Miracle-dz/UniFAR-FTUs huggingface dataset:
Space-time coding and signal processing for high data rate wireless communications

The information capacity of wireless communication systems can be increased dramatically by employingmultiple transmit and receive antennas [? , ? ]. An effective approach to increasing data rate over wireless channels is to employ coding techniques appropriate to multiple transmit antennas, that is space-time coding. Space-time codes introduce temporal and spatial correlation into signals transmitted from different antennas, in order to provide diversity at the receiver, and coding gain over an uncoded system. The spatial-temporal structure of these codes can be exploited to further increase the capacity of wireless systems with a relatively simple receiver structure. This chapter provides an overview of space-time coding techniques and the associated signal processing framework.
R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections

The influence of Deep Learning on image identification and natural language processing has attracted enormous attention globally. The convolution neural network that can learn without prior extraction of features fits well in response to the rapid iteration of Android malware. The traditional solution for detecting Android malware requires continuous learning through pre-extracted features to maintain high performance of identifying the malware. In order to reduce the manpower of feature engineering prior to the condition of not to extract pre-selected features, we have developed a coloR-inspired convolutional neuRal networks (CNN)-based AndroiD malware Detection (R2-D2) system. The system can convert the bytecode of classes.dex from Android archive file to rgb color code and store it as a color image with fixed size. The color image is input to the convolutional neural network for automatic feature extraction and training. The data was collected from Jan. 2017 to Aug 2017. During the period of time, we have collected approximately 2 million of benign and malicious Android apps for our experiments with the help from our research partner Leopard Mobile Inc. Our experiment results demonstrate that the proposed system has accurate security analysis on contracts. Furthermore, we keep our research results and experiment materials on http://R2D2.TWMAN. ORG.
A Framework for Semantic Interoperability over the Cloud

Semantic Interoperability is one of the most important open challenges in the Knowledge Management field. In this work, we propose a framework for making easier information exchanging operations among heterogeneous information sources, over the Cloud. Exploiting the Semantic Web technologies, the framework has the objective of allowing semantic interoperability among distributed software agents preserving not only semantics of transmitted messages, but also the subjectivity of agent's world vision in the communication process. The proposed system, in fact, will help users in the digital documents exchanging activities by extracting the related relevant information and coding their informative contents in a shape capable of preserving the original semantics, also in the case of communications agents using different or incompatible vocabularies. The framework is a an evolution of semantic interoperable methodologies towards cloud computer technologies, thus guaranteeing several advantages in terms of usability, scalability and fault tolerance. In particular, we implemented a prototype that provides interoperability functionalities in the E-Health domain, managing information coming from heterogeneous sources.
A combined solution for the Internet access denial caused by malicious Internet service providers

The Internet is becoming a vital communication tool for individuals, businesses, and governments. Thus, the Internet access reliability is crucial especially against malicious behaviors. When a malicious higher-tier Internet service provider filters transit traffic for the purpose of dropping a specific network's packets, then an Internet access denial occurs. This paper presents a solution for the denial of the Internet access problem that combines a network address translation based solution with a tunnel-based solution. The network address translation based solution is efficient in terms of network performance but suffers from a server reachability problem; a problem that is solved by using a tunnel-based solution. Moreover, the paper evaluates the combined solution performance with respect to the end-to-end delay and the throughput metrics. The combined solution has insignificant effect on these two metrics when traffic originates from the denied network and is forwarded outside the denied network. In contrast, and dependent on the tunneling protocol used, the combined solution increases the end-to-end delay of the network by at least 6% and decreases the throughput of the traffic by at least 1.65% when the traffic is originated outside the denied network and is intended for servers inside the denied network. Copyright © 2013 John Wiley & Sons, Ltd.
WHEN BIGGER IS NOT BETTER: FAMILY SIZE, PARENTAL RESOURCES, AND CHILDREN'S EDUCATIONAL PERFORMANCE*

Although the inverse relationship between the number of siblings and childrens educational performance has been well established explanations for this relationship remain primitive. One explanation resource dilution posits that parents have finite levels of resources (time energy money etc.) and that these resources are diluted among children as sibship size increases. I provide a more rigorous investigation of the dilution model than previous studies testing its implications with a sample of 24599 eighth graders from the 1988 [U.S.] National Education Longitudinal Study. My analyses support the resource dilution model in three ways. First the availability of parental resources decreases as the number of siblings increases net of controls.Second parental resources explain most or all of the inverse relationship between sibship size and educational outcomes. Finally interactions between sibship size and parental resources support the dilution model as children benefit less from certain parental resources when they have many versus few siblings. (EXCERPT)
SPIRS: A Framework for Content-based Image Retrieval from Large Biomedical Databases

