bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiple Thromboembolic Events in Young Patient with Homozygous T-786C Mutation in the Endothelial Nitric Oxide Synthase Gene (ENOS)
Authors: Amzai Gazmend , Mena Krenar , Fazliu Zekije , Apostoloski Branko , Nechofski Stojnela , Dervishoski Alil , Muca Argjent , Karanfilski Oliver
Published: July 2024

Thromboembolic events are a common cause of morbidity and mortality with significant socioeconomic impact especially when young patients are affected. They are a rare medical event in young people and their clinical presentation can be mild or asymptomatic. The manifestation of symptoms and thrombotic events depends on both: the genetic mutations and the external risk factors that will induce the process. We present a case of a 34-year old young female, with three consecutive cerebrovascular insults in a period of ten years, and an acute myocardial infarction. There is a combination of gene mutations and polymorphism, with a predisposition to thromboembolic events. We emphasized the role of e-NOS (Endothelial nitric oxide synthase 786 T>C mutation) and the connection with smoking. The dual effect of the prolonged smoking and dysfunctional nitric oxide synthase in our young patient led to several thrombotic events. We discussed the various diagnostic tests and possible therapeutic and prophylactic strategies.
Association Between Membranoproliferative Glomerulonephritis and Colorectal Cancer – A Case Report
Authors: Severova Galina , Karanfilovski Vlatko , Naunovska Ljupka , Suleyman Sabir , Markovska Zaklina Sterjova , Gjorgjievski Nikola , Severova Ana Stojanoska , Dzekova-Vidimliski Pavlina , Ristovska Vesna , Rambabova-Bushljetik Irena , Arsenkov Ljuben , Petrushevska Gordana
Published: July 2024

Membranoproliferative glomerulonephritis (MPGN) is a rare glomerular disease characterized by mesangial hypercellularity and thickening of the glomerular basement membrane (GBM). MPGN can be idiopathic or associated with malignancy, systemic immune complex disorders and chronic infections. It has rarely been associated with solid organ tumors, such as lung, gastric, breast or prostate cancer. We report a patient with MPGN and coexisting colorectal carcinoma.

A 48-year-old man presented with anemia, loss of weight, hypertension, and nephrotic syndrome. The renal biopsy findings were compatible with type 1 MPGN. The antineutrophilic cytoplasmic antibodies, antinuclear antibodies, anti-GBM, serologic markers of hepatitis B and hepatitis C and tumor markers were negative. After ruling out the secondary causes of MPGN, the patient was treated with pulse doses of methylprednisolone and a single dose of cyclophosphamide. However, due to the worsening anemia and rectal bleeding, a colonoscopy was performed, which established a diagnosis of adenocarcinoma of the descending colon. The patient was treated with left hemicolectomy and oral corticosteroids. Within a year after the cancer treatment, the patient experienced a complete resolution of the proteinuria and improvement of the kidney function.

Although rare, MPGN can be associated with hematologic malignancies and solid organ tumors. The most common causes of secondary MPGN should be ruled out before starting specific treatment. In our patient, cancer treatment has led to a subsequent remission of the nephrotic syndrome, which indicated that this association was not coincidental but rather causal. In patients with a tumor and concomitant glomerulopathy which is suspected to be paraneoplastic in etiology, the treatment of the underlying malignancy should be prioritized.
Aspirin Resistance and Ischemic Stroke
Authors: Lichkova Elena , Nakova Valentina Velkoska , Arsovska Anita , Shorova Meri , Stomnaroska Daniela Ristikj
Published: July 2024

Objective: Acetylsalicylic acid (ASA) is the most widely used antiplatelet agent in treating ischemic strokes. ASA resistance varies between the populations, from 5% to 60%. We aimed to determine the prevalence of ASA resistance in our population, its association with demographic characteristics, risk factors, and the occurrence of recurrent ischemic stroke (IS). (IST).

Methods: One hundred consecutive patients with primary or recurrent IS were prospectively included. Strokes were diagnosed with computed tomography (CT) or magnetic resonance imaging (MRI). In all patients a detailed history of cardiovascular risk factors and fasting blood analyzes (blood count, glycemia, HbA1c, degradation products, lipid profile) were taken, and the ASA resistance was examined with the Innovance PFA 200 system. The ASA resistance was examined after a minimum of 1 month of regular use of ASA 100 mg per day.

Results: The prevalence of ASA resistance was 32%. ASA-resistant patients were statistically significantly older (69.9±7.5 vs, 61±1 y., p<0.05), and of male gender (75 vs, 45.6%, p<0.05). Previous cardiovascular diseases were statistically significantly more common in the ASA-resistant patients compared to the ASA-sensitive patients (46.8 vs 26.5%, p<0.05). The presence of recurrent stroke in the ASA-resistant versus ASA-sensitive patients was statistically significant (75% vs. 22.05%, p<0.0001). There was no statistically significant difference in the investigated laboratory parameters and the risk factors between the ASA-resistant and the ASA-sensitive patients.

