Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum sensing in cognitive radio

Spectrum sensing is an essential part for cognitive radio which is used for directly or indirectly estimating the states of primary users (PUs) to find spectrum holes for second users (SUs). Nowadays, some online spectrum sensing algorithms have been proposed but most of them ignore the time complexity which influences the efficiency of spectrum sensing. In this paper we propose a new filter algorithm named Mixed filter to address this problem. Leveraged by the Hidden Markov model, this algorithm provides an alternative way to estimate parameters of the model online. Extensive simulations have been conducted and the simulation results show that the proposed method can reduce the computational complexity and shorten the executing time withoug out reducing the accuracy. Introduction In physical level spectrum sensing, the condition of spectrum cannot be detected directly. Thus, transforming the problem into estimating the states of primary users (PUs) or channel state are the solutions. However, observation data is not the real state of PUs, and the primary users need a series of measures to evaluate the true condition. The paper mainly researches the algorithm in mathematical way. Existing solutions can be classified into off-line and online modes. Off-line scenarios based on batch inference process download data (after gathered) to infer target component. In [1], Olusegun Peter Awe provides the robust blind spectrum sensing technique which is used in multi-antenna cognitive radio networks. This technique is based on the Variational Bayesian learning only on off-line circumstances. [2] employs the Viterbi algorithm in Hidden Markov model. But on-line ways prefer to make the update step continuously during the data entry providing real-time results. The [3] proposes the maximum likelihood and Bayesian inference to estimate the channel-usage patterns online for determining the presence/absence of PUs. And a parallel algorithm [4] was used as the recursive estimation of sparse signal to estimate all elements with closed-form expression. A variant of the Baum-Welch algorithm are used in non-stationary model to estimate the parameters [5]. [6] employs sequential Monte Carlo technique with sufficient statistics to estimate the transition matrix of the model. However, these algorithms do not consider the influence of time complexity during the process of sensing, which will lead to inefficient communication performance on the higher layer protocol, e.g., the transport layer, as TCP is very sensitive to the end to end delay [7-9]. The paper brings up the alternative technique of Mixed filter to adapt to 164 Advances in Computer Science Research (ACRS), volume 54 International Conference on Computer Networks and Communication Technology (CNCT2016)
SCRIPT: A framework for Scalable Real-time IP Flow Record Analysis

Analysis of IP traffic is highly important, since it determines the starting point of many network management operations, such as intrusion detection, network planning, network monitoring, or accounting and billing. One of the most utilized metering data formats in analysis applications are IP (Internet Protocol) flow records. With the increase of IP traffic, such traffic analysis applications need to cope with a constantly increasing number of flow records. Typically, centralized approaches to IP traffic analysis have scalability problems, which are addressed by replacing existing hardware with more powerful CPUs and faster memory. In contrast, this paper developed and implemented SCRIPT (Scalable Real-time IP Flow Record Analysis), which defines a scalable analysis framework that can be used to distribute flow records to multiple nodes performing traffic analysis in order to balance the overall workload among those nodes. Due to its generic design, the framework developed can be extended and used to distribute other metering data, such as packet headers, payloads, or accounting records.
Accelerated diffusion spectrum imaging with compressed sensing using adaptive dictionaries

Diffusion spectrum imaging offers detailed information on complex distributions of intravoxel fiber orientations at the expense of extremely long imaging times (∼1 h). Recent work by Menzel et al. demonstrated successful recovery of diffusion probability density functions from sub‐Nyquist sampled q‐space by imposing sparsity constraints on the probability density functions under wavelet and total variation transforms. As the performance of compressed sensing reconstruction depends strongly on the level of sparsity in the selected transform space, a dictionary specifically tailored for diffusion probability density functions can yield higher fidelity results. To our knowledge, this work is the first application of adaptive dictionaries in diffusion spectrum imaging, whereby we reduce the scan time of whole brain diffusion spectrum imaging acquisition from 50 to 17 min while retaining high image quality. In vivo experiments were conducted with the 3T Connectome MRI. The root‐mean‐square error of the reconstructed “missing” diffusion images were calculated by comparing them to a gold standard dataset (obtained from acquiring 10 averages of diffusion images in these missing directions). The root‐mean‐square error from the proposed reconstruction method is up to two times lower than that of Menzel et al.'s method and is actually comparable to that of the fully‐sampled 50 minute scan. Comparison of tractography solutions in 18 major white‐matter pathways also indicated good agreement between the fully‐sampled and 3‐fold accelerated reconstructions. Further, we demonstrate that a dictionary trained using probability density functions from a single slice of a particular subject generalizes well to other slices from the same subject, as well as to slices from other subjects. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
Optimized Chamfer Matching for Snake-Based Image Contour Representations

