bluuebunny/crossref_metadata_2025 huggingface dataset:
Prospects for pharmacological screening of oral detoxification drugs with differentiation of targeted pathologies in animal husbandry
Authors: Popova O. S. , Ukrainskaya O. A.
Published: April 2024

In the modern livestock sector, the domestic industry of the North-West region, cases of poisoning of animals on farms and large complexes are increasingly occurring. This is primarily due to the intensive use of various synthetic modulators, growth stimulants, fertilizers in the agronomic industry and the excessive use of antibiotics, hormones and other veterinary drugs in animal husbandry.

Pharmacological screening of oral detoxification agents with differentiation of target pathologies is a promising direction in the development of domestic animal husbandry. A reasonable choice of sorbents in each individual case of poisoning allows you to quickly achieve a therapeutic effect, reduce the toxic load on the animal’s body, which further ensures sustainable productivity and high quality products. This work highlights the results of some studies on the functional activity of the most common enterosorbents in relation to toxins of various natures.

Based on the results of the study, it was noted that with an increase in pH from 2.0 (rennet model) to 7.5 (analogue of the distal small intestine), a release of part of the indicator substance from the pores of the sorbent (desorption) is observed, which reduces its absolute sorption effect [5] . The lowest desorption value was shown by atoxyl (8.5%) and phytopos (9.0%). That is why these drugs are the most effective oral detoxification agents for toxins with a molecular weight close to methylene blue.

The maximum adsorption effect for various poisonings in animals can be achieved by using sorbing agents that are highly selective for a particular toxin. Research on the choice of oral detoxification agents with differentiation of target pathologies significantly expands the database on existing sorbents, makes it possible to prevent and treat poisonings of various types more effectively, and provides opportunities for the combined use of various adsorbent substances.
Study of Tildox AVZ effect on rat blood parameters in a subchronic experiment
Authors: Tokareva O. A.
Published: April 2024

The purpose of our research was to study the effect of Tildox AVZ on rat blood counts in a subchronic experiment. Tildox is a complex antibiotic in powder form. One gram of drug contains doxycycline hyclate – 100 mg and tylosin tartrate - 100 mg as active ingredients, sodium benzoate and sucrose as auxiliary substances. The experiment lasted 90 days. The study was conducted on 150 Wistar rats (75 males and 75 females). The body weight of the animals was 190-230 g. During the experiment 5 groups of 30 animals (15 males and 15 females) were formed, three of them were experimental groups, one - control and one – intact. Of the 150 rats involved in the experiment after its completion 100 individuals (50 males and 50 females) were killed for pathomorphological studies of internal organs.

To identify the ability to recover and the appearance of resistance to toxic effects the remaining 50 animals (5 males and 5 females from each group) were monitored for 28 days after the experiment.

An aqueous solution of the test sample of the drug was administered daily intragastrically using an atraumatic metal probe. The drug was administered to the first experimental group at a dose of 70 mg / kg, the second group - 265 mg / kg, the third group - at a dose of 1000 mg / kg of animal body weight. The control group was in equal conditions and received intragastric saline solution. Intact animals served as a reference. It was found that Tildox AVZ administered intragastrically at doses of 265 and 1000 mg / kg 1 time per day for 90 days has an effect on clinical and biochemical blood parameters. The drug administered at a dose of 70 mg / kg does not cause changes in blood parameters. However when examining the blood of rats 28 days after the recovery period there were no significant changes in clinical and biochemical parameters compared with the control and intact groups.

From this it can be concluded that all blood changes had a dose-dependent effect and after stopping the use of the drug the body recovered which indicates the reversibility of the caused shifts in the blood picture.
Information Search Knowledge and Agricultural Education Students’ Use of Public Library in Cross River State, Nigeria
Authors: I. Ajigo , J. O. Ajigo , E. E. Egbonyi
Published: April 2024

The study determined the influence of information search knowledge on agricultural education students’ use of public libraries in Cross River State, Nigeria. To achieve the purpose, two research questions and two hypotheses were formulated. This study adopted a survey research design. All the 96 final year agricultural education students of the two public universities in Cross River State were purposely selected for the study. A validated questionnaire titled “Information Search Knowledge and Agricultural Education Students’ Use of the Library Questionnaire (ISKAESULQ) was used for data collection. This instrument was face and content validated by three experts. A reliability index of 0.81 was obtained for the questionnaire using Cronbach Alpha reliability coefficient after a pilot test. All hypotheses were tested at .05 significance level using simple linear regression and independent t-test statistics. Findings revealed that knowledge of information sourcing significantly influences the use of libraries by agricultural education students in public universities and that there is no significant difference in the influence of knowledge of information sourcing on male and female agricultural education students’ use of public libraries. Based on the findings, it was recommended amongst others that information search knowledge and literacy should be included in the course outline for use in library, and taught as a course in tertiary institutions, as this would ensure that students including those in Agricultural Education have the necessary knowledge needed to source and search for key information in the library
РЕАГЕНТНЫЙ МЕТОД УДАЛЕНИЯ ФОСФАТОВ
КАК СПОСОБ УЛУЧШЕНИЯ КАЧЕСТВА ОЧИСТКИ СТОЧНЫХ ВОД
Authors: Pakalova Yekaterina Vladimirovna , Abuova Galina Bekmuratovna , Sharagin Leonid Aleksandrovich
Published: April 2024