Conclusion. The prevalence of ASA resistance in our population is high. According to our results, ASA resistance testing should be done in the older male individuals with a previous burden of cardiovascular diseases.
Tumor Budding as a Prognostic Marker in Primary Colon Cancer – A Single Center Experience
Authors: Dukoska Daniela Bajdevska , Zdravkovski Panche , Kostadinova-Kunovska Slavica , Krsteska Blagica , Karagjozov Pance , Dzambaz Darko , Nikolovski Andrej , Antovic Svetozar , Jankulovski Nikola , Petrushevska Gordana
Published: July 2024

Introduction: Tumor budding (TB) is considered to be a morphological and prognostic factor relevant to colon cancer (CC). The aim of our study is to assess the TB and to evaluate its relationship to clinicopathological findings within stage II and III CC patients as a single center experience.

Materials and methods: A total of 120 CC patients operated between 2018 and 2021 at the University Clinic of Digestive Surgery in Skopje, the Republic of North Macedonia were included in this retrospective, single center study. TB was evaluated by the magnification of 200x along the invasive front of the primary tumor on H&E and CKAE1/AE3 immunohistochemically stained sections. Two grades were used: low grade (TB1, 0-4 TBs) and high-grade, which includes intermediate (TB2, 5-9 TBs) and high grade (TB3 ≥10TBs) of TBs.

Results: A statistically significant correlation has been identified between high-grade TB and age (p=0.05) of the patients. There was also a significantly higher occurrence of high-grade TB in patients within stage III CC. Statistically significant correlations were also found in lymph node status (p<0.01), vascular invasion (p<0.05), lymphatic invasion (p<0.01), postoperative relapse (p<0.01), and death (p<0.01). Tumor relapse and death were significantly more frequent in patients with high-grade TB than those with low-grade TB. Patients with registered high-grade TB demonstrated significantly lower relapse-free survival (RFS) and overall survival (OS) rates than patients with low-grade TB over the observation period (RFS: 53.8% vs. 98.5%, p<0.001; OS: 65.4% vs. 97.1%, p<0.001, respectively). Patients with lung and liver postoperative relapses had higher percentage of cases with high-grade TB (94.1%).

Conclusion: Our results are highly suggestive that TB should be included as a histological biomarker in the pathology report of patients with stage II and stage III CC, because of its prognostic value.
Spatial and functional dynamics of regional economic subsystems maintenance intensity by road infrastructure
Authors: KOSOBUTSKAYA Anna Yu. , ZAGORNAYA Tat’yana O.
Published: July 2024

Subject. This article discusses the role of road infrastructure in the development of the economy and the issue of ensuring the interconnection of economic subsystems of the region. Objectives. The article aims to determine the degree of influence of the road infrastructure of the regions of Russia on economic subsystems. Methods. For the study, we used the virtual clustering method and a regression analysis. Results. The study outlines the spatial and functional configuration of the Russian regions distribution by intensity of road infrastructure service of economic subsystems. The relevant statistical indicators are correlated with the length of public roads of federal, regional or inter-municipal and local significance. Calculations help predict the increase in the intensity of service for almost all subsystems. Relevance. The practical application of the study results will contribute to the strengthening of strategic and operational management systems for the development of road infrastructure.
Evaluation of Lettuce Cultivation in an Aquaponic System, With and Without Bioflocs, Compared To a Hydroponic System, In a Greenhouse in Southern Brazil
Authors: Da Rocha Andréa Ferretto ,   Department Of Agricultural Diagnosis And Research
Published: July 2024

A recirculation system was set up to evaluate lettuce production (floating) in aquaponics (Aqua)
Deterministic Multistage Constellation Reconfiguration Using Integer Programming and Sequential Decision-Making Methods
Authors: Lee Hang Woon , Williams Rogers David O. , Pearl Brycen D. , Chen Hao , Ho Koki
Published: July 2024

This paper addresses the problem of reconfiguring Earth observation satellite constellation systems through multiple stages. The Multistage Constellation Reconfiguration Problem (MCRP) aims to maximize the total observation rewards obtained by covering a set of targets of interest through the active manipulation of the orbits and relative phasing of constituent satellites. This paper considers deterministic problem settings in which the targets of interest are known a priori. We propose a novel integer linear programming formulation for MCRP, capable of obtaining provably optimal solutions. To overcome computational intractability due to the combinatorial explosion in solving large-scale instances, we introduce two computationally efficient sequential decision-making methods based on the principles of a myopic policy and a rolling horizon procedure. The computational experiments demonstrate that the devised sequential decision-making approaches yield high-quality solutions with improved computational efficiency over the baseline MCRP. Finally, a case study using Hurricane Harvey data showcases the advantages of multistage constellation reconfiguration over single-stage and no-reconfiguration scenarios.
Low-Earth-Orbit Mega-Constellation Low-Redundancy Design: Rapid Performance Analysis and Adaptive Configuration Layering
Authors: Xiao Yao , Guo Shuai , Luo Yazhong
Published: July 2024

