Reviewerly/exHarmony huggingface dataset:
Research on Application of Computer-Assisted Software in Teaching English Scientific Paper Writing under Blended Teaching Mode

The rapid development of modem information technology has brought great changes to people’s daily work and life, and the extensive application of network information technology in modern English teaching will bring about a series of innovations to the traditional English teaching mode. The application of computer-assisted software to English teaching can improve the teaching quality and increase the learning efficiency of students. Based on the blended English teaching model under the network environment, this paper attempts to clarify and present the research on application of computer-assisted software (Rain Classroom) in teaching English Scientific Paper Writing. This new teaching mode can not only record students’ learning data throughout the whole process, so that the evaluation can be based on the data, but also can improve the teaching effect of the course from many different links, stimulate students’ interest in learning. Taking English Scientific Paper Writing course as the research object, this paper discusses the blended teaching mode based on rain classroom (Rain Classroom +Offline Teaching) in teaching by taking English scientific paper writing course as an example. English scientific paper writing course requires students to read a lot of theses before class. Before class, teacher arranges tasks through rain classroom, and supervises students to finish reading and analyzing tasks in advance. In class, students make reports and statements, and then teacher answers questions and clears up doubts. Through this method, the learning efficiency and students’ enthusiasm are improved. After class, based on the classroom data analysis of rain classroom, students’ learning dynamics are mastered in real time and guidance is provided, which lays the foundation for the scientific evaluation model based on full data-driven. By analyzing the data and results recorded in rain classroom using rain classroom data statistical software, it is concluded that computer-assisted software (rain classroom) is more convenient and objective in assistant means of English writing teaching, which will provide some reference for improving the quality of Chinese college English teaching.
Vertical Result Page Generation for Academic Web Searching

Vertical search engines are meant for answering a user's web query within a specific domain such as news, media, and academic web searching. One main difference between vertical and horizontal web searching is that in vertical web searching, unlike horizontal web searching, a subset of entire web is engaged. The chapter investigates the state-of-the-art in academic web searching and points out shortcomings in this particular domain. Lastly, the authors aimed to propose a summary-based recommender to respond to a user's query by retrieving and ranking them according to their similarity merits on the basis of papers' summaries. Results of the evaluations revealed the fact that the proposed framework has outperformed the state-of-the-art in different metrics such as unanimous ranks and F1 measures.
Teaching Pre-Service Teachers to Repurpose and Innovate Using Online and Mobile Technology Applications

Integrating the use of Web-based and mobile technology applications into K-12 world languages contexts requires innovative teacher preparation models. This chapter evaluates a multi-step technology integration unit that develops in pre-service teachers the skills necessary to plan and carry out learner-centered communicative instruction. Importantly, this unit also incorporates five skills for disruptive innovators. Pre-service teachers blend pedagogy, technology tools, and content in project-based learning lesson design while practicing creative-thinking skills. As student teachers learn to repurpose mobile applications for the language-learning classroom, they empower articulate digital natives and foster 21st century learning. Given technology's constant growth, teaching integration of specific apps will have limited benefits. On the other hand, teaching how to innovate and repurpose will serve student teachers for their entire career. Results of this study show growth in lesson planning, creativity, and innovation skills.
Sentiment Analysis with Text Mining in Contexts of Big Data

The evolution of technology, along with the common use of different devices connected to the Internet, provides a vast growth in the volume and variety of data that are daily generated at high velocity, phenomenon commonly denominated as Big Data. Related with this, several Text Mining techniques make possible the extraction of useful insights from that data, benefiting the decision-making process across multiple areas, using the information, models, patterns or tendencies that these techniques are able to identify. With Sentiment Analysis, it is possible to understand which sentiments and opinions are implicit in this data. This paper proposes an architecture for Sentiment Analysis that uses data from the Twitter, which is able to collect, store, process and analyse data on a real-time fashion. To demonstrate its utility, practical applications are developed using real world examples where Sentiment Analysis brings benefits when applied. With the presented demonstration case, it is possible to verify the role of each used technology and the techniques adopted for Sentiment Analysis.
Virtualization as the Enabling Technology of Cloud Computing

Cloud computing is the newest paradigm in computing that turned upside down the way of resource provisioning and payment. Cloud computing improves the resource utilization through virtualization enabling both customers as well as service providers to reap the benefits. Thus, virtualization is the enabling technology that made this revolution possible. Through virtualization, it is possible to host multiple independent systems on a single hardware without interfering with each other. Server virtualization techniques can be grouped based how the underlying hardware and operating systems are presented to the users. In this chapter, the author takes an in depth look at how different virtualization has been implemented along with their security and quality of service issues.
Automata Theory