В работе рассмотрена проблема, связанная с эвтрофированием водоемов при сбросе в них остаточных концентраций фосфора. Эвтрофирование это природный процесс, однако разные потребители воды увеличили использование биогенных веществ, что свидетельствует увеличения фитоплактона, водной растительности на мелких водоемах и изменение качества

воды. Одним из главных загрязнителей, являются канализационные очистные сооружения, которые сбрасывают в водоемы очищенную воду с содержанием фосфора, превышающие предельно допустимые концентрации. Для решения проблемы, необходимо совершенствовать работу сооружений биологической очистки сточных вод. В статье рассмотрена эффективность работы канализационных очистных сооружений г. Астрахани. Проанализированы данные объемов фактических стоков, качество поступающих и очищенных сточных вод. Для повышения эффективности работы аэротенков предлагается реагентный метод удаления фосфора. Приведено экспериментальное исследование по определению наиболее эффективного реагента и его дозы для удаления биогенных веществ, а также определена точка ввода реагента.
СРАВНИТЕЛЬНО-ИСТОРИЧЕСКИЙ МЕТОД В УПРАВЛЕНИИ ОРГАНИЗАЦИОННЫМИ СИСТЕМАМИ ПРИ ИНТЕГРАЦИИ ГРАДОСТРОИТЕЛЬНОЙ И ОБРАЗОВАТЕЛЬНОЙ СИСТЕМ
Authors: Vlasova Tatiyana Vladimirovna , Vlasova Irina Vladimirovna
Published: April 2024

В аспекте исследования вопросов управления организационными системами при интеграции градостроительнои и образовательнои систем определена актуальность применения сравнительно-исторического метода. Использован принцип научного историцизма для рассмотрения города в условиях его исторического развития, в многообразии структурных связеи градостроительнои и образовательнои систем. Изучен процесс становления образования в области архитектуры и строительства Санкт-Петербурга, его взаимодеи ствие и интеграция с развитием градостроительнои системы. В результате выявлено, что динамика развития города непосредственно отражается на градостроительнои и образовательнои системах. С изменениями в процессах управления градостроительной системой менялась специализация, масштабы и организация подготовки профессионалов данной сферы. Обосновано применение предложенного научного подхода, которыи позволяет учитывать и использовать сложность и уникальность организационнои системы управления городской средой на современном этапе развития.
О ВЫСОКОПРОИЗВОДИТЕЛЬНОЙ РЕАЛИЗАЦИИ МЕТОДА ПРОДОЛЖЕНИЯ ПО НАИЛУЧШЕМУ ПАРАМЕТРУ
ПРИМЕНИТЕЛЬНО К МОДЕЛИРОВАНИЮ ТОНКОСТЕННЫХ ОБОЛОЧЕК
Authors: Zgoda Yuriy Nikolayevich , Semenov Aleksey Aleksandrovich
Published: April 2024

Компьютерное моделирование тонкостенных оболочечных конструкций представляет собой сложный с вычислительной точки зрения процесс. Многие классические подходы к моделированию оболочек предполагают их последовательное

нагружение, что усложняет изучение поведения конструкции в условиях потери устойчивости. Целью данной работы является анализ и совершенствование производительности компьютерного моделирования оболочек при использовании метода продолжения по наилучшему параметру. В алгоритм был встроен механизм валидации, позволяющий получить более полное представление о потере устойчивости оболочки. Предложено также использование предварительной компиляции для сокращения длительности вычислений на этапе адаптивного выбора шага по длине дуги. Результаты вычислительного эксперимента показали, что разработанный алгоритм обеспечивает сокращение длительности вычислений примерно в 20 раз в сравнении с более распространенными методами моделирования. Точность моделирования при этом сохраняется.
ПРОИЗВОДСТВО СОРБЕНТОВ НА ОСНОВЕ НЕФТЕ- И АЛЮМООТХОДОВ
Authors: Yuryev Yuriy Yuryevich , Dudnikova Natalya Vladimirovna , Chayka Yekaterina Romanovna , Yakovlev Daniil Pavlovich , Moskvichev Aleksandr Viktorovich
Published: April 2024

Повышение требований к качеству воды диктует поиск эффективных технологий водоподготовки и водоотведения.

В статье рассмотрен способ получения сорбента, который может использоваться для повышения качества очистки питьевой

воды и сточных вод. Сорбент, полученный из отходов производства алюминия и переработки нефти, обладает высокой адсорбционной способностью к хлорпроизводным органическим веществам, катионактивным и неоногенным ПАВам. Полученный материал обеспечивает высокую степень очистки и может быть применен при очистке воды от нефти и нефтепродуктов. Такие сорбенты относятся к материалам многократного использования. Они дешевле и экологичнее. Экологический эффект заключается в полной или частичной ликвидации алюминиевых шламов, что позволяет снизить их негативное влияние на окружающую среду.
МЕТОДЫ ОЦЕНКИ РЕСУРСОВ ГАЗОВЫХ МЕСТОРОЖДЕНИЙ
Authors: Makarov Albert Vladimirovich , Shurshev Valeriy Fedorovich
Published: April 2024