With the increasing use of medical images in clinical medicine, disease research, and education, the need for methods that effectively archive, query, and retrieve these images by their content is underscored. This paper presents the implementation of a Web-based retrieval system called SPIRS (Spine Pathology & Image Retrieval System) at the U. S. National Library of Medicine that demonstrates recent developments in shape representation and retrieval from a large dataset of 17,000 digitized x-ray images of the spine and associated text records. Users can search these images by providing a sketch of the vertebral outline or selecting an example vertebral image and some relevant text parameters. Pertinent pathology on the image/sketch can be annotated and weighted to indicate importance. This hybrid text-image query yields images containing similar vertebrae along with relevant fields from associated text records, which allows users to examine the pathologies of vertebral abnormalities. Initial experiments with SPIRS have demonstrated the potential for this system, particularly on a large dataset of clinical images.
An Iterative Approach for the Process-level Composition of Web Services

Web service composition is one of the most promising and challenging ideas underlying service oriented applications, particularly in case that the components are themselves structured business processes specified in languages such as WS-BPEL. The manual development of the new composite service is a time consuming and error prone task since it must be driven by the analysis of the interaction protocols of the component services. The automated generation of the composition, on the other side, requires the specification of complex requirements that have to capture all the relevant aspects of the composition. In this paper we propose an iterative semi-automated development process for web service composition which dramatically reduces the effort for the composition task. The proposed approach automatically generates both the internal executable process (executable WS-BPEL) and its user interface (WSDL and abstract WS-BPEL). The composition process starts from composition requirements that can be easily specified through an intuitive graphical notation, and that can be incrementally refined on the basis of the results of the automated composition.
Online MVDR Beamformer Based on Complex Gaussian Mixture Model With Spatial Prior for Noise Robust ASR

This paper considers acoustic beamforming for noise robust automatic speech recognition. A beamformer attenuates background noise by enhancing sound components coming from a direction specified by a steering vector. Hence, accurate steering vector estimation is paramount for successful noise reduction. Recently, time–frequency masking has been proposed to estimate the steering vectors that are used for a beamformer. In particular, we have developed a new form of this approach, which uses a speech spectral model based on a complex Gaussian mixture model (CGMM) to estimate the time–frequency masks needed for steering vector estimation, and extended the CGMM-based beamformer to an online speech enhancement scenario. Our previous experiments showed that the proposed CGMM-based approach outperforms a recently proposed mask estimator based on a Watson mixture model and the baseline speech enhancement system of the CHiME-3 challenge. This paper provides additional experimental results for our online processing, which achieves performance comparable to that of batch processing with a suitable block-batch size. This online version reduces the CHiME-3 word error rate (WER) on the evaluation set from 8.37% to 8.06%. Moreover, in this paper, we introduce a probabilistic prior distribution for a spatial correlation matrix (a CGMM parameter), which enables more stable steering vector estimation in the presence of interfering speakers. In practice, the performance of the proposed online beamformer degrades with observations that contain only noise or/and interference because of the failure of the CGMM parameter estimation. The introduced spatial prior enables the target speaker's parameter to avoid overfitting to noise or/and interference. Experimental results show that the spatial prior reduces the WER from 38.4% to 29.2% in a conversation recognition task compared with the CGMM-based approach without the prior, and outperforms a conventional online speech enhancement approach.
Inter-Frame Space ( IFS )-based Distributed Fair Queuing for Proportional Fairness in IEEE 802 . 11 WLAN s

In this paper, we study fair queuing in the IEEE 802.11 Distributed Coordination Function (DCF). We propose an IFS-based Distributed Fair Queuing (IDFQ) mechanism to provide proportional fairness service for IEEE 802.11 WLANs. IDFQ is designed to emulate Self-Clocked Fair Queuing (SCFQ) in a distributed manner. It eliminates the backoff process as implemented in existing work and introduces a new mechanism to assign the inter-frame space to each station. IDFQ is immune from the implementation problem suffered by existing IFS-based mechanisms and is adaptive to the collision state in the system. Moreover, it can be used to eliminate the performance anomaly problem with 802.11 MAC. The performance of IDFQ is validated by ns -2 simulations. Simulation results show that IDFQ supports fairness service for flows in proportion to their weights, and outperforms existing mechanisms in terms of fairness and stability, rendering IDFQ an excellent candidate to provide weighted fairness in IEEE 802.11 WLANs .
Digital Shape Reconstruction of Vocal Tracts from MRI Images

