Reviewerly/exHarmony huggingface dataset:
DPCD: Discrete Principal Coordinate Descent for Binary Variable Problems

Binary optimization, a representative subclass of discrete optimization, plays an important role in mathematical optimization and has various applications in computer vision and machine learning. Generally speaking, binary optimization problems are NP-hard and difficult to solve due to the binary constraints, especially when the number of variables is very large. Existing methods often suffer from high computational costs or large accumulated quantization errors, or are only designed for specific tasks. In this paper, we propose an efficient algorithm, named Discrete Principal Coordinate Descent (DPCD), to find effective approximate solutions for general binary optimization problems. The proposed algorithm iteratively solves optimization problems related to the linear approximation of loss functions, which leads to updating the binary variables that most impact the value of the loss functions at each step. Our method supports a wide range of empirical objective functions with/without restrictions on the numbers of 1s and -1s in the binary variables. Furthermore, the theoretical convergence of our algorithm is proven, and the explicit convergence rates are derived for objective functions with Lipschitz continuous gradients, which are commonly adopted in practice. Extensive experiments on binary hashing tasks and large-scale datasets demonstrate the superiority of the proposed algorithm over several state-of-the-art methods in terms of both effectiveness and efficiency.
Processing of Condition Monitoring Annotations with BERT and Technical Language Substitution: A Case Study

Annotations in condition monitoring systems contain information regarding asset history and fault characteristics in the form of unstructured text that could, if unlocked, be used for intelligent fault diagnosis. However, processing these annotations with pre-trained natural language models such as BERT is problematic due to out-of-vocabulary (OOV) technical terms, resulting in inaccurate language embeddings. Here we investigate the effect of OOV technical terms on BERT and SentenceBERT embeddings by substituting technical terms with natural language descriptions. The embeddings were computed for each annotation in a pre-processed corpus, with and without substitution. The K-Means clustering score was calculated on sentence embeddings, and a Long Short-Term Memory (LSTM) network was trained on word embeddings with the objective to recreate the output from a keywordbased annotation classifier. The K-Means score for SentenceBERT annotation embeddings improved by 40% at seven clusters by technical language substitution, and the labelling capacity of the BERT-LSTM model was improved from 88.3 to 94.2%. These results indicate that the substitution of OOV technical terms can improve the representation accuracy of the embeddings of the pre-trained BERT and SentenceBERT models, and that pre-trained language models can be used to process technical language.
Estimation of Effectiveness of Vocational Education Offered at Korean Polytechnic Colleges

본 연구의 목적은 한국폴리텍대학 직업교육의 효과성을 추정하는데 있다. 대학 직업교육의 우수성은 다년간 보고되고 있지만 그 효과를 미시적 자료를 이용하여 추정하지는 않았다. 인적자본이론에 바탕을 두고 대학알리미자료와 YP2000를 이용하여 학과 및 개인별 분석을 하였다. 일반 전문대학의 졸업생과 폴리텍 졸업생 사이의 비교를 통해서 폴리텍대학의 직업교육이 개인의 고용에 끼치는 영향을 엄밀하게 분석하였다. 폴리텍대학의 교육이 취업률을 제고하는데 있어서는 상당히 큰 역할을 하고 있지만 졸업생의 임금에 끼치는 영향은 미미하거나 오히려 낮은 것으로 나왔다. 다만 표집된 폴리텍대학 졸업생의 상대적 비율이 상당히 작기 때문에 결과 해석에는 유의해야 한다. 또한 폴리텍대학이 추구하는 직업교육과 다른 전문대학이 추구하는 직업교육의 목표가 다르다는 점에도 유의해야 한다.The purpose of this study is to estimate the effectiveness of Korean polytechnic college in terms of vocational education. The excellence of vocational education offered at polytechnic college has been reported for many years, but the effect has not been estimated using micro data. Based on the human capital theory, departmental and individual analysis was conducted using academyinfo.go.kr data and YP2000. By comparing graduates of general junior colleges and graduates of polytechnic colleges, the effect of vocational education at polytechnic colleges on individual employment was rigorously analyzed. Although polytechnic colleges play a significant role in enhancing the employment rate, the effect on wages is insignificant or rather low. However, care must be taken in interpreting the results because the relative proportion of college graduates sampled is quite small. It should also be noted that the goals of vocational education pursued by polytechic colleges are different from those of vocational education pursued by other junior colleges.
Changes in Core Competencies in the COVID-19 Pandemic Era and Their Implications for University Education - Focused on G University Students in Gyeongsangnam-do -