В статье рассмотрены методы для оценки ресурсов газовых месторождений, выявлены их преимущества и недостатки. Показано, что при оценке ресурсов месторождения имеют место геологические риски. При их анализе необходимо учитывать основные элементы управления залеганием углеводородов. Представлено описание метода геологической аналогии, в котором на практике используются коэффициенты масштабирования других методов и компьютерные имитации. Преимуществом использования объемных методов при оценке залежей является их хорошая привязка к наиболее важным аспектам геологии. Для прогнозирования объемов залежей возможно использовать методы экстраполяции. Сделан вывод, что в методе для оценки залежей газа должна быть заложена некоторая мера риска. Для оценки объема газовых месторождений необходимо использовать методы, основанные на интегрированной системе моделей материального баланса, позволяющие учитывать и корректировать дополнительную априорную информацию о начальных извлекаемых запасах.
НЕОБХОДИМОСТЬ И ВОЗМОЖНОСТЬ ПРИМЕНЕНИЯ BIM-ТЕХНОЛОГИИ В ОЦЕНКЕ УРОВНЯ ТЕХНОСФЕРНОЙ БЕЗОПАСНОСТИ
Authors: Masyagina Nataliya Ivanovna , Zorina Olga Anatolyevna
Published: April 2024

На сегодняшний день в Российской Федерации мало используют BIM-технологии, хотя в них заинтересованы. Переход на данный вид технологий в оценке состояния охраны строительного производства возможно при использовании современных методов. Работа по применению BIM-технологий в оценке уровня техносферной безопасности, согласно постановлению, заключается во внедрении и обеспечении оценки условий труда, использовании и актуализации нормативно-технической документации, усовершенствовании законодательства в техносферной безопасности, реализации всестороннего надзора в техносферной безопасности. За счет методик мониторинга можно отслеживать и оценивать действия превентивных методов. Их необходимо пересмотреть для сохранения жизни и здоровья работающих на производстве; снизить все виды работ, связанных с неблагоприятными условиями труда.
ОЦЕНКА РИСКА В ИСПЫТАТЕЛЬНОЙ ЛАБОРАТОРИИ
Authors: Mukhamedzhanova Olga Gabitovna
Published: April 2024

При аккредитации и подтверждении процедуры компетентности испытательная лаборатория должна внедрять риск-ориентированное мышление в свою лабораторную деятельность. Риск-ориентированный подход предполагает, что все риски определены и идентифицированы, рассчитана вероятность появления и уровень тяжести по каждому риску, установлены мероприятия по предупреждению каждого риска и ответственные лица. Поэтому в данной статье определены градации риска в испытательной лаборатории с помощью шкал вероятности и уровня рисков. На основе методики оценки рисков составлен реестр рисков испытательной лаборатории с определением риска и его последствий, с установлением значимости риска, прописаны мероприятия по корректирующим и предупреждающим действиям, сроки, ответственные лица с отметками по их выполнению.
ПРОЕКТИРОВАНИЕ ИНФОРМАЦИОННОЙ СИСТЕМЫ БЛАГОУСТРОЙСТВА ГОРОДСКОЙ СРЕДЫ В РАЗРЕЗЕ ПИРАМИДЫ ПОТРЕБНОСТЕЙ
Authors: Kuzyakina Lyudmila Semenovna , Sadchikov Pavel Nicolaevich
Published: April 2024

В статье рассмотрена территория города в разрезе пирамиды Маслоу, на основе чего выстраиваются приоритеты в процессе городского благоустройства, городские объекты рассматриваются с позиции реализации различных уровней человеческих потребностей. Авторами исследуется взаимодействие между субъектами городского благоустройства, их связь с объектами и перспективы реализации идеи умного города в условиях существующей городской застройки. В статье описывается модель информационной системы создания комфортной городской среды, реализующей возможность оперативного решения проблем жителей города в едином цифровом пространстве с участием ответственных служб с фиксацией документов, диалогов, обсуждения и результатов, на уровне диаграмм. Данная система позволит не только быстро связывать между собой всех заинтересованных участников процесса, но и контролировать действия сторон, а также выявлять зависимости между проблемами и факторами влияния.
АВТОМАТИЗИРОВАННЫЕ СИСТЕМЫ УПРАВЛЕНИЯ
В ТЕПЛИЧНЫХ ХОЗЯЙСТВАХ АСТРАХАНСКОЙ ОБЛАСТИ
Authors: Skripko Lyudmila Petrovna , Skripko Anastasiya Andreyevna
Published: April 2024

Одни из важных задач Российской Федерации, касающиеся сельского хозяйства – улучшение производственных показателей при сборке урожая, отказ от импорта овощей, повышение урожайности в нашем крае, уменьшение затрат при транспортировке. В данной работе представлена автоматизированная система управления в тепличном хозяйстве на базе контроллеров Arduino и программном обеспечении ONI PLR Studio для эксплуатации. Актуальность заключается в необходимости создания автоматизированной системы управления в тепличном хозяйстве для обеспечения населения круглогодично зеленными культурами. Система управления позволяет экономить использование водных ресурсов вдали от водозаборов, электроэнергию, рабочую силу, время. Научная новизна работы состоит в создании соответствующих режимов системы климат-контроля в теплицах для облегчения труда в сельском хозяйстве. Программа ONI PLR решает задачи контроля над выращиванием сельскохозяйственной продукции, выведении новых сортов растений, управлении технологическим процессом с помощью определенных сигналов.
ОСОБЕННОСТИ УЧЕТА ЭКСПЛУАТАЦИОННЫХ НАГРУЗОК
ПРИ ОБЕСПЕЧЕНИИ МЕХАНИЧЕСКОЙ БЕЗОПАСНОСТИ КОНСТРУКЦИЙ ПОКРЫТИЯ ОБЪЕКТА СТРОИТЕЛЬСТВА
Authors: Gurova Yelena Vladimirovna , Kuramshin Renat Khosyainovich , Korotkova Anastasiya Aleksandrovna , Levshin Georgiy Igorevich , Mashakaryan Ararat Sergeyevich
Published: April 2024

