Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing Simple and Advanced Video Tools as Supports for Complex Collaborative Design Processes

Working with digital video technologies, particularly advanced video tools with editing capabilities, offers new prospects for meaningful learning through design. However, it is also possible that the additional complexity of such tools does not advance learning. We compared in an experiment the design processes and learning outcomes of 24 collaborating participant pairs (dyads) using 2 contrasting types of video tools for history learning. The advanced video tool WebDIVER supported segmenting, editing, and annotating capabilities. In the contrasting condition, students used a simple video playback tool with a word processor to perform the same design task. Results indicated that the advanced video editing tool was more effective in relation to (a) fostering student understanding of the topic and acquisition of cognitive skills, (b) the quality of student design products, and (c) the efficiency of dyad interactions. The implication of our experimental findings for constructivist design-based learning is that mediating functions of video tools may be used as cognitive and social supports, for example when students learn by solving design tasks in school.
Digital neural network on a XLINK XC4000

A new digital neural network, consisting of 16 layers with 128 neurons per layer was built. An XLINK XC4005 was used as a processor for the multilayer network of 128-input digital neural gates. The neural gate is functionally similar to that of an analog gate except that its weights are limited to +1, 0 and -1, and the digital inputs are +1 and -1. Using these discrete weight and input values greatly simplify the discrimination function of the gate and hence could be implemented in digital circuits. The gate consists of N-input, N-bit weight vector and a threshold with value equal to K. A digital K-of-N (K/N) neural gate will 'fire' if the number of bits that matches between the input and the weight vector is K or more. The weight vectors and the K threshold values are stored in an EPROM together with their layered connectivity. Depending upon the architecture several gates may be processed simultaneously, like a vector operation. The XLINK XC4005 microprogrammed control unit supervises the processing and sequencing of the instructions. The system is tested to recognized 90 hand printed digits.
Patient-specific epileptic seizure detection in long-term EEG recording in paediatric patients with intractable seizures

The contemporary diagnosis of epileptic seizures is dominated by non-invasive EEG signal analysis and classification. In this paper, we propose a patient-specific seizure detection technique, which selects the optimal feature subsets and trains a dedicated classifier for each patient in order to maximize the classification performance. Our method exploits time domain, frequency domain, time-frequency domain and non-linear feature sets. Then, by using Conditional Mutual Information Maximization (CMIM) as the feature selection method the optimal feature subset is chosen over which the Support Vector Machine is trained as the classifier. In this study, both train and test sets contain 50% of seizure and non-seizure segments of the EEG signal. From the CHB-MIT Scalp benchmark EEG dataset, we used the EEG data from four subjects with overall 21 hours of recording. Support Vector Machine (SVM) with linear kernel is used as the classifier. The experimental results show a delicate classification performance over the test set: i.e., an average of 90.62% sensitivity and 99.32% specificity are acquired when all channels and recordings are used to form a composite feature vector. In addition, an average of 93.78% sensitivity and a specificity of 99.05% are obtained using CMIM.
Bicorrelations and cross‐bicorrelations as non‐linearity tests and tools for exchange rate forecasting

This paper proposes and implements a new methodology for forecasting time series, based on bicorrelations and cross-bicorrelations. It is shown that the forecasting technique arises as a natural extension of, and as a complement to, existing univariate and multivariate non-linearity tests. The formulations are essentially modified autoregressive or vector autoregressive models respectively, which can be estimated using ordinary least squares. The techniques are applied to a set of high-frequency exchange rate returns, and their out-of-sample forecasting performance is compared to that of other time series models. Copyright © 2001 by John Wiley & Sons, Ltd.
Space Charge Effect in Spectrometers of Ion Mobility Increment with Planar Drift Chamber

The effect of space charge on the ion beam in a spectrometer of ion mobility increment with the planar drift chamber has been investigated. A model for the drift of ions under a non-uniform high-frequency electric field1–3 has been developed recently. We have amplified this model by taking space charge effect into account. The ion peak shape taking into consideration the space charge effect is obtained. The output current saturation effect limiting the rise of the ion peak with increasing ion density at the input of the drift chamber of a spectrometer is observed. We show that the saturation effect is caused by the following phenomenon. The maximum possible output ion density exists, depending on the ion type (constant ion mobility, k0) and the time of the motion of ions through the drift chamber. At the same time, the ion density does not depend on the parameters of the drift chamber.
Web Based 3D Visualization and Interaction for Whole Body Laser Scans

