Reviewerly/exHarmony huggingface dataset:
Using linked data notifications to assemble the scholarly record on the decentralised web

In this presentation we present the results of the Mellon funded Scholarly Communication project that proposes a decentralised architecture for generating, propagating and notification of artefact lifecycle information in scholarly networks. Scholarly artefacts go through many stages from the creation of artefacts, through the registration of these artefacts in repositories, requesting certification at a publisher websites where they will be peer-reviewed and eventually published, to the archivation in a (web) archive. The results of each of these events are typically stored in different environments that are rarely interconnected. This makes assembling the complete lifecycle of artefacts an expensive post-factum endeavour involving mining many information sources and applying heuristics to combine the information into a meaningful result.The Mellon Scholarly Communication project proposes a researcher-centric, institution-enabled scholarly communication system aligned with Decentralised Web concepts and technologies. In this vision researchers use a personal domain and associated storage space (researcher pod) as their long-term scholarly hub. Using Linked Data Notifications these scholarly hubs communicate with service hubs (such as peer review systems, discovery systems, archives) for the fulfilment of the functions of scholarly communication. The research pod stores all the information pertaining to the artefacts that the researcher contributes to the scholarly record where it can be shared and consulted.
Radar based obstacle detection in unstructured scene.

To solve the problem of obstacle detection in unstructured scene, we propose a novel obstacle detection method based on Radar. Compared with other sensors like 3D-Lidar and color camera, Radar has higher environmental robustness especially for sandy road with dust. According to the relative velocity information of detected obstacles, obstacles are divided into static ones and dynamic ones in the proposed method. For static obstacles, map reconstruction based on Bayesian probability model is used to overcome the problem of sparse obstacle detection result in single frame and obstacle retention in the blind area. The integrated navigation system of GNSS and IMU is used to provide position and posture information during map reconstruction. For dynamic obstacles, the historical trajectory of the same target is recorded in the global coordinate frame, then the Kalman predictor based trajectory tracking and prediction is used to predict the movement trend of moving obstacles. The proposed method has been verified in a variety of unstructured scene. The experimental results show that the proposed method can provide useful obstacle perception result and meet the autonomous navigation application of UGV in unstructured scene. We also compare the proposed method with that based on 3D-Lidar in terms of the same scene. And it has obvious advantages in environmental robustness.
CHALLENGES OF CONTEMPORARY PREDICTIVE POLICING

Big data algorithms developed for predictive policing are increasingly present in the everyday work of law enforcement. There are various applications of such technologies to predict crimes, potential crime scenes, profiles of perpetrators, and more. In this way, police officers are provided with appropriate assistance in their work, increasing their efficiency or entirely replacing them in specific tasks. Although it needs to be technologically advanced, police use force and arrest, so prediction algorithms can have significantly different, primarily drastic consequences than those that similar technologies would produce in agriculture, industry, or health. For the further development of predictive policing, it is necessary to have a clear picture of the problems it can cause. This paper discusses modern predictive policing from the perspective of challenges that negatively affect its application.
Smart Voting System using Blockchain Technology

India is the world’s largest democratic country with a population of more than one billion; India has voters of more than 668 million and with 543 parliamentary constituencies. Voting is the vital right of people democratic countries used in formation of government. The last decade have brought a focus on to the technology used in the voting machines. The currently used voting machines systems has many security flaws, and it is hard to prove simple security issues. A voting system can be proven correct has many issues. There are some reasons for the government to use electronic voting systems. Main reasons are to increase elections activities and to reduce the elections expenses. There is scope to work on electronic voting system. There is no way of identification with the electronic voting system that the user is legitimate or not and locking electronic voting machine for culprit. The proposed system is to develop a congenial voting machine with maximum security by using Blockchain technology in to increase security and transparency between the users. The proposed system assures two-way user authentication. The first layer authenticates user with the help of login plus OTP. The second layer addresses issues of secrecy and integrity using blockchain technology.
A Descriptive Study of Students’ Perceptions toward the Focus of Learning English for Specific Purposes: EAP in English Educational Field

