bluuebunny/crossref_metadata_2025 huggingface dataset:
Teacher, I know I'm going to hell! The uneasiness in the face of tension between dominant and marginal morality in two schools in the outskirts of São Paulo
Authors: Grützmann Lidiane Fatima
Published: September 2023

ABSTRACT This paper has as object the final report of the project The ancestor and the contemporary in schools: recognition and affirmation of Afro-Brazilian histories and cultures that was developed by the research group Multiculturalism and Education (Conselho Nacional de Desenvolvimento Científico e Tecnológico) in two different public schools on the outskirts of São Paulo between the years 2016 and 2017. The shared teaching strategy led local teachers and students to enjoy esthetics and artistic experiences that were deep rooted in the African ancestry and its outcomes in the culture of São Paulo outskirts: the hip-hop, the funk, the capoeira, the rap, the grafitti, among others. The reports showed that these elements, although intersected in the midst of the field of interest of teenagers and young people, are absent of the classrooms because they are motivators of a discontentment caused by the tension between a dominant morality and a marginal one that bursts from the worked artistic expressions, essentially critical and disruptive.
Uma herança a ser lida: reflexões educacionais a partir de Hannah Arendt e Paul Ricoeur
Authors: Almeida Vanessa Sievers de
Published: September 2023

Resumo A educação oferece aos mais novos uma herança de conhecimentos e experiências, porém, com a crise da tradição, a relação das novas gerações com esse legado se torna problemática, seja porque ele perdeu sua legibilidade, seja porque é visto como ultrapassado. Este artigo sustenta que, apesar disso, cabe aos herdeiros ler, interpretar e ressignificar essa herança imperfeita. Nessa perspectiva, indaga-se, por um lado, se a tentativa de se apropriar desse legado pode provocar transformações no passado supostamente findo, e, por outro lado, questiona-se em que medida essa herança afeta os que com ela se envolvem. Ponto de partida para essa reflexão são o pensamento sobre educação de Hannah Arendt, em especial, o ensaio “A crise na educação” e a obra Tempo e narrativa de Paul Ricoeur, em particular sua abordagem da leitura no contexto da mímese III. O ato de ler, de acordo com o filósofo, se caracteriza por uma dialética que provoca transformações na narrativa e no leitor. Esse movimento mimético transformador entre leitor e texto ocorre também na dinâmica entre herdeiros e herança, que está no centro da formação dos jovens e das crianças? A partir dessa questão, busca-se estabelecer um diálogo entre a análise de Ricoeur da leitura e a reflexão sobre a tarefa da educação, segundo Arendt, de convidar os mais novos à “leitura” da herança de um mundo que os antecede.
RESPEITO, HUMILDADE, PROCEDER E RESPONSABILIDADE: A CATEGORIA "SUJEITO-HOMEM" COMO APROXIMAÇÃO ENTRE “MUNDO DO CRIME” E MASCULINIDADES PERFORMATIVAS
Authors: Oliveira João Victor Borri de
Published: September 2023

Este trabalho se insere na interface de três debates sociológicos contemporâneos: juventudes, masculinidades e “mundo do crime”. Partindo de uma pesquisa etnográfica com jovens em cumprimento de medidas socioeducativas em meio aberto em São Carlos (cidade do interior de São Paulo), proponho uma reflexão acerca da categoria  “sujeito-homem”. Considerando a perspectiva de que existem múltiplas performances de masculinidades, o meu foco é refletir em como os elementos dessas masculinidades atravessam as práticas, sociabilidades e experiências no “mundo do crime” (FELTRAN, 2008a). Para isso, irei explorar a categoria de “sujeito-homem” como um caso específico desse pensamento conjunto. O “sujeito-homem” é um jovem adulto, que  evoca signos de respeito, humildade, proceder e responsabilidade ao realizar sua performance.
Results of transjugular intrahepatic portosystemic shunt combined with selective gastric vein embolization
Authors: Sapronova N. G. , Kalinin D. S. , Kosovtsev E. V. , Khoronko Yu. V. , Stagniev D. V. , Khoronko E. Yu. , Kosovtsev R. E.
Published: September 2023

Aim. To improve the outcomes of surgical treatment of patients with cirrhosis complicated by clinically significant portal hypertension by performing TIPS with selective embolization of gastric veins.

Materials and methods. The authors explored the immediate and long-term outcomes of treatment of 62 patients with liver cirrhosis: group I included 27 patients who underwent TIPS with selective embolization of one left gastric vein; group II included 35 patients who underwent TIPS with selective embolization of ≥2 gastric veins. The authors tested a non-invasive method for predicting the risk of bleeding from gastric and oesophageal varices after TIPS with selective embolization of gastric veins and compared MRI and EGD results before and after the surgery (n = 14).

Results. The maximum follow-up duration comprised 72 months. Bleeding from the oesophageal veins was not reported in the early period after TIPS with embolization of the left gastric vein, however, the long-term bleeding developed in 2 patients (7.4%). In 6–72 months following TIPS with embolization of the left gastric vein and posterior gastric vein, as well as short gastric veins (when indicated), no recurrences of variceal bleeding appeared. The method of predicting the risk of bleeding after TIPS proved to be effective in all 14 patients in the follow-up period of 6 months (invention application No. 2022129022).

