Reviewerly/exHarmony huggingface dataset:
Research on Practice Teaching System for Network Engineering Major Evaluation

Network engineering is closely combined with computer technology and communication technology and the formation of the emerging field of technology, especially in today's rapid development of Internet and network economy booming prosperous situation, network engineering technology to become one of the hot technologies in the information technology. Major evaluation is a process of judging the value of major by qualitative and quantitative analysis, based on the evaluation standard and feasible evaluation means. Under the major evaluation standard system, mining network engineering major education mode and rule, major practice teaching reform is the key problem to be solved at present, and the construction of network engineering major practice teaching system suitable for major evaluation is the key problem to be solved in this paper.
Harnessing Emotive Features for Emotion Recognition from Text

With the prevalence of affective computing, emotion recognition becomes vital in any work related to natural language understanding.The inspiration for this work is provided by supplying machines with complete emotional intelligence and integrating them into routine life to satisfy complex human desires and needs.The text being a common communication medium on social media even now, it is important to analyze the emotions expressed in the text which is challenging due to the absence of audio-visual cues.Additionally, the conversational text conveys many emotions through communication contexts.Emoticon serves the purpose of selfannotation of writer's emotion in text.Therefore, a machine learning-based text emotion recognition model using emotive features proposed and evaluated it on the SemEval-2019 dataset.The proposed work involves exploitation of different emotionbased features with classical machine learning classifiers like SVM, Multilayer perceptron, REPTree, and decision tree classifiers.The proposed system performs competitively well in terms of f-score 65.31% and accuracy 87.55%.
Improving students' reading comprehension ability of Descriptive text through Mind Mapping strategy at the first grade of MTSN 1 Bandar Lampung

The objectives of this research were to find out whether there is any significant difference of the students’ reading comprehension at the first grade of MTsN 1 Bandar Lampung before and after the implementation of mind mapping strategy and to find out the students’ responses on the implementation of mind mapping strategy at the first grade of MTsN 1 Bandar Lampung. The design used was one group pretest posttest. The subject of the research was the first-grade students of MTsN 1 Bandar Lampung. VII C was chosen as the experimental class and VII D was chosen as the control class. The instrumen were reading test and questionnaire. The data were in form of scores taken from pretest and posttest. The result indicated that there was an improvement of students’ reading ability viewed from the pretest to posttest score (30.72 to 57.82) after they had been taught using mind mapping technique. Besides, a set of questionnaire was used to find out the students’ responses toward the mind mapping technique. It was found that majority of the students had positive responses toward the mind mapping technique. Thus, it can be concluded that Mind Mapping technique facilitates the students to improve their reading ability.
Outlier Detection in Wellness Data using Probabilistic Mapped Mean-Shift Algorithms

In this paper, the Probabilistic Mapped Mean-Shift Algorithm is proposed to detect anomalous data in public datasets and local hospital children’s wellness clinic databases. The proposed framework consists of two main parts. First, the Probabilistic Mapping step consists of k-NN instance acquisition, data distribution calculation, and data point reposition. Truncated Gaussian Distribution (TGD) was used for controlling the boundary of the mapped points. Second, the Outlier Detection step consists of outlier score calculation and outlier selection. Experimental results show that the proposed algorithm outperformed the existing algorithms with real-world benchmark datasets and a Children’s Wellness Clinic dataset (CWD). Outlier detection accuracy obtained from the proposed algorithm based on Wellness, Stamps, Arrhythmia, Pima, and Parkinson datasets was 93%, 94%, 80%, 75%, and 72%, respectively.
Perbandingan Algoritma k-Nearest Neighbors (k-NN) dan Support Vector Machines (SVM) untuk Klasifikasi Pengenalan Citra Wajah

Abstract- The study of face recognition is one of the areas of computer vision that requires significant research at the moment. Numerous researchers have conducted studies on facial image recognition using a variety of techniques or methods to achieve the highest level of accuracy possible when recognizing a person's face from existing images. However, recognizing the image of a human face is not easy for a computer. As a result, several approaches were taken to resolve this issue. This study compares two (two) machine learning algorithms for facial image recognition to determine which algorithm has the highest level of accuracy, precision, recall, and AUC. The comparison is carried out in the following steps: image acquisition, preprocessing, feature extraction, face classification, training, and testing. Based on the stages and experiments conducted on public image datasets, it is concluded that the SVM algorithm, on average, has a higher level of accuracy, precision, and recall than the k-NN algorithm when the dataset proportion is 90:10. While the k-NN algorithm has the highest similarity in terms of accuracy, precision, and recall at 80%: 20% and 70%: 30% of 99.20. However, for the highest AUC percentage level, the k-NN algorithm outperforms SVM at a dataset proportion of 80%: 20% at 100%.
ANALYSIS OF EDUCATION MANAGEMENT POLICIES IN THE STANDARD FIELD OF FACILITIES AND INFRASTRUCTURE IN INDONESIAN ELEMENTARY SCHOOLS

