Reviewerly/exHarmony huggingface dataset:
Incorporation : Constraints on variation

This thesis examines the range of variation regarding the pragmatic, semantic, morphosyntactic, phonological and lexical properties of incorporation constructions, focusing specifically on constraints on the variation. The thesis starts out with a review of the pragmatic, semantic and phonological variation in incorporation described in previous literature and the relevant constraints that can be formulated on the basis of earlier research. This review is followed by three in-depth studies of particular domains of morphosyntactic, pragmatic-semantic and lexical variation in incorporation. These domains of variation are analyzed based on data from a varied sample of languages. The morphosyntactic domain investigated concerns the possible morphosyntactic forms of incorporated elements. The pragmatic and semantic properties that are examined are the referentiality and modifiability of incorporated nouns respectively. With respect to the lexical properties of incorporation, the thesis addresses the question which types of verbs do and do not allow the incorporation of nouns. Finally, it is shown that the different theoretical accounts of incorporation proposed in the literature are only partly able to capture or predict the variation and constraints presented in this thesis. The thesis thus indicates that theoretical work on incorporation may generally benefit from paying more attention to the full range of variation in incorporation constructions and its constraints.
Design and Implementation of Secure File Transfer System Based on Java

The popularization and application of computers and the close integration of computer technology and communication technology make the transmission of information more convenient. In daily work, the use of file transfer systems can greatly improve work efficiency. While the file transfer system brings us convenience, it also has security risks. Through the research and analysis of the current situation of office informatization and information security issues, according to the daily work needs of enterprises and individuals, combined with file transfer technology and cryptography theory, a file transfer system with strong security and convenient operation is designed and implemented. The system consists of four modules: file transfer module, encryption and decryption module, instant communication module and log management module. It can complete the encrypted transmission of files, provide instant messaging functions, and keep transfer records. By testing and using the system, the secure transmission of data can be realized, which provides a good guarantee for the security of the transmitted files.
A FAST DEEP STACKED NETWORK USING EXTREME LEARNING MACHINE

Access to large amounts of data is becoming more common, as well as the use of methods based on deep learning to obtain better results. However, using those techniques can lead to long training times. To deal with this problem, the Deep Stacked Network (DSN) was proposed, where several small modules are stacked to increase the model eciency. However, this architecture suers from some problems that increase its training time and the amount of memory required to store it. To deal with some of these problems, we propose in this paper a fast algorithm to train a DSN using Extreme Learning Machine (ELM). Experiments performed on many classication datasets showed that the proposed method achieves similar accuracy when compared with other techniques, with the advantage of training the network in less time and storing fewer parameters.
Application of Water Circulation Electric Heating System in Energy-saving Treatment of Floor Heating

Li, L. and Hong, Y.F., 2020. Application of water circulation electric heating system in energy-saving treatment of floor heating. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 385–389. Coconut Creek (Florida), ISSN 0749-0208.In the heating process of the current heating system, the temperature fluctuation range is large, the heating stability is poor, the heating power consumption and the heating cost are high, and the application research of the water circulation electric heating system in the energy-saving treatment of floor heating is proposed. This article takes AT89C51 single-chip microcomputer as the core, uses LCD, system clock, input/output parallel interface 8255, keyboard circuit, watchdog circuit, actuator and alarm circuit to realize the system hardware design. Using modular programming method, the system application program is divided into program modules, using assembly language programming, designing program modules, and realizing system software design. The system uses nano-material heaters and uses single-chip microcomputers to perform parameters such as water temperature, water level, and room temperature. Detection and protection of over-temperature, water shortage and electric leakage. Taking the single building of the green farm house experience center as an example, the research results show that the temperature fluctuation of the main indoor room heated by the water circulation electric heater system designed in this paper is small, the heating system heating stability is good, and the heating can be effectively reduced Power consumption, reducing heating costs.
Exploring the Ways to Build a High-Level Teacher Team of Surveying and Mapping Major from the Perspective of Collaborative Innovation

In recent years, higher vocational education has become an integral part of the teaching system in China. How to achieve a strong improvement in the level of teachers in higher vocational education has become the focus of current higher vocational education. Based on the perspective of collaborative innovation, this paper conducts research with teachers of higher vocational surveying and mapping, outlines the analysis of the role of collaborative innovation based on collaborative innovation, and proposes ways for collaborative innovation to create a high-level faculty of surveying and mapping professionals.
MSReNet: Multi-step Reformulation for Open-Domain Question Answering

