bluuebunny/crossref_metadata_2025 huggingface dataset:
Epidemiological profile of migraine admissions at the Brazilian Unified Health System (SUS) between 2012 and 2022: a decade of pain.
Authors: Carneiro Leandro Gouveia , Cuchera Ana Paula , Andreo Lucas
Published: July 2023

Introduction: Migraine is a type of headache characterized by a pulsating pain or sensation, and the pathophysiology is still not fully understood. There are two types of migraines, with aura and without aura, the latter being the most frequent. World Health Organization data suggest that, globally, the estimated prevalence of any type of headache among adults can reach up to 50%, being the sixth highest worldwide cause of years lost due to disability. In Brazil, about 15.8% of the population suffers from migraine. Studies are needed to draw more attention to this disease that causes much morbidity and disabling. Objectives: The aim of this study is to analyze the epidemiology of migraine admissions at the Brazilian Unified Health System (SUS) from 2012 to 2022. Methods: This is a descriptive epidemiological study, in which migraine admissions data was collected using the SUS Hospital Information System database (DATASUS/TABNET), from 2012 to 2022, by region, using the term “Enxaqueca e outras síndromes de algias cefálicos”. Literature review was conducted using PubMed and SciELO databases. Statistical analysis was performed with Kolmogorov-Smirnov and analysis of variance/Tukey tests, using the PRISM software. Results: From 2012 and 2022, Brazil had 96,857 migraine admissions. The most prevalent region is the southeast of Brazil with 33,487 admissions (P < 0.05 when compared to north and midwest). The least prevalent region is the midwest, totalling 5,026 admissions. The year with most recorded migraines were 2019, with a total of 11,996 admissions, and 2012 the least prevalent, with 5,908 admissions. Of all admissions, 65% occurred in women, being the most prevalent age group from 30 to 39 years old. Conclusion: We observed an increase in hospital admissions by migraines in the last decade, particularly between women and in the southeast region of Brazil.
Analgesic potentiation in post-traumatic occipital neuralgia, a case report
Authors: Rios Pedro Gabriel Marcomini , Silva Heloisa Queiroz Carneiro da , Massari Felipe Adolfo Kuriyama , Martins Marina Ferreira , Fernandes Matheus Assunção Souza
Published: July 2023

Context: Occipital neuralgia is characterized as uni or bilateral pain in the topography of the occipital nerve. The condition may be harrowing or acute and worsens with digital pressure on the back of the neck. The pain appears in the distribution of the greater (GON), minor (LON), and third (TON) occipital nerves. Besides that, it may radiate to the retro-orbital region and angle of the mandible, and it can be associated with paresthesias. A less common cause is direct head trauma, and it is believed that the mechanism for its development is the injury or entrapment of the nerve fibers due to post-traumatic fibrosis. The conservative treatment consists of antiepileptics, tricyclic antidepressants, or antipsychotics. In addition, it includes anesthetic blockade of the GON, LON, and TON guided by ultrasonography of the skull, which is an essential option for treatment and identifies the presence of entrapment of the quoted structures. We present the case of a 37-year-old man, a victim of physical aggression with traumatic brain injury, without previous comorbidities or use of daily medications, who developed occipital neuralgia after the event. Cranial computed tomography showed occipital depression in the topography of the GON. Due to the absence of neurological alterations, the medical team chose conservative treatment with phenytoin. As the pain persisted, the professionals performed a hydro section and suboccipital block with anesthesia, resulting in improvements.
Optimization of the extraction of bioactive compounds from Pouzolzia zeylanica using Box-Behnken experimental design and application in the preparation of mixed juice
Authors: THUY Nguyen Minh , THANH Nguyen Van , VY Vo Ngoc Tuong , GIAU Tran Ngoc , TIEN Vo Quoc , TAI Ngo Van , MINH Vo Quang
Published: July 2023

Pouzolzia zeylanica grows naturally in the forest and is quite popular in Vietnam. This study was designed to investigate the influence of extraction parameters and their effective application in the processing of mixed fruit juice from P. zeylanica and orange juice. A three-factor [i.e., solvent ratio and material (5:1–6:1), extraction temperature (85–95 °C), and extraction time (10–15)] and three-level Box-Behnken design consisting of 18 experimental runs with 6 center points was used for the extraction of P. zeylanica. The optimal conditions (maximum extraction yield) based on both individual and combinations of all responses (ratio of water: materials is 5.4:1 v/w, extraction temperature 91 °C, and time 13 min) were found. At these optimum conditions, the TAC and TPC were found to be 13.55 mg/L and 88.26 mgGAE/L with a desirability value of 0.91. The experimental values are in close agreement with the corresponding predicted values (R2=0.942). In addition, by adding orange juice as a natural ingredient that provides additional vitamin C, this study attempted to improve the mixed juice product quality and increase antioxidant capacity and organoleptic value. The mixed juice with the ratio of P. zeylanica extract and orange juice of 80% and 20%, respectively, for a product with high TPC and TAC contents (240.61 mgGAE/L and 10.84 mg/L), significantly improved vitamin C content (255.96 mg/L) and antioxidant activity (67.55% DPPH).
Effect of age and sexual condition on the fatty acid profile of intramuscular fat of cattle finished in feedlot
Authors: CARRILHO Charles de Oliveira , KUSS Fernando , MOLETTA José Luiz , MENEZES Luís Fernando Glasenapp de
Published: July 2023

