Reviewerly/exHarmony huggingface dataset:
Brain Tissue Data Registration based on Context Demons Method

Image registration of brain tissue data has been used in disease diagnosis, surgical navigation, human brain mapping and some other fields for decades. At the present stage, brain image registration process generally adopts nonlinear registration algorithm, among which Demons algorithm is one of the most widely used. Owing to the growing processing requirement of large amount three-dimensional brain tissue data, the calculation burden of registration algorithm should be relieved. In this paper, the distribution of brain image intensities would be limited to a few significant categories by the mean clustering segmentation, which can facilitate the registration speed while ensuring the image registration effect. Then, an adjacent slice context processing configuration is proposed to reduce the redundancy calculation based on the slow spatial variation of brain tissue, and significantly improvement of the convergence rate in the Demons registration can be achieved. Finally, in view of the large tissue differences, an elimination and re-registration procedure is implemented for better accuracy, and a well preparation for the subsequent individual differences (such as lesion, tumor etc.) analysis can be achieved.
Penggunaan Bahasa Indonesia Dalam Media Sosial

Language is a means of communication used by each individual in providing information in the form of thoughts, ideas, intentions and feelings. The most important function of language is as a means of communication and interaction. Social media can be understood as a digital platform that provides facilities to carry out social activities for each user. Some activities that can be done on social media, for example, are communicating or interacting to providing information or content in the form of writing, photos and videos. Social media itself is basically part of the development of the internet. From the explanation above, language in social media has a very big influence for various groups. The language used in social media is of many kinds, from slang, formal language, informal language and the language used does not see the linguistic element. The influence of language like that has a positive or negative impact, therefore good language learning is really applied from an early age.Keywords: language, social media, the existence of the Indonesian language
Possibility analysis of three Gorges Dam to realize sustainable urban development goals—Taking Yichang City as an example

Despite numerous attempts by the government to control floods and boost the economy through water conservancy projects (WCP), a gap between planning and actual results still exists. Therefore, this study explores whether WPC can promote the development of village tourism. Considering the residents and tourists as objects, a mixed research method was adopted, questionnaires were collected, and the impact of village development and natural ecology on re-consumption willingness was analyzed by Pearson performance difference correlation. The results found that the Three Gorges Dam project provides rich tourism resources and vast land for development, further promoting economic development in surrounding rural areas, and improving infrastructure and the community environment. However, if new industries can be developed, diversified tourism activities can be planned, the industrial youth workforce can be maintained, emotional exchanges can be emphasized, water quality can be maintained, garbage can be reduced, and the tourism and living environment can be improved. This will enhance people's desire to relocate and travel as well as promote consumption willingness and behavior.
Healthcare Breaches During COVID-19: The Effect of the Healthcare Entity Type on the Number of Impacted Individuals.

The COVID-19 pandemic led to an increase in cybersecurity attacks on organizations operating in the healthcare industry. Health information professionals and health executives are unable to limit the impact of data breaches on records their organizations handle. While current research focuses on prevention strategies and the understanding of the causes of data breaches, it failed to address how to mitigate the impact of successful cybersecurity attacks. This quantitative research paper examined the effect the healthcare entity type has on the number of impacted individuals for healthcare data breaches that occurred during the pandemic. Health information professionals will be able to mitigate the number of breached records based on their organizational type. Some of this paper's findings include the call for implementation of organizational frameworks aimed to protect patient information, and the call for further research to understand how other factors might affect the impact of healthcare data breaches.
The Effect of Input Size in Deep Learning Semantic Segmentation

Over the last few years, fully convolutional networks (FCN) methods have been broadly applied to image and video semantic segmentation tasks becoming the state of the art. In the medical area, FCNs have been evaluated for lesion and structures localization and segmentation. With the improvement of acquisition devices, the resolution and size of the images have increased. Usually, deep and large architectures produce the best results but requires large amount of computation for the training process. Amount of memory required to load large images can be a restriction. In this study, we investigated the impact of resizing images for training procedure. Generally, better results are obtained when the FCNs are trained with the original image size, however, our experiments showed that the same performance can be achieved by training the models with smaller images and increasing the size of the predicted mask, instead of inferring the mask by feeding larger images to the network.
Assessment and evaluation system based on rapid development platform

