Reviewerly/exHarmony huggingface dataset:
Influencing Factors and Intervention Strategies on Employment Stability of Vocational Graduates at the Beginning of Their Career

From the perspective of employment stability at the beginning of vocational college graduates' career, this paper analyzes the influencing factors, including environmental factors, organizational factors and individual factors. Taking Wenzhou Polytechnic as an example, this paper explores intervention strategies for employment stability in the early career of vocational graduates, analyzes the implementation contents and paths of different intervention strategies from four dimensions of policy intervention, information intervention, service intervention and target group intervention, and then puts forward suggestions for optimizing intervention strategies for stable employment.
Career development stage matters: Effects of elementary school teachers’ professional collaboration on job satisfaction

이 연구는 교사의 전문적 협력 활동 참여와 직무만족도 사이의 관계가 교직 발달단계에 따라 상이한 양상을 보일 것으로 가정하고 이를 실증적으로 검토하였다. 구체적으로, 교사 발달단계에 따라 교사의 특성이 다르다는 이론적 검토 결과에 따라 초등학교 교사를 교직 경력별로 적응단계(5년 미만), 성장/발달단계(5년 이상~20년 미만), 숙련단계(20년 이상)로 나누어 각 발달단계에서 전문적 협력 활동에의 참여와 교사 직무만족도의 관계를 분석하였다. 연구를 위하여 경제협력개발기구(OECD)에서 조사 및 발표하는 ‘교원 및 교직환경 국제비교 연구(TALIS)’의 제3차 조사(2018년) 자료 중 우리나라 초등학교 교사 2,669명의 자료를 활용하였다. 이를 토대로 직무만족도의 두 가지 하위요인인 ‘직업환경만족도’와 ‘교직만족도’에 대한 회귀분석을 수행한 결과, 각 발달단계별로 서로 다른 효과가 관찰되었다. 먼저, 적응단계 교사들의 경우 전문적 협력 활동에 적극적으로 참여할수록 직업환경만족도가 높은 경향을 보였다. 성장/발달단계 교사들은 두 가지 직무만족도 모두 전문적 협력 활동의 효과가 통계적으로 유의미한 반면, 숙련단계 교사에게서는 두 가지 직무만족도 모두 전문적 협력 활동의 통계적으로 유의미한 효과가 관찰되지 않았다. 이러한 결과는 국내·외 여러 연구에서 공통적으로 그 긍정적 효과성과 함의가 논의되고 있는 교사의 전문적 협력 활동에 대해 면밀히 재고할 필요가 있음을 시사한다. 구체적으로, 교사의 전문적 협력 활동이 지닌 이론적 함의와 그 긍정적인 효과에도 불구하고, 전문적 협력 활동 실천이 교사의 발달단계에 따라 그 결과가 상이할 수 있다는 점은 향후 전문적 협력 활동을 장려하기 위한 정책적 시도들이 대상에 따라 서로 다른 접근 방식을 고려할 필요가 있음을 보여주는 것으로 해석이 가능하다. This study empirically examined the relationship between teachers’ participation in professional collaborative activities and job satisfaction by career development stages with an assumption that diverse patterns will show depending on the career development stages of teachers. Based on the theoretical review that teachers have different characteristics depending on their career development stages, elementary school teachers were divided into three stages – adaptation stage, growth/development stage, and expertise stage – to analyze the relationship between professional collaborative activities and job satisfaction at each developmental stage. To this end, data from 2,669 elementary school teachers in Korea were utilized from TALIS 2018. As a result of regression analysis on the two sub-factors of job satisfaction, “job satisfaction with work environment” and “job satisfaction with profession”, different effects were observed for each developmental stage. First, for teachers in the adaptation stage, a positive relationship was found between active participation in professional collaborative activities and job environment satisfaction. For teachers in the growth/development stage, the effects of professional collaborative activities were statistically significant for both job satisfaction sub-factors, while for expert teachers, no static effects of professional collaborative activities on both job satisfaction sub-factors were observed. Policy implications are suggested based on the results.
Sensitivity enhancement in low coherence Fourier transform spectral interferometry

