Miracle-dz/UniFAR-FTUs huggingface dataset:
Five challenges in altmetrics: A toolmaker's perspective

Jean Liu is data curator and blog editor at Altmetric LLP, and Euan Adie is the founder. They can be reached at http://altmetric.com. D riven by the development of new tools for measuring scholarly attention, altmetrics constitute a burgeoning new area of information science. It is an exciting time to be involved in the field since there are so many opportunities to contribute in innovative ways. We develop altmetrics tools and related services at Altmetric LLP, a small London-based start-up founded in 2011 [1]. Like all developers of new altmetrics tools, we frequently encounter challenges in defining what should be measured, accurately collecting attention from disparate sources and making sense of the huge amount of compiled data. We outline five of these challenges in this piece, illustrating them with examples from our experience. It is worth noting that the altmetrics community as a whole comes together regularly to discuss these and other issues, with two open workshops held in 2012 and more planned for the future.
Acoustic transient classification of passive sonar signals by using vector quantization

The automatic classifications of ice-generated transient signals is examined. The classification method is a modified version of one previously used to classify speech sounds and is based on vector quantization. It uses a clustering algorithm on training data to design a signal-specific classification codebook (a set of reference spectra) for each signal type, and it compares an unknown signal event with each of the classification codebooks to make a classification decision. On a test set consisting 7 types of ice-generated signals, a recognition accuracy of 71% was achieved. Details of the experimental conditions and results are given, and recommendations for improving the performance are provided. <<ETX>>
Spectral Clustering Algorithm: MATLAB PCT-Based Parallel Design and Implementation

Spectral clustering algorithms inevitable exist computational time and memory use problems for large-scale spectral clustering, owing to compute-intensive and data-intensive. We analyse the time complexity of constructing similarity matrix, doing eigendecomposition and performing k-means and exploiting SPMD parallel structure supported by MATLAB Parallel Computing Toolbox (PCT) to decrease eigendecomposition computational time. We propose using MATLAB Distributed Computing Server to parallel construct similarity matrix, whilst using t-nearest neighbors approach to reduce memory use. Ultimately, we present clustering time, clustering quality and clustering accuracy in the experiments.
Hybrid Balancing Technique Using GRSOM and Bootstrap Algorithms for Classifiers with Imbalanced Data

To deal with imbalanced data, this paper proposes a hybrid data balancing technique which incorporates both over and under-sampling approaches. This technique determines how much minority data should be grown as well as how much majority data should be reduced. In this manner, noise introduced to the data due to excessive over-sampling could be avoided. On top of that, the proposed data balancing technique helps to determine the appropriate size of the balanced data and thus computation time required for construction of classifiers would be more efficient. The data balancing technique over samples the minority data through GRSOM method and then under samples the majority data using the bootstrap sampling approach. GRSOM is used in this study because it grows new samples in a non-linear fashion and preserves the original data structure. Performance of the proposed method is tested using four data sets from UCI Machine Learning Repository. Once the data sets are balanced, the committee of classifiers is constructed using these balanced data. The experimental results reveal that our proposed data balancing method provides the best performance.
Ask the Expert: Lung function measurement

1. According to the 2005 American Thoracic Society (ATS)/European Respiratory Society guidelines [1], "the use of a nose-clip or manual occlusion of the nares is recommended. ". This refers to spirometry. Previous guidelines stated that for "dynamic" tests, a nose-clip was not necessary, as there should be little time-delay from maximal inspiration to insertion of the mouthpiece and maximal exhalation to end-expiration; however, in practice, this is not always the case. My opinion is that the use of nose-clips rules out air leak from the nose, which may not be apparent to the operator, and which may cause underestimation of measured values. It also prevents the patient from taking a second inspiration through the nose in the middle of a test, and thus giving inaccurate forced vital capacity (FVC) values. Some of my colleagues who routinely test children often make a game of the child holding their own nose while doing the test, and so it becomes more fun than uncomfortable hospital rules! This can be done, provided the child keeps his elbows at his side and not raised; alternatively, ask a parent to do it. I think the advantages outweigh the disadvantages.
An adaptive hybrid coding scheme for HDTV and digital video sequences

In this paper, the image sequences are decomposed into seven sub-bands in the spatial domain using GQMF filters. Then, the base-band is interframe encoded using a simple 3-D block-matching method and LADVQ search algorithm. This band is used to decide the codebooks and the blocks sizes for encoding the high frequency bands. To reduce the complexity, the high-bands are encoded using the LAVQ. The simulation results show that good quality pictures can be obtained at a bit rate as low as 0.290 bpp (about 15 Mbits/sec). This rate will facilitate the transmission of three HDTV channels via a DS3 rated 45 Mbits/sec channel. This algorithm is tested on digital video sequences. We obtain high quality reconstructed images at an average bit rate of 0.460 bpp with PSNR of 35.04 dB. >
Experimental comparison between Hybrid-QPSK/8QAM and 4D-32SP-16QAM formats at 31.2 GBaud using Nyquist pulse shaping

