Reviewerly/exHarmony huggingface dataset:
작문 수준에 따른 통사적 복잡성과 유창성 연구

In Korean writing, the proposition that it is better to write short sentences needs to be studied academically. The purpose of this study is to statistically analyze the syntactic complexity and fluency characteristics of learner texts according to the writing level in terms of sentence length. The hypotheses of this study are as follows. First, syntactic complexity and fluency will differ depending on the level of writing. Second, syntactic complexity and fluency will have a correlation with the level of writing. Third, Syntax complexity and fluency are correlated.As a result of the study, first, syntax complexity and fluency were significantly different according to the writing level because the upper text was high and the lower text was low. Second, syntactic fluency was significantly correlated with the high upper text and lower text. Third, syntax complexity and fluency were not significantly correlated in the upper text group, but there was a close correlation in the lower text group.
AI-based chatbots in customer service and their effects on user compliance

Communicating with customers through live chat interfaces has become an increasingly popular means to provide real-time customer service in many e-commerce settings. Today, human chat service agents are frequently replaced by conversational software agents or chatbots, which are systems designed to communicate with human users by means of natural language often based on artificial intelligence (AI). Though cost- and time-saving opportunities triggered a widespread implementation of AI-based chatbots, they still frequently fail to meet customer expectations, potentially resulting in users being less inclined to comply with requests made by the chatbot. Drawing on social response and commitment-consistency theory, we empirically examine through a randomized online experiment how verbal anthropomorphic design cues and the foot-in-the-door technique affect user request compliance. Our results demonstrate that both anthropomorphism as well as the need to stay consistent significantly increase the likelihood that users comply with a chatbot’s request for service feedback. Moreover, the results show that social presence mediates the effect of anthropomorphic design cues on user compliance.
Experimental Analysis of Hybrid UAV at Different Velocities

The primary goal of this project is to constricting a hybrid UAV with both rotary and flapping wing. The primary objective of this project is to find the Lift in respect to RPM/Frequency in different modes of operation i.e. with operating only the propeller, flapping wing and with both propeller and flapping wing working simultaneously. For finding lift we will be using load cell. we will be studying the effect of a Flapping Wing when placed in Quadcopter and check whether the result have a positive effect or negative effects. The end result show's that there's a minute increase in lift when flapping wing is added to a quadcopter
증거성 표지의 통사적 투사

Languages like Korean employ evidentiality markers such as Inference -kyess-, Sensory -ney/-te-, Reportative -ay, and Quotative -ko. These evidentiality markers receive interpretations outside the scope of negation and certain adverbs are associated with a particular evidential marker. In addition, certain evidentiality markers co-occur while other evidential markers exhibit a co-occurrence restriction. In order account for these facts, the current paper proposes a slightly complicated but fine structure of C area with evidentiality markers. Each evidentiality marker occurs on the relevant functional head in the C domain. By positing this fine structure of CP, the facts that evidentiality is out of the scope of negation and the choice of certain adverbs as well as the selectional restrictions between the functional heads can be accounted for.
ENHANCING STUDENTS' SPEAKING PROFICIENCY BY APPLYING PROJECT-BASED LEARNING

Project-based learning has proven its strengths in improving language learner’s abilities and teaching method diversity. Although it is widely used in teaching a second language like English worldwide, in Vietnam, especially in Thai Nguyen University of Economics and Business Administration (TUEBA), it is the very first step to prove its benefits in language teaching and learning here. This study is conducted in order to investigate its advantages in improving ESL students’ speaking proficiency, which is considered as the most challenging skill with Asian students for its productive aspects.
DETECTING AND CAPTIONING IMAGES USING DEEP NEURAL NETWORKS AND FLASK

Captioning images automatically is one of the heart of the human visual system. There are various advantages if there is an application which automatically caption the scenes surrounded by them and revert back the caption as a plain message. In this paper, we present a model based on CNN-LSTM neural networks which automatically detects the objects in the images and generates descriptions for the images. It uses various pre-trained models to perform the task of detecting objects and uses CNN and LSTM to generate the captions. It uses Transfer Learning based pre-trained models for the task of object Detection. This model can perform two operations. The first one is to detect objects in the image using Convolutional Neural Networks and the other is to caption the images using RNN based LSTM(Long Short Term Memory). Interface of the model is developed using flask rest API, which is a web development framework of python. The main use case of this project is to help visually impaired to understand the surrounding environment and act according to that.
Testing the Weak Form of Efficiency of Cryptocurrencies: A Case Study of Bitcoin and Litecoin

