bluuebunny/crossref_metadata_2025 huggingface dataset:
Problems of Improving the Norm on Responsibility for Kidnapping
Authors: Arkhipkin Igor , Kornakova Svetlana
Published: September 2023

The authors stress the high importance of preventing crimes connected with kidnapping and counteracting the impunity of encroachments on freedom, honor and dignity of a person. They analyze the contents of Art. 126 of the Criminal Code of the Russian Federation and criticize the absence of a definition clause that should contain all the necessary crime-related features of the action prohibited by this legal norm. Such a situation is greatly responsible for the contradictory court practice of applying this norm, which is also presented by the authors. They give a favorable assessment of the concept of kidnapping as formulated by the Plenary Session of the Supreme Court of the Russian Federation in Decree № 58. Russian legislation is compared with the active legislation of the CIS countries in terms of defining this criminal action. Special attention is paid to the Note to Art. 126 of the Criminal Code of the Russian Federation, whose presence and content is negatively assessed by many representatives of the professional community. It is stated that such a Note is included in the similar norms of only four CIS countries. The positive experience of Kirgizia is stressed, as the norms of its corresponding legislation have an unconditional preventive significance. Based on the results of their research, the authors conclude that it is necessary to improve Art. 126 of the Criminal Code of the Russian Federation by adding a definition of this type of crime formulated on the basis of Russian practice and by specifying the cases when the Note is applicable. According to the authors, there are two ways of amending the Note: it could be applied at the discretion of the court if the concept «is exempt» is substituted by «can be exempt»; the text could be supplemented with a number of conditions under which the exemption from criminal liability is justified. This should depend, firstly, on the modus operandi of the action (i.e. the Note should only refer to Part 1 of Art. 126 of the CC of the RF); secondly, on how long the kidnapped person was held captive, the period should not exceed three days; and thirdly, the conditions in which the kidnapped person was held, where the assessment should totally depend on the victim.
Problems of Initiating Criminal Cases on Market Manipulation and Misuse of Insider Information
Authors: Arestova Ekaterina , Borbat Andrey
Published: September 2023

The authors analyze the grounds for initiating criminal cases on market manipulation and misuse of insider information, as well as the specific features of preliminary verification of reports on the abovementioned crimes by the bodies of preliminary investigation. The Bank of Russia, which uncovers the cases of legislative violations in the sphere of economics, experiences difficulties in stopping the actions of unscrupulous persons due to legal and organizational problems arising after turning to the law enforcement bodies. Although there is a certain legislative basis for cooperation between the Bank of Russia and the bodies of preliminary investigation, the latter believe that the information provided by the chief financial agency of the country does not contain sufficient data indicating the elements of crimes. According to the authors, this issue requires the regulation of not only organizational, but also procedural problems associated with collecting evidence of illegal economic activities. They propose an algorithm of actions to collect information necessary and sufficient for making a decision on the initiation of a criminal case on market manipulation and misuse of insider information that is based on the united efforts of three bodies - the Central Bank of the Russian Federation, the Russian Ministry of Internal Affairs and the Investigative Committee of Russia.
Проблема индивидуации в процессуальной философии биологии
Authors: Emanuilov Filipp
Published: September 2023

Работа посвящена постановке и решению проблемы индивидуации в контексте процессуальной философии биологии. Проблема возникает из напряжения между такими чертами процесса, как континуальность и гетерогенность, и может быть сформулирована следующим образом: как возможно существование разнородного множества процессов, если все они в конечном счете сливаются в динамический континуум? В рамках этой метафизической проблемы выделяется два измерения: синхроническое и диахроническое. Показывается, что в процессуальной философии биологии отсутствует удовлетворительная постановка и решение этой проблемы: в силу господства вещных форм мышления исключается либо континуальность процессов (как в случае концепции Дж. Дюпре), либо их качественная разнородность (как в случае концепции жизни-диффузии). В работе предлагается решение проблемы индивидуации, основанное на концепции длительности А. Бергсона и позволяющее соединить указанные черты процессов. Важной чертой процесса жизни, трактуемого в соответствии с этой концепцией, оказывается сохранение прошлого в настоящем. Далее предложенное решение метафизической проблемы индивидуации соотносится нами с более конкретными концепциями в философии биологии и самой биологии. Так, тезис о сохранении прошлого в настоящем находит подтверждение с точки зрения современной генетики, однако в ограниченной степени. Тезис же об индивидуальности живого как тенденции имеет в качестве следствия представление о множественности степеней и оптик рассмотрения этой индивидуальности различными биологическими дисциплинами.
Питер ван Инваген: проблемы материалистического объяснения учения о всеобщем воскресении мертвых
Authors: Pavlov Aleksey
Published: September 2023

