Miracle-dz/UniFAR-FTUs huggingface dataset:
DanNet: udvikling og anvendelse af det danske wordnet

A wordnet for Danish is under compilation as a joint project between the Centre for Language Technology at the University of Copenhagen and the Society for Danish Language and Literature. Both partners have recently been involved in the development of relevant lexical resources which are utilized as an important part of the current project, most importantly The Danish Dictionary, a corpus-based dictionary of modern Danish, and the international SIMPLE project. This article describes how the existing data are reused to create a much sought-after resource within Danish language technology. Typical examples and problems faced during the editing process are presented, with focus on polysemy, synonymy and semantic classification. Finally, we outline some perspectives for lexicographic products aimed at human users. Specifically, the development potential for the productive function of dictionaries is discussed, as are ways of improving the pedagogical function of learners’ dictionaries.
Performance of Matching Algorithms in Non-Standard Expression-Variant Faces

After attending this presentation, attendees will understand the basic principles on which mesh-to-mesh and deep learning algorithms for 3D face recognition are grounded. Attendees will also be more familiar with the performance of 3D-to-3D and 2D-to-3D matching algorithms as tested on expression-variant 3D recordings of human faces.
A 15-W monolithic power operational amplifier

The design of a new general-purpose monolithic power amplifier functional block is described and the flexibility of the block in various applications is discussed. The effects of thermal coupling on the die between components in high-gain dc power amplifiers are examined and a technique is presented for the analytical evaluation of dc circuit performance in the presence of these thermal interactions. Experimental results from the 15-W amplifier are presented. A new integrated power transistor structure is described that includes emitter degeneration resistors as part of the emitter structure. Circuit performance is summarized.
Automated Analysis of Biomedical Data from Low to High Resolution

Recent developments of experimental techniques and instrumentation allow life scientists to acquire enormous volumes of data at unprecedented resolution. While this new data brings much deeper insight into cellular processes, it renders manual analysis infeasible and calls for the development of new, automated analysis procedures. This thesis describes how methods of pattern recognition can be used to automate three popular data analysis protocols: Chapter 1 proposes a method to automatically locate bimodal isotope distribution patterns in Hydrogen Deuterium Exchange Mass Spectrometry experiments. The method is based on L1-regularized linear regression and allows for easy quantitative analysis of co-populations with different exchange behavior. The sensitivity of the method is tested on a set of manually identified peptides, while its applicability to exploratory data analysis is validated by targeted follow-up peptide identification. Chapter 2 develops a technique to automate peptide quantification for mass spectrometry experiments, based on 16O/18O labeling of peptides. Two different spectrum segmentation algorithms are proposed: one based on image processing and applicable to low resolution data and one exploiting the sparsity of high resolution data. The quantification accuracy is validated on calibration datasets, produced by mixing a set of proteins in pre-defined ratios. Chapter 3 provides a method for automated detection and segmentation of synapses in electron microscopy images of neural tissue. For images acquired by scanning electron microscopy with nearly isotropic resolution, the algorithm is based on geometric features computed in 3D pixel neighborhoods. For transmission electron microscopy images with poor z-resolution, the algorithm uses additional regularization by performing several rounds of pixel classification with features computed on the probability maps of the previous classification round. The validation is performed by comparing the set of synapses detected by the algorithm against a gold standard detection by human experts. For data with nearly isotropic resolution, the algorithm performance is comparable to that of the human experts.
Students' Perceptions of Study Modes

This paper reports on a survey of how Australian undergraduate students perceive the benefits of broad study modes: face‐to‐face classes, web‐based study, and print‐based study. Two benefit types were identified through factor analysis: engagement and functionality. Respondents rated face‐to‐face classes highest on engagement and print‐based study highest on functionality. However, they distinguished only marginally between the engagement and functionality benefits of print‐based and web‐based study. Two variables associated with differences in students’ perceptions of study modes were attendance mode and student tenure. The findings raise questions about the learning and marketing rationales for offering web‐based delivery of educational programmes at the expense of both the traditional face‐to‐face experience and the traditional “distance” experience in Australia using print materials.
Chapter VIII The Role of Mediating Artefacts in Learning Design

