Reviewerly/exHarmony huggingface dataset:
The Effects of Intrapersonal Intelligence of Well-Aging Instructors on Educational Competency

본 연구의 목적은 웰에이징 교수자의 자기성찰지능과 교육역량의 관계를 분석하여 웰에이징 교수자의 전문성 강화 및 웰에이징 분야 교육질 제고를 위한 기초자료를 제공하는 것이다. 연구 대상은 웰에이징 교육분야 전문가 393명이었으며, 자료수집은 2022년 11월 14일부터 2023년 1월 16일에 걸쳐 한국갤럽의 온라인 설문으로 이루어졌다. 분석방법은 SPSS 29.0을 이용하여 빈도분석, 신뢰도분석, 독립표본 t-검정, 일원 배치 분산분석, 사후분석, 상관분석, 다중선형회귀분석을 실시하였다. 연구 결과를 요약하면 다음과 같다. 첫째, 웰에이징 교수자의 연령, 교육경력에 따른 자기성찰지능과 교육역량의 차이를 분석한 결과 연령과 교육경력이 증가할수록 자기성찰지능과 교육역량 수준이 높아짐을 확인하였다. 반면 성별에 따라서는 유의미한 차이를 보이지 않았다. 둘째, 웰에이징 교수자의 자기성찰지능이 교육역량에 미치는 영향을 분석한 결과 모든 하위요인들은 서로 유의미한 상관관계가 있음을 확인하였고 웰에이징 교수자의 자기성찰지능이 교육역량에 미치는 상대적 영향력은 자기성찰지능 하위영역인 자기설계, 자기조절 및 정서활용, 자기반성 순으로 전체 교육역량에 긍정적인 영향을 미치는 것으로 파악되었다. 본 연구 결과는 향후 웰에이징 교수자 선발과 역량진단의 기초자료로 활용될 수 있을 것으로 판단된다. The study aims to provide basic data to strengthen well-aging instructors’ professionalism and enhance the quality of education in the field of well-aging education by analyzing the relationship between well-aging instructors’ intrapersonal intelligence and educational competence. The subject of the study were 393 professionals in the field of well-aging education. Data were collected by an online survey conducted by Gallup Korea from November 14, 2022, to January 16, 2023. Frequency analyses, reliability analyses, independent sample t-tests, one-way ANOVA, post hoc analyses, correlation analyses, and multiple linear regression analyses were performed by using SPSS Statistics 29.0. The summary of the study results is as follows. First, the analysis results on the differences in intrapersonal intelligence and educational competence according to the age and educational experience of well-aging instructors confirm that the levels of intrapersonal intelligence and educational competency enhance as their age and educational experience increase. However, no significant difference was recorded by gender. Second, as a result of analyzing the effects of well-aging instructors" intrapersonal intelligence on educational competency, it was confirmed that all sub-factors had significant correlations with one another. It was also found that the sub-domains, such as self-planning, self-control and utilizing, and self-reflection, had positive effects on the overall educational competency in the order. The results of this study are expected to be used as basic data for selecting well-aging instructors and diagnosing their competence in the future.
A Study on the Recognition of Korea Armed Forces Nursing Academy and Military Nursing Officers through Web Crawling and Text Mining