Настоящий текст — это комментарий к русскому переводу статьи Питера ван Инвагена «Возможность воскресения». Чаще всего, по мнению ван Инвагена, воскресение представляют так: Бог собирает атомы, составлявшие человеческие тела, и возвращает их на те места, которые они занимали по отношению друг к другу, когда эти люди еще были живы (квазиаристотелианское объяснение). Тем не менее, по убеждению мыслителя, если это объяснение истинно, то воскрешенный человек не является тем же самым человеком, который умер за некоторое время до Судного дня. В поддержку своего тезиса ван Инваген приводит три аргумента. Во-первых, возможно уничтожение не только тела как составного целого, но и отдельных его элементов (скажем, как в случаях полного разложения и кремации). Во-вторых, даже если составные элементы тела уцелели, за время до второго пришествия Христа они могли бы стать составными элементами других живых существ. В-третьих, не следует также забывать о регулярном обновлении наших тел на клеточном уровне. В качестве предварительного решения ван Инваген предлагает теорию симулякра, в соответствии с которой Бог изымает труп человека и переносит его в другое место, подменяя последний видимым подобием; тем самым обеспечивается сохранность атомов, из которых при наступлении Судного дня будет восстановлена плоть усопшего. Обозначенные ван Инвагеном онтологические и теологические проблемы становятся катализатором дискуссии вокруг консистентности материалистического объяснения христианского учения о всеобщем воскресении мертвых. Собственные подходы к решению проблемы воскресения в разное время предложили Дин Циммерман (модель «падающего лифта»), Лин Бейкер (конституционализм) и Трентон Меррикс (тезис о взаимообусловленности убеждения в материальности личности и веры в воскресение плоти). В 1997 году ван Инваген в написанном им постскриптуме связал проблемы материалистического объяснения воскресения с отсутствием соответствующего терминологического аппарата, который может появиться в нашем распоряжении в недалеком будущем на фоне дальнейшего развития естественных наук и философии.
Роль незнания в эпистемических практиках
Authors: Kostina Alina
Published: September 2023

В статье рассматривается проблема незнания с точки зрения социальной эпистемологии, в частности эпистемологии добродетелей и феминистской философии и методологии науки. Оба направления, возникшие как реакция на кризис позитивистского подхода, выстраивают новые нормативные критерии надежности и объективности знания. Частью этого процесса становится критический анализ содержания понятия и практик незнания. В обеих традициях предлагается рассмотреть природу незнания и механизмы его функционирования как в науке, так и в широком социальном контексте в целом. В рамках эпистемологии добродетелей незнание может служить и залогом непредвзятости эпистемического процесса, выступая в этом смысле добродетелью. Вместе с тем незнание, транслируемое на личностные качества познающего субъекта, выраженные в виде скромности и осторожности, могут превратить качество, воспринимаемое как добродетельное, в интеллектуальный порок. Незнание, выражаемое эпистемическим агентом, может сходным образом проявляться в научной и политической практике. На основании этого рассматривается предложенная Д. Фридманом классификация незнания как рационального, иррационального и неумышленного. В рамках феминистской философии и методологии науки выстраивается отдельный проект эпистемологии незнания. Он, во-первых, критикует доминирующее на протяжении столетий представление об универсальном научном методе, усматривая в его использовании практики эпистемической несправедливости, напрямую связанные с производством и воспроизводством незнания. Последнее становится инструментом, влияющим на формирование научной и политической реальностей, связанных между собой в публичном пространстве, в частности, посредством института экспертизы. В качестве альтернативы выдвигается теория точки зрения, где становится возможным использование более эффективной исследовательской методологии. Пересмотр существующих методологических оснований позволяет по-новому оценить проблему нормативности, надежности знания и доверия эпистемических агентов в познавательном процессе и построении коллективной эпистемологии.
KİMLİK VE MEKAN İLİŞKİSİ BAĞLAMINDA İSLAM HACCINDA KADININ STATÜ DEĞERİ ÜZERİNE SOSYOLOJİK BİR ÇÖZÜMLEME
Authors: ÇAKMAK Fatma
Published: September 2023