Megaconstellations, which offer convenient communication and navigation services, are at the forefront of satellite application advancements. However, traditional constellations with a single uniform configuration fail to meet the various demands in different regions, thus leading to low utilization. In addition, satellite safety becomes a key consideration that megaconstellations cannot ignore. To address the aforementioned problems, this study proposes an adaptive method for designing layered megaconstellations under the assumptions of circular orbits, uniform distribution in each plane, and a pregiven altitude. Two novel methods are developed for evaluating the coverage performance and satellite safety. First, the longitude-coverage-ratio model is proposed based on the street of coverage theory, enhancing the constellation design for latitude-specific coverage needs. Next, a rapid method is derived for calculating the minimum angular distance between planes. Then, the study investigates the models to be used in subconstellation design techniques for assembling multilayer hybrid megaconstellations. Several hybrid megaconstellations are designed, demonstrating the applicability of the methodology for both nonuniform and global uniform coverage requirements. The results show that this method offers reduced redundancy and a lower number of satellites compared to a single Walker. The examples also suggest that low-Earth-orbit hybrid constellations can achieve global uniform coverage when reaching sufficient coverage folds.
Airside Surveillance by Computer Vision in Low-Visibility and Low-Fidelity Environment
Authors: Thai Phat , Alam Sameer , Lilith Nimrod
Published: July 2024

Low visibility at airports can significantly impact airside capacity, leading to ground delays and runway/taxiway incursions. Digital tower technology, enabled by live camera feeds, leverages computer vision to enhance airside surveillance and operational efficiency. However, technical challenges in digital camera systems can introduce low-fidelity transmission effects such as blurring, pixelation, or JPEG compression. Additionally, adverse weather conditions like rain and fog can further reduce visibility for tower controllers, whether from digital video or out-of-tower views. This paper proposes a computer vision framework and deep learning algorithms to detect and track aircraft in low-visibility (due to bad weather) and low-fidelity (due to technical issues) environments to enhance visibility using digital video input. The framework employs a convolutional neural network for aircraft detection and Kalman filters for tracking, especially in low-visibility conditions. Performance enhancements come from pre- and postprocessing algorithms like object filtering, corrupted image detection, and image enhancement. It proves effective on an airport video dataset from Houston Airport, enhancing visibility under adverse weather conditions.
Strategic Planning of Aerial Assets for Disaster Response
Authors: Chin Christopher , Saravanan Akila , Balakrishnan Hamsa , Andreeva-Mori Adriana
Published: July 2024

The rapid deployment of fleets of small, uncrewed aircraft (drones) in the immediate aftermath of a natural disaster to search impacted regions for people in need of rescue is one of the most vital applications of advanced air mobility. Effective drone-based search operations require that the drone fleets operate out of bases that are appropriately located in advance of the disaster. Using a case study based in the Iwate prefecture of Japan, we develop optimization formulations to strategically locate drone bases. It is important to be capable of responding quickly to the locations most likely to require a search, while covering as large an area as possible. We evaluate the disparities in the level of access afforded to different areas. We extend our optimization formulation to account for the probability of the base locations themselves being impacted by the disaster and the possibility of base relocation. Finally, we illustrate how a vehicle routing component can be used to address the tactical portion of drone-based search operations.
Dynamic Model Reduction for Viscously Damped Structures with Statically Determinate Interfaces
Authors: Xu Lian-Kai , Wang Wei , Pan Wang-Bai , Tang Guo-An
Published: July 2024

A novel model reduction method for viscously damped structures with statically determinate interfaces, such as spacecraft flexible appendages, is proposed. The paper presents a derivation of the complete complex modal expansion of the interface dynamic stiffness of these structures. Based on the identity relation for all complex modes, which is obtained during the derivation, it is found that the interface acceleration impedance can be expressed as a rational fraction with high accuracy using only low-order complex modes. Using this rational fraction as an approximation model, numerical results of the frequency response can be fitted. The fitted interface acceleration impedance can be applied to real-time control as a reduced model in the form of a transfer function. Furthermore, it can be transformed into the form of system matrices by introducing auxiliary variables, which then participate in the dynamic analysis of the assembly. The reduction process circumvents complex modal analysis and necessitates only the results of frequency responses. Thanks to the powerful ability of conventional finite element software to perform frequency response analysis, this reduction method can be used for large-scale complex models in actual engineering applications.
Self-Adaptive Turbulence Eddy Simulation of Supersonic Combustor Considering Thermal Radiation
Authors: Xie Pengfei , Xia Zhaoyang , Lu Lu , Han Xingsi
Published: July 2024