국군간호사관학교(국간사)는 한 때 폐교될 위기에 처한 적이 있다. 기업과 마찬가지로 군대내 부대나 조직도 정체성을 스스로 진단하고 그 필요성을 입증해 나가지 않으면 그 존폐를 장담할 수 없을지 모른다. 국간사의 폐교 위기 전후 국간사와 간호장교의 역할에 대해 군 내부적으로 진단하는 연구가 있었지만 군 외부에서 바라보는 시각에 대한 연구가 없었기 때문에 정확한 진단을 하는 것이 제한되었다. 실제로 군 외부에서 국민들이 바라보는 시각에 대한 분석은 군의 신뢰도를 분석하는데 밀접한 관련이 있고 이러한 군의 신뢰도는 군의 무형적인 전투력인 사기와 연관되고 전투나 전쟁의 승패에 큰 영향을 미칠 수 있다. 본 연구는 국민들이 국간사와 간호장교를 대상으로 온라인상에서 2011년부터 2020년까지 개진한 방대한 양의 데이터를 웹크롤링을 통해 수집하고 텍스트마이닝 기법으로 인식도를 분석하였다. 분석시 사용한 K-Means 클러스터링과 Doc2Vec 기법은 의견으로 제시된 단어를 벡터화하고 주변 단어들과의 관련성을 유지하면서 군집 형성을 수행하는 기법을 적용함으로서 군집별 의미론적 분석의 신뢰성을 보장하고 있다. 본 연구 기법은 국간사와 간호장교를 군 외부에서 바라보는 인식을 텍스트마이닝의 토픽모델링 기법을 적용한 분석이라는 의의를 가지며 연구 결과 군 외부 인식이 긍정적임을 확인할 수 있다. The Korean Armed Forces Nursing Academy (KAFNA) once faced the possibility of being shut down. Just like enterprises, The survival of military units or organizations within the military cannot be guaranteed if they do not diagnose their identity and prove its necessity. On the other hand, an accurate diagnosis is limited because there has been no research on the roles of KAFNA and nursing officers from an external perspective before and after the crisis of the KAFNA closure. Indeed, analyzing external perspectives is closely related to analyzing the credibility of the military, and such credibility can have a significant effect on the outcome of battles or wars. This study used web-crawling and text-mining techniques to analyze a vast amount of data on KAFNA and nursing officers posted online from 2011 to 2020. The K-Means clustering and Doc2Vec techniques used in the analysis vectorize the words presented as opinions and perform clustering while maintaining the relevance with surrounding words, ensuring the reliability of semantic analysis by cluster. This research technique is the first text-mining technique to analyze the perception of KAFNA and nursing officers from an external perspective, and the study results show that the external perception is positive.
James Wimshurst's Electrostatic Immortality: Little is Known About the Man, But His Iconic Generators Live On

The British engineer engineer James Wimshurst did not invent the machine that bears his name. But thanks to his many refinements to a distinctive type of electrostatic generator, we now have the Wimshurst influence machine.
Dual-Modality Co-Learning for Unveiling Deepfake in Spatio-Temporal Space

The emergence of photo-realistic deepfakes on a large scale has become a significant societal concern, which has garnered considerable attention from the research community. Several recent studies have identified the critical issue of “temporal inconsistency” resulting from the frame reassembling process of deepfake generation techniques. However, due to the lack of task-specific design, the spatio-temporal modeling of current methods remains insufficient in three critical aspects: 1) inapparent temporal changes are prone to be undermined compared to abundant spatial cues; 2) minor inconsistent regions are often concealed by motions with greater amplitude during downsampling; 3) capturing both transient inconsistencies and persistent motions simultaneously remains a significant challenge. In this paper, we propose a novel Dual-Modality Co-Learning framework tailored for these characteristics, which achieves more effectual deepfake detection with complementary information from RGB and optical flow modalities. In particular, we designed a Multi-Scale Motion Regularization module to encourage the network to equally prioritize both the significant spatial cues and the subtle temporal facial motion cues. Additionally, we developed a Multi-Span Cross-Attention module to effectively integrate the information from both RGB and optical flow modalities and improve the detection accuracy with multi-span predictions. Extensive experiments validate the effectiveness our ideas and demonstrate the superior performance of our approach.
Use of Swarm intelligence algorithms in Internet of Things-based systems: A Comprehensive review

This paper focuses on reviewing the recent work of Swarm Intelligent based algorithms in optimizing the problems of IoT systems. For this, a bibliometric analysis using different databases was done, to select the quality papers to highlight the latest development of Swarm based algorithms in IoT. This will help the researchers to gain an insight of the advancement in this area. To add novelty to the work, highlighted latest Swarm Intelligent algorithms along with its latest variants being used in IoT and the domains of IoT which can be solved using Swarm based algorithms. Researchers can use this study as a guide to identify the best SI-based algorithm being used for the IoT-based systems in the future.
MICROBIOLOGICAL AND PHYSICO-CHEMICAL QUALITY OF BOREHOLE WATER FROM THE MINI AND MAIN CAMPUS OF THE FEDERAL POLYTECHNICS OFFA, KWARA- STATE, NIGERIA