Recent works on open-domain question answering (QA) rely on retrieving related passages to answer questions. However, most of them can not escape from sub-optimal initial retrieval results because of lacking interaction with the retrieval system. This paper introduces a new framework MSReNet for open-domain question answering where the question reformulator interacts with the term-based retrieval system, which can improve retrieval precision and QA performance. Specifically, we enhance the open-domain QA model with an additional multi-step reformulator which generates a new human-readable question with the current passages and question. The interaction continues for several times before answer extraction to find the optimal retrieval results as much as possible. Experiments show MSReNet gains performance improvements on several datasets such as TriviaQA-unfiltered, Quasar-T, SearchQA, and SQuAD-open. We also find that the intermediate reformulation results provide interpretability for the reasoning process of the model.
Generating an image training dataset for edges detection on an image using neural networks

One of the cornerstones of machine learning is training data. In case of the insufficient data, correct generalization becomes difficult. This problem is particularly serious when artificial neural networks are used. This work is devoted to an algorithm for generating parameters of arbitrarily shaped edges and creating images containing these edges. Part of the calculations can be performed at the GPU. It accelerates the overall generation more than 3 times. The dataset created in this way can be used in training artificial neural networks for the edge detection task.
Leveraging a System Model to Initiate Security Architecture Development for Product Lines

ABSTRACT This paper presents a method for leveraging Model Based Systems Engineering to facilitate systems security architecture development, with product line engineering considerations. The sensitivity of systems security information constrains the development of the system security model. Creating a tailored subset of the system of interest (SOI) model can generate value as a system security decision driver, and serve as the cornerstone for system security model development. This establishes clear correlation points between the SOI model and system security model. Conducting this collaboration early in the SOI lifecycle enables engineers to implement security considerations in the system design, reducing the cost and schedule impact of delaying system security development. For product line systems, common features are quickly identified with their associated security considerations. Variants retain these common features, preventing rework.
The main issues of the state policy in education in 2019

In 2019, the implementation of the â€œEducationâ€ national project began in the education sector. If in 2012â€“2018 the state policy's main objective was to raise wages of teaching employees, now within the next six years it is necessary to carry out ten federal projects â€“ included in the specified national project â€“ which set the lines of the long-term development of this sector.
The Application of PropTech in the Fourth Industrial Revolution Era

본 연구에서는 전문가 설문을 토대로 4차 산업혁명 인공지능기술을 감정평가업의 적용방안을 분석하였다. 그 분석결과는 첫째, 인공지능기술적용을 위한 감정평가업계의 주요정책은 데이터 신뢰성 확보방안(7.86)>감정평가규칙정비(7.36)>데이터 거버넌스 구축(7.34)>지식재산제도개선(7.20)>AI활용 책임소재 구축(7.11)>정보통신망법 개정(6.72)>개인정보보호법 개정(6.57)>규제 샌드박스 도입(6.41) 순으로 나타났다. 둘째, 신뢰성확보방안은 데이터 수집과 분류의 감정평가사 역할강화>데이터사용의 블록체인도입>인공지능 도입>관계부처와 정보공유이다. 그리고 감정평가협회의 과제는 데이터 거버넌스 구축>플랫폼 구축>4차 산업기술적용 법제도 개선추진>감정평가사 재교육 프로그램 마련 순으로 나타났다. 셋째, 감정평가업계의 대응방안(신뢰성확보와 감정평가협회 과제)는 연령, 경력, 소속에서 유의미한 차이를 보였다. 데이터 거버넌스는 만60세 이상 연령과 만15년 이상~만20년 미만의 경력과 대형법인이 가장 높은 비율을 보였다. 플랫폼 구축은 만50세 이상~만60세 미만 연령과 만10년 이상~만15년 미만 경력이 가장 많았다. 감정평가사 재교육 프로그램 마련은 연령별 차이가 없고, 만20년 이상 경력과 중소법인이 높은 비율이었다. 4차 산업기술 적용 법제도 개선 추진은 만40세 이상~만50세 미만, 만60세 이상 연령과 만5년 미만 경력, 중소법인이 가장 많았다. 주요정책은 연령과 유의확률 5%에서 규제 샌드박스 도입, 데이터 거버넌스 구축, AI활용 책임소재 행정법 구축, 지식재산제도 개선, 데이터 신뢰성 확보방안, 감정평가 규칙 등 정비가 연령별로 유의미한 차이를 보였다. 경력과는 유의확률 5%에서 AI활용 책임소재 행정법 구축과 지식재산제도 개선가 연령별로 유의미한 차이를 보였다. 소속별 유의미한 차이는 없었다. 유의확률 5%에서 소속별로 유의미한 차이를 보이는 정책적 대응방안은 없었다.This study was based on the survey of application method of artificial intelligence(AI) technology in the appraisal industry. The results suggested firstly that the necessary policies of the appraisal industry for the AI technology application are include measures to secure data reliability, maintenance of evaluation rules, data governance, improvement of intellectual property system, and establishment of responsible materials for AI use; Secondly, the ways to secure the reliability of the appraisal work are to strengthen the role of appraisers for data collection and classification, to introduce a block-chain for data use, and to introduce artificial intelligence. And the task of the Appraisal Association is to build data governance and build a platform; Thirdly, the response methods of the appraisal industry showed significant differences in age, career, and affiliation, the main policy showed a significant difference in age and career, but there was no policy showing a significant difference in each organization(p<.05). Based on these findings, several implications are suggested as follows: First, it is urgent to establish a legal system; Second, it is required to secure independent professional manpower, expand collaboration through the digital talent platform, and prepare education programs required for each group; Third, it is necessary to establish the status and strengthen the role of Korea Appraisal Association.
Game-theoretic semantics and partial specifications

