Reviewerly/exHarmony huggingface dataset:
Movie Recommendation System Using Item Based Collaborative Filtering

In today's digital world where there is an endless variety of content consumed such as books, videos, articles, Films, etc., finding material of one's choice has become an infallible task. Digital content on the other hand Providers want to engage more and more users in their service for maximum time. Where is it the recommender system comes into picture where content providers advise users by content User choice in this paper we have proposed a movie recommendation system .Purpose of movie recommendation system aims to provide users with accurate movie recommendations. Usually basic recommendation system to make recommendations consider one of the following factors; User preference known as content based Filtering or the preference of similar users known as collaborative filtering. To create a stable and accurate recommender system will use of content based filtering.
COMPARISION OF PREPROCESS TECHNIQUES FOR BRAIN IMAGE USING MACHINE LEARNING

A brain tumour is the second leading cause of death in young people.. Tumors of the brain come in a wide range of shapes and sizes. Noncancerous brain tumour exist alongside cancerous brain tumors. In medical image processing, detecting and segmenting brain tumors is extremely difficult. Four forms of preprocessing are used here: Adaptive Median Filter (AMF), Median Filter, Gaussian Filter and Wiener Filter. The performance metrics were then determined using the following1.The Mean Square Error Rate (MSE) is a measurement of a system's accuracy.2.Signal-to-Noise Ratio at Peak (PSNR)Structure Similarity Index 4.Number four is the Spearman rank correlation. The Adaptive median Filter produces the best results for both regular and abnormal images based on the above measurements.
Knowledge Consolidation based Class Incremental Online Learning with Limited Data.

We propose a novel approach for class incremental online learning in a limited data setting. This problem setting is challenging because of the following constraints: (1) Classes are given incrementally, which necessitates a class incremental learning approach; (2) Data for each class is given in an online fashion, i.e., each training example is seen only once during training; (3) Each class has very few training examples; and (4) We do not use or assume access to any replay/memory to store data from previous classes. Therefore, in this setting, we have to handle twofold problems of catastrophic forgetting and overfitting. In our approach, we learn robust representations that are generalizable across tasks without suffering from the problems of catastrophic forgetting and overfitting to accommodate future classes with limited samples. Our proposed method leverages the meta-learning framework with knowledge consolidation. The meta-learning framework helps the model for rapid learning when samples appear in an online fashion. Simultaneously, knowledge consolidation helps to learn a robust representation against forgetting under online updates to facilitate future learning. Our approach significantly outperforms other methods on several benchmarks.
The Exploration of Applying Gamificationalized Mobile Learning Concept in the Field of Education

With the continuous integration and innovation of information technology and education, mobile learning based on the concept of game-based learning is increasingly favored in the field of education because of its fun, mobility and fragmented learning experience. This paper takes the concept of gamification mobile learning as the core research, while expounding the concept of gamification and mobile learning, by analyzing the advantages of the game-based mobile learning mode and carrying out in-depth thinking, hoping to provide reference for the application of gamification mobile learning.
Analysis of the operational benefits of hybrid hydropower-floating solar photovoltaic systems

&amp;lt;p&amp;gt;Floating solar photovoltaics (FPV) systems have become an attractive RE option due to their potential energy, environmental, and social benefits. FPV systems have been deployed as standalone systems and hybridized with other generation or energy storage technologies. Hybrid FPVs, especially those paired with hydropower plants, are of specific interest because of potential cost and performance benefits such as improved system operation at different time scales, additional energy storage opportunities, improved transmission utilization, reduced solar PV curtailment, and water conservation. Despite the interest in hybrid hydropower-FPV systems, there is limited research quantifying the operational benefits of these hybrid systems. To help address this research gap, this study analyzes the potential grid-level operational benefits of a generic hybrid hydropower-FPV system through a modeling exercise. Using a solar resource time-series and resource data for an example hydropower plant, we quantify the potential curtailment reduction, increased transmission utilization, and changes in seasonal and diurnal electricity generation for the hybrid FPV system compared to stand alone systems. Results suggest that depending on the seasonality of hydropower resources and the ratio of the size of the FPV system to hydropower plant sizes, the hybrid hydropower-FPV system could reduce curtailment and lead to more optimal use of limited water resources.&amp;lt;/p&amp;gt;
THE EFFECTIVENESS OF USING VOCABULARY SELF-COLLECTION STRATEGY (VSS) IN TEACHING READING COMPREHENSION OF NARRATIVE TEXT AT THE EIGHTH GRADE STUDENTS OF SMP 25 PURWOREJO IN THE ACADEMIC YEAR OF 2019/2020