In this paper we present a novel method on how to take advantage of the snake representation of target objects, when doing chamfer matching for detection/recognition purposes. In this case several time-consuming steps of classic chamfer matching approaches can be simplified. Moreover, we investigate the possibility of involving fewer pixels from both the target and template object to speed up computations. We introduce an optimization method for such an object reduction, which is valid also in the general application scheme of chamfer matching. Finally, we present our experimental results regarding human body detection
Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models

DESCRIPTION Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration.
Advances in cancer cytogenetics

As the end of the millenium approaches, recognition of the milestones achieved in the field of cancer cytogenetics is mandatory. With regard to cancer cytogenetics, the turning century can be divided in three main era: the pre‐banding period that has posed important hypothesis and technical premises, the fruitful banding era that led to the discovery of the critical chromosomal rearrangements and cloning of cancer genes and the more recent revolutionizing era of molecular cytogenetics where technological advances permit a global visualization and high‐level resolution of chromosomal alterations. J. Cell. Biochem. Suppls. 32/33:173–182, 1999. © 1999 Wiley‐Liss, Inc.
Discovering clues to avoid middle school failure at early stages

The use of data mining techniques in educational domains helps to find new knowledge about how students learn and how to improve the resources management. Using these techniques for predicting school failure is very useful in order to carry out actions to avoid drop out. With this purpose, we try to determine the earliest stage when the quality of the results allows for clarifying the possibility of school failure. We process real information from a Spanish high school by structuring the whole data in incremental datasets, which represent how students' academic records grow. Our study reveals an early and robust detection of the risky cases of school failure at the end of the first out of four courses.
Spacecraft Multiple Array Communication System Performance Analysis

The Communication Systems Simulation Laboratory (CSSL) at the NASA Johnson Space Center is tasked to perform spacecraft and ground network communication system simulations, design validation, and performance verification. The CSSL has developed simulation tools that model spacecraft communication systems and the space and ground environment in which the tools operate. In this paper, a spacecraft communication system with multiple arrays is simulated. Multiple array combined technique is used to increase the radio frequency coverage and data rate performance. The technique is to achieve phase coherence among the phased arrays to combine the signals at the targeting receiver constructively. There are many technical challenges in spacecraft integration with a high transmit power communication system. The array combining technique can improve the communication system data rate and coverage performances without increasing the system transmit power requirements. Example simulation results indicate significant performance improvement can be achieved with phase coherence implementation.
Repulsive and attractive Casimir forces in a glide-symmetric geometry

We describe a three-dimensional geometry that exhibits a repulsive Casimir force using ordinary metallic materials, as computed via an exact numerical method (no uncontrolled approximations). The geometry consists of a zippelike, glide-symmetric structure formed of interleaved metal brackets attached to parallel plates. Depending on the separation, the perpendicular force between the plates/brackets varies from attractive (large separations) to repulsive (intermediate distances) and back to attractive (close separations), with one point of stable equilibrium in the perpendicular direction. This geometry was motivated by a simple intuition of attractive interactions between surfaces, and so we also consider how a rough proximity force approximation of pairwise attractions compares to the exact calculations.
GT2RDF: Semantic Representation of Genetic Testing Data