We discuss partial specifications in first-order logic FO and also in a Turing-complete extension of FO. We compare the compositional and game-theoretic approaches to the systems.
An Empirical Appraisal of McKinnon’s Complementarity Hypothesis in Tanzania

The prediction of McKinnon’s Complementarity Hypothesis (McKinnon 1973) is that money and investment are complimentary due to self-financed investment and that the real interest rate is the key determinant of capital formation for financially repressed developing economies. Tanzania has experienced a long spell of financial repression as manifested in government putting caps or ceilings on interest rates, state ownership or control of domestic banks and financial institutions, heavy bank borrowing by government, restrictions on entry to the financial industry and directing credit to certain sectors and public entities. Although financial repression can facilitate economic development, for the case of most developing countries it is hypothesized by McKinnon (1973) and Shaw (1973) that it retards savings and investment and thereby inhibits capital formation and economic growth. This paper critically appraises the complementarity hypothesis in Tanzania by an empirical approach. The Autoregressive Distributed Lag (ARDL) model estimation results and the Bounds Test are supportive of the hypothesis, confirming basic complementarity between accumulation of money balances and investment. Higher real interest rates raise capital formation via the increase in real money balances. The policy implication is an exit from financial repression by achieving positive market determined interest rates in order to secure greater levels of investment.
Fitur “Kejog” Gojek Indonesia dalam Upaya Meningkatkan Brand Awareness

Abstract — With the change of the revolution era to the 4.0, took the opportunity to change it by releasing a program called kejoG. KejoG is a program released by in the form of year-end report cards. The uniqueness of this program is the approach from the heart with use romantic language. With this program, must try to win positive perceptions from the community so as to foster an image that will strengthen the company's brand awareness. Therefore researchers want to know the kejoG Gojek program in an effort to increase brand awareness. The purpose of this study is to find out how the stages of the team are to analyze the customer so that it matches the customer characteristics, the evaluation process of the program, the reasons for using romantic / poetic language, the reason there are report cards every year and to know the respoms of the fitur. The method used in this research is qualitative with a case study approach. Data collection techniques used were interviews, observation, and literature studies related to research. The informants in this study were staff Indonesia, team @designatgojek, and user. The results of this research that Indonesia has three reasons for providing report cards every year, that is appreciation, end-of-year campaigns, and creating Kejog to be a viral. In a step-by-step analysis, Indonesia uses a two-sided theory, the persona theory and the RFM Growth Market. The use of romantic / poetic language is adjusted to the user's characteristics, conditions and makes the user comfortable comfort. There is a positive increase obtained from the Kejog feature by increasing brand awareness through satisfaction targets and information that is expected to become viral. Keywords —Gojek Indonesia, kejoG, Brand Awareness
Quality Assessment Framework for 3D Face Reconstruction Models

The 3D face quality assessment framework is used for quality inspection of the 3D face reconstructions models. It mainly detects the holes of the 3D face model, counts the number of holes, and returns the data results to the HTML page. This work can further improve the management of 3D reconstruction models, detect the quality of modeling, improve the utilization of the model, prepare for the subsequent development of 3D reconstruction model, feature point extraction, etc., which is of great significance for industry efficiency optimization.
The Behavior of the Solar Panel Temperature under Different Environmental Conditions

The temperature of the module is a parameter that affects the efficiency of the PV system exceptionally. It can modify the productivity of the scheme. In this research, the link between those parameters and the solar module's temperature was explored by several climate parameters. Solar radiation, ambient temperature and wind speed data have been analyzed in a particular site called Al-Diwaniyah - Iraq, for the period (January –December 2017). The outcomes demonstrate that there is a straight relationship between module temperature and ambient temperature. In addition, wind speed can play a significant impact on reducing the solar module temperature. Consequently, the conversion efficiency of PV panel decreases with increasing temperature.
Statistical Modeling of Application Completeness of Two Tone Sandhi Rules / 两组变调规则应用程度的统计建模