This study was undertaken to investigate the microbiological and physico -chemical quality of boreholes water from the mini and main campus of the Federal Polytechnics Offa, Kwara state, Nigeria.The bacteriological agents were isolated and identified by cultural characteristics, Gram staining, and biochemical tests.The total number of seventeen boreholes water (Ten from mini campus and seven from main campus) were collected water into sterile sample bottles.The total aerobic plate counts ranged from 1.3 x 10 2 to 5.4 x 10 3 while the total salmonella shigella counts ranged from 1.1 x 10 2 to 2.0 x 10 4 cfu/ml.The total coliform counts ranged from 0.8 x 10 2 to 2.0 x 10 4 while the total staphylococci counts ranged from 1.1 x 10 2 to 2.7 x 10 4 cfu/ml.The total fungi count ranged from 1.2 x 10 4 to 3.5 x 10 4 sfu/ml.The microorganisms that were isolated from the borehole water sample were Clostridium spp, Staphylococcus aureus, Enterobacter spp, Streptococcus spp, Klebsiella spp, Shigella spp, Proteus spp, Salmonella spp, Bacillus spp, Pseudomonas aeruginosa, Legionella pneumophilia, Penicillium spp, Aspergilus niger, Penicillium chryhsogenum and Clavispora spp.For the physico-chemical results, the P h ranged from 6.94 to 8.93 while the temperature ranged from 27 to 28.The turbidity ranged from 8.58 to 143.20 NTU while the total dissolved solute ranged from 9.50 to 139.00 mg/l.The alkanity of ranged from 10.00 to 36.67mg/l, while total hardness of the water ranged from 6.00 to 116.67 mg/l.The total dissolved oxygen ranged from 4.4 to 6.3 ppm while the total chloride ranged from 31.75 to 85.00 mg/l.The concentration of calcium ranged from 4.00 to 63.33 mg/l while that of magnesium ranged from 1.00 to 22.00 mg/l.The concentration of Zinc ranged from 0.1192 to 0.5121 while that of copper ranged from 0.001 to 0.277.The concentration of iron ranged from 0.00 to 0.067 while that of Cadmium ranged from 0.00 to 0.0006.Some of the borehole water sources fell below the standards approved by WHO and NAFDAC.The isolation of coliform bacteria in this study is an indication that if not check an outbreak could occur in the near future.Regular water quality monitoring and appropriate treatment measures are essential to mitigate these implications and ensure safe drinking water.
Developer Goals for e-Commerce Startups: Applying AI-enhanced Mind Genomics to Thinking about Everyday Issues

Retailers, the brands they carry, and internet service providers are increasingly criticized by privacy advocates and regulators for using data collected from consumers to develop detailed profiles on each one to tailor the commercial experience and to precisely target their messages.In response, most data collectors now offer opt-out methods to limit the data collection, its uses, and sharing with third parties, but doing so is not obvious.There is a widespread growing belief or, at the very least, a loudly expressed recognition, that data created by an individual belongs to them and should be controlled by them, similar to the requirements set forth in the EU's 2018 General Data Protection Regulation [1].Our world is inundated with data.As the speed and volume of data increase, our ability to form scientific questions, track trends, or subject the rapid pace of life to scientific inquiry is lost.Amidst massive amounts of data and massive optimization opportunities, it becomes increasingly hard to 'think slow' .We are accustomed to the slow, majestic, ingrained, now entrenched system of hypothetico-deductive reasoning [2].It is a basic concept that scientists, or even individuals, can 'advance, ' when they form a hypothesis and test it rigorously, trying to falsify the hypothesis.As technology speeds up the production of data and its acquisition, it is also necessary to accelerate knowledge and thought.In the harder sciences like biology and chemistry it may take exceptional creativity
Conceptual Model for Star Schema Data Warehouse

Conceptual modelling plays a critical role in the efficient and scalable design of data warehousing solutions, particularly for star schema architectures.In a star schema data warehouse, data is structured around a central fact table encircled by dimension tables, facilitating simple and high-performance querying.This article presents a comprehensive approach to conceptual modelling for star schema data warehouses, emphasizing the underlying design principles and techniques.The proposed methodology focuses on identifying crucial business dimensions and measures, establishing dimension hierarchies, defining table relationships, and ensuring data integrity and consistency.Additionally, the article explores the integration of advanced concepts such as slowly changing dimensions and degenerate dimensions to handle evolving data and eliminate redundancy.The advantages of adopting the conceptual modelling approach for star schema data warehouses are highlighted, including improved query performance, enhanced data accessibility, and simplified data analysis.Practical implementation and case studies are provided to demonstrate the effectiveness of the proposed approach, offering valuable insights for data warehouse practitioners
Design of a fiber cavity ion trap for a high-efficiency and high-rate quantum network node