In conventional interferometry, the intensity of the superposed field is observed to study the phase information of object / sample field. The schemes like Weak measurement scheme, spectral switching observes the intensity of the output field for enhancing the sensitivity of the phase measurements. A scheme to enhance the sensitivity in the measurement of path delays through spectral interferometry by observing the phase accumulated by the superposed field with respect to an additional reference beam is presented. Through the interference with additional reference beam maintained at out-of-phase condition near zero optical path delay with respect to the sample probe beam, it is shown to introduce nonlinearity in phase change measured. In the experimental demonstration, the classic low coherence spectral interferometry is used. The three-beam interference is achieved by a modified Michelson interferometer. According to the setting of initial path delay and amplitude ratio of the interfering fields, the intensity of superposed field shows spectral modulations. Spectral phase is measured from the modulations in the recorded spectral interference using Fourier transform method of fringe analysis. In the Fourier domain, a linear path delay between in the interfering beams gives a linear shift in the position of secondary peak. By filtering the secondary peak from the Fourier domain, and taking the Inverse Fourier transform, the amplitude and phase information of the interfering fields can be obtained. The proposed method maps the linear path delay to highly nonlinear phase accumulation and has the potential to enhance sensitivity of phase measurements.
Generative Adversarial Networks: Some Analytical Perspectives

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A protocol to create a multi-particle entangled state for quantum-enhanced sensing

We propose a protocol for generating multi-particle entangled states using coherent manipulation of atoms trapped in an optical cavity. We show how entanglement can be adiabatically produced with two control beams and by exploiting cavity-mediated interactions between the atoms. Our methods will allow for optimal generation of entanglement for the measurement protocol we propose. We discuss a possible experimental implementation and compare the performance of the states produced with those of classical states and ideal maximally-entangled Dicke states. We find that our states always feature metrological gain and even outperform ideal Dicke states in the measurement of magnetic field gradients. Due to the easy scalability, our entanglement protocol is a promising tool for quantum state engineering.
MACHINE LEARNING –BASED FALL DETECTION FOR SENIOR CITIZENS

Health is the major worrisome point whose impalpability increases with increase in the age.Thus, taking care of elders is very important responsibility.In such scenario, technology is helping people by providing living assistance.One of the major causes of health degradation or death of elders is 'fall'.In this paper, a fall detection system is proposed based on machine learning.The system detects falls by classifying different activities into fall and non-fall actions and alert the relative or care taker of the elderly person in case of emergency.The dataset SisFall with variety of activities of multiple participants is used to calculate features.Machine learning algorithms SVM and decision tree are used to detect the falls on the basis of calculated features.The system acquires accuracy up to 96% by using decision tree algorithm.
PARKINSON’S DISEASE DETECTION USING DEEP LEARNING

Nowadays, an important research effort in healthcare biometrics is finding accurate biomarkers that allow developing medical-decision support tools.These tools help to detect and supervise illnesses like Parkinson's disease.This model contributes by analysing a convolutional neural network for PD detection from drawing movements.The dataset consists of several Spiral drawings taken from 77 people in which 62 people are diagnosed with PD and other 15 are healthy.These drawings are taken using Wacom Cintiq 12WX graphics tablet.The proposed Deep learning approach is CNN and it includes two parts: feature extraction in convolutional layers and classification with fully connected layers.A new data is tested with model and obtained an accuracy of 96.5%, f1-score of 97.7%, AUC of 99.2%.The output of this model determines whether the person is affected with Pd or not.
FINDING THE MISSING PERSON USING FACIAL RECOGNITION