Проведена оценка влияния особенностей режима эксплуатации объекта незавершенного строительства на параметры

механической безопасности конструкций покрытия. Выполнен анализ влияния негативных внешних воздействий, в частности, повышенных пылевых отложений, на несущую способность элементов покрытия в сложившихся условиях эксплуатации. Разработан вариант усиления конструкций покрытия объекта строительства с изменением расчетной схемы его элементов, который позволяет довести параметры механической безопасности элементов покрытия до нормативных значений

и обеспечить дальнейшую безопасную эксплуатацию объекта.
ДИСПЕРГИРОВАНИЕ ДИЗЕЛЬНОГО ТОПЛИВА В ВЫСОКОВОЛЬТНОМ ЭЛЕКТРОСТАТИЧЕСКОМ ПОЛЕ
Authors: Svintsov Vladimir Yakovlevich , Arabov Mikhail Shugeyevich , Prokin Sergey Vladimirovich
Published: April 2024

В статье приведены результаты исследования диспергирования дизельного топлива за счет энергии высоковольтного

электростатического поля. Процесс диспергирования фиксировался с помощью цифровой фототехники, что позволило определить размеры частиц как функцию напряжения питания высоковольтного блока экспериментальной установки.
МЕТОДОЛОГИЯ ПРИМЕНЕНИЯ НАИЛУЧШИХ ДОСТУПНЫХ ТЕХНОЛОГИЙ ВОССТАНОВЛЕНИЯ НАРУШЕННЫХ ЗЕМЕЛЬ ПРИ КОМПЛЕКСНОМ РАЗВИТИИ ТЕРРИТОРИЙ НЕЖИЛОЙ ЗАСТРОЙКИ
Authors: Spitsov Dmitriy Vladimirovich , Yazhlev Igor Kapitonovich
Published: April 2024

В статье проведен анализ содержания существующих нормативно-методических документов, практики их применения в проектах комплексного развития территорий нежилой застройки и реорганизации производственных территорий в целях создания инструментов гарантированной ликвидации накопленного экологического вреда на городских и производственных территориях, применения наилучших доступных технологий при проведении исследований, оценки участков территорий комплексного развития, разработки планов восстановления нарушенных земель и проведении рекультивационных работ. Сделан вывод о недостаточности действующей нормативно-правовой базы, разработаны предложения по внесению изменений в национальные стандарты, документы национальной системы стандартизации, нормативные документы в строительстве.
СОВРЕМЕННЫЕ ТЕНДЕНЦИИ В АРХИТЕКТУРЕ АЛТАРНОЙ ПРЕГРАДЫ ХРАМОВ Г. БАРНАУЛА
Authors: Savenkova Olga Vladislavovna , Pomorov Sergey Borisovich
Published: April 2024

В статье рассмотрены современные тенденции в архитектуре алтарной преграды. Объектом изучения являются иконостасы в храмах г. Барнаула, возведенных за последние тридцать лет. Авторами была собрана информация о более тридцати храмах, находящихся в городе Барнауле. Собран фотоматериал для описания архитектурно-художественных и символических

особенностях иконостасов. Приводятся примеры деревянных, мраморных, фаянсовых и кованных алтарных преград в современных православных храмах. Алтарные преграды были классифицированы по материалам, типам и количеству ярусов. Рассмотрены тенденции конструкций современных иконостасов. Результаты исследования работы могут быть использованы для создания проектов и строительства новых иконостасов, а также для образовательной и исследовательской деятельности.
ОБ ОРГАНИЗАЦИИ ОПЫТНО-ЭКСПЕРИМЕНТАЛЬНОЙ РАБОТЫ
В ХОДЕ ИССЛЕДОВАНИЯ ВЛИЯНИЯ КОМПЛЕКСНОСТИ ВИБРОВОЗДЕЙСТВИЙ НАЗЕМНОГО И ПОДЗЕМНОГО ТРАНСПОРТА НА ЗДАНИЯ И СООРУЖЕНИЯ
Authors: Fedorov Viktor Sergeyevich , Kupchikova Natalya Viktorovna , Lazutkin Yuriy Viktorovich
Published: April 2024

В статье представлены исследования по подбору современных приборов неразрушающего контроля с целью определения параметров вибро-динамических воздействий и динамических свойств грунтов в организации опытно-экспериментальной работы в ходе исследования влияния комплексности вибровоздействий наземного и подземного транспорта на здания и сооружения. Для решения задач исследования показаны отличительные особенности и параметрические исходные данные следующих методов: полевые методы оценки динамических свойств грунтов; лабораторные методы динамических испытаний грунтов; лабораторные методы динамических испытаний физических моделей (главным образом методы центробежного моделирования с возможностью создания дополнительных динамических нагрузок, испытания на вибростолах).
Attention-Based Multi-Layered Encoder-Decoder Model for Summarizing Non-Interactive User-Based Videos
Authors: Charul Bhatnagar Vasudha Tiwari,
Published: April 2024