Kadın kimliğinin tarih öncesi dönemlerde ve modern zamanlardaki temsiline ilişkin yaklaşımlar farklı paradigmaların eşliğinde değerlendirilmiş ve kutsal mekan olgusunun kadının ontolojik statüsüne dair ortaya koyduğu fikirsel çerçeve üzerinde yeterince durulmamıştır. Bu çalışmada kadın mekan ilişkisi, kutsal mekanlar ekseninde gerçekleşen “insan-mekan etkileşimi” üzerinden temellendirilmiştir. Bu amaçla sembolik anlamlar ve çağrışımlarla birlikte sosyolojik olarak da derin bir anlam alanına sahip olan hac ibadeti İslami kodları ekseninde ele alınmış ve İslam haccının kadının ontolojik varlığı ve toplumsal statüsü konusundaki somut yapısı ve sembolik yönleri farklı boyutlarıyla analiz edilmiştir. Bu kapsamda öncelikle kavramsal çerçevenin kuşatıcılığı analiz edilmiştir. Diğer taraftan hac mekanları ve ritüelleri ile birlikte ideal bir düşünsel zemine oturtulmuş olan kadın kimliğinin tipolojik görünümlerine dair ideal planda öne çıkan yorum biçiminin, zaman içerisindeki anonimleşmesi üzerinde durulmuştur. Çalışma teorik tarama yöntemi ile konu hakkındaki kaynakların birbirini bütünleyecek biçimde ele alınması ile gerçekleştirilmiş; araştırmanın fikirsel bağlamı İslami, filolojik ve sosyolojik kaynakların bir arada kullanıldığı multidisipliner bir literatürden hareketle oluşturulmuştur. Ayrıca bazı kadın düşünür ve yazarların kaleme almış oldukları kişisel hac hatıratlarından yapılan referanslarla konunun teorik arka planı zenginleştirilmiştir. Sonuç olarak lehte ve aleyhte olmak üzere kadının toplumsal kimliği ile ilgili İslami kaynak ve göstergelerin ele alınışında İslam’da kulluğun ikmali olarak tanımlanan kutsal bir yolculuğa denk gelen hac ibadetinin özgün bir düşünce zeminine sahip olduğu dikkati çekmiştir. İslam haccında kurucu bir aktör olarak Hz. Hacer’in görünen kadın kimliği ve bu çerçevede kadının kimlik değerini yücelten sembolik zenginlik derin bir düşünsel repertuar sunması itibariyle alternatif yorum mekanizmaları arasında yerini almakta gecikmiştir.
Use of Aymara in the Chile, Peru, and Bolivia Frontiers: A Micro-Sociolinguistic Analysis
Authors: Mamani Morales Juan Carlos
Published: September 2023

The Aymara language (AL) is one of the most important languages in the central Andean region. However, there are few studies on its use from a microsociolinguistic approach. This paper aims to analyze the use of the Aymara language in six commercial speech events in a tri-border context involving Aymara speakers from Chile, Peru, and Bolivia. The conversations that happened within these events were collected through audio recordings and written records in a qualitative ethnographic intervention in the so-called three-part fair or “Feria Tripartita” (FT), a commercial event that occurs weekly in the three-border area. The analysis is based on ethnography of communication, conversational analysis, and interactional sociolinguistics. Drawing on this analytical framework, the use of the AL that is manifested there shows code-switching with Spanish, both inter- and intra-orally, along with a series of interlinguistic phenomena, such as the presence of a series of Spanish lexical bases with Aymara suffixation, and the use of unnecessary Spanish loans. Thus the FT, in spite of being an Aymara space that conforms a bilingual speaking community, is a space of influence of the Castilian language, which structurally affects the use of the AL.
Causalidad y posicionamientos en el discurso de la historia escolar en español
Authors: Leiva Natalia , Oteíza Teresa
Published: September 2023

En la construcción discursiva de la causalidad confluye el uso de una serie de recursos que van mucho más allá de los denominados “conectores causales” en la tradición lingüística española. Estudios en español han mostrado que la conexión puede realizarse implícita y explícitamente a través de diversas configuraciones. Algunas de estas configuraciones, además de realizar conexión, implican determinados posicionamientos interpersonales. El objetivo de este artículo es caracterizar la interacción entre los significados de conexión y significados interpersonales en la construcción de la causalidad histórica. Para ello, se analizan las secuencias causales en fragmentos provenientes de un texto escolar chileno de Historia para tercer año de enseñanza secundaria, desde una perspectiva semántico-discursiva utilizando la lingüística sistémico-funcional. El análisis de las secuencias permite observar que el sistema de conexión interactúa con los subsistemas interpersonales de compromiso y gradación. En relación con el subsistema de compromiso, las conexiones realizadas verbalmente (p. ej. A permitió B) juegan un rol en el cierre o apertura del espacio dialógico. Respecto del subsistema de gradación, las mismas conexiones permiten agudizar o suavizar la actualización de la conexión causal. Desde una mirada multifuncional del lenguaje, se concluye que la construcción de la causalidad genera ensambles con significados lógicos e interpersonales que son relevantes en la interpretación del pasado.
La escritura y las experiencias formativas en entornos reales en una universidad colombiana
Authors: Narváez-Cardona Elizabeth
Published: September 2023

En América Latina, se han desarrollado iniciativas institucionales e investigaciones centradas en la formación de escritores en asignaturas disciplinares y profesionales. Sin embargo, se requieren estudios que exploren las relaciones entre la escritura y experiencias formativas en entornos reales, como las prácticas preprofesionales, las profesionales y las pasantías. Este artículo presenta los resultados emergentes de un proyecto de investigación cualitativa que indagó sobre los aprendizajes asociados a las experiencias formativas en dichos entornos de estudiantes de pregrado. El análisis se hizo desde la perspectiva de los estudiantes y de otros actores asociados con las prácticas preprofesionales, profesionales y pasantías como los directivos académicos, los coordinadores, los profesores, y los asesores. El estudio fue llevado a cabo en cuatro programas de una universidad privada colombiana y se basó en cuestionarios y entrevistas, realizadas a los diferentes actores. El análisis muestra que el acceso, el uso y la producción de géneros discursivos con finalidades sociohumanísticas, académicas, profesionales o laborales forman parte de los aprendizajes asociados a dichas experiencias. Por eso, los resultados sugieren que los defensores de la alfabetización académica tienen una oportunidad pedagógica para acompañar las prácticas preprofesionales, profesionales y pasantías, con el fin de potenciar la reutilización de conocimientos especialmente relacionados con la escritura.
Depth and proximity of third molars to the inferior alveolar canal in panoramic radiographs of a Latin American population
Authors: Garcés-Elias María Claudia , León-Manco Roberto Antonio , Beltrán-Silva Jorge Arturo
Published: September 2023

