bluuebunny/crossref_metadata_2025 huggingface dataset:
Probing and deploying key wireless sensing technologies in the realm of 6G
Authors: Shi Yilong
Published: January 2024

In an effort to implement seamless, precise, and real-time wireless sensing within indoor environments, this paper delves into the principles and applications of sensing technology grounded in indoor wireless signals. The cornerstone of this study is the comprehensive understanding of wireless signal sensing which is intrinsically composed of four major stages. Initially, signal acquisition occurs, serving as the foundation for the entire process. Subsequently, data pre-processing refines these signals, ensuring the relevance and accuracy of the information for the upcoming stages. Thereafter, the methodical process of feature extraction takes place, which provides a nuanced understanding of the signal's key characteristics. This is vital in offering clear insights into the signal's inherent traits and potential implications. Finally, classification and identification occur. This stage sorts and labels the signals based on their unique attributes, allowing for an organized and efficient analysis. Furthermore, this paper extends to analyzing three distinct application scenarios that utilize this intelligent sensing technology. The first one entails behavior recognition, which could be instrumental in understanding and predicting human activity patterns within a specific space. Another application is in passive location identification, offering a non-intrusive means to track movements and locations within an indoor setting. By investigating these applications, we aim to provide a broad understanding of the potential of indoor wireless signal-based sensing technology, and to further its development and refinement for more diverse and efficient uses.
Diving into the virtual realm: Exploring the mechanics of virtual reality
Authors: Lai Zeyu
Published: January 2024

Virtual reality (VR) is a burgeoning technology that aspires to create an immersive digital experience for its users. This essay aims to explore how VR works by inspecting its hardware and software components, as well as the integration of both. The hardware components include the head-mounted display (HMD) with display screens, lenses, and motion tracking sensors for generating visual output and detecting head movements; Input devices, such as hand controllers, enable user interaction. The software components involve 3D computer graphics and rendering techniques, which allow the creation of virtual objects and environments. Real-time rendering ensures smooth and responsive visuals, while audio processing and sound simulation promote a realistic auditory experience. Integrating hardware and software components concerns real-time tracking and synchronization, recognizing and matching user movements with the virtual environment, and ensuring accurate interactions. Feedback mechanisms, especially haptic feedback like vibrations, enhance immersion. Understanding the workings of VR provides insights into its potential applications and its ability to transport users to virtual worlds.
Panoramic image stitching technology and its application in the field of autonomous driving
Authors: Wang Yahui
Published: January 2024

Image processing technology is an indispensable part of the development of many fields, in which panoramic image stitching technology is one of the most widely used technologies in image processing, which is not only applied in the frontier fields of technology such as unmanned aerial vehicles and machine vision detection, but is also closely related to people's lives, for example, the panoramic camera shooting function of the smart phone. The driverless car is also a widely concerned field, its development means the liberation of manpower, the realization and improvement of self-driving car technology can alleviate traffic congestion, the use of transportation for people without the ability to drive and many other social problems. This paper will firstly introduce the panoramic collage technology, including its principle, system architecture and application prospect. Secondly, it focuses on the application of panoramic collage technology in the field of self-driving cars, which is divided into two aspects: sensor hardware and collocation algorithm, and analyzes the applicability of different algorithmic techniques in this field based on the demand characteristics of self-driving cars. The research in this paper points out the optimization direction of panoramic collage technology required by self-driving cars, which will be of great value to the development and application of panoramic collage technology in the field of self-driving cars.
Deep learning-based glioma grading and feature visualization analysis
Authors: Chai Yunmeng , Wang Yuehan , Xue Wenqi
Published: January 2024

Gliomas can be separated into high- and low-grade gliomas according to the classification method developed by the World Health Organization (WHO). Glioma classification is significantly related to prognosis, and accurate glioma classification is very important. This study aims to evaluate and verify the analytical performance of different models based on deep learning for glioma grading. Firstly, the glioma grading clinical and mutation feature data sets were included. The training cohort included 20 genes with the most common mutations and 2 clinical features in the Cancer Genome Atlas Low Grade Glioma (TCGA-LGG) and TCGA- Glioblastoma Multiforme (GBM) glioma projects. Then, four pre-trained models are used to extract deep learning features from the data. Preprocessing is used to reduce redundancy and select the most predictive value. To assess the performance, indexes, including the area under the data working curve (AUC) and the accuracy prediction value, are leveraged. Finally, the prediction performance of the test queue is compared to determine the optimal classification model
Comparative analysis of machine learning techniques for cryptocurrency price prediction
Authors: Yu Siqi
Published: January 2024

