bluuebunny/crossref_metadata_2025 huggingface dataset:
AN EFFICIENCT RULE MINING MODEL USING [S]3 FCM AND ANN TECHNIQUES
Authors:   Prist University, India, T Thamaraiselvan , K Saravanan ,   Prist University, India
Published: October 2024

We are living in the era known as information era where numerous sectors especially health sectors are put to handle tremendous amount of information. To reduce this burden, an efficient data mining technology has been employed which is a successful evolving technique that has a big future for helping businesses and concentrates on the most valuable data in their data warehouses. Thus this paper presents the review of Safe Semi Supervised Fuzzy C Means clustering algorithm which is the key aspect of this work aids in achieving the goal. It has been utilized to cluster and classify the clear and relevant global data formats that many other clustering approaches unable to handle. By limiting the subsequent predictions obtained by unsupervised clustering, incorrectly labelled samples are thoroughly investigated. Meanwhile, the other labelled sample’s predictions are equivalent to the assigned labels. As a result, the labelled samples are safely examined using a combination of unsupervised clustering and SSC. Therefore, it has been clear that FCM yields better result compared to other techniques. The ANN based classification algorithm is used, which learns from the training dataset to construct a model. This model helps in the classification of new objects.
FEATURE SUB-SPACING BASED STACKING FOR EFFECTIVE IMBALANCE HANDLING IN SENSITIVE DATA
Authors:   Rajah Serfoji Government College, India, S Josephine Theresa , D J Evanjaline ,   Rajah Serfoji Government College, India
Published: October 2024

Several real world classification applications suffer from an issue called data imbalance. Handling data imbalance is crucial in developing an effective classification system. This work presents an effective classifier ensemble model, Feature Sub-spacing Stacking Model (FSSM) that has been designed to operate on highly imbalanced, complex and sensitive data. The FSSM technique is based on creating subspace of features, to aid in the reduction of data complexity and also to handle data imbalance. First level trains models based on these features, which is followed by creating a stacking architecture. The second level stacking architecture trains on the predictions from the first level base models. This has enabled better and qualitative predictions. Experiments were conducted on bank data and also the NSL-KDD data. Results reveal highly effective performances compared to the existing models.
PREDICTING DEPRESSION FROM SOCIO-ECONOMICAL FACTORS
Authors:   Asia Pacific University, Malaysia, Rahman Lubnaa Abdur , Booma Poolan Marikannan ,   Asia Pacific University, Malaysia
Published: October 2024

With the sudden arrival of the Covid19, people have been experiencing higher levels of pressure which has given rise to the number of cases of Depression, a mental illness which can further lead to suicide and contribute to global burden, and therefore, faster ways for its diagnosis need to be sought to prevent further fatalities. Machine Learning, which has been implemented with proven results across various sectors especially for the prediction of diseases, promises to be of great help to facilitate the detection of depression within patients. However, up to now, most implementation for mental health prediction are greatly built on clinical data which takes time to be generated as several tests need to be taken which is not always plausible for everyone. Subsequently, this work explores the application and evaluation of three different machine learning algorithms; ANN, CART DT and SVM, for the prompt prediction of depression based on readily available data; behavioural and social-economical characteristics, and thus provides the best algorithm which could be applied in the context. SVM produced the highest accuracy and was therefore tuned whereby the highest recorded accuracy was of 93.85%. As this work has shown promising results, it is further recommended that future works explore deeper into assessing depression severity.
FORECASTING DISCLOSURE OF CARDIOVASCULAR DISEASE USING MACHINE LEARNING
Authors:   Dr. G.R. Damodaran College of Science, India, G Sugendran , S Sujatha ,   Dr. G.R. Damodaran College of Science, India
Published: October 2024

Data mining is a process that uses a combinational framework out of a supportable assessment and machine learning data collection development to eliminate hidden models from massive informative collections. Further, clinical data mining is a basic assessment field in light of its substance in the progression of numerous applications in the flourishing clinical benefits zone. However, considering the current occurrences around the globe, the coronary ailment radiates an impression of being the primary source. The ID of the probability of coronary disease in an individual is a tangled endeavor for clinical experts since it requires extended lengths of contribution and genuine clinical preliminaries to be considered. In this study, four data mining techniques for data collection, namely K-Nearest Neighbour, Random Forest, Decision Tree, Navie Bayes, are utilized to establish a figure model to evaluate and identify risk factors of coronary disease. primary goal of this preliminary inquiry is to determine the optimal representation count fitting for providing the highest level of precision when collecting data from regular and periodic individuals. With the assistance of the coronary disease benchmark dataset recovered from the UCI repository, an unstable setup was created for the evaluation of the show of counts. When compared to other estimations for coronary disease inference, Random Forest count achieves the highest accuracy with 90.16 %.
AN EFFECTIVE DATA MINING TECHNIQUE TO IDENTIFY AND CLASSIFY RESPIRATORY DISEASES IN CHILDREN AND ADULTS
Authors:   Sri Chandrasekharendra Saraswathi Viswa Maha Vidyalaya, India, K Nithyanandan , S Prakasam ,   Sri Chandrasekharendra Saraswathi Viswa Maha Vidyalaya, India
Published: October 2024

