bluuebunny/crossref_metadata_2025 huggingface dataset:
Dialectics of Pleasure in Thomas More’s Utopia
Authors: Holmesland Oddvar
Published: September 2023

Thomas More’s Utopia represents not a pleasurable alternative world, but rather a debate on how to make life more pleasurable in the actual world. It involves a tussling with questions of truth in an age in which unifying transcendental answers were giving way to more instrumental solutions as demanded by the growth of mercantile city-states. This article traces the function of pleasure in Utopia as a dialectically mediating agent on the recognition that pleasure is available only in compromised form. For More, solutions must be sought through the mind’s capacity to form agreeable relations out of contradictions. It implies assembling meaning from the perspectives Utopia provides, and a constant balancing and rebalancing process in search of an overall point of view that may give pleasure.
Outcome of Pregnancies with Severe Oligohydramnios in the 3rd Trimesters
Authors: Rahman Mahin , Mina Mst. Nazmunnaher , Sarker Taposhi , Areen Samira , Ahamed Tanwir Iqbal Ibn , Chowdhury Kanta
Published: September 2023

Background: Amniotic fluid volume (AFV) of less than 200 ml is considered as insufficient, and is referred as significant oligohydramnios. Approximately 8% of pregnant women may experience low amniotic fluid levels ( less than normal / AFI < 8 cm ) But among them about 4% of pregnant women are diagnosed with severe or significant oligohydramnios. A range of unfavorable perinatal outcomes, including fatal growth restriction meconium aspiration of fetus, fetal distress and surgical intervention for foetal distress in labour and even perinatal death, are linked to oligohydramnios which are found during the antepartum period of pregnancy. The purpose of the study was to determine the outcome of pregnancies with severe oligohydramnios in the 3rd trimester. Material & Methods: This prospective observational study was carried out on the admitted patients in the Department of Gynecology & Obstetrics at Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, from February to July 2013 (6 months). A total of fifty women (N=50) having Oligohydramnios in pregnancy were included in the study. Completed data forms were reviewed, edited, and processed for computer data entry. The data analysis was performed using Statistical Package for Social Sciences (SPSS) Version 25.0. The ethical clearance of this study was obtained from the Institutional Review Board (IRB) of BSMMU, Dhaka, Bangladesh. Results: Mean age of the mothers was 25.8 years and two-fifths of the mothers (20, 40.0%) belonged to 21-25 years old. Twenty-three mothers (23, 46.0%) were nulliparous. Of fifty mothers (N=50), eighteen (18, 36.0%) had borderline oligohydramnios & thirty-two (32, 64.0%) had severe oligohydramnios. Normal CTG tracing was found in eighteen patients (18, 36.0%) and abnormal CTG was found in thirty-two patients (32, 64%). Based on fetal outcome (N=50), 23 babies (23, 46.0%) were admitted to the NICU, of whom 7 (7, 14.0%) had birth asphyxia, 8 (8, 16.0%) had neonatal sepsis, 4 (4, 8.0%) had neonatal jaundice, 2 (2, 4.0%) had meconium aspiration syndrome, 4 had stillbirths, and 5 had died as neonates. Conclusion: Nowadays, routine obstetric USG is more routinely used to detect oligohydramnios. In the third trimester of pregnancy, PIH and postdated pregnancies are the most common causes of decreasing amniotic fluid. Unfavourable perinatal outcomes can be avoided with careful fetal heart rate monitoring during antenatal period and at labour. Every case of oligohydramnios necessitates a comprehensive prenatal assessment, parental counselling, and a personalized delivery time and technique. This study found no connection between meconium-stained liquor and oligohydramnios and found that caesarean section deliveries were considerably more common in these women.
SOCIAL SPHERE DEVELOPMENT AND REGION’S ECONOMY ASSESSMENT
Authors: Таусова И.Ф. , Паатова М.Э.
Published: September 2023

Социальная сфера является одним из ключевых векторов развития любого региона. Она включает в себя различные направления, такие как здравоохранение, образование, культура, социальная защита населения и т.д. Важно следить за показателями развития социальной сферы, чтобы определить эффективность работы власти региона в этом направлении. Статья посвящена исследованию комплекса показателей развития социальной сферы в Республике Адыгея и влияющих на них факторов.

The social sphere is the key vectors of development of any region which includes Public Health, Education, Culture, Social Protection. It is important to monitor the development of the social sphere to determine the effectiveness of the regional authorities’ work The level of the social sphere development in the Republic of Adygheya is considered.
Russia and South Ossetia United Civilizational Platform: Socio-Political and Cross-Cultural Interaction
Authors: Dumina E. V.
Published: September 2023

