Miracle-dz/UniFAR-FTUs huggingface dataset:
Contention MAC Protocols Efficiency Testing in a Small Wireless Network

Medium access protocols are one of the most important issues in the network design. It can be seen especially while using contention protocols in wireless networks. For every protocol it is possible to evaluate its efficiency using probability calculus. However, it is interesting how these protocols behave in a practical network. To test the protocols efficiency, an experimental wireless network has been created. It consists of one control station (receiver) and three local stations, sending frames to the receiver. Several MAC protocols have been tested: Aloha, slotted Aloha, CSMA and MACA. The results, shown on the pictures, are similar to the theoretical results, although some differences can be observed
Music emotion recognition using two level classification

Rapid growth of digital music data in the Internet during the recent years has led to increase of user demands for search based on different types of meta data. One kind of meta data that we focused in this paper is the emotion or mood of music. Music emotion recognition is a prevalent research topic today. We collected a database including 280 pieces of popular music with four basic emotions of Thayer's two Dimensional model. We used a two level classifier the process of which could be briefly summarized in three steps: 1) Extracting most suitable features from pieces of music in the database to describe each music song; 2) Applying feature selection approaches to decrease correlations between features; 3) Using SVM classifier in two level to train these features. Finally we increased accuracy rate from 72.14% with simple SVM to 87.27% with our hierarchical classifier.
ON THE OPTIMALITY OF SAMPLE-BASED ESTIMATES OF THE EXPECTATION OF THE EMPIRICAL MINIMIZER ∗, ∗∗

We study sample-based estimates of the expectation of the function produced by the empirical minimization algorithm. We investigate the extent to which one can estimate the rate of convergence of the empirical minimizer in a data dependent manner. We establish three main results. First, we provide an algorithm that upper bounds the expectation of the empirical minimizer in a completely data-dependent manner. This bound is based on a structural result due to Bartlett and Mendelson, which relates expectations to sample averages. Second, we show that these structural upper bounds can be loose, compared to previous bounds. In particular, we demonstrate a class for which the expectation of the empirical minimizer decreases as O(1/n) for sample size n, although the upper bound based on structural properties is Ω(1). Third, we show that this looseness of the bound is inevitable: we present an example that shows that a sharp bound cannot be universally recovered from empirical data.
Notice of RetractionStudy on Regulation of Bad Network Information Based on Evolutionary Game

How to effectively filter out vulgar network cultural products is something we must address the issue with the increasing of all kinds of bad information on the internet. The rise of evolutionary game theory is a theory combining together with the game theory analysis and dynamic analysis of the evolution process. For the effective implementation of incentive policy to prevent bad information, this paper analyzes the strategies' choice on the interaction between the network regulators and the network operators with the evolutionary game theory, and the optimal strategy is put forward.
Optimizing logistic processes using a fuzzy decision making approach

This paper addresses the problem of optimizing logistic processes that can be modeled as a birth-and-death process. A fuzzy decision making algorithm is proposed to assign components to orders, which is a common task in a large number of logistic processes. The dynamic assignment of components to orders is the key issue in optimizing logistic processes. This paper proposes several criteria for this optimization. These criteria are combined using weighted fuzzy aggregation in a fuzzy decision making environment. First, a simple but illustrative example shows that the proposed techniques can be applied with good results to this type of processes. Then, the proposed method is applied to a real-world logistic process at Fujitsu-Siemens Computers.
How to efficiently detect different data-rate communications in multiuser short-range impulse radio UWB systems

Low and high data-rate applications can be foreseen for future ultra-wideband systems which are based on impulse radio and proper detection schemes have to be designed for the most general scenarios. In this paper, an innovative frequency domain detection strategy is tested in two different indoor short-range communication scenarios where several mobile terminals transmit low or high data-rate flows to a base station. Both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) criteria have been investigated and compared with the classical RAKE. The results show that the proposed approach is well suited for the considered scenarios.
TERp System Description

This paper describes TER-Plus (TERp) the University of Maryland / BBN Technologies submission for the NIST Metric MATR 2008 workshop on automatic machine translation evaluation metrics. TERp is an extension of Translation Edit Rate (TER) that builds off of the success of TER as an evaluation metric and alignment tool while addressing several of its weaknesses through the use of paraphrases, morphological stemming, and synonyms, as well as edit costs that are optimized to correlate better with various types of human judgments.
Creating various styles of animations using example-based filtering