Conclusion. The obtained results confirmed the efficacy of TIPS combined with gastric vein embolization. The unique patent solution determined the technique, indications and peculiarities of the intervention.
Determination of the optimal reconstruction for pancreaticoduodenal resection based on modified scintigraphy of gastrointestinal motility
Authors: Shabunin A. V. , Bedin V. V. , Tavobilov M. M. , Karpov A. A. , Karalkin A. V. , Vasilenko E. I. , Abramov K. A. , Lantsynova A. V.
Published: September 2023

Aim. To improve the outcomes of pancreaticoduodenal resection by determining the optimal reconstruction based on objective assessment of the functional state of the upper gastrointestinal tract using a modified “double” scintigraphic study.

Materials and methods. 147 pancreaticoduodenal resections were performed in the period of 2016–2022. Patients underwent “double” scintigraphic study on days 30 and 90 after surgery. The mean age of the patients was 59.6 years (23–83); the male to female ratio was 1.27:1. All patients underwent gastropancreatoduodenal resection or pancreatoduodenal resection with pylorus preservation. The patients were divided into 3 groups according to the variant of the reconstructive stage of surgery. Group 1 underwent reconstruction according to Child, group 2 – Child reconstruction and interintestinal anastomosis formation according to Brown, the reconstructive stage in group 3 involved Roux-en-Y isolation of the small intestine (Roux-en-Y reconstruction).

Results. “Double” scintigraphic study revealed that the best result on the 30th and 90th postoperative days was observed in patients who underwent pancreaticoduodenal resection with pylorus preservation, reconstructive stage according to Child and formation of interintestinal anastomosis after Brown.

Conclusion. “Double” scintigraphy is an effective procedure to determine the motility of the stomach, biliodigestive anastomosis and motility of the small intestine. As a result, the optimal reconstruction after pancreaticoduodenal resection was determined in patients with neoplasms of the pancreatic head or the periampullary region and chronic pancreatitis.
Non-invasive assessment of destructive changes in the gallbladder and severity of acute cholecystitis
Authors: Timerbulatov M. V. , Yamalov R. A. , Timerbulatov Sh. V. , Kakaullina L. N. , Garipov R. M. , Gafarova A. R. , Timerbulatov V. M. , Garaev R. R.
Published: September 2023

Aim. To study the potential of ultrasound examination for assessment of pathomorphological changes in the gallbladder wall according to A1 and A2 criteria and severity of acute cholecystitis (G1-G3 score).

Materials and methods. The authors analyzed the results of examination and treatment of 556 patients with acute cholecystitis for the last 2 years. The study involved clinical, laboratory and ultrasound results, their coincidence with the results of histological examination of the removed gallbladder.

Results. Clinical and laboratory data coincided with histopathological data in G1 in 84.9% of cases, G2 – in 74.5%, G3 – in 63.2%; ultrasound findings coincided with histopathological data in A1 in 81.54% of cases, in A2 – in 86.59%. The incidence of postoperative complications in G1 comprised 4.6%, in G2 – 8.4%, in G3 – 32.1%, in A1 – 6.8%, and in A2 – 27.7%. Fatal outcomes appeared only in G3 (3.77%) and A2 (2.12%) patients, the overall postoperative mortality was 0.42% and the incidence of postoperative complications was 10.94%.

Conclusion. Ultrasound examination in 86.6% of patients with acute cholecystitis enables pathomorphological changes in the gallbladder wall to be evaluated, which significantly facilitates decision making about the timing and extent of surgical intervention.
Activation processes during operation of an Ag/SnSe/Ge2Se3/W ion memristor with a self-forming current-conducting channel
Authors: Aleshin A. N. , Ruban O. A.
Published: September 2023

In an Ag/SnSe/Ge2Se3/W ionic type memristor, the activation energy of two main processes responsible for its operation has been determined, namely: the activation energy for the formation of a conductive channel and the activation energy for memristor degradation. By measuring the current-voltage characteristics, the electrical conductivity of the memristor in low- and high-resistance operating modes was assessed. To determine the activation energy, the Arrhenius law and the provisions of the thermodynamics of irreversible processes were used, in particular the second postulate of Onsager, according to which the growth rate of the irreversible part of the entropy of a system tending to equilibrium is proportional to the sum of the products of the flows occurring in the system and the generalized thermodynamic force corresponding to each flow. The equilibrium state of the memristor was taken to be the state in which the memristor lost the ability to function as a resistive memory cell. The flow of Ag+ ions – electromigration was used as a substance flow. For the first process, the activation energy was 0.24 eV, and for the second, 1.16 eV. The different values of activation energy reflect the difference between the agglomeration mechanism of formation of a current-conducting channel, typical of an Ag/SnSe/Ge2Se3/W memristor, and the “standard” mechanism of substance transfer based on a group of point defects, which accompanies the process of memristor degradation.
Телеономные и когнитивные факторы направленности эволюции
Authors: Sukhoverkhov Anton , Kobyakova Irina , Pozdeyev Ilya
Published: September 2023