The authors of this study have built an outstanding data mining model for the classification of respiratory issues in children and adults, which they have applied in their research. Deep learning ensembles are built by utilising support vector regression (SVR), long short-term memory neural networks (LSTMs), and a metaheuristic optimization strategy that incorporates nonlinear learning in the DL ensemble (MHO). A collection of LSTMs with variable hidden layers and neurons is used to detect and exploit the underlying relationships in order to overcome the limitations of a single deep learning approach limited generalisation skills and robustness when faced with diverse input. The LSTM classification is then combined with a nonlinear-learning SVR and MHO to optimise the top-layer parameters. Nonlinear-learning meta-layer and LSTM classification. Finally, the final classification of the ensemble is provided by the fine-tuning meta-layer. Using data from six benchmark studies as well as energy consumption data sets, the proposed EDL is put to the test in two classification scenarios: ten-ahead and one-ahead classification.
CARDIOVASCULAR DISEASE PREDICTION USING ENSEMBLE CLASSIFICATION ALGORITHM IN MACHINE LEARNING
Authors:   St. Xavier's College, India, Roy Rajarshi Sinha , Sen Anupam ,   Government General Degree College, India
Published: October 2024

Cardiovascular disease includes a wide range of heart-related illnesses and has surpassed cancer as the top cause of mortality worldwide in recent decades. Many people nowadays are engrossed in their daily lives and engage in various activities while ignoring their health. As a result of their rushed lifestyles and disrespect for their health, the number of people becoming unwell is increasing every day. According to the World Health Organization, heart disease claims the lives of over 31% of the world''''s population. As a result, doctors must be able to predict whether a patient may develop heart illness, but the amount of data collected by the medical sector or hospitals, on the other hand, is so vast that it can be difficult to analyze at times. This research paper assessed several aspects of heart illness and develops a model based on supervised learning methods like Gaussian Naïve Bayes and AdaBoosting algorithm. The purpose of this research is to figure out how to anticipate whether a patient will develop heart disease. The AdaBoosting algorithm achieves a great accuracy score of 95%, according to the data.
AN EFFICIENT BRITWARI TECHNIQUE TO ENHANCE CANNY EDGE DETECTION ALGORITHM USING DEEP LEARNING
Authors:   St. Joseph's College, Trichy, India, S Britto Ramesh Kumar , A Bhuvaneshwari ,   St. Joseph's College, Trichy, India
Published: October 2024

Artificial Intelligence edge detection refers to a set of mathematical techniques used to recognize digital image locations. The picture brightness plays a vital role in detecting dissimilarities and making decisions. Edges are the sharp changes in pictures with respect to the brightness and are commonly categorized into a collection of curved line segments. The main focus of this paper is to find sharp corner edges and the false edges present in the MRI images. The canny edge algorithm is a popular method for detecting these types of edges. The traditional canny edge detection technique has various issues that are discussed in this paper. This study analyses the canny edge algorithm and enhances the smoothing filter, pixel identifier, and feature selection. The proposed Britwari technique, Tabu Search Heuristic Pattern Identifier (TSHPI) enhances the edge detection using SUSAN Filter. Feature Selection is performed to improvise the canny edge method. Deep Learning algorithm is used for classification of pre-trained neural networks to find a greater number of edge pixels. The implementation results show that the Britwari proposed technique (SUSAN Filter Tabu Search Heuristic Pattern Identifier Hill Climbing) reached better accuracy than the traditional Canny Edge Detection algorithms. The results produced better feature set selection using edge detection in MRI images.
AUTOMATIC SEGMENTATION OF INFANT BRAIN MRI USING SOFT COMPUTING TECHNIQUES
Authors:   R C Patel Institute of Technology, India, Jaware Tushar , Badgujar Ravindra ,   R C Patel Institute of Technology, India, Patil Jitendra ,   R C Patel Institute of Technology, India, Patil Vinod ,   R C Patel Institute of Technology, India, Patil Prashant ,   R C Patel Institute of Technology, India, Dembrani Mahesh ,   R C Patel Institute of Technology, India
Published: October 2024

This article is concerned with exploration and diagnostic implementation of an effective neo-anatomical brain MRI classification method to classify primal cognitive development and investigate neuro-anatomical intellectual disability correlations. A crucial stage in the research as well as appraisal of the newborn brain growth is neonatal brain tissue classification. Owing to the major variations in anatomy and tissues among neonate and mature brains, the largest proportion of developing technology for the classification and segmentation of the adult brain really aren''''t sufficient for newborns brain. The existing brain tissue classification strategies for MRIs rely either on manual interactions or involve the use of atlases or models, which ultimately skew the findings from the population used to extract atlas. This article, focuses on atlas free soft computing approach to classify the neonatal brain tissue. Classification of brain tissue is the main process in which regional brain tissue examination is conducted. This helps the regional brain development to be characterized and the correspondence with therapeutic conditions to be studied. The modified BM3D approach is utilized for image enhancement along with 32 Gabor filter bank based feature extraction. The innovative aspect of this research is the multistage classification methodology, which produces higher dice coefficients and lower MHD values when compared to existing approaches.
EXAMINATION SCHEDULER USING A LINEAR-TIME GRAPH COLORING ALGORITHM
Authors:   St. Xavier’s College, India, Datta Debabrata , Banerjee Neelabha ,   St. Xavier’s College, India, Adhikary Sohan ,   St. Xavier’s College, India, Acharya Anal ,   St. Xavier’s College, India
Published: October 2024