The objective of this study was to evaluate the fatty acid (FA) profile of intramuscular fat of cattle of two categories (16 or 26 months old) and two sexual conditions (Bulls or Steers) finished in feedlot. A total of 32 castrated (n=16) or noncastrated (n=16) animals of the genetic groups ½Purunã + ½Canchim were used. The animals were finished in feedlot, receiving a diet with 50% roughage and 50% concentrated feed. After the slaughter, one Longissimus dorsi sample from each animal was sent to the laboratory for FA profile analyses. The FA content of C17:0 iso and C18:0 was higher for animals slaughtered at 26 months. Lignoceric acid (C24:0) showed a higher content for animals aged 16 months. Animals slaughtered at 16 months showed higher C18:1 cis 11, C18:1 cis 12, C18:1 cis 15, and lower C18:1 trans 16 than those slaughtered at 26 months. The C20:4 and C22:5 were lower as the animals' slaughter age increased. The unsaturated/saturated and polyunsaturated/saturated ratios showed no difference for slaughter age. The concentrations of C24:0, C18:1 trans 10, C18:1 cis 11, C18:1 cis 12, and C22:1 were greater in the meat of bulls than in steers. Bulls had a higher content of polyunsaturated FAs and polyunsaturated/saturated ratio than steers.
Intelligence support for the operational level counter-deception
Authors: Stanciu Cristian-Octavian , TOROI George-Ion
Published: July 2023

Given modern warfare’s complex and dynamic nature, military deception has become a vital tool in the contemporary operating environment for gaining strategic advantage and achieving operational success. For this reason, countering enemy deception operations has become an operational requirement to support mission accomplishment. Furthermore, with the increased use of modern technologies and information warfare tactics by adversaries, intelligence has become a critical asset in countering enemy deception operations and protecting the safety and security of military personnel and operations. The Russian-Ukrainian ongoing war has proven once again that deception remains a viable tool in the contemporary operating environment and can still have a huge impact on the battlefield. Considering its value, this article explores approaches to diminish and counter the impact of deception at the operational level of war. Moreover, our research explores how the joint function of intelligence can support the efforts of counter-deception throughout its entire process.
FACTORS INFLUENCE THE DECISION OF RUBBER FARMERS IN TAKING KUR IN LUBUK RAJA DISTRICT OKU REGENCY
Authors: Citra Devi Saputri  , Yetty Oktarina  , Fifian Fifian Permata Sari
Published: July 2023

Capital is needed to procure production facilities (seeds, fertilizers, pesticides and equipment), plant maintenance costs, storage, marketing and transportation costs. In rubber farming, a lack of capital causes a lack of input, which raises the risk of failure or low productivity. KUR is MSME credit/financing in the form of working capital and investment supported by guarantee facilities for productive businesses whose distribution is through banks but the source of funds comes entirely from government bank funds with a ceiling of up to IDR 25 million per debtor. This farm credit facility is felt to have helped farmers in carrying out agricultural production activities better in order to achieve higher farmer income. This study examines the factors that influence rubber farmers in taking people's business credit (KUR) to help farmers' capital. The research was carried out deliberately in Lubuk Raja OKU District as a rubber center where many farmers took KUR for capital. The research method used is the survey method and the sampling method uses a simple random method using the slovin formula. The number of samples taken were 83 farmers from 482 farmers. Data analysis using logistic regression. The results of the analysis show that the variables of total family income (X1), land area (X2), production costs (X3) and price (X4) have a significant effect on rubber farmers' decisions in borrowing KUR funds at Bank BRI. Meanwhile, the land ownership status variable (X5) has no significant effect on rubber farmers' decisions in borrowing BRI Bank KUR funds in Lubuk Raja District, OKU Regency.
THE ROLES OF TEACHERS AND SCHOOLS IN CONDUCTING EFFECTIVE CLASSROOM ASSESSMENT
Authors: I Nyoman Suwandi
Published: July 2023