This chapter discusses automata theory, including finite-state machines, pushdown automata and Turing machines. Finite-state machines are abstract machines that are in only one state at a time, and the input symbol causes a transition from the current state to the next state. Pushdown automata have greater computational power, and they contain extra memory in the form of a stack from which symbols may be pushed or popped. The Turing machine is the most powerful model for computation, and this theoretical machine is equivalent to an actual computer in the sense that it can compute exactly the same set of functions.
Introduction

Since its idealistic proposal to build a computing machine using quantum mechanics by the aspiring physicist, Richard P. Feynman, in the 1980s (Feynman in Int J Theor Phys 21:467, 1982 [1]), the term “quantum computer” becomes a holy grail of many physicists, computer scientists, and engineers, because it promises speedup and robust computational power over its classical counterparts.
Daily briefing: One paper, two conclusions

An unusual reproducibility experiment, the escalating Ebola crisis in the DRC and let’s all go to Venus. An unusual reproducibility experiment, the escalating Ebola crisis in the DRC and let’s all go to Venus.
MCOQR (Misuse Case-Oriented Quality Requirements) Metrics Framework

In today's information age, software is attacked deliberately resulting in breach of security &amp; people's trust. These malicious attacks provide harm to individuals, organizations, and the world at large. The attacker targets vulnerabilities to exploit the software. The chapter highlights the importance of security metrics which is comprehensive in nature and easily implementable. It also emphasis on the early implementation of security metrics i.e., from the requirements elicitation phase of requirement engineering stage so that a comprehensive and complete set of security requirements could be defined with their countermeasure to develop a secured software. For development of security metrics a framework has been proposed using use case and misuse case tree modeling. The proposed work may help the Software Security Team to identify and analyse the potential vulnerabilities and associated threats which may be exploited by the attacker to harm the system well in advance in the requirements engineering phase thereby balancing the security using misuse cases modeling.
Personal authentication and risk evaluation by sensible keyboard sound

Personal authentication is an essential process in various network applications such as online shopping, mobile banking, e-government services, etc. The authentication processes normally use personal or device information which include user password, IP address, device number, MAC address, and bio information such as fingerprints or iris scan. In addition to the direct personal or device information, environmental information can be used for authentication. For example, the location and time of the device use may be considered as important factors to evaluate the risk of false use. The authentication technique is getting more important as the volume of online business and the chances of non-face-to-face contacts enormously increase. This paper proposes a personal authentication technique using sensible sound of keyboard input device. We can extract the unique features of the keyboard stroke sound, and use the features for personal authentication and also for risk evaluation to protect from fraud.
Mitigating Strategy of Cyber Crime for Indonesian National Police

This study aims to determine the level of professionalism of the performance of the National Police Apparatus and find a strategy to improve the professionalism of the Indonesian Police based on information technology in dealing with cyber-crime. The approach used in this study was descriptive qualitative, where the research informants were 2 representatives from the National Police, Ministry of Communication and Information Officials and community leaders respectively. Data sources were obtained from the results of interviews, FGDs and observations where data were analyzed using the ASOCA approach (Ability, Strength, Opportunity, Culture and Agility). ASOCA analysis is used to determine the strategy of the National Police in handling Cyber Crime. The results of the study indicate that the resources of the Indonesian Police apparatus in dealing with cyber-crime are not professional. This is indicated by various obstacles faced by the national police, both technical and non-technical obstacles. The results of the ASOCA analysis show that there are six strategies related to the priority of cyber crime mitigation. All six strategies proposed should be accommodated by POLRI national police to support successful programs for mitigating impact of cyber-crime in Indonesia.
Performance Evaluation of VM Placement Using Classical Bin Packing and Genetic Algorithm for Cloud Environment

In current era, the trend of cloud computing is increasing with every passing day due to one of its dominant service i.e. Infrastructure as a service (IAAS), which virtualizes the hardware by creating multiple instances of VMs on single physical machine. Virtualizing the hardware leads to the improvement of resource utilization but it also makes the system over utilized with inefficient performance. Therefore, these VMs need to be migrated to another physical machine using VM consolidation process in order to reduce the amount of host machines and to improve the performance of system. Thus, the idea of placing the virtual machines on some other hosts leads to the proposal of many new algorithms of VM placement. However, the reduced set of physical machines needs the lesser amount of power consumption therefore; in current work the authors have presented a decision making VM placement system based on genetic algorithm and compared it with three predefined VM placement techniques based on classical bin packing. This analysis contributes to better understand the effects of the placement strategies over the overall performance of cloud environment and how the use of genetic algorithm delivers the better results for VM placement than classical bin packing algorithms.
Initial pose estimation and update during robot path planning loop

