nils-herrmann/clean_scirepeval huggingface dataset:
Constructivist Learning Environments on the Web : Engaging Students in Meaningful Learning

An antidote for reproductive learning is to engage learners in active manipulative), constructive, intentional, complex, authentic, cooperative (collaborative and conversational), and reflective learning activities. Those characteristics are the goal of constructivist learning environments (CLEs). This paper presents a model for designing CLEs, which surround a problem/project/issue/question (including problem context, problem representation space, and problem, manipulation space) with related cases (to supplant learners’ lack of experiences and convey complexity), information resources that support knowledge construction, cognitive tools, conversation and collaboration tools, and social-contextual support for implementation. These components are supported by instructional supports, including modeling, coaching, and scaffolding. This model is directly applicable to web-based learning. Examples of web-CLEs will be demonstrated in the presentation.
Ripple: Overview and Outlook

Ripple is a payment system and a digital currency which evolved completely independently of Bitcoin. Although Ripple holds the second highest market cap after Bitcoin, there are surprisingly no studies which analyze the provisions of Ripple. In this paper, we study the current deployment of the Ripple payment system. For that purpose, we overview the Ripple protocol and outline its security and privacy provisions in relation to the Bitcoin system. We also discuss the consensus protocol of Ripple. Contrary to the statement of the Ripple designers, we show that the current choice of parameters does not prevent the occurrence of forks in the system. To remedy this problem, we give a necessary and sufficient condition to prevent any fork in the system. Finally, we analyze the current usage patterns and trade dynamics in Ripple by extracting information from the Ripple global ledger. As far as we are aware, this is the first contribution which sheds light on the current deployment of the Ripple system.
Teaching Self-Care to Caregivers : Effects of Mindfulness-Based Stress Reduction on the Mental Health of Therapists in Training

Preparation for the role of therapist can occur on both professional and personal levels. Research has found that therapists are at risk for occupationally related psychological problems. It follows that self-care may be a useful complement to the professional training of future therapists. The present study examined the effects of one approach to self-care, Mindfulness-Based Stress Reduction (MBSR), for therapists in training. Using a prospective, cohort-controlled design, the study found participants in the MBSR program reported significant declines in stress, negative affect, rumination, state and trait anxiety, and significant increases in positive affect and self-compassion. Further, MBSR participation was associated with increases in mindfulness, and this enhancement was related to several of the beneficial effects of MBSR participation. Discussion highlights the potential for future research addressing the mental health needs of therapists and therapist trainees.
Creating an ambient-intelligence environment using embedded agents

The Essex intelligent dormitory, iDorm, uses embedded agents to create an ambient-intelligence environment. In a five-and-a-half-day experiment, a user occupied the iDorm, testing its ability to learn user behavior and adapt to user needs. The embedded agent discreetly controls the iDorm according to user preferences. Our work focuses on developing learning and adaptation techniques for embedded agents. We seek to provide online, lifelong, personalized learning of anticipatory adaptive control to realize the ambient-intelligence vision in ubiquitous-computing environments. We developed the Essex intelligent dormitory, or iDorm, as a test bed for this work and an exemplar of this approach.
Minding the Source: Automatic Tagging of Reported Speech in Newspaper Articles

Reported speech in the form of direct and indirect reported speech is an important indicator of evidentiality in traditional newspaper texts, but also increasingly in the new media that rely heavily on citation and quotation of previous postings, as for instance in blogs or newsgroups. This paper details the basic processing steps for reported speech analysis and reports on performance of an implementation in form of a GATE resource.
Community Detection in Social Networks: An In-depth Benchmarking Study with a Procedure-Oriented Framework