본 연구는 코로나19 시대 대학생의 핵심역량 변화를 통해 대학교육에서의 시사점 탐색하고 대학교육 운영 방안을 모색하기 위한 목적으로 수행되었다. 핵심역량 수준은 경상남도에 소재한 G대학에서 자체 개발한 핵심역량진단 도구를 활용하여 측정하였다. 2020년과 2021년, 2년 연속 진단에 참여한 재학생 437명을 연구대상으로 선정하고 2년 연속 참여한 학생 중 2020학번을 제외한 재학생 662명의 결과와 비교하였다. 핵심역량 및 하위역량 수준과 변화 정도, 각 역량 사이의 관계를 분석한 결과, 2020학번은 세계시민(글로벌 역량)과 도전정신(리더십 역량)을 제외한 나머지 역량의 평균값은 높아졌으며, 창의융합, 문제해결, 자기주도 역량은 통계적으로 유의한 차이를 보였다. 그리고 모든 핵심역량 사이에 관계는 매우 높은 것으로 나타났다. 이러한 결과를 바탕으로 코로나19 시대 대학교육에서 핵심역량 향상을 위한 교수방법, 교육과정 및 프로그램 개발, 평가도구 개발 및 체계 마련, 콘텐츠 개발 및 학습관리체계 구축 등, 앞으로 대학교육이 나아가야 할 방향성에 대한 시사점을 도출하였다.The purpose of the study was to exploring implications in university education and seeking ways to operate university education through changes in core competencies of university students in the Untact era. To this end, a survey was conducted on 437 students who participated in the test for two consecutive years in 2020 and 2021, using a core competency diagnosis tool developed by G University located in Gyeongsangnam-do. Analysis of the relationship between the core competency and sub competency level and degree of change, and each competency was conducted. As a result of the analysis, the class 2020 improved all competencies except for global citizenship(global competency) and challenging spirit(leadership competency), and showed significant differences in creative convergence, problem solving, and self-direction. Students outside of class 2020, all competencies improved, and it was found that self-directed competencies were significant. Also, the relationship between all core competencies was found to be very high. Based on these results of this study, implications for the future direction of university education, such as teaching method, curriculum and program development, evaluation tool development and system preparation, content development and learning management system establishment, for improving core competency in university education in the Untact era Implications were drawn.
PENGEMBANGAN APLIKASI MONITORING EVALUASI PEMBELAJARAN SISWA SMP NEGERI 2 GEMPOL BERBASIS ANDROID DENGAN METODE RAD (RAPID APPLICATION DEVELOPMENT)

&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; Monitoring is a form of supervision carried out by teachers and parents on learning carried out by students. Parents can check the activities and liveliness in following the learning carried out by students such as attendance and doing assignments. The teacher's efforts in reminding students at school are still not able to maximize the implementation of learning and grades by students. Especially considering the current conditions in the midst of the Covid-19 pandemic, monitoring of students is less effective. This system has been tested several times in accordance with the expected needs and in accordance with the mutual agreement that this system has been successfully created. With the Android-Based Learning Evaluation Monitoring Application for SMP Negeri 2 Gempol Students, it can make it easier for teachers and parents to monitor the progress and activity of students in following the learning that has been carried out by students and is equipped with effective student assignments and attendance.&lt;/p&gt;
PENGARUH MEDIA AUDIOVISUAL DALAM KEMAMPUAN SISWA MENULIS PUISI