The article is devoted to the topical after the collapse of the USSR problem of regional integration of sovereign countries for the joint solution of geopolitical, socioeconomic, general cultural and other tasks. The article analyzes the situation associated with the ambiguity of international legal criteria for the recognition of newly formed states and the inconsistency in the interpretation of the right of peoples to equality and self-determination. The historical justification is given and the legal basis for the entry of the Republic of South Ossetia into the Russian Federation as a new subject is described. It is shown that the reunification of two Ossetias, North and South, which created a new historical reality in the life of the Ossetian ethnic group, became the basis for the decision of the leadership of South Ossetia to join Russia by holding a referendum. The circumstances of the postponement of the referendum for an indefinite period are substantiated. The author concluded that the integration of Russia and South Ossetia will lead mainly to positive consequences for both states.
IDENTIFICATION OF ETHNOMEDICAL MEDICAL PLANTS FOR DEGENERATIVE DISEASES IN TARERAN DISTRICT, SELATAN MINAHASA REGENCY, NORTH SULAWESI, INDONESIA
Authors: Tumbel Ferny , Montolalu Friska , Kalitouw Devitha
Published: September 2023

This study aims to: Obtain distribution data and types of medicinal plants in Tareran District, South Minahasa. Obtain data on the use of medicinal plants for degenerative diseases in Tareran District, South Minahasa. Plant samples can be in the form of leaves, stems and roots or whole plants obtained in Tareran District, South Minahasa Regency. Samples of medicinal plants are devoted to medicinal plants that are used for degenerative diseases. The samples used were wet samples and dry samples (10% moisture content) and wet samples. Materials used include ethanol, alcohol, plant specimen paper, electric oven, etc. Inventory of medicinal plants using plant determination books and writing instruments, cameras and specimen boxes. Data on the use/utilization of medicinal plants using a questionnaire. The results showed that in Tareran District there are many types of plants used as medicinal plants for degenerative diseases, including: Cinnamon (hypertension), Noni (Diabetes), Temulawak (hyperlipidemia). The community has not cultivated medicinal plants intensively. Public knowledge of the scientific efficacy of medicinal plants is still very little so that it affects the utilization of these medicinal plants. In terms of the use of medicinal plants, the economically weak community uses medicinal plants more than the middle to upper economic community. In fact, there are more doubts about the efficacy of medicinal plants in the middle and upper economic community. The use of medicinal plants in the middle to upper economic community is only carried out by the elderly.
ANALYSIS OF THE EFFECT OF PGPR FERTILIZER USE ON GROWTH ACCELERATION OF CHERRY TOMATO (Solanum lycopersicum var. cerasiforme)
Authors: Kojongian Genade , Naharia Orbanus , Lawalata Helen
Published: September 2023

Cherry tomatoes are a type or commodity of horticulture that has a very relatively high economic value compared to ordinary tomatoes. Cherry tomato plants (Solanum lycopersicum var,. cerasiforme. It is one of the local plants that is neglected and not used and is often considered as a wild plant. This study aims to determine the effect of PGPR fertilizer application on the growth of cherry tomato plants. This research was carried out in the urban village). Rerewokan, West Tondano sub-district starting from August to November 2021. The method used is a quantitative method with the type of experimental research in the form of a Randomized Block Design (RAK) with five types of treatment, each repeated four times. P1 = without using fertilizer, P2 = 100ml, P3 = 200ml, P4 = 300ml, P5 = 400ml, so there were 20 treatment combinations, and the data obtained were then analyzed using analysis of variance (ANOVA). From the results of this study, it showed that good plant height growth was found in treatment P4 with the application of a mixture of PGPR fertilizer concentration of 300ml / 2 liters of water, because there was the most effective growth, while the growth in the number of leaves and the number of fruits was very good in treatment P2 with the addition of a mixture. PGPR fertilizer concentration 100ml / 2 liters of water.
EFFECT OF FEEDING MARKET VEGETABLE WASTE ON WEIGHT GIAN OF RABBITS (Oryctolagus cuniculus L.)
Authors: Kotambunan Michael Stiff , Simanjuntak Suddin , Roring Verawati Ida Yani
Published: September 2023

Rabbits are livestock that has the potential to provide meat in a relatively short time, so people's consumption of animal protein is expected to be fulfilled. Market vegetable waste can also be used as feed, especially for rabbits. When processed into rabbit feed, waste is not only a product, but from the feed consumed by rabbits, it can produce meat of good quality. This study aimed to determine whether feeding vegetable waste can increase rabbit body weight and whether combining pellets and vegetable waste can increase rabbit body weight. This study used a quantitative experimental method using an experimental design that was Completely Randomized Design (CRD) with six treatments and four replications. The survey results showed that feeding vegetable waste was effective as feed for rabbits because it could increase the body weight of rabbits (Oryctolagus Cuniculus L.). The more balanced the market vegetable waste feed in the form of cabbage, carrots, pattern (young corn shoots) and pellets were given, the higher the weight gain of rabbits (Oryctolagus Cuniculus L.). Market vegetable waste is not recommended as a good feed. Still, it can be used as a supplement only because research results show that market vegetable waste does not have a significant effect.
first phase of clean India mission: A step towards new India
Authors: Chakraborty Nandini
Published: September 2023