The emergence of cryptocurrencies has revolutionized the concept of digital currencies and attracted significant attention from financial markets. Predicting the price dynamics of cryptocurrencies is crucial but challenging due to their highly volatile and non-linear nature. This study compares the performance of various models in predicting cryptocurrency prices using three datasets: Bitcoin (BTC), Litecoin (LTC), and Ethereum (ETH). The models analyzed include Moving Average (MA), Logistic Regression (LR), Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM). The objective is to uncover underlying patterns in cryptocurrency price movements and identify the most accurate and reliable approach for predicting future prices. Through the analysis, it could be observed that MA, LR, and ARIMA models struggle to capture the actual trend accurately. In contrast, LSTM and CNN-LSTM models demonstrate strong fit to the actual price trend, with CNN-LSTM exhibiting a higher level of granularity in its predictions. Results suggest that deep learning architectures, particularly CNN-LSTM, show promise in capturing the complex dynamics of cryptocurrency prices. These findings contribute to the development of improved methodologies for cryptocurrency price prediction.
Review of object tracking algorithms in computer vision based on deep learning
Authors: Luo Xiao
Published: January 2024

This paper is a survey of object tracking algorithms in computer vision based on deep learning. The author first introduces the importance and application of computer vision in the field of artificial intelligence, and describes the research background and definition of computer vision, and Outlines its broad role in fields such as autonomous driving. It then discusses various supporting techniques for computer vision, including correcting linear unit nonlinearities, overlap pooling, image recognition based on semi-naive Bayesian classification, human action recognition and tracking based on S-D model, and object tracking algorithms based on convolutional neural networks and particle filters. It also addresses computer vision challenges such as building deeper convolutional neural networks and handling large datasets. We discuss solutions to these challenges, including the use of activation functions, regularization, and data preprocessing, among others. Finally, we discuss the future directions of computer vision, such as deep learning, reinforcement learning, 3D vision and scene understanding. Overall, this paper highlights the importance of computer vision in artificial intelligence and its potential applications in various fields.
Utilizing stable diffusion and fine-tuning models in advertising production and logo creation: An application of text-to-image technology
Authors: Wang Chenyang
Published: January 2024

This article delves into the implementation of text-to-image technology, taking advantage of stable diffusion and fine-tuning models, in the realms of advertising production and logo design. The conventional methods of production often encounter difficulties concerning cost, time constraints, and the task of locating suitable imagery. The solution suggested herein offers a more efficient and cost-effective alternative, enabling the generation of superior images and logos. The applied methodology is built around stable diffusion techniques, which employ variational autoencoders alongside diffusion models, yielding images based on textual prompts. In addition, the process is further refined by the application of fine-tuning models and adaptation processes using a Low-Rank Adaptation approach, which enhances the image generation procedure significantly. The Stable Diffusion Web User Interface offers an intuitive platform for users to navigate through various modes and settings. This strategy not only simplifies the production processes, but also decreases resource requirements, while providing ample flexibility and versatility in terms of image and logo creation. Results clearly illustrate the efficacy of the technique in producing appealing advertisements and logos. However, it is important to note some practical considerations, such as the quality of the final output and limitations inherent in text generation. Despite these potential hurdles, the use of artificial intelligence-generated content presents vast potential for transforming the advertising sector and digital content creation as a whole.
Forecasting red wine quality: A comparative examination of machine learning approaches
Authors: Zhan Bohui
Published: January 2024

This research explores the forecast of red wine quality utilizing machine learning algorithms, with a particular emphasis on the impact of alcohol content, sulphates, total sulfur dioxide, and citric acid. The original dataset, comprised of Portuguese "Vinho Verde" red wine data from 2009, was bifurcated into binary classes to delineate low-quality (ratings 1-5) and high-quality (ratings 6-10) wines. A heatmap verified the potent correlation between the chosen variables and wine quality, paving the way for their inclusion in our analysis. Four machine learning techniques were employed: Logistic Regression, K-Nearest Neighbors (KNN), Decision Tree, and Naive Bayes. Each technique was trained and assessed through resulting metrics and graphical visualizations, with diverse proportions of data assigned for training and testing. Among these techniques, Logistic Regression achieved an accuracy score of 72.08%, while KNN slightly surpassed it with an accuracy rate of 74%. The Decision Tree technique rendered the peak accuracy of 74.7%, while Naive Bayes underperformed with a score of 60.2%. From a comparative viewpoint, the Decision Tree technique exhibited superior performance, positioning it as a viable instrument for future predictions of wine quality. The capacity to predict wine quality carries significant implications for wine production, marketing, customer satisfaction, and quality control. It enables the identification of factors contributing to high-quality wine, optimization of production processes, refinement of marketing strategies, enhancement of customer service, and potential early identification of substandard wines before reaching consumers, thereby safeguarding the brand reputation of wineries.
Exploring the application and performance of extended hamming code in IoT devices
Authors: Shen Liuxu
Published: January 2024