This study examines the weak form of efficiency of the exchange rate of cryptocurrencies against US Dollar. The study is based on the exchange rate of Bitcoin and Litecoin against US Dollar from 2013 to 2017. The data is tested for heteroscedasticity, and the efficiency of these coin market is analysed using unit root and stationary tests such as Augmented Dickey Fuller (ADF) test, Philips Perron (PP) test and Kwiatkowski Phillips Schmidt Shin (KPSS) tests. The results of the study reveal that the Bitcoin and Litecoin exchange rate exhibit a random walk. Speculation helps for the rapid growth of these currency markets. It is advisable for the investors to invest for short term to get higher returns rather than for the long term. Investment in cryptocurrencies involves market shocks due to its unpredictable nature.
Mobile application For Emergency Services

This paper introduces Mobile Emergency Services Application using Geolocation for Command Centres. It is a combination of a mobile application for responding to emergency requests for ambulance, fire truck and police by people in a certain area or city. The mobile application would detect user’s current location through geolocation and sends to the web application deployed in a command Centre the name, age, mobile number and location of the user for easily dispatching of emergency units.
Library Research Guides: Journalism, advertising, PR and communication: Home

This guide will assist you to find information and library resources for journalism, advertising, public relations and communication studies, and provide research and referencing tips.
TabReformer: Unsupervised Representation Learning for Erroneous Data Detection

Error detection is a crucial preliminary phase in any data analytics pipeline. Existing error detection techniques typically target specific types of errors. Moreover, most of these detection models either require user-defined rules or ample hand-labeled training examples. Therefore, in this article, we present TabReformer, a model that learns bidirectional encoder representations for tabular data. The proposed model consists of two main phases. In the first phase, TabReformer follows encoder architecture with multiple self-attention layers to model the dependencies between cells and capture tuple-level representations. Also, the model utilizes a Gaussian Error Linear Unit activation function with the Masked Data Model objective to achieve deeper probabilistic understanding. In the second phase, the model parameters are fine-tuned for the task of erroneous data detection. The model applies a data augmentation module to generate more erroneous examples to represent the minority class. The experimental evaluation considers a wide range of databases with different types of errors and distributions. The empirical results show that our solution can enhance the recall values by 32.95% on average compared with state-of-the-art techniques while reducing the manual effort by up to 48.86%.
LibGuides: Permalinks: Databases

Learn how to create permanent URLs for the library's electronic resources: databases, journals, articles, ebooks, etc
상향식 교육과정 평가 모형 개발 및 적용에 관한 협력적 실행 연구

This collaborative action study aimed to develop and apply a school-based national curriculum evaluation model. Considering the situation in South Korea, following a centralized curriculum development system, teachers had scarce formal opportunities to evaluate the national curriculum and suggest improvements, despite being the subjects of curriculum implementation. Through cooperation between a research team and middle school teachers, this study developed and applied a model that can be used when evaluating the current national curriculum at the school level. The application of the curriculum evaluation model to a designated school showed that the evaluation of the national curriculum enabled teachers to recognize the need for understanding and being further involved the national curriculum in a deeper sense. Further, it allowed them to provide authentic opinions for improvement based on field experience, and to form the dynamic of ‘becoming the subject’ of the national curriculum. Based on the findings of the study, this article suggested future measures to spread and further implement the bottom-up curriculum evaluation model.
학습자 삶의 맥락을 강조하는 모바일 플랫폼 기반의 대학 교양 생물학 교육과정 고안 및 학습자 동기의 변화 이해

The purpose of this study was to provide a general biology course to enhance students’ interest in biology and to recognize biology as a useful subject in life. The ARCS motivation strategies were performed, and a mobile platform was constructed to promote student participation. Fifty-eight college students were participated in this study. During a semester, there were two hours of class time per week, and three times of achievement tests and CIS (Keller, 2000) questionnaires were performed in five-week period. The changes of students’ CIS scores through time and the relationships with their achievement were analyzed. As a result, the participants showed highly motivated through the given biology course. Among the four elements of motivation, the relevance and satisfaction aspects were relatively high while the attention aspect was relatively low. It is encouraging in that participants recognized the biology is important and relevant in their lives, and satisfied with learning activities from the lesson. The participants’ motivation level was not consistently increased nor decreased over time, rather it has high correlation with their achievement. The attitude on the using mobile was very high, but not related the level of achievement nor motivation. The implications of using CIS to capture participants’ motivation level was furtherly discussed.
Don’t beat a dead horse: Recognizing a person who returns to a done-deal in a multi-party conversation