We present a method for computing surface models from MRI images with specific design for vocal tract extraction. As the vocal tract consists of empty space with connection to the outside, it is difficult to segment with common methods based on consideration of intensity differences. In the proposed method, surfaces are extracted via three steps. First, void voxels in an image of a human head are extracted using a morphological closing operator. Then, the significant and unnecessary noise contained in the results is removed via connected-component labeling. Finally, a vocal tract mesh is formed by applying the Marching Cubes algorithm in the extracted region and used to provide masked images. As the method does not require user input, it is efficient for batch processing.
Dialogical action research: a case study

Action Research (AR) originated from the work of Kurt Lewin during the 1940s and has been summarised as an approach that “combines theory and practice (and researchers and practitioners) through change and reflection in an immediate problematic situation within a mutually acceptable ethical framework” (Avison et al., 1999 p 94). The application of AR has not been without controversy particularly in debates with positivist science on the justification and generation of knowledge. These arguments were addressed by Susman & Evered (1978) in their influential description of AR as consisting of a cyclical process involving five phases: diagnosing, action planning, action taking, evaluating, and specifying learning. The focus of AR is to address real-life problems through intervention together with the research objective of making a contribution to knowledge. Coghlan and Brannick (2005 p 125) emphasise the importance of the social and academic context in which action research is carried out. Dick (1993) , an academic working in the field of psychology, proposes that the AR methodology has the twofold aim of action and research: • action designed to bring about change in some community, organization or program • research to increase understanding on the part of the researcher or the client, or both – and in many cases some wider community Reason and Bradbury aim to “draw together some of the main threads that form the diverse practices of action research” and propose an almost lofty vision of AR contributing to the world’s wellbeing and sustainability; in areas ranging from the economic and political to the psychological and spiritual. The following quotation with its emphasis on understanding and reflection is of particular relevance to this study (Reason & Bradbury, 2001 p 2).
A novel application of the unscented transformation to the debiased CMKF

This paper presents a modification to the original debiased converted-measurement Kalman filter (CMKF), a modern estimation algorithm used for long-range radar and sonar target tracking [1], [2]. The modification improves the original debiased CMKF by approximating the Cartesian-prediction-conditioned means of the converted-measurement error's true bias and covariance using a novel application of the unscented transformation (UT) [3]. Simulations show the improved performance of the modified debiased CMKF over that of the original debiased CMKF.
PRICE: Power reduction by placement and clock-network co-synthesis for pulsed-latch designs

Pulsed latches have emerged as a popular technique to reduce the power consumption and delay for clock networks. However, the current physical synthesis flow for pulsed latches still performs circuit placement and clock-network synthesis separately, which limits achievable power reduction. This paper presents the first work in the literature to perform placement and clock-network co-synthesis for pulsed-latch designs. With the interplay between placement and clock-network synthesis, the clock-network power and timing can be optimized simultaneously. Novel progressive network forces are introduced to globally guide the placer for iterative improvements, while the clock-network synthesizer makes use of updated latch locations to optimize power and timing locally. Experimental results show that our framework can substantially minimize power consumption and improve timing slacks, compared to existing synthesis flows.
SHORT MARITAL ADJUSTMENT AND PREDICTION TESTS: THEIR RELIABILITY AND VALIDITY

justment and prediction have used a very large number of items. The length of these tests is their main disadvantage. The Burgess-Wallin Marital-Success Schedule contains 892 numbered items, but several of these have multiple subitems.3 Counting the multiple subitems, it requires answers to a possible maximum of 246 questions.4 Enumerating items on this basis, the Terman Happiness Test contains 75 items;5 the modified Terman-Oden test contains 103 items.6 The Locke Marital-
A receiver scheme for the dual PN-MC padding OFDM in doubly selective channels

The inter-carrier interference (ICI) of an OFDM system introduced by the time selectiveness of a multi-path channel degrades the system performance, especially for those with high-order constellations which is often used in HDTV broadcasting. In this paper, we propose the algorithm to combat such ICI for the OFDM structure with dual PN-MC padding defined in DTMB-A. Based on the dual PN-MC structure and the assumption that within an OFDM symbol, the variation of each channel tap is approximately linear, an approach to reconstruct the circular convolution and mitigate the ICI with a low complexity, is described. The simulation shows a good performance under Rician fading channels with the bandwidth efficiency at 5 bits/s/Hz.
Integrative workplace: studying the effect of digital desks on users' working practices