This study primarily focuses on the implementation of extended Hamming code within Internet of Things (IoT) devices and examines its impact on device performance, particularly in relation to communication protocols. The research begins by introducing and explaining the essential principles surrounding the extended Hamming code and its system. This introduction is followed by a detailed analysis of its practical application in IoT device communication and the subsequent influence on performance. Additionally, the study explores the potential role of extended Hamming code in strengthening the security measures of IoT devices. Experimental findings indicate that incorporating extended Hamming code can effectively enhance the communication efficiency of IoT devices, ensuring accurate data transmission. It also improves the overall operational efficiency of the devices and fortifies their security framework. Yet, despite these promising outcomes, the real-world application of extended Hamming code presents significant challenges. These hurdles highlight the need for continued research and exploration to maximize the potential of the extended Hamming code in the IoT domain. The study concludes with an optimistic outlook, encouraging ongoing investigation and innovation to further optimize the benefits of this code and drive advancements in IoT technology.
Research on feature coding theory and typical application analysis in machine learning algorithms
Authors: Wang Pengxiang , Xiao Kailiang , Zhou Lihao
Published: January 2024

Nowadays, the world is still in the environment of economic depression. In order to promote economic recovery, improve Relations of production and production efficiency, stimulate consumption expansion and upgrading, and accelerate industrial transformation and upgrading, problems such as industrial upgrading need to be solved urgently. Solving the above problems requires more useful tools, and artificial intelligence is one of them. Machine learning is the key to distinguishing artificial intelligence from ordinary program code. Unlike people learning knowledge, machine learning has its own unique language algorithms and behavioral logic. Machine learning, as a technology active in the field of artificial intelligence in recent years, specializes in studying how computers learn, simulate and realize part of human learning behavior, so as to provide data mining and behavior prediction for humans, to obtain new knowledge or skills, or to strengthen the original basic ability of machines. In this study, a variety of common coding algorithms and learning strategies in machine learning are discussed, supervised learning algorithms are selected as examples in the learning strategies, models are further selected and evaluated for a variety of algorithms, and parameters are adjusted and performance is analyzed. As for the theoretical analysis in the research, the paper makes a tentative application in the three fields of housing price, physical store sales and digital recognition, explores and selects the corresponding application method in the appropriate scenario, and expands the application field of machine learning.
Comparison of different algorithms in Reversi AI
Authors: Chen Xi
Published: January 2024

Minimax and alpha-beta pruning have been widely applied in AI for various strategic board games, the utilization of greedy algorithms in this context has received less attention. The Greedy algorithms aim to make locally optimal choices at each step, exploiting immediate gains. This research aims to reveal the potential benefits and limitations of applying greedy algorithms in Reversi gaming AI, specifically through a comparison with the Minimax algorithm. A series of AI versus AI matches were conducted to evaluate and compare the performance of the three different AI algorithms. The objective was to assess their gameplay strategies and decision-making abilities by measuring their average execution time and win rates. Relevant codes and experiments will be carried out in a C++ environment, and the shown codes in this article will only have pseudocode and comments. In conclusion, the findings of this study indicate that the Greedy Algorithm is not a superior alternative to the Minimax Algorithm in competitive scenarios, particularly with increased searching depth. However, greedy algorithms still have weak competitiveness with reduced computational time. For future research, concentrating on improving the performance of the Greedy Algorithm by incorporating more advanced heuristics or adaptive strategies maybe a good choice. Additionally, combining the strengths of both the Greedy Algorithm and the Minimax Algorithm could be a promising direction for further investigation.
Stochastic simulation methods in the study of cell rhythm
Authors: Xu Haiqing
Published: January 2024

Stochastic simulation methods play a crucial role in the study of cellular rhythms. Based on the characteristics of stochastic algorithms, we can more accurately capture the noise effects existing in biological systems and explore their impact on cell rhythms. The findings from stochastic simulation methods shed light on how cell rhythms operate at the molecular level, and this paper presents them inductively for different algorithm types, enabling a deeper understanding of their characteristics. Furthermore, based on the analysis of existing studies, this paper finds that a stochastic simulation approach that considers spatial heterogeneity and intercellular coupling helps reveal the design principles and functional characteristics of the cellular rhythmic system. However, existing stochastic methods also have limitations, including the arbitrariness of parameters and ignoring spatial features. This paper argues that future improvements should focus on integrating quantitative data, accounting for spatial effects, and increasing computational efficiency. These enhancements will contribute to a comprehensive understanding of the generation of cellular rhythms and their importance in biological processes.
Biosensors for ocean acidification detection
Authors: Guo Ziyi
Published: January 2024

