Reviewerly/exHarmony huggingface dataset:
(MOLDING DESIGN OF PADANG STATE POLYTECHNIC LOGO SOUVENIR MOLDING ON PRESSED PLASTIC INJECTION MOLDING MACHINE 1,960 KG / CM²)

ABSTRACT&#x0D; Padang State Polytechnic has been established since 1987 under the name Polytechnic Engineering and then changed its name several times to the management policy by Andalas University then, until now it is independent until now with the name Padang State Polytechnic. The 33-year-old polytechnic of the Padang State Polytechnic establishment must have an icon, symbol and trinkets that have PNP characteristics so that they are easy to recognize and remember. Souvenirs are a form of applying media for promotion and souvenirs for people who already know and come to Padang State Polytechnic.&#x0D; Plastic injection molding machine is a machine used to mold plastics with a basic material in the form of plastic pellets. Plastic injection molding machine is the process of processing plastic material in the form of seeds which are heated until they become liquid and then injected into the molding which then freezes / hardens according to the shape of the mold. The products produced by injection molding machines vary, from electronic tools, automotive tools, home appliances, plastic souvenirs, to tableware. The success of the resulting product is highly dependent on Molding. The plastic injection molding machine has parts, namely the Injection Unit, Molding Unit and Clamping Unit. The Injection Unit and Clamping Unit are the most important parts in the manufacturing process of plastic products where the control operation is executed on the control panel found on the plastic injection molding machine. The control panel on the machine can adjust the amount of clamping pressure, stroke length, plastic volume, and temperature used.&#x0D; The molding unit is the main part of the plastic product manufacturing process. Mold (mold) is a tool / tool used to make products according to the desired design (shape and dimensions). Plastic molding has its respective functions, parts of the mold, namely Cavity and Core, Sprue, Runner and Gate, Undercut. The printing process on a Plastic Molding machine has several stages such as the cutting process, mold safety and machine safety, execution, product check, setting, execution, and final. Materials used in the Plastic Molding process are usually materials that are often used daily and are safe for use by all groups, such as Polyproplene, Polycarbonate, and High Density Poly Ethylene. The product that will be produced from the molding made is a key toy souvenir made of plastic, with a shape like the Padang State Polytechnic logo, measuring 6 cm long, 6 cm wide and 5 mm thick.&#x0D; The test results obtained will be shown through field applications, socialization at the Padang State Polytechnic and writing in national journals are the targets and outputs of this novice lecturer research activity.&#x0D; &#x0D; Keywords— Mold, Souvenir, Cavity, Core, Pnp.
the Usage of artificial intelligence in recognition of embossed numbers on billet

The article is focused on the recognition and localization of numbers on steel billets.Serial numbers are embossed to each billet.Our automated solution allows product identification without human interaction.There are several problems caused by embossing to the hot steel.First, the numbers are not clearly visible.There is a lot of noise around the serial number which causes shadows and reflections.Next, the surface of the billet is rough with grooves and ridges.These issues affect object detection.As a part of the 4 th Industrial Revolution, artificial intelligence and neural networks are used to automate production.Object recognition identifies which numbers are presented in the image.Another problem occurs when the serial number is located anywhere on the billet surface.The aim is to detect multiple objects in the scene using a single neural network.Our proposed solution is based on an extremely fast and accurate model from a class of deep learning algorithms.To localize and identify individual numbers, the You Only Look Once (YOLO) algorithm is implemented.It predicts bounding boxes and assigns classes from category 0 -9.The approach is fully automatic and detects embossed numbers in real time.A custom dataset and annotations for train the model is created.Due to the lack of training images, data augmentation is used to extend a dataset by increasing the amount of data.
VISUAL MEDIA-BASED ENGLISH TEACHING AT THE 11 TH GRADE OF AL-FALAH AL-ISALMEE SCHOOL, BANNANG SATA DISTRICT, YALA-THAILAND