Clean India's mission is the world’s largest toilet-building and behavioral change initiative. The Mission is the world’s largest toilet-building and behavioral change initiative. Media’s role is to inform, educate, and entertain; so mass media make nationwide campaigns to open the eyes of poor, backward-class people; and also want to enlighten the open-minded ideas into rigid superstitious people. Most of all third-world countries are facing a big problem of access to safe and healthy sanitation. Media can spread the message of safe and hygienic sanitation for all the citizens. The Clean India movement will fulfill the dream and vision of Mahatma Gandhiji to make a ‘Swachha Bharat’ for all Indians in a real sense.
DESENVOLVIMENTO PROFISSIONAL NA EDUCAÇÃO INFANTIL: FORMAÇÃO, RECONHECIMENTO E VALORIZAÇÃO DOCENTE
Authors: Côco Valdete , Mello André Da Silva
Published: September 2023

Abordamos a temática da docência na Educação Infantil (EI), por meio da proposição de apontamentos vinculados às políticas de formação, reconhecimento e valorização, no horizonte da atenção ao desenvolvimento profissional. Na aproximação aos referenciais teórico-metodológicos Bakhtinianos, em articulação com os compromissos afirmados para EI (notadamente de expansão e qualificação do atendimento), partimos de um conjunto de produções vinculadas a um grupo de pesquisa. Com a revisão desses acúmulos, destacamos a complexidade dos intervenientes que marcam os processos de participação, de produção de normativas (para o delineamento da formação e o desenvolvimento da EI) e das condições postas no campo de trabalho (em especial, no provimento dos quadros funcionais). Como resultados, apontamos para a abordagem do desenvolvimento profissional como movimento, agregado às condições que marcam o desenvolvimento da EI, de modo a reivindicar investimentos nesse campo de trabalho.
O ESTUDO DA EROSÃO DOS SOLOS SOB UMA CONCEPÇÃO SISTÊMICA
Authors: Borges Neto Inocencio De Oliveira , Santos Leonardo José Cordeiro , Suertegaray Dirce Maria Antunes , Xavier Rafael Albuquerque
Published: September 2023

O presente artigo objetivou compreender como os processos erosivos podem ser analisados, sob uma visão sistêmica. Sendo assim, aqui considera-se a erosão dos solos um fenômeno de ocorrência natural, que pode (e geralmente é) ser influenciado pelas atividades antrópicas, se configurando como um dos principais problemas ambientais do planeta, além de ser o principal agente modelador da superfície terrestre. As consequências da atuação acelerada dos processos erosivos são inúmeras, como por exemplo: redução da fertilidade natural e capacidade produtiva dos solos; assoreamento e poluição dos corpos hídricos; empobrecimento das comunidades rurais, êxodo rural, entre muitos outros. Entender a dinâmica deste fenômeno, se torna fundamental, pois, a compreensão da sua abrangência espaço-temporal associada com o conhecimento dos possíveis problemas que podem vir a ocorrer com sua atuação acelerada, fornece subsídios para a elaboração de gestões sustentáveis, deste recurso tão valioso, haja vista que, os solos são o ‘alicerce’ da fauna, flora, e principalmente da subsistência humana. Os procedimentos analíticos deste manuscrito, estão fundamentados na construção de um sistema baseado em um estudo de caso, exemplificando como a abordagem sistêmica pode ser desenvolvida nos estudos dos processos erosivos. Ao analisar a erosão dos solos sob uma abordagem sistêmica, foi possível observar como os diversos fluxos de matéria e energia ocorriam entre as variáveis, explicitando a importância de compreender os processos erosivos de forma integrada, evitando interpretações fragmentadas e reducionistas.
SINAL DO FENÔMENO ENOS NA PRECIPITAÇÃO PLUVIAL DA REGIÃO OESTE DO PARANÁ
Authors: Pedron Isabel Tamara , Limberger Leila
Published: September 2023

Um dos moduladores da variabilidade no padrão de precipitação na região Sul do Brasil é o fenômeno El Niño/Oscilação Sul (ENOS), foco deste estudo que tem como objetivo investigar a influência do ENOS no Oeste do Paraná, sul do Brasil. Avaliou-se a complexidade de manifestação em escala local (precipitação pluvial) de um fenômeno de escala global (ENOS). O estudo foi desenvolvido utilizando-se série mensal de chuva para Cascavel, Toledo, Palotina, Foz do Iguaçu e Guaíra. Os resultados indicam que não há um comportamento uniforme em toda a região para a identificação de sinal dos efeitos dos eventos ENOS. Somente Cascavel e Palotina apresentaram correlação de Spearman significativa entre acumulados mensais de precipitação e o índice ONI (Oceanic Niño Index), não só em dados pareados (mesmo mês) como também defasados de um a quatro meses. Por outro lado, a análise de ondeletas indica o sinal do fenômeno ENOS nos dados de chuva, ressaltando o pico nos períodos de dois a sete anos no espectro de energia para Cascavel, Foz do Iguaçu e Palotina. Na análise de coerência em ondeletas, todos os locais exibem correlação entre o índice ONI e as séries de acumulados mensais, no período em torno de quatro anos. Este trabalho destaca a complexidade da manifestação do ENOS em escala local, sendo que a variabilidade climática das cidades analisadas não responde somente a esse modulador de variabilidade, sendo necessária a consideração de outras áreas oceânicas e outros fatores, locais, que geram variabilidade, evidenciando o desafio colocado para previsão climática.
Hybrid-Plasma is an Energy Generator: A Novel Method of Energy Production
Authors: J Scherlag Benjamin
Published: September 2023

