Reviewerly/exHarmony huggingface dataset:
Perencanaan Perhitungan AKNOP Pada Daerah Irigasi Mrican Sebagai Upaya Peningkatan Kinerja Irigasi

Food security is one of the targets of the Sustainable Development Goals that must be achieved by 2030. One of the problems faced in achieving this target is the decrease in the function of irrigation infrastructure by ± 70%, resulting in the reduced water supply to agricultural land. The purpose of this research is to recalculate the operational and maintenance needs of the Mrican Irrigation Area by the applicable regulations and the current conditions of the study area for the needs of the 2021 budget year.The research was conducted in the Mrican Irrigation Area with an area of ​​30,341 ha located in 3 districts, namely Kediri, Nganjuk and, Jombang. The result of optimization calculation of personnel for operational activities and maintenance of irrigation networks in the Mrican Irrigation Area is 577 people. The length of the carrier line is 366 km and the drainage is 248 km long. The number of waterworks as many as 966 units. The results of calculations and analyzes that have been carried out, it is found that the amount of the Operational and Maintenance Real Needs of Mrican Irrigation Area for the irrigation operational management component is Rp. 6,329,767,232, the component of surface irrigation operation costs Rp. 31,490,208,724, and the maintenance component of the surface irrigation network is Rp. 22,685,844,371. The total cost of the Operational and Maintenance Real Needs of Mrican Irrigation Area is Rp. 60,505,820,327.
THE EFFECT OF STORY FACE IN INCREASING THE STUDENTS’ READING COMPREHENSION OF NARATIVE TEXT OF THE TENTH GRADE AT SMK SWASTA YPIS MAJU BINJAI.

The objective of this study was find out whether there was an effect of using Story Face in increasing the students’ reading comprehension of narative text. The writer design in this study was quasi-experimental design by using pre-test and post-test non-equivalent control group design. This study was conducted with the tenth grade students of SMK Swasta YPIS Maju Binjai as the population of the study. The sample was taken by cluster random sampling, with 60 students as the sample of this study. The writer used class X TBSM with consist of 30 students as the experimental class and X TKJ wich consist of 30 students as the controled class.The writer used test asthe instrument of collecting data. The data collected from this study were analyzed using t-test formula. The result of this study that was a positive effect of the result students’ reading comprehension narative text after using Story Face strategy. It can be seen from the data analysis, it was found that value of t-observed (to) was higher than t-table (tt). The result from calculating the data was t- observation (to= 5,68) and t-table (tt=1,672) it means, to is higher than tt in significant levvel 5%, so the null hypothesis (Ho) is rejected, and the alternative hypothesis (Ha) is accepted. in order words, using Story Face had effect on students’ reading comprehension of narative text of the tenth grade students at SMK Swasta YPIS Maju Binjai.
Risk assessment of heavy landing based on BWM and cloud model

Aiming at the systemic, ambiguity and randomness characteristics of the aircraft's heavy landing risk, this paper starts from the system perspective and proposes a risk assessment method based on the Best- Worst method (BWM) and cloud model. Aiming at the ambiguity and randomness of the information in the risk assessment, the cloud model is used to describe the language. In view of the difference in weights, combining BWM and cloud models for weighting. Finally, an example is given to ver ify the reasonableness and effectiveness of the model.
Detecting Anomalies in Sequences of Short Text Using Iterative Language Models

Business managers using Intelligent Virtual Assistants (IVAs) to enhance their company's customer service need ways to accurately and efficiently detect anomalies in conversations between the IVA and customers, vital for customer retention and satisfaction. Unfortunately, anomaly detection is a challenging problem because of the subjective nature of what is defined as anomalous. Detecting anomalies in sequences of short texts, common in chat settings, is even more difficult because independently generated texts are similar only at a semantic level, resulting in an abundance of false positives. In addition, literature for detecting anomalies in time ordered sequences of short text is shallow considering the abundance of such data sets in online settings. We introduce a technique for detecting anomalies in sequences of short textual data by adaptively and iteratively learning low perplexity language models. Our algorithm defines a short textual item as anomalous when its cross-entropy exceeds the upper confidence interval of a trained additive regression model. We demonstrate successful case studies and bridge the gap between theory and practice by finding anomalies in sequences of real conversations with virtual chat agents. Empirical evaluation shows that our method achieves, on average, 31% higher max F1 scores than the baseline method of non-negative matrix factorization across three large human-annotated sequences of short texts.
Research on Multi-level Cooperative Detection of Power Grid Dispatching Fault Based on Artificial Intelligence Technology

