022

Hybrid BNs (HBNs) extend Bayesian networks (BNs) to both discrete and continuous variables.Among inference methods for HBNs, we focus on dynamic discretization (DD) that converts HBN to discrete BN for inference.Complexity of BN inference is exponential on treewidth, which extends to DD for HBNs.We presents a novel framework where HBN is transformed into NAT-modeled BN (NAT: Non-impeding noisy-AND Tree) for tractable inference.A case-study under the framework is presented on sum of continuous variables.We report significant efficiency gain of approximate inference by NAT-modeled DD over alternative methods.
Tracking using Human Pose Matching with Deep Association Metric
Authors: Jain Atishay , Dhiman Abhishek , Pailla Balakrishna
Published: May 2022

This paper proposes a novel approach to track multiple people utilizing skeletal information combined with visual appearance features to improve the accuracy of tracking people across different frames of a video. We extracted the appearance feature vectors and skeletal feature vectors for each detected person in every frame. Each individual was tracked by considering the cosine distance between the skeletal feature vectors along with the euclidean distance between the appearance feature vectors across different frames of a video. This reduces the dependency of the tracker over appearances of people thus making it more consistent, especially in videos with people having similar appearances such as sports videos with players wearing similar jerseys. The stance of an individual in continuing frames is expected to be similar considering the high frame rate of modern camera devices. Therefore it is befitting to consider skeletal features along with appearance features for tracking. Our paper is an incremental paper demonstrating improvement over SORT with a deep association metric approach. Our approach utilizing skeletal information combined with visual appearance information returns better MOT results on the MOT17 dataset using the yolov3 detector.
Customer Appointment Analysis in Automobile Dealerships
Authors: Saha Priya , Hubele Joachim , McDonald Stephen
Published: May 2022

Appointment scheduling prior to in-person visit to vehicle service centers is a well-known activity in our daily lives; we often do that to save our- selves time during our visits. Prior knowledge of customer arrivals help the service store manage- ment navigate through their daily demand and estimate a revenue goal. However in real-world, several people end up missing their appointments. To avoid business losses, dealers often practise en- gaging with customers beyond their capacity, but it only leads to operational inefficiency. In our work, we extrapolate several vehicle dealer stores that have high as well as low missed appointment rates and show interesting customer visit patterns post-scheduling. Additionally, we propose a Ma- chine Learning based solution to empower deal- ers with optimal allocation of appointment slots among their customers and generate maximum revenue from the arrangement. Our motivation in the paper is to enhance the daily service demand process in the dealerships with excellent customer care.
On Information Hiding in Natural Language Systems
Authors: Bihani Geetanjali , Rayz Julia Taylor
Published: May 2022

With data privacy becoming more of a necessity than a luxury in today's digital world, research on more robust models of privacy preservation and information security is on the rise. In this paper, we take a look at Natural Language Steganography (NLS) methods, which perform information hiding in natural language systems, as a means to achieve data security as well as confidentiality. We summarize primary challenges regarding the secrecy and imperceptibility requirements of these systems and propose potential directions of improvement, specifically targeting steganographic text quality. We believe that this study will act as an appropriate framework to build more resilient models of Natural Language Steganography, working towards instilling security within natural language-based neural models.
On Heuristics for Parsing-based Verification of Hierarchical Plans with a Goal Task
Authors: Ondrčková Simona , Barták Roman , Bercher Pascal , Behnke Gregor
Published: May 2022

Verification of hierarchical plans deals with the problem if a given action sequence is a valid hierarchical plan – the action sequence can be obtained by decomposing a particular (goal) task using given decomposition methods. The existing parsing-based verification approach greedily composes actions until it obtains the goal task. Greediness implies that this approach alsogenerates tasks unrelated to the goal task. In this paper, we study the use of heuristics when creating new tasks. We also ask whether the prior knowledge of the goal task improves efficiency.
Language-independent Metric for Measuring Text Simplification that does not Require a Parallel Corpus
Authors: Mucida Lucas , Oliveira Alcione , Possi Maurilio
Published: May 2022

Natural language processing encompasses several tasks, one of which is the automatic text simplification. Telling whether one text is simpler than another involves not only knowledge about the language being analyzed, but also a cultural knowledge of the target audience to which the text is being directed. Most of the current metrics used to measure text simplification are based on the use of parallel corpora, prepared by humans, which makes it difficult to apply the metrics in automatic text simplification in real time. In this paper, we present ISiM (Independent Simplification Metric), a metric that dismiss a parallel corpus, is simple, fast, language and human annotation independent, capable of quantifying the simplicity/complexity of a sentence, thus contributing improve automating text simplification. The results of the tests performed indicate that the proposed metric has the potential to be used to evaluate automatic methods of simplification.
Towards Machine Learning Interpretability for Tabular Data with Mixed Data Types
Authors: Pokhrel Prativa , Lazar Alina
Published: May 2022