Introduction: Our previous reports have documented the discovery, properties and applications of a new form of nonthermal plasma which has an indefinite life span. Plasmas are defined as physico-chemical reactions involving ions, free electrons and neutral atoms. In the present study we measured the energy of Hybrid-Plasma (HP) whose major components are water (H2 0) and Hydrogen Peroxide (H2 02 ) Methods: Two electrically activated misters containing either distilled H2 0 or H2 02 were placed in a 36-quart plastic container with 2 aluminum foil strips applied on either side of the container to serve as electrodes. The same procedure was performed in a 6.5quart container. An ion counter was also placed at the bottom of the container which was sealed with snap covers. A digital voltmeter connected to the 2 electrodes were used to determine electrical current for the next 5 minutes during the first hour and then again at 24 hours. Results: The ion counter registered maximal levels as soon as the combined water misters were started. Alternating Current (AC) levels progressively increased in the first hour and was greatest at 24 hours. Conclusions: Our newly discovered HP can serve as an electrical generator of AC current that persists for several days.
The Greening of Our Hills
Authors: Gole Prakash
Published: September 2023

This article explains the efforts taken in greening a patch of the barren hills in Western Ghats. The plant life on the hills is destroyed by the annual burning. Regeneration on such patches is a slow process. Various experiments carried out throughout different seasons which showed positive results. Such restored and protected patches are valuable resources of indigenous flora, forest produce and a sanctuary for wild animals.
Response of Jatropha seedlings to seed size and growing medium
Authors: Kaushik Naresh , Kaushik J. , Kumar Sushil
Published: September 2023

An experiment was conducted at HAU Regional Research Station, Bawal in order to get good quality seedlings for planting; on investigating the effect of seed size and rooting media on the growth of Jatropha curcas seedlings. Seedlings from large sized seeds showed significant increase in height, collar diameter, root length, number of leaves and dry matter production than small sized seeds. Rooting medium containing farmyard manure (FYM) was significantly better than rooting medium without farmyard manure.
THE IMPACT OF GEOPOLITICAL SITUATION ON THE VOLUME OF DECLARED GOODS AND FINANCIAL RECEIPTS TO THE BUDGET FROM CUSTOMS PAYMENTS IN THE SOUTHERN ELECTRONIC CUSTOMS
Authors: Рощина Л.Н. , Соленая С.В. , Трушина А.А.
Published: September 2023

Введение. В статье содержится оценка влияния геополитической ситуации на объемы декларирования товаров и финансовые поступления в бюджет от таможенных платежей на примере Южной электронной таможни. Материалы и методы. Основу методического аппарата исследования составляют общенаучные методы (синтез, диалектический метод) и метод логического и дескриптивного анализа. Результаты исследования. Представлены пути решения проблем, связанных с отрицательным влиянием геополитической ситуации на объемы декларирования товаров и финансовые поступления в бюджет от таможенных платежей Обсуждение и заключение. Изучены результаты мероприятий по нивелированию отрицательного влияния геополитической ситуации на объемы декларирования товаров и финансовые поступления в бюджет от таможенных платежей южной электронной таможни. Проведенный анализ деятельности органов Южной таможни при декларировании товаров, поставляемых железнодорожным транспортом из азиатского региона, позволил определить его значимость в целях пополнения доходной части бюджета.

Introduction. This article presents an assessment of the influence of the geopolitical situation on the volume of declared goods and financial receipts to the budget from customs payments, using the Southern Electronic Customs as an example. Materials and Methods. The methodological apparatus of the research is based on general scientific methods (synthesis, dialectical method) and the method of logical and descriptive analysis. Results. The article outlines solutions to address challenges related to the negative impact of the geopolitical situation on the volume of declared goods and financial receipts to the budget from customs payments. Discussion and Conclusion. The results of measures aimed at leveling the negative impact of the geopolitical situation on the volume of declaration of goods and financial revenues to the budget from customs payments of the southern electronic customs are studied. The analysis of the activities of the southern customs authorities when declaring goods delivered by rail from the Asian region allowed us to determine its importance in order to replenish the revenue side of the budget.
From Cosmopolitanism to Cosmology and Back Again: Co-Curating a Practice-Centred South African Jazz Collective, 2020-2022
Authors:   University of the Witwatersrand, Johannesburg, Pyper Brett , Moshugi Kgomotso
Published: September 2023