С учетом современных открытий в естественных науках в статье пересматриваются модели эволюционного процесса, основанные на идее направленного (телеономического) развития биологических и биосоциальных систем. Систематизируются существующие телеономические (ортогенетические, номогенетические) подходы к эволюции, особенно российских ученых. Критически оценивается теория и методология неодарвинизма (синтетической теории эволюции), предлагающего в качестве главной действующей причины эволюционного развития изменения среды и объясняющего образование новых признаков (изменчивость, адаптация) случайной мутацией генов. Обосновывается, что биологические системы являются частично интеллектуальными, обладают широко исследованным «минимальным познанием» (minimal cognition), способны к сбору информации и направленному преобразованию себя и окружающей среды. Для описания когнитивных процессов у организмов, не обладающих нервной системой, используется парадигма телесно реализуемого, или воплощенного, познания (embodied cognition). Для объяснения природы развивающихся систем и системных переходов в эволюции в работе также используются понятия «распределенная деятельность» и «распределенное познание» (distributed cognition). В статье показано наличие в природе не только индивидуальной, но и системной, надындивидуальной целесообразности (например, у бактерий и общественных насекомых). В связи с этим традиционная модель эволюции снизу вверх (bottom-up evolution) — от элементов к системе — дополнена моделью эволюции/детерминации сверху вниз (top-down evolution) — от системы к элементам системы. Отмечается, что важную роль во взаимодействиях между системой и элементами играют социально-познавательные и информационные процессы, которые мало учитывались в предыдущих макроэволюционных исследованиях. В системных взаимодействиях показана также определяющая роль генетических и негенетических (эпигенетических) систем наследования. Они позволяют накапливать видоспецифичный опыт, обуславливают формирование инстинктивного поведения, обеспечивают общее воспроизведение структуры биологических и социальных систем.
The effect of thermo-mechanical densification process on the physical properties of wood material
Authors: ATILGAN Abdi
Published: September 2023

It can be made into high strength, and valuable products by compacting low density, and low commercial value wood species. In this study, black pine (Pinus nigra) and Uludağ fir (Abies nordmanniana subsp. bornmulleriana) tree species were densified by using Thermo-mechanical (TM) method, which is an environmental modification method, at 140 oC and two different ratios of 25% and 50% (in the radial direction). Compression ratio in air-dry moisture, spring-back ratio after densification, and physical properties of air-dry densities were determined. The obtained data were subjected to statistical analysis in the MSTAT-C program. According to the results, wood type, densification type, and all their interactions were found to be effective on the compression ratio, and spring-back ratio in air dry moisture. The compression ratio in air-dried moisture was lower in Uludağ fir (Uludağ fir: 0.40 gr/cm³, black pine: 0.49 gr/cm³) compared to black pine due to the spring-back effect. While the volumetric recovery (spring-back) rates were 15.44% in Uludağ fir, it was determined as 19.40% in black pine. After the condensation process, the air-dry density value increase was lower in black pine compared to Uludağ fir, and it was determined as 35.94% in Uludağ fir and 34.53% in Black Pine
CUTAC for FFPEs v2
Authors: Henikoff Steven
Published: September 2023

For more than a century, Formalin Fixed Paraffin Embedded (FFPE) sample preparation has been the preferred method for long-term preservation of biological material. However, the use of FFPE samples for epigenomic studies has been difficult because of chromatin damage from long exposure to high concentrations of formaldehyde. Previously, we introduced Cleavage Under Targeted Accessible Chromatin (CUTAC), an antibody-targeted chromatin accessibility mapping protocol based on CUT&Tag. Here we show that simple modifications of our single-tube CUTAC protocol are sufficient to produce high-resolution maps of paused RNA Polymerase II (RNAPII) at enhancers and promoters using FFPE samples. We find that transcriptional regulatory element differences produced by FFPE-CUTAC distinguish between mouse brain tumors and identifyand mapregulatory element markers with high confidence and precision, including microRNAs not detectable by RNA-seq.Our simple workflowsmakepossible affordable epigenomic profiling of archived biological samples for biomarker identification, clinical applications and retrospective studies.
What is the existing evidence base for adult medical Same Day Emergency Care in UK NHS hospitals? A scoping review protocol v1
Authors: Dean Sue
Published: September 2023