The article aims to describe the students’ perceptions toward the focus of learning English for specific purposes: EAP in the English Educational Field after the students had learned English for specific purposes course. A quantitative approach was used to process the questionnaire data analyzed statistically, and a qualitative approach with a descriptive study was conducted to answer the problem of this study. The researcher used a a closed questionnaire and document of observation to the 6th-semester students of Islamic Institute of Hasanuddin, Pare Kediri in the academic year 2020/2021. The result of this study from a closed questionnaire indicates that students' perceptions toward the focus of learning ESP: EAP in the English Educational Field refers to a very strong group with 88,8% based on the score interpretation criteria. It was also proved from 34 respondents answering 15 points related to data sources that the average percentage in the strongly agreed was 56 %, agreed was 35%, doubtful was 6%, disagreed was 3%, and strongly disagreed was 0%. Therefore, it can be concluded that although the students had different perceptions, they were able to focus more on learning English for specific purposes or academic-related English or based on their field or needs. The result of observation obtained from the field as data sources was the involvement of the students’ needs towards the particular use of vocabularies and the use of tactics to accomplish the target of learning English for specific purposes/ English for academic purposes through presentation and negotiation. Keywords: Students’ perceptions, English for specific purposes, English for academic purposes
Knowledge-Based Construction of Confusion Matrices for Multi-Label Classification Algorithms using Semantic Similarity Measures.

So far, multi-label classification algorithms have been evaluated using statistical methods that do not consider the semantics of the considered classes and that fully depend on abstract computations such as Bayesian Reasoning. Currently, there are several attempts to develop ontology-based methods for a better assessment of supervised classification algorithms. In this research paper, we define a novel approach that aligns expected labels with predicted labels in multi-label classification using ontology-driven feature-based semantic similarity measures and we use it to develop a method for creating precise confusion matrices for a more effective evaluation of multi-label classification algorithms.
DETERMINING LEARNING SUCCESS of kNN ALGORITHM on ZOO DATASET

People learn by examining, observing and researching their environment. They actually gains experience from what they have learned. By using the experience they have gained, they can adapt to the new situation they encounter and make decisions. People always make decisions by comparing their previous knowledge while describing objects and classifying them. Similarities and differences to previously learned objects are very effective in decision making. It has been shown in the studies that the experiential learning method can also be used on machines. Intelligent machines and devices that use machine learning methods in their structure are widely used in many areas. Machine learning can be performed using different algorithms. These algorithms use the attributes of the objects in the data set when making decisions. Similarities and differences in the attributes of objects are obtained by comparing them with previous experiences. As a result of the comparison, a decision is made and predictions are made about the classes of the objects. In this study, kNN machine learning algorithm, which is a supervised learning method, was used on the Zoo dataset. In this data set, there are attributes of common living things. By using these attributes, the classes of living things in the data set are determined. The “k” neighbor value and weight parameter selected in the kNN algorithm affect the learning success. In this study, the effect of two parameters used in the kNN algorithm on learning success is shown. According to the results obtained, the "k=1" neighbor value and the "Distance Weight" parameter were selected and the highest success result was obtained.
Poroelastic coupling effects on spatio-temporal patterns of 2016-2018 Pohang earthquakes.

and subsequent stress transfer through a rigid and low-permeability rock to the fault. This study demonstrates that the proper mechanistic model and optimal well operations need to be accounted for to mitigate unexpected seismic hazards in the presence of the site-specific uncertainty such as hidden/undetected faults and stress regime.
HUBUNGAN KEGEMARAN MEMBACA DENGAN KEMAMPUAN MENGARANG SISWA DI SDN TANGGUL REJO 2 KECAMATAN TABUNGANEN KABUPATEN BARITO KUALA

This research was conducted with the aim of finding out the relationship between reading fondness and the ability to compose students at SDN Tanggul Rejo 2, Tabunganen District, Marabahan Regency. SDN Tanggul Rejo 2, Tabunganen Subdistrict is made as a place for research, while the object of research is about the relationship of reading fondness with the ability to compose students in SDN Tanggul Rejo 2, Tabunganen District, while the research subjects are all grade V students at SDN Tanggul Rejo 2, Tabungenen District.The population of this study was all students of class V at SDN Tanggul Rejo 2, amounting to 45 students and a sample of 45 students was determined using saturated sampling techniques. The research method used is quantitative descriptive method, while the data digging tool used is a questionnaire for reading fondness and composing tests for writing ability. Validity test is done is to use the Product Moment Collation formula. Obtained the results of 26 statements worthy of use from 32 statements that exist to determine the fondness of reading. Reliability was calculated using the Alpha Cronbach technique which showed 0.97 results so that it was declared reliable with a very strong relationship level. Analysis of the data used uses the statistical analysis of Product Moment Collation.The results of statistical analysis using the Product Moment Collation technique obtained a calculated value of 0.711. Meanwhile, the price of table with N = 45 at the 5% significance level, which is 0.294. From these results it can be seen the value of r count > r table, this shows that there is a relationship between reading fondness in writing ability of fifth grade students who are categorized as less.
Intelligent Collection of Detection Data and Automatic Generation of Report Based on LabVIEW in ABS Adhesion Coefficient Utilization Test