At this time poetry writing activities are less attractive to elementary school students even to the level of higher education students. This is due to their difficulty in determining themes, words and of course they are difficult to realize their fantasies in real life. Because writing this poem is writing that contains the results of one’s thought and feelings. Writing poetry can be easier and more fun if you use the right and enjoyable media. In this study, the aim was to see the magnitude of the influence of audiovisual media to improve students’ ability to write poetry. In this study using the literature review methode. This research shows that audiovisual media is very influential in improving students’ ability to write poetry. In this study, using the results of several studies that have been verified, the results show an increase as evidenced by the increasing number of percentages compared to before using audiovisual media.
Pemetaan Terhadap Penyebaran Unit Cabang Kantor Pos Di Kabupaten Wonogiri

The Post Office is one of the public facilities for the community because it serves service facilities in the form of postal services, package delivery, logistics and reliable financial services. However, the lack of information makes access to the location of post office services not informed of the location distribution. The purpose of this research is to create a mapping application for branch post office units to make it easier for the general public to get information about the nearest post office unit, using the K-Means Clustering Method. Users can choose which post office unit they want to choose based on their criteria. In functional testing (Blackbox) it was found that the system had been running according to the system design plan that had been made previously, while the validity test using the Silhouette Coefficient method showed the average value for cluster 1 was 0.282674, cluster 2 was 0.297377, and cluster 3 is 0.423516, which means the object is in a good or appropriate group because the Silhouette Coefficient value in each cluster is closer to 1, which means the better the grouping of data in one cluster.Keywords : K-Means Clustering, Post Office, Silhouette Coefficient
GRAMMATICAL INTRICACY AND LEXICAL DENSITY OF READING TEXTS OF ENGLISH TEXTBOOK FOR SENIOR HIGH SCHOOL GRADE XII

ABSTRACTThis study deals with the grammatical intricacy and lexical density of reading texts of English textbook for senior high school students grade XII. The objectives of this study are to investigate the level of grammatical intricacy (GI), and lexical density (LD) of the reading texts of English Textbook. This study was conducted by using descriptive qualitative and content analysis design. The data of this study were simple clauses, clauses complexes, sentences, lexical items and content carrying lexical items (nouns, verbs, adjectives and adverbs) of the English reading texts of Look Ahead 3, English textbook for senior high school grade XII published by Erlangga 2007. The result of the analysis showed that: (1).The level of grammatical intricacy of four out of six reading texts is high (3.53, 2.3, 2.71, and 2.25) and the other two texts are medium (2) and low (1.83). (2).The level of lexical density of four out of six reading texts are low (42.67%, 45.93%, 48.47%, and 36.99%) and the other two texts are high (58.36, and 55.40%). Keywords: grammatical intricacy; lexical density; reading texts
Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay (Student Abstract)

A lifelong learning agent is able to continually learn from potentially infinite streams of pattern sensory data. One major historic difficulty in building agents that adapt in this way is that neural systems struggle to retain previously-acquired knowledge when learning from new samples. This problem is known as catastrophic forgetting (interference) and remains an unsolved problem in the domain of machine learning to this day. While forgetting in the context of feedforward networks has been examined extensively over the decades, far less has been done in the context of alternative architectures such as the venerable self-organizing map (SOM), an unsupervised neural model that is often used in tasks such as clustering and dimensionality reduction. Although the competition among its internal neurons might carry the potential to improve memory retention, we observe that a fixed-sized SOM trained on task incremental data, i.e., it receives data points related to specific classes at certain temporal increments, it experiences severe interference. In this study, we propose the c-SOM, a model that is capable of reducing its own forgetting when processing information.
KATG: Keyword-Bias-Aware Adversarial Text Generation for Text Classification