The newly developed self-adaptive turbulence eddy simulation (SATES) method coupled with three turbulent combustion models, i.e., the finite-rate model, eddy-dissipation model, and steady laminar flamelet model, is used to numerically study the non-premixed supersonic hydrogen combustion in a DLR (German Aerospace Center) model scramjet combustor with a wedge flame holder. The study investigates the interactions of the shock waves and the flowfields as well as the flame structures. The SATES-based combustion simulation results demonstrate satisfactory agreement with the available experimental data. The study also explores the effect of fuel injection temperature on the combustion process and reveals that an increase in hydrogen temperature improves combustion efficiency. Additionally, thermal radiation effects are considered with the discrete ordinates method/weighted-sum-of-gray-gases method. The results indicate that thermal radiation heat transfer reduces the flame temperature and significantly affects the flame shape and temperature fluctuations. Also, radiation heat flux is an important factor and should be included in supersonic combustion simulations. The study demonstrates the potential of the SATES method for complex supersonic combustion and also provides a reference for thermal radiation in supersonic combustion.
Factors Affecting Taxpayer Compliance
Authors: Mariana Citra , Andari Diah , Andriana Nadila
Published: July 2024

The aim of this study is to investigate how taxpayer awareness and tax sanctions affect individual taxpayer compliance at the Bandung Cicadas Pratama Tax Service Office. The study population comprises 102.520 individual taxpayers registered at KPP Pratama Bandung Cicadas in 2022. The sample size for this research is 100 individual taxpayers registered at the Bandung Cicadas Pratama Tax Service Office. The data analysis method in this research uses multiple regression analysis. The findings suggest that taxpayer awareness and tax sanctions have a significant impact on the compliance of individual taxpayers registered at the Bandung Cicadas Pratama Tax Service Office. However, tax socialization does not seem to influence the compliance of individual taxpayers in this office.
Effects of Türkiye’s Credit Rantings and Credit Default Swaps (CDS) on BIST ALL
Authors: Keskin Meltem
Published: July 2024

In the study, the relationship between Turkey's Credit Default Swaps (CDS) premiums and credit ratings of Standard and Poor's (S&P), Moody's Investors Service (Moody's) and Fitch Ratings (CRA) and the BIST ALL index listed in Borsa Istanbul and The aim is to observe their effects on each other. The universe of the study; consists of 3956 daily Turkey CDS credit risk premiums and BIST ALL data and 93 credit ratings given by CRAs in the period 2009:1–2024:4. The effect of the increase or decrease in CDS and credit scores on the closing values of the BIST ALL index was analysed with Johansen cointegration and Granger causality tests. Findings obtained in the study; Increasing the credit rating and outlook of CRAs causes an increase in BIST ALL closing values in the short term. The change in Türkiye CDS premiums triggers changes in BIST ALL closing values in the short and long term. Finally, the study concluded that the change in CDS premiums has a negative effect on BIST ALL, while the increase in credit score and outlook has a positive effect on BIST ALL.
Pregnancy and Unilateral Krukenberg Tumour: Factual or Fictious – A Case Report
Authors: Thomas Joel Abraham , Mathew Riya Mariam , Angela Devafrey Devaraj , Chauhan Harshit , Kingsley Pamela Alice
Published: July 2024

Krukenburg tumor, a secondary ovarian neoplasm, arises from various primary sites. It’s occurrence during pregnancy is extremely rare. We are reporting the case of a 24 year old G2P1L1 lady with a unilateral Krukenberg tumor diagnosed in first trimester of pregnancy. The case posed as a diagnostic challenge as the presentation is non-specific and radiological diagnosis is very challenging owing to the similarity of the tumour to ectopic pregnancy on imaging. The sparsity of data and unique presentation of the patient inspired us to write this report. This is a 24 year old lady who presented to the emergency department with the complaints of amenorrhea for 2 months, pain abdomen and bleeding per vaginum for 2 days. Urine Pregnancy Test done at home was positive. She was found to be in shock and was resuscitated. Ultrasonography done showed a possibility of an ectopic pregnancy with rupture or a partial molar pregnancy. She was taken up for emergency laparotomy, a lobulated, irregular right sided ovarian mass suggestive of a right ovarian neoplasm with a normal left ovary and an intrauterine incomplete abortion was found. She underwent right salpingo-oophorectomy along with the ovarian mass; with stepwise exploration of pelvis and abdomen followed by dilatation and curettage for the evacuation of the retained product of conception. Histopathological examination revealed features suggestive of metastatic Signet Ring Cell Carcinoma. Further investigation with CECT chest, abdomen and pelvis and upper GI endoscopy revealed a gastric primary. This case depicts the challenges faced by physicians in correctly diagnosing malignant tumours during pregnancy. By reporting this case, we aim to raise awareness among physicians regarding the need for heightened vigilance and multi-disciplinary approach in order to timely and accurately diagnose such conditions.
OPTIMIZATION MODELING OF THE SYSTEM FUNCTIONING OF HOMOGENEOUS OBJECTS IN A MULTI-ASPECT DIGITAL ENVIRONMENT
Authors: Сорокин С.О.
Published: July 2024