Every day, many thousands of people go missing for a variety of reasons such as age, mental or emotional disorders, Alzheimer's disease, and so on.The majority of them go untraced, and the effort of locating the missing person fails.This project prioritises the safety of police officers and the general public by expediting the search for a missing person.When a new case is filed, its information is saved in the application's database.When someone comes across such a person, he will take a picture of him and look up the record in the current database.If a match is found, they can submit the details into the database, save the present location when uploading, and the case will be reported to higher authorities.The other case is if the match for the lost person is found, the details from the database will be retrieved and police or the family members will be informed.
On the Unity of the Situational Construction of HUA JIAN CI

As the first collection of ancient Chinese literati lyrics, The 〈HUA JIAN JI〉 has left an important mark on the development of ancient Chinese literature, with lyricists such as Wen Tingyun, Ouyang Jiong and Wei Zhuang, who were used to combining a variety of artistic techniques to arrange and combine a variety of life-like imagery, and then constructing a context. It is also necessary to explore the ways in which the contextual construction of HUA JIAN CI was intentionally constructed by their creators. This paper will use an internal approach to literary studies to do so. On the basis of an understanding of the original words, the way in which contextual integrity is revealed is examined in terms of the three stages of contextual construction: initial, sublimation and completion, and the three corresponding dimensions of reality, spirit and discourse; the way in which contextual integrity is constructed is analysed in terms of the object of reference of the text, the choice of imagery of the text, and the style of diction of the text, with a view to demonstrating that integrity is the inevitable result of the dominance of its aesthetic pursuit. Of course, while this paper examines the construction of contextual unity in HUA JIAN CI, it can also be used as a guide to answer more academic questions related to HUA JIAN CI.
NFTs and Healthcare

I have tried to stay abreast and on the cutting edge of new technology, ideas, and investments. However, NFTs—or non-fungible tokens—have so far eluded me. I have asked my children and their contemporaries, and no one has been able to explain it to me. When it comes to NFTs, or the emerging form of digital certificate that certifies an asset as one-of-a-kind, the medical community seems to be divided between pro- and anti-NFT camps. Those belonging to the former camp tout it as a novel approach to finance and ownership of digital data. Those against NFTs point to—among many other things—their devastating impact on global climate or their use of tremendous amounts of energy to compute the blockchain transfers of billions of dollars that take place regularly in the metaverse. On the other hand, NFTs represent a unique potential in the digital health age: that of patients, rather than companies, owning their digital healthcare data. With such a level of ownership, physicians and patients could leverage its advantage to monetize their data rather than have companies profit off them, as traditionally has been the case. This article walks you through the basics of NFTs, explains how they can further empower patients in the digital health age, and raises concerns pertinent to the technology.
Drone System Capable of Inserting an Object While Moving on a High-Rise Building Wall

이 연구에서는 건물 외벽에서 벤트캡 삽입 작업이 가능한 드론을 설계하고 제어기를 개발하였다. 드론시스템은 벽에 부착되는 드론 기구 메카니즘과 3축 로봇팔을 이용하여 벤트 구멍에 벤트캡을 삽입하는 제어 알고리즘으로 구성하였다. 드론의 안정적인 비행을 위해 센서로부터 얻은 각속도, 각도, x,y 축 선속도 값을 이용한 3중 PID 제어를 진행하였고, 전면부에 모터 및 프로펠러를 추가적으로 배치하여 벽 쪽 방향으로 밀어주는 힘을 발생시켜 드론이 벽에 안정적으로 고정될 수 있도록 하였다. 벤트 구멍인식에서는 최소 자승법 및 RANSAC 알고리즘을 이용하였다. 구멍 인식에서 발생하는 미세 오차는 RCC(remote center compliance) 기구를 이용하여 삽입 성공률을 높였다. This work describes the designed a drone and controller capable of inserting a vent cap on the wall of building, moving on the wall, and attaching the drone to the wall. The drone system is composed of the mechanism attaching to wall and inserting a vent cap with 3-axis robot arm. For the drone flight stability, the drone system was controlled by triple PID control using angular velocity, angle, and linear velocity values received from several sensors. Additional two motors and propellers in the front side of the drone generates force to make the drone attach to wall. In recognition of the vent hole on the wall, the least squares method and RANSAC algorithm were used. Small errors in the hole recognition were overcome using a designed RCC(remote center compliance) devise to increase the success rate of vent cap insertion.
Detecting Phishing Attacks Using Natural Language Processing And Machine Learning

