Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Control Scheme for Three-level Shunt Active Filter Using Artificial Neural Network Controllers to Eliminate the Current Harmonics and Compensate Reactive Power

The increased use of nonlinear devices in the industry has resulted in the direct increase of harmonic distortion in power systems during these last years. Active filter systems are proposed to mitigate current harmonics generated by nonlinear loads. The conventional scheme based on two-level voltage source inverter controlled by a hysteresis controller has several disadvantages and cannot be used for medium or high power applications. To overcome these drawbacks and improve the APF performance there’s a great tendency to use multilevel inverters controlled by intelligent controllers. Three level (NPC) inverter is one of the most widely used topologies in various industrial applications such as machine drives and power factor compensators. On the other hand, artificial neural networks are under study and investigation in other power electronics applications. In order to gain the advantages of the three-level inverter and artificial neural networks and to reduce the complexity of classical control schemes, a new active power filter configuration controlled by two MLPNN (Multi-Layer Perceptron Neural Network) is proposed in this paper. The first ANN is used to replace the PWM current controller, and the second one to maintain a constant dc link voltage across the capacitors and compensate the inverter power losses. The performance of the global system including power and control circuits is evaluated by Matlab-Simulink and SimPowerSystem Toolbox simulation. The obtained results confirm the effectiveness of the proposed control scheme.
Learning Horn-Clauses as Classification Rules for Relations.

Explanation-based learning (EBL) has been applied numerous times in many different domains using as much background knowledge as possible to guide the learning process. We design and imple­ ment a new EBL based algorithm called FORGE (FOrming Rules from Ground Explanations) which operates utilizing limited background knowledge. The input to the FORGE algorithm consists of exam­ ples and counterexamples of the target concept in the form o f ordered tuples along with example tuples o f base relations. This limited input is used to construct explanation trees which produce ground rules. These ground rules are then generalized and evaluated using simple cover counts. Different heuristics for pruning the explanation trees are proposed and examined. The FORGE algorithm is compared to the empirically based FOIL algorithm and it is shown that the number of rules evaluated is often signifi­ cantly reduced by utilizing the EBL methods of FORGE even in the limited knowledge based domain of FOIL. Chapter 1 Classification and Explanation-Based Learning
Dynamic Building of Domain Specific Lexicons Using Emergent Semantics

The majority of current Natural Language Processing (NLP) methods and research is based on statistical analysis and machine learning. While these methods are quite effective, they are not perfect and the search continues for better and more accurate methods for NLP. The work of Kleiner et al. (Kleiner et al. 2009) takes a very different approach. They look at NLP as a model transformation problem, utilising configuration as a model transformation to deal with the ambiguity of natural language. Model transformations are used heavily in Model Driven Engineering (MDE) and are the process of producing an output model, or several, from one or more input models. Configuration is a general method of constraint based searching that, in this case, is used to search for a model conforming to the desired meta-model. Although Kleiner et al. (Kleiner et al. 2009) show promising results, their method requires the use of a predefined lexicon to support the transformations from natural language to a useful model representation. This means that in order to utilise this method a complete lexicon needs to be defined for the domain it is being used for, which is quite impractical. This research aims to develop a method of dynamically building a lexicon based on a multi-agent system, and the principles of Emergent Semantics, and Semiotic Dynamics in a similar way to that described by Steels and Hanappe (Steels and Hanappe 2006). By dynamically generating a lexicon based on the input text the amount of time required to define a lexicon would be reduced, with the potential for a fully automated process. Therefore, the overall development time of software would be reduced through the automatic transformation of specifications to formal representations (such as UML class diagrams). In addition, it would make updating the lexicon simpler as it would become a natural ability of the system. Finally, the dynamic generation may have longe range benefits for research in semantic interoperability and
Perceived Interaction in Online Classes and Technology Acceptance Model to Student Satisfaction

본 연구의 목적은 기술수용모델이 원격교육환경에서 인지된 상호(相互)작용에 미치는 영향을 탐색하고, 확장된 기술수용모델이 원격교육환경에서의 고객만족에 미치는 영향을 총체적으로 탐색하고자 하였다. 자료는 2009년 봄 학기에 원격교육대학에 등록된 842명의 학생들로부터 수집하였다. 또한 수집된 자료는 요인분석과 구조방정식 모형을 이용하여 분 석하였다. 자료.
Boosting histogram-based denoising methods with gpu optimizations