Дана характеризация системы однородных объектов, ее интер- и интрафункциональности. Предложена классификационная схема цифровизации и оптимизации функционирования системы однородных объектов. Показано, что цифровая трансформация приводит к формированию многоаспектной цифровой среды, по данным которой формируется множество математических моделей, характеризующих связи с управляющим центром, внешней средой и компонентами внутреннего функционирования. Обоснована необходимость построения инвариантных и аспектно ориентированных оптимизационных моделей решения ресурсных и структурных задач, обеспечивающих эффективность функционирования однородных объектов и удовлетворенность показателями функционирования объектов внешней среды.

This paper introduces the characterization of a homogeneous objects system and as well as its inter- and intra- functionality. It is proposed a classification scheme for digitalization and optimization of the system functioning of homogeneous objects It is demonstrated that digital transformation causes to create multi-aspect environment with many mathematical models. These models characterize the communication with the managing center, with the external environment and with the components of internal functioning. The necessity of constructing invariant and aspect-oriented optimization models for solving resource and structural problems ensuring the efficiency of the functioning of homogeneous objects and satisfaction of the performance indicators of the objects of the external environment is substantiated.
METHOD OF THE SOLUTION OF SOME CLASSES OPTIMISING TASKS
Authors: Ганичева А.В.
Published: July 2024

Актуальность данной работы обусловлена широким распространением во всех сферах жизнедеятельности важных практических задач, которые могут быть решены методами линейного программирования. Основной трудностью при применении универсального способа решения таких задач (симплекс-метода) является его вычислительная сложность. Для решения данной проблемы разрабатываются специальные методы решения частных задач линейного программирования, например, для положительных или ограниченных исходных данных. Эти частные случаи обоснованы экономическим, социальным, техническим, технологическим смыслом. В данной статье разработан метод максимизация линейной функции при одном линейном ограничении с положительными коэффициентами. Этот метод обобщен на случай максимизации линейной функции при нескольких линейных ограничениях. Полученные теоретические результаты обоснованы доказательством соответствующих теорем. Для иллюстрации полученных результатов приведены числовые примеры. Алгоритмическая сложность разработанного метода оценена для решаемых задач путем подсчета числа использованных операций и сравнении с их количеством при использовании симплекс-метода. Полученные результаты позволяют решать прикладные оптимизационные задачи в различных областях, в том числе в задачах планирования выпуска продукции, рационального питания и диеты, управления образовательным процессом и т.д.

The relevance of this work is caused by wide circulation in all spheres of activity of important practical tasks which can be solved by methods of linear programming. The main difficulty at application of a universal way of the solution of such tasks (a simplex - a method) is its computing complexity. For the solution of this problem special methods of the solution of private problems of linear programming, for example, are developed for positive or limited basic data. These special cases are proved by economic, social, technical, technological sense. In this article the method maximizing linear function at one linear restriction with positive coefficients is developed. This method is generalized on a case of maximizing linear function at several linear restrictions. The received theoretical results are proved by the proof of the corresponding theorems. For an illustration of the received results numerical examples are given. The algorithmic complexity of the developed method is estimated for solvable tasks by calculation of number of the used operations and comparison with their quantity when using a simplex - a method. The received results allow to solve applied optimizing problems in various areas, including in problems of planning of production, a balanced diet and a diet, management of educational process, etc.
MULTI-ASPECT DIGITAL ENVIRONMENT DESIGN OPTIMIZATION OF HOMOGENEOUS OBJECTS SYSTEM BASED ON THE PROCEDURES OF DECOMPOSITION AND AGGREGATION
Authors: Львович Я.Е. , Питолин А.В. , Сорокин С.О.
Published: July 2024

В статье рассматривается функционирование системы однородных объектов в условиях активной цифровизации. Показано, что интегральной структурой, объединяющей все аспекты цифровой трансформации, является многоаспектная цифровая среда, которая требует постоянного совершенствования по мере развития новых инструментов цифровизации. Возникающая задача проектирования такой среды носит оптимизационный характер. Предложено систему оптимального проектирования построить на основе сочетания нисходящего и восходящего процессов принятия проектных решений. Основой нисходящего проектирования является формализация процесса декомпозиции многоаспектной цифровой среды с использованием модели бинарного дерева. Процедуры восходящего проектирования базируются на моделях и алгоритмах многоальтернативной оптимизации с определением множества доминирующих вариантов на основе переходной матрицы марковской цепи и применения экспертного оценивания.