Assessment is one of the activities carried out to measure and assess the level of achievement of the curriculum and the success or failure of the learning process. The principles and strategies of the classroom assessment are used to guide how teachers always carry out intensive assessments of their students to find out their students' progress. This research examined the role of teachers and schools in implementing classroom assessments. This research method is a qualitative method where the data were analysed descriptively. Data required for this study were collected through interviews and field observations. This study found that teachers and schools have an essential role in implementing the assessment. The active role of teachers and schools in carrying out class assessments improve the quality of learning so that students' abilities can always increase. This research has implications that teachers and schools must increase their role in implementing class assessments so that schools can produce higher-quality graduates
Human Ecology: proposed requirements for academic research
Authors: Estevam Anilton da Silva , Azevedo Sérgio Luiz Malta de Azevedo , Almeida Maria do Socorro Pereira de
Published: July 2023

This research aims to propose requirements that will characterize research in Human Ecology (HE) in Brazil. As a methodological proposal, a bibliographic review on the subject was used, using the contributions of national and international authors, which allowed the analysis of information through the construction of articulation links. To this end, the pillars proposed by Bomfim were established as requirements to be analyzed: Interface/interchange nature-human being, that is, culture-environment; interdisciplinarity; systemic conception of the real; human emancipation. The discussion about the analyzed pillars stands out in the research and which may constitute a reference for the research carried out. Thus, this article contributes to the discussion on the theme of the epistemology of Human Ecology in Brazil.
Screening of eating disorders among adolescents
Authors: Malik Madeeha , Arshad Aqdas , Hussain Azhar , Hashmi Ayisha
Published: July 2023

The objective of the present study was to screen adolescencts for eating disorders and anxiety in Pakistan. Methodology: A sample of 382 adolescent respondents was selected from high schools located in twin cities (Rawalpindi and Islamabad) of Punjab Pakistan and Mirpur. Four pre-validated data collection tools i.e. Sick Control One Fat Food questionnaire, Eating Disorder Examination Questionnaire, Clinical impairment assessment and state trait anxiety inventory were used for screening of eating disorders and anxiety among conveniently selected adolescents. All the data was coded, entered and analyzed using SPSS 21. The results of the current study showed that among adolescent respondents the prevalence of Eating Disorders was 57.6 % (n=220) after screening. ED was more common among early aged adolescents, of 13 years 30% (n=15) and 14 years 26% (n=13) age. Females were more prone to ED 80% (n=40), than males 20% (n=10). Anxiety levels were quite high 30.6% (n=117) among adolescents. Conclusion: The study concluded high prevalence of eating disorders and anxiety among adolescents. Anorexia and Bulimia nervosa were the most commonly identified eating disorders among adolescents. Educational programs should be arranged in high schools and at the community level to improve the knowledge and awareness regarding eating disorders
La mediación como estrategia para la resolución de conflictos laborales
Authors: Morataya Mitchell Karla Vanessa
Published: July 2023

El ámbito laboral es uno de los más propensos a conflictos de distintas índoles, pero en raras ocasiones se cuenta con una buena estrategia de mediación para solucionarlos, razón por la cual suelen ascender a niveles mayores de conflictividad, generando consecuencias no satisfactorias. Por ello, es importante conocer adecuadamente el proceso de la mediación que, implementado de manera voluntaria, ética y profesional, ha de conducir a soluciones que beneficien o satisfagan a las partes involucradas; ya sean disputas entre compañeros de trabajo, con jefes, clientes, proveedores u otros entes con los que se relacionen. Cabe destacar que la satisfacción o beneficio no solo se limita a una buena resolución del conflicto, sino también a la optimización del tiempo y al ahorro de dinero en comparación al procedimiento judicial. Así mismo, mejora significativamente la competitividad empresarial y el ambiente laboral; las actividades fluyen adecuadamente y se crea una cultura de resolución de conflictos mediante el diálogo asertivo.
BIO-INSPIRED GREEN SYNTHESIS OF NICKEL NANOPARTICLES USING STERCULIA FOETIDA LEAF EXTRACT AND ITS APPLICATION FOR REMOVAL OF TRIVALENT CHROMIUM FROM AQUEOUS SOLUTION
Authors: Rani N Usha , P. Pavani , Tulasi S Lakshmi , Rao P T. S. R. K. Prasad ,   Department of Freshman Engineering, PVP Siddhartha Institute of Technology, Kanuru, Vijayawada - 520 007, Andhra Pradesh, India
Published: July 2023