Video summarization extracts the relevant contents from a video and presents the entire content of the video in a compact and summarized form.  User based video summarization, can summarize a video as per the requirement of the user. In this work, a non interactive and a perception-based video summarization technique is proposed that makes use of attention mechanism to capture user’s interest and extract relevant keyshots in temporal sequence from the video content. Here, video summarization has been articulated as a sequence-to-sequence learning problem and a supervised method has been proposed for summarization of the video. Adding layers to the existing network makes it deeper, enables higher level of abstraction and facilitates better feature extraction. Therefore, the proposed model uses a multi-layered, deep summarization encoder-decoder network (MLAVS), with attention mechanism to select final keyshots from the video. The contextual information of the video frames is encoded using a multi-layered Bidirectional Long Short-Term Memory network (BiLSTM) as the encoder. To decode, a multi-layered attention-based Long Short-Term memory (LSTM) using a multiplicative score function is employed. The experiments are performed on the benchmark TVSum dataset and the results obtained are compared with recent works. The results show considerable improvement and clearly demonstrate the efficacy of this methodology against most of the other available state-of-art methods.
Improving Performance of Solar Array Fed BLDC Drive Using Firefly Algorithm Based High Gain Converter
Authors: Valantina Stephen, Vinod, Ramprasad Reddy Femi R.,
Published: April 2024

The improved transient response of PID controller for improved Luo converter supplied Brushless DC (BLDC) motor using solar energy source is extensively investigated. The BLDC drive uses a hybrid PV system and battery-based power generation as a power source to assure continuous power supply to pump water regardless of solar insolation. The PV system serves as the main energy source, and the battery providing as a backup source that discharged its power only during inclement weather or at night if the photovoltaic panel is insufficient to operate the centrifugal pump. The solar panel feeds power into the battery, whenever water to the field is not required, thus there is no need for an extra power source to charge the batteries. The high output voltage gain DC-DC converter does not make any discomfit to the system performance in regards to irradiance variation, switching loss, or power loss by converter or motor side respectively. Moreover, current sensor, voltage sensor, and control circuits are completed excluded which enhance performance and the cost of the system get reduced effectively. A bidirectional charging control allows a bi-directional converter to alter the battery operation mode automatically. The overall system performance is validated using simulation and experimental setup.
Research and Application of Active Security Protection Methods for Automotive Cloud
Authors: Qiang Zhang, Baizheng Wang Kexun He,
Published: April 2024

With the gradual maturity of the Internet of vehicles and cloud computing industry and the continuous evolution of network attack forms, the demand for cloud security in the automotive industry will increase year by year. In the automobile cloud platform environment, because the traditional security scheme is still effective for the north-south traffic, the security problem of the automobile cloud platform mainly lies in the security protection of the east-west traffic of the platform and the division of the security boundary. The purpose of this project is to solve the security risk of east-west cross-subnet traffic of the automobile cloud platform, especially the traffic security problem between hosts, in order to provide the next generation firewall, intrusion prevention and other professional security protection functions for the virtual network environment without affecting the service virtual machine. In order to achieve the above purpose, it is necessary to solve the problem of virtual switch diversion and virtual machine drift on the cloud platform, study the service security requirements of the automotive cloud platform, the relationship between data transfer and processing on the cloud platform, and finally provide a prototype system of active security protection for the cloud platform risks. The system implements VM microisolation, network attack defense, malicious code defense, ip address-based secure access policies, application-type secure access policies, and VM migration security functions in cloud application scenarios.
Machine Learning-Based Prediction Methods for Home Burglary Crimes
Authors: Xiaomin Li, Lixuan Zhao, Qi Wu, Wei Du, Shangxuan Jiang Shuo Wen,
Published: April 2024

In today’s rapidly evolving society, as technology continues to advance, various new forms and methods of crime emerge incessantly. It becomes particularly crucial to accurately predict future criminal behaviors. This paper delves into the study of forecasting home burglary crimes in the realm of property-related offenses. Utilizing a dataset of criminal cases, relevant variables with high correlation to crime prediction are selected as features. Through employing diverse machine learning algorithms, the likelihood of the occurrence of home burglary crimes is forecasted. Consequently, a crime prediction model specifically tailored for home burglary cases is constructed, and the accuracy of the model is evaluated. By using the accuracy of the model as the benchmark, the optimal crime prediction model is chosen, and a system is implemented for building and evaulating the model. Experimental results demonstrate that the developed crime prediction model is capable of effectively foreseeing home burglary crimes, thereby providing valuable support and scientific evidence for the prevention and handling of such criminal cases.
An Analysis on Integration of Solar and Wind Power into a Single-Phase Grid with an Optimal Parameterized Fractional-Order Pid Controller
Authors: Sumit Saroha, Avnesh Verma Kalyan Singh,
Published: April 2024

Because of the complimentary nature of solar and wind electricity, hybrid solar-wind power systems are the most effective renewable energy sources. Weather conditions have a significant impact on the amount of power that can be generated by wind and solar photovoltaic systems. Their intermittent nature causes output fluctuations. The purpose of this research is to offer a technique for a hybrid wind–solar power plant that makes the most efficient contribution of renewable energy resources and is backed by technology that allows batteries to store energy. The fact that solar and wind power display power profiles that are complimentary was the driving force for the construction of the hybrid solar–wind power system.
Integrated Sensor Fusion and Multi-Modal Hierarchical Neural Network for Activity Recognition in Lower Limb Prosthetics
Authors: S. Prakash M. Jeyasudha,
Published: April 2024