The primary aim of the study aims to provide a solution for scheduling examinations for most of the universities and colleges across India which follow the Choice Based Credit System (CBCS) using a graph coloring algorithm. Nowadays, due to the flexibility of opting various subjects, and many students taking up different courses in their colleges and universities, it becomes difficult to schedule these examinations. Creating an examination schedule can be quite challenging and time-consuming for controlling the body of an examination. Our research work focuses on reducing the efforts for scheduling such examinations. With the knowledge of graph theory and graph traversing and coloring algorithms, our algorithm with the help of a few assumptions gives an efficient solution to the examination scheduling problem. A detailed correctness proof along with performance analysis has been done. The efficiency of our proposed algorithm is then compared to that of the coloring algorithm using backtracking.
META-HEURISTIC OPTIMISATION FOR OPTIMAL VIDEO QUALITY ENHANCEMENT
Authors:   Sri Shakthi Institute of Engineering and Technology, India, J Jasmine
Published: October 2024

We have seen a rapid development in technology over the past few years, from basic mobile phones to highly advanced surveillance monitoring systems that can record and analyze video clips. The process of video capture inevitably leads to a decline in overall video recording quality. Inadequate lighting is due to either an open aperture or a slow shutter speed. Images taken in such conditions typically have poor contrast and noisy backgrounds. If the contrast in your video is off, it could be because of a malfunctioning imaging device or an untrained operator. These two outcomes are equally plausible. When recording videos, this causes a loss of the dynamic range that could have been captured. Because of this, the video may appear distorted or washed out, and some of the finer details may be lost. In order to lessen the impact of these problems on the viewer experience, contrast enhancement techniques can be used to boost the visual quality. Work presented here will take a two-pronged approach to addressing the aforementioned problems. Videos can be compressed and their contrast can be increased, both of which are useful techniques that complement one another. Video quality can be improved with the help of a method called ant colony optimisation ACO based image quality enhancement. The frames of a video can be analyzed in greater detail using this hybrid method than with the conventional method. The noise is further reduced when the non-divisible median filter is used. To do this, the study develops an optimisation to attain increased rate of peak signal to noise rate than the other existing methods. After examining available options, the researchers settled on the DLACDHE procedure as the best option. Based on the results, it is reasonable to infer that the proposed strategy offers better contrast enhancement than the conventional methods.
LIGHT GRADIENT BOOSTING MACHINE FOR OPTIMIZING CROP MAINTENANCE AND YIELD PREDICTION IN AGRICULTURE
Authors:   AURO University, India, Kumar Sunil , Sohail Mohammed Ali ,   Jazan University, Kingdom of Saudi Arabia, Jadhav Sandhya ,   Bharati Vidyapeeth College of Engineering, India, Gupta Raj Kumar ,   Sardar Vallabhbhai Patel College, India
Published: October 2024

In agriculture, optimizing crop yield and maintenance practices is essential for ensuring food security and sustainable farming. Traditional approaches often lack the efficiency needed to process large agricultural datasets and accurately predict yield under varying environmental conditions. This project leverages the Light Gradient Boosting Machine (LightGBM), a high-performance, gradient- boosting framework specifically designed for large-scale data handling, to address the challenge of yield prediction and crop maintenance optimization. By integrating LightGBM, which handles heterogeneous data with high accuracy, we aim to enhance predictions on crop yield while minimizing resource use. The proposed method analyzes a range of factors, including soil quality, weather conditions, irrigation practices, and historical crop yield records. Initial results indicate that LightGBM outperforms conventional models with a 94.7% accuracy rate in yield prediction and reduces maintenance costs by up to 20% by recommending optimized agricultural practices based on specific environmental conditions. These findings underscore the potential of LightGBM as an effective tool in precision agriculture, ultimately aiding farmers in making informed decisions and improving agricultural productivity.
Home Transcutaneous Electrical Stimulation Rehabilitation Program for Patients With Ankylosing Spondylitis: Crossover Trial
Authors: Lin Yu-Chih , Wu Chen-Ching , Sung Wan-Yu , Yen Jeng-Hsien , Lin Yi-Ching
Published: October 2024

Background

Maintaining physical function and preserving spinal flexibility have been challenging in managing ankylosing spondylitis (AS). Most rehabilitation programs, including manual therapy, massage, hydrotherapy, and acupuncture, cannot be performed at home. The effect of transcutaneous electrical nerve stimulation (TENS) was validated in treating AS, but no home TENS system has explored its efficacy to date.

Objective

This study aims to evaluate the efficacy of a home TENS system with a novel treatment program for patients with AS.

Methods

The modified WeHeal TS-200 TENS and galvanic response system provided home-based TENS treatment for patients with AS. Patients were divided into a 2-month course group and a 1-month course group. After the first treatment course, patients went through a washout period for the same duration of their treatment course. Participants could decide whether to accept the second course of treatment. The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Schober test, finger-to-floor flexion test, enthesis score, cytokines, chemokines, inflammatory factors, and immunoglobulins were measured to evaluate its efficacy. The clinical trial protocol (1096607481) received approval from the Ministry of Health and Welfare in Taiwan.