Introduction: extraction of lower third molars involve the possible occurrence of complications such as injury of the content of the Inferior Alveolar Canal. Methods: a cross-sectional study was conducted with a sample of 6488 lower molar records of digital panoramic radiographs of patients from 6 Latin American countries from 2010-2015. The variables studied were the depth of lower third molar according to the Pell and Gregory classification, and the proximity of a third molar to the Inferior Alveolar Canal that was evaluated according to the proposed classification, based on a modification of the Langlais et al classification.20 Descriptive and bivariate statistical analyses were performed. Results: in terms of the proximity, the highest frequency was Intact with 27.45%(n=1781). Regarding the depth of the lower third molar, the most frequent were the Position B with 46.90%(n=3043) and Position A with 46.75%(n=3033). The proximity and depth of the lower third molar had statistical difference according to age(p<0.01) and sex (p<0.001). The overall proximity of the lower third molar to the Inferior alveolar canal, according to depth was 37.52%(n=1766) in Position A, in Position B it was 54.51%(n=2566) and Position C was 7.97%(n=375) and had association between variables(p<0.001). Conclusions: taking into consideration the modified classification of Langlais et al.20, lower third molars are close to the Inferior Alveolar Canal, and according to the Pell and Gregory classification for the depth, the most frequent positions are A and B. In addition, proximity and depth were associated with each other, and with the co-variables country, age, and sex.
Next Generation Small Urban Manufacturing: Apprentices’ Perspective on Location Factors, Mixed-Use, and Shared Spaces
Authors: Meyer Kerstin
Published: September 2023

Advancements in technology and architecture enable mixed-use development while normative settings like the European Commission’s New Leipzig Charter support the concept of a productive city. Nonetheless, small urban manufacturers (SUMs) including crafts still face displacement due to property prices, conflicts with housing, planning laws, and building regulations. Urban planning and economic development emphasise the importance of identifying and redeveloping suitable sites for urban manufacturing companies. Largely unanswered, however, is whether the next generation of manufacturers (apprentices) want mixed-use locations within the city or space sharing, and if so, under which conditions. Based on two written surveys, this article examines the location requirements of SUMs in Germany and the willingness of apprentices in the Ruhr area to embrace mixed-use buildings and shared spaces. The study focuses on three craft groups: store crafts, workshop crafts, and construction site crafts. The results show that SUMs in Germany and manufacturing apprentices in the Ruhr prioritise car- and security-related infrastructure, as well as low real-estate costs. Store crafts specifically seek affordable and well-connected ground-floor locations. Construction site crafts prioritise (un)loading facilities for trucks on industrial land over sustainable transport infrastructure, and they differ significantly from the other craft groups in terms of mixed-use preferences. However, all craft groups express openness to mixed-use locations with offices and additional workshops and shared spaces like garages, canteens, and showrooms. The article suggests that commercial courtyards could effectively meet the requirements and desires of apprentices and urban planners alike.
Secure Cluster-based Routing using TCSA and Hybrid Security Algorithm for WSN
Authors: Supriya M. , Adilakshmi T.
Published: September 2023

Wireless Sensor Network (WSN) is operated as a medium to connect the physical and information network of Internet-of-Things (IoT). Energy and trust are two key factors that assist reliable communication over the WSN-IoT. Secure data transmission is considered a challenging task during multipath routing over the WSN-IoT. To address the aforementioned issue, secure routing is developed over the WSN-IoT. In this paper, the Trust-based Crow Search Algorithm (TCSA) is developed to identify the Secure Cluster Heads (SCHs) and secure paths over the network. Further, data security while broadcasting the data packets is enhanced by developing the Hybrid Security Algorithm (HSA). This HSA is a combination of the Advanced Encryption Standard (AES) and Hill Cipher Algorithm (HCA). Therefore, the developed TCSA-HSA avoids malicious nodes during communication which helps to improve data delivery and energy consumption. The performance of the TCSA-HSA method is analyzed using Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), energy consumption, End to End Delay (EED), and throughput. The existing methods namely Optimal Privacy-Multihop Dynamic Clustering Routing Protocol (OP-MDCRP) and Secure and Energy-aware Heuristic-based Routing (SEHR) are used to evaluate the TCSA-HSA performances. The PDR of TCSA-HSA for 100 nodes is 99.7449%, which is high when compared to the OP-MDCRP and SEHR.
Critical issues in Leveraging Blockchain in Healthcare Sector
Authors: More Jyoti , Deshmukh Jyoti , Niture Deeplaxmi V.
Published: September 2023