Objectives Same Day Emergency Care (SDEC) is a new model of care, which has emerged over thepast 5 years, building upon prior ambulatory care services. The NHS EnglandNational Strategy for SDEC suggests SDEC can meet local health needs byproviding alternatives to emergency department attendance or hospitaladmission, for people with an urgent health care need, beyond the limited scopeof an urgent treatment centre. This review focuses on acute medical SDEC, asmedical patients represent a significant proportion of emergency admissions.The planned scoping review aims to map the existing evidence base. Methods and Analysis This is a protocol for a scoping review to be conducted in accordance with the format of the JBI methodology for scoping reviews. The databases to be searched will include EMBASE, MEDLINE and CINAHL, via EBSCOhost. Sources of unpublished studies, policies and grey literature will include Google Scholar, the Cochrane Library, TRIP database, ProQuest Dissertations and Theses Open, and the Health Management InformationConsortium. Papers relating to acute medicine adult patients attending NHS SDECservices in the UK will be included. International papers will be excluded, aswill those over five years old, and those where full text is not available. The resultsof the search and study inclusion / exclusion process will be reported andpresented in a PRISMA-SCR flow diagram. Data will be extracted from papers included in the scoping review by two reviewers, using a JBI data extraction tool. Any differences of opinion will be discussed until consensus is reached. If needed, a third reviewer will be askedto join the review team to achieve consensus. Data and themes extracted will be summarised and presented in tables. A narrative thematic summary will accompany the presented results, describing how the results relate to the review objective. Literature gaps will be identified and recommendations for future research made.
Wake Forest University Health Sciences Manual of Procedures Biospecimen Collection and Processing v1
Authors: not provided kkennedy
Published: September 2023

This includes the methods associated with obtaining muscle, blood, and urine along with demographic, clinical, health, and functional data from younger and older participants.
10x Protocols: Chromium Single Cell/Nuclei Gene Expression Flex Multiplex -- University of Minnesota TMCs (CG000527 Rev D) v1
Authors: Genomics IOx
Published: September 2023

10x Genomics Chromium Single Cell Expression flex protocol for library construction. Protocol ID# (CG) and Revision letter provided here: 10x protocol CG000527, Revision D -- Library construction of 10x fixed single cell or nuclei Note: These protocols may not be the current version offered by the company but were used to produce the specific datasets connected to them. Please review the company support websites for the most recent versions of the protocols prior to starting your experiment.
Discursive Configurations About the Francophone World and the French Language in Colombian Written Press
Authors: Lamprea-Abril Nathalia
Published: September 2023

The notion of francophonie still raises many questions in various fields, such as the didactic, economic, political, and media fields, among others, making it difficult to understand the concept. In this article, we analyze the ways in which the discursive contours of the francophone issue and its representation in the discourse of the Colombian print media are defined, based on a corpus of 35 journalistic articles. To this end, we combined textometric analyses obtained with the Iramuteq® software with linguistic discourse analysis tools, in order to propose an interpretative hypothesis. On this basis, we were able to demonstrate that, in the Colombian print media, the issue of francophonie is mainly elaborated on the basis of its relationship to the French language and, more concretely, on the basis of its pragmatic aim, which configures a discursive register of education and work. In addition, there is a quest linked to the desire for social mobility, where language takes on the role of auxiliary, even in the absence of cultural, social, political or historical dimensions. From this point of view, its learning and its use are reduced to a rather technical and individual subject without considering its complex character also constituting the social.
Text Mining
Authors: Zamarra Londoño Julián Esteban , Pérez Noreña Daniela , Barrera Montoya Carlos Andrés
Published: September 2023

El presente artículo evalúa el contenido del informe de auditoría —para caso de Colombia, informe del revisor fiscal— en las empresas cotizadas en la bolsa de valores de Colombia en el periodo 2010-2021, por medio de la metodología Text Mining, que posibilitó el análisis del texto incluido en 647 informes de revisor fiscal, identificando los términos más recurrentes y su importancia dentro del informe, a través del estadístico de frecuencia de términos y nubes de palabras. Con lo anterior, se encontró que los informes del revisor fiscal siguen un formato estándar que, sin embargo, incluyen temas relativos al proceso de auditoría e información adicional a través de los párrafos de énfasis y otros asuntos, mostrando que las palabras o términos que más se usan dentro de los informes son “financiero”, “auditoría” y “opinión”, pero en los párrafos de revelaciones adicionales como párrafos de énfasis y cuestiones clave se incorporan otros temas como procedimientos, deterioro, cartera, evolución y activos para hacer referencia a la información adicional de evaluación de los auditores diferente a solo emitir una opinión de auditoría.
Methods of Multi-Criteria Judgment and Selection of Objects Based on Relations with the k-th Order of Strict Preference
Authors:   Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russian Federation, Korneenko V. P.
Published: September 2023

Methods of multi-criteria judgment and selection of objects based on the resulting relation with the к -th order of their strict preference are proposed. It is shown that the resulting Pareto and Slater dominance relations are a special case of the resulting relationship with the k-th order of strict preference. A detailed analysis of the method of narrowing the set of nondominable objects, which is based on the coefficient of relative importance (coefficient of compromise) for a pair of criteria, is carried out. Based on the example when one criterion is more important than another in advance, it is shown that there is no need to recalculate the vector estimates of objects, since the initial set of estimates narrows if one simply excludes a less important criterion from consideration. The presented methods of multi-criteria judgment and selection of objects do not require additional expert information on the importance of criteria, are mathematically justified and illustrated by an example.
Factors and Criteria for Choosing an IT Project Implementation Methodology (Based on Expert Survey Materials)
Authors:   Pacific State University, Khabarovsk, Russian Federation, Vatolina O. V. , Kolodin D. V. ,   Far Eastern Federal University, Vladivostok, Russian Federation
Published: September 2023