The traditional power grid dispatching fault detection method has low detection efficiency and accuracy due to the lack of uncertainty in modeling. Aiming at the above problems, a multi-level cooperative fault detection method based on artificial intelligence technology is studied. After the preliminary processing of the dispatching data, the multilevel fault detection architecture is established. BP neural network is used to realize the multi-level cooperative detection of scheduling faults in the multi-level detection architecture. Through simulation experiment, it is proved that the failure rate and false detection rate of the proposed method are far lower than those of traditional methods, and the method has high stability and advantages.
Employing the flat pattern in the implementation of bachelor students graduation project in the Faculty of Home Economics

The ready-made garment industry goes through several interrelated stages, and the pattern stage is considered one of the most important stages that the industry goes through. The basic pattern also represents the main factor on which the quality of the product as a whole depends, and in which the element of control and comfort must be available. Good control is one of the important matters that determine the final shape of clothes. Controlled clothing shows the good shape of the body and helps to hide defects, while any error or weakness in the control process distorts the general appearance (10), and the preparation of the flat basic form requires two basic elements to adjust it in a correct way, they are accurate sizes It represents the body and the additional amount that the body needs to give it freedom of movement in each of its parts and It is used in the preparation of the pattern on either standard size tables or personal sizes, and the success of the flat basic model depends on the lines, curves and darts that represent the basis for controlling the shape of the dress on the body. The pattern is also a map or an illustration for recording sound information about proportions, shape, and position of the main body. It also represents a translation of body measurements including rotations and lengths in the form of a set of lines and curves drawn on paper or cloth to represent the dimensions of the human body according to the measurements that were taken for him in advance. The graduation project also represents a big problem for female students in drawing the pattern, especially if the project is for special occasion clothes because it requires good preparation of the pattern and adjusting the sizes, which is why I was invited to think about employing a flat pattern for drawing and implementing the project in the bachelor's stage. One of the most important problems of the current research was how to employ the flat pattern in implementing and controlling the graduation project The research aims to overcome the pattern problems in preparing and implementing the final project for the undergraduate stage The research assumes that there are statistically significant differences between the evaluation of the models implemented from employing the flat pattern in achieving control in terms of the general shape according to the opinions of specialists. One of the most important results of the research was the presence and statistically significant differences between the models implemented from employing the flat pattern in achieving control in terms of the general shape according to the opinions of specialists, where Model No. (3) obtained the best results as it obtained a quality factor of 100% and Model No. (5) On the lowest results, as it got a quality factor of 84% and from One of the most important recommendations of the research is to pay attention to the application of various methods of pattern drawing in the implementation of different styles of clothing.
On the CTW-based Entropy Estimator

Estimating the entropy of a sequence of discrete observations is a problem that raises in many different fields. There are numerous different applications of it, specifically in neuroscience, where entropy has been adopted as the main measure for describing the amount of information transmitted between neurons (see Gao et. al. 2008 and reference therein). Gao et. al. 2008 conducted a thorough comparison of the performance of the most popular and effective entropy estimators. They have shown that the context tree weighted (CTW) based estimator, which uses the probability estimation produced by the CTW lossless compression algorithm by Willems et. al., 1995, repeatedly and consistently provides the most accurate results. The motivation for using the CTW probability for estimating the entropy is the well-known Shannon-McMillan-Breiman (SMB) result. However, the CTW probability is a result of a &ldquo;twice universal&rdquo; approach, meaning it is a weighted combination of the estimated probabilities of the sequence, over all possible bounded memory tree models (up to a predetermined maximum memory). Motivated by this we examine the CTW based estimator from the view point of the CTW algorithm redundancy performance analysis (Willems et. al., 1995). We define the SMB entropy as the normalized logarithm of the true probability, assuming a specific model for the source. We consider this finite length quantity to be the best possible estimator of the entropy given a specific model. By defining a random variable distributed over all possible bounded memory tree models we extend this definition and define the conditional SMB entropy. We bound the over estimation of the CTW-based estimator compared to both the conditional SMB entropy as well as the SMB entropy of a specific model. In both cases we show that the over estimation approaches zero according to O(log T/ T), where T is the length of the sequence.
ID-based, Proxy, Threshold Signature Scheme

We propose the proxy threshold signature scheme with the application of elegant construction of verifiable delegating key in the ID-based infrastructure, and also with the bilinear pairings.The protocol satisfies the classical security requirements used in the proxy delegation of signing rights.The description of the system architecture and the possible application of the protocol in edge computing designs is enclosed.
Segmentation Method for Face Modelling in Thermal Images

Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast RCNN, Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was configured to train with 5 epochs and 131 iterations. The final model predicted and located the face correctly using the test image.
Need Assessment For Developing An Online English Proficiency Test Instrument In Higher Education During Covid-19 Pandemic

This study aims to find out things needed to develop an online English proficiency test instrument in higher education during COVID-19 pandemic. The method of this study was descriptive qualitative method by using observation and interview as the data collection techniques. This study mention three main points that are needed in developing an online test instrument. The first is the system or application that will be used in conducting the online test. The second is the administrator of the online test. The last point is the device and facilities that support the online test.
Synchronous Computer-Mediated Interactions in English

This paper aims to investigate to what extent Synchronous Computer-Mediated Communication with non-native speakers of English affects Engineering students' speaking skills, and how the use of SCMC in speaking practice is perceived by the students.Grounded in an ex post facto design, the data were gained from teacher journals, and interviews to fifteen vocational secondary students majoring in Engineering engaged in SCMC for one semester.Findings showed that SCMC did not indicate positive effects on improving Engineering-related vocabulary and accurate grammar use compared with their pronunciation aspect.The use of SCMC was considered negative in terms of interaction with their interlocutors, and technicalities.However, few students positively perceived that they found it joyful learning within SCMC and got motivated to improve their speaking skills within their interaction with their nonnative speakers of English they met online.
Pelatihan Penulisan Buku dan Nama Samaran

The pseudonym given by Law No. 3-2017 will present a dilemma for lecturers in producing scientific books obtained at the National Library. Activities carried out with careful planning, activities carried out and the results of discussions about what will be written in books and popular articles that can be written by the participants. Training activities essentially provide an understanding of the rights and obligations of special authors in pseudonyms. Popular themes for lecturers with ISI, ASBI and Popular Article themes.
Bayesian refinement of full profile diffraction patterns for uncertainty quantification

Advancements in x-ray and neutron characterization instruments provide the ability to examine the structures of newly developed materials.Full profile diffraction patterns collected from these instruments can be analyzed through Rietveld refinements using least-squares fitting routines to obtain sample, structural, lattice, and instrumental parameters.An alternative statistical framework using a Bayesian analysis method can also be applied to full profile fitting in order to quantify the uncertainty in the model parameters [1].In Bayesian inference, parameters are taken to be random variables having associated posterior distributions.This representation provides descriptive insight to the uncertainties in the parameters and the model fits.In this work, Rietveld refinements are initially performed with GSAS-II [2] on the metastable perovskite material system of (Ba 1-x Sn x )(Zr 0.5 Ti 0.5 )O 3 (BSZT) [3].The Bayesian refinement method is then employed to enrich the model information, specifically to provide higher fidelity uncertainty quantification on the atomic occupancies and positions.The effects of refining instrumental parameters via the Bayesian method are also investigated.[1]
The Effectiveness of Learning the Indonesian Language Using Spada in the Pandemic Time Covid-19 at Prima Indonesia University Medan

This study aims to find out The Effectiveness of Learning the Indonesian Language Using Spada in the Pandemic Time Covid-19 at Prima Indonesia University Medan. This research is a descriptive qualitative and quantitative descriptive study using online questionnaires and interviews, this is based on the formulation of research problems that require researchers to explore in order to understand and explain what is being studied through an intensive relationship with data sources. Based on the results of questionnaires and interviews and in accordance with the problems, several conclusions can be drawn, namely: 1.Learning Indonesian using SPADA during the Covid-19 pandemic was effective, namely, both from the results of questionnaires and interviews with lecturers and students. 2. The process of learning Indonesian using SPADA starting from planning, implementation and assessment is carried out effectively. 3. The opinion of lecturers and students to make Indonesian language learning more effective using SPADA is to add other features such as Zoom Meeting or Google Classroom.
Penggunaan Metode Naïve Bayes untuk Memprediksi Tingkat Kemenangan pada Game Mobile Legends

The research conducted aims to predict the win or loss of a game in the Mobile Legend game. Because victory will greatly affect the level of play that is owned in the Mobile Legend game, and victory is also influenced by the player's ability to play the game and mastery of a game character that is used. The results of the study will show the results of the classification of the success rate of the method we use in predicting the success or victory of the game in the online game Mobile Legend which can be called the most popular game today. Many play this online game even from small children to adults. This game is very popular at this time, but there are still many who play while playing this game so that it greatly affects performance when doing battle games which results in many rankings dropping to the herro who doesn't move due to lag cellular network.
A study of the relationship between Sudongpo and his friends