Accelerated by the Human Genome Project, genetic testing has become an increasingly integral component in diagnosis, treatment, management, and prevention of numerous diseases and conditions. More than 480 laboratories perform genetic tests for more than 4,600 rare and common medical conditions. These tests can effectively help health professionals to determine or predict the genetic conditions of their patients. However, physicians have not actively incorporated such innovative genetic technology into their clinical practices according to two national wide surveys commissioned by UnitedHealth Group. To fill the gap of insufficient use of a large number of genetic tests, we generated a single Resource Description Framework (RDF) resource, called GT2RDF (Genetic Testing data to RDF) by integrating information about disease, gene, phenotype, genetic test, and drug from multiple sources including Genetic Testing Registry (GTR), Online Mendelian Inheritance in Man (OMIM), MedGen, Human Phenotype Ontology (HPO), ClinVar, National Drug File Reference Terminology (NDF-RT). Meanwhile, we manually annotated and extracted information from 200 randomly selected GeneReviews chapters, and integrated into the GT2RDF. We performed two case studies to demonstrate the usability of the GT2RDF. GT2RDF will serve as a data foundation to support the design of a genetic testing recommendation system, called iGenetics, which will ultimately facilitate the pace of precision medicine by means of actively and effectively incorporating innovative genetic technology in clinical settings. Abbreviations: GT2RDF: Genetic Testing data to RDF; SWT: Semantic web technology; OWL: Ontology Web Language; RDF: Resource Description Framework; SPARQL: SPARQL Protocol and RDF Query Language; GTR: Genetic Testing Registry; OMIM: Online Mendelian Inheritance in Man; HPO: Human Phenotype Ontology; NDF-RT: National Drug File Reference Terminology; UMLS: Unified Medical Language System.
Dynamic Cloud Resource Reservation via Cloud Brokerage

Infrastructure-as-a-Service clouds offer diverse pricing options, including on-demand and reserved instances with various discounts to attract different cloud users. A practical problem facing cloud users is how to minimize their costs by choosing among different pricing options based on their own demands. In this paper, we propose a new cloud brokerage service that reserves a large pool of instances from cloud providers and serves users with price discounts. The broker optimally exploits both pricing benefits of long-term instance reservations and multiplexing gains. We propose dynamic strategies for the broker to make instance reservations with the objective of minimizing its service cost. These strategies leverage dynamic programming and approximate algorithms to rapidly handle large volumes of demand. Our extensive simulations driven by large-scale Google cluster-usage traces have shown that significant price discounts can be realized via the broker.
A Survey on Approaches for Interoperability and Portability of Cloud Computing Services

Over the recent years, the rapid development of Cloud Computing has driven to a large market of cloud services that offer infrastructure, platforms and software to everyday users. Yet, due to the lack of common accepted standards, cloud service providers use different technologies and offer their clients services that are operated by a variety of proprietary APIs. The lack of standardization results in numerous heterogeneities (e.g., heterogeneous service descriptions, message level naming conflicts, data representation conflicts etc.) making the interoperation, collaboration and portability of services a very complex task. In this work we focus on the problems of interoperability and portability in Cloud Computing, we address their differences and we discuss some of the latest research work in this area. We evaluate and point out relationships between the identified solutions. Finally we present a use case scenario of the FI-STAR project, that aims to bridge the gap of healthcare provision in cloud computing. We demonstrate the architecture of the project and we discuss possible interoperability and portability issues.
Highly Dynamic and Sex-Specific Expression of microRNAs During Early ES Cell Differentiation

Embryonic stem (ES) cells are pluripotent cells derived from the inner cell mass of the mammalian blastocyst. Cellular differentiation entails loss of pluripotency and gain of lineage-specific characteristics. However, the molecular controls that govern the differentiation process remain poorly understood. We have characterized small RNA expression profiles in differentiating ES cells as a model for early mammalian development. High-throughput 454 pyro-sequencing was performed on 19–30 nt RNAs isolated from undifferentiated male and female ES cells, as well as day 2 and 5 differentiating derivatives. A discrete subset of microRNAs (miRNAs) largely dominated the small RNA repertoire, and the dynamics of their accumulation could be readily used to discriminate pluripotency from early differentiation events. Unsupervised partitioning around meloids (PAM) analysis revealed that differentiating ES cell miRNAs can be divided into three expression clusters with highly contrasted accumulation patterns. PAM analysis afforded an unprecedented level of definition in the temporal fluctuations of individual members of several miRNA genomic clusters. Notably, this unravelled highly complex post-transcriptional regulations of the key pluripotency miR-290 locus, and helped identify miR-293 as a clear outlier within this cluster. Accordingly, the miR-293 seed sequence and its predicted cellular targets differed drastically from those of the other abundant cluster members, suggesting that previous conclusions drawn from whole miR-290 over-expression need to be reconsidered. Our analysis in ES cells also uncovered a striking male-specific enrichment of the miR-302 family, which share the same seed sequence with most miR-290 family members. Accordingly, a miR-302 representative was strongly enriched in embryonic germ cells derived from primordial germ cells of male but not female mouse embryos. Identifying the chromatin remodelling and E2F-dependent transcription repressors Ari4a and Arid4b as additional targets of miR-302 and miR-290 supports and possibly expands a model integrating possible overlapping functions of the two miRNA families in mouse cell totipotency during early development. This study demonstrates that small RNA sampling throughout early ES cell differentiation enables the definition of statistically significant expression patterns for most cellular miRNAs. We have further shown that the transience of some of these miRNA patterns provides highly discriminative markers of particular ES cell states during their differentiation, an approach that might be broadly applicable to the study of early mammalian development.
Ieee Transactions on Communications, Accepted for Publication Generalized Design of Low-complexity Block Diagonalization Type Precoding Algorithms for Multiuser Mimo Systems