A number of nonphotorealistic rendering methods for producing artistic style images have been developed. Recently, a method called "Image Analogies" was proposed. This method is based on the idea of example-based filtering that uses a pair of images (an original image and a filtered image) as training data and creates an image which has a style that resembles the filtered image of the training data. This method has great flexibility since the users can create various styles of images by simply changing the training data. We extend "Image Analogies" to create various styles of animations. The coherence between frames is considered by computing the pixel flows between the frames. From experimental results, the proposed method can create nice animation sequences.
Decoding the Regulatory Landscape of Ageing in Musculoskeletal Engineered Tissues Using Genome-Wide DNA Methylation and RNASeq

Mesenchymal stem cells (MSC) are capable of multipotent differentiation into connective tissues and as such are an attractive source for autologous cell-based regenerative medicine and tissue engineering. Epigenetic mechanisms, like DNA methylation, contribute to the changes in gene expression in ageing. However there was a lack of sufficient knowledge of the role that differential methylation plays during chondrogenic, osteogenic and tenogenic differentiation from ageing MSCs. This study undertook genome level determination of the effects of DNA methylation on expression in engineered tissues from chronologically aged MSCs. We compiled unique DNA methylation signatures from chondrogenic, osteogenic, and tenogenic engineered tissues derived from young; n = 4 (21.8 years ± 2.4 SD) and old; n = 4 (65.5 years±8.3SD) human MSCs donors using the Illumina HumanMethylation 450 Beadchip arrays and compared these to gene expression by RNA sequencing. Unique and common signatures of global DNA methylation were identified. There were 201, 67 and 32 chondrogenic, osteogenic and tenogenic age-related DE protein-coding genes respectively. Findings inferred the nature of the transcript networks was predominantly for ‘cell death and survival’, ‘cell morphology’, and ‘cell growth and proliferation’. Further studies are required to validate if this gene expression effect translates to cell events. Alternative splicing (AS) was dysregulated in ageing with 119, 21 and 9 differential splicing events identified in chondrogenic, osteogenic and tenogenic respectively, and enrichment in genes associated principally with metabolic processes. Gene ontology analysis of differentially methylated loci indicated age-related enrichment for all engineered tissue types in ‘skeletal system morphogenesis’, ‘regulation of cell proliferation’ and ‘regulation of transcription’ suggesting that dynamic epigenetic modifications may occur in genes associated with shared and distinct pathways dependent upon engineered tissue type. An altered phenotype in engineered tissues was observed with ageing at numerous levels. These changes represent novel insights into the ageing process, with implications for stem cell therapies in older patients. In addition we have identified a number of tissue-dependant pathways, which warrant further studies.
Neural correlates of different self domains

The neural substrates of states devoted to processing self‐related information (“self‐related states”) remain not fully elucidated. Besides the complexity of the problem, there is evidence suggesting that self‐related states vary according to the information domain being considered. Here, we investigated brain correlates for self‐related states concerning historical aspects of one's life (autobiographical self), and one's ongoing body status (core self). We focused on memory‐related regions, body‐related regions, CMSs (cortical midline structures), and ICs (insular cortices).
Consistent analytical model for single and dual thickness capacitive Micromachined Ultrasound Transducers (cMUT)

Capacitive Micromachined Ultrasound Transducers (cMUTs) are recognized as key enablers for emerging applications of ultrasound waves in gaseous, liquid and solid-state media, from positioning/ranging to medical treatment, through actuation, levitation, drug delivery, bio-sensing. This paper presents an improved consistent model for cMUTs implementing uniform or bossed membranes in transmit and receive modes. Key in our model are the consistent description of the mechanical modal resonant equivalent circuit and the transduction between electrical, mechanical and acoustic domains as well as the proper description of the acoustic load, not only resistive but also inductive, and thus the accurate representation of the frequency drift introduced by the medium supporting the propagation. In particular, we demonstrate, through comparison with FEM simulations, the accuracy of the model to define the center frequency, 3dB-fractional bandwidth and output pressure levels of cMUTS.
α1-Antitrypsin Binds to and Interferes with Functionality of EspB from Atypical and Typical Enteropathogenic Escherichia coli Strains