Ocean acidification is a global environmental problem that significantly impacts Marine ecosystems and biodiversity. The traditional chemical analysis method has the problems of complex equipment and high cost in ocean acidification monitoring. In recent years, fluorescent protein biosensor technology, as an innovative monitoring method, has provided a new solution for the real-time detection of ocean acidification. Compared with traditional chemical analysis methods, fluorescent protein biosensors have the advantages of simple operation, high sensitivity and low cost. Current studies have demonstrated the potential of fluorescent protein biosensors for ocean acidification monitoring. The researchers designed a variety of fluorescent protein biosensors and conducted indoor and outdoor experimental validation. These results show that fluorescent protein biosensors can detect ocean acidification quickly and accurately and maintain stable performance under different environmental conditions. Further studies are needed to verify the consistency and reliability of fluorescent protein biosensors and traditional chemical analysis methods for ocean acidification monitoring. Future research directions include further improving the performance of the fluorescent protein biosensor, increasing its sensitivity and stability, and verifying its application in real Marine environments. This will help establish a better monitoring network for ocean acidification and provide a reliable scientific basis for Marine environmental protection and management decisions. The development and application of fluorescent protein biosensor technology will provide important support and guidance for us to better understand the impact of ocean acidification.
VGG16 based on dilated convolution for face recognition
Authors: Meng Fanxing
Published: January 2024

Face recognition has wide applications in fields such as security systems, biometrics, and human-computer interaction. However, traditional face recognition methods face challenges in capturing details and reducing model complexity. To address these issues, this paper proposes a new method based on VGG16, which improves recognition accuracy and reduces parameter quantity by introducing dilated convolution and parameter pruning. First, the hole convolution is introduced to expand the Receptive field and capture more details to enhance the ability of the model in distinguishing facial features. Next, parameter pruning is applied to reduce redundant parameters, optimize model structure, and improve computational efficiency. This article conducted experimental evaluation on the classic face recognition dataset CK+ dataset. The results show that the proposed method is significantly superior to the traditional VGG16 model in terms of recognition accuracy. At the same time, the use of pruning technology significantly reduces the number of parameters in the model and improves computational efficiency. The experimental outcomes conclusively validate the effectiveness and feasibility of the proposed method.
Research on image classification leveraging deep convolutional neural networks and visual cognition
Authors: Liu Chen
Published: January 2024

The field of image classification has experienced remarkable improvements with the advent of deep learning techniques, especially Deep Convolutional Neural Networks. The present study provides an extensive exploration of the junction where image classification based on Deep Convolutional Neural Networks meets human visual cognition. Utilizing the inherent ability of these networks to automatically learn hierarchical features from raw pixel data, this research examines their potential in classifying images from diverse complex datasets, emphasizing predominantly on the extensively utilized ImageNet dataset. The initial aspect of this study involves training and evaluating models based on Deep Convolutional Neural Networks on the ImageNet dataset, which comprises millions of labeled images spanning across thousands of categories. Well-established network architectures such as AlexNet, VGGNet, GoogLeNet, and ResNet are employed, and their performance in the challenging task of image classification is assessed. Rigorous experiments highlight the strengths and weaknesses of each model while emphasizing the prospects of transfer learning and fine-tuning. Following this, the interpretability of Deep Convolutional Neural Networks is explored by using visualization techniques to comprehend the learned feature representations. By visualizing activation maps and class-specific saliency maps, valuable insights are gained into the regions of interest that guide the decision-making of these models. Moreover, the correlation between the features extracted by these models and human visual attention mechanisms is examined to shed light on the focus of attention of the models. The study also addresses the difficulties that adversarial attacks, data bias, and generalization capabilities present to Deep Convolutional Neural Networks. Strategies to enhance the robustness and adaptability of the models across various domains are examined, linking these observations to human cognitive behavior.
Advancements in robotics engineering: Transforming industries and society
Authors: Bai Zuheng
Published: January 2024

Robotics engineering is a dynamic and multidisciplinary field that has undergone rapid evolution in recent years, transforming various aspects of our lives. This paper serves as a comprehensive exploration of robotics engineering, delving into its historical development, contemporary applications, and the exciting prospects that lie ahead. The history of robotics engineering is a fascinating journey, from the early automata and industrial robots to the cutting-edge autonomous systems and humanoid robots of today. It traces the evolution of technology and human ingenuity, showcasing how robotics has become an integral part of our modern world. Current applications of robotics engineering span a wide range of industries, from the manufacturing sector, where robots enhance efficiency and precision, to healthcare, where they assist in surgery and patient care. Furthermore, robots are venturing into hazardous environments, disaster response, and space exploration, expanding their utility. However, as robotics technology continues to advance, it raises ethical and societal questions. This paper will explore these concerns, such as the impact on employment, privacy, and human-robot interaction, emphasizing the importance of responsible development and use of robotic systems. In conclusion, robotics engineering is a transformative force, shaping industries and influencing society in profound ways. This paper seeks to shed light on its pivotal role in our world, inspiring discussions and responsible practices that ensure its positive impact on the future.
Data analysis with different variables and credit risk assessment
Authors: Jin Ruixin , Zhou Huanyu
Published: January 2024

