Reviewerly/exHarmony huggingface dataset:
Applying Collocation Analysis to Chinese Discourse: A Case Study of Causal Connectives

Abstract Collocation analysis can be used to extract meaningful linguistic information from large-scale corpus data. This paper reviews the methodological issues one may encounter when performing collocation analysis for discourse studies on Chinese. We propose four crucial aspects to consider in such analyses: (i) the definition of collocates according to various parameters; (ii) the choice of analysis and association measures; (iii) the definition of the search span; and (iv) the selection of corpora for analysis. To illustrate how these aspects can be addressed when applying a Chinese collocation analysis, we conducted a case study of two Chinese causal connectives: yushi ‘that is why’ and yin’er ‘as a result’. The distinctive collocation analysis shows how these two connectives differ in volitionality, an important dimension of discourse relations. The study also demonstrates that collocation analysis, as an explorative approach based on large-scale data, can provide valuable converging evidence for corpus-based studies that have been conducted with laborious manual analysis on limited datasets.
Locality Preserving Discriminant Projection for Speaker Verification

In this paper, a manifold subspace learning algorithm based on locality preserving discriminant projection (LPDP) is used for speaker verification.LPDP can overcome the deficiency of the total variability factor analysis and locality preserving projection (LPP).LPDP can effectively use the speaker label information of speech data.Through optimization, LPDP can maintain the inherent manifold local structure of the speech data samples of the same speaker by reducing the distance between them.At the same time, LPDP can enhance the discriminability of the embedding space by expanding the distance between the speech data samples of different speakers.The proposed method is compared with LPP and total variability factor analysis on the NIST SRE 2010 telephone-telephone core condition.The experimental results indicate that the proposed LPDP can overcome the deficiency of LPP and total variability factor analysis and can further improve the system performance.
자율성장 인공지능 기술

Currently, a majority of artificial intelligence is used to secure big data; however, it is concentrated in a few of major companies. Therefore, automatic data augmentation and efficient learning algorithms for small-scale data will become key elements in future artificial intelligence competitivene...
MotePy: A domain specific language for low-overhead machine learning and data processing

A domain specific language (DSL), named MotePy is presented. The DSL offers a high level syntax with low overheads for ML/data processing in time constrained or memory constrained systems. The DSL-to-C compiler has a novel static memory allocator that tracks object lifetimes and reuses the static memory, which we call the compiler-managed heap.
RPEEE (Reasonable Prospects for Eventual Economic Extraction): The critical core to the SAMREC Code

SYNOPSIS Reasonable Prospects for Eventual Economic Extraction (RPEEE) is the critical basis for effective implementation of the SAMREC Code as it applies to Mineral Resources, and implicitly to Mineral Reserves that are derived from Mineral Resources. This implementation follows the founding principles of materiality, transparency, and competence. The SAMREC definition of a Mineral Resource specifically includes RPEEE. SAMREC provides guidance for all minerals on what RPEEE means, with some specific additional guidance for diamonds. SAMREC instructs the Competent Person that RPEEE must be demonstrated through reasoned assessment of multiple technical and non-technical parameters, and with disclosure in reporting. A recommended chapter in a CPR includes a sub-section for RPEEE. SAMREC definitions and guidance are presented with discussion of the factors that must be assessed to demonstrate RPEEE. Comparison with guidance in other reporting countries and examples of actual practice are presented. Keywords: reporting codes, Mineral Resources, definitions, disclosure, SAMREC.
Simultaneous Estimation of Derivatives, Equilibrium States, and Disturbances for Modeling as a Linear Time-Invariant System

In this paper, we propose an estimation method based on recursive least squares method for dynamic systems to be modeled as a linear time-invariant system, taking account of the influence of disturbance. It is assumed that disturbances are additive to the state variables and expressed as linear combinations of known functions of the states and unknown parameters. From simulation results, it has turned out that it is possible to simultaneously estimate derivatives of the state equation and disturbance as well as equilibrium states.
The Construction of Online Media in Indonesian Artist: Critical Discourse Analysis

Discourse analysis has become a significant concern that attracted many recerachers of disciplines to disscuss and generate the theories of their prerspectives. Celebrity life is one of an exciting topic of broadcasting and constructing about news in the online media. The purpose of this study was
Steering System of Electric Vehicle using Extreme Learning Machine