—Block diagonalization (BD) based precoding techniques are well-known linear transmit strategies for multiuser MIMO (MU-MIMO) systems. By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed into multiple independent parallel single user MIMO (SU-MIMO) channels and achieves the maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix. In this work, low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. We devise a strategy based on a common channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Analytical and simulation results show that the proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
Mechanism of the Stereoselective α-Alkylation of Aldehydes Driven by the Photochemical Activity of Enamines

Herein we describe our efforts to elucidate the key mechanistic aspects of the previously reported enantioselective photochemical α-alkylation of aldehydes with electron-poor organic halides. The chemistry exploits the potential of chiral enamines, key organocatalytic intermediates in thermal asymmetric processes, to directly participate in the photoexcitation of substrates either by forming a photoactive electron donor–acceptor complex or by directly reaching an electronically excited state upon light absorption. These photochemical mechanisms generate radicals from closed-shell precursors under mild conditions. At the same time, the ground-state chiral enamines provide effective stereochemical control over the enantioselective radical-trapping process. We use a combination of conventional photophysical investigations, nuclear magnetic resonance spectroscopy, and kinetic studies to gain a better understanding of the factors governing these enantioselective photochemical catalytic processes. Measurements of the quantum yield reveal that a radical chain mechanism is operative, while reaction-profile analysis and rate-order assessment indicate the trapping of the carbon-centered radical by the enamine, to form the carbon–carbon bond, as rate-determining. Our kinetic studies unveil the existence of a delicate interplay between the light-triggered initiation step and the radical chain propagation manifold, both mediated by the chiral enamines.
Automating Pre-Virtualization for Memory Objects

A golf practice and training guide to assist a golfer in identifying and replicating a preferred ball position. The golf practice and training device includes a first and second alignment guides pivotally mounted on the ground and spaced apart such that the alignment guides are capable of pivoting towards each other and intersecting at a point proximate a preferred ball position. The invention also includes a method for determining a golfer's preferred ball position and capturing that ball position for future practice sessions.
ADF/cofilin use an intrinsic mode of F-actin instability to disrupt actin filaments

Proteins in the ADF/cofilin (AC) family are essential for rapid rearrangements of cellular actin structures. They have been shown to be active in both the severing and depolymerization of actin filaments in vitro, but the detailed mechanism of action is not known. Under in vitro conditions, subunits in the actin filament can treadmill; with the hydrolysis of ATP driving the addition of subunits at one end of the filament and loss of subunits from the opposite end. We have used electron microscopy and image analysis to show that AC molecules effectively disrupt one of the longitudinal contacts between protomers within one helical strand of F-actin. We show that in the absence of any AC proteins, this same longitudinal contact between actin protomers is disrupted at the depolymerizing (pointed) end of actin filaments but is prominent at the polymerizing (barbed) end. We suggest that AC proteins use an intrinsic mechanism of F-actin's internal instability to depolymerize/sever actin filaments in the cell.
S-parameters optimization in both segmented and unsegmented insulated TSV

A segmented and unsegmented 3D insulated copper through silicon vias (TSVs) of diameter 10μm, height 100μm and silicon of sizes 100μm by 100μm by 100μm are modelled using analysis system (ANSYS) and equivalent circuit using advanced design system (ADS) at frequency ranges between 100MHz and 20GHz at 10MHz step sizes. The segmented via is divided into three parts; part 1, part 2 and part 3. Each part is modelled separately. The scattering parameters especially the S21 which defines power loss in TSVs in both cases are found. The outputs are optimized to give accurate results. The results show that the outputs reflect the transmission characteristics of an ideal TSV. It's concluded that segmented TSV experiences a much lower insertion loss compared to the unsegmented one. Since insertion loss is a key reliability problem in TSVs, we propose this kind of modelling to eradicate it. However other reliability issues need to be eradicated too.