Results

A total of 9 patients (5 in a 2-month course group and 4 in a 1-month course group) completed the first treatment course, and 5 patients (4 in a 2-month course group and 1 in a 1-month course group) completed the sequential treatment course. The weighted results showed that patients reported an improving BASFI score (mean difference –0.9, SD 1.7; P=.03) after treatment. Looking into the trajectories, declined BASFI and BASDAI scores were noticed during treatments; this score increased during the washout period. There were improving trends in the Schober test (mean difference 1.9, SD 4.9; P=.11) and finger-to-floor flexion test (mean difference –0.6, SD 9.5; P=.79), but the results were not statistically significant. The response of cytokines, chemokines, inflammatory factors, and immunoglobulins before and after treatment did not show a consistent trend, and all results were not statistically significant (all P>.05).

Conclusions

The home TENS device demonstrated a potential role in AS management. It may improve accessibility and adherence for patients with AS and provide remote monitoring for clinicians. Further research can compare the effectiveness of electrotherapy at home or in a medical setting and focus on integrating the home TENS system and exercise program to enhance patients’ physical functions and spinal flexibility.
Themes in Abortion Forum Discussions in a Restrictive Access Context: Qualitative and Quantitative Analyses
Authors: Klimiuk Krzysztof Bartosz , Kot Amelia , Majcherek Ewa , Kubiak Katarzyna B , Balwicki Łukasz
Published: October 2024

Background

Abortion is one of the most common medical procedures worldwide. Despite this, access to abortion on demand remains restricted in many countries, including Poland. As a result, many women resort to undergoing the procedure without medical supervision, putting themselves at risk of serious health consequences such as drug poisoning, excessive bleeding, and hypovolemia. Unfortunately, some abortions also lead to severe infections.

Objective

This study aims to qualitatively identify key themes in abortion forums to analyze the issues faced by individuals. The forums were then quantitatively analyzed to determine which problems were most prevalent.

Methods

The most popular abortion forums were identified. A preliminary thematic analysis was conducted for the qualitative phase, followed by a manual quantitative analysis. Two independent researchers reviewed forum posts, categorizing them into specific themes.

Results

An analysis of 13,397 responses from 370 threads across 4 forums revealed “Abortion Process Progression” as the most discussed theme, highlighting a strong demand for information, emotional support, and medical guidance. The highest percentage of threads (162/886, 18.3%) focused on the need for mental support and the desire to have someone in contact during the abortion process. Concerns about the effectiveness of the termination also emerged as a significant topic, accounting for 83 of the 886 (9.4%) discussions. “Emotional and Psychological Aspects” and “Medical and Pharmacological Aspects” were also significant, highlighting the need for holistic care. Anxiety and fear related to the process were frequently discussed, accounting for 60 of the 886 (6.8%) responses. The issue of isolation and lack of support was also a common topic, appearing in 30 of the 886 (3.4%) threads. Notably, “Social and Ethical Perception” accounted for only 13 of the 886 (1.5%) responses and appeared in just 13 threads.

Conclusions

This study highlights the critical need for information and support for women navigating abortion, particularly in regions where access is restricted. It emphasizes the importance of addressing the multifaceted challenges women face and calls for policy changes and strengthened support networks to improve the health and rights of women, as well as all those seeking gynecological care in abortion contexts. Further research is encouraged to refine and expand support strategies.
Institutional Framework for Methane Emissions Reduction in Nigeria: Policy Insights and Implementation Strategies (Preprint)
Authors: Raimi Morufu Olalekan , Ezekwe Ifeanyichukwu Clinton , Agusomu Tano Dumoyei , Enyinnaya Okoro , Amakama Nimisingha Jacob , German Ikimi Charles
Published: October 2024

UNSTRUCTURED

This report presents an analysis of the institutional framework for methane emissions reduction in Nigeria, focusing on the Niger Delta region. Methane emissions in this area arise mainly from oil and gas extraction activities, particularly through gas flaring and fugitive emissions. Nigeria stands among the world’s leading methane emitters, with the Niger Delta playing a significant role due to its dense oil extraction infrastructure. However, the existing data on methane emissions remains inconsistent, revealing gaps between local assessments and satellite observations. This discrepancy hampers efforts to accurately gauge emissions and implement effective strategies for reduction. The environmental impact of methane emissions in the Niger Delta is profound, affecting air quality and contributing to climate change. Limited monitoring and reporting efforts restrict the ability to assess emissions accurately. Recent studies indicate that capturing gas from flaring could yield economic benefits and enhance public health. Nigeria’s initiatives for methane reduction, such as the 2018 Short-Lived Climate Pollutants Action Plan, aim to eliminate gas flaring by 2030. However, slow progress stems from inadequate infrastructure and enforcement challenges, highlighting the need for a more robust institutional framework. To address these challenges, stakeholders, including funding agencies, research institutions, and local communities must adopt actionable strategies to mitigate methane emissions effectively. The development of policy components should include stringent regulations, robust monitoring mechanisms, and incentives for adopting cleaner technologies. This report proposes both national and global policy statements that outline clear goals for reducing methane emissions while fostering collaboration among various stakeholders. By prioritizing transparency, education, and community engagement, Nigeria can create a cohesive framework for effectively tackling methane emissions, advancing both environmental sustainability and economic growth.
Research on the Current Status and Countermeasures of Family Education Guidance Provided by Kindergartens in the Transition from Kindergarten to Primary School: A Case Study of X Kindergarten in Jimo District, Qingdao City, Shandong Province
Authors: Zhao Mengyao , Yan Jingru
Published: October 2024