This article examines the functioning of the homogeneous objects system in the conditions of active digitalization. It is shown that the integral structure uniting all aspects of digital transformation is a multiaspect digital environment, which requires constant improvement as new tools of digitalization develops. The arising task of designing that sort of an environment has an optimization nature. The optimal design system is proposed to build on the basis of a combination of descending and ascending processes of decisionmaking. The descending design basis is the formalization of the decomposition process of a multidimensional digital environment using a binary tree model. The ascending design procedures are based on models and algorithms of multialternative optimization with the determination of the dominant variants set based on the transition matrix of the Markov chain and the use of expert evaluation.
CONSTRUCTION OF DECISION RULES USING THE ARTMAP NEURAL NETWORK
Authors: Каширина И.Л. , Федутинов К.А.
Published: July 2024

В статье рассматривается нейросетевая архитектура ARTMAP, совместимая с символическим представлением, основанным на IF THEN правилах. В частности, знания, полученные в процессе обучения сети ARTMAP, могут быть трансформированы в компактный набор решающих правил для классификации исходных данных, которые могут быть проанализированы экспертами предметной области, по аналогии с интерпретируемыми методами машинного обучения, такими, как деревья решений или линейная регрессия. Аналогичным образом, знания в априорной области, представленные в форме правил IF THEN могут быть преобразованы в нейросетевую архитектуру ARTMAP. Наличие предварительного набора правил, используемых при инициализации сети, повышает точность классификации и эффективность обучения. Исходный набор правил может быть дополнен с помощью алгоритма обучения ARTMAP. Каждое правило, сформированное в процессе обучения сети имеет коэффициент достоверности, который можно интерпретировать как его важность или полезность. Описание архитектуры, алгоритмов обучения и функционирования сети ARTMAP для извлечения правил представлено в терминах предложенной авторами ранее обобщенной модели сетей семейства АRT.

This article discusses the ARTMAP neural network architecture, compatible with a symbolic representation based on IFTHEN rules. In particular, the knowledge gained during the training of the ARTMAP network can be transformed into a compact set of decision rules for classifying the source data, which can be analyzed by domain experts, by analogy with interpreted machine learning methods, such as decision trees or linear regression. Similarly, knowledge in the a priori area presented in the form of IFTHEN rules can be transformed into the ARTMAP neural network architecture. The presence of a preliminary set of rules used in the initialization of the network increases the accuracy of classification and the effectiveness of training. The original set of rules can be supplemented using the learning algorithm ARTMAP. Each rule formed in the process of learning a network has a confidence factor that can be interpreted as its importance or usefulness. The architecture, training algorithms and functioning of the ARTMAP network for the extraction of rules are described in terms of the previously proposed generalized model of networks of the ART family proposed by the authors.
OACH TO ESTABLISHING A DECISION MAKING SYSTEM OF RESOURCES DISTRIBUTION FOR AUTO TRANSPORTATION COMPANY
Authors: Салих Х.С. , Егоров С.Я.
Published: July 2024

Совершенствования методов оптимального распределения ресурсов предприятий является одной из приоритетных задач развития экономики. В статье предложен подход к созданию системы поддержки принятия решений при управлении распределением транспортных и технологических машин автотранспортного предприятия по строительным объектам. В качестве примера рассмотрено автотранспортное предприятие, имеющее обширный парк грузового автотранспорта и специализированных машин для выполнения строительных работ. Для реализации механизмов управления, основанных на использовании оперативных данных со строительных объектов в работе предлагается модель управления, для которой характерно наличие гибкой обратной связи. Разработан алгоритм формирования управляющих воздействий в системе управления с обратной связью, минимизирующий расходы автотранспортного предприятия при решении комплекса задач по распределению ресурсов предприятия (машин и механизмов) по удаленным объектам.В основе подхода лежит принцип координации выполнения работ проектов по сетевым планам построенным с учетом технического состояния машин и механизмов автотранспортного предприятия. Координация решения задач производственной и технической эксплуатации парка машин и механизмов позволяет принимать обоснованные решения по использованию техники и способствует повышению общей технической готовности автотранспортного парка, что в свою очередь ведет к повышению эффективности деятельности всего предприятия, к менее затратному решению задач, поставленных в рамках крупных проектов государством.