Since 2005 as a researcher, and since the early 1990s as an organiser who worked in Pretoria as South Africa transitioned towards democracy, Brett Pyper has had the privilege of knowing a community of practice that occupies a distinct, under- recognised position in the country’s internationally famous jazz culture. Known variously as jazz appreciation societies, social clubs or stokvels (mutual aid associations), these township-based collectives played no small part, during the long night of apartheid, in preserving and developing the vibrant, cosmopolitan African cultures that were suppressed and dispersed under racial and ethnic segregation policies. They did so in spite of restrictions on public gatherings, and in communities with hardly any civic or cultural amenities. After the formal end of apartheid and the lifting of cultural boycotts in the 1990s, the country’s reintegration into circuits of international cultural exchange resulted in the establishment of several globally benchmarked festivals. Meanwhile, these community-based jazz societies underwent their own efflorescence, though in relative isolation from the festivals that take place in downtown convention centres for a globally mobile, relatively elite clientele. These developments emblematise the promise as well as the limitations of the post-apartheid transition: while the existence of platforms for international jazz luminaries serves as a powerful symbol of change and a vehicle for the assertion of transnational cultural and political ties, the audience for jazz music in South Africa remains largely excluded from participating in these celebrations of avowedly post-apartheid culture.
The Another Roadmap Africa Cluster (ARAC) Un/Chrono/Logical Timeline of Histories of Arts Education: From the Wits School of Education to Documenta 15, Kassel Germany
Authors:   University of the Witwatersrand, Johannesburg, Andrew David
Published: September 2023

This paper explores the development and evolution of the un/chrono/logical timeline of histories of arts education initiated by the Another Roadmap Africa Cluster (ARAC) Histories of Arts Education Research Project. The timeline, consisting of multiple iterations, challenges the traditional notions of history and engages with personal narratives, language, and multimodal elements. The research project aims to map and understand the diverse models of arts education, emphasising local perspectives and resistance to imported models. Drawing inspiration from the Medu Art Ensemble, the research framework employs intergenerational collaboration, dialogue, decentralisation, and a focus on language and ideology. The paper highlights the significance of the timeline in reimagining and practicing arts education.
Developing a Healing Arts Pedagogy and Practices (HAPPy) Training: An Arts-Based Curriculum for Trauma Stabilisation and Stress Alleviation in the South African Educational System
Authors:   University of the Witwatersrand, Johannesburg, De Beer Welma , Draper-Clarke Lucy ,   University of the Witwatersrand, Johannesburg
Published: September 2023

This paper discusses the theoretical foundations and pedagogical principles underlying the “Mas’phefumle” project, which explores healing arts practices and pedagogy as a response to trauma in South Africa. The authors propose that artistic research has transformed and advanced arts-based pedagogies in the country, offering impactful healing practices that can help communities during challenging times and regulate individuals after traumatic incidents. The curriculum developed, called Healing Arts Pedagogy and Practices (HAPPy), aims to establish culturally sensitive activities that promote resilience and create safe learning environments. The foundations of the curriculum are based on healing, the arts, pedagogies, and practices, integrating elements of polyvagal theory, psychotraumatology, and the African philosophy of Ubuntu. The paper describes the action research method used and presents the initial cycle of the curriculum’s development.
Creative Curatorial Practice as a Means of Reorientating Display Tropes in Museums of Natural History
Authors:   University of Cape Town, Langerman Fritha
Published: September 2023

This paper provides a critical analysis of natural history museums and their display practices. It explores the contradictions inherent in the concept of “natural history” and the dominance over nature it implies. The paper argues that museums still promote authoritative classification and knowledge systems that reinforce hierarchical structures and colonial ideologies. The author, an artist-curator and printmaker, shares her experiences with three exhibitions that challenge traditional display methods. By disrupting linear progression, introducing complex interconnections, and emphasizing sensory experiences, the exhibitions aim to create alternative models of display that reflect the entangled and web-like nature of speciation. The goal is to move beyond colonial narratives and imagine new ways of representing and understanding the natural world within museum spaces.
A Return to Practices and Pedagogies: Artistic Research as Untethering and Foraging
Authors:   University of the Witwatersrand, Johannesburg, Barry Hedwig , Andrew David ,   University of the Witwatersrand, Johannesburg
Published: September 2023

This paper reflects on the intertwining of artistic research and pedagogies within the context of a collaborative project conducted at the University of the Witwatersrand, Johannesburg. The authors explore the concepts of proximities, grids and flows, confrontations, and time as entry points into the space of artistic research. They emphasize the importance of untethering and foraging, challenging established boundaries and embracing discomfort as a catalyst for creative growth. The paper also highlights the significance of proximities and the relational aspect of artistic research, inviting a communal and interdisciplinary approach. The authors reflect on their experiences during the pandemic and the evolving nature of teaching and learning in relation to time.
CNNs and RNNs in aspect-level sentiment analysis and comparison
Authors: Qi Yijun
Published: September 2023