This study investigates the current status of family education guidance provided by kindergartens during the transition from kindergarten to primary school in Jimo District, Qingdao City, Shandong Province, and proposes recommendations and strategies for improvement. The research identifies several issues, including deficiencies in the organizational management of family education guidance by kindergartens and the lack of a robust regulatory framework. To address these challenges, kindergartens should establish a constructive mutual assistance mechanism for family education during the transition from kindergarten to primary school and enhance teachers' empathetic skills. Additionally, a collaborative effort between home and kindergarten is essential to ensure a smooth transition for both parents and children into the primary school stage.
Evaluating the Role of Community Resource Person in the Establishment of the Startup Village Entrepreneurship Programme (SVEP) Ecosystem in West Bengal
Authors: Mazumdar Dr. Harajyoti
Published: October 2024

The role of CRP-EPs (Community Recourse Persons for Enterprise Promotion) in Bolpur-Sriniketan and Simlapal blocks of West Bengal was analysed based on mixed quantitative and qualitative research methodologies. The selection process for CRP-EPs is an essential part of the success of the Startup Village Entrepreneurship Programme (SVEP). The performance of CRP-EPs is measured by their maximum support to entrepreneurs in receiving the CEF Loan, its repayment, and the and the business facilitation for market linkage and bank linkage under the SVEP-Programme. The support is not limited to promotion but focuses on identifying potential entrepreneurs from the beginning with training, market, financial linkages, etc. In both blocks, entrepreneurs are using the retailer market as a mode of marketing, followed by wholesalers and other modes of marketing for business. Facebook, followed by WhatsApp and Instagram, is the online mode of marketing for entrepreneurs, guided by both CRP-EPs and the BRC (Block Resource Centre) Committee.
An Experimental Investigations on Design and Weight Optimization for a Light Motor Vehicle (LMV) Drive Shaft Using a Composite Material Aluminum and Glass Fiber (Al + GF)
Authors: Navghar Shailaja V.
Published: October 2024

Aluminum is primarily used in Metal Composites because of its lighter weight and higher strength. Glass fibers are wound around an aluminum shaft to create the composite. ANSYS results determine the relative amounts of aluminum and Eglass fiber in each shaft. The purpose of this study is to use a torsion test to evaluate the mechanical performance of a composite shaft composed of aluminum and glass fiber. The results are carefully examined for different combinations of glass fiber layers and aluminum layers. When the weight proportion of aluminum in the composite increases, the mechanical properties of the composites improve.
Unlocking Complexity: D-Wave\'s Role in Quantum Computing Breakthroughs
Authors: Mistry Yash
Published: October 2024

In this new era of Quantum Computing, a transformative paradigm is emerging for the enhancement of Cyber Security using the special-purpose systems like D-Wave's quantum annealers which helps the encryption system become more resilient. As quantum computing evolves, it provides new paradigms for breaking the traditional encryption methods, as the recent breakthroughs is accomplished by researchers from Shanghai University that uses D-Wave's quantum annealing capabilities in providing the researchers to successfully demonstrated the potential to compromise widely used encryption systems, including RSA and AES. The usage of quantum annealing (QA) that makes the D-Wave’s a specialized quantum system which enables an efficient computation in tackling cryptographic problems, demonstrates the implications for the data security and privacy by applying the quantum-classical hybrid architectures. This research aims to get attention on the urgent need for developing a new security measures in response to the vulnerabilities exposed by the quantum advancements which emphasizes the crucial role of D-Wave's in unlocking the complexities of quantum computing and its implications for the future of cybersecurity.
Biological literacy skills of senior high school student using local potential-based biodiversity question sets
Authors: Hidayat Arkhis Emilia , Wisanti W. , Isnawati I.
Published: October 2024

One of the efforts to improve the quality of education in Indonesia is through learning by integrating environmental culture. Environmental culture can be packaged in more meaningful learning through biological literacy. This study aims to assess the biological literacy skills of high school students using local potential-based biodiversity question sets. This study includes research with quantitative descriptive methods that aim to describe the biological literacy skills of high school tenth grade students. Biological literacy research data consists of 4 indicators, namely nominal, conceptual, multidimensional and functional. The number of participants was 60 high school students. The initial stage used expert judgment for content validation which was tested by 3 expert validators. Construct validation was carried out based on data collection with the results of 12 question sets that were declared valid. Data analysis of the percentage of students who answered correctly on biological literacy indicators were all at a high level, namely on nominal indicators of 69.37%, conceptual indicators of 70%, functional indicators of 66.87%, and multidimensional indicators of 70%. It is concluded that the local wisdom-based biodiversity question set can be used to measure students' biological literacy skills in schools.
Правовые изъяны градостроительной проектной деятельности
Authors: Митягин Сергей
Published: October 2024