The evaluation and evaluation of the company's employees by the personnel department is an important part of the personnel management work. Although there are many general office software systems on the market, these general software cannot meet the business needs of the personnel department due to the different assessment contents and evaluation rules of each company. In view of the business needs of a company's employee assessment and evaluation, this paper realizes the development, testing and deployment of the assessment and evaluation system in a short development cycle based on a professional rapid development platform under the premise of low investment and rapidity. After practical use, the newly developed system has met the actual requirements of the personnel department.
Processing and remedial methods of missing information in vehicle trajectories

With the rapid development of information technology, the application of data analysis and processing technology is becoming more and more extensive. In the data processing stage, necessary tools and technical means should be used to identify and process erroneous or missing data. The problem of missing positioning information data and picture additional information data will occur in the data recorded by the driving track of the car. This paper discusses the complementation methods for the above data information missing, and uses fragment interpolation, Lagrangian interpolation and other methods to achieve the complementation of missing data.
Study on optimal arc trajectory planning of robot based on artificial life system

The trajectory planning optimization can improve the performance of robot, and therefore the artificial life system method is applied in arc trajectory planning of robot. Firstly, the mathematical model of arc trajectory planning of robot is analyzed. Secondly, the basic theory of artificial life system is studied, and the corresponding algorithm procedure is designed. Finally, the simulation analysis is carried out, and the optimal trajectory of robot is obtained, and results shown that the artificial life system optimization method can be applied in the trajectory planning of robot effectively.
Perception and Preparation for the English Proficiency Test (EPT) among Aspiring Public Senior High School Teachers

This study discovered the perception and preparation on the English Proficiency Test (EPT) among aspiring public Senior High school (SHS) teachers of Davao City. The descriptive-correlational research design was used through a survey method. There were 30 respondents identified using snowball sampling technique where the researcher relied more on the referrals of the candidates qualified to contribute to the study. Results revealed that in terms of course, majority of the respondents were non-education graduates. In terms of discipline, majority are Science majors. Aspiring public SHS teachers’ overall mean for the perception on the EPT showed that they perceived EPT as highly valid, necessary, and fair. The Multivariate Analysis of the General Linear Model revealed that there is no significant difference on the level of perception on the EPT and the level of preparation in terms of course, discipline, EPT rating, and RQA rank respectively. Nevertheless, because of the inferential statistics, the results showed a comparable result because the overall results are not large enough to say that it has no significant difference. Moreover, the perception of the aspiring public SHS teachers especially on the necessity affects their RQA rank. The way they perceive the test has an impact to their test preparation. Furthermore, the Pearson’ Product Moment Correlation revealed that there is a significant relationship between the level of perception and the level of preparation as regards to the EPT among aspiring public SHS teachers. Keywords: English Proficiency Test, Department of Education, Senior High School, Registry of Qualified Applicants, Descriptive-Correlation
Risk Assessment

This chapter deals with risk assessment. Foreseeability is the trump card to the Risk Assessment. Foreseeability means that if an event has occurred on the property before, then it is possible that it will happen again. History is a good indicator of potential hazards, so if the environment allowed an incident to occur, and the security environment does not change to meet that threat, then it can happen again. This becomes a liability issue. Notice is sometimes inter-changed with foreseeability, but it is a bit different and more specific. The security plan is a document that explains what security measures will be taken to mitigate risks (prevent crime and accidents) on and around the property. Prevention is usually not the sole responsibility of Security, but since we are on the front lines and see most incidents, we can make recommendations for change.
Physical Security and Crime Prevention Through Environmental Design (CPTED)

Physical Security is just about everything that is not in the Cyber Security toolbox. Since the parts and pieces of Physical Security have so many applications and combinations, ASIS and others have organized them into what is called the Physical Protection System. Crime Prevention Through Environmental Design is a science that is somewhat young, but has its foundations in design and architecture going back centuries. Certain bushes have thorns or sharp leaves that prevent someone from easily climbing over or around them. Lumens are the measurement of light being produced by a lamp. Diffused or shaded lighting is a technique used to aim or control the intensity of lighting.
Employee Awareness

Behavioral Recognition, Security Awareness, and Social Engineering are some of the skills being taught and applied throughout the Security Industry (and the hospitality industry). Besides sales, drugs are usually associated with other criminal activity like prostitution, robbery, and organized crime. Their loyalty may depend on whether they are in on the action, but they need to understand the consequences of not reporting prostitution. One series of popular movies depicted the international aspect fairly accurately, but in the US authors are far more likely to see the domestic form of trafficking that they know as prostitution. Signs of drug use, used condoms, blood, and familiar smells do not necessary equate to prostitution but when combined with other information may be enough to identify criminal activity or someone in trouble. Employee awareness programs without a reporting process on the back end are useless. Some become victims of killers and some are turned to prostitution or some other form of slavery.
Application of ensemble learning in breast cancer cell classification