The development of electric vehicle technology is currently increasing and growing very fast. Some efforts have been conducted, one of which is using BLDC (brushless direct current) motors to improve efficiency. This study utilized extreme learning machine (ELM) embedded on the microcontroller as well as the differential method for controlling the rotational speed of the BLDC motor. The experimental results on the acceleration testing by traveling a distance of 200 meters achieved the average current of 1.09 amperes. The average power efficiency test is 104 watts. Furthermore, the results of the efficiency experiment with a track length of 3.3 km (kilometers) in 10 minutes obtained the energy efficiency of 177.34 km / kWh (kilowatt for one hour).
Conditions for Unnecessary Logical Constraints in Kernel Machines

A main property of support vector machines consists in the fact that only a small portion of the training data is significant to determine the maximum margin separating hyperplane in the feature space, the so called support vectors. In a similar way, in the general scheme of learning from constraints, where possibly several constraints are considered, some of them may turn out to be unnecessary with respect to the learning optimization, even if they are active for a given optimal solution. In this paper we extend the definition of support vector to support constraint and we provide some criteria to determine which constraints can be removed from the learning problem still yielding the same optimal solutions. In particular, we discuss the case of logical constraints expressed by Łukasiewicz logic, where both inferential and algebraic arguments can be considered. Some theoretical results that characterize the concept of unnecessary constraint are proved and explained by means of examples.
LibGuides: Exploring Technique in Art: Sources to Consider

Topics such as text in art, art & emotion, landscapes, portraiture, and recycled art can be found in this LibGuide
Stable predictions for health related anticausal prediction tasks affected by selection biases: the need to deconfound the test set features

In health related machine learning applications, the training data often corresponds to a non-representative sample from the target populations where the learners will be deployed. In anticausal prediction tasks, selection biases often make the associations between confounders and the outcome variable unstable across different target environments. As a consequence, the predictions from confounded learners are often unstable, and might fail to generalize in shifted test environments. Stable prediction approaches aim to solve this problem by producing predictions that are stable across unknown test environments. These approaches, however, are sometimes applied to the training data alone with the hope that training an unconfounded model will be enough to generate stable predictions in shifted test sets. Here, we show that this is insufficient, and that improved stability can be achieved by deconfounding the test set features as well. We illustrate these observations using both synthetic data and real world data from a mobile health study.
Enhash: A Fast Streaming Algorithm For Concept Drift Detection

We propose Enhash, a fast ensemble learner that detects \textit{concept drift} in a data stream. A stream may consist of abrupt, gradual, virtual, or recurring events, or a mixture of various types of drift. Enhash employs projection hash to insert an incoming sample. We show empirically that the proposed method has competitive performance to existing ensemble learners in much lesser time. Also, Enhash has moderate resource requirements. Experiments relevant to performance comparison were performed on 6 artificial and 4 real data sets consisting of various types of drifts.
Shape retrieval by using multi‐scale angle‐based representation and dynamic label propagation

To improve the robustness and discrimination power of the triangle-area representation, a novel shape matching method based on multi-scale angle representation is proposed in this study. By analysing the configurations of different sample points from each shape contour, shape descriptors are constructed by using space angles at different scale levels. With the proposed shape representation, the multi-scale information of shape contours is efficiently described, and the dynamic programming is further used to determine the correspondence between samples from different shapes and calculate the shape distance in the feature matching step. Moreover, to improve the shape retrieval results based on pairwise shape distances, the dynamic label propagation is introduced as the post-processing step. Unlike previous distance learning methods learning the database manifold implicitly, the authors method retrieves relative objects on the shortest paths from near to far explicitly, and the underlying structure can be effectively captured. The proposed method tested on different shape databases provides the performances superior to many other methods, and it can be applied to visual data processing and understanding of the internet of things.
Query Processing Technology to Support Concurrency Control and Recovery in Column Oriented Databases

Recently, NoSQL (Not Only SQL) is receiving attention as one of the technologies to deal with Big Datacountless users are making around the world. NoSQL is a database presented as an alternative to the technicaland monetary restrictions of conventional relational database and focusing on availability and expandabilityfor swift treatment of atypical data. But, NoSQL does not guarantee data integrity because it abandonstransaction for availability and scalability. Thus, studies are underway to implement the multi-row transactionon NoSQL, In particular, various studies on the multi-row transaction system based on HBase has beenactively in progress. However, traditional studies are limited to performance improvement proportional tonumber of clients and low concurrency because there are too many information that column manages.Therefore, In this paper, propose an efficient multi-row transaction system based on HBase has exceptionalperformance improvement proportional to number of clients and supports high concurrency. This systemcreates column for managing transaction information. In addition, designs and implements the transactionmanager for efficiently controlling the state of transaction and communication manager for exchanginginformation it need for transaction by communicating with HBase
Prevention Of Minors Delinquent Behavior In Activities Of The Internal Affairs Officers