The scientific article discusses with the problem of the dependence of the choice of methodology for the implementation of IT projects on the factors influencing the effectiveness of such activities. An IT project and its performance is considered in terms of the capacity of an IT project, the type of IT project. The basis of the empirical study was an expert survey based on the Delphi methodology. In the survey, the authors invite experts to consider what factors and criteria, in addition to the classical ones, can affect the image of the result in the implementation of IT projects.
Evaluation оf the Automated System of Scientific Research on the Survivability of Gas Production Facilities Effectiveness
Authors:   Gazprom Dobycha Orenburg, Orenburg, 460018, Russian Federation, Valeev A. F.
Published: September 2023

In this article, the existing approaches to evaluating the effectiveness of automated research systems are considered. The choice of the evaluation method is justified and a criterion for evaluating the effectiveness of scientific studies of the survivability of gas production facilities is developed, taking into account generalized indicators: research time, resource efficiency, effectiveness. Based on expert assessments, the values of the coefficients of the significance of performance indicators are determined. The efficiency of scientific research on the survivability of gas production using existing automation systems and the proposed one has been evaluated. The analysis of the evaluation results showed an increase in the effectiveness of scientific research of survivability according to the integral criterion with the use of a new automated system by more than 2 times, which indicates the effectiveness of the developed software, methodological and informational support of such a system.
Mathematical Modeling Method for Detecting the Fuzzy Occurrence of Dangerous Events
Authors:   Institute of Mathematics and Information Technology, Petrozavodsk State University, Petrozavodsk, 185910, Russian Federation, Rego G. E.
Published: September 2023

The article describes a mathematical modeling method for detecting the fuzzy occurrence of dangerous events. A distinctive feature of this study is the assessment of the occurrence of dangerous events based on the use of fuzzy sets. Each dangerous event is associated with a subset of the set of sensors. The data is converted into some characteristics of the occurrence of an event, which are then fed to the input of the membership function of a set of dangerous events. In addition, an example of the application of this mathematical model is given, demonstrating its advantages and possibilities for its expansion. The appendix contains a table of possible dangerous events associ­ated with the functioning of the forest robot. The presented model can also be used to detect the fuzzy occurrence of dangerous events associated with human movement. The developed mathematical modeling method for detecting the occurrence of dangerous events has many applications. In particular, it contributes to the creation of a digital assistant to expand the capabilities of the senses of a remote human operator, and can also be used to control a mobile robot.
Expert System for Diagnosing Post-Traumatic Stress Disorder
Authors:   Volgograd State Medical University, Volgograd, 400131, Russian Federation, Stebenkov A. M. , Sunagatullina A. I. ,   Volgograd State Medical University, Volgograd, 400131, Russian Federation
Published: September 2023

By analyzing the results of research in the field of diagnosing post-traumatic stress disorder, the necessary crite­ria were identified, as well as test methods and scales used in this direction. This article discusses the problematic issues of diagnostics that currently exist in Russia. The algorithm of the expert system for diagnosing post-traumatic disorder developed by the authors is presented in the form of a console application. Such an algorithm can partially replace specialists in this field and help improve and speed up the primary diagnosis of the disorder. The operation of the algorithm and confirmation of its efficiency are presented.
SAVING UKRAINIAN CULTURAL HERITAGE DURING THE WAR: PRACTICES OF INTERNATIONAL INTERACTIONS
Authors:   Taras Shevchenko National University of Kyiv, Kyiv, Ukraine, Rohozha Mariya
Published: September 2023

The article deals with the experience of preserving cultural heritage in the armed conflict in Ukraine and international cooperation in this field. The historical reconstruction of the legal protection of cultural heritage is carried out. It is indicated in the article that during the 19th century, international legal bases for the preservation of cultural heritage were actively developed. However, in the 20th century, two world wars brought significant destruction of cultural heritage by all parties of the conflict. And the optimism of the Europeans of the 19th century regarding a civilized attitude to cultural heritage was destroyed, although the work on the creation of international normative documents in the field continued and international organizations were founded that took care of cultural heritage. In the 21st century, the previous trends persist. Such reconstruction can become the context for the Ukrainian situation. To clarify it, the method of situational analysis is used. The situations with the Hryhorii Skovoroda museum in the village of Skovorodinivka in the Kharkiv region and the Ivankiv Local History Museum unfold in time and space and focus the theoretical framework. In the article, the author addresses the problem of the biography of a place, which is relevant in modern social sciences and humanities. Despite objections to anthropomorphization, scholars emphasize the close link of places and human destinies there. Skovorodinivka ceases to be exclusively a place of memory of an outstanding Ukrainian philosopher and becomes evidence of the attitude towards the object of cultural heritage in the current war. The article shows that in Ukraine today, the war is blurring the "battlefield" and military actions are spreading to the territory where the civilian population and cultural heritage sites are located. The striking difference in the attitude towards the cultural heritage of mankind during the military conflicts of the optimistic modern XIX and the postmodernist relativistic XX centuries illustrates the loss of position by modern phenomena. The situation with the Hryhorii Skovoroda museum testifies that today international aid comes for the preservation of the destroyed cultural artifacts. International cooperation is also essential in the issue of digitizing the cultural heritage of Ukraine and creating conditions for its preservation. The article indicates the initiatives of SUCHO (Saving Ukrainian Cultural Heritage Online) and the Vasa Museum, Stockholm, on this path
A Condition Monitoring System for Electric Vehicle Batteries Based on a Convolutional Neural Network Using Thermal Image
Authors: Senthilraj S. , Shanker N. R.
Published: September 2023