Blockchain innovation has brought various benefits to the healthcare sector. Utilizing blockchains in clinical contexts will reduce handling time since when a patient signs up for a review, the complete collected data will be accessible at once because of accessibility on the distributed ledger. Also, specialists will not need to stress over the patients giving them a legit clinical history, because of their capacity to progressively see the correct, credible, and quality source-recorded information. It eliminates any likely clinical history mistakes. Similarly, the patients will not need to stress over having a second assessment from another specialist, because of the straightforwardness of the information. Having patient records on a blockchain organization will prompt individuals to know and associate with various others, across the globe, with similar ailments as they have, which is not only valuable for their well-being, but also make the patients feel acknowledged, upheld, and have reinforced determination to battle the ailment. Patients will have total independence regarding their information, and they will choose who to impart the information to. In this paper, we present all the challenges and critical issues associated with implementing blockchains in the healthcare sector.
Metamaterial Inspired Azimuth Pattern-Reconfigurable Antenna for 5G Applications
Authors: Orugu Rangarao , Nesasudha M. , Janapala Doondi Kumar
Published: September 2023

A Radiation reconfigurable antenna is presented for n78 band 5G applications. A planar monopole is combined by a tuning fork and a U shaped strip to form radiating element. A partial ground is maintained at back side. Four metamaterial unit cells are used in this design, two at each side of the radiator to achieve the radiation re-configurability. Comb shaped metamaterial unit cells are placed in a clock wise direction around the antenna and connected to radiator via BAR-64-02V PIN diodes. The proposed reconfigurable antenna operates at 3500MHz for almost all switching conditions. On the basis of the condition of switching diode the antenna radiation pattern is mainly reconfigured into 45o and 135o directions. The antenna’s overall dimensions in X×Y×Z directions are 30mm×26mm×1.57mm. The designed antenna achieved different pattern combinations when diode switching conditions are applied, making it suitable for n78 band 5G applications.
Analytical Study of Two Serial Channels with Priority and Reneging
Authors: Saini Aarti , Gupta Deepak , Tripathi A. K.
Published: September 2023

Most of the studies of queuing theory, which are useful in our daily life has been investigated by many researchers. The present research is the study of pre-emptive priority queuing system consisting two serial channels in stochastic environment. The impatient behavior of customer’s will be discussed with exponential service distribution and Poisson arrivals. Higher priority customers have pre-emptive priority over the low priority customers. The G.F. technique is used to derive the performance measures of high & low priority queues and assuming FCFS discipline in busy schedule of higher priority class. Also evaluate queue behavior graphically and discussed a special case at the end which shows utilization of channels.
Hybrid Optimization Based Hindi Document Summarization Using Deep Learning Technique
Authors: Bandari Sumalatha , Bulusu Vishnu Vardhan
Published: September 2023

The proliferation of textual information today is a result of the internet's recent development, which is widely accessible to anybody, at any time. Generally speaking, several Natural Language Processing (NLP) techniques can be used to analyze the textual information that is offered on the basis of text documents. In recent years, various text summarization techniques have been implemented in English text documents but a little amount of work is carried out in Hindi text documents summarization. In this research investigation, the Coot Remora Optimization (CRO) technique based on Deep Recurrent Neural Network (DRNN) is used to summarize Hindi documents. Here, the CRO algorithm is used to train the DRNN, which is used to compute the sentence scores.The highest scored sentences are going to included in the summary. When compared to recent optimization algorithmic techniques, such as MCRMR-SSO, Graph-based_PSO, Genetic Algorithms (GA), and Political Elephant Herding Optimization (PEHO) based Deep Long Short Term Memory (DLSTM) algorithm, the developed method is shown to be superior. Additionally, three evaluation metrics such as precision, recall, f-measure are used to analyze the performance of the CRO based DRNN technique and obtained high performance.
Ascertaining Along With Taxonomy of Vegetation Folio Ailment Employing CNN besides LVQ Algorithm
Authors: Sunitha M , Manasa K , Kumar G Sravan , Vijitha B , Farhana Sheik
Published: September 2023

In agriculture, early disease detection is crucial for increasing crop yield. The diseases Microbial Blotch, Late Blight, Septoria leaf spot, and yellow twisted leaves all have an impact on tomato crop productivity. Automatic plant illness classification systems can assist in taking action after ascertaining leaf disease symptoms. This paper emphasis on multi-classification of tomato crop illnesses employs Convolution Neural Network (CNN) model and Learning Vector Quantization (LVQ) algorithm-based methodology. The dataset includes 500 photographs of Tomato foliage with four clinical manifestations. CNN paradigm performs feature extraction and categorization in which color information is extensively used in plant leaf disease investigations. The model's filters have been applied to triple conduit similar tendency on RGB hues. The LVQ was fed during training by a yield countenance vector of the convolution component. The experimental results reveal that the proposed method accurately detects four types of solanaceous leaf diseases.
Design an Optimal Decision Tree based Algorithm to Improve Model Prediction Performance
Authors: Pathan Shabana , Sharma Sanjeev Kumar
Published: September 2023

