Reviewerly/exHarmony huggingface dataset:
HYDROPONIC MONITORING SYSTEM BASED ON AND MACHINE LEARNING

The process of increasing agricultural production is currently difficult due to limited land, the large amount of land that has been converted into industrial land areas causes the land to be narrowed and the quality of the agriculture is reduced, in large areas of agricultural land there are still obstacles including the crop control system in a large area and different causes difficulty in controlling food supply and regulating water distribution, the solution to this problem is to create a planting pattern using hydroponics, where the advantages of this method of farming can produce crop production with a limited area, a large area control system can use IOT technology, this technology is connected to several sensors that can measure room temperature, planting temperature and quality condition settings in testing this technology system is able to connect to applications in the form of web based or Android platforms so that the settings and information of bi If it is easily detected and recorded by the system, data from sensors can be stored and reused if needed, the data becomes a reference for plant conditions.
LibGuides: Science for First Grade: Ecosystems

This science based libguide is for first grade teachers and homeschool partnerships working with ages 5-7. It is specific to the North Carolina Common Core for science but is easily adaptable for other science curricula studies.
The Existential Basis of Consciousness: to the Analysis of Epistemological Limits of Symbolic Description of the Consciousness Functions

The purpose of the study is to establish the epistemological limits of the symbolic description of the consciousness functions. As a result of the study, the author comes to the conclusion that consciousness cannot be explained in computational terms, as there is something in its activity that goes beyond purely algorithmic actions. This is due to the small resource of human memory and there is no clearly fixed, clear purpose. In a situation of such uncertainty, it is impossible to build a clear algorithm of actions in advance, so a person is “doomed” to be a free and creative being. According to the author, consciousness is always opened through activity when it correlates behavior with space-time, cultural contexts, therefore, the existential basis of consciousness is revealed through its manifestation in the “world of ideas”, in the “world of values”, as well as in the “world of activity”, which helps to overcome the boundaries between these worlds in a single integrity of being.
A Reflection on Kyong-Bae Min’s Apolitical Interpretation of the Great Revival of 1907: Focusing on Problems and Development Plans

The purpose of this paper is to reflect on Kyong-bae Min’s apolitical interpretation of the Great Revival of 1907 (hereafter GR) in relation to its concept/definition, logic, and sources and discuss development plans for developing studies on the GR and politics. To achieve this, I will perform the following procedures; First, section two focuses on the concept/definition of his apolitical interpretation, reviewing the logic and the period of his view. Specifically, I shall test whether or not Min’s apolitical interpretation has problems, according to three criteria 1) I will focus more on the sources related to the results of the GR 2) Does Min use data produced between 1907 and 1910?, and 3) Are the data direct sources of the GR? and Who created the data?. Second, section three discusses how we can develop studies on the GR and politics, considering the conclusions from the previous section. The results are as follows. 1) we have to consider the historical context when defining concepts/terms, coming to a consensus on that among scholars and requiring collaboration. 2) we have to overcome studying loosely and pursue an goal to reconcile inductive/deductive method, and 3) we have to gather Korean sources of the GR. Finally, I shall sum up the previous sections and suggest my opinion about his apolitical interpretation and contributions and weaknesses of my paper. The contribution of this paper is related to reflect on his apolitical interpretation, which has dominated in the study of Korean church history.
Extractive Summarization System for Annual Reports

In this paper, we report on our experiments in building a summarization system for generating summaries from annual reports. We adopt an “extractive” summarization approach in our hybrid system combining neural networks and rules-based algorithms with the expectation that such a system may capture key sentences or paragraphs from the data. A rules-based TOC (Table Of Contents) extraction and a binary classifier of narrative section titles are main components of our system allowing to identify narrative sections and best candidates for extracting final summaries. As result, we propose one to three summaries per document according to the classification score of narrative section titles.
A Deep Learning Architecture for Profile Enrichment and Content Recommendation

The objective of our work is to propose a personalized recommender system based on user–resource interactions and user/resource characteristics in order to suggest the most appropriate resources to users. Recommender systems are commonly used in connection with artificial intelligence because machine learning techniques are frequently used to create recommendation algorithms. We suggest using neural networks to improve resource suggestions. Neural networks can quickly perform complex tasks and easily handle massive data. Our new approach is based on an auto-encoder used as a data extractor to improve user performance and a deep neural network (DNN) for item recommendation. For this, we use an information extraction technique based on the reduction of dimensionality by the use of an auto-encoder to compress the features (the proposed tags). We want to create some semantics between the data in order to enrich the profile of the user. Then based on the history of user ratings as well as data on users and items (useful information such as genre, year, tag and rating), we develop a framework for deep learning to learn a similarity function between users and predict item ratings. We evaluate the effectiveness of the proposed approach through an experimental study on a real-world dataset such as the MovieLens film recommender system, according to a number of properties. Experimental validation combines both the accuracy of the recommendation system and a set of quality metrics.
Education of Expression as a Cognitive Process