Aspect-based sentiment analysis (ABSA), also known as fine-grained sentiment analysis, may offer a precise polarity for each aspect in statement aspect. CNN and RNN neural network models, the most fundamental and widely used deep neural network models, have been created by researchers using a variety of methodologies to offer reliable findings in ABSA. This paper will sort out the development process of CNN and RNN models in completing various tasks in aspect-level sentiment analysis and find out the current SOTA model. In addition, by comparing the representatives of the two models in the same environment, the advantages and disadvantages of the two models are analysed to provide guidance for choosing different baseline models. The results show that the CNN-based model has the advantages of high accuracy and fast training speed, but the design is more complicated, and the pooling layer is prone to lose position or sequence features. The RNN-LSTM based model is easier to capture sequence data, has high reliability, and has a relatively simple design structure. However, it requires significantly longer training time, the model is complex, and the computational cost is high. Considering the characteristics of the two most basic neural models, new tasks require researchers to propose better hybrid neural network models.
Security analysis of blockchain-based service network
Authors: Zhang Xuzhuo , Lyu Pengju
Published: September 2023

Recently, the extensive applications of blockchain technology in fields like financial exchanges, insurance, Logistics and healthcare has proven to be pragmatic and revolutionary. In order to enable the blockchain to have a more complete development space, Blockchain-based Service Network (BSN) was proposed. It integrates the developers, portal, cloud resources and blockchain framework to provide the basic environment for blockchain applications. Researches on its security have kept place with the advent of blockchain technology, while potential issues on BSN security remain largely unexplored. In this paper, we are devoted to diving deep into BSN security-related problems, specifically the security of BSN is analysed, and corresponding real attacks are summarised and investigated by checking the blockchain system adopted by BSN, which will provide a good reference for the future research. Finally, we reach the conclusion that although security issues still exist, there are fewer security issues compared with traditional blockchain.
Iterative algorithms and architectures in massive MIMO detection
Authors: Liu Qirui
Published: September 2023

Massive multiple-input multiple-output (MIMO) wireless systems play an important role in the 5G networks. The complexity of signal detection in massive MIMO is increasing rapidly due to the growth of the number of transmitting antennas. In this paper, we introduced different iterative algorithms to decrease the computational cost of the approximate minimum mean-square error (MMSE) algorithm, including the Neumann Series algorithm, Jacobi method, Gauss-Seidel method, Successive Over Relaxation method and the Conjugate Gradient method. In addition, the VLSI architecture implementations of algorithms mentioned above are also discussed in the article.
Optimization of Alpha-Beta pruning based on heuristic algorithm
Authors: Ma Don Yitong
Published: September 2023

Games have become an important place for testing Artificial Intelligence (AI). Minimax and Alpha-Beta Pruning are two common and basic algorithms implemented in game AIs. However, there are still limitations of the searching time and searching depth. This paper strives to improve the game AI with a Heuristic Algorithm to optimize both the searching time and depth. The experiment consists of three AIs built with Minimax, Alpha-Beta Pruning, and Heuristic Algorithm to evident the improvement. These AIs are built to play a traditional Chinese zero-sum game, Gobang, which can be seen as an enhanced version of tic-tac-toe but more advanced. The data is collected when AIs compete with each other. Comparing the search time of three AIs, there is significant improvement of AI implemented Heuristic Algorithm; the median search time for Heuristic AI is only half of the Alpha-Beta Pruning AI, and only quarter of the Minimax AI. Moreover, because the search time decreases, the searching depth of the Heuristic AI can also be increased. With the larger searching depth, the Heuristic AI also gains a higher winning rate against the other two AIs.
Driver fatigue detection based on lightweight MobileNetV2
Authors: Wang Haoyuan
Published: September 2023

Fatigue driving brings a huge potential threat to the property and life safety of drivers and pedestrians. In order to improve the intelligence level of driver fatigue driving detection, a driver fatigue detection method based on MobileNetV2 lightweight separable convolutional neural network is proposed in this study. Firstly, the driver images in the data are pre-processed to make the data compatible with the model and improve accuracy, then the MobileNetV2 network model is used to detect and extract key features (mainly eye and mouth information) from the face, and finally the softmax function is used to classify the acquired features (based on the trained parameters, which have been obtained to discriminate fatigue) and determine whether the driver is in a fatigue state. The experimental results show that the proposed method has the satisfactory performance in terms of the accuracy, can basically adapt to driving scenes under different lighting, and has high robustness.
Classification of overpass structures based on convolutional neural networks
Authors: Xie Zhaoyang
Published: September 2023

The navigation of overpass structures heavily relies on high-definition road maps, but in cases where these maps are unavailable, the automated classification system can enable the vehicle to identify potential road designs when access to satellite images is available, and navigate around the structure. In the paper, different Convolutional Neural Networks (LeNet5, AlexNet, and ResNet) are used for classification, and their effectiveness are compared. Data in the research is collected from Google Maps and Amap. The experiment results have shown that AlexNet has the best results, reaching 98% accuracy. ResNet is the second, reaching 96%. LeNet5 has the least accuracy, 75%. The classification model can easily identify the structure of common overpasses in cities as well as the countryside.
BERT for sentiment analysis in the era of epidemic
Authors: Li Yanshu
Published: September 2023