Breast cancer has become the most growing cancer, of which the early diagnosis and prediction require precise medical development tools. However, the accuracy of conventional machine learning classification prediction should be improved. Accordingly, ensemble learning has been proposed, a novel idea of machine learning, which is capable of significantly improving the accuracy of prediction and presenting novel insights into breast cancer disk classification prediction. In this paper, six of the latest ensemble learning classification algorithms (i.e., Xgboost, Catboost, GBDT, LGBM, Random Forest and Extra Tree as an ensemble learning model) are compared with one conventional machine learning algorithm (i.e., K Near Neighbor (KNN)). The original breast cancer data set of Wisconsin is adopted to train the model, and the model effect is assessed using model evaluation indicators (e.g., accuracy, recall, and accuracy) after the model is trained. In addition, the Xgboost algorithm is indicated with the maximum prediction accuracy for breast cancer cells. Furthermore, it was revealed that ensemble learning algorithms generally have higher accuracy than other machine learning algorithms.
Vehicle re-identification method based on semantic information enhancement and feature complementarity guided by keypoints

Vehicle re-identification aims to retrieve and match vehicles under non-overlapping cameras. Although this technology has made some progress in recent years, the problem of vehicle appearance ambiguity caused by perspective shift still can not be well resolved. To alleviate the above problem, this paper proposes a vehicle re-identification method based on keypoint-guided semantic feature alignment and graph matching strategy to enhance complementary information under the transformer framework. The method first uses the pre-trained vehicle attitude detection model to extract keypoints, and proposes an information mapping strategy. Through the coordinate information of keypoints, the corresponding local feature tokens under the transformer framework are extracted and given semantic content to achieve the same semantics. Feature alignment for attribute tokens. Then, a graph matching network is constructed to realize the transfer of semantic information between similar samples, and the expressive ability of features is further improved through the multivariate interaction of information. The proposed model achieves state-of-the-art performance and superiority compared to similar methods on two large vehicle re-ID datasets.
Phishing websites detection by machine learning and deep learning techniques

In this paper, we try to find two methods based on deep learning and machine learning to detect phishing websites from those legal ones. In terms of machine learning models, first, both phishing and benign URLs of websites are gathered from online resources, and required URL features and website content-based features are extracted and selected to form the data set. 5 different training methods are used and analyzed. In terms of deep learning model, a character - embedded Bidirectional LSTM is used for training. And the model is testified then.
Security Analysis on Content Management Systems

This paper is dedicated to the challenges of the use of the most popular content management systems (CMS) in software development. Fundamental information about the selected CMS platforms and vulnerability analysis are introduced. The review is made on CMS like Umbraco, Sitecore, WordPress and Drupal categorized in two groups defined by the technology used for development. And as the IT world changes a lot these brings one constant battle against threats. Therefore, this article will add some vulnerabilities analysis of the selected systems since 2014. Results were grouped by common vulnerabilities of the selected platforms and such specific ones.
Research on the application of artificial intelligence system in string teaching

Artificial intelligence is a hot topic in current information technology research. Undoubtedly, the progress of artificial intelligence technology needs to strengthen the cultivation of talents, and the development of technology is essentially the development of talents. For college teaching, its own teaching mode and teaching philosophy have also been adjusted accordingly. As far as the teaching of string chamber music is concerned, it is a problem that contemporary music teachers should pay attention to the practice reform and innovation of the whole teaching. Influenced by the traditional teaching concept, there is a big gap in the mode and equipment of contemporary music teaching. In today's era of rapid development of social science and technology, the society is gradually moving towards an intelligent development trend. At the same time, the appearance of artificial intelligence system has brought great convenience to the society and met people's daily needs in all aspects. The application of artificial intelligence system in music education not only breaks the traditional music education mode, but also promotes the development of music education in China. Therefore, the department of artificial intelligence has become an important auxiliary means in current teaching work. The teaching equipment of artificial intelligence system effectively combines images, words, sounds and other elements, which can be vividly displayed to students. For the current string music education, the application of artificial intelligence system can make string students absorb and transform music knowledge more quickly, and achieve twice the result with half the effort.
Data mining and analysis system based on two-brain Trading Strategy Model