The main purpose of this paper is to design a novel coupled system of an ion trap and a fiber cavity. This integrated solution is achieved by fabricating a fiber cavity with a metal mask on the side and end faces of the fiber. The fiber cavity with the metal mask can transmit light and electric charges, and the metal mask on the fiber end-face can shield electric charges on the dielectric high-reflection film. This system is designed to trap a single &lt;inline-formula&gt;&lt;tex-math id="M1"&gt;\begin{document}$ ^{138}\text{Ba}^{+} $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M1.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M1.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt; ion and realize coupling of the fiber cavity to the fluorescence at a 493 nm wavelength of &lt;inline-formula&gt;&lt;tex-math id="M2"&gt;\begin{document}$ ^{138}\text{Ba}^{+} $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M2.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M2.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt;. To efficiently collect fluorescent photons, we perform a theoretical analysis of the overall system to achieve optimal coupling of each individual part. The cavity length is designed to be &lt;inline-formula&gt;&lt;tex-math id="M3"&gt;\begin{document}$ 250 $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M3.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M3.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt; μm, and the optimized coupling parameters are &lt;inline-formula&gt;&lt;tex-math id="M5"&gt;\begin{document}$(g,\kappa,\gamma)/2{\text{π}}=(55,\;105,\;20)$\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M5.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="JUSTC-2023-0005_M5.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt; MHz. We also improve the stability and reliability of the system by analyzing the vibration, performance of the ion trap, and thermal stability. The core of the system is composed of materials with similar thermal expansion coefficients to improve thermal stability. The system uses spring connections to isolate vibrations inside and outside the vacuum chamber. We theoretically solve the difficulties of manufacturing the coupled system and have completed the experimental verification of some key technologies. The whole system is expected to be extended into a complex quantum network system to realize quantum computation and communication.
Thank You to Our 2022 Peer Reviewers

Abstract Members of the editorial board of the Journal of Geophysical Research — Earth Surface express their appreciation to those who served as peer reviewers for this journal in 2022.
MVCE-Net: Multi-View Region Feature and Caption Enhancement Co-Attention Network for Visual Question Answering

Visual question answering (VQA) requires a deep understanding of images and their corresponding textual questions to answer questions about images more accurately. However, existing models tend to ignore the implicit knowledge in the images and focus only on the visual information in the images, which limits the understanding depth of the image content. The images contain more than just visual objects, some images contain textual information about the scene, and slightly more complex images contain relationships between individual visual objects. Firstly, this paper proposes a model using image description for feature enhancement. This model encodes images and their descriptions separately based on the question-guided co-attention mechanism. This mechanism increases the feature representation of the model, enhancing the model’s ability for reasoning. In addition, this paper improves the bottom-up attention model by obtaining two image region features. After obtaining the two visual features and the spatial position information corresponding to each feature, concatenating the two features as the final image feature can better represent an image. Finally, the obtained spatial position information is processed to enable the model to perceive the size and relative position of each object in the image. Our best single model delivers a 74.16% overall accuracy on the VQA 2.0 dataset, our model even outperforms some multi-modal pre-training models with fewer images and a shorter time.
Deterioration of pre-war and rehabilitation of post-war urbanscapes using generative adversarial networks

The urban built environment of contemporary cities confronts a constant risk of deterioration due to natural or artificial reasons. Especially political aggression and war conflicts have significant destructive effects on architectural and cultural heritage buildings. The post-war urbanscapes demonstrate the striking effects of the armed conflicts during the hot war encounters. However, the residues of the urbanscapes become the actual indicators of damage and loss. Since today we can make future predictions using a variety of machine learning algorithms, it is possible to represent hybrid projections of urban heterotopias. In this context, this research proposes to explore dystopian post-war projections for modern cities based on their architectural styles and demonstrate the utopian scenarios of rehabilitation possibilities for the damaged urban built environment of post-war cities by using generative adversarial network (GAN) algorithms. Two primary datasets containing the post-war and pre-war building facades have been given as the input data for the CycleGAN and pix2pix GAN models. Thus, two different image-to-image GAN models have been compared regarding their ability to produce legible building facade projections in architectural features. Besides, the machine learning process results have been discussed in terms of cities’ utopian and dystopian future predictions, demonstrating the war conflicts’ immense effects on the built environment. Moreover, the immediate consequence of the destructive aggression on tangible and intangible architectural heritage would become visible to inhabitants and policymakers when the AI-generated rehabilitation potentials have been exposed.
EYE CONTROLLED ENDOSCOPY - A BENCHTOP TRIAL OF A NOVEL ROBOTIC SYSTEM