Activity recognition plays pivotal role in enhancing functionality for prosthetic devices, ensuring seamless integration with users' movements. However, the complexity arises from the diverse data sources, including acceleration, angular velocity, joint angles, orientation, electromyography (EMG), and marker data, necessitating a robust approach to overcome challenges in information integration. The primary challenge lies in the effective utilization of multiple sensor modalities, each with unique characteristics and potential noise sources. The proposed solution addresses this by employing advanced sensor fusion techniques, such as Kalman filtering, during data collection. Synchronization and resampling ensure temporal consistency, while noise reduction techniques, such as low-pass filters, mitigate signal distortions. To further refine the process, a hybrid optimization-based feature selection Adaptive Step Size in Marine Predators Algorithm (ASSMPA) is introduced, focusing on marker data features. ASSMPA synergizes Marine Predators Algorithm (MPA) and Pathfinder Algorithm (PFA) for optimal feature selection in marine predator pathfinding tasks. The Feature Fusion step integrates attention mechanisms to dynamically weigh the significance of different sensor modalities during the fusion process. This strategic fusion enhances the overall performance of the Multi-Modal Hierarchical Neural Network (MMHNN). The proposed model is implemented using Python.
“Deep Learning Based Classification of Single-Hand South Indian Sign Language Gestures”
Authors: Rajesh Yakkundimath, Ramesh Badiger, Naveen Malvade
Published: April 2024

Gesture recognition is a branch of computer science and language technology dedicated to utilizing mathematical algorithms for the analysis of human gestures. Within the realm of non-verbal communication, the pivotal role of human arm movements and gestures remains a focal point. This research introduces advanced multi-stream deep transfer learning models tailored for identifying signs from South Indian languages, specifically Kannada, Tamil, and Telugu. The primary aim is to offer support to individuals encountering speech disorders or disabilities. The key deep transfer learning models utilized include Inception-V3, VGG-16, and ResNet-50, which have been modified and improved to attain heightened classification efficacy. The dataset comprises 35,000 images capturing single-hand gestures. In the realm of models, Inception-V3 exhibits the utmost test accuracy, standing at 91.45%, alongside a validation accuracy of 93.45% when tasked with the classification of single-hand gesture images across thirty-five distinct categories. The importance of this study lies in its prospective utility for creating an automated system that can support and improve the functional capabilities of individuals facing speech disorders or disabilities.
Stress-Nets- A Novel LSTM Ensembled Single Feed Forward Layers for Stress Classification with EEG Signals
Authors: S. Jerritta Muhammadu Sathik Raja M. S.,
Published: April 2024

Mental instability and emotional imbalance   of the individual can be reflected in the form of stress which results  in an inappropriate work ethics.  There are various methods for the Stress creation. Moreover , several bio-signal sources such as Electroencephalograph(EEG), Electrocardiography(ECG) and Electromyography(EMG) are considered to be the important catalyst for developing the stress detection systems(SDS). Recently, machine and deep learning algorithms has gained more popularity in designing the SDS using the bio-signals. Further, EEG based SDS with ML and DL algorithms plays an important role for its high classification accuracy and performance. However, these EEG based SDS  systems needs the better lime light of improvisation in terms of  performance and computational overhead to deal with multiple datasets.  In this context, this manuscript proposes new  Long Short term Memory recurrent units(LSTM) for extracting temporal features while enhanced extreme learning machines are employed for better classification with less computational complexity. The different data sources are used to collect the EEG signals in which the collected  signals are preprocessed for evaluating the proposed model. Additionally, the experiments are performed by DEAP  and Kaggle datasets as well as performance parameters and  compared by conventional  Fused  Support vector machines (F-SVM),BI-Long Short Term Memory(BILSTM), Random Forest(RF) and  Deep Convolutional Neural network(DCNN).  Results shows which proposed EEG based SDS has better performance than other conventional  ones  of high accuracy in stress detection and for diagnosing classify the stress-levels .
“Multi-Criteria Group Decision Making Approach for Scheduling Algorithms Selection by Short Term Scheduler using Fuzzy TOPSIS”.
Authors: Riddhi Garg, Shubham Kumar, Atul Kumar Goel, M. K. Sharma Rajeev Sharma,
Published: April 2024

The fundamental objective of the CPU scheduler is to equitably and effectively allocate CPU time among competing processes. Within the realm of schedulers, the short-term scheduler specifically addresses this objective by selecting processes from the ready queue for execution on the CPU, guided by various scheduling algorithms. The critical challenge faced by the short-term scheduler lies in the prudent selection of the most suitable algorithm, as an erroneous choice can detrimentally impact system performance, leading to increased waiting and response times for processes. To surmount this challenge, we employ the Fuzzy TOPSIS method within the framework of Multi-Criteria Decision Making (MCDM) to rank scheduling algorithms, taking into account both quantitative and qualitative factors. The proposed approach involves two steps: firstly, defining criteria for algorithm selection, and secondly, obtaining linguistic ratings from experts for potential alternatives based on the specified criteria. The principal aim of this investigation is to utilize the Fuzzy TOPSIS method, integrating fuzzy sets, to produce comprehensive scores that assist in selecting the optimal alternative.
Artificial Intelligence-Powered Sentiment Analysis Tool to Assess the Popularity of Political Leaders in Informal Communities
Authors: Rakesh Kumar Yadav Chandra Shekhar,
Published: April 2024