With the continuous progress of Internet technology, the network platform has gradually entered everyone's life, providing a platform for ordinary people to express their ideas. Since the occurrence of COVID-19, monitoring and analyzing public opinion on the Internet platform has become more practical. Through timely monitoring and analysis, it is of great practical significance for the relevant departments to analyze and control sentiment information and stabilize and guide public sentiment. Therefore, it is essential and of practical significance to select a suitable model for classifying and analyzing public opinion on the Internet platform. This paper reviews the development of word vector technology from the perspective of technology development and then lead to the more advanced Bidirectional Encoder Representations from Transformers (BERT) model with great significance. On this basis, this paper fine-tunes the pre-trained Bert model. It applies the transfer learning strategy to analyzing the public sentiment of the occurrence of COVID-19 during the recent epidemic in Shanghai based on Sina Weibo data. In addition, tests are conducted to compare the model with the previous models. The experimental results show that the Bert model has significant advantages over the traditional model in character vector encoding and feature extraction.
Unveiling the potential of pre-processing and differentiable binarization thresholds for invoice text detection
Authors: Liang Feiran , Wu Yu , Yang Jialun
Published: September 2023

Invoice text detection aims to automatically identify key information in invoices, which is one of the representative applications of Optical Character Recognition (OCR) technology and a research hotspot in the computer vision community. The classic traditional OCR method consists of three key steps: preprocessing stage, text detection and text recognition. In the feature extraction stage, it faces problems such as insufficient generalization ability and poor robustness. In this paper, we reveal the great potential of preprocessing strategies in improving OCR accuracy, and propose an invoice text detection method based on DBNet and differentiable binarization thresholds. Specifically, we first introduce color segmentation and local adaptive threshold to improve the preprocessing process, which can effectively suppress the influence of background information and context noise on detection results. In addition, a differentiable binarization threshold is introduced in the feature extraction, which improves the error correction speed in the whole deep learning process. Studies have shown significant improvements in test results after color segmentation or background removal compared to the original image. Therefore, we propose to properly consider the text detection of invoices in the preprocessing stage for improvement.
Comparison study of data adaptability based on k-nearest neighbor(KNN), multilayer perceptron(MLP), and decision tree(DT)
Authors: Liu Yitong
Published: September 2023

In the current context of increasingly popular and developed human-computer interaction, machine learning (ML) and data mining are becoming more and more important in various areas, such as image detecting, medicine, and commercial companies. Different researchers from various fields have considered ways to improve the correctness rate for data mining. This paper used data sets from Kaggle and UCI machine learning repository, by applying k-nearest neighbor (KNN), multilayer perceptron (MLP), and decision tree (DT) classifiers to these data sets, the confusion matrix shows the result of the correctness rate for different classifiers under these data sets. As a result, the confusion matrices have shown that data adaptability is based on the data sets characteristics which rely on different classifiers specialties.
A comparison of multiple word embeddings and performance analysis
Authors: Wang Jinghua , Lin Zhongtian
Published: September 2023

Based on IMDB data sets for sentiment analysis, this research evaluates the performance of two types of neural networks, namely FNN and BERT. According to the experimental findings, both varieties of neural networks performed well (over 80%) on IMDB data sets. BERT performs the best of them all. The version of FNN improves when the number of layers is increased. The causes behind BERT's outstanding performance are then further examined in this research. In this article, it is hypothesized that a few factors, such as feature extraction capability and classification capability, account for BERT's exceptional performance. The results show that for the two coupling variables of BERT assumed in this paper, including feature extraction and classification ability, BERT has obvious advantages in feature extracting, and its classification ability has certain advantages over SVM and MLP. The deep learning model has achieved excellent performance in the sentiment classification task. The next step of this paper will focus on the robustness of the BERT model in sentiment analysis.
The estimation of spatial distribution patterns of different socio-economic status (SES) groups by housing advertisement data and machine learning techniques: a case study in brooklyn, new york
Authors: Yuan Wei
Published: September 2023

Poverty eradication has long been a central issue for sustainable development goals (SDGs), which draws attention to the issue of urban inequalities that can hinder regional economic development and increase unemployment and crime rates. It is critical to understand the local socio-economic distribution pattern for better urban policies and planning strategies. Traditional SES measurements are mainly based on census data and surveys, which are slowly updated and often fail to apply in the latest analysis. The SES inference methods using other data (e.g., satellite maps, nighttime lighting data) lack a theoretical basis and are of coarse resolution. The study takes advantage of the latest data (i.e., online housing advertisement data) and point of interests (POIs) to infer fine-grained block-group-level SES in Brooklyn through machine learning techniques. In addition, natural language processing (NLP) methods are used to derive twelve housing-related SES predictors. The results show that the speculative models and predictors are feasible, and the Global decision tree (GBDT) algorithm is the most efficient of the seven algorithms. The SES distribution map demonstrates a clear socio-economic stratification in Brooklyn. The rich are mainly concentrated in the western and northern areas with a high density of facilities. Based on the analysis of the local SES, three policy recommendations are proposed. First, for the inequitable distribution of facilities, additional investment should be made in the central and eastern regions. Second, a high level of greenery should be given priority in urban planning. Third, in terms of housing, disadvantaged groups should be given attention.
A channel attention and feature manipulation network for facial expression recognition
Authors: Guo Zixin , Yang Ruizhi
Published: September 2023