: We propose a high-performance GPU implementation of Ray Histogram Fusion (RHF), a denoising method for stochastic global illumination rendering. Based on the CPU implementation of the original algorithm, we present a naive GPU implementation and the necessary optimization steps. Eventually, we show that our optimizations increase the performance of RHF by two orders of magnitude when compared to the original CPU implementation and one order of magnitude compared to the naive GPU implementation. We show how the quality for identical rendering times relates to unﬁltered path tracing and how much time is needed to achieve identical quality when compared to an unﬁltered path traced result. Finally, we summarize our work and describe possible future applications and research based on this.
Fault geometry and kinematics of the 2021 Mw 7.3 Maduo earthquake from aftershocks and InSAR observations

The 2021 Mw 7.3 Maduo earthquake revealed the significant seismic hazard of faults developed within the Bayan Har Block of eastern Tibet, China (e.g., the Kunlun Pass–Jiangcuo Fault). Relocated aftershock data are in good agreement with the Interferometric Synthetic Aperture Radar (InSAR) coseismic displacement field and field investigations. In this study, we used aftershock point cloud fitting to model the relocated aftershocks of the Maduo earthquake, and obtained the detailed geometry and characteristics of the seismogenic fault. Based on InSAR coseismic deformation, the geometric model of the seismogenic fault and its slip distribution were retrieved. The results show that this event was shallow (0–10 km) and characterized by sinistral strike-slip motion. We identified four asperities along the fault strike; the maximum slip of 4.84 m occurred on the eastern segment of the fault, in an area where the strike changed. The results suggest that the central segment of the main seismogenic fault is mature and smooth, while western and eastern segments are complex and immature.
Distributed Indexing and Locking : In Search of Scalable Consistency

Indexing and locking are two important components of a Relational Database Management System (RDBMS), which pose as potential bottlenecks when scaling. We present novel distributed alternatives to both of these components which are based on a spatial partitioning tree designed for scalable low-latency information storage and retrieval. The proposed solutions provide strong consistency, fault-tolerance and low latency. Our initial evaluations using the TPC-C workload show they are capable of utilizing more processing power for scalability. We believe our contributions to be an important first step toward our goal of a scalable, cloud aware and full-featured RDBMS architecture.
Distribution systems analysis and optimization

Distribution systems (DS) are the last stage of any large power system, delivering electricity to the end-users. Conventionally, simplicity of DS operation has been a priority over its optimality. However, with the recent advancements in the automation and measurement infrastructures, it is now possible to improve the efficiency of DS operation. In this dissertation, a load modeling procedure is proposed which takes advantage of the data available at the smart meters. An algorithm is proposed to decompose the load at each customer level using the smart meter measurements. The proposed load model represents the voltage dependence of loads according to the load composition. Based on the voltage-dependent load model, a linear power flow formulation is developed for DS analysis. The linear current flow equations are then proposed which calculate the branch flows directly without requiring the nodal voltages. Sensitivity factors in terms of current transfer and branch outage distribution factors are also derived using the linear power flow concept. The advantages of having a set of linear equations describing the system statics are demonstrated in a variety of DS optimization problems, such as topological reconfiguration, capacitor placement, and volt-VAR optimization. Using the linear current flow equations, the mixed-integer nonlinear programming problem of DS reconfiguration is reformulated into a mixed-integer quadratic/linear programming problem, which substantially reduces the computational burden of the nonlinear combinatorial problem. Besides developing a direct mathematical optimization approach, a fast heuristic method is also developed here for the minimum-loss network reconfiguration based on the minimum spanning tree problem. This heuristic method provides a good suboptimal solution to initialize the direct mathematical optimization approaches such as branch-and-cut algorithm used for solving combinatorial problems. Based on planar graph theory, an efficient mathematical formulation for the representation of the radiality constraint in reconfiguration problems is introduced. It is shown that this formulation is advantageous over the available methods in terms of accuracy and computational efficiency. The proposed algorithms are tested using a variety of DS benchmarks and promising results are achieved.
and Symbolic Test Generation for Safety Properties

This paper presents a combination of veri(cid:10)cation and conformance testing techniques for the formal validation of reactive systems(cid:11) A formal speci(cid:10)cation of a system (cid:12) an input(cid:12)output automaton with variables that may range over in(cid:10)nite domains (cid:12) is assumed(cid:11) Additionally(cid:13) a set of safety properties for the speci(cid:10)cation are given under the form of observers described in the same formalism(cid:11) Then(cid:13) each property is veri(cid:10)ed on the speci(cid:10)cation using automatic techniques (cid:14)e(cid:11)g(cid:11)(cid:13) ab(cid:12) stract interpretation(cid:15) that are sound but not necessarily complete for the class of safety properties considered here(cid:11) Next(cid:13) for each property(cid:13) a test case is automatically generated from the speci(cid:10)cation and the property and is executed on a black(cid:12)box implementation of the system(cid:11)
Online and out of synch: Using discussion roles in online asynchronous discussions