A new monitoring technique has been developed to evaluate the capacity and performance of Lithium-ion batteries batteries by utilizing two convolutional neural networks (CNNs) models, Deep convolutional neural network (DnCNN) and CNN with BFGS quasi-Newton optimization. The system utilizes thermal images of lithium-ion batteries as input for training and testing. DnCNN model is utilised to accurately calculate battery capacity and performance, and the performance is evaluated using mean squared error (MSE) and PSNR. The CNN-based training method employs the BFGS quasi-Newton algorithm to measure battery capacity accurately by evaluating the mean squared error (MSE) and regression results. The proposed condition monitoring system using thermal imaging and CNN models, specifically the CNN- BFGS quasi-Newton algorithm model, can accurately detect battery capacity with an accuracy rate of 98.5%, compared to the DnCNN model with an accuracy rate of 96.7%. The proposed system can address the critical issue of battery capacity and degradation in EVs, providing a more sustainable and efficient alternative for real-time applications.
Gaussian Coordinate Feature Set Optimisation (GCFSO) Model for Analysing the Impact of Urbanisation on Cultural Identities and City Images
Authors: Wang Fangxuan
Published: September 2023

Urbanization, characterized by the rapid growth of cities and the associated changes in social, economic, and physical landscapes, has been a significant global phenomenon in recent decades. As cities expand and transform, they play a crucial role in shaping cultural identity and projecting a distinct city image. The constructed framework process comprises the multi-modal image processing with the Gaussian Coordinate estimation with the Optimization model. The proposed model comprises the estimation of the feature sets associated with the feature set for the classification of cultural identity. The model comprises the Gaussian Coordinate Feature Set Optimization (GcFSO). The GcFSO model estimates the feature sets in the data related to the cultural identity for the shaping of images to analyze the urbanization process. The GcFSO model computes the feature set based on the Mandami Fuzzy set model for the classification of cultural identity in China. The fuzzy set rules are computed for the estimation of the features in the process of Urbanization. The performance of the GcFSO model is examined with the deep learning model for classification. The simulation analysis stated that GcFSO model achieves a higher classification accuracy of 0.99 with a minimal error rate.
Empowering Visually Impaired through the Assistance of SAHAYAK – A Walking Aid for the Blind
Authors: Sunitha M. , Kumar G. Sravan , Manasa K. , Rajani B. , Jaheda Shaik
Published: September 2023

To help blind people overcoming difficulty in their movement in the physical environment and even in their home, a study on an engineering concept is very much necessary. So, our research comes out with an aid that will help blind people in their surroundings. It can detect any obstacle that will block the path of the blind. And The motion of the user can be sensed by the bot. Thus, Blind people can comfortably receive the help of our bot in assisting their movement from one place to another. This paper describes about an automated vehicle which can be controlled by an ultrasonic sensor to avoid obstacles when they move in their environment. Our automated robotic system is made up of an ultrasonic sensor and Arduino micro controller controls our automated bot. It is located in the front part of the bot. The ultrasonic sensor retrieves the data from the environment through the sensors attached to the bot. When any obstacle is detected then immediately that path is changed and an obstacle free path is chosen. The bot wheel is moved based on the data received by the controller from the sensor. The direction and wheel movement of the bot and will be decided from the ultrasonic sensor sensing and also using wheel encoder. It is used for detection and avoidance of interference. The controller is also programmed to be used with an android application.
Comparative Review of Object Detection Algorithms in Small Single-Board Computers
Authors: Tuan Rashid Tuan Muhammad Naeem Bin , Fadzil Lokman Mohd
Published: September 2023

Object detection is a crucial task in computer vision with a wide range of applications. However, deploying object detection algorithms on small single-board computers (SBCs) poses unique challenges. In this review article, we present an in-depth comparative analysis of object detection algorithms tailored for small SBCs. We have conducted an extensive literature review on existing research in object detection algorithms and evaluated the performance of different approaches on benchmark datasets. Our review encompasses cutting-edge deep learning methods, which are YOLO, SSD, and Faster R-CNN. We delve into the challenges and limitations of implementing these algorithms on small SBCs and offer recommendations for optimizing their performance in such environments. Our analysis aims to shed light on the strengths and weaknesses of various object detection algorithms for small SBCs, ultimately guiding practitioners in making informed decisions and identifying potential avenues for future research in this domain.
Integrated Approach for Emotion Detection via Speech and Text Analysis
Authors: Birari Dipika , Walunjkar Gajanan , Dandavate Aarti , Antad Sonali Mallinath , Phatangare Sheetal
Published: September 2023