In the present work, a facile, eco-friendly, and cost-effective approach is described to remove Cr3+ toxic metal ions in an aqueous solution by nickel nanoparticles (NiNPs) synthesized via a green method utilizing Sterculia foetida leaf extract. The synthesized nickel nanoparticles were characterized by EDS (Energy- Dispersive X-Ray Spectroscopy), XRD (X-Ray diffraction), FT-IR (Fourier Transform Infrared Spectroscopy), and FE-SEM (Field Emission Scanning Electron Microscopy) spectroscopic methods. The spectroscopic signature studies revealed that the synthesized NiNPs are of spherical to irregular in shape with a mean particle size of 10±20 nm. The FT IR spectra confirmed the presence of OH, CC and CHO cross-linked stretching, CO and CCl stretching, representing the functional groups of polyphenols, flavonoids, and alkaloids type compounds in the synthesized nanoparticles. The EDS spectra confirmed the presence of nickel in the synthesized nanoparticles with a metal composition of 52.2%. In the XRD spectra, sharp diffraction peak two angles of green-produced NiNPs, which correspond to 111, 200 and 221 crystal planes, confirm the lattice structure of NiNPs. The synthesized NiNPs were used for the reduction of hexavalent chromium from aqueous solutions. The result revealed that immobilization of chromium heavy metals is an effect of initial concentration, ie. 100 µg mL-1 of Cr3+ concentration at 1 g L-1 of NiNPs adsorbent dosage within an average contact time of 1 h at 75 RPM. The present investigation revealed that these newly synthesized NiNPs might be potentially utilized for many environmental remediation applications.
PHYTOCHEMICAL SCREENING, ANTIBACTERIAL, ANTIOXIDANT AND ANTIINFLAMMATORY ACTIVITY OF ACMELLA OLERACEA FLOWERS
Authors:   Department of Quality Assurance, SVKM’S Dr. Bhanuben Nanavati College of Pharmacy, Mumbai-400 056, Maharashtra, India, Sanap Nikita , Khan Tabassum
Published: July 2023

Acmella oleracea flowers are traditionally used to treat mouth ulcers in the rural areas of Nashik, Maharashtra, India. This research project is an effort to understand the scientific basis for the utility of A. oleracea flowers and validate it for potential antimicrobial, anti-inflammatory and antioxidant activity, some of the main causes of mouth ulcers. The aim of this project was to study the phytochemistry of the ethanol extract of A. oleracea flowers and evaluate antibacterial anti-inflammatory and antioxidant potential. The phytochemical screening ethanol extract indicates the presence of phenolics, flavonoids, glycosides, alkaloids and carbohydrates. The total phenolic and flavonoid content in the ethanol extract determined by Folin-Ciocalteu reagent and aluminum chloride method were found to be 29.992 mg GAE g-1 and 93.2 mg QE g-1, respectively. The antibacterial activity of the ethanol extract was evaluated against Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis and Staphylococcus aureus, using streptomycin as the reference standard. The best activity was observed against P. aeruginosa. The antioxidant activity of the was determined by 2,2-diphenyl-1-picrylhydrazyl, hydrogen peroxide, nitric oxide scavenging and ferric reducing antioxidant power assays. The IC50 in the DPPH, hydrogen peroxide and nitric oxide scavenging assays were found to be 89.589 µg mL-1, 89.178 µg mL-1 and 50.86 µg mL-1 respectively. The anti-inflammatory activity was evaluated by in vitro albumin denaturation assay using naproxen as the reference standard. The ethanol extract demonstrated significant antibacterial, antiinflammatory and antioxidant activity, these combined effects could be responsible for its effectiveness in mouth ulcers and potentially justify the traditional use of A. oleracea flowers in mouth ulcers.
Primer Foro Subregional de Mujeres Indígenas y Comunidades Locales de Àfrica Central y la Cuenca del Congo: Declaración
Authors:   Rights and Resources Initiative,   REPALEAC
Published: July 2023

Del 8 al 12 de mayo de 2023, mujeres líderes de comunidades Indígenas y locales se unieron a donantes y filántropos internacionales, así como a ministros y actores políticos africanos, en Brazzaville para reforzar y promover el papel de las mujeres y niñas de las comunidades Indígenas y locales de la región en la resiliencia climática y la conservación de la biodiversidad. El ecosistema de la cuenca del Congo, en África Central, es el segundo pulmón más grande del mundo después de la selva amazónica, y alberga una extraordinaria biodiversidad de importancia crucial para los objetivos climáticos mundiales. Las mujeres de las comunidades Indígenas y locales desempeñan un papel esencial en la gestión y protección de los ecosistemas naturales que almacenan biodiversidad, secuestran carbono, apoyan los medios de vida locales y salvaguardan sus culturas y conocimientos tradicionales. Para poner de relieve su contribución, a menudo ignorada, a la conservación de la naturaleza y a la resiliencia climática – y sobre todo, para luchar contra la injusticia y la discriminación generalizadas – REPALEAC y las mujeres Indígenas líderes han unido fuerzas con RRI para organizar el primer Foro de Mujeres Indígenas y Comunidades Locales de África Central y la Cuenca del Congo. Esta declaración es un llamamiento mundial a la acción.
Critical Path Method and Project Evaluation and Review Technique under Uncertainty:A State-of-Art Review
Authors:   School of Advanced Sciences, VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati AP, India, M. Navya Pratyusha. ,   School of Advanced Sciences, VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati AP, India, Kumar Ranjan
Published: July 2023

