Reviewerly/exHarmony huggingface dataset:
PERANCANGAN SISTEM INFORMASI PERTANIAN BERBASIS WEB PADA DINAS PANGAN, TANAMAN PANGAN DAN HORTIKULTURA

&lt;p&gt;&lt;em&gt;This study aims to design an agricultural information system using the MySQL database programming language at the Riau Province food, agriculture and horticultural service by using the Design Unified Modeling Language (UML) modeling, one of the advantages of this system is the availability of fast information services. For agencies, this is the right way to share programs or services not only to employees but also to the public directly. The fact is that this information information system not only provides information online, but also with service value. It is hoped that the system that the authors develop This can be a place of service for all agencies, so that the design can be useful for the food, food plants and horticulture office of Riau province to develop the official website.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Agricultural Information Systems, Website&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;This study aims to design an agricultural information system using the MySQL database programming language at the Riau Province food, agriculture and horticultural service by using the Design Unified Modeling Language (UML) modeling, one of the advantages of this system is the availability of fast information services. For agencies, this is the right way to share programs or services not only to employees but also to the public directly. The fact is that this information information system not only provides information online, but also with service value. It is hoped that the system that the authors develop This can be a place of service for all agencies, so that the design can be useful for the food, food plants and horticulture office of Riau province to develop the official website.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Agricultural Information Systems, Website&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;&lt;br /&gt;&lt;/em&gt;&lt;/p&gt;
Link Prediction on Dynamic Heterogeneous Graphs via GNN with Multiple Attention Mechanisms

Link prediction on dynamic heterogeneous graphs has attracted much attention in recent years, because it is an ideal abstract model of many problems in real application, such as the prediction of customer’s consuming behavior in electronic commerce. However, most existing link prediction methods are designed for homogeneous graphs and static heterogeneous graphs, which cannot perform well on dynamic heterogeneous graphs owing to lack of the ability of processing the dynamic information. In this paper, we propose a graph neural network (GNN) with multiple attention schemes to deal with the problem of link prediction on dynamic heterogeneous graphs. Specifically, the attention mechanism of the GNN learns the influences of the node features, the edge types and the transformation of dynamic heterogeneous graphs on link prediction. We evaluate our method on a real-world dataset which expresses the customer-commodity relations by a set of snapshots of dynamic heterogeneous graphs. Experimental result shows that our method outperforms the original method and other state-of-art baseline methods.
The Modified Cubature Kalman Filter for Relative Navigation of Space Target Tracking

Abstract At present, the trend of improving the mobility of fast acquisition, long-term tracking and high-precision control has been formed in China. The continuous observation ability of non-cooperative targets and good imaging performance in motion are important trends in the development of optical remote sensing technology. Aiming at the high-precision observation and real-time tracking requirements of high orbit space satellites, this paper studies the high-precision relative navigation of space non cooperative targets. In order to solve the problem that the estimation accuracy of Cubature Kalman filter (CKF) decreases when the system visibility is low, a modified Cubature Kalman filter (MCKF) based on the visibility is proposed. This algorithm defines a system visibility characterization method based on the error gain matrix of the filtering process, and proposes the visibility scaling parameter based on this method, The filter gain covariance matrix is adjusted online, so that the algorithm can adjust the weight of state prediction and system observation online according to the observability of the current time. Numerical simulation shows that compared with CKF, the estimation accuracy of MCKF is improved by about 4 times, and MCKF stabilizes faster and has higher accuracy.
From extended chunking to dependency parsing using traditional Arabic grammar

We describe in this paper the adopted approach combining a phrase structure grammar and dependency rules to develop AlkhalilPArser. The general architecture of this parser is composed of three main levels. The first level includes basic tasks such as tokenization, part-of-speech tagging, and chunking. The next level deals with analysis tasks such as managing common, internal and external dependencies according to the nature of the proposal. The last level detects and corrects anomalies. This parser is an extension to verbal sentences of a system previously designed for parsing the nominal sentences. Several modifications have been made to adapt this system to all types of sentences and improve its accuracy. The tests carried out on a representative corpus and the comparisons with other parsers testify to the robustness of our system.
Old crimes reported in new bottles: the disclosure of child sexual abuse on Twitter through the case #MeTooInceste