The study emphasizes the writing in pursuit of individual ideas, expressions, and cognitive process. A new model of writing education was created based on the cognitive process which involves responding to stimuli of objects with five senses - integrating sensory information with previous experiences to establish an objective and detailed recognition framework, - subjectively conceptualizing the perception, cause, and judgment. In particular, the study highlights the following concepts : ① To absorb an object with all five senses ② To make an emotional communion with an object in various contact methods ③ To draw out previous experiences and integrate with current experiences in order to exercise imagination and creativity ④ To connect and newly conceptualize the essence of object and the essence of ‘I’ and the nature of life by putting I into the object. Accordingly, the study involves the following stages : ① The Sensory stage : conducting ‘sensory reaction training’ → ‘activate five senses’ ② The Detection stage : writing a sensory response diary. ③ The Perception stage : splitting into a small group of three to four members to practice ‘finding sensory search terms and sensory descriptive terms’ → ‘sharing the story of experiences’ ④ The Cognition stage : ‘dialoguing with objects’ → ‘categorize the properties of objects’ → ‘imagine ‘I’ become an object and make a description in the first point of view’ → ‘a few moments of quite meditation’ ⑤ The Writing stage : using landscape photos containing various objects, writing practice incorporating the cognition process was conducted ⑥ The Final stage : stating one’s impression in writing after finish writing practice. The writing in pursuit of cognitive process is an effective way that can restore modern peoples brains, which are transforming into the reptile brains nowaday, but also modern peoples lives into a decent human life. After completing the writing in pursuit of cognitive process, students have stated following thoughts behind: ‘insight into the appearance and properties of objects’·‘fe ling of being one with objects through communion’·‘fe ling of positively changed mind and widen views’·‘had a chance of improving myself’·‘a lot of things to express and hold.’ In conclusion, the writing in pursuit of cognitive process reminds us once again what the equation of life = writing signifies, and the equation of life = writing is the truth that penetrates the nature of life and the nature of writing.
Extracting fine-grained economic events from business news

Based on a recently developed fine-grained event extraction dataset for the economic domain, we present in a pilot study for supervised economic event extraction. We investigate how a state-of-the-art model for event extraction performs on the trigger and argument identification and classification. While F1-scores of above 50{%} are obtained on the task of trigger identification, we observe a large gap in performance compared to results on the benchmark ACE05 dataset. We show that single-token triggers do not provide sufficient discriminative information for a fine-grained event detection setup in a closed domain such as economics, since many classes have a large degree of lexico-semantic and contextual overlap.
Improper versus finitely additive distributions as limits of countably additive probabilities

The Bayesian paradigm with proper priors can be extended either to improper distributions or to finitely additive probabilities (FAPs). Improper distributions and diffuse FAPs can be seen as limits of proper distribution sequences for specific convergence modes. In this paper, we compare these two kinds of limits. We show that improper distributions and FAPs represent two distinct features of the limit behavior of a sequence of proper distribution. More specifically, an improper distribution characterizes the behavior of the sequence inside the domain, whereas diffuse FAPs characterizes how the mass concentrates on the boundary of the domain. Therefore, a diffuse FAP cannot be seen as the counterpart of an improper distribution. As an illustration, we consider several approach to define uniform FAP distributions on natural numbers as an equivalent of improper flat prior. We also show that expected logarithmic convergence may depend on the chosen sequence of compact sets.
Penerapan Model Waterfall Pada Sistem Informasi Penjualan Berbasis Web

Technology has become a necessity that cannot be separated from lifestyle, even in its development humans are increasingly dependent on technology. In the field of business, the development of information technology has had a significant impact in increasing business activities, especially in terms of data management that provides support for business decision making and in terms of improving services. Everest Chicken Penyet Restaurant is a company engaged in the sale of food in the form of fried chicken, penyet chicken, sweet grilled chicken, spicy grilled chicken, duck penyet, catfish penyet and many others. At present the sales system at Ayam Penyet Everest Restaurant has not used a computerized system, the workmanship is still manually where it still uses a handwriting system to recap the ordered product data and the sales process. The research method used is a research and development method with the waterfall model. The results of this study are customers get information about the latest menus quickly on the Ayam Penyet Everest website, so that it becomes more efficient. With a web-based sales information system this makes the company's performance better and more professional in its activities. .
Local Competition and Stochasticity for Adversarial Robustness in Deep Learning