1 A web based system that allows the user to select, sort, and measure 3D bodies using displays inside of ordinary web browsers without the use of 3D plug-ins is presented. Our system, AnthroWeb3DMeasure (AW3DM), allows the user to visually explore a set of 3D laser scanned bodies. The bodies we use come from the CAESAR[3] data set, however nothing inherently limits applicability of these techniques to this specific data set. The user is presented with a set of controls, the 3D view of the body, and a tabular view of demographic data associated with each body. We use X3DOM[1] as the basis for the 3D body visualizations. X3DOM is a “declarative 3D” language that enables us to place the graphical elements of the body directly into the DOM (Document Object Model) of the web page itself. This has significant implications for the extensibility and practical usefulness of the system as it is not dependent on arcane plugins and is interoperable among all modern web browsers.
Assessing Student's Mental Representations of Complex Problem Spaces with EEG Technologies

We have developed a neurophysiologic-based assessment of student's understanding of complex problem spaces that blends the population-based advantages of probabilistic performance modeling with the detection of neurophysiologic signals. It is designed to be rapid and effective in complex environments where assessment is often imprecise. Cohorts of novices, and experts encoded chemistry problem spaces by performing a series of online problem solving simulations. The stable memory encoding was verified by comparing their strategies with established probabilistic models of strategic performance. Then, we probed the neural correlates of the encoded problem space by measuring differential EEG signatures that were recorded in response to rapidly presented sequences of chemical reactions that represented different valid or invalid approaches for solving the chemistry problems. We found that experts completed performances in stacks more rapidly than did novices and they also correctly identified a higher percentage of reactions. Event related potentials revealed showed increased positivities in the 100–400 ms following presentation of the image preceding the decision when compared with the other stack images. This neural activity was used to explore reasons why students missed performances in the stack. One situation occurred when students appeared to have a lapse of attention. This was characterized by increased power in the 12–15 Hz range, a decrease in the ERP positivities at 100–400 ms after the final image presentation, and a slower reaction time. A second situation occurred when the students' decisions were almost entirely the reverse of what were expected. These responses were characterized by ERP morphologies similar to those of correct decisions suggesting the student had mistaken one set of chemical reactions for another.
Effect of plasma needle on cultured cells

To investigate a possible application of plasma in fine surgery, we studied the effects of a small atmospheric glow discharge on living cultured cells. The plasma source used for this purpose was the "plasma needle". Plasma needle is a small (below 1mm) non-thermal radio-frequency glow, operating in helium mixtures with air at ambient pressure. Plasma treatment of cultured cells resulted in detachment of the cells. Viability tests using propidium iodide staining in combination with confocal laser scanning microscopy confirmed that detached cells as well as surrounding cells remained alive. When the cells received a low dose of plasma treatment, they reattached within a few hours to the surface of the culture flask and to each other. Removal of cells with high precision, without damage to adjacent cells, promises to become a new surgical technique. For investigation of the mechanism causing this detachment we investigated the gas mixture of the plasma with Raman scattering measurements. Radicals diffusing from the plasma into a liquid were detected by means of fluorescent probe in combination with laser-induced fluorescence spectroscopy.
Evaluation of Parallel Algorithms of Traffic Volume Statistics per Cell in Cellular Network Based on MapReduce Programming Model

Understanding traffic per unit time in cell dimension in cellular data network can be of great help for mobile operators to improve the performance of the cellular data network. It is important for network design and resource optimization. In this paper, we describe three methods to count the traffic per unit time per cell. Moreover, we compare the results of the three methods by the deviation distribution of the traffic and time complexity analysis. Our work is distinguished from other related work by using big data which contains around 1.4 billion records and 20 thousands cells. Generally, we expect this paper could deliver important insights into cellar data network resource optimization.
Experimental results for adaptive sidelobe cancellation techniques applied to an HF array

The authors describe an experimental analysis of adaptive array processing techniques conducted using a 16-element high frequency (HF) array. The results demonstrate the ability of these techniques to cancel both narrow-bandwidth interference and wide-bandwidth noise. The effects of calibration errors and the nonstationary HF channel on beamforming and constrained adaptive processing are discussed. The HF channel will support both beamforming and constrained processing over short time intervals. However, for longer periods robust adaptive array processing techniques may be required. Two robust methods are described, the diagonal loading algorithm and a principal components projection method. It is shown that adaptive array processing algorithms can be used in conjunction with a matched filter to extract a spread-spectrum signal from interference. <<ETX>>
A low-power 12-b analog-to-digital converter with on-chip precision trimming