The research article offers an extensive examination of extended fuzzy principles and their practical applications for addressing networking problems. Extended fuzzy principles have gained a significant impact that serve as an act of expansion from crisp and fuzzy logic, in addressing various uncertain environmental conditions. The Critical Path Method (CPM) and Project Evaluation and Review Technique (PERT) have emerged as valuable tools for tackling complex applications of network problems. The main emphasis lies on the discussion of three important extended fuzzy principles: Intuitionistic, Pythagorean, and Neutrosophic, specifically in the context of CPMPERT. Overall, this research article aims to provide valuable insights into the application of extended fuzzy principles, enabling better decision-making under different environmental conditions. The findings contribute to the ongoing development of fuzzy extensions and their potential to overcome challenges in networking.
Application of recall methods in recommendation systems
Authors: Wang Yumeng
Published: July 2023

In order to have a more comprehensive introduction and understanding of the re-search progress of recall strategies in recommender systems, this paper reviews the application of diverse recall methods in various recommender systems by different researchers. By searching and reading literature in major databases like Google Scholar, it is found that the recall method suitable for news recommendation system is also generally applicable in other recommendation systems. Therefore, this paper takes news recommendation system as an example to introduce traditional content-based recall and collaborative filtering-based methods. Hot-based recall and Embed-ding-based recall also developed in recent years. Furthermore, recall strategies (emo-tion-based recall and UIBB) that are specifically applicable to music and e-commerce recommendation systems are introduced. This paper briefly introduces these recall styles and collects researchers' evaluations and attitudes towards these recall styles, aiming to provide help for recommender system designers in optimizing recall methods.
Review on the coupling and promotion of machine learning methods to CFD
Authors: Zheng Haocheng
Published: July 2023

As the computer level advances in 1990s, CFD (the computational fluid dynamics, for short) has promoted fast. The process of using CFD to analyze complex or ideal conditions has a very wide application background. However, confronted by cases with higher accuracy as well as larger number of samples, CFD needs to spend much time and money for the sake of resolving the issues. ML (Machine learning, for short) approach provides a promising choice for CFD. This paper reviews the coupling of ML and CFD and the progress in promoting the application of CFD. This paper briefly introduces CFD along with ML approaches, such as supervised learning, unsupervised learning and reinforcement learning. This article also discusses challenges and issues with the aim of being resolved in the research of ML model based on CFD, such as using multiple machine learning models or hybrid models to solve problems and quantifying the uncertainty of machine learning models. If these problems are solved, ML method can provide a promising development prospect for CFD.
Analysis of digital transformation of furniture market in the context of big data application
Authors: Liu Siming
Published: July 2023

The whole furniture industry customization boom creates more and more significant demand for digitalization, and the impact of the epidemic on the furniture industry has further made many furniture companies realize the importance of industry digitalization. And in order to achieve the digital transformation of furniture enterprises, the collection and application of big data is the key: through the collection and use of customer and equipment data, you can achieve optimization of the supply chain in the furniture industry to reduce the inventory of raw materials and finished products; to achieve digital design and production intelligence to improve production efficiency and material utilization; to analyze the target customer groups and improve marketing strategies to attract more customers and increase turnover. In recent years, many scholars have also provided ideas on specific approaches to digital transformation in the furniture industry. This paper uses the literature review method and summary induction method to summarize the role that big data can play in the digital transformation of the furniture industry from three aspects: furniture production supply chain, furniture design digitalization and manufacturing digitalization, and furniture marketing.
Analysis of different transformer variants
Authors: Li Yisu
Published: July 2023

Efficient self-attention models are crucial in applications where long sequences are modeled, such as documents, images, and videos, are often composed of relatively large numbers of pixels or tokens. Therefore, the efficiency of dealing with long sequences is crucial for the broad adoption of Transformers. This paper talks about four transformer variants: Longformer, Transformer-XL, Big Bird, and Star transformer. This paper makes a comparative analysis of the four varieties theoretical methods, and obtains the advantages of the four methods and their applicable fields. Longformer has lower complexity and can be used for various document-level tasks. Transformer-XL improves the accuracy by addressing context fragmentation. BigBird replaces the Bert-like whole attention mechanism with Block Sparse Attention, which has achieved the SOTA effect on many tasks with long text sequences, such as long text summaries, long text questions, and answers. Star-Transformer reduces the time complexity to and performs well in the synthetic data set.
License plate classification based on MobileNetV2
Authors: Xu Tianqi , Zhang Ziqi
Published: July 2023