Performance of decision trees is assessed by prediction accuracy for unobserved occurrences. In order to generate optimised decision trees with high classification accuracy and smaller decision trees, this study will pre-process the data. In this study, some decision tree components are addressed and enhanced. The algorithms should produce precise and ideal decision trees in order to increase prediction performance. Additionally, it hopes to create a decision tree algorithm with a tiny global footprint and excellent forecast accuracy. The typical decision tree-based technique was created for classification purposes and is used with various kinds of uncertain information. Prior to preparing the dataset for classification, the uncertain dataset was first processed through missing data treatment and other uncertainty handling procedures to produce the balanced dataset. Three different real-time datasets, including the Titanic dataset, the PIMA Indian Diabetes dataset, and datasets relating to heart disease, have been used to test the proposed algorithm. The suggested algorithm's performance has been assessed in terms of the precision, recall, f-measure, and accuracy metrics. The outcomes of suggested decision tree and the standard decision tree have been contrasted. On all three datasets, it was found that the decision tree with Gini impurity optimization performed remarkably well.
Enhancing Handwriting in the Peruvian Educational Context: Design of an Interactive Web Platform
Authors: Lida Violeta Asencios-Trujilo , Lucia Asencios-Trujillo , Carlos Jacinto La Rosa-Longobardi , Djamila Gallegos-Espinoza , Cristina Piñas-Livia , Rosa Perez- Siguas , Hernan Matta-Solis
Published: September 2023

The main objective of this research work is to design a web platform so that through its use they can learn to write, it is aimed at a general public regardless of their age. A Design Thinking methodology was used since it was found to be adequate to explain each stage of the research in their respective phases of the methodology. On the other hand, a survey was conducted with 15 people from an Alternative Basic Educational Center (CEBA) to find out if they were willing to use a web platform to learn to write.

Finally, it was concluded that it is necessary to take advantage of technological advances for problems that may occur in the field of education and have solutions through its use.
Evolution and Stylistic Characteristics of Ancient Chinese Stone Carving Decoration LSTM-DL Approach with Image Visualization
Authors: Tian Yuan
Published: September 2023

In recent years, advancements in data analysis techniques and deep learning algorithms have revolutionized the field of art and cultural studies. Ancient Chinese stone carving decoration holds significant historical and cultural value, reflecting the artistic and stylistic evolution of different periods. This paper explored the Weighted Long Short-Term Memory Deep Learning (WLSTM – DL) evolution and stylistic characteristics of ancient Chinese stone carving decoration through the application of image visualization techniques combined with a Long Short-Term Memory (LSTM) time-series deep learning architecture. The WLSTM-DL model uses the optimized feature selection with the grasshopper optimization for the feature extraction and selection. By analyzing a comprehensive dataset of stone carving images from different periods, the WLSTM-DL model captures the temporal relationships and patterns in the evolution of stone carving decoration. The model utilizes LSTM, a specialized deep-learning architecture for time-series data, to uncover stylistic characteristics and identify significant changes over time. The findings of this study provide valuable insights into the evolution and stylistic development of ancient Chinese stone carving decoration. The application of image visualization techniques and the WLSTM-DL model showcase the potential of data analysis and deep learning in uncovering hidden narratives and understanding the intricate details of ancient artworks.
Text Data Mining for Uncovering the Influence of Religion on Ancient Greek Philosophical Thought with Optimization
Authors: Jiang Bian , Kong Shuai
Published: September 2023

Text data mining can provide valuable insights into the influence of religion on the development of ancient Greek philosophical thought. This paper presented text data mining techniques to perform feature extraction and classification with Gaussian Optimization (FeCGO), to analyze the influence of religion on the development of ancient Greek philosophical thought. This paper explores the application of text data mining techniques, specifically feature extraction and classification with Gaussian Optimization (FeCGO), to analyze the influence of religion on the development of ancient Greek philosophical thought. The FeCGO examined the relevant texts, including works by ancient Greek philosophers, religious texts, myths, and historical accounts. These texts are subjected to preprocessing steps, such as tokenization, stop word removal, stemming, and normalization, to ensure the data is prepared for analysis. The proposed FeCGO method combines the Gaussian Optimization algorithm with a classification model to optimize the classification accuracy and performance. Labeled data is used to train the FeCGO model, with texts categorized based on their religious or philosophical themes. The findings contribute to a deeper understanding of the interplay between religion and philosophy in ancient Greek society. The application of text data mining techniques, specifically FeCGO, demonstrates the potential of computational methods to extract valuable insights from large-scale textual datasets.
Feature Selection with Integrated Gaussian Seahorse Optimization Data Mining for Cross-border Business Cooperation between the Malaysian Medical Industry and Tourism Industry
Authors: Ma Yuaner , Jabar Juhaini , Aziz Nor Azah Abdul
Published: September 2023