Nowadays, credit payment is a very common way to pay, such as credit cards, loans, many people can use their credit as a guarantee to borrow money from the bank, however some people will default. So we have to predict whether the borrower will pay on time, it is known as credit risk assessment. In this paper, we analyze a data set on credit risk to predict whether individuals will be late on their payments, helping financial firms improve their earnings and reduce their losses. We not only made predictions on the data, but also analyzed the relationship between the variables that affect the overdue probability to find some specific associations. Specifically, we performed ANOVA analysis and found that married people borrowed significantly more than other groups, and the delinquency rate of people with higher education was lower, and the delinquency rate of married people was higher than that of unmarried people. In addition, we conducted a binary logistic regression and found that gender had no significant impact on the prediction results, but an individuals amount of bill statement, amount of previous payment, past repayment situation and Amount of the given credit had an impact on the prediction results. Other variables, such as marital status and education, can also impact the predicted results. Our research puts forward more factors affecting credit risk and also different angles that can be used to analyzes individual credit risk. This has a guiding role for financial firms like banks and other companies in the financial industry, providing more ways to help them analyze the credit risk of borrowers.
A New and Efficient Pan Sharpening Method Based on Optimized Pixel Coefficients
Authors: Çağlıkantar Tuba , Kılıç Melih Can
Published: January 2024

Pan sharpening aims to create a multispectral, high spatial resolution image by combining the multispectral image (MSI) with a high spatial resolution panchromatic image (PAN). Pan sharpening methods are performed between the MS image, which is the MSI image brought to PAN dimensions with the help of interpolation, and the PAN image. In this study, PAN sharpening is approached as an optimization problem. It is assumed that the optimal solution consists of multiplying the pixels of the MS image by optimized coefficients. It would be costly to optimize all the coefficients in this coefficient matrix one by one. For this reason, these coefficients were tried to be found with 5 different optimizationbased methods. It was also compared with 19 different methods commonly used in the literature. 6 different evaluation criteria were used for this comparison. These comparisons were made on 3 different datasets. It has been observed that the proposed methods are superior to other methods.
Role of herbs and spices in prevention and treatment of chronic diseases
Authors: Mukhopadhyay Swagata , Roy Chandana , Ghosh Pratiti
Published: January 2024

Lifestyle diseases are of growing concern and lead to reduced life span. The current therapies for treatment of life-threatening diseases have many undesirable side effects. Therefore, identification of safer and more effective treatment options for diseases is needed in modern drug discovery. Herbs and spices play pivotal role in the prevention and treatment of several diseases. This review thus focuses on such naturals in combating common diseases such as cancer, diabetes, arthritis, cardiovascular diseases, tuberculosis, malaria, liver disorders, kidney problems, asthma, etc. It focuses on 200 medicinal plants and 2258 bioactive components with potent therapeutic activities, highlighting their phytochemistry and pharmacognosy. All the plants exhibit pharmacological potency against prevalent ailment, necessitating further studies on mechanism of action of their bioactive compounds.
Emerging Potentials of Oral Gold Therapeutics (Swarna Prashana ) For Pediatric Age in Post COVID Era
Authors: Verma Piyush , Pathak Ashutosh
Published: January 2024

Objective- To review the potential benefits of Swarna / Swarnaprashana (a kind of gold therapeutics) in pediatric age for infectious diseases.
Data Source- various published researches has been reviewed.
Review Methods- qualitative analysis of the themes of the researches done previously was done and potential benefits and future prospects and idea was generated.
Results- Swarna (gold) nanoparticles has proven virucidal effect.
Conclusion- The use of Swarna in Indian system of medicine is from very ancient times. This sacred element had very broad use since it was incorporated in human civilizations. Today we are facing the covid-19 pandemic with such a disastrous effect on public health. This era has shown the mankind that whatever be the understanding and developments of modern medical system for infectious diseases, the microbe world is always a step ahead of us and modifying itself. The ancient use of Swarna as swarnaprashana in children has better chances of improving the immunity and fighting certain viral infections.
Cumhuriyet Öncesi ve Sonrası Arkeolojiye Genel Bir Bakış
Authors: USLU AZARAK Laleş
Published: January 2024