Abstract Movements such as #MeToo have shown how an online trend can become the vehicle for collectively sharing personal experiences of sexual victimisation that often remains unreported to the criminal justice system. These social media trends offer new opportunities to social scientists who investigate complex phenomena that, despite existing since time immemorial, are still taboo and difficult to access. They also bring technical difficulties, as the challenge to identify reports of victimisation, and new questions about the characteristic of the events, the role that victimisation testimonies play and the capacity to detect them by analysing their characteristics. To address these issues, we collected 91,501 tweets under the hashtag #MeTooInceste, posted from the 20 to 27 January 2021. A model was fitted using Latent Dirichlet Allocation that detected 1688 tweets disclosing experiences of child sexual abuse, with an accuracy of 91.3% [± 3%] and a recall of 93.1% [± 5%]. We performed Conjunctive Analysis of Case Configurations on the tweets identified as disclosures of victimisation and found that long tweets posted by users with small accounts, without URL or picture, were more likely to be related to disclosure of child sexual abuse. We discuss the possibilities of these trends and techniques offer for research and practice.
Analisis Portal Repository Tugas Akhir Mahasiswa (RAMA) Repositori Ristekdikti

Rama Ristekdikti is an integrated portal with institutional repositories in Indonesia that functions as information technology-based scientific communication. The number of institutional repositories on the Rama Ristekdikti portal is 171, this number is not comparable to the number of universities in Indonesia, which are 4,670 universities. From this, it is necessary to conduct further research on the Rama Ristekdikti portal. The method in this research is descriptive quantitative, data collection techniques by observation and literature study. While the data analysis using the percentage equation. The results of this study are obtained 170 repositories registered in the Rama Ristekdikti portal, 9 institutions have not yet known the webometric ranking. The development of the largest institutional repository in East Java province, both private and public. The applications used are dominated by 154 E-prints, while the majority of the languages ​​used are English. The most common type of content is student's final project. Meanwhile, the most documents uploaded to institutional repositories are Universitas Gadjah Mada. From the results of the discussion, there are several recommendations that can be given regarding the development of the Repository portal. Institutions should apply institutional repositories for those who have not applied, and institutions that have applied institutional repositories should immediately be integrated with the Rama Ristekdikti portal.&#x0D; &#x0D;
Mining the Health Information Needs of COVID-19 Patients Based on Social Q&amp;A Community

COVID-19 has become a global pandemic, and COVID-19 patients are in a medical dilemma with no effective treatment and no effective drugs. The questions and answers in the social Q&A community can reveal the characteristics and evolution rules of the health information needs of COVID-19 patients. Using the Q&A data in Baidu Zhidao ( https://zhidao.baidu.com/ ) as the research object, using the web crawlers to capture the data, automatic topic recognition on the acquired data by constructing an LDA topic model, exploring the content of COVID-19 patients' health information needs, and revealing the change rule of Q&A publication volume and health information need topics from the time dimension. Combining statistical information such as the number of answers, the number of likes, and the level of respondents, cluster analysis is used to reveal the changing rules of social characteristics and health information need topics. By analyzing the Q&A data on COVID-19 patients in Baidu Zhidao, it is found that the topic distribution of health information needs topic is relatively concentrated. Moreover, the number of Q&A and the types of health information needs to be changed in different development periods. There are differences in social characteristics that correspond to different topics of health information needs. Through in-depth analysis of the characteristics of health information needs of COVID-19 patients in the social Q&A community, on the one hand, it is beneficial for COVID-19 patients to obtain the required health information content timely. On the other hand, it is beneficial to optimize the community information display mechanism and improve the organization of information resources.
‘I Did Digital Tidying up for a More Adult Stage of Life’: Ritualistic Technology Appropriations During Life Transitions

Abstract Life transitions, such as the transition from childhood to adulthood, are often accompanied by meaning-making actions such as rituals. Rituals increasingly involve the use of interactive technology. While previous research has focused on specific contexts or technologies, a bird’s eye view of the many appropriation styles during life transitions is missing. To identify the range of technology’s appropriations, we analysed stories from 84 participants and compared these across different life transitions and technologies. We identified three roles interactive technology can play during life transitions: the role of (i) a facilitator easing the accomplishment of tasks within life transitions, (ii) an enabler creating opportunities for new transition rituals and (iii) a social actor that itself is the trigger or the content of transition rituals. We propose the three roles as a classification scheme to structure existing and future research and reflect on the design challenges and evaluation approaches.
Classification of racehorse limb radiographs using deep convolutional neural networks