The main paper studied the relationship between poetry, the words of a song and epistles through the Wangjeongguk, Seogunyu, and Jeonjemyeong. They maintained the friendship formed in the Confucian customs of the time by keeping the righteousness when the Sudongpo was in trouble. It is difficult for ordinary people to keep traditional friends of relationships, but the Sudongpo and his friends continued this friendship by encouraging and comforting each other in adversity. It is said that Wangjeongguk showed friendship between the 刎頸之交, Seogunyu showed friendship between the 金蘭之交, and Jeonjemyeong showed friendship between the 布衣之交. On the other hand, the Sudongpo exclaimed, “From Emperor to beggars,” suggesting that it was derived from his deep learning and literary talents, his humor and free thinking of the 儒佛道. The relationship between the friends and the relationship was illuminated through the poetry, the words of a song and epistles presented of the literature of the part.
Sistem Informasi Akuntansi BMD Terhadap Pengelolaan Asset Daerah Pada DPPKAD Kota Gorontalo

The purpose of this study was to determine the effect of regional accounting information systems on regional asset management. The method used in this study uses quantitative methods using simple regression analysis. The results in this study are the Regional Accounting Information System influences the Regional Asset Management. The independent variable studied had a contribution of 70.1% to the Regional Asset Management variable, while the other 29.9% was influenced by other factors outside the variable under study.
Online Multi-Object Tracking in Videos Based on Features Detected by YOLO

With the rapid development of different applications that rely on multi-object detection and tracking, significant attention has been brought toward improving the performance of these methods. Recently, Artificial Neural Networks (ANNs) have shown outstanding performance in different applications, where objects detection and tracking are no exception. In this paper, we proposed a new object tracking method based on descriptors extracted using the convolutional filters of the YOLOv3 neural network. As these features are detected and processed during the detection phase, the proposed method has exploited these features to produce efficient and robust descriptors. The proposed method has shown better performance, compared to state-of-the-art methods, by producing better predictions using less computations. The evaluation results show that the proposed method has been able to process an average of 207.6 frames per second to track objects with 67.6% Multi-Object Tracking Accuracy (MOTA) and 89.1% Multi-Object Tracking Precision (MOTP).
News marketing recognition based on attention neural network model

Aiming at the problem of insufficient text feature extraction in the existing short news text classification methods for identifying marketing intentions and difficulty in capturing the semantic information in the text, a short text news marketing recognition method based on the attention mechanism neural network model is proposed. The model uses convolutional neural network to extract local features, and then uses bidirectional long and short-term memory network to extract contextual semantic information, strengthens the learning of features, and introduces a double-layer attention mechanism to calculate feature weights to further obtain influential features between sentences. Finally, perform text classification at the softmax function layer. Through experiments on two standard data sets, the experimental results show that this method has better classification performance, and has a significant improvement in accuracy compared with other models.
PDEODE-WEB-BASED Blended Learning As 21st Century Learning Development Solutions

The purposes of this study are to develop a PDEODE-WEB based Blended Learning model, and determine the quality of the developed PDEODE-WEB based Blended Learning model on digestive system material in terms of validity, practicality, and effectiveness. This study employed a 4D development research (R&amp;D) which consists of Define, Design, Development, and Disseminate. The results showed that the validation of material and media experts for content validation was 3 with very important categories. Analysis from a learning expert for the construction validation category obtained 4.03 with the very good category. The results of the limited trial obtained a score of 81.47 in the good category and the practicality test obtained 90.6 which could be categorized as very practical. The effectiveness test was carried out obtained the N-Gain of 0.6 with the medium category. The PDEODE-WEB Blended Learning model that was developed meets the criteria of validity, practicality, and effectiveness as a solution for the development of learning in the 21st century.
Applying flower writing strategy to the tenth graders in writing descriptive text

Writing is regarded as a challenging subject in school. At the same time, it was a critical skill for students to master because it is so important in this age of globalization. This study aimed to find out whether or not the Flower Writing Strategy was effective to be used in teaching writing descriptive text. The quasi-experimental method was used in this study. The sample of the study was 68 students taken by using the purposive sampling technique. The data was gained by using a written test. The data were analyzed by using a t-test. Based on the result of the independent sample t-test, it was found that t-obtained (3.439) was higher than ttable (1.9955) and pvalue (0.001) was less than άvalue (0.05). It meant that the null hypothesis (Ho) was rejected and alternative hypothesis (Ha) were accepted. Hence, Flower Writing Strategy was effective to be used in teaching descriptive text.