Digitally augmented workspaces have been extensively researched in the last two decades. However, no studies exist which compare the work at digital desks with the work at normal desks to examine how digital desks might change knowledge work practices and its outcomes. This paper reports our work on the design and implementation of Integrative Workplace, a digital desk to support legal work. The prototype allows the user to search and excerpt content from digital and printed documents. In contrast to related works, the system enables parallel interaction with multiple paper documents spread on an entire desk. We identified five key requirements to develop the system and tested it in a pre-study. The study revealed a system usability between ok and good having an average SUS score of 66.94. In future work, we want to conduct a compa-rative study to research the effect of digital desks on users' working practices in the domain of legal work.
A New Sampling Technique for Tensors

In this paper we propose new techniques to sample arbitrary third-order tensors, with an objective of speeding up tensor algorithms that have recently gained popularity in machine learning. Our main contribution is a new way to select, in a biased random way, only $O(n^{1.5}/\epsilon^2)$ of the possible $n^3$ elements while still achieving each of the three goals: \\ {\em (a) tensor sparsification}: for a tensor that has to be formed from arbitrary samples, compute very few elements to get a good spectral approximation, and for arbitrary orthogonal tensors {\em (b) tensor completion:} recover an exactly low-rank tensor from a small number of samples via alternating least squares, or {\em (c) tensor factorization:} approximating factors of a low-rank tensor corrupted by noise. \\ Our sampling can be used along with existing tensor-based algorithms to speed them up, removing the computational bottleneck in these methods.
Comparative Population Genomics of the Borrelia burgdorferi Species Complex Reveals High Degree of Genetic Isolation among Species and Underscores Benefits and Constraints to Studying Intra-Specific Epidemiological Processes

Lyme borreliosis, one of the most frequently contracted zoonotic diseases in the Northern Hemisphere, is caused by bacteria belonging to different genetic groups within the Borrelia burgdorferi species complex, which are transmitted by ticks among various wildlife reservoirs, such as small mammals and birds. These features make the Borrelia burgdorferi species complex an attractive biological model that can be used to study the diversification and the epidemiology of endemic bacterial pathogens. We investigated the potential of population genomic approaches to study these processes. Sixty-three strains belonging to three species within the Borrelia burgdorferi complex were isolated from questing ticks in Alsace (France), a region where Lyme disease is highly endemic. We first aimed to characterize the degree of genetic isolation among the species sampled. Phylogenetic and coalescent-based analyses revealed clear delineations: there was a ∼50 fold difference between intra-specific and inter-specific recombination rates. We then investigated whether the population genomic data contained information of epidemiological relevance. In phylogenies inferred using most of the genome, conspecific strains did not cluster in clades. These results raise questions about the relevance of different strategies when investigating pathogen epidemiology. For instance, here, both classical analytic approaches and phylodynamic simulations suggested that population sizes and migration rates were higher in B. garinii populations, which are normally associated with birds, than in B. burgdorferi s.s. populations. The phylogenetic analyses of the infection-related ospC gene and its flanking region provided additional support for this finding. Traces of recombination among the B. burgdorferi s.s. lineages and lineages associated with small mammals were found, suggesting that they shared the same hosts. Altogether, these results provide baseline evidence that can be used to formulate hypotheses regarding the host range of B. burgdorferi lineages based on population genomic data.
A Protein Encoded by the Bovine Herpesvirus 1 Latency-Related Gene Interacts with Specific Cellular Regulatory Proteins, Including CCAAT Enhancer Binding Protein Alpha

ABSTRACT Following acute infection, bovine herpesvirus 1 establishes latency in sensory neurons of trigeminal ganglia (TG). Reactivation from latency occurs periodically, resulting in the shedding of infectious virus. The latency-related (LR) RNA is abundantly expressed in TG of latently infected calves, and the expression of LR proteins is necessary for dexamethasone-induced reactivation from latency. Previously published studies also identified an alternatively spliced LR transcript which is abundantly expressed in TG at 7 days after infection and has the potential to encode a novel LR fusion protein. Seven days after infection is when extensive viral gene expression is extinguished in TG and latency is established, suggesting that LR gene products influence the establishment of latency. In this study, we used a bacterial two-hybrid assay to identify cellular proteins that interact with the novel LR fusion protein. The LR fusion protein interacts with two proteins that can induce apoptosis (Bid and Cdc42) and with CCAAT enhancer binding protein alpha (C/EBP-α). Additional studies confirmed that the LR fusion protein interacts with human or insect C/EBP-α. C/EBP-α protein expression is induced in TG neurons of infected calves and after dexamethasone-induced reactivation from latency. Wild-type C/EBP-α, but not a DNA binding mutant of C/EBP-α, enhances plaque formation in bovine cells. We hypothesize that interactions between the LR fusion protein and C/EBP-α promote the establishment of latency.