The automobile anti-lock braking system (ABS) is a hot spot in the current research and development of automobiles. The country also has corresponding standards for its performance requirements and test methods. Among them, the utilization rate of the adhesion coefficient is one of its important performance evaluation indicators. In the adhesion coefficient utilization test, the post-processing workload of the data is large, and the authenticity of the data is crucial to the test results. In order to overcome the shortcomings of manual reporting, which takes a long time and is prone to human errors. Based on the LabVIEW platform, this paper constructs a method for automatic generation of test reports, and designs a comprehensive program for automatic report generation. Experimental shows that the use of integrated automation software to issue an adhesion coefficient utilization test report can reduce data post-processing work and greatly improve the efficiency and accuracy of the report.
Android Based Application For Immersive Image Processing Learning

This project aims to develop an Immersive Image Processing learning application to assist in the Image Processing lecture class for Faculty of Electronic and Electrical Engineering (FKEE), in University Tun Hussein Onn Malaysia (UTHM). The immersive Image Processing learning application focuses on seven important modules covered in the Image Processing syllabus. The Graphical User Interface (GUI) development of Android based for Immersive Image Processing learning application is implemented by using Android Studio software. The portability of the Android Image Processing learning application makes users easier to learn image processing and editing image at anywhere and anytime. The application is provided with the notes of the seven modules to users more understanding with the theory. The performance analysis of the Image Processing learning application is evaluated through data collection from survey conducted. Immersive Image Processing learning application market test survey discusses the awareness of respondents on Android Studio software, basic knowledge of respondents in Image Processing course and the implementation of existing Image Processing learning application. In a meanwhile, performance review discusses the performance analysis of the Immersive Image Processing learning application. 100% of the respondents agreed that the application was extremely helpful in assisting in better understanding in image processing.
the plasma cutting Rancang Bangun Mesin Potong Plat Menggunakan Plasma Cutting: plasma cutting

Metal cutting technology in Indonesia is increasingly developing with various cutting methods, one type of cutting used in industry is metal cutting using plasma cutting. In the Mechanical Workshop of the Caltex Riau Polytechnic the metal cutting process has used plasma cutting, as for the maximum air pressure required for the metal cutting process in the design of a plate cutting machine using a maximum 6 Bar plasma cutting, and a maximum current variation of 60A-90A with a plate thickness of ≤ 5mm which will be cut. The compressor is needed to design a plate cut machine with a maximum air pressure capacity of 12 Bar with a power of 7.5 KW on a 3-phase motor as a driving force. The plate cutting plan uses a plate cutting machine design using plasma cutting driven using an electric motor with a torque planning of 0.92Nm as a driving source, and the resulting movement is in the same direction as the horizontal axis (back and forth). From the results of the machine design, it can produce cuts at plate thickness of 1mm, 2mm and 3mm with a maximum current of 70A, and a maximum wind pressure of 4 bar at a distance of 1mm from the torch to the iron plate with a maximum motor movement of 10rpm on horizontal cutting, while at 4mm and 4mm plate thickness. 5mm with a maximum current of 90A, and a wind pressure of 6 bar at the torch to plate distance is 1mm, with a motor movement of 5 rpm on horizontal cutting. The purpose of this tool design is to make a machine to assist plasma cutting which produces horizontal cuts on a plasma cutting machine with a more stable cutting movement. after testing at the time of cutting the iron plate. For the most effective results using a speed of 5 rpm, a wind pressure of 6 bar, a tilt angle of 90o, a current of 90A, and a distance of the torch on the plate 1 mm.
The Influence of Teachers' Corrective Feedback on the Accuracy of English Writing

Feedback plays a vital role in writing. Corrective feedback can be defined as the feedback input of teachers to students in writing. In order to explore influence cognitive factors on students' writing accuracy under teachers' corrective feedback, this study uses sample survey, data analysis and drawing method to analyze corrective feedback and streamline the algorithm. The subjects are 66 students from the 6th class of the first high school in a certain county, and the follow-up study lasted for two months. In addition, for comparative analysis, 66 students were divided into two groups, experimental group and the control group. The results showed that most students believe that teachers' corrective feedback can improve writing accuracy, which basically realized the purpose of this study, and pave the way for further research.
THE EVALUATION OF USER`S REPRESENTATION OF PERSONAL COMPUTER