This study investigates the utility of Artificial Intelligence sentiment analysis tools in assessing the popularity of political leaders within informal communities. In contemporary socio-political landscapes, understanding public sentiment towards political figures is paramount for gauging societal perceptions and predicting electoral outcomes. Leveraging sentiment analysis techniques, this research delves into the nuanced expressions and sentiments prevalent in informal online communities regarding political leaders. By analyzing textual data from social media platforms, forums, and other digital sources, the study aims to discern patterns and trends indicative of public opinion dynamics. Through natural language processing and machine learning algorithms, sentiment analysis tools enable the automated extraction of sentiments, emotions, and attitudes towards political leaders, providing valuable insights into their perceived popularity and public reception. The findings contribute to our understanding of the intersection between technology, politics, and public opinion, shedding light on the evolving landscape of political discourse in digital spaces. The study underscores the significance of sentiment analysis for political analysts, policymakers, and researchers in comprehending and navigating the complexities of contemporary political environments.
Empirical Evaluation of Microgrid Fault Identification Models from a Statistical Perspective
Authors: Jagdish G. Chaudhari, Bhupendra Kumar Rashmi S. Phasate, Asha D. Shendge,
Published: April 2024

Microgrid fault identification models are developed via integration of extensive data collection, pre-processing of collected data, current & voltage segmentation, feature representation, identification of variant feature sets, their classification & post-processing operations. Existing models that perform microgrid fault identification are either highly complex, or cannot be applied for heterogeneous fault types. Moreover, these models also showcase large variance in terms of their qualitative & quantitative performance levels. Due to these issues, it is difficult for researchers to identify optimum models for their performance-specific deployment use cases. To overcome these issues, a detailed review of different microgrid fault detection & mitigation models in needed, which can evaluate their performance in terms of qualitative & quantitative parameters. Thus, this text initially discusses characteristics of some of the recently proposed microgrid fault detection models in terms of their functional nuances, application specific advantages, deployment specific limitations, and context-specific future research scopes. After referring this discussion, it was observed that linear models that incorporate pattern recognition are highly useful for fault pre-emption and mitigation purposes. This text also compares these models in terms of their accuracy of detection, delay needed for fault identification, computational complexity, deployment cost, and scalability metrics.
Classification of Mango Leaf Disease using Machine Learning to Enhance Yield Productivity
Authors: Harshali Patil, Varsha Bendre, Jayashree Katti Deepali Joshi,
Published: April 2024

Fruits provide critical nourishment to the human body. Proper Care and upkeep are essential for the fruit to be healthy. Lack of maintenance, infections, spot, fungus all cause significant production and profit losses. Mango is a seasonal and famous fruit which is consumed all over the world. It is a delicate fruit that is susceptible to disease that reduce the quality as well as quantity. Manual illness or infection inspection is a time-consuming and labour-intensive technique that necessitates a large amount of resources and therefore it is inefficient. On the other hand, automatic inspection provides various advantages such as less time consuming, less labour and also the number of resources required are less. Image classification techniques and algorithms can be used to distinguish between infected and healthy mangoes, decreasing losses.
Detection of Gender in Crowds Using ResNet Model
Authors: Rajeev G. Vishwakarma Priyanka Singh,
Published: April 2024

The ResNet model is used in this investigation to suggest a gender detection solution for use in congested settings. Due to occlusions, varied stances, and various features, determining a person's gender in crowded surroundings may be a difficult and time-consuming job. The ResNet model, which is a deep convolutional neural network architecture, is used to solve these difficulties because of its capacity to capture detailed characteristics and its efficiency in managing deep network structures. The strategy that has been suggested entails preprocessing the input photos, sending those images through the ResNet model, and then extracting gender-related characteristics from those images. The ResNet model is made up of a number of residual blocks with skip connections, which makes it easier to learn complicated representations. After that, the learnt characteristics are input into fully linked layers, and then softmax activation is used to determine the subject's gender. The usefulness of the technique that was developed was shown by experimental findings on a large dataset, which achieved a high level of accuracy in gender determination. The use of the ResNet model helps the system to handle complicated scenarios and improves the system's ability to accurately recognize gender in situations with a large number of people. The method that has been developed has the potential to find applications in areas such as surveillance, crowd control, and the study of social behavior.
A MIMO-Based Dual Polarized Antenna Applicable for Mobile Terminal
Authors: Biqing Li, Shiyong Zheng, XiaoguangYue
Published: April 2024

At present, numerous small-size mobile terminal devices, such as mobile phones, have embedded the antenna in the cases, which will lead to considerable restrictions on the space for installing multiple antennas. Aiming at the requirements of rational design and layout of multi-antennas for MIMO mobile terminals and combining with the broadband and miniaturization technologies, a dual polarized antenna suitable for mobile terminals was designed in this paper through an adoption of polarization diversity. For a dual polarized multilayered micro-strip antenna with a ground plate, it is easy to be conformal to the carrier. In this paper, the design and the process of simulation optimization of the antenna unit were analyzed in detail. The bandwidth of the antenna unit was 1890 to 2200 MHz, the return loss was superior to -33dB, and both of the horizontal polarization gain and the vertical polarization gain were 8.2 dB. Accordingly, the characteristics of a high gain and dual polarization were achieved.
Research on Intelligent Monitoring System of Intelligent Transmission Line Based on Computer Internet of Things Technology
Authors: Kaipeng Zhang, Jingxu Zuo
Published: April 2024