Практика регулирования градостроительной деятельности на базе Градостроительного кодекса Российской Федерации показала возможность относительно легитимного снижения общей обеспеченности населённых пунктов объ­ектами социальной сферы. Причиной этого стал объектный подход к нормированию территориальной организации страны, регионов и муниципальных образований, связанный с размещением объектов капитального строительства, а также фактически свободный выбор территорий для подготовки проектной документации по планировке, к которым нельзя адекватно при­менить расчётные нормы доступности и обеспеченности объектами инженерного обустройства и социального обслуживания населения. Предлагается вернуться к единой системе проектной архитектурно-градостроительной деятельности, в основу которой необходимо положить комплексное территориальное планирование административно-территориальных образований и градостроительных комплексов.
Основная полоса расселения - концептуализация производных понятий
Authors: Григорьев Владимир
Published: October 2024

Теоретическое развитие концепции «Основной полосы расселения на территории Российской Федерации», используемой в отечественной географии расселения, а также в градостроительстве и районной планировке, позволило обо­сновать актуальность применения ряда производных понятий, таких как зона обживания РФ, ресурсная зона РФ, охраняемые районы РФ. Данные элементы могут оказаться перспективными для целей пространственного макрозонирования территории страны. Зона обживания РФ в этом случае рассматривается как территория, предназначенная для обеспечения устойчивого социально-демографического воспроизводства населения Российской Федерации. Намечены базовые критерии выделения зоны обживания на территории страны. Дана краткая функциональная характеристика трёх рассматриваемых макрозон.
Модернизация и инновационное развитие городов:взаимообусловленные процессы
Authors: Кулешова Галина
Published: October 2024

Эффективность развития инновационной экономики и модернизация городов - взаимосвязанный и взаимо­обусловленный процесс создания комфортных условий для проживания населения, улучшения инвестиционного климата и формирования предпринимательской среды. Для обеспечения этого процесса принят рад директивных документов, в рамках которых разрабатываются современные планировочные стратегии модернизации городской среды, направленные на привле­чение высококвалифицированных специалистов, развивающих инновационную сферу. Во многих регионах этот процесс идёт с недостаточной скоростью и наполненностью, в связи с чем очевидны необходимость и целесообразность раскрытия сути теоретических предпосылок модернизационных процессов городской среды. Новизна подхода заключается в обосновании взаимосвязи и взаимообусловленности процессов модернизации городской среды и развития инновационной экономики.
Визуализация моделей урбанизированных территорий на игровых движках
Authors: Парыгин Данила , Феклистов Владислав , Назаров Константин , Финогеев Антон , Акользин Максим
Published: October 2024

В статье приведён обзор подходов к решению проблем создания цифровых двойников с использованием графических движков в задачах информационного моделирования. Приводятся результаты сравнения существующих ре­шений на основе движков Unreal Engine и Unity. Описан процесс подготовки исходных данных по комплексу строительных объектов и территории в целом с использованием программ Archicad и Blender, а также технологии Lidar для воссоздания и уточнения специфических объектов пространства. Выделены три этапа подготовки модели к внедрению в приложение, включающие импорт подготовленных моделей объектов, настройку окружения и визуальных эффектов с использованием Lumen и разработку функций внутри модели. Детализирован процесс создания динамического функционала и проработки компонентов модели, реализуемый с использованием возможностей игрового движка Unreal Engine. Сделаны вывод о пер­спективах применения Unreal Engine для решения архитектурных и инженерных задач.
Анализ влияния принципов гетерогенной кристаллизации на формирование структуры и свойств пеностекла
Authors: Федосов Сергей , Баканов Максим , Грушко Ирина
Published: October 2024

В статье представлены результаты экспериментальных исследований, направленных на влияние различных сырьевых материалов и методов технологической обработки на структуру и свойства пеностекла. Теоретические предпосылки к работе изложены в первой части статьи. Проанализированы процессы подготовки шихты, включающие в себя измельчение и отсев сырья, а также мето­дика формовки образцов с использованием гидравлического пресса. Особое внимание было уделено анализу полученных образцов пеностекла с помощью рентгенофазового анализа и микротомографии для определения их фазового состава и пористости. Результаты исследования показали, что изменение содержания оксида хрома и мела в составе пеностекла оказывает влияние на его пористость и структуру, что является ключевым фактором при разработке новых материалов с улучшенными эксплуатационными свойствами.
Часть 1. «Введение в методологию исследования» статьи «Анализ влияния принципов гетерогенной кристаллизации на формирование структуры и свойств пеностекла» опубликована в № 1 журнала «Academia. Архитектура и строительство» за 2024 год.
Оценка теплозащитных свойств наружных стен из полистиролбетонных блоков каркасно-монолитного здания
Authors: Корнилов Терентий , Эверстова Варвара
Published: October 2024