Revealing the latent community structure, which is crucial to understanding the features of networks, is an important problem in network and graph analysis. During the last decade, many approaches have been proposed to solve this challenging problem in diverse ways, i.e. different measures or data structures. Unfortunately, experimental reports on existing techniques fell short in validity and integrity since many comparisons were not based on a unified code base or merely discussed in theory. We engage in an in-depth benchmarking study of community detection in social networks. We formulate a generalized community detection procedure and propose a procedure-oriented framework for benchmarking. This framework enables us to evaluate and compare various approaches to community detection systematically and thoroughly under identical experimental conditions. Upon that we can analyze and diagnose the inherent defect of existing approaches deeply, and further make effective improvements correspondingly. We have re-implemented ten state-of-the-art representative algorithms upon this framework and make comprehensive evaluations of multiple aspects, including the efficiency evaluation, performance evaluations, sensitivity evaluations, etc. We discuss their merits and faults in depth, and draw a set of take-away interesting conclusions. In addition, we present how we can make diagnoses for these algorithms resulting in significant improvements.
Low-loss compact ku-band waveguide low-pass filter

A lower-loss, more compact alternative to the classical E-plane corrugated waveguide low-pass filter is proposed in this paper. The novel design is capable of achieving very steep slopes in the fundamental TE10-mode frequency response along with a drastic reduction in terms of insertion loss and size. The design method is based on step-shaped bandstop elements separated by very short waveguide sections. Moreover, the matching of the novel filter is achieved by very short input/output networks based on stubs of optimized heights. A simple method is proposed allowing the designer to obtain a compact low-pass filter fulfilling stringent specifications.
Finite State Machine based Vending Machine Controller with Auto-Billing Features

Nowadays, Vending Machines are well known among Japan, Malaysia and Singapore. The quantity of machines in these countries is on the top worldwide. This is due to the modern lifestyles which require fast food processing with high quality. This paper describes the designing of multi select machine using Finite State Machine Model with Auto-Billing Features. Finite State Machine (FSM) modeling is the most crucial part in developing proposed model as this reduces the hardware. In this paper the process of four state (user Selection, Waiting for money insertion, product delivery and servicing) has been modeled using MEALY Machine Model. The proposed model is tested using Spartan 3 development board and its performance is compared with CMOS based machine.
Hybrid elevation maps: 3D surface models for segmentation

This paper presents an algorithm for segmenting 3D point clouds. It extends terrain elevation models by incorporating two types of representations: (1) ground representations based on averaging the height in the point cloud, (2) object models based on a voxelisation of the point cloud. The approach is deployed on Riegl data (dense 3D laser data) acquired in a campus type of environment and compared against six other terrain models. Amongst elevation models, it is shown to provide the best fit to the data as well as being unique in the sense that it jointly performs ground extraction, overhang representation and 3D segmentation. We experimentally demonstrate that the resulting model is also applicable to path planning.
How Mental Systems Believe

Is there a difference between believing and merely understanding an idea?Descartes thought so. He considered the acceptance and rejection of an idea to be alternative outcomes of an effortful assessment process that occurs subsequent to the automatic comprehension of that idea. This article examined Spinoza's alternative suggestion that (a) the acceptance of an idea is part of the automatic comprehension of that idea and (b) the rejection of an idea occurs subsequent to, and more effortfully than, its acceptance. In this view, the mental representation of abstract ideas is quite similar to the mental representation of physical objects: People believe in the ideas they comprehend, as quickly and automatically as they believe in the objects they see. Research in social and cognitive psychology suggests that Spinoza's model may be a more accurate account of human belief than is that of Descartes.
A new posterolateral approach without fibula osteotomy for the treatment of tibial plateau fractures.