The article reveals the features of the work of police officers with delinquent adolescents and minors in modern sociocultural conditions, as well as the process of formation of readiness of Internal Affairs officers for preventive activities with this category of minors. The article deals with the main issues involving the pedagogical activity of Law Enforcement officers related to the prevention of juvenile delinquency, crime and other unlawful acts. The article considers the social and educational activities of Internal Affairs officers in relation to juvenile offenders and children at risk. The term "delinquent behavior" is defined in more detail and the terms "delinquent behavior" and "deviant behavior" are differentiated. The pedagogical model of readiness of police officers for preventive activities with minors of delinquent behavior is developed, proved and verified. The general methodological basis of the research is constituted by the provisions of modern science on the unity, universal connection and causality of the phenomena of the world, on the process of cognition and harmonious development of personality, on the systematic approach to the study of pedagogical phenomena, personal-activity approach to the process of specialist training. The results allow to make conclusions that the objectives of the study to improve the pedagogical training of the Internal Affairs officers for working with minors can be resolved in the conditions of the educational process in accordance with the structural and functional model, taking into account the peculiarities of adult education and the specifics of the functioning of continuing education institutions.
Penyuluhan Pemahaman Layanan Informasi Tentang Studi Lanjut

This community service activity aims to equip children with various kinds of knowledge about further study, have a view on further study so that students are able to make decisions in choosing and planning their studies, according to their talents and interests. The method used in this service activity is counseling with lectures and open discussions in conveying material, this can facilitate the extension process and students are more flexible to ask questions about various matters related to further study. The target of this community service activity is the students of class XII SMA Negeri 1 Labuapi, West Lombok, totaling 30 students. The result of this service activity is that students are able to plan and make further study decisions they want after graduating from high school that is tailored to their talents and interests.
Rancang Bangun Sistem Informasi Geografis Lokasi Pelayanan Kesehatan Menggunakan Algoritma A-Star

Nowadays technological developments have penetrated in all aspects of life. Technology has helped many people, and computers are tools that provide information to meet needs. The development of information technology in the geographical field, information can be displayed better and faster through computers. GIS (Geographic Information System) technology is a technology about geographic information that has been highly developed. At this writing will discuss making the application of Web-based Geographic Information Systems, especially in the field of health service facilities in the city of Pekanbaru. The location of health services is a place that is visited by many people. But there are still many people who do not know the location of the health service, it is necessary to develop applications to support the needs of the community in obtaining information on the location of the health service along with information on the nearest route, and the road to the object. If a user can maximize this technology, he should not be afraid of getting lost or losing his way if traveling to an area that is still unfamiliar to him. Based on the identification of the problem, obtained whether a geographic information system can be built that informs the distribution of health service facilities and service schedules and can provide route recommendations. The results obtained are the distribution of health facilities that are displayed in the Map and each facility has service schedule information, while the route of travel is calculated based on the A-Star algorithmKeywords: Geographic Information System (GIS), Health services, A-Star algorithm.
Inovação na governança da água: o papel da tecnologia blockchain e dos sistemas complexos de fluxos

According to the World Economic Forum, the water crisis ranks among the five most dangerous risks to global welfare. In this context, water governance is becoming increasingly vital in various regions, especially as the multiple and competitive uses of water mount increasing pressures on its supply. Despite the evolution of water governance rationales, global water resources are, unfortunately deteriorating. Current water governance models are limited by two intertwined aspects: financial sources and trust. In this context, the objective of this paper is to discuss how blockchain technology can aid in improving water governance, increasing financial transparency, and stakeholders’ trust. Such an improvement could be achieved, for example, with the creation of cryptocurrencies to encourage actions aimed at the conservation of water resources, and also via the adoption of smart contracts.
Improvement of Counting Abilities Through the Powerpoint Media in Elementary School Grade II