The chapter provides a theoretical framework for understanding learning activities, centering on two key aspects: (1) the capture and representation of activities and (2) mechanisms for scaffolding the design process, which is introduced here as a formal methodology for learning design. The chapter begins by describing how information can be abstracted from learning activities via a range of different forms of representation (models, iconic diagrams, textual case studies, etc.), which are defined here as ‘mediating artefacts. ’ It discusses how different mediating artefacts can be used to inform the process of designing a new learning activity. It augments and provides an illustration of the theoretical arguments developed in the chapter by summarizing some of the findings from relevant research on learning design and uses the DialogPlus toolkit as a case study and an example of a mediating artefact that can be used to support the design of a learning activity. The toolkit includes examples of learning activities (i.e., representations of activities as outlined in 1 above) as well as guidelines and support (i.e., mechanisms for scaffolding the design process as outline in 2 above). The chapter argues that this approach to learning design, which centres on the concept of mediating artefacts and their role in the design process, can be used as a descriptive framework for describing the dynamics, processes, and different aspects involved in learning design.
Impact of creating critical mass classrooms for females

CONTEXT For many years the makeup of Engineering Foundation Year (EFY) student groups at Curtin University has been on the premise of creating diverse groups viz. 1 mature age student, 1-2 international students, and at least two females in a group of 20. In 2016 groups were arranged to achieve a minimum of 7 females in a group where possible. The rationale for the change was based on research that indicates stereotyping and discrimination is minimised in organisations that had achieved 30-35% representation of women (Kanter, 1977 in Hurtado and Ruiz, 2012). Research indicates that numbers matter because it contributes to the perception that women have the ability to succeed in engineering (Creamer, 2012). In addition, extensive “research and evaluation by the STEM education community underscore that building a critical mass matters. ” (Malcom and Malcom-Piqueux, 2013, 178)
Dual-Rail Asynchronous Implementation of a VLSI Processor for Digital Cellular Neural Networks

Abstract An ernulated digital CeUular Neural Network (CNN) Universal Machine chip was designed by a research group of Analogic and Neural Computing Systems Laboratory of HAS, almost 1 O years ag o. During the design period of the chip, particulat attention had to be paid to the docking and control system of the chip, since each architecture e lement, placed on a large silicon area chip (l cm2), operated in a totally synchonous mode, using a single global clock. The designer's manipulations for eliminating the consequences of the too high propagation delay of long interconnections resulted in a relatively large chip, and a significant part of the chip was totally superfluous from the point of view of logical operation. The clock rate was limited at a lower level than it would have been possihle without the long interconnections. So the development of 'CASTLE' CNN processor array showed the most significant problems of the submicron VLSI, which arose from the too long interconnections ofbig size chips. The e limination of clocking problems and the re-designing of the CASTLE architecture using delay-insensitive, self-synchronized, asynchronous logic elemenis were performed. The result of the re-designing work, which is presented in this paper, is a clocldess, totally asynchronous architecture. The combination of the DUAL-RAIL logic and the methods of the well known 4phase asynchronous inter-register communication were chosen. Obviously the tüning and control unit of the synchronous version is um1ecessary in the asynchronous one. So the tasks of re-designing several synchronous uni ts to their dual-rail versions consisted in designing an application specific dualrail aríthmetic unit with feedback and dual-rail multidirection FIFOs. Several new dual rail logic elements were introduced, which were modeled and simulated as follows: • Two-input dual-rail register with a common acknowledge output and priority order for inputs • Twoor more-input dual rail register with independent acknowledge outputs and dual-rail selection inputs • Dual-rail register with CLEAR single-rail control inputs, which enable setting the register into so called DATA-TOKEN and BUBBLE states. The lecture presents the most interesting parts of the design process.
Laboratory Device For Demonstrating Medical Imaging In The Classroom

In this paper, we describe the details of the experimental setup developed with the objective of demonstrating the principles of tomography using visible light. Most tomographic methods use invisible forms of radiation (e.g., x-rays or ultrasound) and therefore it is not very instructive to see them in operation. The proposed setup consists of a translucent object illuminated by a simple white-light source and imaged with the digital camera at different angles. Collimation is provided by using a readily available telecentric lens to perform the imaging. This eliminates the need for a collimated light source, which can increase the cost of the system, and which usually involves hazardous sources such as lasers or laser diodes. By using visible light, students can observe the whole process directly. The students can control the image acquisition parameters and observe the reconstruction process on a computer. In this paper we focus on providing detailed design information so that the experimental setup can be reproduced by interested educators. A separate paper [3] discusses the educational issues relating to the proposed experiment including assessment results.
Final Guidelines and Procedures for Teacher Development Systems: Integrating Technology and Instruction.