&lt;p&gt;The purpose of this article is to know the management and policies based on the regulation of the Minister of National Education of the Republic of Indonesia No. 24 of 2007 relating to facilities and infrastructure for elementary schools. The method used is a literature study because it evaluates Indonesian education standards, particularly facilities and infrastructure in elementary schools. The results showed that the standard of facilities and infrastructure was still categorized as low because schools with complete facilities were only for schools with good accreditation; conversely, schools with good accreditation did not have complete facilities. The geographic area is the influence of each school. The geographic area of each school influences each school’s geographic area for the standard of financing for facilities and infrastructure in elementary schools.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0520/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
Schooling leadership motivation level according to the 2030 vision in the government of Jeddah’s villages and its obstacles from their point of view: مستوى دافعية القيادات المدرسية للتطوير وفق رؤية 2030 في قرى محافظة جدة ومعوقاته من وجهة نظرهن

The study aimed to measure the motivation of school leaders in the villages of the Jeddah governorate for development according to the vision of 2030, and to identify the most important obstacles to the motivation of school leaders for development from the point of view of school leaders and in the light of the variables (years of service - academic qualification - educational area - training courses in the field of management and leadership) The researcher used the quantitative approach (descriptive and analytical), and the study tool was represented by an intended stratified number of (90) leaders and agents in my office (Rabigh Education - Khulais Education) belonging to Jeddah Governorate. The study found results, including; The motivation of school leaders in the villages affiliated with the Jeddah development region in the light of the Kingdom’s vision 2030, the motivation axis got a total average (3.57 out of 5), that is, by evaluating motivation (high), while the obstacles axis got a total average (3.94 out of 5), with a verbal rating. (big) at the dimensional level; Obstacles related to the school environment got the highest average (4.21) with an average of (very large), then the school curriculum with an average of (3.90), and thirdly, obstacles related to the teacher and learner with an average of (3.87), and finally, obstacles related to educational administration with an average of (3.85), all of them with a rating of (large) The results also showed that there are no statistically significant differences between the level of school leaders' motivation to develop according to Vision 2030 in the villages due to the variables (years of experience - educational qualification - educational area - training courses) Based on the results, the researcher presented a set of recommendations and proposals to enhance the motivation of school leaders to develop according to Vision 2030 and reduce its obstacles in the villages of Jeddah Governorate and all schools in the Kingdom.
IS INSIDER TRADING SUCCESSFUL? AN EXTENSIVE ANALYSIS WITH BUYING AND SELLING EVIDENCE

Purpose: The goal of the present study is to first, understand the market timing capabilities of a set of internal stakeholders while trading (buying and selling) stock, and second, shed some light on some of the characteristics that make them (or not) successful.Design/methodology/approach: We use a relative transaction price approach (RTP) on 842 aggregated trades coming from insiders.These were taken from publicly disclosed information available on the Portuguese regulator.Furthermore, we use a median regression-based method to infer on our conclusions.Findings: We find that insiders buy (sell) at a relatively lower (higher) price when compared to other traders.This shows signs of market timing capabilities.Furthermore, from the studied characteristics, neither the frequency nor gender are good predictors for performance, but the seniority in the organization can help us to understand that some insiders, mostly on the managerial level, might have an edge.Overall, we also find that insiders' trades made OTC generally overperform the ones made on the open market.At last, we find that insiders did not lose any performance during the Portuguese bailout period.Originality/value: By using a thorough analytical approach and a never-used sample of trading data, comprising both buying and selling trades at high-frequency (daily) level, we build on the literature of insider trading as well as on the knowledge around the effects of trading on the open market vs. OTC.We also make yet another contribute towards the literature around the Portuguese bailout effect.
Metode Natural Feature Tracking dan Fast Corner Detection dengan Teknik Virtual Button Pada Aplikasi Sistem Pernafasan Manusia

At this time the development of information and communication technology has developed very rapidly. As in smartphones, the technology contained in smartphones today has an important role for human activities. The technology that is currently being implemented on smartphones is Augmented Reality. Augmented reality can be used in all fields of human activity, one of which is in the field of education. The purpose of this research is to develop an educational media about the organs of the human respiratory system that is interactive and can be understood by users such as students. In this study, 2 methods were used, namely Fast Corner Detection and Natural Feature Tracking Methods to read a marker which would later bring up information and also use the virtual button technique in the application. In testing using 5 smartphones. The results of testing at an angle of 60o and 90o the five smartphones can detect markers. The distance test has different results from the smallest having a minimum distance of ±70 cm to a maximum distance of ±150 cm. In tests based on light intensity, the five smartphones can detect markers at light intensities above 5 lux
Mobile-based Activity Monitoring System for the Self-quarantine Patient