The design and performance of a 12-b charge redistribution analog-to-digital converter (ADC) is described. The architecture is chosen to minimize power dissipation. Die area is minimized by a modified self-calibration algorithm and nonvolatile memory based on polysilicon fuses. The ADC is fabricated in a 1- mu m CMOS process. It converts at a 200-kHz rate with a power dissipation of 10 mW. >
A New Approach for 3D Edge Extraction by Fusing Point Clouds and Digital Images

Edges are crucial features for object segmentation and classification in both image and point cloud processing. Though many research efforts have been made in edge extraction and enhancement in both areas, their applications are limited respectively owing to their own technical properties. This paper presents a new approach to integrating the edge pixels in the 2D image into boundary data in the 3D point cloud by establishing the mapping relationship between these two types of data to represent the 3D edge features of the object. The 3D edge extraction based on the adoption of Microsoft Kinect as a 3D sensor - involves the following three steps: first, the generation of a range image from the point cloud of the object, second the edge extraction in the range image and edge extraction in the digital image, and finally edge data integration by referring to the correspondence map between point cloud data and image pixels.
Very low rate quasi-optimal convolutional codes for CDMA

The applications of low rate convolutional codes in code division multiple access (CDMA) and high error rate channels is well known. Unfortunately. In searching for optimal long constraint length and very low rate codes the computational effort is prohibitive. In this paper. A method for generating quasi-optimum new very low rate (1/128/spl les/R/spl les/1/3) and moderately long constraint length (K/spl les/14) codes is presented. These codes have the interesting characteristics of being rate compatible and easy to generate. The codes presented in this paper provide superior performances to the known low rate codes of the same rates and constraint lengths. <<ETX>>
Bird information retrieval using fuzzy semantic concepts

This paper describes the bird information retrieval system using the fuzzy semantic concepts. To deal with the uncertainty, fuzzy logic is often used to provide a convenient tool for interfacing linguistic categories with numerical data and for expressing one user's preferences in a gradual and qualitative way. Based on this idea, we can develop a fuzzy semantic query model that formulates a query by using a natural language like process. The proposed system has the capability to deal with problems that are beyond the reach of existing key-word-based techniques as it more of a strategy than a precise methodology in handling uncertainty problems. The key feature of this approach are providing a systematic query process in an environment of impression, uncertainty, and partial truth supporting numerous weighting factors for users to achieve a desired target and developing a friendly interface that is easy for users to form a query.
The Concept of the Modularized Subsystem Performing Mobile Platform Navigation Tasks

Abstract Robotic vehicles autonomy is the subject of many researches performed by various institutions. There is growing tendency to conduct research in the field of autonomous mobile units, unmanned vehicles and robots moving without operator supervision. Authors of this article presents the concept of the modularized subsystem implementing the functionality of the mobile platform navigation in an unknown environment. The concept has been implemented in the real mobile robot.
Mobile cloud service of geo-based image processing functions: a test iPad implementation

The fast-growing technological trends influencing Internet service businesses, cloud computing and mobile platforms are opening new opportunities for implementing and deploying geo-spatial applications. In particular, there are numerous variations or extensions of cloud computing services running on mobile devices. As for the geo-based application services, mobile cloud computing is at an early stage of research and development. The main goal of this study is to present a test case for geo-based image processing functions in the mobile cloud environment. Geo-based image processing algorithms for the mean difference change detection, maximum auto-correlation factor and threshold computation were used as the test case on an iPad in the Amazon web service cloud environment, and the processed results with real data sets are presented in this letter. It is suggested that mobile services with the geo-based image processing functions that fulfil user requirements in a cloud platform can provide opportunities to widen the range of remote-sensing applications.
On-Chip Hybrid Power Supply System for Wireless Sensor Nodes

With the miniaturization of electronic devices, small-size but high-capacity power supply systems appear to be more and more important. A hybrid power source, which consists of a fuel cell (FC) and a rechargeable battery, has the advantages of long lifetime and good load-following capabilities. In this article, we propose the schematic of a hybrid power supply system that can be integrated on a chip compatible with present CMOS processes. For the on-chip, fuel-cell-based hybrid power system in wireless sensor node design, we propose a two steps optimization: (1) dynamic power management (DPM), and (2) adaptive fuel cell optimal power point tracking (AOPPT). Simulation results demonstrate that the on-chip FC-Bat hybrid power system can be used for wireless sensor nodes under different usage scenarios. Our proposed DPM method can achieve 12.9% more energy savings than the method without DPM. Meanwhile, implementing our AOPPT approach can save about 17% energy compared with the fixed architecture for the fuel cell system. For an on-chip power system with 1cm2 area consumption, the wafer-level battery can power a typical sensor node for only about five months, while our on-chip hybrid power system will supply the same sensor node for two years steadily.
Hierarchical computation of image velocity from local phase information