This paper examines how technology was used to enhance instruction in schools that are viewed as "promising" in their technology use by individuals in state education agencies. Four elementary, three middle and two high schools from'Arizona, California and Nevada were examined. Extensive document review and telephonl interviews were conducted in preparation for two-person 1to 2-day site visits. Four schools reported that teachers actively used technology in instructional delivery; minimal equipment included a computer, Video Cassette Recorder (VCR) and large video monitor in each classroom for multimedia presentations. A few teachers incorporated online telecommunications into their curriculum and instruction. Students used computers for learning keyboarding or practicing word processing and graphics; students at schools with Internet capacity used it for doing research for class projects. Five schools offered video production opportunities for students. In terms of technology integration, three trends were consistent: (1) using technology in project-based curriculum, (2) concerns with articulation issues between grade levels, and (3) an increased legitimation of "technology as curriculum" at upper-grade levels. Staff training and support depended on technology types, schools' equipment and availability of training personnel, the purposes and manner for which technology was going to be used, and the breadth and level of technology skills already held by the teachers. Schools used two additional strategies to provide support for technology use: access to a variety of technologies and use of technology beyond the school. Contains ten references. (AEF) Southwest Regional Laboratory 4665 L.4cripson Me. Los Alamo. , CA 90720 (310) 59g-7661 U.3 DEPARTMENT OF EDUCATION Office or Educational Research and improvement EDUCATIONAL RESOURCES INFORMATION CENTER ;ERIC/ r ThS document has been reproduces:1 as tece,. 6d Iron) the Person or organization onginatmg it r Minor Changes have been made to improve re0,0Che7bOn Quality Points of wee br opine:Ina Sialee en Ihisdocu merit do not necessaray represem 011.C. al OE Ri position or pohcy Treseen Fleming-McCormick, Glenn F. Nyre, Malma T. Schwager, and Naida C. Tushnet Southwest Regional Laboratory
A model for figure-ground segmentation by self-organized cue integration

The goal of image segmentation is to divide an image into meaningful regions for understanding the image. The major challenge is the absence of a single reliable information source or cue that can provide universal segmentation criteria under all situations. Most segmentation methods concentrate on improving one aspect of the cues, and are only designed for their particular application domains. We believe that such difficulties can be alleviated by cue integration, which shares information from multiple modalities. This dissertation presents an efficient and reliable approach for segmenting coherent objects from video sequences that are taken with a stationary camera. A probabilistic cue integration framework is formulated using a modified Bayes’ rule. The pixels in each frame can decide their distributions between the figure and ground regions by deriving the posterior probabilities from the likelihood models of the bottom-up cues (background subtraction, color, and texture) and the prior probability model of the top-down cue (generalized object representation). These models of the cues provide independent and complementary observations that are subsequently trained by self-adaptation toward the segmentation consensus. The contribution of an individual cue under different situations is adjusted by measuring that cue’s quality based on its similarity with the overall segmentation. Allowing cooperation and competition among the cues at the same time, the system maintains and improves its segmentation results in xv a self-organized manner. Results on various sequences show accuracy and robustness of the system with real time performance. The cue integration model presented in this dissertation unifies bottom-up and top-down cues in a parallel fashion. Each cue corresponds to one or a few Gestalt principles of perceptual organization. Two segmentation systems are compared, where one integrates only the bottom-up cues while the other further incorporates the top-down contribution. The latter system demonstrates greater performance under difficult situations such as abrupt lighting changes. The top-down process allows development of adaptive representations for objects, which can be directly applied to other applications such as object recognition, detection and tracking. With the help of this top-down information, the unified integration system is able to handle ambiguous scenes containing multiple objects with occlusions.
BAYESIAN ANALYSIS FOR SIMULATION INPUT AND OUTPUT

The paper summarizes some important results at the intersection of the fields of Bayesian statistics and stochastic simulation. Two statistical analysis issues for stochastic simulation are discussed in further detail from a Bayesian perspective. First, a review of recent work in input distribution selection is presented. Then, a new Bayesian formulation for the problem of output analysis for a single system is presented. A key feature is analyzing simulation output as a random variable whose parameters are an unknown function of the simulation’s inputs. The distribution of those parameters is inferred from simulation output via Bayesian response-surface methods. A brief summary of Bayesian inference and decision making is included for reference.
Design of a Wireless Sensor Node for Vibration Monitoring of Industrial Machinery