To assess the capability of deep convolutional neural networks to classify anatomical location and projection from a series of 48 standard views of racehorse limbs.Radiographs (N = 9504) of horse limbs from image sets made for veterinary inspections by 10 independent veterinary clinics were used to train, validate and test (116, 40 and 42 radiographs, respectively) six deep learning architectures available as part of the open source machine learning framework PyTorch. The deep learning architectures with the best top-1 accuracy had the batch size further investigated.Top-1 accuracy of six deep learning architectures ranged from 0.737 to 0.841. Top-1 accuracy of the best deep learning architecture (ResNet-34) ranged from 0.809 to 0.878, depending on batch size. ResNet-34 (batch size = 8) achieved the highest top-1 accuracy (0.878) and the majority (91.8%) of misclassification was due to laterality error. Class activation maps indicated that joint morphology, not side markers or other non-anatomical image regions, drove the model decision.Deep convolutional neural networks can classify equine pre-import radiographs into the 48 standard views including moderate discrimination of laterality, independent of side marker presence.
Examination of Facial Convexity and Concavity Values With Reference to the External Acoustic Pore: A Retrospective Study

The human skull serves as an essential material for facial reconstruction. In particular, the petrous part of the temporal bone is vital due to its compact structure, which can resist mechanical forces. The study aims to give descriptive values to estimate the face shape and produce regression formulas through the external acoustic pore as a reference point. The study was carried out on 3-dimensional computed tomography images, a total of 83 adult images (45 females and 38 males) in the Department of Radiology of Bursa Uludag University Medical Faculty. The distances between the imaginary vertical line passing through the porion and the anthropometric points revealing the facial features were measured for the soft and hard tissue. The vertical distances between the soft and hard tissue landmarks were also measured for both sexes. Measurements were performed with the Image J program, and for the statistical analysis, SPSS 25.0 was used ( P < 0.005). Linear simple regression analysis was used to produce formulas to estimate the soft tissue thickness using hard tissue. Also, discriminant function analysis was performed to determine sex in the presence of an unknown skull. The descriptive values of the variables on the axial and vertical planes and the differences between sexes are given. Also, all formulas make accurate predictions of 90% or more. The authors tried to estimate the anatomical points that roughly reveal the facial features with the regression formulas developed using anthropometric measurements. The authors think that the shape of the face, which is more specific to the individual, can be reached more clearly using mathematical models, and the authors believe that this study will set an example for future studies.
Underwater low-light enhancement network based on bright channel prior and attention mechanism

At present, there are some problems in underwater low light image, such as low contrast, blurred details, color distortion. In the process of low illumination image enhancement, there are often problems such as artifacts, loss of edge details and noise amplification in the enhanced image. In this paper, we propose an underwater low-light enhancement algorithm based on U-shaped generative adversarial network, combined with bright channel prior and attention mechanism, to address the problems. For the problems of uneven edges and loss of details that occurred in traditional enhanced images, we propose a two-channel fusion technique for the input channel. Aiming at the problems of brightness, texture and color distortion in enhanced images, we propose a feature extraction technique based on the attention mechanism. For the problems of noise in enhanced output images, we propose a multi-loss function to constrain the network. The method has a wide range of applications in underwater scenes with large depth. This method can be used for target detection or biological species identification in underwater low light environment. Through the enhancement experiment of underwater low light image, the proposed method effectively solves the problems of low contrast, blurred details, color distortion, etc. of underwater low light image. Finally, we performed extensive comparison experiments and completed ablation experiments on the proposed method. The experimental results show that the proposed method is optimal in human visual experience and underwater image quality evaluation index.
Text validation: Overlooking discrepancies in question constructions.

There is converging evidence that readers monitor text coherence and consistency by immediate, nonstrategic processes of validation. The literature also offers numerous instances of deficient validation. A prominent example of the latter is that understanders tend to overlook discourse anomalies that are embedded in given (presupposed) sentence information. However, we previously documented reading time "consistency effects" (O'Brien & Albrecht, 1992) that exposed readers' sensitivity to both given and new text discrepancies in numerous declarative syntactic constructions (Singer et al., 2017; Singer & Spear, 2020). Five new experiments addressed these phenomena with reference to constructions regularly shown to mask discourse inconsistencies: namely, interrogatives. In striking contrast with declaratives, five interrogative conditions in four experiments yielded no significant consistency effect. Experiments 2-4 documented coincident consistency effects with declarative but not interrogative constructions. A fifth experiment denied that the interrogative-construction findings resulted from readers' lack of knowledge about critical concepts. The cognitive-scientific linguistic construct of verb resolutivity offers a possible basis for these outcomes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Classifying the Instructional Practice Types of Middle School Teachers and Exploring Predictive Factors: Evidence from TALIS 2018