Describes a hierarchical algorithm for the computation of dense displacement fields from a pair of images. The algorithm uses local phase from band-pass filters rather than image brightness to establish a correspondence between the images. The main contribution of this paper is that it describes how to combine orientation and scale specific measurements into a flowfield without ad hoc assumptions. <<ETX>>
Error Performance Measurements on an Experimental 12/14 GHz Satellite Link

This correspondence presents results related to measurmg the error performance of an experimental 12/14 GHz satellite link established between Carleton University, Ottawa, Canada, and NASA Ames Research Center, California, in 1976-1977. The measurements were performed on a 9.6 kbit/s voiceband data channel which supported the continuous synchronous transmission of fixed length frames (composite packets). The results include measurements of packet error rate versus uplink power settings under various atmospheric conditions, densities of packet error-free interval lengths, within-packet error statistics, and propagation delay variations.
People Prefer Less Stress and Fewer Crossings

Human experiments in GraphDrawing, such as the seminal papers of Purchase et al. [1], have concentrated on tasks, such as path-tracing. Here we report the first results in an ongoing series of experiments to investigate the geometric properties of graph drawings that users prefer. The specific experiment described in this poster investigates the impact of edge crossings and stress in straight-line drawings on human preference. Our results suggest a positive preference for drawings with less stress and fewer crossings.
From Simple Metaphors to Conceptual Blending: The Mapping of Analogical Concepts and the Praxis of Translation

I have five goals for this paper. First, I will demonstrate the influence that the understanding of metaphor has had on the praxis of translation. Second, I will introduce and apply more recent insights in human conceptual processes, in particular those of image-schemas, conceptual metaphors and conceptual blends. Third, I will introduce optimality principles and relate them to the suggested conceptual blends. Fourth, I will present some translations of conceptual blends and then suggest optimality principles for translating conceptual blends and evaluate the translations by them. Finally, I will suggest areas that require further research. This study is exploratory and suggestive. Hopefully, readers will wish to broaden their understanding of cognitive linguistics and refine what is presented here.
Image fusion using a 3-D wavelet transform

We present a new approach to 3-D image fusion using a 3-D separable wavelet transform. Several known 2-D WT fusion schemes have been extended to handle 3-D images and some new image fusion schemes (i.e. fusion by hard and soft thresholding, composite fusion, fusion of the WT maxima graphs) have been proposed. The goal of this paper is to present the new framework for 3-D image fusion using the wavelet transform, rather than to compare the results of the various fusion rules. Wavelet transform fusion diagrams have been introduced as a convenient tool to visually describe different image fusion schemes. A very important advantage of using 3-D WT image fusion over alternative image fusion algorithms is that it may be combined with other 3-D image processing algorithms working in the wavelet domain, such as 'smooth versus textured' region segmentation, volume compression, where only a small part of all wavelet coefficients are preserved, and volume rendering, where the volume rendering integral is approximated using multiresolution spaces. The integration of 3-D WT image fusion in the broader framework of 3-D WT image processing and visualisation is the ultimate goal of the present study.
Interactive Simulated Patient: Experiences with Collaborative E-Learning in Medicine

Interactive Simulated Patient (ISP) is a computer-based simulation tool designed to provide medical students with the opportunity to practice their clinical problem solving skills. The ISP system allows students to perform most clinical decision-making procedures in a simulated environment, including history taking in natural language, many hundreds of laboratory tests (e.g., images and endoscopy), and physical examination procedures. The system has been evaluated in a number of courses at three universities, Karolinska Institutet and Uppsala University in Sweden, and Stanford University in the United States. This article describes a study conducted in 2002, with an emphasis on results that pertain to collaboration between students. Results indicate that ISP is engaging and stimulates more active student involvement than traditional paper-based case presentation methods and that students seem to collaborate more easily when using ISP compared to traditional paper-based methods.
Low-complexity and error-resilient hyperspectral image compression based on distributed source coding

In this paper we propose a lossless compression algorithm for hyperspectral images based on distributed source coding; this algorithm represents a significant improvement over our prior work on the same topic, and has been developed during a project funded by ESA-ESTEC. In particular, the algorithm achieves good compression performance with very low complexity; moreover, it also features a very good degree of error resilience. These features are obtained taking inspiration from distributed source coding, and particularly employing coset codes and CRC-based decoding. As the CRC can be used to decode blocks using a reference different from that used to compress the image, this yields error resilience. In particular, if a block is lost, decoding using the closest collocated block in the second previous band is successful about 70% of the times.