The selection of a surgical approach for the treatment of tibia plateau fractures is an important decision. Approximately 7% of all tibia plateau fractures affect the posterolateral corner. Displaced posterolateral tibia plateau fractures require anatomic articular reduction and buttress plate fixation on the posterior aspect. These aims are difficult to reach through a lateral or anterolateral approach. The standard posterolateral approach with fibula osteotomy and release of the posterolateral corner is a traumatic procedure, which includes the risk of fragment denudation. Isolated posterior approaches do not allow sufficient visual control of fracture reduction, especially if the fracture is complex. Therefore, the aim of this work was to present a surgical approach for posterolateral tibial plateau fractures that both protects the soft tissue and allows for good visual control of fracture reduction. The approach involves a lateral arthrotomy for visualizing the joint surface and a posterolateral approach for the fracture reduction and plate fixation, which are both achieved through one posterolateral skin incision. Using this approach, we achieved reduction of the articular surface and stable fixation in six of seven patients at the final follow-up visit. No complications and no loss of reduction were observed. Additionally, the new posterolateral approach permits direct visual exposure and facilitates the application of a buttress plate. Our approach does not require fibular osteotomy, and fragments of the posterolateral corner do not have to be detached from the soft tissue network.
Support Vector Machine Ensemble with Bagging

Even the support vector machine (SVM) has been proposed to provide a good generalization performance, the classification result of the practically implemented SVM is often far from the theoretically expected level because their implementations are based on the approximated algorithms due to the high complexity of time and space. To improve the limited classification performance of the real SVM, we propose to use the SVM ensembles with bagging (bootstrap aggregating). Each individual SVM is trained independently using the randomly chosen training samples via a bootstrap technique. Then, they are aggregated into to make a collective decision in several ways such as the majority voting, the LSE(least squares estimation)-based weighting, and the double-layer hierarchical combining. Various simulation results for the IRIS data classification and the hand-written digit recognitionshow that the proposed SVM ensembles with bagging outperforms a single SVM in terms of classification accuracy greatly.
Epistasis — the essential role of gene interactions in the structure and evolution of genetic systems

Epistasis, or interactions between genes, has long been recognized as fundamentally important to understanding the structure and function of genetic pathways and the evolutionary dynamics of complex genetic systems. With the advent of high-throughput functional genomics and the emergence of systems approaches to biology, as well as a new-found ability to pursue the genetic basis of evolution down to specific molecular changes, there is a renewed appreciation both for the importance of studying gene interactions and for addressing these questions in a unified, quantitative manner.
QoE management in DASH systems using the segment aware rate adaptation algorithm

Dynamic Adaptive Streaming over HTTP (DASH) enables the video player to adapt the bitrate of the video while streaming to ensure playback without interruptions even with varying throughput. A DASH server hosts multiple representations of the same video, each of which is broken down into small segments of fixed playback duration. The video bitrate adaptation is purely driven by the player at the endhost. Typically, the player employs an Adaptive Bitrate (ABR) algorithm, that determines the most appropriate representation for the next segment to be downloaded, based on the current network conditions and user preferences. The aim of an ABR algorithm is to dynamically manage the Quality of Experience (QoE) of the user during the playback. ABR algorithms manage the QoE by maximizing the bitrate while at the same time trying to minimize the other QoE metrics: playback start time, duration and number of buffering events, and the number of bitrate switching events. Typically, the ABR algorithms manage the QoE by using the measured network throughput and buffer occupancy to adapt the playback bitrate. However, due to the video encoding schemes employed, the sizes of the individual segments may vary significantly. For low bandwidth networks, fluctuation in the segment sizes results in inaccurate estimation the expected segment fetch times, thereby resulting in inaccurate estimation of the optimum bitrate. In this paper we demonstrate how the Segment-Aware Rate Adaptation (SARA) algorithm, that considers the measured throughput, buffer occupancy, and the variation in segment sizes helps in better management of the users' QoE in a DASH system. By comparing with a typical throughput-based and buffer-based adaptation algorithm under varying network conditions, we demonstrate that SARA manages the QoE better, especially in a low bandwidth network. We also developed AStream, an open-source Python-based emulated DASH-video player that was used to evaluate three different ABR algorithms and measure the QoE metrics with each of them.
Flower Pollination Algorithm: A Novel Approach for Multiobjective Optimization