The cross-border collaboration between the medical industry and the tourism industry has gained significant attention as a promising avenue for economic growth and development. Data mining techniques are employed to extract valuable patterns and insights from large-scale datasets, shedding light on the opportunities and challenges associated with this collaborative effort. This study proposes an integrated approach that combines feature selection with Gaussian Seahorse Optimization Data Mining (GSH-DM) to identify the most relevant features and optimize the data mining process. The GSH-DM assembling comprehensive datasets encompassing information from both the Malaysian medical industry and tourism industry. The integrated GSH-DM model then applies the Gaussian Seahorse Optimization algorithm to optimize the data mining process, enhancing the accuracy and efficiency of pattern discovery. the GSH-DM model, this study aims to uncover hidden patterns, relationships, and predictive models that can guide decision-making and strategy development for cross-border business cooperation. The findings of this study contribute to a deeper understanding of the factors that influence cross-border business cooperation between the Malaysian medical industry and the tourism industry. The integrated GSH-DM approach showcases the potential of combining feature selection techniques with advanced optimization algorithms in data mining applications. The results of GSH-DM provide actionable insights for stakeholders, enabling them to make informed decisions and foster successful cross-border collaborations between the Malaysian medical industry and the tourism industry. The analysis of the results demonstrated that GSH-DM exhibits improved performance for feature selection and classification.
A New Automatic Watercolour Painting Algorithm Based on Dual Stream Image Segmentation Model with Colour Space Estimation
Authors: Zhou Ye , Sirivesmas Veerawat , Joneurairatana Eakachat , Simatrang Sone
Published: September 2023

Image processing plays a crucial role in automatic watercolor painting by manipulating the digital image to achieve the desired watercolor effect. segmentation in automatic watercolor painting algorithms is essential for region-based processing, color mixing and blending, capturing brushwork and texture, and providing artistic control over the final result. It allows for more realistic and expressive watercolor-like paintings by processing different image regions individually and applying appropriate effects to each segment. Hence, this paper proposed an effective Dual Stream Exception Maximization (DSEM) for automatic image segmentation. DSEM combines both color and texture information to segment an image into meaningful regions. This approach begins by converting the image from the RGB color space to a perceptually-based color space, such as CIELAB, to account for variations in lighting conditions and human perception of color.  With the color space conversion, DSEM extracts relevant features from the image. Color features are computed based on the values of the color channels in the chosen color space, capturing the nuances of color distribution within the image. Simultaneously, texture features are derived by computing statistical measures such as local variance or co-occurrence matrices, capturing the textural characteristics of the image. Finally, the model is applied over the deep learning model for the classification of the color space in the painting. Simulation analysis is performed compared with conventional segmentation techniques such a CNN and RNN. The comparative analysis states that the proposed DSEM exhibits superior performance compared to conventional techniques in terms of color space estimation, texture analysis and region merging. The performance of classification with DSEM is ~12% higher than the conventional techniques.
Voting Classifier for The Interactive Design with Deep Learning for Scene Theory
Authors: Yang Ying
Published: September 2023

Tool products play a pivotal role in assisting individuals in various domains, ranging from professional work to everyday tasks. The success of these tools is not solely determined by their functionality but also by the quality of user experience they offer. Designing tool products that effectively engage users, enhance their productivity, and provide a seamless interaction experience has become a critical focus for researchers and practitioners in the field of interaction design. Scene theory proposes that individuals perceive and interpret their surroundings as dynamic "scenes," wherein environmental and situational factors influence their cognitive processes and behavior. This research paper presented a novel approach to the interaction design of tool products by integrating scene theory, flow experience, the Moth Flame optimization (MFO), cooperative game theory (CGT), and voting deep learning. Tool products play a vital role in various domains, and their interaction design significantly influences user satisfaction and task performance. Building upon the principles of scene theory and flow experience, this study proposes an innovative framework that considers the contextual factors and aims to create a seamless and enjoyable user experience. The MFO algorithm, inspired by the behavior of moth flame, is employed to optimize the design parameters and enhance the efficiency of the interaction design process. Furthermore, CGT is integrated to model cooperative relationships between users and tool products, fostering collaborative and engaging experiences. Voting deep learning is employed to analyze user feedback and preferences, enabling personalized and adaptive design recommendations. With the proposed CGT, this paper investigates the impact of the proposed approach on user engagement, task efficiency, and overall satisfaction. The findings contribute to the field of interaction design by providing practical insights for creating tool products that align with users' cognitive processes, environmental constraints, flow-inducing experiences, and cooperative dynamics.
Mobile Platform with Dynamic Optimization of the Pattern in Education in Colleges Through the Perspective of Network Informatization
Authors: Wang Xue , Yu Qing
Published: September 2023