We report on the performance comparison between two modulation formats carrying each 2.5 bits per transmitted 2D-symbol. Using Nyquist pulse shaping and a 33-GHz spacing grid, we show that the 4D-32SP-16QAM format outperforms the Hybrid-QPSK/8QAM format over a transmission link made of standard single mode fiber.
Grain boundaries in nanocrystalline catalytic materials as a source of surface chemical functionality

Abstract This review considers for the first time the effects in heterogeneous catalysis of grain boundaries (GB) created as a result of consolidation of catalytic materials nanoparticles without their sintering. Different methods proposed for quantitative characterization of nanoparticles consolidation extent were considered together with theoretical basis for increasing of catalytic activity at the GB surface areas between consolidated nanocrystals of metals and metal oxides. The review systemizes the GB effects observed in different areas of heterogeneous catalysis implementing metallic and oxide catalysts with acidic, basic, and redox surface functionality. The review analyzed experimental data that demonstrated the fine details of the structure of GB’s. Their contribution to improving the performance of catalytic materials should be accounted for in development of novel catalysts and deeper understanding of catalysts functioning.
Functional MRI activation maps from empirically defined curve fitting

Online MRI software for clinical functional magnetic resonance imaging (fMRI) testing is currently limited to a simple t-test method. Here we evaluate a repeated block design general linear model (GLM) method of analysis, BOLDfold, that is simple and robust enough to be used directly on a clinical MRI without the need for off-line processing. Six subjects performed block design touch and overt speech tasks while being continuously imaged with an echo planar imaging sequence. The time series images were analyzed for hemodynamic activity using BOLDfold and a two condition (test/control) t test for both motion corrected (aligned) and uncorrected data. Less false positive activations were found using BOLDfold over the t test for corrected and uncorrected data. The number of false activations caused by head motion in the BOLDfold maps was low enough, even with overt speech acquisition, that motion correction would not normally be necessary. BOLDfold has several advantages over the t test that would allow it to be used for routine clinical fMRI exams with little or no off-line data processing. These advantages are (1) a robustness to head motion artifact that reduces or eliminates the need to align images before analysis, (2) activation time series that can easily be interpreted by eye to confirm the map computations for individual patients, and (3) no a priori assumptions about the hemodynamic response is made. © 2005 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 24B: 46–55, 2005
Channel equalization and cross-talk cancellation for high density optical recording

This paper deals with channel equalization and cross talk cancellation for high density optical recording. The performance of both linear and decision feedback adaptive equalization is evaluated. Maximum likelihood sequence estimation is also considered. To cope with interference from adjacent tracks, an algorithm for cross talk cancellation based on a three spot detection system is analyzed.
Distributed Kalman filtering: a bibliographic review

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this study, a bibliographical review on distributed Kalman filtering (DKF) is provided. The study contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area.
Aromaticity in Polyacenes and Their Structural Analogues

The successful synthesis of different polyacenes including theoretical assessment on the stability of larger acenes are dis- cussed. The existence of favorable aromaticity criterion in polyacenes is understood in terms of different aromaticity indicators like nu- cleus independent chemical shift (NICS), harmonic oscillator model of aromaticity (HOMA), bond resonance energy (BRE). Clar's � - sextet rule is also very much effective in explaining their aromaticity. By virtue of low HOMO-LUMO gap, the probable application of polyacenes in the field of organic electronics is also highlighted. The polyacene analogues of inorganic ring compounds, viz., BN-acenes, CN-acenes, BO-acenes, BS-acenes, AlN-acenes and of alkali ring compounds, viz., Na-acenes and K-acenes also have polyacene-like aromaticity although in few cases the origin of aromaticity and qualitative nature of aromaticity differ significantly.
Research of Tree Modeling and Rendering in Virtual Reality

In the field of virtual reality, tree modeling and rendering technique is a hotspot. This paper summarizes the current basic methods of tree modeling and rendering. At first, we present basic principles of making tree models, then show the two methods of tree modeling and rendering used in game scenes in virtual reality. One is the tree modeling technique based on 3Dmax, the other is the tree rendering technique based on OpenGL. At last we give the application examples of these two methods and compare the two methods in navigation system project.
Direct conversion using lowpass sigma-delta modulation