Abstract: This research is conducted to know the students’ reading comprehension and to find out whether or not use of vocabulary self-collection strategy (VSS) effective in teaching reading of SMP 25 Purworejo in the academic year of 2019/2020. The population of this research is 186 students of the eighth grade students of SMP 25 Purworejo in the academic year of 2019/2020 and the amount of sample is 30 students. From the computation, the result showed that the mean score of pre-test is 62.93 (sufficient category) and the mean of post-test is 77.07 (good category). It shows that the result of computation is t value obtained bigger than t table (3.705>2.000) it can be concluded that vocabulary self-collection strategy (vss)is effective to teaching reading Narrative text at the eighth grade students of SMP 25 Purworejo in the academic year of 2019/2020. Key w ords : e ffectiveness, vocabulary self-collection strategy (vss), reading comprehension,narrative text.
PERANCANGAN APLIKASI PERMAINAN ANDROID RHINO RUN UNTUK MENUMBUHKAN KEPEDULIAN PADA BADAK BERCULA SATU UNTUK ANAK USIA 7-12 TAHUN

This paper aims to explain how gaming applications can be a medium of approach and introduction to Javan rhinoceros (or widely known as the lesser one-horned rhinoceros) especially for children. From the creator's observation towards children's habits, the creator is aware that today, children are actively using smartphones. Therefore, the creator thinks about the benefits that can be derived from the aforementioned habits, especially about the best approach solution to cultivate a sense of caring for other organisms. Parents can still interact and guide the children while they play the gaming applications such as animal names, native habitats, and their foods. This gaming application introduces the children how the lesser one-horned rhinoceros, and their native habitat. This gaming application is based on communication theory, visual communication theory, and refers to gameplay theory. The creator is inspired by several gaming applications, namely Temple Run by Imangi Studio, Subway Surf by Kiloo, Despicable Me Minion Rush by Gameloft, and Sonic Dash by Sega. It can be concluded that this gaming application was created with the aim of introducing and approaching the children about the lesser one- horned rhinoceros.
FORMATION OF CIVIL COMPETENCE OF FUTURE TEACHERS

From the point of view of the modern competence approach in modern education, civil competence is one of the most important learning outcomes. Therefore, the article is devoted to an urgent problem that meets the needs of today. Today, in the conditions ofchanging life, not only flexibility of adaptation is required, but also the need for continuous professional development, including the formation of civil competence of future teachers. The authors analyzed the ways and methods of formation of civil competence of students in secondary schools. Taking into account that the future teacher is tomorrow's young specialist who needs to be deeply involved in the educational process of the school, effective, advanced methods of forming students ' civic competence are analyzed. Based on the coverage of research papers on the research topic, the author's conclusion is given
Color2Style: Real-Time Exemplar-Based Image Colorization with Self-Reference Learning and Deep Feature Modulation.

Legacy black-and-white photos are riddled with people's nostalgia and glorious memories of the past. To better relive the elapsed frozen moments, in this paper, we present a deep exemplar-based image colorization approach named Color2Style to resurrect these grayscale image media by filling them with vibrant colors. Generally, for exemplar-based colorization, unsupervised and unpaired training are usually adopted, due to the difficulty of obtaining input and ground truth image pairs. To train an exemplar-based colorization model, current algorithms usually strive to achieve two procedures: i) retrieving a large number of reference images with high similarity in advance, which is inevitably time-consuming and tedious; ii) designing complicated modules to transfer the colors of the reference image to the grayscale image, by calculating and leveraging the deep semantic correspondence between them (e.g., non-local operation). Contrary to the previous methods, we solve and simplify the above two steps in one end-to-end learning procedure. First, we adopt a self-augmented self-reference training scheme, where the reference image is generated by graphical transformations from the original colorful one whereby the training can be formulated in a paired manner. Second, instead of computing complex and inexplicable correspondence maps, our method exploits a simple yet effective deep feature modulation (DFM) module, which injects the color embeddings extracted from the reference image into the deep representations of the input grayscale image. Such design is much more lightweight and intelligible, achieving appealing performance with real-time processing speed. Moreover, our model does not require multifarious loss functions and regularization terms like existing methods, but only two widely used loss functions. Codes and models will be available at this https URL.
Anaphora Resolution in Punjabi Language

In this paper, we present an effort to implement an AR (Anaphoric Resolution) system in Punjabi, a language with limited resources. For this task, we developed our own corpus and used the Punjabi Shallow Parser to provide the required information like part of speech (POS) tags, chunking information, gender, person and number. The data is manually annotated with attributes - animacy, pronoun type, NER and links of anaphors to corresponding entities. This paper introduces the first attempt to perform anaphora resolution in Punjabi using Machine Learning approach. It has been represented as a two-class classification problem. Features are extracted from the annotated corpus and different classifiers have been used to perform the task. Precision, Recall and F-Score are used as evaluation metrics. Analyzing the results, it has been observed that the performance of Ensemble classifiers is better than the rest of the classifiers. To analyze the contribution of different features, we experimented using a different subset of features during classification and analyze the performance of the system. Accuracy of pre-processing tool i.e. Punajbi Shallow Parser and quality of annotation task also contributes to the overall performance of the system. As it is pioneering work, results can be enhanced by using a larger corpus and employing rule-based strategy along with machine learning approach which is the future scope for the present work.
Verifying the Classification Accuracy for Korea's Standardized Classification System of Research F&E by using LDA(Linear Discriminant Analysis)