This paper presents a modified path planning algorithm with time spent monitoring of searching loop, estimating initial pose of ego-vehicle and updating reference global path. Modified reference path can be well-used by trajectory tracking module. The advantages of our proposed algorithm are attributed to strict monitor of time spent in path search loop, estimation and update of initial pose and reference path. Monitor of time spent ensures that abnormal information will be detected and reported when desired planning frequency is not reachable because of too much unexpected time spent on path searching. Experiments confirm that our proposed modification shows no obvious extra cost on time spent of the whole algorithm, and significantly decrease distance error between initial pose of reference path and robot actual pose in different scenarios.
A User-Aware and Semantic Approach for Enterprise Search

This article describes how in addition to general purposes search engines, specialized search engines have appeared and have gained their part of the market. An enterprise search engine enables the search inside the enterprise information, mainly web pages but also other kinds of documents; the search is performed by people inside the enterprise or by customers. This article proposes an enterprise search engine called AMBIT1-SE that relies on two enhancements: first, it is user-aware in the sense that it takes into consideration the profile of the users that perform the query; second, it exploits semantic techniques to consider not only exact matches but also synonyms and related terms. It performs two main activities: (1) information processing to analyse the documents and build the user profile and (2) search and retrieval to search for information that matches user's query and profile. An experimental evaluation of the proposed approach is performed on different real websites, showing its benefits over other well-established approaches.
Big and Small Lies

Lying often involves many decisions that can yield big or small benefits. We investigate how asymmetry in the size of a lie affects lying behavior within a two-dimensional context, by conducting a laboratory experiment with three treatments. In the Big and Small Lie (BSL) treatment, participants can simultaneously tell a big and a small lie. In the Big Lie (BL) treatment, participants can misreport only a high-stakes outcome because a computer exogenously determines the low-stakes outcome. The Small Lie (SL) treatment reverses the BL treatment. We find that participants in the BSL treatment lie in both the low- and the highstakes, but they lie more about the outcome of the high-stakes. Interestingly, we also show that participants behavior—either lying or truth-telling—is consistent between the big lie and small lie dimensions. Moreover, the level of lying on both the high-stakes (BSL vs. BL) and the lowstakes outcome (BSL vs. SL) does not differ between treatments. It means that the second outcome, regardless of being an exogenous prize or endogenously determined, does not affect participants’ lying behavior regarding the first outcome. Notably, however, we find that repeatedly being lucky (unlucky) on a high-stakes prize leads to less (more) lying on the report of a low-stakes outcome.
In Search of the Performance- and Energy-Efficient CNN Accelerators

In this paper, starting from the algorithm, a performance- and energy-efficient 3D structure or shape of the Tensor Processing Engine (TPE) for CNN acceleration is systematically searched and evaluated. An optimal accelerator's shape maximizes the number of concurrent MAC operations per clock cycle while minimizes the number of redundant operations. The proposed 3D vector-parallel TPE architecture with an optimal shape can be very efficiently used for considerable CNN acceleration. Due to implemented support of inter-block image data independency, it is possible to use multiple of such TPEs for the additional CNN acceleration. Moreover, it is shown that the proposed TPE can also be uniformly used for acceleration of the different CNN models such as VGG, ResNet, YOLO, and SSD. We also demonstrate that our theoretical efficiency analysis is matched with the result of a real implementation for an SSD model to which a state-of-the-art channel pruning technique is applied.
Qubits

Information in computing (classical or quantum) is represented as binary 0 and 1. Quantum computing uses quantum states to represent 0 and 1, allowing a superposition of 0 and 1 simultaneously. This superposition of 0 and 1 is called a qubit which is the fundamental unit of quantum computing.
Video 5: How to make your own paper making frame and paper