Nowadays, not all the patient can be hospitalized because of the COVID-19 pandemics. So, the self-quarantine for the patient with the various diseases will be the given solution by the hospital. It would make the hospital needs a system that can monitor the activity and the position of the patient from a distance. Nowadays, mobile phone is equipped by the sensor that can detect the user movement. Not only the user’s position, but also the user’s activity. In this paper, it will be developed an activity and position monitoring system for the self-quarantine patient that can be used in their home. The mobile activity monitoring can be achieved by activity recognition using classification method. For the needs of performance testing, we evaluate some classification method for activity recognition to compare the among classification method for the activity recognition. Some tested classification methods are Naïve Bayes, KNN, KStar and TreeJ48. Furthermore, we tested the impact of sliding windows per N samples taken to the accuracy of the activity recognition. We choose the best N sample that could give the best accuracy for activity recognition. The system not only monitor the patient’s activity, but also the patient’s position. The position monitoring can be achieved using Google Maps API. The result is Naive bayes has the accuracy of 81.25%, KNN has the accuracy of 78.125%, KStar has the accuracy of 78.125% and TreeJ48 has the accuracy of 75%. The N sample that could give the best accuracy is 6 with the accuracy of 90.15%.
ANALISIS RESPON TANTANGAN YANG DIHADAPI PENGAJAR TERHADAP E-LEARNING DI POLITEKNIK PELAYARAN SORONG

This Research Focused On The Findings Of The Questions On The Problem Research, Namely "What Are The Challenges Faced By The Teacher Toward E-Learning?". This Research Used The Social Constructivism Pattern Model (The Social Constructivism Paradigm) As A Qualitative Research Framework To Interpret The Issues Related To This Research (Crotty, 1998). Then, The Researcher Used The Question-List Model (Questionnaire) As A Tool For Data Collection, As Suggested By Sugiyono (2010). Therefore, Data Analysis That Used In This Study Is By Reducing Data (Data Reduction), Displaying Data (Data Display), And Concluding, As Suggested By Miles &amp; Huberman (1994). Therefore, Researchers Provided Several Solutions To Overcome The Difficulties Faced By Teachers As Challenges To E-Learning In The Discussion And Conclusions Of This Research.
Design of Intelligent Riding System Based on STM32

Today's riding equipment is mostly for professional riding users, with single function and high price.According to this situation, this paper intends to design an intelligent riding system based on STM32, which can provide key riding data for riders at a reasonable price.To a certain extent, it can ensure the safety of riders on the way, and achieve the purpose of healthy riding and green travel.The design is mainly composed of four parts, namely the main control part, detection part, display part and alarm part.Firstly, the STM32F103ZE microcontroller is used as the main control core, and the heart rate sensor, blood oxygen sensor and Hall sensor are expanded to realize the data acquisition and display of the rider's heart rate, blood oxygen, speed and mileage.Secondly, the intelligent riding instrument will compare the real-time collected data with the preset threshold, and start the sound light prompt and voice alarm when a certain data is close to or beyond the preset range.In addition, this design realizes automatic lighting in the dark through photosensitive sensor.Finally, this design adopts solar power supply mode; the intelligent riding instrument designed in this paper can measure the riding speed, mileage, heart rate and blood oxygen of the rider, and is easy to operate.
Penerapan Metode Data Mining Pada Point of Sale Berbasis Web Menggunakan Algoritma Apriori

To be able to understand which products have been purchased by customers, it is done by describing the habits when customers buy. Use association rules to detect items purchased at the same time. This study uses an a priori algorithm to determine the association rules when buying goods. The results of the study and analyzing the data obtained a statement that using the a priori algorithm to select the combined itemset using a minimum support of 25% and a minimum confidence of 100%, found the association rule, namely, if the customer buys at the same time. Buying goods has the highest value of support and trust. Likewise with the support value of 25%, the confidence value is 100%. In this way, if a customer buys an item, the probability that the customer buys the item is 100%
Research of Promising Network-on-Chip Topologies: application of root and direct products of Paley graphs

This paper provides an overview of existing network-on-a-chip (NoC) topologies.The study of Paley graphs as a topological graph basis for the design of NoC is carried out.Various modifications of circulant graphs are considered.The main focus of the research is directed to the study of the direct and root products of Paley graphs, the substantiation of the irrelevance of considering tensor, lexicographic and strong products of graphs is given.The comparison of the most important parameters of the graphs, which directly affect the main parameters of networks-onchip, including the network bandwidth and the speed of data transfer between network nodes, is performed.
THE IMPLEMENTATION OF STUDENT TEAM ACHIEVEMENT DIVISION (STAD) TO MOTIVATE STUDENTS’ SPEAKING ACTIVITY