In China, there are various colors of license plates which represent different kinds of vehicles and we construct a model on Edge Impulse platform to deal with problems in actual engineering programs like parking, traffic flow control, city planning, etc. Lots of researchers have proposed different techniques about license plate classification but most of them have difficulties maintaining the balance between the size of the dataset and a decent accuracy. In order to achieve that, this research would combine transfer learning and MobileNetV2 to build a model on edge impulse. Transfer learning, as our models learning method, decrease the size of dataset under the precondition of maintain decent accuracy. MobileNetV2 is a lightweight CNN architecture, developed by Google and it allows our model applying on mobile devices so that our model would have more application prospect. In the process of model designing, the SoftMax function was utilized as the activation function and the Adam optimization algorithm was also applied to optimize the neural network. Training the model with a modest scale of data selected from the CCPD dataset and PKU vehicle dataset, our best-trained model based on MobileNetV2 gives the highest accuracy of 99.0 %.
Analysis of text mining methods and comparison of differences between different e-commerce platforms based on text mining
Authors: Fan Wenjie
Published: July 2023

With the further popularity of online shopping, people can buy the goods they want on online platforms without leaving home. However, due to the asymmetry of information, it is difficult for consumers or companies to compare the advantages and disadvantages of the same goods on different e-commerce platforms. This paper uses the word cloud method for text mining and Python to crawl and analyze customer reviews of the same product on two e-commerce platforms, which are Taobao and Jingdong, in order to compare the similarities and differences of the same product on different platforms. Through the comparison, we found that customers on the Jingdong platform think that the Jingdong platform provides good logistics services, while customers who consume on Taobao more often think that the products on that platform have high cost performance.
Review of automatic image cropping in practical application
Authors: Li Qiuyu
Published: July 2023

There is now a greater demand for photo Aesthetics and a desire for higher quality images. As a result there is also a greater demand for image cropping. Although there is a lot of work currently addressing this need, there has not been a comprehensive paper on the current state of development in this area until now. So this paper summarise the classical approach and some general datasets and some evaluation metrics. More importantly, this paper analyse the current challenges in the field and hope that future research will address these issues and lead to a better development of the field.
Real-time vehicle detection and tracking based on the combination of YOLOv7 and ByteTrack
Authors: Zhang Yining
Published: July 2023

Real-time tracking of vehicles is important for monitoring whether the roads are congested or not. How to achieve and maintain a high frame rate is a key problem to be solved in practical applications. In recent years, SORT, BOT-SORT [1] and other state-of-the-art target tracking algorithms have achieved fruitful results in target tracking tasks. The author combines YOLOv7(You Only Look Once v7) with bytetrack and compares the frame rate with some popular algorithms like Deepsort and bytetrack in real-time tracking to demonstrate that YOLOv7-bytetrack is more suitable for real-time detection, tracking of vehicles.
Blockchain-based technology in the healthcare industry and trend analysis
Authors: Hu Yuxiang
Published: July 2023

To sort out the current research status and trend analysis of blockchain technology in medical development. Logistic regression techniques are applied in this article to sort out the research and application trends of blockchain technology in the medical industry by using data cleaning and feature engineering, and by collecting domestic and international literature for analysis. At present, the application of blockchain technology in the medical industry is still in the early experimental stage. The medical industry should seize the development opportunities and strengthen technical research and R&D innovation so that blockchain technology can really play a role in reshaping the future information technology of the medical industry.
Review of the development of gesture recognition technology in recent years
Authors: Gao Xuehan
Published: July 2023

Currently, gesture recognition is the most rapidly advancing field in processing images and artificial technology. Gesture processing entails a procedure whereby gestures of the human body are recognized and used to coordinate PCs and other intelligent devices. This research will broadly outline human and PC coordination through gesture recognition technology over the past few years. Gesture recognition develops a simplified communication path between humans and PCs called Human-Computer Interaction (HCI). This study seeks to expose the significance of gesture recognition technology in recent years. In addition, this research will outlay the various methods in which gesture recognition technology can be applied in different perspectives, namely in education, transport, healthcare, and entertainment. This research will also elaborate on the pros and cons of every application process in each aspect. Lastly, this research will give an insight into the negative factors that hinder the development of gesture recognition technology. The research of gesture recognition mainly focuses on the visual aspect, and gesture provides an easy to understand recognition method. This makes gesture recognition products come into being and are widely used in the world. Now people do not need to touch anything. As long as they can wave their hands in the air, they can realize a series of complex operations that can be completed by touching the screen with the mouse and keyboard in the past.
Sensor-based gesture recognition with convolutional neural networks
Authors: Bi Ran
Published: July 2023

Sensor-based gesture recognition is an active research field of great significance with a wide range of applications in control systems for virtual reality, medical monitoring, and abnormal behavior determination. This problem has drawn the attention from both the academia and industry and many methods are proposed in the literature. Recently, deep learning has been widely applied in sensor-based gesture recognition and achieved good effects. In this paper, we proposed a classifier model based on Convolutional Neural Network (CNN) and applied it to EMG-based and smartphone-based datasets, respectively. For these two datasets, our model both achieved better classification accuracies than traditional machine learning models, with the results of approximately 97% and 72% accuracies, respectively. We also analyzed the effects of different parameters on the results of the proposed CNN model.
A review of CNNs application on the BCI signal processing module
Authors: Xiao Yang
Published: July 2023