In this paper, we construct a corpus that contains a person who returns to a done-deal in a multi-party conversation. We call the person "BDH (Beat a Dead Horse) participant." Each conversation in the corpus consists of utterances about a topic with three participants. We prepare two topics for the corpus and one of three in participants is the BDH participant. The BDH participant mentions negative opinions about a done-deal in the previous conversation. For recognizing a BDH participant in a conversation, we generate a recognition model based on a machine learning approach from the corpus. We propose nine features and apply them to Support Vector Machines. We obtained 0.743 on the F-score by using the model with the best feature set. The bi-gram and tri-gram in them were the most effective features in the experiment.
THE IMPORTANCE OF DEVELOPING ACADEMIC MOBILITY (ACTIVITY) IN STUDENTS OF HIGHER EDUCATIONAL INSTITUTIONS

The article discusses the importance of the development of academic mobility of university students. In this regard, studies were carried out by scientists-educators.
고흥군 양식어업형 어촌계의 입지에 따른 어업효율성 분석에 관한 연구

The purpose of this study is to understand the production efficiency of individual fishing communities and provide directions for improvement. The subject of the study is aquaculture type Ochon-Gye in Goheung-gun. The analysis method used bootstrap-DEA to overcome the statistical reliability problem of the traditional DEA analysis technique. In addition, data mining-GIS was applied to identify the spatial productivity of fishing communities. The values of technology efficiency, pure technology efficiency, and scale efficiency were estimated for 32 aquaculture-type fishing villages. Then, using the benchmarking reference set and weights, the projection was presented through adjustment of the input factor excess, and furthermore, the confidence interval of the efficiency values considering statistical significance was estimated using bootstrap.
Proses Produksi Video Berita Langsung Di DISKOMINFO Kota Sukabumi

The development of technology and communication are currently experiencing very rapid progress, especially video technology. All forms of activity become a video. Any activity can be disseminated through video to social media and become public consumetion. Video consists of interesting audio visual because besides it can be disseminated but it can also be a document and can be saved. The Department of Communication and Information Technology Sukabumi City is an institution under the auspices of the Sukabumi City Government, the aim is to convey information from the government to the people of Sukabumi City and surrounding areas. The Process of producing live video news in the department of communication and Information Technology Sukabumi city includes three stages : pre-production, production, and post-production. Pre production starts from the preparation before the coverage. Production during video reporting and editing processes. Post-production is the final result of agreed editing and uploading of videos to social media.
Kesulitan Menyimak dan Menulis Siswa Kelas Rendah Pada Pembelajaran Bahasa Indonesia di Sekolah Dasar

The purpose of this study was to describe the difficulties faced by low-grade students in listening and writing activities in Indonesian language learning in elementary schools. This research design is a literature study with a qualitative approach. The data collection technique is in the form of documentation study and literature study. The validity of the data was tested by increasing the persistence in the study. The analysis technique uses content analysis techniques. The results showed that, (1) the difficulties faced by low-grade students in listening activities in Indonesian language learning included: (a) difficulty focusing on listening to learning from the teacher, (b) difficulty understanding and answering questions about the contents of the tales that were listened to, and identify intrinsic elements of the story, (c) difficulty remembering and retelling orally the contents of the tale that is being listened to, (d) difficulty understanding and answering questions about the content of the story being listened to. Furthermore, (2) the difficulties faced by low-grade students in writing activities in Indonesian language learning include: (a) difficulty memorizing and distinguishing the shape and size of loose letters, (b) the advantages and disadvantages of the number of loose letters written, (c) difficulties arranging and completing letters, syllables, words, and sentences according to the pattern, (d) difficulty in writing loose, neat, and clean letters, (e) difficulty in writing cursive letters correctly based on shape, size, letter completeness, writing spacing , and row (f) difficulty writing cursive letters neatly and cleanly, (g) difficulty writing capital letters and punctuation correctly, (h) difficulty finding ideas, combining, and organizing sentences in writing essays, (i) difficulty writing back in the fairy tales and stories that are listened to.
An Effective Approach for Virtual Machine Migration and Dynamic Placement Using Elephant Herd Optimization