“Geçmişin tanığı” olarak adlandırabileceğimiz arkeoloji kültürlerin maddi kalıntılarını inceleyerek, geçmiş yaşantılarını gözler önüne sermeyi amaçlamakta, onların sosyolojilerini, felsefelerini, inanç ve ritüellerini, diğer kültürlerle ilişkilerini incelemektedir. Arkeoloji aynı zamanda tarih, antropoloji, etnografya, sosyoloji ve daha birçok bilimsel alanla işbirliği kurarak bulguları yorumlama çabasındadır. Geçmişi aydınlatmayı amaçlayan bu bilim dalı, ilk başlarda kültürlerin ulus olma bilincini geliştirme ve ulusların kökenlerinin çok eskiye dayandığını kanıtlamaya çalışan bir disiplin olarak ortaya çıkmış, sonraları daha evrensel bir ivme kazanmıştır. Kökleri derinlerde olan halkların varlıklarını sürdürme çabaları da ancak arkeolojik kalıntılarda ve sanat eserlerinde kendini göstermektedir. Geçmişe duyulan merak, arkeolojik eserleri popüler hale getirmiş; bu durum yabancı gezgin, maceracı ve oryantalistlerin kültürel miras açısından zengin olan Osmanlı topraklarındaki tarihi eserlere ilgi duymalarına neden olmuştur. 19. yüzyılın sonlarında Osmanlı İmparatorluğu topraklarında yer alan Anadolu yabancı bilim insanlarının ilgisini çekmiştir. Osmanlı topraklarında yapılan kazılar, bu topraklardan adeta tarih fışkırdığını kanıtlar niteliktedir. Gerek izinli gerek izinsiz bir şekilde yapılan birçok kazıda ortaya çıkarılan eserlerin bazıları Avrupa’daki müzelerde sergilenmektedir. Çalışmada cumhuriyet öncesi ve sonrası yapılan arkeolojik çalışmalara genel olarak değinilmiştir. Tarihi eser ve kültür varlıkları açısından son derce zengin olan bu coğrafyada çok sayıda bilimsel araştırma ve kazı yapıldığından dolayı konu sınırlandırılması yapılmıştır.
Pregnancy and gingival considerations: A review
Authors:   Department of Periodontology and Oral Implantology, Rishiraj College of Dental Science and Research Centre, Bhopal, India, Bharadwaj Pooja
Published: January 2024

Pregnancy is one of the wonderful period in the life of a woman. During this period, a woman goes through various moments of happiness and sorrow and these moments are reflected systemically in her body. One of the utmost concerns about pregnancy is that apart from systemic changes, many women go through a period of oral cavity changes and these changes become much more pronounced in pregnancy. This article reviews what oral changes a woman goes through her pregnancy and how she can handle these oral changes with care.
A case report of posterior reversible encephalopathy syndrome in a patient diagnosed with emphysematous necrotizing biliary pancreatitis
Authors:   Specialist Physician Department of Internal Medicine, Kuwait Hospital Sharjah, Sharjah, United Arab Emirates, Ahmad Maryam Nazir , Damodaran Anandi ,   Consultant Neurologist Department of Internal Medicine, Kuwait Hospital Sharjah, Sharjah, United Arab Emirates, Iftikhar Sarah Muhammad ,   General Practitioner Department of Internal Medicine, Kuwait Hospital Sharjah, Sharjah, United Arab Emirates, Kotekar Devdutt Nayak ,   Consultant Neurologist Department of Internal Medicine, Kuwait Hospital Sharjah, Sharjah, United Arab Emirates
Published: January 2024

Posterior reversible encephalopathy syndrome (PRES), a clinical radiological syndrome, is characterized by the abrupt development of neurological symptoms such as headaches, convulsions, altered sensorium, and visual problems. PRES has been linked to a number of risk factors or etiologies, including the use of immunosuppressants or cytotoxins, hypertensive encephalopathy, eclampsia, preeclampsia, and underlying autoimmune diseases. A 41-year-old female was admitted with acute necrotizing emphysematous pancreatitis complicated by posterior reversible encephalopathy syndrome. She remained normotensive on presentation and during the hospital stay. All her investigations were within normal except double-stranded DNA, which came positive. This could explain the immune-mediated mechanism leading to endothelial dysfunction. This case has been presented for its rarity. When acute neurological abnormalities occur in the context of systemic inflammatory conditions, such as acute pancreatitis, it is crucial to take PRES into account.
Análise da percepção e uso de cigarro eletrônico entre acadêmicos de Medicina
Authors: Gomes Nícolas Louzada Borchardt , Neto Benjamim Alves Pessoa , Silva Kaio Klaywer Sousa Da , Marques Rossana Vanessa Dantas De Almeida
Published: January 2024

A pesquisa visa elucidar o perfil sociodemográfico do público efetivamente usuário de cigarro eletrônico entre os estudantes do curso de medicina, em Imperatriz-MA. Trata-se de um estudo quantitativo, observacional e transversal, realizado no primeiro trimestre de 2022. Participaram da pesquisa 113 estudantes, dos quais 50 pertenciam ao sexo masculino e 63 ao sexo feminino, com idade média de 20,5 anos (±2,09). 34% das pessoas que já fumaram CE têm renda média de 8 salários-mínimos, obtendo-se um p-valor de 0,021. Constatou-se que estudantes que possuíam pais com ensino médio ou ensino superior representavam 81% do total de pessoas que já fumaram CE. Além disso, notou-se maior prevalência de uso do CE na população masculina. Frente a um perfil tão delimitado, ações legislativas e educacionais fazem-se necessárias para impedir o alastramento destes dispositivos na sociedade, em especial entre os estudantes.
PENGARUH ENVIRONMENTAL AWARENESS. GREEN PRODUCT, DAN GREEN PROMOTION TERHADAP KEPUTUSAN PEMBELIAN PRODUK BIO2000 FORMULA KURAS WC STUDI KASUS KONSUMEN DI SURAKARTA
Authors: Salsabilla Nur Azzahra
Published: January 2024