Copyright and moral rights to this thesis/research project are retained by the author and/or other copyright owners. The work is supplied on the understanding that any use for commercial gain is strictly forbidden. A copy may be downloaded for personal, non-commercial, research or study without prior permission and without charge. Any use of the thesis/research project for private study or research must be properly acknowledged with reference to the work’s full bibliographic details.
Design and Efficient FPGA Implementation of Ghash Core for AES-GCM

AES-GCM(Advanced Encryption Standard with Galois Counter Mode) is an encryption authentication algorithm, which includes two main components: an AES engine and Ghash module. Because of the computation feedback in Ghash operation, the Ghash module limits the performance of the whole AES-GCM system. In this study, an efficient architecture of Ghash is presented. The architecture uses an optimized bit-parallel multiplier. In addition, based on this multiplier, pipelined method is adopted to achieve higher clock rate and throughput. We also introduce a redundant register method, which is never mentioned before, for solving the big fan- out problem derived from the bit-parallel multiplier. In the end, the performance of proposed design is evaluated on Xilinx virtex4 FPGA platform. The experimental results show that our Ghash core has less clock delay and can easily achieve higher throughput, which is up to 40Gbps.
Temporal Random Indexing: a Tool for Analysing Word Meaning Variations in News

The availability of data spanning different epochs has inspired a new analysis of cultural, social, and linguistic phenomena from a temporal perspective. This paper describes the application of Temporal Random Indexing (TRI) to the news context. TRI is able to build geometrical spaces of word meanings that consider several periods of time. Hence, TRI enables the analysis of the evolution in time of the meaning of a word. We propose some examples of application of TRI to the analysis of word meanings in the news scenario; this analysis enables the detection of linguistic variations that emerge in specific time intervals and that can be related to particular events.
Using hidden Markov models for topic segmentation of meeting transcripts

In this paper, we present a hidden Markov model (HMM) approach to segment meeting transcripts into topics. To learn the model, we use unsupervised learning to cluster the text segments obtained from topic boundary information. Using modified WinDiff and Pk metrics, we demonstrate that an HMM outperforms LCSeg, a state-of-the-art lexical chain based method for topic segmentation using the ICSI meeting corpus. We evaluate the effect of language model order, the number of hidden states, and the use of stop words. Our experimental results show that a unigram LM is better than a trigram LM, using too many hidden states degrades topic segmentation performance, and that removing the stop words from the transcripts does not improve segmentation performance.
Embedding Temporal Display into Maps for Occlusion-Free Visualization of Spatio-temporal Data

It is often necessary to analyze spatio-temporal data such as traffic flow, air pollution, and vehicle trajectories in a city. A map is often used to show the spatial context while various temporal displays like time series plots can be used to present the changes in the data over time. In this paper, we present a novel visualization that can seamlessly embed temporal displays into a map for occlusion-free visualization of both the spatial and temporal attributes of the data. We first extend the seam carving algorithm to broaden the roads of interest in a map with the least distortion to other areas, and then embed temporal displays into the roads to reveal temporal patterns without the occlusion of map information. We study various design choices in our method, including the encoding of the time direction and temporal display, and conduct two comprehensive user studies to validate our design decisions. We also demonstrate the usability of our approach with case studies on real traffic flow data in a major city.
A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems

The basic aim of a biometric identification system is to discriminate automatically between subjects in a reliable and dependable way, according to a specific-target application. Multimodal biometric identification systems aim to fuse two or more physical or behavioral traits to provide optimal False Acceptance Rate (FAR) and False Rejection Rate (FRR), thus improving system accuracy and dependability. In this paper, an innovative multimodal biometric identification system based on iris and fingerprint traits is proposed. The paper is a state-of-the-art advancement of multibiometrics, offering an innovative perspective on features fusion. In greater detail, a frequency-based approach results in a homogeneous biometric vector, integrating iris and fingerprint data. Successively, a hamming-distance-based matching algorithm deals with the unified homogenous biometric vector. The proposed multimodal system achieves interesting results with several commonly used databases. For example, we have obtained an interesting working point with FAR = 0% and FRR = 5.71% using the entire fingerprint verification competition (FVC) 2002 DB2B database and a randomly extracted same-size subset of the BATH database. At the same time, considering the BATH database and the FVC2002 DB2A database, we have obtained a further interesting working point with FAR = 0% and FRR = 7.28% ÷ 9.7%.
Question Answering in Webclopedia

SHAPE ADJECTIVE COLOR DISEASE TEXT NARRATIVE* GENERAL-INFO DEFINITION USE EXPRESSION-ORIGIN HISTORY WHY-FAMOUS BIO ANTECEDENT INFLUENCE CONSEQUENT CAUSE-EFFECT METHOD-MEANS CIRCUMSTANCE-MEANS REASON EVALUATION PRO-CON CONTRAST RATING COUNSEL-ADVICE To create the QA Typology, we analyzed 17,384 questions and their answers (downloaded from answers.com); see (Gerber, 2001). The Typology contains 94 nodes, of which 47 are leaf nodes; a section of it appears in Figure 2. Each Typology node has been annotated with examples and typical patterns of expression of both Question and Answer, as indicated in Figure 3 for Proper-Person. Question examples Question templates Who was Johnny Mathis' high school track coach? who be <entity>'s <role> Who was Lincoln's Secretary of State? Who was President of Turkmenistan in 1994? who be <role> of <entity> Who is the composer of Eugene Onegin? Who is the CEO of General Electric? Actual answers Answer templates Lou Vasquez, track coach of...and Johnny Mathis <person>, <role> of <entity> Signed Saparmurad Turkmenbachy [Niyazov], <person> <role-title*> of <entity> president of Turkmenistan ...Turkmenistan’s President Saparmurad Niyazov... <entity>’s <role> <person> ...in Tchaikovsky's Eugene Onegin... <person>'s <entity> Mr. Jack Welch, GE chairman... <role-title> <person> ... <entity> <role> ...Chairman John Welch said ...GE's <subject>|<psv object> of related role-verb Figure 3. Portion of QA Typology node annotations for Proper-Person.
Novel Coplanar Line-Points Invariants for Robust Line Matching Across Views

Luo, Z. X., Zhou, X. C., David XianFeng, G. U. (2014). From a projective invariant to some new properties of algebraic hypersurfaces.), 2273-2284.  Fan, B., Wu, F., Hu, Z. (2010). Line matching leveraged by point correspondences.   Fan, B., Wu, F., & Hu, Z. (2012). Robust line matching through line–point invariants. Pattern Recognition, 45(2), 794-805.  López, J., Santos, R., Fdez-Vidal, X. R., & Pardo, X. M. (2015). Two-view line matching algorithm based on context and appearance in low-textured images. Pattern Recognition, 48(7), 2164-2184. Dalian University of Technology Qi Jia, Xinkai Gao, Xin Fan*, Zhongxuan Luo, Haojie Li,and Ziyao Chen Novel Coplanar Line-points Invariants for Robust Line Matching Across Views
Key issues in conducting sentiment analysis on Arabic social media text

The problem of extracting sentiments from text is a very complex task, in particular due to the significant amount of Natural Language Processing (NLP) required. This task becomes even more difficult when dealing with morphologically rich languages such as Modern Standard Arabic (MSA) and when processing brief, noisy texts such as “tweets” or “Facebook statuses”. This paper highlights key issues researchers are facing and innovative approaches that have been developed when performing subjectivity and sentiment analysis (SSA) on Arabic text in general and Arabic social media text in particular. A preprocessing phase to sentiment analysis is proposed and shown to noticeably improve the results of sentiment extraction from Arabic social media data.