Al-Falah Al-Islamee School is located in Bannang Sata District, Yala Province- Thailand. Al-Falah is a school located in the border area between southern Thailand and Malaysia. This school is located in the village but has great expectations to be able to compete with other schools. One of the efforts to improve the quality of education is starting from teaching. Teaching English in Al-Falah is very important, this is done to prepare students to be able to communicate well. The problem of students in learning English is that they cannot be active and consider English difficult. Of course, it is the teacher's responsibility to be able to make the students understand by teaching them. The purpose of this study was to find out how the activity and effectiveness of English learning by Al-Falah Al-Islamee teachers based on planning stages of teaching, stages of teaching implementation, and teaching evaluation stage. In this case, the teacher of Al-Falah Al-Islamee has chosen visual media-based English teaching to make the atmosphere of student learning active, creative, and effective. In other words, students can easily understand English language learning. The research method used is a qualitative descriptive method. The research subjects are principals, English teachers, and students. The object in this study is a learning model using visual media-based English teaching. The data collection technique carried out in this study was a triangulation of data namely observation, interviews, and documentation. The data analysis technique in this study was the reduction of display data and verification and then analyzed using qualitative descriptive analysis. The result of this study are that the development of learning using visual media-based English teaching is very effective, this can be seen from students who enthusiastically follow classroom learning and confidence in telling the events of the text. So that these learning activities support in achieving student learning achievements.
PINSA Learning Media (Cow Digestion Billboard) on Healthy Food Theme

Interactive learning media has not yet been developed by utilizing visual media to experience abstract learning difficulties. Students do not understand the material during the learning process. This study aims to develop a media billboard for cow digestion that can be used as an alternative media to help the learning process. This type of research is research and development (R&amp;D), with the development model used being the ADDIE model. Respondents in this study were six teachers and 58 fifth-grade elementary school students. This study involved three material experts and three learning media experts. The techniques used in collecting data are interviews, observations, questionnaires, and documentation. The instrument used is a questionnaire. The data analysis technique used is quantitative and qualitative. The results of this study were obtained based on the validity test results from the assessment of the media expert validator with a score of 99% (excellent), learning material expert 98% (excellent). The results of the practicality test were obtained based on the teacher's response assessment of 94% (excellent) and 99% of students (excellent). It can be concluded that the beef digestive billboard media is valid and practical to use on the theme of healthy food, the sub-theme of how the body processes food for fifth-grade elementary school students.
Revisiting the Dissimilarity Representation in the Context of Regression

In machine learning, a natural way to represent an instance is by using a feature vector. However, several studies have shown that this representation may not accurately characterize an object. For classification problems, the dissimilarity paradigm has been proposed as an alternative to the standard feature-based approach. Encoding each object by pairwise dissimilarities has been demonstrated to improve the data quality because it mitigates some complexities such as class overlap, small disjuncts, and low-sample size. However, its suitability and performance when applied to regression problems have not been fully explored. This study redefines the dissimilarity representation for regression. To this end, we have carried out an extensive experimental evaluation on 34 datasets using two linear regression models. The results show that the dissimilarity approach decreases the error rates of both the traditional linear regression and the linear model with elastic net regularization, and it also reduces the complexity of most regression datasets.
Discussion and Practice of Blended Teaching in Basic Theory and Application of GSM-R

In order to accommodate the trend of high-speed railway signaling integrating with communication techniques, Basic Theory and Application of GSM-R is a crucial curriculum for students majoring in Traffic Information Engineering and Control and Transportation Engineering. It helps students to master the latest theory and application of train-ground communication techniques. However, with the application of the next generation railway mobile communication technique, several advanced communication techniques are presented in the form of English materials. It is of great significance to have a bilingual teaching mode for this course. This would contribute to cultivating research-oriented and professional talents with international competitiveness. Through the blended teaching reform of bilingual education, the proportion of topic selection of interdisciplinary research papers by postgraduates has increased from 6% to 15%. In this article, the characteristics and the current problems of bilingual teaching are discussed from theory to practice in three aspects: the production of bilingual courseware, the supplement of English materials, and the guidance of research topics. Additionally, corresponding teaching reform schemes are proposed in this article.
Innovative Cardio Educational Software System in Support of Medical Education

The article presents an innovative software system that allows for processing and comparative analysis of biomedical data. The presented system uses real cardiological data obtained with modern medical devices - electrocardiography, continuous Holter monitoring, photoplethysmographic device, and others. The software system enables students studying at higher medical universities, majoring in cardiology to get acquainted and acquire skills for working with real cardiac records. The presented system allows the examination and use of cardiac recordings obtained using modern non-invasive technologies for research and procedures - modern electrocardiographic equipment, Holter-monitoring systems, photoplethysmographic devices. This will enable students to gain prior experience in working with real biomedical patient records. The presented software system together with the traditional training will help to increase the quality of modern education, will contribute to the acquisition of abilities, skills, and competencies necessary for future medical professionals.
A Demonstration of ScriptEase Motivational Ambient and Latent Behaviors for Computer RPGs