A method for quadrature demodulation by subsampling with sigma-delta analog-to-digital converters is discussed, and a correlator receiver structure based on this method is described. The almost completely digital demodulator structure is based on second-order sampling and sigma-delta analog-to-digital converters. A theoretical performance analysis is presented, and a measurement system for the method is described. The proposed structure can be implemented on a single integrated circuit. <<ETX>>
Trap avoidance and protection schemes in networks with shared risk link groups

Shared risk link group (SRLG) has been widely recognized as an important concept in survivable optical networks. However, there are still several SRLG-related problems of both theoretical interest and practical importance that have not been explored fully. Specifically, there are two major issues that are still open: avoiding failures in path determination caused by "traps" and maximizing bandwidth sharing. These issues are more challenging when considering shared path protection in networks with SRLGs. In this paper, we address the above two open issues, starting with a heuristic approach to avoiding traps. In networks with SRLGs, a simple heuristic may run into traps up to 30% of the time. Integer linear programming (ILP)-based approaches, on the other hand, are not feasible for large SRLG networks. One of the widely used heuristics for trap avoidance is based on K shortest paths (KSP). As an alternative to KSP, we propose an innovative trap avoidance (TA) heuristic that requires much less running time than KSP (and ILP) and yet can effectively avoid almost all the avoidable traps as an ILP-based approach. We also propose an efficient shared SRLG protection scheme based on TA that can achieve a bandwidth efficiency that is nearly as high as other schemes based on ILP or KSP.
BellBot - A Hotel Assistant System Using Mobile Robots

There is a growing interest in applying intelligent technologies to assistant robots. These robots should have a number of characteristics such as autonomy, easy reconfiguration, robust perception systems and they should be oriented towards close interaction with humans. In this paper we present an automatic hotel assistant system based on a series of mobile platforms that interact with guests and service personnel to help them in different tasks. These tasks include bringing small items to customers, showing them different points of interest in the hotel, accompanying the guests to their rooms and providing them with general information. Each robot can also autonomously handle some daily scheduled tasks. Apart from user-initiated and scheduled tasks, the robots can also perform tasks based on events triggered by the building's automation system (BAS). The robots and the BAS are connected to a central server via a local area network. The system was developed with the Robotics Integrated Development Environment (RIDE) and was tested intensively in different environments.
The worst case cell arrival patterns that conform to the GCRA in ATM networks

The asynchronous transfer mode (ATM) is well known technology for implementing broadband integrated services digital networks. A major issue in ATM technology is traffic control. We introduce the concepts of conservative cell loss ratio (CLR) estimation and worst case cell arrival patterns, and apply them to cell arrival patterns that conform to the generic cell rate algorithm (GCRA). We define new sets of cell arrival patterns which contain the worst case cell arrival patterns for compliant cell arrival patterns. Based on these sets, we propose a connection admission control method. A numerical example demonstrates its effectiveness.
Design of MAHA Supercomputing System for Human Genome Analysis

During the past decade, many changes and attempts have been tried and are continued developing new technologies in the computing area. The brick wall in computing area, especially power wall, changes computing paradigm from computing hardwares including processor and system architecture to programming environment and application usage. The high performance computing (HPC) area, especially, has been experienced catastrophic changes, and it is now considered as a key to the national competitiveness. In the late 2000`s, many leading countries rushed to develop Exascale supercomputing systems, and as a results tens of PetaFLOPS system are prevalent now. In Korea, ICT is well developed and Korea is considered as a one of leading countries in the world, but not for supercomputing area. In this paper, we describe architecture design of MAHA supercomputing system which is aimed to develop 300 TeraFLOPS system for bio-informatics applications like human genome analysis and protein-protein docking. MAHA supercomputing system is consists of four major parts - computing hardware, file system, system software and bio-applications. MAHA supercomputing system is designed to utilize heterogeneous computing accelerators (co-processors like GPGPUs and MICs) to get more performance/$, performance/area, and performance/power. To provide high speed data movement and large capacity, MAHA file system is designed to have asymmetric cluster architecture, and consists of metadata server, data server, and client file system on top of SSD and MAID storage servers. MAHA system softwares are designed to provide user-friendliness and easy-to-use based on integrated system management component - like Bio Workflow management, Integrated Cluster management and Heterogeneous Resource management. MAHA supercomputing system was first installed in Dec., 2011. The theoretical performance of MAHA system was 50 TeraFLOPS and measured performance of 30.3 TeraFLOPS with 32 computing nodes. MAHA system will be upgraded to have 100 TeraFLOPS performance at Jan., 2013.
Satellite Image Segmentation based on YCbCr Color Space