This paper aims to provide a comprehensive solution for effective reviews using deep learning models. Customers often have difficulty to find accurate reviews of the things they are interested in. The proposed framework implements a review mechanism to address this problem, which will give customers relevant reviews based on video reviews supplied in the product description. The goal of this system is to turn video reviews into a particular rating so that viewers may get a summary of the review without having to watch the full thing by simply glancing at the rating. Deep learning neural networks are used by the model for both text and audio processing in order to achieve this. The well-known RAVDESS dataset serves as the basis for the audio model's training and offers a wide range of emotional expressions. The suggested system uses two methods to provide reviews: text-based natural language processing and audio frequency spectrograms. By utilizing these two techniques, it may provide consumers accurate and trustworthy ratings while guaranteeing that the review procedure is not impeded. The aim is achieved with high accuracy to ensure that users can make informed decisions when purchasing products based on the provided reviews. With the aid of this review system, customers will be able to quickly find out crucial details about a product they are interested in, thus increasing their pleasure and loyalty.
Hybrid Simulated Annealing: An Efficient Optimization Technique
Authors: Ankita Ankita , Kumar Rakesh
Published: September 2023

Genetic Algorithm falls under the category of evolutionary algorithm that follows the principles of natural selection and genetics, where the best adapted individuals in a population are more likely to survive and reproduce, passing on their advantageous traits to their offsprings. Crossover is a crucial operator in genetic algorithms as it allows the genetic material of two or more individuals in the population to combine and create new individuals. Optimizing it can potentially lead to better solutions and faster convergence of the genetic algorithm. The proposed crossover operator gradually changes the alpha value as the search proceeds, similar to the temperature in simulated annealing. The performance of the proposed crossover operator is compared with the simple arithmetic crossover operator. The experiments are conducted using Python and results show that the proposed crossover operator outperforms the simple arithmetic crossover operator. This paper also emphasizes the importance of optimizing genetic operators, particularly crossover operators, to improve the overall performance of genetic algorithms.
Optimized Matrix Feature Analysis – Convolutional Neural Network (OMFA-CNN) Model for Potato Leaf Diseases Detection System
Authors: Rohilla Neeraj , Rai Munishwar
Published: September 2023

One of the most often grown crops is the potato. As a main food, potatoes are prioritised for cultivation worldwide. Because potatoes are such a rich source of vitamins and minerals, we can create a robust system for food security. However, a number of illnesses delay the growth of agriculture and harm potato output. Consequently, early disease identification can offer a better answer for effective crop production. In this research work aim is to classify and detect the potato leave (PL) diseases using OMFA-CNN deep learning model. An optimized matrix feature analysis-CNN deep learning model for PL disease detection is implemented. In the first phase, the PLs features are extracted from the potato leave images using K-means clustering image segmentation method. At the last phase, a new OMFA-CNN model are proposed using CNN to classify virus, and bacterial diseases of PLs, The PL disease dataset consists 2351 images gathered in real-time and from the Kaggle (PlantVillage) dataset. The implemented OMFA-CNN model attained 99.3 % precision and 99 % recall on potato disease detection. The implemented method is also compared with MASK RCNN,SVM and other models and attained significantly high precision and recall.
Detect and Evaluate Visual Pollution on Street Imagery Taken of a Moving Vehicle
Authors: Bharadwaj Rakhi , Kulkarni Radhika , Thombre Aditya , Gaikwad Yash , Suri Sushil , Patekar Umesh
Published: September 2023

Visual pollution is a growing problem in urban areas. It is important for environmental management to identify, formalize, measure and evaluate visual pollution. This paper presents a study on the development of an automated system for visual pollution classification using street images taken from a moving vehicle. The proposed system uses convolutional neural networks to classify different types of visual pollutants such as graffiti, faded signage, potholes, litter, construction zones, broken signage, poor street lighting, poor billboards, road sand, sidewalk clutter, and unmaintained facades.In this study, we utilized a large dataset of raw sensor camera inputs gathered from a fleet of multiple vehicles in a specific geographical area. Our aim was to develop convolutional neural networks that simulate human learning to classify visual pollutants from these images. The successful implementation of this system would be a significant contribution to the development of urban planning and the strengthening of communities worldwide. Additionally, it could lead to the creation of a "visual pollution score/index" for urban areas, which could serve as a new metric for urban environmental management. Our findings, which we present in this paper, will be a valuable addition to the academic community and the field of computer vision for environmental management applications.
A Novel Cryptography-Based Multipath Routing Protocol for Wireless Communications
Authors: Venkatramulu S. , Rao V. Chandra Shekar , Vinay Kumar K. , Srinivas C. , Raghuram B. , Rasool Shaik
Published: September 2023