This work addresses adversarial robustness in deep learning by considering deep networks with stochastic local winner-takes-all (LWTA) activations. This type of network units result in sparse representations from each model layer, as the units are organized in blocks where only one unit generates a non-zero output. The main operating principle of the introduced units lies on stochastic arguments, as the network performs posterior sampling over competing units to select the winner. We combine these LWTA arguments with tools from the field of Bayesian non-parametrics, specifically the stick-breaking construction of the Indian Buffet Process, to allow for inferring the sub-part of each layer that is essential for modeling the data at hand. Then, inference is performed by means of stochastic variational Bayes. We perform a thorough experimental evaluation of our model using benchmark datasets. As we show, our method achieves high robustness to adversarial perturbations, with state-of-the-art performance in powerful adversarial attack schemes.
메이지기 일본 국어 교과서의 접사(接辭) 설정 양상 고찰 -「초학일본문전(初學日本文典)」을 중심으로-

This paper is an exploration of the affix classification system set in “初學日本文典(Shogakunihonbunten)”, an elementary school language textbook used in Japan as one of the studies to investigate the process of establishing the grammar of contemporary Japanese schools.“初學日本文典(Shogakunihonbunten)” is one of the Japanese language textbooks published by Mozume Takami in the early days of introducing the Meiji period and Western school system.This book is composed of two volumes, upper and lower. The upper volume explains ‘體言(uninflected word)’ and ‘用言(predicate)’, and the lower volume explains ‘接辭(setsuji)’.Mozume presents 20 affixes through “初學日本文典(Shogakunihonbunten)”, which are almost equivalent to ‘助詞(postposition)’, ‘副詞(adverb)’, ‘助動詞(auxiliary verb)’ in contemporary Japanese school grammar. It became clear that the collection treated ‘體言(uninflected word)’ and ‘用言(predicate)’ as the main component of the sentence, and otherwise treated it as an ‘接辭(setsuji)’ and treated it as a so-called accessory component.
NLPRL System for Very Low Resource Supervised Machine Translation.

This paper describes the results of the system that we used for the WMT20 very low resource (VLR) supervised MT shared task. For our experiments, we use a byte-level version of BPE, which requires a base vocabulary of size 256 only. BPE based models are a kind of sub-word models. Such models try to address the Out of Vocabulary (OOV) word problem by performing word segmentation so that segments correspond to morphological units. They are also reported to work across different languages, especially similar languages due to their sub-word nature. Based on BLEU cased score, our NLPRL systems ranked ninth for HSB to GER and tenth in GER to HSB translation scenario.
ASSESSING THE FRUSTRATIONS OF PRACTICING USER EXPERIENCE DESIGN (UXD) AMONG THE UXD COMMUNITY OF PRACTICE IN MALAYSIA: A NETNOGRAPHIC APPROACH

In this study, netnography, an ethnography method used to study communities on the Internet was employed. It adapted common ethnographic participant-observation procedures such as making a cultural entrA©e, gathering and analysing data, ensuring trustworthy interpretation, conducting membership checks and conducting ethical research in computer-mediated contingencies. The results reveal a collection of UXD practice related frustrations in industry.
Efektifitas Pembelajaran Sistem Daring (Online) Mata Kuliah Statistik Ekonomi Di Masa Pandemi

The period of the Covid 19 pandemic continues and do not know how long it will end, the world of education must continue to run, many methods are used to deliver lecture material for students. Especially in PTS, where PTS is very dependent on students for the sustainability of educational institutions, they continue to look for the best way to provide services to their students. One of the ways that is used is with an online system, this system in certain subjects, for example, economic statistics, becomes a relatively difficult system to implement. Therefore, in this study, a study was carried out to what extent the application of online systems was able to achieve learning outcomes that were ideally achieved by lecturers in teaching. This study used a descriptive descriptive method, in which a survey research was carried out by describing the achievement of learning economic statistics subjects to students. The questionnaire was conducted by assessing the responses of students receiving lectures using an online system during this pandemic. The data analysis technique uses descriptive techniques by comparing the reality with the ideal according to the concept. The results showed that the effectiveness of statistical learning with this online system had a positive and significant impact on student satisfaction in learning as well as increasing the enthusiasm for learning and the seriousness of students in learning statistics.
Privacy preserving-aware over big data in clouds using GSA and MapReduce framework