Segmentation is one of the most important processes in the satellite image processing to retrieve most useful information from the satellite images. This paper proposed an effective fuzzy based method of segmentation of satellite images in YCbCr color space. The YCbCr Color space represents color as intensity and exploits the characteristics of human eye. Our eye is more sensitive to intensity than hue. The intensity component can be stored with greater accuracy as the amount of information to be minimized. The JPEG file format mostly uses this color space to discard the unwanted or unimportant information. In the proposed approach, the satellite image in RGB color space is transform into YCbCr color space and then the transformed satellite image is split into three different components (channels or images) based on luminance and chrominance. Subsequently Fuzzy based segmentation is applied separately for all three components for efficient segmentation. Finally the threshold is applied to extract the foreground (object) from the background. The experimental result reveals that the proposed fuzzy based segmentation method is efficient and accurate for extracting the necessary information from the satellite images.
Automatic control of camera pan, zoom and focus for improving object recognition

In this paper we consider the use of the GETAFIX robot vision head for object recognition by automatic active panning, zooming and focussing. It is shown that given appropriate areas of interest (which may be defined by motion, change detection or colour segmentation) the sensor can be driven to isolate these regions. Subsequent processing is made more reliable in this process. The effective signal to noise ratio of the data is increased by the process and many features which were unreliably detected by passive techniques can be reliably and accurately acquired by the active approach. Experiments are demonstrated for the case of detecting cylindrical 3D objects in table-top scenes.
Proceedings of the First International Workshop on Aliasing, Confinement and Ownership in Object-oriented Programming (IWACO)

This paper describes an efficient technique for supporting safe runtime downcasts in a system with ownership types. This technique uses the type passing approach, but avoids the associated significant space overhead by storing only the runtime ownership information that is potentially needed to support safe downcasts. Moreover, this technique does not use any inter-procedural analysis, so it preserves the separate compilation model of Java. We implemented our technique in the context of Safe Concurrent Java, which is an extension to Java that uses ownership types to statically guarantee the absence of data races and deadlocks. Our approach is JVM-compatible: our implementation translates programs to bytecodes that can be run on regular JVMs.
Macro Segmentation and Content Analysis of TV Broadcast Stream

This study addresses a non-supervised approach to extract TV programs via repetition based detection of the Inter-Programs (IPs) and audio based segmentation and classification algorithm to analyze the massive raw TV stream. Acoustic and visual information are both adopted for IPs detection so as to avoid missing true-positive. Novel audio fingerprints scheme and shot based indexing algorithm are introduced to guarantee the efficient and superior detection performance. After the TV programs are further segmented into clips, Gaussian Mixture Models (GMMs) are used to classify the clips into three types, namely, pure speech, non-pure speech, and non-speech. Experiments on a test dataset composed of more than 500 hours content-unknown TV streams show that the F-measure of the programs extraction and content analysis achieve 0.986 and 0.887 respectively. The experiments also demonstrate that the proposed algorithm for detecting repeated IPs outperforms the state-of-art approach.
Sulfonic Acid Based Cation-Exchange Resin: A Novel Proton Source for One-Pot Diazotization—Iodination of Aromatic Amines in Water.

One-Pot Diazotization–Iodination of Aromatic Amines in Water V ct r D. Filimonov,*a Nadya I. Semenischeva,a Elena A. Krasnokutskaya,a Alexei N. Tretyakov,a Ho Yun Hwang,b Ki-Whan Chi*b a Department of Organic Chemistry, Tomsk Polytechnic University, 634050 Tomsk, Russia Fax +7(3822)563637; E-mail: filimonov@tpu.ru b Department of Chemistry, University of Ulsan, 680-749 Ulsan, Republic of Korea E-mail: kwchi@ulsan.ac. kr Received 14 September 2007; revised 19 October 2007
Applying Item-based and User-based collaborative filtering on the Netflix data

The GroupLens research lab introduced Item-Based collaborative filtering [3] as an approach for providing personalised recommendations superior to User-based collaborative filtering. User-based collaborative filtering [5] gives personalised recommendations by finding similiar users. Item-Based collaborative filtering recommends similiar items. Both approaches have been compared [3]. However, the applied testing procedure did not employ equal conditions for both approaches. The aim of this report is to give an evaluation on both approaches by employing a fair testing procedure on data provided by Netflix [2]. Test results and their dependency to the employed algorithms are interpreted.
A study of the 1997 forest fires in south east Asia using SPOT quicklook mosaics

The ground station at the Centre for Remote Imaging, Sensing and Processing (CRISP), Singapore has acquired numerous SPOT images of the region during the 1997 forest fire episode in South Asia with almost complete coverage of Sumatra and Borneo. Mosaics of the SPOT quicklook images have been generated to provide a synoptic view of the areal extent of the fires affected areas. The total area of burnt scars was estimated to be 1.50/spl times/10/sup 6/ ha in Sumatra and 3.06/spl times/10/sup 6/ ha in Kalimantan.