ABSTRACT Enteropathogenic Escherichia coli (EPEC), including diffusely adhering atypical E. coli, strains use a type III secretion system to deliver effector proteins into the membrane and cytoplasm of infected cells. The E. coli secreted proteins A, B, and D (EspA, EspB, and EspD) are required for the formation of the characteristic attaching and effacing (A/E) lesions. EspB and EspD are thought to form a translocation pore in the host cell membrane through which effector proteins are injected into the host cytosol. Besides its function in pore formation, EspB has been found in the cytosol and implicated to function as an effector protein. We screened for putative host cell proteins interacting with EspB of atypical EPEC strains and identified α1-antitrypsin (AAT) as a binding partner for EspB. AAT binds to EspB in pull-down and overlay experiments and also to EspD in overlay experiments. In agreement with the role of EspB and EspD in pore formation, EPEC-mediated hemolysis of red blood cells is strongly reduced by AAT in a concentration-dependent manner, indicating that AAT interferes with type III secretion by inhibiting the formation of the translocation pore. This is further supported by a decreased actin polymerization after infection of HeLa or CaCo-2 cells with EPEC in the presence of physiologically relevant concentrations of AAT. In this study, we identify AAT as a new binding partner for EspB and EspD, suggesting a previously unappreciated role for AAT in host cell defense against EPEC infections and potentially also against other bacterial pathogens.
Comparative Analysis of AGPase Genes and Encoded Proteins in Eight Monocots and Three Dicots with Emphasis on Wheat

ADP-glucose pyrophosphorylase (AGPase) is a heterotetrameric enzyme with two large subunits (LS) and two small subunits (SS). It plays a critical role in starch biosynthesis. We are reporting here detailed structure, function and evolution of the genes encoding the LS and the SS among monocots and dicots. “True” orthologs of maize Sh2 (AGPase LS) and Bt2 (AGPase SS) were identified in seven other monocots and three dicots; structure of the enzyme at protein level was also studied. Novel findings of the current study include the following: (i) at the DNA level, the genes controlling the SS are more conserved than those controlling the LS; the variation in both is mainly due to intron number, intron length and intron phase distribution; (ii) at protein level, the SS genes are more conserved relative to those for LS; (iii) “QTCL” motif present in SS showed evolutionary differences in AGPase belonging to wheat 7BS, T. urartu, rice and sorghum, while “LGGG” motif in LS was present in all species except T. urartu and chickpea; SS provides thermostability to AGPase, while LS is involved in regulation of AGPase activity; (iv) heterotetrameric structure of AGPase was predicted and analyzed in real time environment through molecular dynamics simulation for all the species; (v) several cis-acting regulatory elements were identified in the AGPase promoters with their possible role in regulating spatial and temporal expression (endosperm and leaf tissue) and also the expression, in response to abiotic stresses; and (vi) expression analysis revealed downregulation of both subunits under conditions of heat and drought stress. The results of the present study have allowed better understanding of structure and evolution of the genes and the encoded proteins and provided clues for exploitation of variability in these genes for engineering thermostable AGPase.
dietary perturbation -synthase and apolipoprotein E double knockout mice with and without β Hyperhomocysteinemia accelerates atherosclerosis in cystathionine

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LSOSS: Detection of Cancer Outlier Differential Gene Expression

Detection of differential gene expression using microarray technology has received considerable interest in cancer research studies. Recently, many researchers discovered that oncogenes may be activated in some but not all samples in a given disease group. The existing statistical tools for detecting differentially expressed genes in a subset of the disease group mainly include cancer outlier profile analysis (COPA), outlier sum (OS), outlier robust t-statistic (ORT) and maximum ordered subset t-statistics (MOST). In this study, another approach named Least Sum of Ordered Subset Square t-statistic (LSOSS) is proposed. The results of our simulation studies indicated that LSOSS often has more power than previous statistical methods. When applied to real human breast and prostate cancer data sets, LSOSS was competitive in terms of the biological relevance of top ranked genes. Furthermore, a modified hierarchical clustering method was developed to classify the heterogeneous gene activation patterns of human breast cancer samples based on the significant genes detected by LSOSS. Three classes of gene activation patterns, which correspond to estrogen receptor (ER)+, ER– and a mixture of ER+ and ER–, were detected and each class was assigned a different gene signature.
Continuous Speech Recognition of Kannada language using triphone modeling

This paper aims to build continuous speech recognition of regional language Kannada using phoneme modeling wherein each phoneme is represented by tristate Hidden Markov Model(HMM) with each state being represented by Gaussian Mixture Model (GMM). The recordings were sampled at the rate of 16 kHz, blocked into overlapped frames of 25msec duration with 10 msec frame overlap using hamming window, converted into 39 dimensional Mel Frequency Cepstral Coefficients(MFCC), then modeled using continuous density HMM. Kannada language has 46 phonemes, out of which 12 phonemes represent vowels (swaragalu) and 34 phonemes represent consonants (vyanjanagalu). The recognition performance is tested for monophone modeling, word internal triphone modeling and tied state triphone modeling for different gaussian mixtures and results have been presented.
QoS Preemptive Routing with Bandwidth Estimation for Improved Performance in Ad Hoc Networks