This article through the establishment of quantitative model and the corresponding prediction model orientation of network information mining, through the database to adjust some of this information and integration, the database of the directivity classification work, can according to the requirements in terms of system analysis of data at the same time, through the data to forecast its trend, get the best prediction model and the prediction results. In this paper, a data set is established based on the stage new information indicators of database information and the corresponding rise and fall trend broken line graph, and a quantitative Model and trend prediction system based on two-brain Strategy Model are established to predict and evaluate the situation of directional information. And then to predict the trend of fluctuations is relatively accurate prediction results quantitative optimization model is established, the grid strategy and hedge strategy is adopted to improve the decision-making and judgment, decision variable coding as operands, can converge to the optimal solution with large probability, data analysis and forecast the dynamic change of process, with different weights allocation scheme to give corresponding risk prediction.
The Effect of Assistance Quiz Team Model with Lectora Inspire Media on Biology Learning Outcomes and Student Activity

Learning outcomes are indicators of success in learning, learning outcomes are closely related to activity, namely if student learning activities are good then learning outcomes will be good, so that activeness and learning outcomes are important to have, but the reality in school learning outcomes and student activity is low, this is because the model and the media used does not facilitate active students in learning which has an effect on learning outcomes, one solution to the problem of the media and the module is the use of the quiz team model assisted by the lectora inspire. The purpose of this study was to determine the effect of the Quiz Team model with the help of Lectora Inspire on learning outcomes and activeness of class X. The design of this study was a pretest - posttest control group design with a quasi-experimental type. The sampling technique using cluster random sampling was obtained X MIA 1 as the experimental class and X MIA 2 as the control class. Hypothesis testing using MANOVA obtained sig 0.00 &lt; 0.05, meaning that there is an effect of the Quiz Team model assisted by the Lectora Inspire media on learning outcomes and student activity.
Visual Mining Method of Japanese Movie Resources Based on Association Rules

One of the crucial fields of study that is getting more attention is association rule mining. It is crucial to databases' knowledge discovery (KDD). KDD and association rule mining have a very broad use. It has evolved at a rapid rate over the past fifteen years. Association Rule Mining is a novel technology, although it is still in the discovery and development stages.&#x0D; Video is an illustration of interactive media data since it contains text, pictures, meta-data, visual, sound, and different kinds of data. It is frequently used for a variety of important likely reasons, such as security and reconnaissance, amusement, healthcare, educational endeavours, and sports. One of the main issues for the local data-mining research community is video data mining, which aims to find and comprehend fascinating examples from the large volume of video data. Video data mining is still in its infancy when compared to mining other sorts of data.&#x0D; It is pivotal to grasp and naturally mine the information from video databases considering the continually extending computerized libraries and video databases. Differentiating association rules between components in a significant video library is critical in the field of video data mining. As per continuous imaginative work, association rule mining is being utilized rapidly in various tasks, including perception, social affairs, broadcast news, sports, records, films, clinical data, as well as on the web and individual media assortments. This exploration tries to give a far reaching method to association rule extraction from video databases.
Quantum Dynamic Network Modeling Algorithm in Mathematical Modeling Training Combined with BOPPPS Comprehensive Networking System Construction

A quantum self-organizing feature mapping network model and clustering algorithm are proposed. The inputs and weights of quantum neurons are quantum bits, and the output is real numbers. The characteristics and relationship of BOPPPS model and problem-driven teaching method are studied, BOPPPS model and teaching method The relationship between elements 5W, and taking the "Algorithm and Data Structure" course as an example, gives strategies and practices for cultivating computational thinking. The quantum self-organizing feature map network is composed of input layer and competition layer. The multi-objective programming model is established by mathematical methods such as linear weighting, objective programming and hierarchical sequence, and the solution to the dynamic allocation of resources in the logistics network is given by analyzing the model.
Java Implementation of Intelligent Platform for College English Flipped Classroom based on Data Mining of "SPOC+STEAM" Information System

Taking the SPOC course practice of "Technology Translation" as an example, based on the "SPOC+STEAM" information system data mining for blended teaching and flipped classroom teaching theory, the online teaching resources construction of SPOC-based blended and flipped classroom teaching is designed. Online and offline blended teaching process and teaching evaluation design model. In the deep integration stage, the discussion on teaching mode mainly includes three aspects: flipped classroom teaching mode, blended teaching mode, and information technology-based teaching mode.