Penelitian ini bertujuan untuk menganalisis pengaruh Environmental Awareness, Green Product, dan Green Promotion terhadap Keputusan Pembelian produk BIO2000 FORMULA KURAS WC di Surakarta. Sampel dalam penelitian ini adalah 100 Responden yang merupakan konsumen dari produk BIO2000 FORMULA KURAS WC yang sudah pernah melakukan pembelian produk sebanyak 1 pcs. Dengan menggunakan Teknik Pengumpulan data yang digunakan adalah metode Survei dengan instrument penelitian yang digunakan adalah Kuisioner. Hasil Uji Intrumen menyatakan bahwa data dalam penelitian ini terbukti valid dan reliabel. Pada Uji Asumsi Klasik dinyatakan bahwa data dalam penelitian ini terdistribusi secara normal dan menghasilkan model regresi yang bebas dari multikolinearitas, dan heteroskedastisitas. Hasil Penelitian ini membuktikan bahwa : (1) Environmental Awareness berpengaruh signifikan secara positif terhadap Keputusan Pembelian Produk BIO2000 FORMULA KURAS WC di Surakarta, (2) Green Product berpengaruh signifikan secara positif terhadap Keputusan Pembelian Produk BIO2000 FORMULA KURAS WC di Surakarta (3) Green Promotion Tidak memiliki pengaruh terhadap Keputusan Pembelian Produk BIO2000 FORMULA KURAS WC di Surakarta,Hasil ini membawa implikasi bagi peneliti selanjutnya untuk mengkaji perilaku konsumen pada beragam produk kebersihan sanitasi yang ramah lingkung. Temuan penelitian ini membawa impliaksi bagi produsen produk ramah lingkungan untuk merumuskan strategi Green Promotion pada konsumen agar mampu mempengaruhi keputusan pembelian konsumen.
The Effect of Emotional Intelligence Skills on Leaders’ Performance: An Empirical Study Applied on Egyptian Public Universities
Authors: Zaghamero Nashwa Aly
Published: January 2024

This study is conducted to determine the effects of emotional intelligence on leaders’ performance within Egyptian universities. The concepts of emotional intelligence and employee engagement have received significant attention in both academic and business fields in the recent years. Much of the attention has been focused on the relationship between the leaders’ performance and organizational results. The attention has not come without controversy related to many aspects of each concept. The debate continues amongst researchers of how to define and measure emotional intelligence, and whether emotional intelligence is a new type of intelligence or simply another way of assessing personality characteristics. The research examines the role that emotional intelligence plays in leaders’ performance at the Egyptian universities. The goal is to draw conclusions about the effect of emotional intelligence on leaders’ performance among leaders’ candidates, and offer relevant recommendations for selecting, training, developing, and evaluating leaders. 
The research sample includes the university leaders, as higher education is so important in Egypt. It reveals importance of education in enhancing the competitiveness and economic development. It will help developing the knowledge economy, which will in turn create a demand for higher skill levels in most occupations. A new range of competences such as adaptability, team work, communication skills and motivation for continual learning has become critical. 
The public Egyptian universities have been chosen to be the research society because of being an important sector, which has an impact on other productive and service sectors. All sectors are affected by education policies; it is the environment which affects the mechanism of all other sectors. In short, the success or failure of the leadership process within any sector would directly affect the success of business in other sector.
A Study Cultural Policy for Strengthening Cultural Urban Competitiveness
Authors:   The Korean Society of Human and Nature, Lee Han Su , Kim Se Jin , Park Jeong Bae
Published: January 2024

This study focused on examining recent trends and solutions for urban revitalization through cultural means, responding to the heightened concerns and growing interests of many cities in augmenting the value and competitiveness of city. Accordingly,a case study of the Gongju Cultural City Center was conducted as a model to address the enhancement of urban competitiveness through cultural means, focusing on aspects such as facility expansion, population growth, and the activation of economic activities from a problem-solving perspective. Gongju City was designated as a cultural city by the Ministry of Culture, Sports, and Tourism(2021). Leveraging preliminary investigations and specialized textual studies, it has spearheaded specific projects focusing on future cultural heritage domains. As a core project, efforts were made to enhance the competitiveness of the region and the city through initiatives such as the Gongju Art Shop Street and the Gallery Weekly Project. Analytical results revealed significant achievements across all aspects related to urban competitiveness, including the expansion of cultural facilities, population growth and development, and the activation of economic activities. To enhance the role and sustainability of the Cultural City Center, it is considered essential to facilitate diverse collaboration among various stakeholders and engage in multifaceted consultations with administrative bodies from the planning to the execution stages of a broader spectrum of initiatives. This study is considered valuable not only for establishing theoretical frameworks but also as foundational data that can be utilized in the field for deriving future directions and advancements in the Cultural City project.
Types and Success of Language Communication
Authors:   The Korean Society of Human and Nature, Yang KyongMi
Published: January 2024