Imperial College London, United Kingdom.
Urdu Semantic Parsing: An Improved SEMPRE Framework for Conversion of Urdu Language Web Queries to Logical Forms

The paper presents a semantic parser for Urdu language web queries about the journal’s dataset. It is built on the Sempre framework and trained using natural language paraphrases of logical queries from the Tehqeeqat domain. The parser uses linguistic information, including part of speech (POS), skip-bigrams, word alignment, and paraphrases. Sempre can be used on a new domain with zero training examples. In this methodology, First, we used domain-specific and domain-general grammars to generate canonical utterances paired with logical forms. The canonical utterances are meant to capture the meaning of logical forms, and logical forms cover the meaning of the set of compositional operators. These queries are then paraphrased carefully, keeping the semantics of the original query. The result data set containing utterances, paraphrases, and logical forms was used to train the semantic parser. Our semantic parser performs well on domain-specific queries and can be easily trained on a new domain.
Deletion and Recovery Scheme of Electronic Health Records Based on Medical Certificate Blockchain

The trusted sharing of Electronic Health Records (EHRs) can realize the efficient use of medical data resources. Generally speaking, EHRs are widely used in blockchain-based medical data platforms. EHRs are valuable private assets of patients, and the ownership belongs to patients. While recent research has shown that patients can freely and effectively delete the EHRs stored in hospitals, it does not address the challenge of record sharing when patients revisit doctors. In order to solve this problem, this paper proposes a deletion and recovery scheme of EHRs based on Medical Certificate Blockchain. This paper uses cross-chain technology to connect the Medical Certificate Blockchain and the Hospital Blockchain to realize the recovery of deleted EHRs. At the same time, this paper uses the Medical Certificate Blockchain and the InterPlanetary File System (IPFS) to store Personal Health Records, which are generated by patients visiting different medical institutions. In addition, this paper also combines digital watermarking technology to ensure the authenticity of the restored electronic medical records. Under the combined effect of blockchain technology and digital watermarking, our proposal will not be affected by any other rights throughout the process. System analysis and security analysis illustrate the completeness and feasibility of the scheme.
Social Engineering as a Tool of Crime Committed by Criminal Communities

The report states that social engineering involves techniques, methods and technologies that allow criminals to obtain confidential information necessary to steal money from bank cards from the victims themselves.
NTRU_ SSS: Anew Method Signcryption Post Quantum Cryptography Based on Shamir’s Secret Sharing

With the advent of quantum computing, numerous efforts have been made to standardize post-quantum cryptosystems with the intention of (eventually) replacing Elliptic Curve Cryptography (ECC) and Rivets-Shamir-Adelman (RSA). A modified version of the traditional N-Th Degree Truncated Polynomial Ring (NTRU) cryptosystem called NTRU Prime has been developed to reduce the attack surface. In this paper, the Signcryption scheme was proposed, and it is most efficient than others since it reduces the complexity and runs the time of the code execution, and at the same time, provides a better security degree since it ensures the integrity of the sent message, confidentiality of the data, forward secrecy when using refreshed parameters for each session. Unforgeability to prevent the man-in-the-middle attack from being active or passive, and non-repudiation when the sender can’t deny the recently sent message. This study aims to create a novel NTRU cryptography algorithm system that takes advantage of the security features of curve fitting operations and the valuable characteristics of chaotic systems. The proposed algorithm combines the (NTRU Prime) and Shamir's Secret Sharing (SSS) features to improve the security of the NTRU encryption and key generation stages that rely on robust polynomial generation. Based on experimental results and a comparison of the time required for crucial exchange between NTRU-SSS and the original NTRU, this study shows a rise in complexity with a decrease in execution time in the case when compared to the original NTRU. It’s encouraging to see signs that the suggested changes to the NTRU work to increase accuracy and efficiency.