Intended audience: Primary school science and technology teachers and learners &lt;br&gt;&lt;br&gt;I have been doing paper-making workshops with children for 20 years where we recycle waste paper to make decorative recycled paper. The problem is that all website videos I have ever been able to find show you how to make paper using an expensive wooden frame. This means that if you show either learners or teachers how to make paper, they will never do so at home because the frame is too difficult to come by. This video shows how to make an effective frame using a plastic container and stretchy mesh that is used to pack lemons in supermarkets. Now, student teachers can all leave my workshops with their own frames that they can use with their learners in their classrooms OR which they can help their own learners to make for themselves. This greatly extends the potential for implementing this activity in poorly resourced classrooms. Also, it combination with the ‘why recycle paper’ video, it is an effective way of showing the relationship between science and technology in primary school classrooms.&lt;br&gt;
I'd Like to Teach the World to Think

At the time of this writing, 2017, there is noticeable reduction in the perceived ability of people to think critically. Both the popular press and the scientific/professional literature recognize this worldwide drop. This chapter presents the use of experimental design of ideas, conjoint measurement, originally a tool used in marketing, as a tool to inspire creative thinking. The chapter presents the approach and application of conjoint measurement as a tool for discovery, and then delineates a new computer APP, Big Mind, as user friendly to enhance critical thinking. Big Mind embodies conjoint measurement to help researchers study topics, uncover new substantive findings, and learn to think critically as an outcome from the process.
Databench-T:A Transactional Database Benchmark for Financial Scenarios

This paper reviewed current transactional database benchmark, especially TPC-C. There are some limitations to apply TPC-C into financial industry for benchmarking transactional database. In order to simulate real financial business, the project member has designed a benchmark named Databench-T, which is based on money transfer scenario. The model and workloads of the benchmark is introduced in detail in this paper. The benchmark is implemented by project members to provide a unified toolkit. To run a test, there are four steps: toolkit installation, data generation, workload execute and results display. All those steps are presented in the paper.
A Hybrid Cloud Model for Cloud Adoption by Multinational Enterprises

As a new IT paradigm for users, cloud computing has the potential to transform the way that IT resources are utilized and consumed. Many multinational enterprises (MNEs) are interested in cloud computing but do not know how to adopt and implement cloud computing in their enterprise settings. In an effort to help MNEs understand cloud computing and develop successful enterprise adoption strategies for cloud computing, the authors propose a hybrid cloud model for MNEs and illustrate the utility of this model by using two case studies. Insights for adopting and implementing this model in international settings are provided as well.
Translation Semantics and Static Analysis

We present and discuss the translation techniques and the static analysis of programs. After abstractly defining a translation as a relation between strings, we present the operational models of transliteration and purely syntactic translation. These models are defined by means of regular translation expressions and by transduction grammars, also known as syntactic translation schemes; they are, respectively, computed by finite or pushdown transducers. Then we move to the more practical approach known as semantic translation, which consists of functions that operate on the syntactic tree of the source text, and compute the values of semantic attributes. Semantic translations are formalized by means of attribute grammars. We show some typical applications of attribute grammars for checking variable declaration, code generation and semantics-directed parsing. We examine the dependencies between semantic attributes and how they condition the evaluation order, and the number and direction of compiler passes. Finally, we consider the static analysis of programs: the program is viewed as a finite control-flow graph, and a few important properties concerning its correctness and efficiency are established, through an approach based on writing flow equations and iteratively solving them. The approach is illustrated by the problems of liveness intervals and reaching definitions, and their use for memory allocation and constant propagation.
Push

tutorial Push Share on Author: Lee Spector UMass Amherst UMass AmherstView Profile Authors Info & Claims GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference CompanionJuly 2020 Pages 1174–1189https://doi.org/10.1145/3377929.3389883Online:08 July 2020Publication History 0citation31DownloadsMetricsTotal Citations0Total Downloads31Last 12 Months8Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Robust Discriminative Object Tracker Optimized with KL Divergence

Object tracking is to evaluate the state of a target object in a video sequence at each frame. Despite the astonishing improvements in visual tracking over the years, trackers remain vulnerable to target drift in target estimation when confronting similar distractors or intricate backgrounds. To address these problems, We disaggregate the object tracking task into a conjunction of a classification task and a regression task. For the classification task, Our online multi-layer fusion branch makes the most of target and contextual information. For the regression branch, we adopt the IoU-based method optimized with Kullback-Leibler divergence using Monte Carlo sampling, which models label noise stemming from inaccurate annotations. This simple and effective tracker is termed as MInet. Without bells and whistles, MInet enables leading performance with realtime speeds on five tracking benchmarks comprising OTB2015, VOT2018, LaSOT, UAV123 and GOT-10K, achieving an NP of 0.706 on LaSOT and AO of 0.656 on GOT-10K.