This study examines the application of two Mandarin tone sandhi rules on real and wug words varying in degrees of phonological and semantic dependency. Using two statistical methods, we examined the surface f0 contours and underlying pitch targets. For the third tone sandhi, a lexical effect was discovered on the relationship between “word-likeness” of stimuli and completeness of rule application. The degree of application for the half-third sandhi tone, however, was less consistent. This study offers new insights in the debate between categorical and gradient views of sandhi rules. We propose three hypothesized situations and argue that the Mandarin tone sandhi rule application involves computation of sandhi forms, though it becomes more incomplete on wug words containing more illegitimate morphemes. Finally, between the two rules, the application of the third tone sandhi rule is less phonetically motivated and more biased in wug words, exhibiting differences between real words and wug words.
Clue Extraction for Fine-Grained Emotion Analysis

The emotion analysis in texts is a popular task in natural language processing. Existing research mainly recognizes the types of emotions by encoding sentences. However, in many cases, pure explicit encoding is easy to lose the fine-grained emotional clues hidden in the sentences due to the complexity and subtlety of emotions. We argue that narratives are inextricably emotionally structured and narrative analysis is used as a method to study and examine emotional clues. In this paper, we propose a new unified task: clue extraction for fine-grained emotion analysis (CLUE), which attempts to extract fine-grained emotional clue triples (Why, How, What): Why emotions occur, How people express emotions and What emotions they trigger. We propose a span-based method to address this CLUE task, which directly takes all possible spans as input. The advantage of span is to ensure that each clue is not segmented and semantically complete. The experimental results on a benchmark emotional cause corpus prove the feasibility of the CLUE task as well as the effectiveness of our method.
QuickSilver: A Modeling and Parameterized Verification Framework for Systems with Distributed Agreement

Fully-automated parameterized verification of distributed systems, i.e., verification of systems instantiated with an arbitrary number of processes, suffers from scalability challenges, even when it is decidable. This paper seeks to push the boundaries of parameterized verification in the types of systems that can be verified automatically as well as practically, by incorporating abstractions into the verification pipeline. We develop a framework---QuickSilver---for modeling and automated parameterized reasoning about systems that build on distributed agreement protocols, such as consensus or leader election. QuickSilver includes a modeling language, Mercury, with primitives for abstracting distributed agreement, syntactic conditions for decidable and practical parameterized verification of systems modeled in Mercury, and an implementation that has been demonstrably used for efficient, automated parameterized verification of several benchmarks.
A lightweight perception module for planning purposes

Sensing is an essential component for robots to perform the manipulation tasks in real environments. This study proposes a lightweight deep-learning-based sensing modules which allows the robots to automatically model the workspace for manipulation planning. This sensing module is developed as a part of our ongoing manipulation planning framework. It will be used to enhance the sensing accuracy and make it capable of planning the manipulation tasks in real environments. The retrained model is further trained over commonly used objects to enhance the prediction accuracy.
A Path Planning Algorithm for Mobile Robot with Restricted Access Area

In the actual path planning of the mobile robot, the algorithm planning of the robot is almost always to find the shortest path, but if the robot is in a narrow working environment with many corners, it will make the robot too close to the obstacle, and the robot’s edge will contact with the obstacle, resulting in the path planning failure. In order to solve the security problem of mobile robot path planning, we put forward a kind of inflation obstacles, refinement algorithm first determine skeleton and area of the mobile robot on the map, and then the refinement algorithm can get skeleton to improve traffic area, connected to the path of starting point and end point, define the passage area. Then by searching the first and second nodes, we can find the optimal path that accords with the safety of the robot. The new path planning algorithm can realize non-collision planning, improve the safety and stability of the robot, and verify its effectiveness and authenticity through simulation results.
A Metaheuristic Methodology Based on Fuzzy Logic Principles

Various methods are so complex to be handled quantitatively; However, human beings have achieved by using simple rules that are extracted from their experiences. Fuzzy logic resembles human reasoning in its use of information to generate inaccurate decisions. Diffuse logic incorporates an alternative way of processing that allows complex systems to be modeled using a high level of abstraction originating from human knowledge and experiences. Recently, several of the new evolutionary computing algorithms have been proposed with exciting results. Several of them use operators based on metaphors of natural or social elements that evolve candidate solutions. Although humans have demonstrated their potential to solve complicated optimization problems of everyday life, they are not mechanisms to include such aptitudes into an evolutionary optimization algorithm. In this chapter, a methodology to implement human intelligence based on strategy optimization is presented. Under this approach, a procedure carried out is codified in rules based on Takagi-Sugeno diffuse inference system. So, to implement fuzzy practices, they express the conditions under which candidate solutions are evolved into new positions. To show the capability and robustness of the proposed approach, it is compared to other well-known evolutionary methods. The comparison examines several benchmark functions (benchmark) that are generally considered within the literature of evolutionary algorithms. The results confirm a high performance of the method in the search for a global optimum of different benchmark functions.