При строительстве многоэтажных зданий широко применяется технология каркасного домостроения из моно­литных железобетонных конструкций. Рассмотрена возможность применения однослойных наружных стен из полистиролбетон­ных блоков (ПСБ-блоков) в каркасно-монолитных зданиях при экстремальных условиях Севера. Выполнен теплотехнический анализ с применением ПК HEAT 3 трёх различных фрагментов ограждающих конструкций с теплопроводными включениями при расчётной температуре наружного воздуха в условиях строительства в городе Якутске и определены их теплотехнические характеристики. Установлено, что в угловых участках примыкания наружных стен из ПСБ-блоков к железобетонной плите пере­крытия минимальная температура на внутренней поверхности ниже температуры точки росы. В результате натурных обследований эксплуатируемого здания выявлена инфильтрация воздуха на горизонтальных участках примыкания кладки из ПСБ-блоков к нижней поверхности железобетонной плиты перекрытия. Предложено конструктивное решение, улучшающее тепловую защиту на угловом участке примыкания наружной стены к плите перекрытия.
Эксперименты Ивана Жолтовского
Authors: Нащокина Мария
Published: October 2024

Статья посвящена малоизученной проблеме творчества архитектора И.В. Жолтовского - эксперименту как неотъемлемой­емлемой части его творческого метода. Материалом для исследования стали три произведения зодчего 1910-х годов. Раскрываются истоки методологии «подражания», которая, сформировавшись в эстетике классицизма, немного трансформировалась, но в целом сохранялась в эпоху романтизма и в период эклектики, то есть превалировала в учебном процессе Императорской Академии худо­жеств на протяжении всего XIX века. Эта методология во многом предопределила мировоззрение Жолтовского, что ярко проявилось уже в одном из его самых известных произведений - особняке Тарасовых. Эксперименты с ордером рассмотрены на примерах перестройки усадебного дома в Покровском-Рубцове и в строительстве текстильной фабрики Коноваловых в Бонячках (Вичуге). Использованы библиографические источники и записи учеников И.В. Жолтовского (в том числе ранее не публиковавшиеся).
Нормы для жилища периода Великой Отечественной войны 1941–1945 годов
Authors: Яхкинд Светлана
Published: October 2024

В военное время ХХ века велась разработка нормативов для проектирования жилища, но, в первую очередь, - временного. В статье впервые анализируются положения ГОСТ 1039-41 «Общежития временные. Нормы проектирования» и один из этапов формирования отечественного нормирования жилых зданий (развития типов объектов и их типологических характеристик). Влияние социально-политических и экономических факторов является важным для понимания условий становления и последующего развития нормативной базы в целом.
Проводится сравнение отдельных параметров казарм для рабочих в дореволюционной России, а также фактического состояния обеспеченности жилищем на одного заселяемого в СССР - в довоенный и военный периоды.
Вознесенская церковь в деревне Пияле Архангельской области.Строительная история, архитектура, работы по сохранению
Authors: Жигальцова Татьяна , Бодэ Андрей , Ханова Оксана
Published: October 2024

Объектом исследования является Вознесенская церковь 1654 года в деревне Пияле - уникальный памятник деревянного зодчества, относящийся к редкому архитектурному типу и отличающийся самой большой высотой среди русских деревянных храмов. Актуальность работы определяется неизученностью истории и архитек­туры объекта, нераскрытым пониманием места объекта в типологической картине русского деревянного зодчества, недостаточной определённостью его значения как объекта культурного наследия. Предметом исследования является типологические особенности Вознесенской церкви в ряду деревянных крещатых храмов, строительные этапы объ­екта, его историко-культурная ценность. Объект впервые получает достаточно полное комплексное исследование, включающее изучение архивных источников, анализ архитектуры в контексте типологии и истории русского дере­вянного зодчества. В статье проанализированы все ранее проводившиеся работы по сохранению объекта, подведены их итоги на сегодняшнее время. Теоретическая значимость статьи заключается в расширении знаний по истории и типологии русского деревянного зодчества, полноценном введении в научный оборот одного из лучших памятников деревянного зодчества. Практическая значимость статьи - в том, что в ней сформулированы основные реставраци­онные проблемы, комплексно сложившиеся в результате прошлых работ, которые предстоит разрешить в проекте реставрации, разрабатываемом в настоящее время.
Об объекте и предмете архитектуры и капитального строительства
Authors: Кияненко Константин
Published: October 2024

На протяжении последних десятилетий происходит процесс замещения в официальном языке российских документов, значимых для архитектурной практики, терминов, обозначающих объект архитектурной деятельности. «Объект капитального строительства» (ОКС) агрессивно вытесняет ещё недавно привычные «архитектурной объект» и «здания и со­оружения». Это явление обнаруживается в результате понятийно-терминологического анализа нескольких нормативных и законодательных документов, изданных за период с 1995 по 2022 год. С использованием энциклопедического определения и на основе модели «жизненного цикла» здания выводится истинное значение концепта ОКС как относящегося только к этапу строительства, неоправданность его претензий на роль зонтичного понятия, охватывающего все состояния создаваемого и эксплуатируемого объекта. Показано, что только «здание» и «архитектурный объект», но не ОКС, являются носителями композиционных, функционально-планировочных и эксплуатационных, потребительских свойств. Подмена первых вторым в лексиконе архитекторов и строителей теоретически необоснованна и чревата проблемами для всего архитектурно-строи­тельного дела.
О дискретности городских пространств
Authors: Бондаренко Игорь
Published: October 2024