Recently, research F&E(Facilities and Equipment) have become very important as tools and means to lead the development of science and technology. The government has been continuously expanding investment budgets for R&D and research F&E, and the need for efficient operation and systematic management of research F&E built up nationwide has increased. In December 2010, The government developed and completed a standardized classification system for national research F&E. However, accuracy and trust of information classification are suspected because information is collected by a method in which a user(researcher) directly selects and registers a classification code in NTIS. Therefore, in the study, we analyzed linearly using linear discriminant analysis(LDA) and analysis of variance(ANOVA), to measure the classification accuracy for the standardized classification system(8 major-classes, 54 sub-classes, 410 small-classes) of the national research facilities and equipment established in 2010, and revised in 2015. For the analysis, we collected and used the information data(50,271 cases) cumulatively registered in NTIS(National Science and Technology Service) for the past 10 years. This is the first case of scientifically verifying the standardized classification system of the national research facilities and equipment, which is based on information of similar classification systems and a few expert reviews in the in-outside of the country. As a result of this study, the discriminant accuracy of major-classes organized hierarchically by sub-classes and small-classes was 92.2 %, which was very high. However, in post hoc verification through analysis of variance, the discrimination power of two classes out of eight major-classes was rather low. It is expected that the standardized classification system of the national research facilities and equipment will be improved through this study.
On Maxwell’s Reversed Laws as Root of Magnetic Monopoles in Dark Matter

According to the Standard Model of cosmology, dark matter is an entity to explain the dynamics of galaxies and structures on a larger scale. Ubiquitous, it represents about 80% of the matter in the universe. Evanescent to the extreme, it resists any attempt at detection, whether by astronomers or particle physicists. We do not know what it consists of and could be very different from what we think. We offer another track to apprehend this deep something that escapes us. The idea is this. To explain dark matter, we conjectured that it is composed of very light or very heavy particles, such as neutrinos and antineutrinos associated with a magnetic charge and that these neutrinos essentially originate from primordial black holes and classical black holes. We therefore assumed that when baryonic matter crosses the event horizon and there is a blackout, Maxwell's laws are reversed, the electric charge turns into a magnetic charge and it is the magnetic current that induces electric current. In the peripheral internal regions of the black hole, the density and temperature of baryonic matter are very high. The particles would undergo a phase transition and behave like magnetic particles. Standard neutrinos become sterile magnetic neutrinos, true magnetic monopoles. Neutrinos cross the horizon (in several ways) outward to form this all-pervading darkness. They would be essential to the formation of galaxies and clusters of galaxies. The model we are sketching indicates that sterile neutrinos associated with a magnetic charge would interact with the weak force via the magnetic fields that shape the cosmos. These neutrinos form the halos that surround galaxies. They receive the energy of magnetic fields from stars of outer galaxies or pulsars and would be related to the distribution of visible and invisible matter. The magnetic energy, converted into kinetic energy, which they receive from magnetic fields could cause gamma-ray glows in the dark.
SISTEM TATA KELOLA KEAMANAN TEKNOLOGI INFORMASI BERBASIS FRAMEWORK COBIT 5 (STUDI KASUS : SMA NEGERI 1 PALEMBANG)

SMA Negeri 1 Palembang is a favorite national high school located in Palembang. This school applies technology of information in its teaching system to support learning system dan school's vision and mision. This study determined the domain process in control objectives for information and related technology (COBIT 5) and the  measurement of capability level of in formation technology security management. Methods used are descriptive, cualitative and balance score card (BSC) analysis and COBIT 5. Based on The result of the study, it is found out that the domain process of cobit framework 5 which is appropriately used with the information technolgy security system are: (1). APO13 level 2-managed process,. (2). DSS02 level 2- managed process and (3). DSS05 level 2 -managed process.
인공지능기술과 우리나라 특허법의 발명의 성립성