This article starts from the types of language communication and combines research methods from multimodal corpus linguistics and related theories from counseling psychology to introduce several types of communication that occur in daily life and explain the process by which discourse leads to success and failure. It was an observational analysis.
Eight types of language data were collected, including face-to-face voice communication between family members, untact text communication, text communication between Korean and Chinese friends, and untact voice communication for solving problems in daily life. The communication language is mostly Korean, but sometimes Chinese.
Linguistic materials were analyzed from the perspectives of the purpose of communication, communication space, relationships between participants, type of communication medium, and double messages.
Problems and Improvement Direction of PSAT(Public Service Aptitude Test)
Authors:   The Korean Society of Human and Nature, CHOI SU-JEONG
Published: January 2024

PSAT(Public Service Aptitude Test)), introduced in 2004, is an evaluation system that measures comprehensive thinking skills that can be acquired through normal school education to test the qualities and abilities necessary to perform public office. Rather than knowing against the changing times, the purpose of “problem-solving” is to solve real problems and achieve results in work for the purpose of recruiting talented people with the aptitude and competence required by the organization.
However, more than 20 years later, questions are being raised as to whether the test faithfully fulfilled the purpose of selecting talented people with practical skills.
First of all, it is necessary to reconsider the specificity and expertise of public officials because PSAT(Public Service Aptitude Test) is a public office qualification evaluation, and to reexamine whether there is a correlation with the core competencies of public officials in selecting talented people suitable for public office in the public office recruitment examination.
To this end, public officials have some characteristics unlike other occupations, some administrative differences from other countries, and PSAT (Public Service Aptitude Test) in Korea has identified its advantages and disadvantages compared to similar tests.
As a result, PSAT is currently achieving great results in terms of efficiency in evaluating civil service qualifications, but it still has the problems that were initially presented. Internally, passages and questions tend to be repeated or recycled with other tests, and externally, the lack of connection between the first and second tests and lack of connection with actual administrative work were identified as the biggest problems. The solution is to change the test time and passages compared to the College Scholastic Ability Test (CSAT), LEET (legal Education Eligibility test)) or NCS (National Competency Standards), diversify the test sources, and link it with actual work. It suggests ways to do so.
Sifat Kimia, Fisika dan Organoleptik Selai Kulit Buah Nanas
Authors: Nanda Wahyu Mega , Widyowanti Reni Astuti , Partha Ida Bagus Banyuro
Published: January 2024

Jam is a semi-solid food product made from a mixture of sugar and fruit. In this study, pineapple peel waste was used as the main ingredient for making jam because the use of pineapple peels is still unknown to the general public. The purpose of this study was to see the effect of adding sugar and natural citric acid on the chemical, physical and organoleptic properties of pineapple peel jam. The experimental design used the Randomized Complete Block Design (RCDB) method with 2 factors, namely the addition of sugar and the addition of natural citric acid from lime, lemon and lime with 2x repetition. The test parameters used were water content, pH, vitamin C, flavonoids, anthocyanin, and organoleptic including taste, aroma, color, and spreadability. The results showed that the addition of sugar had an effect on the test for water content, pH, vitamin C, flavonoids, and viscosity. The addition of citric acid had an effect on the water content, pH, vitamin C, flavonoids, viscosity, and anthocyanin tests. For the organoleptic test of pineapple rind jam the panelists were most interested in were the samples treated with the addition of 50% sugar and the addition of natural citric acid from lime (K3G3) with a moderately favorable score (5.01).
Web-Based Land and Building Tax Records Information System
Authors: Yuniarti Yuniarti , Utami Alia Tri , F Ganjar Nurul , Suwarno Adi
Published: January 2024

The property tax registration process in One of The Regions in Bandung is carried out manually, resulting in the reliance on books and archiving in cabinets for information registration. The PBB registration process also includes inputting and reporting information through personal calls made via social media chat. This process especially demands citizens to physically visit the village without possessing an official letter when they receive a call. The absence of written proof when contacting the inhabitants causes them to feel anxious and uncertain, resulting in physical fatigue for the village staff. The Property Tax registration information system can oversee the data recording process for all system users (administrators, operators, visitors), including data recording, biodata recording, village services, and calling operations. Furthermore, residents can access and examine this information system via the Internet, enabling efficient monitoring and viewing of relevant data.