Communication in a heterogeneous, dynamic, low-power, and lossy network is dependable and seamless thanks to Mobile Ad-hoc Networks (MANETs). Low power and Lossy Networks (LLN) Routing Protocol (RPL) has been designed to make MANET routing more efficient. For different types of traffic, RPL routing can experience problems with packet transmission rates and latency. RPL is an optimal routing protocol for low power lossy networks (LLN) having the capacity to establish a path between resource constraints nodes by using standard objective functions: OF0 and MRHOF. The standard objective functions lead to a decrease in the network lifetime due to increasing the computations for establishing routing between nodes in the heterogeneous network (LLN) due to poor decision problems. Currently, conventional Mobile Ad-hoc Network (MANET) is subjected to different security issues. Weathering those storms would help if you struck a good speed-memory-storage equilibrium. This article presents a security algorithm for MANET networks that employ the Rapid Packet Loss (RPL) routing protocol. The constructed network uses optimization-based deep learning reinforcement learning for MANET route creation. An improved network security algorithm is applied after a route has been set up using (ClonQlearn). The suggested method relies on a lightweight encryption scheme that can be used for both encryption and decryption. The suggested security method uses Elliptic-curve cryptography (ClonQlearn+ECC) for a random key generation based on reinforcement learning (ClonQlearn). The simulation study showed that the proposed ClonQlearn+ECC method improved network performance over the status quo. Secure data transmission is demonstrated by the proposed ClonQlearn + ECC, which also improves network speed. The proposed ClonQlearn + ECC increased network efficiency by 8-10% in terms of packet delivery ratio, 7-13% in terms of throughput, 5-10% in terms of end-to-end delay, and 3-7% in terms of power usage variation.
Reinforcement Learning and Advanced Reinforcement Learning to Improve Autonomous Vehicle Planning
Authors: Agrawal Avinash. J. , Welekar Rashmi R. , Parati Namita , Satav Pravin R. , Thakur Uma Patel , Potnurwar Archana V.
Published: September 2023

Planning for autonomous vehicles is a challenging process that involves navigating through dynamic and unpredictable surroundings while making judgments in real-time. Traditional planning methods sometimes rely on predetermined rules or customized heuristics, which could not generalize well to various driving conditions. In this article, we provide a unique framework to enhance autonomous vehicle planning by fusing conventional RL methods with cutting-edge reinforcement learning techniques. To handle many elements of planning issues, our system integrates cutting-edge algorithms including deep reinforcement learning, hierarchical reinforcement learning, and meta-learning. Our framework helps autonomous vehicles make decisions that are more reliable and effective by utilizing the advantages of these cutting-edge strategies.With the use of the RLTT technique, an autonomous vehicle can learn about the intentions and preferences of human drivers by inferring the underlying reward function from expert behaviour that has been seen. The autonomous car can make safer and more human-like decisions by learning from expert demonstrations about the fundamental goals and limitations of driving. Large-scale simulations and practical experiments can be carried out to gauge the effectiveness of the suggested approach. On the basis of parameters like safety, effectiveness, and human likeness, the autonomous vehicle planning system's performance can be assessed. The outcomes of these assessments can help to inform future developments and offer insightful information about the strengths and weaknesses of the strategy.
Scene Detection Classification and Tracking for Self-Driven Vehicle
Authors: Pande Sanjay P. , Khandelwal Sarika
Published: September 2023

A number of traffic-related issues, including crashes, jams, and pollution, could be resolved by self-driving vehicles (SDVs). Several challenges still need to be overcome, particularly in the areas of precise environmental perception, observed detection, and its classification, to allow the safe navigation of autonomous vehicles (AVs) in crowded urban situations. This article offers a comprehensive examination of the application of deep learning techniques in self-driving cars for scene perception and observed detection. The theoretical foundations of self-driving cars are examined in depth in this research using a deep learning methodology. It explores the current applications of deep learning in this area and provides critical evaluations of their efficacy. This essay begins with an introduction to the ideas of computer vision, deep learning, and self-driving automobiles. It also gives a brief review of artificial general intelligence, highlighting its applicability to the subject at hand. The paper then concentrates on categorising current, robust deep learning libraries and considers their critical contribution to the development of deep learning techniques. The dataset used as label for scene detection for self-driven vehicle. The discussion of several strategies that explicitly handle picture perception issues faced in real-time driving scenarios takes up a sizeable amount of the work. These methods include methods for item detection, recognition, and scene comprehension. In this study, self-driving automobile implementations and tests are critically assessed.
A Comprehensive Survey of Deep Learning: Advancements, Applications, and Challenges
Authors: Yamini B. , Prasanna V. , Ambhika C. , M Anuradha. , Maheswari B. , R Siva Subramanian. , Nalini M.
Published: September 2023

Artificial intelligence's "deep learning" discipline has taken off, revolutionizing a variety of industries, from computer vision and natural language processing to healthcare and finance. Deep learning has shown extraordinary effectiveness in resolving complicated issues, and it has a wide range of potential applications, from autonomous vehicles to healthcare. The purpose of the survey to study deep learning's present condition, including recent advancements, difficulties, and constraints since the subject is currently fast growing. The basic ideas of deep learning, such as neural networks, activation functions, and optimization algorithms, are first introduced. We next explore numerous topologies, emphasizing their distinct properties and uses, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). Further concepts, applications, and difficulties of deep learning are all covered in this survey paper's thorough review. This survey aid the academics, professionals, and individuals who want to learn more about deep learning and explore its applications to challenging situations in the real world.