The purpose of this research was to find out whether the implementation of Student Team Achievement Division (STAD) able to motivate students’ speaking activity or not. The researcher used classroom action research design in this study. The subject was the class VIII B of eighth grade students of SMP Negeri 1 Sangkub consisting on 25 students which comprised 12 females and 13 boys. In this present research, the researcher used some instruments to collect the data, such as; Lesson Plan (RPP), Tests, observation, Interview, and documentation. In applying the test, the researcher asked the subject under the research to practice a simple dialogue about expression of giving instruction and expression of asking permission.In this research, there were three cycles, namely; Pre-Cycle, Cycle I, and Cycle II. Furthermore, Cycle I and II consisted on two sessions. In Pre-Cycle, the completeness percentage was low (36%) so that the present classroom action study was conducted to solve the problems of the students. The result of Cycle I showed that STAD motivated students’ speaking activity. It could be seen from the increase of the completeness percentage of Cycle I (64%). The researcher continued the research by conducting the Cycle II to revise the problem in Cycle I and the completeness percentage of Cycle II was (88%). Based on the result above, the STAD technique has a positive influence to students of class VIII B at eighth grade students of SMP Negeri 1 Sangkub speaking activity, and this STAD Technique could be used to be one of the alternative teaching techniques. Key Words: STAD, Motivate, Speaking Activity.
Perbandingan Metode Certainty Factor dan Theorema Bayes dalam Mendiagnosa Penyakit Kandidiasis pada Manusia Menggunakan Metode Perbandingan Eksponensial

Candidiasis is an infectious disease caused by the fungus candida. Research on this fungus has been widely carried out until several types of candida fungi are found that can attack and cause infections in humans. Types of candidiasis also vary, but can be classified in general into three types, namely attacking the mouth (Candidiasis Thrush), vagina (Vulvoginal Candidiasis), and skin (Cutaneous Candidiasis). Candidiasis is very susceptible to infection and infection, therefore a study is needed to diagnose candidiasis. Today, expert systems are often used to diagnose diseases. There are several methods commonly used in expertise, including the Certainty Factor method and the Bayes Theorem. However, the problem faced in implementing an expert system in any field is uncertainty. This is caused by the user's hesitation in answering questions during the consultation session or even the inaccuracy of the methods used in building the system. Therefore, it is necessary to study and compare the methods that can be used to build the system. Exponential is a simple comparison that can reduce bias in the analysis process. This study aims to apply and analyze both methods and the results compare with an exponential comparison in detecting candidiasis in humans. The results of this study showed that both methods achieved the same results, namely the lowest percentage level was Candidiasis Truth, then Vuvoginal Candidiasis, and the highest was Candidiasis Cutaneous. Of these two methods, Certanty Factor is more accurate in diagnosing candidiasis.
Do Simplified Text Can Improve Students’ Reading Comprehension in Narrative Text?: A Classroom Action Research Perspective

This research was based on the researcher's preliminary study which found that the students could not comprehend the meaning of texts in their textbook. This Classroom Action Research (CAR) aims to improve the students’ reading comprehension in narrative text through simplified text at grade VIII of SMP Budhi Luhur Pekanbaru. The research was administered to the second year students of SMP Budhi Luhur Pekanbaru. The total population was 34 students. After analyzing the data, the researcher found a significant effect of simplified text toward reading at the second-year SMP Budhi Luhur Pekanbaru students, where the average score from the based score was 58. It increased to 66 at the end of the cycle I. Finally, the average score of cycle II was 75. So it can be concluded that simplified text can increase the students' reading skill at grade VIII SMP Budhi Luhur Pekanbaru
You Get What You Sow: High Fidelity Image Synthesis with a Single Pretrained Network

State-of-the-art image synthesis methods are mostly based on generative adversarial networks and require large dataset and extensive training. Although the model-inversion-oriented branch of methods eliminate the training requirement, the quality of the resulting image tends to be limited due to the lack of sufficient natural and class-specific information. In this paper, we introduce a novel strategy for high fidelity image synthesis with a single pretrained classification network. The strategy includes a class-conditional natural regularization design and a corresponding metadata collecting procedure for different scenarios. We show that our method can synthesize high quality natural images that closely follow the features of one or more given seed images. Moreover, our method achieves surprisingly decent results in the task of sketch-based image synthesis without training. Finally, our method further improves the performance in terms of accuracy and efficiency in the data-free knowledge distillation task.
Can an iPhone save your life? Multimodal forensic analysis of bullet damage to a smartphone

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