With the rapid development of convolutional neural networks (CNN) in the field of deep learning, there has been a great process in brain-computer interaction (BCI) in the past few years due to its efficient processing of images. The review aims to discuss the application of CNN in the BCI design module, especially the data processing module, and analyses the problems and corresponding solutions in the researchers process. The author first briefly describes the application of the CNN architecture in BCI design modules and reviews various research in recent years on regarding improving the accuracy of CNN in BCI data processing modules and maintain high performance, including research on models that tries to solve the problem of commands, changes in feature extraction methods, computational methods, and changing the dimensions of the CNN architecture to attain better computation, etc. By analyzing the problems caused by some researchers using CNN architecture in BCI deep learning applications and related solutions, the author summarizes some of the shortcomings of CNN in BCI research and proposes possible research directions.
Dynamic malware detection based on CNN-LSTM network
Authors: Chen Jiate
Published: July 2023

As cyberspace continues to evolve, so does malicious behavior across the network. Attacks in cyberspace, such as the spread of malware, bring harm and risks to users. Malware will attempt to steal user information or impair system resources. Therefore, to protect against malware, a series of detection software such as firewalls have been developed to protect users information and systems from damage. As malware continues to evolve and develop, and the forms of attack are increasing, the corresponding malware and detection techniques should also be evolving issues. The commonly used raw detection technique is based on signature and behavior specification, which has the advantages of fast speed and less computation. However, this method is limited to known software, the target software which is an unknown software will not be applicable. Therefore, one obvious shortage of traditional malware detection techniques is that new or unknown malware are not likely to be detected. To solve this problem, this paper uses machine learning to analyze different features of malware. By this way, new malware can be detected by the model. Based on the API call of the Windows system, this paper proposed a convolutional neural network for the classification of malware types. On this basis, this paper used CNN to extract the features, considering the text characteristics of the API sequence. After subsequence debonding and meaningless suffixes deletion of the original API sequence, word vectors were obtained through training as the input of the subsequent machine model. Then, different convolution kernels were used to process contextual semantic information. Then, the LSTM model is used to extract the long-distance features from the features.
A review on the construction and application of medical knowledge graph
Authors: Qi Zhi
Published: July 2023

With the development of Artificial Intelligence, Knowledge Graph has become a popular direction in recent years, with which many practical problems have been solved. As a special type of Knowledge Graph, Medical Knowledge Graph is an important research field. While most of related research describes the construction and application of Medical Knowledge Graph (MKG) for a certain disease, there lacks reviews on previous research on Medical Knowledge Graph in recent years. In order to investigate recent research of Medical Knowledge Graph, this paper reviews studies of the construction and application of Medical Knowledge Graph in recent years, dividing them into six parts according to the content. Subsequently, some suggestions are put forward for the development of Knowledge Graph.
Research on big data privacy protection technology
Authors: Lu Tianyou
Published: July 2023

The extensive application of big data technology makes data burst with unprecedented value and vitality. However, due to the large amount of data, many data sources, and complex data access relationships, the current development of privacy protection technology is seriously lagging behind the development of big data technology, which restricts the application and promotion of big data. At present, it is urgent to sort out the development status of big data privacy protection technology, so as to provide a reference for the research and breakthrough of key issues of big data privacy protection. This paper analyzes k-anonymity and differential privacy protection, and points out that a protection method that can reduce the cost of high-dimensional data processing and ignore the background knowledge requirements of attackers is urgently needed for privacy protection in big data scenarios. At the same time, this paper also puts forward suggestions for the application and future development of these technologies.
Explore the identification of Chinese herbal medicine based on the VGG-16 model
Authors: Zhao Peiwen
Published: July 2023

Chinese Chinese herbal medicine has a long history, is the crystallization of thousands of years of wisdom of the Chinese people, and plays a very important role in the world's medical system. Different from western medicine, Chinese herbal medicine is mainly the fruit, root system, leaves, and other parts of herbal plants, so some Chinese herbal medicine is difficult to distinguish the characteristics. In this paper, the vGG-16 model is proposed to recognize Chinese herbal medicine images automatically, which helps reduce the practical difficulty of identifying Chinese herbal medicine species. 950 images of different kinds and forms of Chinese herbal medicine were obtained through the network, and the vGG-16 model was trained by deep learning, with a final recognition accuracy of 70%. At the same time, the model was evaluated from various angles according to the main characteristics of Chinese herbal medicine, which laid a foundation for subsequent research and software development.
A review of flexible wearable sensors
Authors: Wang Dandi
Published: July 2023

With the improvement of science and technology, wearable sensor technology has been widely used in health management, human-computer interaction and many other fields, becoming a mainstream research direction. Moreover, it has a good application prospect in various industries. In this paper, the performance requirements of wearable sensors are analyzed, and the future direction of wearable sensors is discussed in combination with the development of polymer for flexible sensors on flexible substrates and conductive materials. Based on the limitations of current technology, the optimization of wearable sensor technology mainly focuses on the improvement of sensing element materials and the accuracy of collected signals.
A systematic review and outlook on machine-learning-based methods for spam-filtering
Authors: Gao Yufeng
Published: July 2023