Abstract We completed a qualitative study focusing on our students’ use of Discussion Roles in our general and entry level online classes and presented the information at a Brown Bag presentation for University of Phoenix instructors and staff in October 2016. The following contains the results of the study including: (1) ways to use Discussion Roles in class discussions without assigning them, (2) ways to encourage students’ use of Discussion Roles, (3) how students reacted to using Discussion Roles, (4) results of students’ use of Discussion Roles, and (5) How instructors’ future use of Discussion Roles can help adult students acclimate to asynchronous, online discussion. Discussion Roles provide scaffolding that helps students create written responses that reflect higher level thinking. Implications for improving practice relate to asynchronous discussion, students’ use of higher level thinking skills, and instructors encouraging students’ use of Discussion Roles. Finally, ideas for new types of Discussion Roles led the researchers to suggest further study of Discussion Roles and how they can be used by students to take control of their learning and maximize the benefits of asynchronous discussion.
Optimality of threshold policies for heterogeneous server systems

The problem of optimally controlling a multiserver queuing system is studied. Arriving customers join a single queue, which is served by N servers, S/sub 1/, S/sub 2/, . , S/sub N/. The servers are exponential, but of different rates. The goal is to determine the policy that minimizes the total expected time a customer spends in the system. It is shown that the optical policy is of threshold type, i.e., it activates server S/sub i/ only when m/sub i/ does not depend on the condition of other (slower) servers at the decision instant. The optimal control problem is reformulated as a linear program and a novel argument is used based on the structure of the constraint matrix, in order to establish the results. <<ETX>>
Teaching programming by immersion, reading and writing

In the introductory programming course at UMass Boston we teach Java/spl trade/ by immersion. Instead of starting with the traditional "Hello, world", students read, modify and write about a 200 line bank ATM simulation program consisting of two cooperating classes. By the end of the semester they are working with a 3500-line application that models a command line shell and a hierarchical file system. Our students learn programming the same way one best learns a spoken language: by immersion. We focus immediately on questions of interfaces, architecture and design. We spend little time on syntactic details, which students simply absorb as they need them. So in this first course, students get a taste of and an appreciation for what real programming is all about.
Introduction

It is our great pleasure to present this inaugural issue for the ACM Transactions on Knowledge Discovery from Data (TKDD). Knowledge discovery from data has become a dynamic, fast-expanding, and interdisciplinary research field, and has attracted great attention in the computer science research community and high-tech industry, as well as with data-intensive application users and the general public. With the rapid development of computer technology, data collection, and information management and processing technology as well as the advent of World Wide Web, huge volumes of data have been collected and made widely available in the past decade. There is an imminent need to turn the huge volume of data into knowledge. In response to such a grand challenge, research into knowledge discovery and data mining has been growing into a new field with the confluence of several disciplines, including statistical data analysis, machine learning, database systems, data warehousing, algorithms, high-performance computing, and data-intensive applications. It is now well recognized that knowledge discovery and data mining has become an important research field in computer science. Thus, a dedicated, authoritative high-quality ACM journal will foster the development of knowledge discovery from data as a strong scientific and engineering discipline. To promote research in the field of Knowledge Discovery and Data Mining, ACM's Publication Board has decided to launch this new journal. The journal will publish high-quality research papers in the area of data mining and knowledge discovery on the principles, algorithms, methods, systems, and applications of knowledge discovery and data mining. It will concentrate on papers that have practical relevance to the construction, evaluation, application, and use of knowledge discovery and data mining systems and the infrastructure to support them. The style of this ACM journal is similar to many other ACM Transactions. The transactions will consist primarily of high-quality regular research contributions. This is an archival journal, and it is intended that the articles will have lasting importance and value over time. The journal expects to publish, at a steady rate, 4-5 articles per issue and 4 issues per year. With an overwhelming response to the call for papers for this new journal and careful reviews of the submission, we are presenting you with the first issue of this new journal and hope you will enjoy reading it. You are encouraged to prepare your high-quality research papers for submissions to this new journal. All the submissions will be handled electronically by …
Ad hoc and Opportunistic Routing in Static Scatternet Environment