The combination of mobile learning platforms and network informatization offers numerous benefits to learners, educators, and institutions. Learners can take control of their learning journey, accessing educational materials at their convenience and engaging in collaborative learning activities with peers from diverse backgrounds. This paper aims to explore the integration of mobile learning platforms and network informatization, examining their impact on educational practices, learner engagement, and the overall learning experience. The network informatization is assessed and monitored with Dynamic Programming Optimization (DPO) to compute the feature in reverse osmosis in English education. The attributes and features in the English language are computed and estimated for the periodic information update within the system. The DPO process is implemented along with the mandhani fuzzy set for the estimation of features in English education in colleges and universities. The information processed is updated in the mobile learning platform for the computation of the features in the English language and classification is performed with the deep learning model. Simulation analysis stated that constructed model is effective for the estimation and computation of the features and patterns in English language teaching in colleges and universities.
An Adaptive Blockchain based Three-Tier Architecture in Fog based IoT for Personal Healthcare Data Application
Authors: Naidu J.N.S.S Janardhana , Ganesh E.N
Published: September 2023

To protect patient health data (PHD) and ensure the security of healthcare IoT devices, this paper presents an Advanced Signature-Based Encryption algorithm (ASE), a blockchain analytical model, a mathematical framework, and an Adaptive Fog Computing based Three-tier Architecture (AFCTTA). The aim is to enable safe access to real-time services and IoT for end users. This AFCTTA was constructed on a blockchain platform, providing trustworthy data transmission between patients, clinicians, fog nodes, and IoT. Additionally, a decentralized fog computing-based blockchain analytical model along with a mathematical framework were produced to ensure secure transfer of data and transactions within healthcare IoT. To ensure secure communication between devices and fog nodes, a private block chain was implemented in order to validate certificates and keys. As an added security measure, an ASE method was devised. This algorithm utilizes War Optimization Strategy (WOA) to select optimal keys for securing data from heterogeneous and homogeneous IoT healthcare equipment. Through its encryption process utilizing various cryptographic techniques, all traffic is encrypted before being decrypted once it reaches its intended destination. To validate its proposed approach, UCI machine library is collecting health care data. To execute this method, Python is utilized and compared to traditional algorithms such as Rivest-Shamir-Adleman (RSA), Elliptical Curve Cryptography (ECC), and Tiny Lightweight Symmetric Encryption-Aquila Optimization Algorithm (TLSE-AOA).
A Cloud Computing-based Research on the Relationship between Educational Internship and Pre-Service English Teachers' Professional Development
Authors: Wang Panpan
Published: September 2023

Educational internships are a crucial component of teacher education programs, as they evaluated the experience practical opportunities for preschool teachers with the development of skills, experience of practical scenarios, and experience feedback. Through educational internships, pre-service teachers can also develop their professional identities and gain a deeper understanding of the complex challenges and rewards of teaching. This paper explores the relationship between educational internships and heuristic optimization cloud environments for the professional development of English pre-service teachers. The research presents a novel approach called Cloud Spider Wolf Optimization (CSWO) that utilizes cloud computing technology to enhance the effectiveness of educational internships. The study evaluates the impact of CSWO on pre-service teachers' professional development by examining their learning outcomes and perceptions of the internship program. The data for the analysis is collected through primary data among the pre-service English teachers. The data for analysis is collected from 200 pre-service teachers in academic schools in China. The results indicate that CSWO significantly improves pre-service teachers' professional development by providing them with opportunities to engage in authentic, real-world tasks that enhance their knowledge and skills in English language teaching. The study also suggests that the use of cloud computing technology can provide a valuable tool for enhancing the effectiveness of educational internships. The findings have important implications for teacher preparation programs and suggest that the integration of cloud computing technology and heuristic optimization techniques can be used to improve the quality of teacher education.
Secure MapReduce Framework with Data Compression Model to Evaluate Ideological Evaluation Contribution on Students
Authors: Wu Juan
Published: September 2023

Ideological education is the process of transmitting and instilling a particular set of beliefs, values, and worldviews in individuals, with the goal of shaping their attitudes, behaviors, and perceptions. In colleges, ideological education plays an important role in shaping students' values, beliefs, and attitudes toward society, politics, and culture. The primary objective of ideological education in colleges is to promote critical thinking skills, social responsibility, and civic engagement among students. However, the use of big data in ideological education also raises concerns about privacy and ethical considerations. It is important to ensure that students' personal information is kept secure and that data is only used for educational purposes. It is also important to ensure that the use of big data does not lead to bias or discrimination of certain students or groups based on their demographics or backgrounds. This paper constructed a framework of Stream Cipher MapReduce Fractal Index (ScMFI). The ScMFI model performs the processing of information about students in ideological education in colleges. Through the Fractal Index Tree data is compressed with the MapReduce Framework. Finally, the ScMFI model uses the Stream Cipher process for data processing and storing in the cloud environment. The developed ScMFI model contribution of ideological education toward students’ awareness is classified as a machine learning model. The simulation analysis stated that ScMFI model minimizes the data storage, encryption and decryption time.