Gradient Boosting (GB) algorithms have been proposed for a variety of automated predictions and classification tasks with applications in many domains. These methods work faster and provide superior performance compared to deep learning methods when applied to tabular datasets. Another advantage is their interpretability. There are many machine learning methods that can train tabular data successfully, however, the inner workings are usually hidden from the user. In this context, SHAP values combined with GB methods, increase model transparency and provide not only consistent feature rankings but also show the contributions of the predictors for individual instances. In this work, we train multiple GB models using several tabular datasets and compare the result in terms of speed, performance, and the global and local models' interpretability.
An Introduction to Graph Neural Networks
Authors: Lazar Alina
Published: May 2022

Graph Neural Networks (GNNs) are considered a subset of deep learning methods designed to extract important information and make useful predictions on graph representations. Researchers have been working to adapt neural networks to operate on graph data for more than a decade. Most practical applications come from the areas of physics simulations, object detection and recommendation systems. Given the extended application areas, GNNs are one of fastest growing and most active research topic, that attracts increasing attention not only from the machine learning and data science community, but from the larger scientific community as well. The materials for this tutorial will be selected and organized for researchers with no prior knowledge of GNNs. Further reading, applications and most popular software packages and frameworks will also be discussed.
Exploration of AI-enabled Contents for Undergraduate Cyber Security Programs
Authors: Lasisi Ramoni , Menia Matthew , Farr Zachary , Jones Corey
Published: May 2022

This paper investigates the AI courses and/or topics that are needed to enhance cybersecurity education towards preparation of the future AI-enabled cybersecurity leaders.~We found that, although sophisticated cyber crimes are now been perpetrated using AI technologies, AI courses and topics are currently missing in virtually all the undergraduate cybersecurity programs we reviewed.
Discovering Breach Patterns on the Internet of Health Things: A Graph and Machine Learning Anomaly Analysis
Authors: Lamichhane Prabin B , Mannering Hannah , Eberle William
Published: May 2022

Due to the rise in the Internet of Health Things (IoHT), cyber-attacks, particularly data intrusions, have become an issue for security experts. In this work, we analyze the performance of traditional statistical, machine learning, and graph-based anomaly detection approaches in response to this problem. We believe that understanding intrusion patterns can aid in the prevention of future attacks. In this work, we use the ARMA model for statistical analysis. We also use several machine learning approaches such as multinomial naive bayes, ran- dom forest, neural networks, XGBClassifier, and support vector machines (SVM). However, while our experiments show that machine learning (ML) techniques have higher precision, accuracy, and F1 score than graph-based techniques, there are aspects to a graph-based approach that could aid security experts in the discovery of certain data breaches by combining the graph-based with the statistical and ML methods. Experiments also show combining different anomaly detection techniques allows for a diverse set of intrusion patterns to be discovered. By recognizing the power of both machine learning and graph-based approaches, we analyze their precision and accuracy while explaining how existing state-of-the-art methods can detect breach patterns. Finally, by identifying the characteristics of breach patterns, we present information that security experts can use to prevent future data intrusions.
Temporal Alignment and Demonstration Selection as Pre-Processing Phase for Learning by Demonstration
Authors: Donjat Jérémie , Legeleux Amélie , Buche Cédric , Duhaut Dominique
Published: May 2022

Robots can benefit from users’ demonstrations to learnmotions. To be efficient, a pre-processing phase needsto be performed on data recorded from demonstrations.This paper presents pre-processing methods developedfor Learning By Demonstration (LbD). Thepre-processing phase consists in methods composedof alignment algorithms and algorithms that select thegood demonstrations. In this paper we propose sixmethods and compare them to select the best one.
Pseudo-visibility: A Game Mechanic Involving Willful Ignorance
Authors: Alexander Samuel , Pedersen Arthur Paul
Published: May 2022

We present a game mechanic called pseudo-visibility for games inhabited by non-player characters (NPCs) driven by reinforcement learning (RL). NPCs are incentivized to pretend they cannot see pseudo-visible players: the training environment simulates an NPC to determine how the NPC would act if the pseudo-visible player were invisible, and penalizes the NPC for acting differently. NPCs are thereby trained to selectively ignore pseudo-visible players, except when they judge that the reaction penalty is an acceptable tradeoff (e.g., a guard might accept the penalty in order to protect a treasure because losing the treasure would hurt even more). We describe an RL agent transformation which allows RL agents that would not otherwise do so to perform some limited self-reflection to learn the training environments in question.