This demonstration describes the generation of ambient and latent NPC behavior scripts using generative behavior patterns with ScriptEase. Our behavior model supports behavior roles, a powerful mechanism that allows an NPC to change behavior sets during the story. Our motivation model for selecting ambient behaviors generates more realistic NPC behaviors and our novel collaboration protocol simplifies and extends the NPCs' collaborations with a broader range of NPCs. We demonstrate motivational ambient and latent behaviors for a guard NPC in a custom Neverwinter Nights game module. With ScriptEase, game authors can use, adapt, and create behavior patterns that generate complex, versatile, and engaging NPC behaviors
Engaging Undergraduate Students In Machine Learning Research: Progress, Experiences And Achievements Of Project Emd Mlr

His research interests include surface wave device modeling, optical character recognition, video image processing, and biomedical instrumentation.He is serving as the Assistant Dean for Distributed Learning for the College of
Plausible Environment Reconstruction Using Bayesian Networks

To save precious time and space, many games and simulations use static terrain and fixed (or random) reconstruction of areas that a player leaves and later revisits. This can result in noticeable differences between the reconstructed area and the player's recollections (or expectations). These differences can lessen a player's immersion in the game, or the usefulness of the simulation. We propose an approach for environment reconstruction that uses a Bayesian Network to quickly and easily calculate likely effects that external factors have on the environment. The reconstruction of revisited areas becomes less disconcerting and permits the incorporation of plausible changes based on unobserved, yet reasonably expected, events that could have occurred during the player's absence.
A semantic search approach for hyper relational knowledge graphs

Information Retrieval Systems usually employ syntactic search techniques to match a set of keywords with the indexed content to retrieve results. But pure keyword-based matching lacks on capturing user's search intention and context and suffers of natural language ambiguity and vocabulary mismatch. Considering this scenario, the hypothesis raised is that the use of embeddings in a semantic search approach will make search results more meaningfully. Embeddings allow to minimize problems arising from terminology and context mismatch. This work proposes a semantic similarity function to support semantic search based on hyper relational knowledge graphs. This function uses embeddings in order to find the most similar nodes that satisfy a user query.
A Blockchain-Integrated Divided-Block Sparse Matrix Transformation Differential Privacy Data Publishing Model

With the rapid development of information technology, people benefit more and more from big data. At the same time, it becomes a great concern that how to obtain optimal outputs from big data publishing and sharing management while protecting privacy. Many researchers seek to realize differential privacy protection in massive high-dimensional datasets using the method of principal component analysis. However, these algorithms are inefficient in processing and do not take into account the different privacy protection needs of each attribute in high-dimensional datasets. To address the above problem, we design a Divided-block Sparse Matrix Transformation Differential Privacy Data Publishing Algorithm (DSMT-DP). In this algorithm, different levels of privacy budget parameters are assigned to different attributes according to the required privacy protection level of each attribute, taking into account the privacy protection needs of different levels of attributes. Meanwhile, the use of the divided-block scheme and the sparse matrix transformation scheme can improve the computational efficiency of the principal component analysis method for handling large amounts of high-dimensional sensitive data, and we demonstrate that the proposed algorithm satisfies differential privacy. Our experimental results show that the mean square error of the proposed algorithm is smaller than the traditional differential privacy algorithm with the same privacy parameters, and the computational efficiency can be improved. Further, we combine this algorithm with blockchain and propose an Efficient Privacy Data Publishing and Sharing Model based on the blockchain. Publishing and sharing private data on this model not only resist strong background knowledge attacks from adversaries outside the system but also prevent stealing and tampering of data by not-completely-honest participants inside the system.
METHOD OF STATISTICAL IMITATION, ITS CREATOR S. ULAM AND BASIC PRINCIPLES OF APPLICATION FOR RANDOM PROCESSES MODELING

METHOD OF STATISTICAL IMITATION, ITS CREATOR S. ULAM AND BASIC PRINCIPLES OF APPLICATION FOR RANDOM PROCESSES MODELING
Virtual Experiment in Data Acquisition, Display, and Monitorin

This paper describes a virtual experiment in data acquisition, monitoring, and processing.The experiment was recently implemented as part of establishing a virtual laboratory that allows engineering technology students to perform experiments online.A front panel in LabVIEW displays the results and permits remote monitoring and control of devices and storage of acquired data.A digital camera that provides real-time pictures of monitored equipment is included in the system configuration.Details about the system design and development along with its programming and testing are given.
Root Causes and Reduction Techniques for Rework in Global Software Development