This paper reviews the stages of development and common approaches to spam text classification. This was followed by an introduction to the basic knowledge of spam filtering. After that, some research results are presented. The last part will be a discussion of the literature review and some suggestions for the future development of spam filtering techniques. This paper found that the future direction of spam filtering should be a combination of machine learning techniques and deep learning techniques and propose to take into consideration diversified features of the emails other than text such as IP addresses and IP reputation values into the machine learning models.
Research on the paradoxes in the artificial intelligence images
Authors: Zeng Xiaoxin
Published: July 2023

There is a wide argument about the development of artificial intelligence and whether it has emotions right now, conveying concern about Artificial Intelligence in the future. While people have not formed a consensus about Artificial Intelligence, even in the technical development field, this article explores a paradox in the common recognition of Artificial Intelligence image, which is the mixture of fiction and reality, collection and individual, by focusing on media served as extensions of the body and perspective, and the difference between a world in artwork and reality. The article is going to talk about the paradox between the conceptional Artificial Intelligence image and the existing technology by illustrating how media like film and fiction played a role in shaping the conceptual image in human mind. Using the story and narrative layer theory in narratology and extension theory in philosophy to analyze excerpts in In Search of Lost Time, how the illusion provided by novel can be distinguished and understood will be more concrete and practical in the following texts. All the elements including time and character should be distinguished since the world in a fictional work is unequal to the real world. Moreover, how the fictional work can provide a different perspective of substance and inspiration for our future actions is crucial, instead of trapping us in the anxiety of being replaced by a machine in the future, which can never have an answer at this time.
Comparison of several PID controls for quad-rotor UAV under wind disturbance
Authors: Gui Yihan
Published: July 2023

For achieving the stable flying of the UAV with wind disturbance, it is necessary to select an appropriate flight control system. This paper takes the quad-rotor UAV as the research object. First of all, it briefly introduces the structure and working principle of the UAV. Then it designs classical PID controller, cascade PID controller, fuzzy PID controller based on the system model. Finally, it uses MATLAB/Simulink to simulate the effectiveness of the control algorithm, and analyzes and compares the control effects of the three controllers. From the results of the experiment, it can be seen that the fuzzy PID controller can control the quad-rotor UAV more stably than the classical PID controller and cascade PID controller.
Movie information AI question answering system based on knowledge graph
Authors: Wang Bohan
Published: July 2023

Knowledge is essential for understanding. The ongoing explosion of information highlights the need for electronic texts that allow machines to better understand human language. The explosion of information in various fields has greatly changed our lives. Among them, the information explosion of the film is particularly prominent. Nowadays, people's requirements for high quality of spiritual life are increasing, and people's demand for movies is also increasing. With the extensive coverage of the Internet, the amount of movie-related information is also increasing, so how to design and build a question-and-answer system about movies is more and more urgent and important. At the same time, the original intention of the knowledge graph is to express various entities, concepts that exist objectively in the real world, and various relationships between them. It can better understand the abstract components in the language, and better to confirm the information through the interaction of the ambiguous parts of the language. In addition, the upgrade of deep learning natural language processing technology allows us to better understand and analyse language. In view of the above advantages, the movie question answering system in this paper is constructed based on the knowledge graph and uses natural language processing technology.
Low complexity signal detection based on traditional methods and neural networks for massive MIMO systems
Authors: Guo Jiachi
Published: July 2023

For the massive multiple-input multiple-output (MIMO) uplink, even though linear signal detection methods like zero-forcing (ZF) method or minimum mean square error (MMSE) method are capable of achieving near-optimal performance, the high computational complexity on account of matrix inversion has to be accepted. Existing methods to deal with this problem can be divided into three typical categories including approximation methods, iterative methods and methods based neural networks. In this paper, the characteristics of these algorithms and the connections between them are introduced in detail. Meanwhile, the letter points out the application of neural networks and machine learning is the future research direction in the field of communication systems.
A survey of face recognition based on machine learning
Authors: Wang Yufei
Published: July 2023

Face recognition technology based on machine learning methods is the most popular nowadays. This research, based on existing literature and data, was mainly focused on the face recognition system. The paper is written on the basis of existing face detection methods. Then, according to the difference in feature information, five methods were used to extract face features to apply them to face recognition. Then, this paper focused on two kinds of neural networks: support vector machines (SVM) and integrated learning methods, especially the Adaboost algorithm. Finally, the hidden danger of privacy disclosure was specially discussed. The results showed that the main direction of future research should be to expand the functional dimension and promote more applications to the public on the basis of ensuring the real-time and accuracy of the system.