Facial expression conveys a variety of emotional and intentional message from human beings, and automated facial expression recognition (FER) has become an ongoing and promising research topic in the field of computer vision. However, the primary challenge of FER is learning to discriminate similar features among different emotion categories. In this paper, a hybrid architecture using Efficient Channel Attention (ECA) residual network ResNet-18, and feature manipulation network is proposed to tackle the above challenge. First, the ECA residual network effectively extract input features with local cross-channel interaction. Then, the feature decomposition network (FDN), feature reconstruction network (FRN) modules are added to decompose and aggregate latent features for enhancing the compactness of intra-category features and discrimination of inter-category features. Finally, an expression prediction network is connected to FRN to draw the final expression classification result. To examine the efficacy of the suggested approach, the model is trained independently using in-the-lab (CK+) and in-the-wild (RAF-DB) datasets. Several important evaluation metrics such as confusion matrix, Grad-CAM are reported, and the ablation study is conducted for demonstrating the efficacy and interpretability of the proposed network. It achieves the state-of-the-art accuracy compared to the existing facial recognition work, at 99.70% in CK+ and 89.17% in RAF-DB.
Video action recognition: A survey
Authors: Duan Qingqing
Published: September 2023

In recent years, as computer vision technology advances quickly, video action recognition has become a research hotspot. However, the field of video action recognition still faces many problems and challenges, such as the complex temporal dynamics of video data and the high computation cost caused by the explosive growth of video data. This paper summarizes the algorithms of video action recognition, and introduces them in two parts, namely, traditional handcrafted representation methods and deep learning representation methods. Among them, the traditional handcrafted representation methods are divided into two categories: Holistic Representation Methods and Local Representation Methods; The deep learning representation methods can be divided into RGB data based methods and Kinect-Based methods according to the type of input data modality. This paper focuses on the methods based on RGB data. This paper introduces the representative achievements according to different research directions, compares the advantages and disadvantages of various algorithms, and finally puts forward the prospect of the future development direction.
Sentimental analysis for clothing dataset
Authors: Ding Zhezhong , Du Zhuoheng , Yang Qingqi
Published: September 2023

In recent years, sentiment analysis has been applied to various fields, including politics, business, education, etc. Simultaneously, with the development of science and quality of life, clothes have become an increasingly important part of people's daily lives, especially women. In this research, using Natural Language Processing, we interpret a dataset about clothing by trying different approaches, which include other models (CNN, RNN, and LSTM), different optimizers (Adam, RMSProp, and SGD), and different hyper-parameters (Epochs, Batch Sizes, and Learning Rate). Then, we analyze the influences of those approaches by all kinds of valuation standards. Ultimately, we improve our accuracy by 8.0 %.
Masked face reconstruction and recognition through principle components analysis
Authors: Cui Chenxin
Published: September 2023

Due to the Covid-19 virus infecting humans since 2019, the traditional methods of face recognition are not suitable anymore, for the reason that lots of countries and regions request people to wear masks in public places, whereas the masks will add additional noise in the recognition process. To solve this problem, we suggest a new method named masked face recognition, whose principle is first converting the masked face image to an unmasked reconstruction image by applying Principle Components Analysis. We call it the Reconstruction Process; then using Convolutional Neural Network to exert face recognition on unmasked reconstruction images, we call it the Recognition Process. During the Reconstruction Process, we first detect the unmasked area, then linearly fit the unmasked area with Eigenfaces generated from the PCA process and a set of coefficients, which are the objectives we optimize. After the optimization, we are able to obtain the reconstruction image by the linear combination of the Eigenface with its corresponding coefficient. Experimental results clearly show the high effectiveness of our method, and the accuracy of being recognized correctly is increased from about 80% if we use the original masked images to 96.36% if we use the unmasked reconstruction images.
Security analysis in federated learning based on adversarial attacks
Authors: Jiang Haonan
Published: September 2023

Federated learning can fully use more data to improve the model's performance, but there will be a significant risk once the communication data (such as gradient information) is exposed. The risk of communication data leakage is unacceptable to users. When an attacker gets a little communication data from somewhere, the leaked communication data is a deadly poison. Attackers only need this communication data to launch destructive attacks and quickly break through the defensive line. This paper studies how to defend this risk to improve the security of federated learning through simulated attack experiments. For example, a random pruning strategy compresses the attack model (deep neural network). The purpose is to change the model's structure without affecting the model's performance as much as possible to make the structure of the proxy model (attacker) and the attacked model different to verify whether the strategy can improve the defense capability of the model. The experimental results show that the gradient-based attack method has good generalization. Even if the structure of the neural network model is modified in this paper, it still cannot resist the specific attacks brought by gradient exposure.