One of the primary tasks of economics is to improve methods of the optimal distribution of company resources.The article proposes an approach to creating a decision-making system for managing the distribution of transport and technological vehicles of an auto transportation company across its construction sites. As an example, we consider a truck company that has an extensive fleet of freight vehicles and specialized vehicles for construction work.To implement control mechanisms based on the use of operational data from construction sites, a resources management model is proposed, which is characterized by the implementation of flexible feedback.We developed an algorithm for generating managing actions in a feedback-based control system that minimizes the costs of am auto transport company when solving a set of tasks for distributing the companys transport resources to remote objects.The approach is based on coordinating the implementation of projects according to the network plans that were built, taking into account the vehicles technical condition. Coordination of solving the problems of production and technical operation of a transport vehicle fleet allows us to make informed decisions on the use of the vehicles and helps to increase the overall technical readiness of the fleet. That, in turn, leads to an increase in the efficiency of the entire company and provides a less costly solution to large governmental projects.
STUDY OF THE EFFECTIVENESS OF VARIOUS CONTROL ALGORITHMS TO ENSURE THE PROTECTION OF QUEUES FROM CONGESTION IN RESOURCE RESERVATION SYSTEMS
Authors: Алькади У.
Published: July 2024

Контроль перегрузки сети является весьма актуальной задачей при обеспечении защиты очередей в системах резервирования ресурсов. Это - один из ключевых элементов, так как многие контроллеры вводились с целью контроля перегрузки для решения проблемы. Статья посвящена анализу влияния рабочей нагрузки сети на производительность различных активных контроллеров управления очередями, включая традиционный контроллер Drop Tail, для обеспечения защиты очередей от перегрузок в системах резервирования ресурсов. Данная работа представляет анализ четырех возможных сценариев с одинаковыми сетевыми параметрами за исключением рабочей нагрузки сети. Производительность каждого контроллера измеряется при помощи различных метрик производительности. Влияние нагрузки сетевого трафика на производительность сетевых контроллеров можно легко наблюдать в четырех представленных сценариях. Поведение всех контроллеров четко указывало на влияние нагрузки сетевого трафика на их производительность. Полученные результаты показали, что нагрузка на сетевой трафик прямо пропорциональна пропускной способности, потере пакетов и задержке. Результаты могут быть использованы при создании отказоустойчивых систем резервирования ресурсами.

Controlling network congestion is a very urgent task while securing queues in resource reservation systems. This is one of the key elements, as many controllers were introduced to control overload to solve the problem. This article analyzes the impact of network workload on the performance of various active queue management controllers, including the traditional Drop Tail controller, to ensure that queues are protected from congestion in resource reservation systems. This paper presents an analysis of four possible scenarios with the same network parameters except for the network workload. The performance of each controller is measured using various performance metrics. The effect of network traffic load on the performance of network controllers can be easily observed in the four presented scenarios. The behavior of all controllers clearly indicated the effect of network traffic load on their performance. The results showed that the load on network traffic is directly proportional to bandwidth, packet loss and delay. The results can be used to create fault-tolerant resource reservation systems.
STRUCTURIZATION OF ENVIRONMENTAL INFORMATION WITH APPLICATION OF GEOINFORMATION TECHNOLOGIES
Authors: Федутинов К.А.
Published: July 2024

В статье рассматриваются вопросы разработки управленческих решений по улучшению состояния окружающей среды на основе внедрения геоинформационных технологий, включающих методы оценки и прогнозирования экологической ситуации на основе мониторинговых подходов. Развитие технологий обработки больших данных определило тенденции широкого внедрения систем мониторинга, функционирующих в реальном времени. В связи с этим, задачу мониторинга природных объектов предлагается решать как задачу определения и контроля свойств и состояний сложного объекта в режиме реального времени и активного взаимодействия с окружающей средой, а также выработки управленческих решений и рекомендаций. В качестве математического аппарата для структуризация экологической информации предлагается использовать нейронную сеть Fuzzy ART, хорошо зарекомендовавшую себя при обработке данных в режиме реального времени. Для визуализации получаемой информации и интеграции результатов работы сети сети Fuzzy ART в геоинформационную систему предлагается использовать Python-библиотеку Folium, предназначенную для графического отображения географических данных, и содержащую всю необходимую картографическую информацию. С помощью Folium результаты структуризации экологических данных можно изображать непосредственно на Google-картах, что дает возможность при увеличении масштаба карты визуально определять границы кластеров и возможные буферные зоны.

The article discusses the development of managerial decisions to improve the environment through the introduction of geographic information technologies, including methods for assessing and predicting the environmental situation based on monitoring approaches. The development of big data processing technologies has identified trends in the widespread implementation of real-time monitoring systems. In this regard, the task of monitoring natural objects is proposed to be solved as the task of determining and controlling the properties and states of a complex object in real time and actively interacting with the environment, as well as developing managerial decisions and recommendations. It is proposed to use the Fuzzy ART neural network as a mathematical apparatus for structuring environmental information, which has proven itself in real-time data processing. To visualize the received information and integrate the results of the network operation of the Fuzzy ART network into a geographic information system, it is proposed to use the Folium Python library, which is intended for graphical display of geographic data and contains all the necessary cartographic information. Using Folium, the results of the structuring of environmental data can be displayed directly on Google maps, which makes it possible to visually determine the boundaries of clusters and possible buffer zones when the map is scaled up.
Stream data classification based on bayesian criteria
Authors: Ломакина Л.С. , Субботин А.Н.
Published: July 2024