Peer-to-peer connectivity between mobile phones using technologies such as Bluetooth has given a new dimension to the mobile communication. Peers through the help of various underlying protocols can form piconets and scatternets to transparently communicate the content across the network. There however are issues like reliability in communication, delay and the cost of communication that need to be considered before resorting to this form of communication. This paper presents a study where opportunistic concept such as Bubble Rap is tested in Bluetooth ad hoc networking environment. The notion behind this research is to study the properties of these two networking environments, since opportunistic networks are derived from ad hoc networks. Thus, study of these two different environments yet related to each other may help us find new ways of message forwarding in Bluetooth communication environment. This paper is aimed at investigating the behaviour of nodes present in Bluetooth static scatternet environment by 1) studying message transfer from a source to destination using traditional ad hoc communication protocols such as AODV and 2) message transfer using opportunistic algorithms such as Bubble Rap on top of traditional ad hoc communication. This paper also proposes a concept of ranking to transfer messages to the node that has higher social centrality ranking compared to the current node. Nodes with varying social ranking are allowed to join piconets and forward messages based on Bubble Rap concept in scatternet environment. In BR algorithm, nodes forward messages to only those encountering nodes which are more popular than the current node.
Malay framenet: An application for bilingual dictionary

Boas (2009) has established that the recent trends in computational lexicography encompass computational methods and tools designed to assist in various lexicographical tasks, including the preparation of lexicographical evidence from many sources, the recording in database form of the relevant linguistic information, the editing of lexicographical entries and the dissemination of lexicographical products. In line with this development, Intan Safinaz’s research (2011) on frame-based analysis on Malay corpus has produced essential semantic information compiled in a reference database that can assist lexicographers in editing dictionary entries for Malay-English bilingual dictionaries. This paper aims to discuss the frame-based analysis that incorporated Frame Semantics methodology and the benefits of compiling the database as a reference database. The entry ‘ memberi ’ is analysed and the findings contribute to the semantic content of the reference database. This reference database is able to facilitate the task of editing entries of the Malay monolingual dictionaries, Malay-English bilingual dictionaries, as well as the Malay language reference books. This paper also discusses the possibility of building a Malay FrameNet based on the architecture of the English FrameNet which was set up at the International Computer Science Institute in Berkeley. The proposed methods of building the Malay FrameNet is also inspired from the FrameNets of other languages for example the German, French and Japanese FrameNets. The setting up of the Malay FrameNet can be seen as an effort towards processing the Malay language and strengthening the Malay computational lexicography as well as encouraging future linguistic and computational lexicography research and cooperative efforts in natural language processing of the Malay language
AC 2012-3680: LEARNING MATLAB IN THE INVERTED CLASSROOM

Robert Talbert is Associate Professor of mathematics at Grand Valley State University. Formerly, he was Associate Professor of mathematics and computing science at Franklin College, where he was also the Director of that school’s 3+2 engineering program with Purdue University. His scholarly interests include cryptography, computer science, and educational technology with a special emphasis on using technology to support active learning environments in the university classroom. He holds a Ph.D. in Mathematics from Vanderbilt University.
Error Measurement & its Impact on Bilateral - Canny Edge Detector-A Hybrid Filter

Image Processing, a subset of Computer Vision, is an important branch in modern technology. Edge detection is a subset of segmentation to detect object of interest. Different image edge detection filters and their evaluating parameters are introducing rapidly. But the performance of an edge detector is an open problem. In this paper different performance measures of edge detection have been discussed in details and their application on a hybrid filter using Bilateral and Canny is proposed. Its parametric performance has been evaluated and other well established or classical existing edge detecting filters have been compared with it to measure its efficiency.
Automated Data-Driven Hint Generation for Learning Programming

Tiffany Barnes CS, NCSU Feedback is an essential component of the learning process, but in fields like computer science, which have rapidly increasing class sizes, it can be difficult to provide feedback to students at scale. Intelligent tutoring systems can provide personalized feedback to students automatically, but they can take large amounts of time and expert knowledge to build, especially when determining how to give students hints. Data-driven approaches can be used to provide personalized next-step hints automatically and at scale, by mining previous students’ solutions.
Perceptions of Clickbait: A Q - Methodology Approach

Clickbait is a class of internet content characterized by attention-grabbing headlines, but is criticized for being shallow, misleading, or deceptive. Information sciences can offer a range of solutions to clickbaiting, but the field lacks a concrete, unifying definition of the phenomenon. This posteraddresses this need by investigating perceptions and understandings of clickbait through Q-methodology.
Improving the Capacity of QR Code by UsingColor Technique

Now a days Quick Response (QR) codes are used everywhere, we can see them on posters, magazine ads, websites, product packaging and so on. Maximum storage capacity of QR code using only two colors (black & white) is 4296 characters in version 40. This capacity can be further improved by considering more colors along with black and white i.e.; red, blue, green etc. or by using multiplexing technique. In this paper a new color QR code generation algorithm is proposed, which uses both multiplexing technique and color coding technique. This algorithm increases the QR code capacity by 3 times compared to the present black and white QR codes. QR code damaged up to 30% can be efficiently decoded using RS codes. The codeword of RS code is generated using finite fields.