Machine healthy monitoring is a type of maintenance inspection technique by which an operational asset is monitored and the data obtained is analysed to detect signs of degradation, diagnose the causes of faults and thus reducing the maintenance costs. Vibration signals analysis was extensively used for machines fault detection and diagnosis in various industrial applications, as it respond immediately to manifest itself if any change is appeared in the monitored machine. However, recent developments in electronics and computing have opened new horizons in the area of condition monitoring and have shown their practicality in fault detection and diagnosis processes. The main aim of using wireless embedded systems is to allow data analysis to be carried out locally at field level and transmitting the results wirelessly to the base station, which as a result will help to overcome the need for wiring and provides an easy and cost-effective sensing technique to detect faults in machines. So, the main focuses of this research is to design and develop an online condition monitoring system based on wireless embedded technology that can be used to detect and diagnose the most common faults in the transmission systems (gears and bearings) of an industrial robot joints using vibration signal analysis.
Guided filtering for solar image/video processing

A new image enhancement algorithm employing guided filtering is proposed in this work for enhancement of solar images and videos, so that users can easily figure out important fine structures imbedded in the recorded images/movies for solar observation. The proposed algorithm can efficiently remove image noises, including Gaussian and impulse noises. Meanwhile, it can further highlight fibrous structures on/beyond the solar disk. These fibrous structures can clearly demonstrate the progress of solar flare, prominence coronal mass emission, magnetic field, and so on. The experimental results prove that the proposed algorithm gives significant enhancement of visual quality of solar images beyond original input and several classical image enhancement algorithms, thus facilitating easier determination of interesting solar burst activities from recorded images/movies.
Showing Real-time Recommendations to explore the stages of Reflection and action

The majority of Personal Informatics (PI) tools which use Ubiquitous Computing (UbiComp) devices are focused on the collection stage of PI as described by Li et al. [4]. However, tools supporting the reflection and action stages with UbiComp are underexplored. To date, tools for reflection are mostly limited to visualisations of prior performance of an individual, and how to support action is still very much in debate. In this work, we explore how reflection and action might be supported through UbiComp and HCI techniques. We implemented Tip-Me-lens; a prototype designed for exploring and understanding recommendations based on PI data in context. It uses AR tags to differentiate between products; while a mobile device and its camera act as a magic lens which visually overlays digital and real-world browsing. It acts as a futuristic grocery shopping tool that displays recommendations on-the-go as they relate to one’s dietary goals.
Equivalence of Screen Versus Print Reading Comprehension Depends on Task Complexity and Proficiency

ABSTRACT As reading and reading assessment become increasingly implemented on electronic devices, the question arises whether reading on screen is comparable with reading on paper. To examine potential differences, we studied reading processes on different proficiency and complexity levels. Specifically, we used data from the standardization sample of the German reading comprehension test ELFE II (n = 2,807), which assesses reading at word, sentence, and text level with separate speeded subtests. Children from grades 1 to 6 completed either a test version on paper or via computer under time constraints. In general, children in the screen condition worked faster but at the expense of accuracy. This difference was more pronounced for younger children and at the word level. Based on our results, we suggest that remedial education and interventions for younger children using computer-based approaches should likewise foster speed and accuracy in a balanced way.
A New Attempt to Fast Recognition Using 3D Eigenfaces

Face recognition is a very challenging issue and has attracted much attention over the past decades. This paper makes a new attempt to face recognition based on 3D point clouds by constructing 3D eigenfaces. First, a 3D mesh model is built to represent the face shape provided by the point cloud. Then, the principle component analysis (PCA) is used to construct the 3D eigenfaces, which describe each mesh model in a lower-dimensional space. Finally, the nearest neighbor classifier and K-nearest neighbor classifier are utilized for recognition. Experimental results on 3D_RMA, a likely largest 3D face database available currently, show that the proposed algorithm has promising performance with a low computational cost.
User Adaptive Mobile Video Streaming and User Behavior Oriented Video Pre- Fetching In Cloud

With exponential increase in the effective video streaming in mobile network.There is an increasing need for optimizing the quality of video delivery along mobile network. Exist result shows the poor service quality of video streaming over mobile network such long buffering time and interrupt happen in the streaming video. We propose a new mobile video streaming method using cloud. In cloud we use user-Adaptive Mobile Video Streaming (AMoS) and the User Behavior Oriented Video Pre-Fetching (UBoP). We create private agent for video distribution process. It adjusts her streaming and reduces the traffic using SVC.It shows the social interaction between the mobile users. Video quality based on feedback of link quality. Result shows that the cloud can effectively provide the video streaming and video sharing on network. Efficient perfecting video content done in cloud. Prefetching done based on user resolution and bandwidth.