This paper proposes a privacy preserving-aware-based approach over Big data in clouds using GSA and MapReduce framework. It consists of two modules such as; MapReduce module and evaluation module. In MR module, convolution process is applied to the dataset and creates a new kernel matrix. The convolution process is correctly done; the utility and privacy information of the data is well secured. Once the convolution process is over, the privacy-persevering framework over big data in cloud systems is performed based on the evaluation module. In Evaluation module, the neural-network is trained based on the Gravitational Search Algorithm with Scaled conjugate gradient (GSA-SCG) algorithm which is improving the utility of the privacy data. Finally, the reduced privacy data's are stored in the service provider (CSP). The MapReduce framework is to ensure the private data, which is in charge for anonymising original data sets as per privacy requirements.
My face is yours: facial recognition software and copyright ownership

The popular NBA 2K series include a facial recognition software that scans the user's face to generate a lookalike avatar. However, end user licence agreements provide for all intellectual property rights, including copyright, to be licensed or assigned to game publishers or developers. Consequently, the user may have no say whether an avatar with their facial features may be used, for instance in advertising for the game. In addition, the facial features stored in the game may be biometric data, and thus subject to strict data protection rules. This paper will analyse whether the avatar generated using a face scan is a copyrightable work of authorship. The analysis questions whether the face scan fits into different categories of works; photography, film and databases, including the sui generis photography and database rights. It concludes that copyright fails to protect the individual's facial features. Even so, the ownership clause in licence agreements on the one hand and the facial features as biometric data on the other further complicate the question of what the individual can assert as his own.
How to increase hotel employee organisational job embeddedness: management commitment to safety perspective

There are many problems with staff turnover in the hospitality industry. Drawing from social exchange and conservation of resources theories, this study extends and tests a theoretical model of organisational job embeddedness using a confirmatory analysis. The data was collected from 202 frontline hotel employees working in Abuja through a structured questionnaire and analysed using SmartPLS 3.2.6. The findings show that distributive justice, procedural justice and perceived job security predict organisational job embeddedness. Further, management commitment to safety moderated the links between the predictors' constructs and organisational job embeddedness. The relationship between procedural justice and perceived job security on organisational job embeddedness is stronger for hotels with a high level of management commitment to safety, but not for hotels with a low level of management commitment to safety. However, unexpectedly, the relationship between distributive justice and organisational job embeddedness is stronger for hotels with a low level of management commitment to safety, but not for hotels with high levels of management commitment to safety. Implications and future research directions are provided.
Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation

We propose a new character-based text classification framework for non-alphabetic languages, such as Chinese and Japanese. Our framework consists of a variational character encoder (VCE) and character-level text classifier. The VCE is composed of a β-variational auto-encoder (β -VAE) that learns the proposed glyph-aware disentangled character embedding (GDCE). Since our GDCE provides zero-mean unit-variance character embeddings that are dimensionally independent, it is applicable for our interpretable data augmentation, namely, semantic sub-character augmentation (SSA). In this paper, we evaluated our framework using Japanese text classification tasks at the document- and sentence-level. We confirmed that our GDCE and SSA not only provided embedding interpretability but also improved the classification performance. Our proposal achieved a competitive result to the state-of-the-art model while also providing model interpretability.
Potential applications of smart contract technology in subsidy distribution (source code for data structures and problem solving using solidity)

The way governments distribute subsidies in terms of targeting and their effects on public economics has always been one of the biggest management challenges, especially in developing countries. The purpose of this research is to outline the application of blockchain technology in the context of the subsidies distribution through the transfer of digital currency; also, a blockchain-based targeted subsidy system has been performed under the Ethereum network using solidity language. The written program is based on a platform extracted from the library research method and through the research conducted over recent years. This study aims to achieve an intelligent, autonomous, and self-executing subsidy distribution system. Furthermore, this study can make it possible for governments to provide a subsidy payment platform that can prevent data manipulation due to its decentralised nature, create a more reliable method for subsidy payments, and increase transparency in the distribution of subsidies.
Blockchain's influence on digital marketing : An exploratory study examining blockchain in relation to big data and digital marketing

Today's society has grown to be highly digitalized where technologies are playing a large role in everyone's lives. Moreover, society is still developing at a rapid pace, with a new innovation arou ...
Student models to generate automated feedback on intermediate steps in solving mathematical problems

Digital technology can help with providing detailed assessment of mathematical competences. We present the Advise-Me project, in which evidence of the level of mastery is collected from free-form input, without restricting user interaction. We discuss the novel components of our approach, such as the use of a domain reasoner and Bayesian networks for open algebra problems, and an upcoming evaluation study in three countries.