Cloud computing is a platform for offering computational services as a method to deal with multiple problems in virtualized data management. Therefore, it is necessary to position and migration of virtual machines in order to accomplish several contradictory objectives. This work explores the state-of-the-art in the field in regards to the difficulty of these tasks and the vast number of existing proposals. Cloud Measurement combines new technologies that shape our lives in a way that saves investments in the upfront infrastructure for consumers operating on VMs on physics machines provided by a cloud service. Multiple VMs on the same PM could have different work completion times due to the heterogeneity of numerous works. PMs are heterogeneous in the meantime as well. Consequently, multiple VM placements have differing completion periods. Our goal is to reduce the completion time for VM input requests through a realistic schedule for VM placement. This dilemma is NP-hard so it can be simplified to a problem with knapsack. We suggest an offline approach for VM placement by way of emulated VM migration, and an actual migration mechanism for VM solves the online VM placement. The migration algorithm is a heuristic approach, where we explicitly position the VM to its best PM, given that it is capable of doing so. Otherwise we can move another VM from this PM to handle the new VM if the migration limitation is met. In addition, this work incorporates and suggests the introduction of the online dynamic positioning Elephant Herd Optimization (EHO) approach, and the assessment results show the high efficiency of the proposed algorithm.
A Study on Improving Free-Hand Sketch Recognition of Infants Using Deep Learning

Due to its unique characteristics, infant paintings have a significantly lower recognition rate than adult images. According to the study of infant art, infant paintings have many features that are different from adult images, such as the appearance of many self-centered and exaggerated expressions. In this paper, we will introduce a method to improve the recognition rate of such children's drawings by utilizing deep learning. Create a pre-processor that generalizes the unique characteristics of the child to improve the low recognition rate of the infant figure, and primarily refine the data. High accuracy was obtained as a result of securing and executing 80 adult sketches for each of 250 classified items using CNN, which is often used for image recognition. Through this research, it is expected that it will be possible not only to improve the cognitive ability of infant figures, but also to measure learning ability and child development through infant drawings, and to utilize it in child psychotherapy through emotion recognition.
Calculation of Proton Mass and Neutron Mass by Q-theory

The logarithmic compressive strength of quantum space imparts mass to particle. If particles are tightly connected to each other, their sum mass should be calculated as logarithmic masses. If particles are free from each other, their sum mass should be calculated as arithmetic masses. Proton is composed of two up quarks, one down quark, one strong particle force, and one electromagnetic particle force. From the logarithmic masses, the proton is calculated as 89.8% mass of the measured value. Here, 5D dark force acts to the electromagnetic particle force, and the proton mass is calculated as 98.3% of the meas-ured value. 6D dark force also acts to the strong particle force, and the proton mass is calculated as 99.8% of the measured value. Calculating this inversely, the mass of down quark is calculated as 4.756 MeV. Neutron is composed of one proton, one electron, and one shell anti-brane. Here, the electron is held in the form of particle inside neutron by the observer effect of the shell brane. The difference between the calculated mass and the measured mass of neutron was +8,966 eV. This value is the separating energy of shell brane, which is the reason of negative beta decay.
계층분석법(AHP)을 이용한 GAP 인증기준 개선 방향 수립 연구

As the number of agricultural products produced or imported increases, the issue regarding the quality of the safety of agricultural products arises. The government is implementing various certification systems to ensure safety in the production process in order to increase the reliability of consumers'' food safety. Unlike other certification systems that focus on the safety issue in the production side, the GAP certification system manages the agricultural environment and hazards at all stages from the production of agricultural products to the distribution process. Despite the necessity and importance of the system, the GAP certification system is experiencing difficulties in terms of activation. This study examines the ways to establish a direction for improving GAP certification standards using the Analytic Hierarchy Process(AHP). As a result of the analysis, the promotion of consumption of GAP agricultural products is recognized as the most important improvement direction, and the detailed strategies with high priority are strengthening the safety management at the production stage and strengthening the safety management of the harvest. Therefore, when improving GAP certification standards, it is necessary to focus on strengthening production-level safety management in consideration of the consumption promotion aspect of consumers in the short term. However, in the medium and long term, the pursuit of GAP internationalization should also be considered. The results of this analysis are expected to be used as preliminary data to establish a plan to activate the GAP certification system.
Distributed-to-Centralized Data Management through Blockchain Technologies in Large-Scale IoT Networks of Multicampus University

Traditionally, blockchain technologies focus on data security and privacy issues in different business domains of smart cities. However, we believe that blockchain technologies can be beneficial for data and resource management in large-scale internet of things (IoT) networks of smart cities. Blockchain technologies and their related consensus algorithms and miners may apply through multilevel information communication technology (ICT) architecture in large-scale IoT networks of smart cities to organize the city-data and ICT resources. This position paper addresses an initial idea about the contribution of different smart cities and ICT concepts, including “blockchain technologies,” “distributed-to-centralized ICT architecture (D2C-ICT),” “distributed-to-centralized data management (D2CDM),” and “smart university.” We first present our D2C-ICT architecture in the smart university context using different distributed and centralized technologies, including cloudlet and cloud technologies. Finally, we show that the facilities of blockchain technologies for data and resource management through D2C-ICT architecture in large-scale IoT networks of smart cities.