Purpose: In this study, the instructional practice types of middle school teachers in Korea were derivedand important factors were explored to classify and predict each instructional practice type.&#x0D; Methods: The OECD TALIS 2018 data consisting of 2,308 middle school teachers and 148 middleschool principals in Korea was utilized as analysis data. Latent Profile Analysis(LPA) was conductedto derive instructional practice types, and random forest analysis was conducted to explore importantfactors in classifying and predicting each instructional practice type.&#x0D; Results: Five types of instructional practice for middle school teachers in Korea were derived: ‘Active’,‘Unconditional knowledge delivery’, ‘Student control-centered’, ‘Innovative pursuit’, and ‘Inactive’. Important factors classifying and predicting each instructional practice type were common factors(teacherefficacy, regular teacher teaching experience, number of students in target class, class time distribution,subjects) and unique factors(external teaching choice motivation, principal teaching experience, classautonomy, and teacher collaboration).&#x0D; Conclusion: Based on the results of this study, educational implications related to support accordingto the types of instructional practice of middle school teachers in Korea were proposed.
Analysis of the Relationship Between Stress, Self-efficacy, and Self-esteem on the Career Maturity of University Students Using GSCA-SEM

The purpose of this study is to confirm the relationship between stress, self-efficacy, and self-esteem and the mediating effect of self-esteem on career maturity in university students. 1,365 university students in the 14th(2020) of the ｢Youth Panel｣ conducted by the Korea Employment Information Service were selected as research subjects. The data of this study were analyzed through a structural equation model using SPSS 26.0 and GSCA Pro 1.1.8. First, university students' stress had a negative effect on self-esteem, but had no significant effect on career maturity. Second, self-efficacy had a significant positive effect on self- esteem and career maturity. Third, stress had a negative effect on career maturity with self-esteem as a fully mediating effect. Self-efficacy had a positive effect on career maturity with self-esteem as a partial mediating effect. The results of this study can be used as basic data for the development of a career support model to promote and strengthen the career maturity of university students.
Charity Box Based Camera and Security System Internet Of Things and Telegram

Theft in a place of worship is a crime by stealing things that are not privately owned but public propertywithout permission and these activities are carried out from religious places such as mosques, churches andmonasteries. The theft of charity box funds is an interesting topic for some people and the mosque manager personallyin particular, considering that charity box funds are general funds intended for the renovation or purchase of mosqueneeds and the needs of religious events. By using a microcontroller as an auxiliary component to monitor valuables.This microcontroller control system can be used to secure charity box funds in any mosque equipped with a securityfeature based on Selenoid door locks that can only be opened by ESP 32-CAM and using a vibration sensor will detectshocks and a buzzer will sound. sounds like an alarm for Telegram to alert the Mosque management in the event ofthe forced destruction of the charity box. So, looking at the source of the problem and technological developments ashappened before, it is very appropriate to use them to reduce the rampant theft in mosques. Therefore researcherswill design a tool, namely a camera system and security for charity boxes based on the internet of things and telegrams.
Design and implementation of earthquake information management system

Aiming at the problem of seismic data sharing occlusion, a seismic information management system is designed. Using Eclipse development platform, B/S architecture based on Internet technology (Browser/Server structure), based on Java language and MySQL database, information technology, digital technology as the core, according to the work needs to set six modules, so as to achieve the purpose of data sharing. The system fully collects, excavates and integrates earthquake information resources to form a social security system, in order to grasp earthquake information timelier. By registering and logging in, users can quickly view the earthquake information and give feedback. It is also very convenient for people to gather information about earthquakes to improve their knowledge about the disaster reduction and prevention. Doing so will help them become more aware of the various steps involved in the planning and implementation of a disaster.
Probabilistic data association algorithm based on adaptive robust Kalman filtering

The data association problem in cluttered environments is one of the difficult problems in the field of object tracking. When probabilistic data association algorithms are used in motion model deviation scenarios, incorrect tracking occurs. Combining the adaptive robust Kalman filter (ARKF) with the probabilistic data association (PDA), this paper presents the adaptive robust probabilistic data association (ARPDA) algorithm for estimating the target state in cluttered environments. The results of the experiment indicate that the proposed algorithm has higher tracking accuracy under the condition of motion model deviation compared with the traditional probabilistic data association algorithm.