Ad hoc networks are collection of mobile nodes which communicate using wireless media without any fixed infrastructure. Each mobile host acts both as a network router and an end point as packets are forwarded over multiple hops. Node mobility being the distinguishing feature of the mobile ad hoc network, makes routing an important challenge. Hence, Quality of Service (QoS) is not easily achieved in ad hoc networks. To provide QoS routing in Ad hoc networks, it is not just sufficient to provide a basic routing functionality where only a feasible route is found, other aspects like the bandwidth constraints due to shared media, dynamic topology due to continuously changing topology and the power consumption due to limited battery powers must also be considered. The nodes in the Ad hoc network move randomly, hence, the topology changes continuously resulting in route breakage. Thus, the route breakage must first be detected and a new route should be found to the destination in advance. This paper proposes a QoS Preemptive Routing protocol with Bandwidth estimation (QPRB) that computes the available bandwidth in the route and then sets up the route based on the network traffic and maintains the route using preemptive routing procedure. This protocol provides QoS support to the real time applications by providing a feedback about the network status. The algorithm improves network performance and performs well in route breakage conditions as better routes are found in advance to route breakage. The cost incurred to detect the route breakage and to find a new route is avoided. Simulation results show that the protocol significantly improves the packet delivery ratio and reduces the end-to-end delay in the route breakage conditions.
Rembrandt - a named-entity recognition framework

Rembrandt is a named entity recognition system specially crafted to annotate documents by classifying named entities and ground them into unique identifiers. Rembrandt played an important role within our research over geographic IR, thus evolving into a more capable framework where documents can be annotated, manually curated and indexed. The goal of this paper is to present Rembrandt's simple but powerful annotation framework to the NLP community.
On Conflict-driven variable ordering heuristics

It is well known that the order in which variables are instantiated by a backtracking search algorithm can make an enormous difference to the search effort in solving CSPs. Among the plethora of heuristics that have been proposed in the literature to efficiently order variables during search, a significant recently proposed class uses the learning-from-failure approach. Prime examples of such heuristics are the wdeg and dom/wdeg heuristics of Boussemart et al. which store and exploit information about failures in the form of constraint weights. The efficiency of all the proposed conflict-directed heuristics is due to their ability to learn though conflicts encountered during search. As a result, they can guide search towards hard parts of the problem and identify contentious constraints. Such heuristics are now considered as the most efficient general purpose variable ordering heuristic for CSPs. In this paper we show how information about constraint weights can be used in order to create several new variants of the wdeg and dom/wdeg heuristics. The proposed conflict-driven variable ordering heuristics have been tested over a wide range of benchmarks. Experimental results show that they are quite competitive compared to existing ones and in some cases they can increase efficiency.
Enhanced stock prediction using social network and statistical model

As a fundamental part of capital market, stock investment has great significance in optimizing capital allocation, funding as well as increasing the value of assets. To predict and evaluate the stock price also has important practical significance for investors due to the high income and high-risk characteristics of stock investments. However, the stock price is usually random fluctuation which affecting by speculative factors, thus make it is almost impossible to make accurate prediction. Considering conformist mentality is essential for accurately predict stock price. Recently, with expansive development of social networks (e.g. Facebook, Tweet or Sina weibo, etc.), huge users publish and exchange a variety of financial-related information with other users. Therefore, social network is an important approach to comprehend conformist mentality. In view of the above analysis, this paper proposed a new stock prediction method based on social networks and regression model, and we also used real dataset of NASDAQ market and Twitter to verify the proposed model. Experimental results show that the proposed method can accurately predict stock price.
Programming the FlexRAM Intelligent Memory Architecture

Advances in VLSI technology have enabled the implementation of computer architectures based on Processing-inMemory (PIM) chips. These architectures can help bridge the growing gap between processor and main memory speeds and, as a result, improve the performance of both numeric and symbolic codes. While PIM organization has been extensively studied from the machine organization point of view, the problem of effectively programming this kind of systems has been largely ignored. In this paper, we address how to program FlexRAM, a generalpurpose computer with PIM memory modules. We present CFlex, a family of compiler directives inspired in OpenMP, which enable the development of portable programs. We also explore enhancing the programmability with libraries of functions called Intelligent Memory Operations (IMOs). These libraries are optimized to make use of the PIMs but hide all their complexity. The geometric mean of the speedups achieved for our test suite by a system with one FlexRAM chip programmed with CFlex relative to a conventional machine is 14.4.