&lt;p class="Default"&gt;&lt;em&gt;This purpose of the study was to improve the ability to counting with long and short storage techniques with powerpoint for students grade II of SD Negeri Selomerto for the 2020/2021 academic year. This research was conducted in two cycles. Where in each cycle has stages that start from doing planning, action, observation and reflection. The results of the study : cycle 1 shows increase from pre cycle, 55% students complete and cycle two shows increase form cycle 1, 76% student complete from 29 students in the class. The results of the research that have been done show that the powerpoint media improves students counting skills, especially in adding long and short storage techniques in Grade II SD Negeri Selomerto. &lt;/em&gt;&lt;/p&gt;
SafeChain: Securing Trigger-Action Programming From Attack Chains

The proliferation of Internet of Things (IoT) is reshaping our lifestyle. With IoT sensors and devices communicating with each other via the Internet, people can customize automation rules to meet their needs. Unless carefully defined, however, such rules can easily become points of security failure as the number of devices and complexity of rules increase. Device owners may end up unintentionally providing access or revealing private information to unauthorized entities due to complex chain reactions among devices. Prior work on trigger-action programming either focuses on conflict resolution or usability issues, or fails to accurately and efficiently detect such attack chains. This paper explores security vulnerabilities when users have the freedom to customize automation rules using trigger-action programming. We define two broad classes of attack--privilege escalation and privacy leakage--and present a practical model-checking-based system called SAFECHAIN that detects hidden attack chains exploiting the combination of rules. Built upon existing model-checking techniques, SAFECHAIN identifies attack chains by modeling the IoT ecosystem as a Finite State Machine. To improve practicability, SAFECHAIN avoids the need to accurately model an environment by frequently re-checking the automation rules given the current states, and employs rule-aware optimizations to further reduce overhead. Our comparative analysis shows that SAFECHAIN can efficiently and accurately identify attack chains, and our prototype implementation of SAFECHAIN can verify 100 rules in less than one second with no false positives.
基于层次注意力机制和门机制的属性级别情感分析(Aspect-level Sentiment Analysis Based on Hierarchical Attention and Gate Networks)

近年来,作为细粒度的属性级别情感分析在商业界和学术界受到越来越多的关注,其目的在于识别一个句子中多个属性词所对应的情感极性。目前,在解决属性级别情感分析问题的绝大多数工作都集中在注意力机制的设计上,以此突出上下文和属性词中不同词对于属性级别情感分析的贡献,同时使上下文和属性词之间相互关联。本文提出使用层次注意力机制和门机制处理属性级别情感分析任务,在得到属性词的隐藏状态之后,通过注意力机制得到属性词新的表示,然后利用属性词新的表示和注意力机制进一步得到上下文新的表示,层次注意力机制的设计使得上下文和属性词的表达更加准确;同时通过门机制选择对属性词而言上下文中有用的信息,以此丰富上下文的表达,在SemEval 2014 Task4和Twitter数据集上的实验结果表明本文提出模型的有效性。
A Research and Strategy of Remote Sensing Image Denoising Algorithms

Most raw data download from satellites are useless, resulting in transmission waste, one solution is to process data directly on satellites, then only transmit the processed results to the ground. Image processing is the main data processing on satellites, in this paper, we focus on image denoising which is the basic image processing. There are many high-performance denoising approaches at present, however, most of them rely on advanced computing resources or rich images on the ground. Considering the limited computing resources of satellites and the characteristics of remote sensing images, we do some research on these high-performance ground image denoising approaches and compare them in simulation experiments to analyze whether they are suitable for satellites. According to the analysis results, we propose two feasible image denoising strategies for satellites based on satellite TianZhi-1.
Personalization of Art Students' Training in the Context of the Transition to the Digital Economy

Today, one of the main resources for the effective functioning of many political, sociocultural, and communication processes is transition to the digital economy and digital reality in general. Informatization, computerization, automation naturally integrate into the artistic culture and transform it into a digital one. As a result, changes in the professional field of art definitely require changes in both the content, methodology and technological base of art education in the context of transition to digital economy. At the same time, digital technologies are a factor in the modernization of the higher education system, and its tool. There is an objective need to individualize and personalize educational technologies. In turn, digitalization creates the foundations by which these processes can be implemented. The article specifies pedagogical conditions for personalization of art students' training: activating self-education and self-development mechanisms through the creation of individual educational routes; enriching the informational educational and methodological base to maintain an individual format for studying the content of artistic culture; adopting a personal position of an adviser and a facilitator by the university teacher, which contributes to the design, stimulation and reflection of the personal and competent development of art students. The reliability of conclusions made within this theoretical study is confirmed by the positive results of experimental work.