This article studies a potential conflict between artificial intelligence (AI) inventions and the Korean jurisprudence of patentability (or patent-eligibility). Article 2(1) of the Korean Patent Act defines an invention as “the highly advanced creation of technical ideas utilizing the law of nature.” Among others, Korean patent law determines patentability of an invention based on whether the invention “utiliz[es] the law of nature.” Abstract ideas and human mental steps are excluded from patentable subject matter as they do not “utiliz[e] the law of nature.”More specifically, when determining the patentability of the invention, the Korean Patent Office and the Korean courts focus on 1) whether the invention has a technical character, 2) whether the invention has specific and practical effects, and 3) whether the invention has technical means to bring about such effects. According to case law, an invention is held to be patentable when the invention physically transforms an object to another within or outside hardware. In addition, an invention is deemed patent-eligible when the invention specifically implements information processing by software to hardware or a computer. The Korean jurisprudence of patent-eligible subject matter seems to share some similarities with that of Japan, the United States, and Europe.With the development of AI technology, AI invention may be at odds with the Korean jurisprudence of patent-eligible subject matter in the following aspects. First, it is hard to explain the mechanism of AI, while the specification of an AI patent should specifically describe the invention in detail in order for the invention to be patentable. Second, AI is applied to non-technical fields such as linguistics, literature and economics, as well as technical fields such as science and engineering. Such a broad application of AI technology may be inconsistent with the jurisprudence of patent-eligibility, which requires that inventions have technical characteristics to be patent-eligible. Third, as AI evolves from weak AI to strong AI, Korean courts are likely to deny the patentability of AI invention on the ground that the invention merely applies an abstract idea or a human mental process to a general-purpose computer without an inventive concept.Fortunately, the potential conflict could be resolved by a flexible interpretation of the term “invention” under the Korean Patent Act. Without a revision of the Patent Act by the legislature, Korean courts and the Korean Patent Office should be allowed to broadly interpret the phrase “utilizing the law of nature” of the Patent Act, expanding the scope of the term “invention” to include AI technology.
Reaksi Fisi dan Reaksi Fusi dalam Mekanisme Bom Atom dan Senjata Termonuklir

Tujuan penelitian ini membahas mengenai reaksi fisi dan fusi pada bom atom dan senjata termonuklir. Penelitian ini adalah penelitian kualitatif, jenis penelitiannya menggunakan studi analitik komprehensif. Bagian paling vital dari ledakan fisi yang terjadi dalam bom atom tak lain adalah material yang berfisi itu sendiri. Ada dua unsur radioaktif yang biasa dipakai, yakni uranium dan plutonium, masing-masing dengan aneka isotopnya. Mulai dari U-232, U-234, U-235, dan U-238 untuk uranium, hingga Pu-238, Pu-239, dan Pu240 untuk plutonium. Elemen pemicu ledak yang dipakai dalam ledakan termonuklir ialah deuterium (D) alias hydrogen berat atau yang juga popular dengan sebutan ‘air berat’ (heavy water). Dari setiap 5000 atom hydrogen, bisa dipastikan satu isotop di antaranya dalam bentuk deuterium. Inti deuterium (deutron) terdiri dari satu proton (p) dan satu neutron (n). saat berpasangan, dua deutron membentuk inti atom helium (He-4) yang relatif stabil. Dalam semua jenis reaksi ini, inti atom berat terbentuk melalui proses fusi. Kata Kunci: bom atom, reaksi fisi, reaksi fusi, senjata termonuklir The purpose of this research is to discuss fission and fusion reactions in atomic bombs and thermonuclear weapons. This research is a qualitative research. This type of research uses a comprehensive analytical study. The most vital part of the fission explosion that occurs in an atomic bomb is none other than the fission material itself. There are two radioactive elements in common use, uranium and plutonium, each with its different isotopes. They range from U-232, U-234, U-235, and U-238 for uranium, to Pu-238, Pu-239, and Pu240 for plutonium. The explosive trigger element used in thermonuclear explosions is deuterium (D) heavy hydrogen or also popularly known as "heavy water" (heavy water). For every 5000 hydrogen atoms, one can be sure of one of them in the form of deuterium. The nucleus of heuterium (deutron) consists of one proton (p) and one neutron (n). When paired, the two deutrons form a relatively stable nucleus of helium (He-4). In all of these types of reactions, heavy atomic nuclei are formed by fusion. Keywords: atomic bombs, fission reactions, fusion reactions, thermonuclear weapons
한국 대학생들의 영어 작문에서 접속어 사용 코퍼스 분석

The purpose of this study was to analyze the use of connectors in English writing between Korean college students’ corpus and LOCNESS. Specifically, the study examined the students’ use of connectors in terms of the three categories of connectors such as coordinators, subordinators, and conjunctive adverbials by Yoon and Yoo(2007) and four categories of the conjunctive adverbials by Celce-Murcia and Larsen-Freeman(1999). The participants were 24 students who took the Intermediate English Composition in a local university in Busan. The findings have shown that the Korean university students overused ‘but, when, so, first’ and underused ‘and’ than LOCNESS. In addition, the findings showed that their use of connectors have increased gradually over the course of the semester. The findings will shed light on how better college instructors may be able to help teach the use of connectors in Korean students’ English writing.