Статья преследует цель показать, что древним и средневековым городам была присуща пространствен­ная дискретность, обусловленная патриархально-общинной системой землепользования, замкнутостью семейного быта, строгой социальной и церковной субординацией. Поселения включали в себя самодостаточные «микромиры», разделённые лишь вспомогательными межевыми пространствами. Существовали и относительно крупные улицы и площади, но им тоже была свойственна пространственная обособленность. Совсем по-другому стали осмысливаться и формироваться города Нового и Новейшего времени. Приоритетное развитие в них получил пространственный каркас государственной значимости. Приватные пространства при этом оказались второстепенными и сократились до мини­мума. Метаморфоза произошла под знаком борьбы с дробностью и «рыхлостью» городской ткани во имя достижения её максимально возможной объёмно-планировочной и композиционно-стилистической целостности. Автор приходит к выводу о целесообразности возвращения к более традиционной и умеренной системе пространственной структури­зации современного города.
Классификация плотного облака точек при моделировании рельефа
Authors: Данилова Лада , Рашевский Николай , Рекунов Сергей , Трудов Ярослав , Гуртяков Александр
Published: October 2024

В статье рассмотрены существующие алгоритмы классификации элементов модели поверхности. Приведён порядок действия для фотограмметрической обработки снимков беспилотных летательных аппаратов. Описано оборудование, необходимое при подготовке исходных материалов аэрофотосъёмки для фотограмметрии. Представлены особенности обработки данных, полу­ченных с беспилотных летательных аппаратов, с использованием программного комплекса «Agisoft Metashape». Предложен новый подход к классификации элементов модели поверхности и группировки однотипных элементов в отдельные слои плотного облака точек, а также проанализирована возможность построения достоверной цифровой модели рельефа по материалам аэрофотосъемки полностью в автоматическом режиме. Подведены итоги проведённой работы по связке «геодезия - генплан - здание» и выявлены положительные и проблемные стороны применения новых информационных технологий в проектировании.
Disciplinary Liability and Other Means Impacting the Employee’s Behaviour in Labour Relations in Latvia and Lithuania
Authors: Kārkliņa Annija , Mačernytė-Panomariovienė Ingrida
Published: October 2024

The article examines the regulation and practice of employee liability in employment relationships in two Baltic states – Latvia and Lithuania. Considering that the Latvian Labour Law regulates the disciplinary liability of employees, while in Lithuania disciplinary punishments (except for the most severe punishment – dismissal) have not been provided for since 2017, the authors analyse the regulatory framework of these countries and reflect on the case law, as well as outline the main differences and problematic issues in the context of employee liability.
Direct Recall as an Instrument of Political Liability of Public Authorities Before Voters in the Republics of Poland and Latvia
Authors: Jackiewicz Andrzej , Rytel-Warzocha Anna
Published: October 2024

The direct and participatory democracy is becoming increasingly popular in recent years in Europe. States are introducing new institutions into their constitutional systems, which, on the one hand, strengthen the ability of citizens to influence decision-making processes and, on the other hand, allow them to control the actions of public authorities. One of such institutions is a “recall”, which provides citizens with the right to recall, by way of voting, the public authorities elected directly by citizens. The institution of recall may take either direct or indirect form. Nevertheless, only a “direct recall” that takes place at the request of citizens can fully satisfy their interests. The direct recall at the national level is a relatively rare institution, hence, Latvian solutions in this area that allow for the recall of parliament before the end of its term may be considered unique, whilst in Poland the institution of direct recall occurs at the local level. Polish experiences with the practice of recalls indicate that for this institution to function effectively, it is necessary to adopt appropriate legal regulations. For example, the high turnout threshold adopted in both countries, which determines the binding nature of the vote, may be a factor that significantly reduces the effectiveness of this measure. The authors present the current legal regulations concerning the institution of direct recall in both states, as well as provide their critical assessment.
Domestic Violence in the Focus of Estonian Penal Policy and Implementation of the Law in the Light of the Istanbul Convention Requirements
Authors: Kaugia Silvia
Published: October 2024

Domestic violence is a multi-faceted phenomenon, encompassing social, psychological, medical and, certainly, legal aspects. Depending on the existing legal framework, it is the lawyers who have the possibility and even the duty to assist and protect the victim and to apply various sanctions against the perpetrator. The decision on the Principles of Criminal Policy until 2030, adopted by the Estonian Parliament, formulates the goal of the penal system as supporting law-abiding lifestyles and thus ensuring that the norms based on the values of our society are implemented, violations are responded to and conflicts are resolved fairly. These are goals that, if realised, could also contribute to reducing domestic violence in society. Estonia has ratified the Istanbul Convention and has made amendments to national legislation in accordance with the requirements of the Convention. Dealing with cases of domestic violence is nevertheless relatively problematic, especially from the perspective of the victim. The predominance of the settlement procedure or the practice of out-of-court restorative justice and conciliation in domestic violence cases, in the opinion of this author, tends to support the position of the perpetrator of violence.