Recent work has shown that current text classification models are vulnerable to small adversarial perturbation to inputs, and adversarial training that re-trains the models with the support of adversarial examples is the most popular way to alleviate the impact of the perturbation. However, current adversarial training methods have two principal problems: worse model generalization and ineffective defending against other text attacks. In this paper, we propose a Keyword-bias-aware Adversarial Text Generation model (KATG) that implicitly generates adversarial sentences using a generator-discriminator structure. Instead of using a benign sentence to generate an adversarial sentence, the KATG model utilizes extra multiple benign sentences (namely prior sentences) to guide adversarial sentence generation. Furthermore, to cover more perturbation used in existing attacks, a keyword-bias-aware sampling is proposed to select sentences containing biased words as prior sentences. Besides, to effectively utilize prior sentences, a generative flow mechanism is proposed to construct latent semantic space and learn a latent representation for the prior sentences. Experiments demonstrate that adversarial sentences generated by our KATG model can strengthen the victim model's robustness and generalization.
Flood disaster in South Sidoarjo, 1910–1957

Sidoarjo is geomorphologically located between two tributaries of the Brantas River, named as the Porong River and the Mas River.Because of the fertile soil, the Dutch East Indies Government built many sugar industries and sugarcane plantations.Additionally, the river streams in Sidoarjo's can lead to ecological problems, such as flooding.This research tries to find more about the flood disasters that have occurred frequently in Sidoarjo, especially in the Southern Sidoarjo, since the 20th century.The research uses historical methods that have five steps: topic selection, heuristics, source criticism, interpretation, and historiography.The research conclusion is that flooding is caused by geographical position and the frequency of high rainfall and land changes.
Planning to Avoid Side Effects

In sequential decision making, objective specifications are often underspecified or incomplete, neglecting to take into account potential (negative) side effects. Executing plans without consideration of their side effects can lead to catastrophic outcomes -- a concern recently raised in relation to the safety of AI. In this paper we investigate how to avoid side effects in a symbolic planning setting. We study the notion of minimizing side effects in the context of a planning environment where multiple independent agents co-exist. We define (classes of) negative side effects in terms of their effect on the agency of those other agents. Finally, we show how plans which minimize side effects of different types can be computed via compilations to cost-optimizing symbolic planning, and investigate experimentally.
Application of K-Means Clustering to Monitoring the level of Fertilizer Usage in Rice Fields in Ngawi Regency

Fertilizer is a substance given to plants that could be food for plants. Fertilizer itself divided into two types, that is inorganic fertilizers and organic fertilizer. Fertilizer is very important to the needs of farmers, especially farmers. Therefore fertilizer needs should be able to in monitoring in order not to occur lack. The purpose of this study is a grouping of the use of fertilizer in every town in the districts of Ngawi with k-Means algorithm. The formulation of the problem to overcome is how to apply the method of k-means algorithm to categorize fertilizer needs in every town in the Ngawi. K-means is clustering algorithm where one object can be in group based on data similarities. Clustering results K-means Clustering is seen in the first group high (Cluster 1) contains 6, In the second group medium (Cluster 2) contains 2 sub-districts, while in the third group low (cluster 3rd) contains 11 sub-districts.
BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract)

We present a method for constructing synthetic datasets of Competency Questions translated into SPARQL-OWL queries. This method is used to generate BigCQ, the largest set of CQ patterns and SPARQL-OWL templates that can provide translation examples to automate assessing the completeness and correctness of ontologies.
SISTEM MONITORING TERPADU PADA JASA LAUNDRY (STUDI KASUS MARKAS LONDRE)

&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; &lt;em&gt;At the Headquarters of Londre Data management is still done manually or still using paper and customer laundry items is estimated based on instinct, which means that every time a customer comes in, their laundry will be finished based on instinct so that consumers will have difficulty knowing the laundry is in the process and sometimes on the appointed day it was over, it was still not finished. The employees also had difficulties during the process of managing and controlling, because the number of orders increased and the employees also had difficulty when differentiating the customer's laundry items that had entered the laundry stages.&lt;/em&gt;&lt;/p&gt;&lt;em&gt;At the Londre Headquarters the monitoring process is still not available at that place. Therefore, this thesis will be made a "INTEGRATED MONITORING SYSTEM IN LAUNDRY SERVICES (LONDRE MARKAS CASE STUDY)" which will hopefully help owner and consumers in the monitoring process.&lt;/em&gt;
Implementasi Model Prototype untuk Pengembangan Sistem Informasi Bank Sampah Enviro 18