Relevance. The increasing complexity of technical devices used by humans and the high rate of emergence of new devices and their functions lead to the emergence of various practices and habits of working with them. It is possible to see a specific representation of what a personal computer (PC) consists of and how it works for each of these practices. This representation has developed in the process of working with a PC as its mental model. However, the task of reconstructing these models and comparing different respondents with each other according to the specifics of their understanding of the PC does not have the necessary methodological support. It is necessary to get representations of PC in a comparable form to effectively compare the different people`s/group`s representations of PC with each other and study their mental models, preserving the qualitative specifics of these “images of PC”. The purpose of this work is to empirically approbate the technology of reconstructing the representations of PC users about the computer itself as a multidimensional psychological space of descriptions of its work. Methods. Methods of group interviews and card sorting were used to collect descriptions of “how PC works”, multidimensional scaling methods were used to reconstruct representations of PC among groups of study participants. Results. We have reconstructed and described the representations about the work of the PC of three groups of users — schoolchildren (N = 22), programmers (N = 22) and ordinary adults without special education (N = 21) as multidimen-sional spaces of descriptions of the work of the PC. We identified the bases of classification of PC operation descriptions for each group of users and develop a technology for analyzing the results of studying their representations about PC as latent characteristics that form the basis of classification of PC operation descriptions.
Total recall: obtaining value ‘on demand’ from unstructured and structured data

Disclaimer Text and Data Mining. Any automated analytical technique aimed at analysing text and data in digital form in order to generate information including - but not limited to - patterns, trends and correlations (so-called Text and Data Mining) may only be applied if it is done by a research organisation or cultural heritage institution solely for the purpose of (non-commercial) scientific research as mentioned in Clause 3 of Directive (EU) 2019/790 (the Digital Single Market Directive) and Clause 15n of the Dutch Copyright Act [Auteurswet]. Text and Data Mining for commercial purposes is not allowed; all rights in this respect are reserved pursuant to Clause 4 paragraph 3 of the Digital Single Market Directive and Clause 15o paragraph 1 of the Dutch Copyright Act.
The Application of Visual Vocabulary for ESL Students’ Vocabulary Learning

Vocabulary is often neglected despite being one of the most crucial aspects of language acquisition. Due to the lack of emphasis on vocabulary learning, ESL students have issues in learning the English language effectively, which resulted in low-level language proficiency. Hence, this paper attempts to address this problem by introducing Visual Vocabulary to learn the target words. The main research question: How effective is the use of the Visual Vocabulary to learn vocabulary for Form Two learners? To investigate the effectiveness of the use of the Visual Vocabulary, 60 students of Form Two from sub-urban schools in Ipoh and Teluk Intan, Perak, were selected. These students were instructed to learn a total of 45 target words and Visual Vocabulary was applied to assist them to learn and simultaneously understand the meaning of the target words. The independent sample t-test, paired sample t-test, and descriptive statistics were used to analyze the scores of the pre and post-tests. The score comparison and total improvement score in percentage were also presented. The paired sample t-test results are (t=-17.85, df=29, p<.05) for the experimental group and (t=-4.85, df=29, p<.05) for the control group. Based on the stated results, both experimental and control groups improved significantly (p=.000*) in the post-test with a mean difference of 15.62. The results of this study confirm the effectiveness of Visual Vocabulary in learning and understanding the target words. This approach is proven to increase the success rate of vocabulary learning among ESL learners.
Visual acoustical performance analysis and storytelling

With photo-enabled sound intensity systems acoustical practitioners can investigate and understand the root cause of acoustical performance previously unavailable to our industry. This seminar will show examples of measured performances that show the opportunities, limitations, and opportunities for acoustical assessment with this unique technology. See case studies on rapid prototyping, performance validation, and challenges to common “rule of thumb" approaches.
Real-Time Object Detection and Localization System with Mild Artificial Intelligence

This project is about the detection and localization of an object, implemented using MATLAB simulation software, in order to replace work that requires human vision and produce higher throughput and better efficiency. This project aims to develop a system that uses a built-in camera of a laptop as an input to detect an object, identify the class of the object and locate the position of the object in a real-time video. The system will go through three stages of development which are, training preparation, training process, and performance evaluation. A random number of images will be fed into the system to evaluate the performance of the system, and the result obtained will be classified into three classifications (TP, FP, and FN). More input data used to train a system will produce better accuracy and performance. The surface area of an object is another key factor that helps the system to increase its performance.