Machine learning is a field of artificial intelligence that allows computers to improve their performance on specific tasks by learning from data instead of just following predefined rules.It encompasses supervised, unsupervised, and semi-supervised learning, which depend on the availability of labeled data.Phishing detection employs machine learning to extract features, classify URLs, adapt to new threats, and analyze data to detect clusters of phishing attack.It plays a crucial role in automating the detection of phishing attacks.The proliferation of malicious websites and internet criminal activities have raised concerns among web users and service providers.To address this issue, we propose a learning-based algorithms such as Catboost, Adaboost, Random Forest and Support vector machine to classify websites based on the URLs into three categories: benign, spam, and malicious.Benign websites offer legitimate services and are safe to use, while spam websites inundate users with ads, fake surveys, or dating sites.Malicious websites are created by attackers with the intent of disrupting computer operations, stealing confidential data, or gaining unauthorized access to private systems.The proposed mechanism analyzes only the Uniform Resource Locator (URL) of websites and does not access their content, reducing runtime latency and eliminating the possibility of exposing users to browser-based vulnerabilities.A large dataset of labeled URLs is used to train a classification model, which is then used to classify new URLs.After experimentally evaluating the proposed approach using a publicly available dataset, it is demonstrated that the approach achieves 98.3% accuracy, with the random forest model and SVM model, outperforming traditional blacklisting services in generality and coverage, and having the ability to adapt to new threats and enhance its performance over time.It presenting a promising solution for accurately detecting phishing attacks in URLs and of interest to researchers and practitioners working in cybersecurity.
Advanced High Secured Smart ATM System

Abstract: Automated Teller Machines are widely used nowadays by people. But It’s hard to carry their ATM card everywhere, people may forget to have their ATM card or forget their PIN number. The ATM card may get damaged and users can have a situation where they can’t get access to their money. In our proposal, use of biometrics for authentication instead of PIN and ATM card is encouraged. Here, The Face ID is preferred to high priority, as the combination of these biometrics proved to be the best among the identification and verification techniques. The implementation of ATM machines comes with the issue of being accessed by illegitimate users with valid authentication code. This project provides service to the user only when the user is legitimate or the user is verified by the legitimate user of the ATM card. The users are verified by comparing the image taken in front of the ATM machine, to the images which are present in the database. If the user is legitimate the new image is used to train the model for further accuracy. This system uses openCV to process the image being obtained and Haar Cascade Classifier to detect the faces in the image. The face recognition is done using Local Binary Pattern.To overcome these problems,the project ’ATM Security system based on Face recognition, PIN and OTP’ consists of conventional features ie is Personal Identification Number (PIN) along with additional features like face recognition and one-time password (OTP) is used. Database holds information about a user’s account details, images of his/her face and a mobile number which will improve security to a large extent.
Sistem Informasi Layanan Klaim Asuransi Berbasis Web Pada Ajb Bumiputera 1912 Kantor Cabang Telanaipura Jambi

AJB Bumiputera 1912 Telanaipura Jambi Branch Office is an insurance company that provides services to the community. In the current system, the claim submission service process is still done manually, that is, submitting claims can only be processed if the agent and customer have a meeting and the customer completes a claim submission form. This causes the length of the claim submission process and the services provided do not run optimally. Based on the existing problems, a claim submission service system is needed in order to assist AJB Bumiputera 1912 Telanaipura Jambi Branch Office in terms of claim submission services. The purpose of this research is to design a prototype of the claim submission service system using the system modeling tool, namely UML and the diagrams used include use case diagrams, activity diagrams, and class diagrams. The results of this research are in the form of designing a prototype claim submission service system that can be implemented by AJB Bumiputera 1912 Telanaipura Jambi Branch Office to help facilitate the management of information on life insurance claims submissions.
Preface: 2023 International Conference on Algorithms, Mathematical Modeling and Machinery Processing (AMMMP 2023)