The author proposes an intelligent early-warning system for preventing external damage of transmission lines. The system uses TI-TMS320DM6446 as the core, the peripheral circuit configuration and video monitoring; The moving objects captured by PTZ camera are detected and identified by using mixed Gaussian model, background difference and minimum tangent matrix, and alarm signals are provided. According to the particularity of the power supply of the equipment on the transmission line, the basic power management of the system is analyzed in detail. A reliable power management scheme is designed. The practical application proves that this method has good real-time performance and has obvious effect on preventing power cable damage by force.
Influence of Digital Leadership on Employees’ Digital Creativity Based on the Research Perspective of the Mediating Effect of Job Crafting
Authors: Haigang Zhuang, Yue Liu, Zepeng Yu
Published: April 2024

Employees’ digital creativity have become important driving forces for enterprises to use digital technology to create business benefits. However, research on digital creativity is still insufficient. Digital leadership, due to its unique characteristics and important role in driving the digital development process of individuals, businesses, and society, is used as antecedent variable in this study to influence employees’ digital creativity. Job crafting is the mediating variable, and power distance is the moderating variable. This study uses mature scales to compile a questionnaire distributed to digital enterprises in China in two periods. Finally, 344 valid questionnaires were obtained, and the hypotheses were tested using AMOS 24.0 software and the hierarchical regression method. Research has found that digital leadership is positively related to employees’ digital creativity. Job crafting mediates between digital leadership and employees’ digital creativity. Power distance negatively moderates the relationship between digital leadership and employees’ digital creativity, and negatively moderates the mediating role of job crafting between digital leadership and employees’ digital creativity. Based on the theoretical results of this study, in addition to emphasizing the cultivation of digital leadership, enterprises should also pay attention to exploring employees with low power distance and consciously encourage them to job crafting, so as to effectively unleash their digital creativity.
Innovation and Practice of “Job-Course-Competition-Certification” Professional Talents’ Cultivation Model in Tourism Major under the Background of Digitalization Era
Authors: Wei Yin, Lijie Yin
Published: April 2024

The rapid development of new digital economies such as artificial intelligence, cloud computing, and big data is profoundly changing various industries, especially the tourism industry. The digital upgrade has promoted the transformation and development of the tourism industry, and has given rise to a series of new employment positions closely related to digital technology, providing broader development space and transformation opportunities for the cultivation of tourism professionals. In this digitalization context, The most urgent thing is to explore the best talent cultivation model to adapt to the changes in the tourism industry environment and the demand for tourism talents. On the basis of drawing on the practical experiences from professional talent cultivation reform in existing universities, combined with the problems in the process of tourism majors` talents cultivation, this paper proposes an innovative plan for the talent cultivation mode of higher vocational tourism majors under the theoretical framework of “job-course-competition-certification” integration. It is hoped that through the vivid practice of three integration scenarios: “job- course integration”, “course-competition integration”, and “course-certification integration”, it will optimize the talent training system for tourism majors in higher vocational colleges, and achieve high-quality and skilled training for tourism majors talents.
An Empirical Study on the Educational Application of ChatGPT
Authors: Xu Fang, Xiuge Wang, Wenying Ma
Published: April 2024

At present, the digital transformation of education has become a national strategy, and ChatGPT is of great significance to the in-depth promotion of the digital transformation of education.Chatgpt has become a hot spot at home and abroad. The application of ChatGPT in daily education and study need to be deepened, but there is still a lack of attention to the current situation and effect of ChatGPT at home and abroad. Based on expectation confirmation theory, information system success theory and TAM model, this study constructs a model of the influencing factors of ChatGPT learners' use satisfaction. The results of structural equation analysis show that perceived usefulness, expectation confirmation and information quality have significant positive direct effects on learners' satisfaction; perceived ease of use, system quality and social influence have significant positive direct effects on learners' perceived usefulness; system quality and information quality have significant positive direct effects on learners' expectation confirmation; perceived usefulness has significant positive direct effects on behavior intention; system quality has significant positive direct effects on perceived ease of use. The results of qualitative comparative analysis of fuzzy sets show that there are six schemes to promote learners' satisfaction. The overall coverage of the six configurations is 0.974215, and the consistency is 0.71898. On the basis of the above research, some countermeasures and suggestions are put forward finally.
Research on the Application of Intelligent Multi-branch Version Management Strategy of Electricity Marketing Service System Software
Authors: Zhihao Shen
Published: April 2024

In recent years, the Market Marketing Department of State Grid Corporation of China, in collaboration with the Internet Department, has initiated the construction of an intelligent energy internet marketing service system. This paper aims to improve the development efficiency and quality of the power marketing service system. To achieve this goal, an intelligent multi-branch version management strategy has been introduced. Firstly, the necessity of multi-branch version management is analyzed in relation to the characteristics of the power marketing service system software and the potential issues that may arise in its development and version management process. Then, based on the concept of productizing the general functions of the entire network and projecting the functions of each provincial network, a multi-branch version management strategy is designed, which includes the core components of intelligent multi-branch version management and intelligent multi-branch version protection. Finally, an application case of power marketing service system development is presented. This solution not only standardizes the version management process, improves software development efficiency, ensures the order and control of versions, but also demonstrates the enormous potential of intelligent technology in enhancing system development and management efficiency.