Waste Bank is a business The Enviro'18 entity engaged in the social sector that manages and utilizes waste with the aim of maintaining the environment and welfare in the surrounding community. Processes related to activities that can be carried out in the waste bank, such as customer registration, sales of waste, withdrawal of customer balances, preparation of waste sales reports. There are shortcomings in the waste bank process, where all processes are carried out manually and there is no system to facilitate the process. To overcome this, we need a web-based information system that aims to assist in managing customer data and waste data. Making this system using the System Development Life Cycle method with a prototype model. Based on the results of blackbox testing, it can be ensured that the system created can help make it easier for customers to register and view catalogs and make it easier for waste banks to collect waste data and manage data. Broadly speaking, from the test results, all system functionality can run well. This can be proven in process testing and can also be proven in the questionnaire analysis process which shows the functionality of the system that has been built is considered quite good in supporting the processes that run in the enviro'18 waste bank.
Enhance Weakly-Supervised Aspect Detection with External Knowledge (Student Abstract)

Aspect detection aims to identify aspects of reviews and is an essential up-stream task of opinion mining and so on. However, existing weakly-supervised methods suffer from lacking the ability of identifying implicit aspects with infrequent aspect terms and "Misc" aspects. To tackle these problems, we propose to enhance the representation of segment with external knowledge by a weakly-supervised method. Experiments demonstrate the effectiveness of our model and the improvement by incorporating external knowledge.
Prediksi Persediaan Obat Untuk Proses Penjualan Menggunakan Metode Decision Tree Pada Apotek

Inventory of drugs in a pharmacy is information that is needed to see the availability of drugs for the sales process. Oftentimes, the stock of drugs that are needed by the community is empty, while drugs that are not needed are actually abundant in stock in the warehouse. The unavailability of the drugs needed, of course, disappointed the people who were in dire need of these drugs. Meanwhile, the abundance of drugs that are not needed will cause losses because the drugs have expired due to being stored in the warehouse for too long. Another problem is that pharmacies feel overwhelmed in predicting which drugs are needed a lot and which drugs are not needed by the community. Considering that the prediction process is still manual, it is only by estimating it without any mathematical calculations.Based on these problems, the authors decided to design a drug inventory prediction system for the drug sales process using the decision tree method. The purpose of this study is how to build an application to predict drug sales that can be used to optimize drug stock control and increase sales at pharmacies.The Decision Tree algorithm is used because it is a suitable algorithm for classification problems and data mining, mapping attribute values into classes that can be applied to new classifications. The concept of the Decision Tree Algorithm is to convert data into a decision tree and decision rules. The Decision Tree Algorithm was introduced by (Quinlan, C.45: Programs for Machine Learning, 1993) which is a development of the ID3 Algorithm, the algorithm is used to form a decision tree. Decision tree is considered as one of the most popular approaches.The results of functional testing indicate that the application can run properly according to its design. The results of the validity test stated that the Prediction of Drug Sales at Pharmacies with the C.45 Method with 30 samples of sales transaction data had an accuracy of 89%, thus indicating that the system that has been created has a fairly good performance and can be used by pharmacies to predict drug sales in the future. which will come.
IMPROVING ENGLISH WRITING SKILL BY UTILIZING QUIZIZZ AS A TECHNOLOGY-BASED ASSESSMENT

The insertion of technology in English language teaching has been massively implemented by the English teachers during the pandemic Covid-19. This massive use of technology is also found during the assessment process. On the other hand, students still find difficulties in composing English texts. To fill this gap, this current study is investigating the current use of Quizizz as a technology-based assessment to improve the students’ writing skill during the English teaching and learning in the pandemic Covid-19. By deploying a pre-experimental research design, this study involved sixteen eighth grade students in SMP Negeri 13 Semarang as the subjects. To obtain the data, a writing test was employed in term of pre-test and post-test. The result shows that students’ writing skill was improved well after Quizizz was implemented regularly during the English teaching and learning. This result implies that Quizizz as a technology-based assessment helps the students to enhance their writing skill.