рассматривается проблема классификации потоковых данных, поступающих из различных источников в случайные моменты времени. Это может быть поток данных, содержащих результаты измерения датчиков, расположенных в прибрежных зонах океанов, позволяющий оценивать параметры состояния экосистемы, и также поток текстов, получаемых, например, в письмах электронной почты и т. д. Интернет содержит большие объёмы неструктурированной информации, отсутствие организации которых делает работу с данными неудобной и ресурсоёмкой. Преодоление указанного недостатка является актуальной задачей. Классификация служит инструментом, позволяющим облегчить работу с неструктурированной информацией. Разработан алгоритм классификации потоковых данных на основе байесовского критерия. Построена математическая модель потоковых текстовых данных, позволяющая применять алгоритмы классификации текстов на естественном языке на потоковых данных. Предложена модификация наивного байесовского классификатора, использующая характеристику tf-idf как меру принадлежности терминов классам, позволяющая улучшить качество классификации. Классификатор был обучен с помощью машинного фонда русского языка. Разработано программное обеспечение, позволяющее извлекать потоковые текстовые данные из сети Интернет и производить классификацию разработанным алгоритмом в реальном времени

The paper describes the issue of stream data classification. Stream data is described as a set of objects arriving from different sources at random moments of time. It might be a stream of data containing ocean coastal area sensors measure information and describing the parameters of the ecosystem condition, as well, it might be a stream of texts acquired from incoming emails attachments, etc. The Internet contains vast volumes of unstructured information. The lack of organization makes data inconvenient and resource-intensive to work with. Addressing to such an issue considered to be a relevant problem. Classification provides an opportunity to make it easier to work with unstructured information. The paper describes the algorithm for stream data classification based on Bayesian criteria. Text stream data model is proposed. This model allows applying natural language text classification algorithms to stream data. Naive Bayes classifier modification using tf-idf measure for evaluating the proximity of a classified document to a particular class that allows improving the classification quality is proposed. The classifier has been trained using the machine Fund of the Russian language. Software allowing text data stream extraction from the Internet and its classification using the proposed algorithm in real-time scale is proposed
Configuration of commercial bank project portfolio based on simulation model
Authors: Усманова З.А. , Ханова А.А.
Published: July 2024

Решается задача построения имитационной модели конфигурирования портфеля проектов коммерческого банка. Рассмотрены основные процессы имитационной модели проектной деятельности коммерческого банка. Рассмотрена логическая схема моделирующего алгоритма, представляющая собой структуру модели процесса функционирования системы. Осуществлен анализ стохастических факторов, выявленных на основе консультаций со специалистами из различных структурных подразделений коммерческого банка, изучения специализированной литературы. Факторы случайности классифицированы в соответствие с вызываемыми ими видами банковских рисков. Подобраны распределения вероятностей для каждого из выделенных факторов случайности. Формализована задача вычисления совокупного риска портфеля проектов коммерческого банка, на основе имитационной модели. Определены структура и взаимосвязи субмоделей в имитационной модели проектной деятельности коммерческого банка. Описаны элементы имитационной модели конфигурирования портфеля проектов коммерческого банка, формирующие субмодели с использованием различных способов представления. Определены взаимосвязи между типами риска банковских проектов (входными параметрами) и совокупным риском портфеля проектов коммерческого банка (результирующим показателем). Проведены эксперименты с моделью, на основе факторного плана. Показана возможность уточнения и оценки конфигурации портфеля проектов коммерческого банка на основе теории планирования экспериментов с имитационной моделью.

The task of building a simulation model of configuration of a portfolio of commercial bank projects is solved. The main processes of simulation model of commercial bank project activity are considered. The logic scheme of the modeling algorithm is considered, which is the structure of the model of the system functioning process. The analysis of stochastic factors identified on the basis of consultations with specialists from various structural divisions of the commercial bank, study of specialized literature was carried out. The factors are classified according to the types of banking risks they cause. Probability distributions are selected for each of the selected accident factors. The task of calculating the total risk of a portfolio of commercial bank projects, based on a simulation model, has been formalized. The structure and relationships of submodels in the simulation model of commercial bank project activity are defined. Elements of simulation model of configuration of portfolio of commercial bank projects forming submodels using different presentation methods are described. Relationships between risk types of bank projects (input parameters) and the aggregate risk of the business bank portfolio (result indicator) are defined. Experiments were carried out with the model, based on the factor plan. The possibility of clarifying and evaluating the configuration of the portfolio of commercial bank projects based on the theory of planning experiments with the simulation model is shown.