We sincerely invite you to participate in the 2023 International Conference on Algorithms, Mathematical Modeling and Machinery Processing (AMMMP 2023). This conference was successfully held in Dalian, China during February 25-26, 2023 for researchers, engineers, etc. on topics related to algorithmic intelligence, mathematical modeling, simulation, soft computing, control theory and automation.&#x0D; AMMMP 2023 aims to elaborate basic and applied researches from all over the world. In particular, as our theme for this conference, we encourage researchers to present their researches on algorithms and mathematical modeling. The participants attending this two-day conference reach 75 people. We design that the participants can present their work either in oral or poster types. Furthermore, the crucial factor for AMMMP 2023 is that we facilitate the works from the participants that can be published at a journal with the peer-reviewed process.&#x0D; We have worked hard to process all accepted manuscripts reviewed by professionals and experts in related science fields. At least, one manuscript is under reviewed by two reviewers, and the handling editor decided whether a manuscript can be accepted or rejected mainly based on the reviewer's comments.&#x0D; With best regards,&#x0D; Technical Program Committees of AMMMP&#x0D; Dalian, China
A case study on the quality of machine translation and the source text difficulty : A case of a Korean-English statutory translation by Google Translate.

This paper attempts to investigate the relationship between the source text difficulty and the quality of machine translation output. We examined the results of human evaluation of the Korean-English statutory translation by Google Translate and the source text difficulty measured in terms of lexical and terminological difficulty and syntactic complexity. The translations of two different statutes revealed varying correlation patterns examined in terms of fluency, accuracy, terminology and others. The results demonstrate that the two source texts’ syntactic complexity had a negative correlation with the machine translation quality evaluation. In other words, Google Translate was found to be weak at translating long and syntactically complex sentences. On the other hand, lexical and terminological difficulty did not have any correlation with the results of human evaluation despite the fact that statutes contain a lot of difficult words. Overall, the source text difficulty had a strong negative correlation with the human evaluation results, which was generally supported by the evaluators’ comments on fluency and accuracy errors.
Analysis of Reading Literacy in the PISA Examination and Its Enlightenment to Chinese Reading Education

The Programme for International Student Assessment Test (PISA) is a particular research organized by OECD to assess students’ extensive knowledge and skills from different areas of the world. The excellent performance of Chinese students in PISA has attracted wide attention from the world. Maths subjects of Chinese students in PISA are particularly strong, followed by science, and reading scores are also relatively good, but are the weakest. At the same time, compared with other subjects like Maths, Chinese language education has always been criticized for taking too much time and being inefficient in China mainland teaching field for a long time. World learn from China. China also learns from the world. By focusing on the reading content of the PISA test, the paper reflects on the content brought by the PISA reading assessment framework and evaluation criteria, aiming to find the international elements of reading education and giving some enlightenment to Chinese language reading strategies.
Single-View View Synthesis with Self-rectified Pseudo-Stereo

Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view view synthesis problem to a multi-view setting. Specifically, we leverage the reliable and explicit stereo prior to generate a pseudo-stereo viewpoint, which serves as an auxiliary input to construct the 3D space. In this way, the challenging novel view synthesis process is decoupled into two simpler problems of stereo synthesis and 3D reconstruction. In order to synthesize a structurally correct and detail-preserved stereo image, we propose a self-rectified stereo synthesis to amend erroneous regions in an identify-rectify manner. Hard-to-train and incorrect warping samples are first discovered by two strategies, (1) pruning the network to reveal low-confident predictions; and (2) bidirectionally matching between stereo images to allow the discovery of improper mapping. These regions are then inpainted to form the final pseudo-stereo. With the aid of this extra input, a preferable 3D reconstruction can be easily obtained, and our method can work with arbitrary 3D representations. Extensive experiments show that our method outperforms state-of-the-art single-view view synthesis methods and stereo synthesis methods.