Global software development (GSD) is a trend adopted by numerous software companies to reduce development cost and time.However, potential cost and time savings are seldom realized due to unprecedented challenges in GSD environment.These challenges often hamper software development and project management activities.Moreover, they led to confusions, misinterpretations and conflicting perceptions regarding the software to be built, which in turn induce excessive rework.This rework significantly wastes lots of time as well as resources and may doom projects to fail.Rework in GSD setting can be reduced, if root causes of rework can be identified and thus avoided for GSD.However, there is paucity of research on this aspect.Thus, in this paper, root causes of rework in GSD are investigated.Techniques to reduce rework for GSD are also suggested.A metric for verifying the understanding score of distributed teams is also proposed.This study would aware practitioners and researchers about the causes of rework and its reduction techniques for GSD setting.
Analysis and resynthesis of real instruments using Pure Data and the MKMR library

In this experience report, I present my method for synthesizing realistic sounding instruments. Starting from the analysis of a marimba sample to how to recreate it using additive synthesis while reducing the number of objects, memory and CPU load. This synthesized model only uses pd vanilla objects, allowing an ease of implementation with projects using libpd. The instrument detailed in this article and many more are part of my open-source library: mkmr. This repository is a compilation of vanilla made abstractions with different categories such as: oscillators, filters, effects, instruments, waveshapers, sequencers, etc.
Investigating the Relationship between English Language Proficiency and Academic Performance of Engineering Students in Mehran University Jamshoro, Pakistan

The present study investigated the relationship between language proficiency and academic performance of students at Mehran university Jamshoro, Sindh. The study employed quantitative correlational research design to measure the variables. The researchers adapted English language test to measure the language proficiency of the learners. And CGPA (cumulative grade point average) to measure the academic performance of the research participants. The researchers collected data from 100 undergraduate students by doing simple random sampling. The data was collected in two phases: first pilot study and then main study. The pilot study was done before the actual research to measure validity and feasibility of the adopted English language proficiency test. The cronbach alpha was used to check reliability of the data. SPSS version 26 was used to perform the Pearson correlation analysis. The findings revealed that data was reliable with alpha value. 702 and the correlation was highly positive with a value of .826 at the significance value .000. The study confirms that the language has played a pivotal role to improve academic performance of the students studying in Mehran university of science and technology.
Implicit Learning of Chinese Numeral Classifiers Using the Stimulus Equivalence Paradigm

Chinese Numeral Classifiers (NCs), which are obligatory in the quantification of nouns, have been observed to pose serious challenges to learners of Chinese as a second language.Learners typically have difficulties generalizing the use of classifiers to new nouns and produce collocation errors due to: (1) the inherent complexity and inconsistencies of the Chinese NC system and (2) insufficient exposure to input containing classifier-noun collocations.The current study adopted a pre-testpost-test randomized group design to investigate whether implicit instruction using the stimulus equivalence (SE) paradigm (Sidman, 1971) would have a positive impact on the learning of Chinese NCs and whether the variability in classifier category membership (determined via typicality ratings of native Chinese speakers) would influence the learning process.Eighty-Seven native-English speakers, assigned to one of two learning conditions (an implicit learning [i.e., SE] group or an explicit learning group), were systematically exposed to four Chinese NCs.Only the group that learnt Chinese NCs using the SE paradigm showed a significant improvement in overall classifier retention one week after training.More fine-grained analyses revealed that the implicit-learning (SE) group was significantly more accurate in generalizing the use of the classifiers to new objects than the explicitlearning group when matching classifier-object pairs with lower typicality ratings.In the case of classifier-object pairings with high prototypicality ratings, the overall effectiveness of implicit learning of Chinese NCs (based on the SE paradigm) was comparable to the explicit instruction condition.The results highlight the SE paradigm's success vis-à-vis explicit instruction in facilitating the inferential learning of fuzzy rules based on less prototypical classifier-object pairings.The findings of the study contribute to our understanding of the Chinese NC system as well as semantic categorization from a cognitive linguistic perspective and have significant implications for the development of effective instructional methods to optimize language learning.
Discrete Algorithms - Programming and Collaborative Work: An Experience From the Virtual Classroom Environment

Collaborative learning understands learning as a social process of knowledge construction that goes beyond the individual instance of analysis, conceptualization and appropriation. Discrete Mathematics and Cryptography are two subjects of careers with a systemic and computational profile suitable for the early introduction of programming. With the aim of stimulating student participation and the development of transversal competencies, such as the ability to face a problem, teamwork, programming in a new language, improving oral communication; and in accordance with the line of research in Mathematics Education and training for the improvement of teaching and learning processes in the university classroom, a series of problems were activated in the virtual environment so that students could try to solve them and communicate the results to their peers. The students showed totally adequate resolution qualities, they were timid in their oral communications, but capable of defending the resolution of the problem. That is to say that there is benefit from this type of learning based on the possibilities offered by the new technologies.