Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracting Textual Associations in Part-of-Speech Tagged Corpora

Identifying textual associations from text corpora is a useful pre-processing step for many applications in Natural Language Processing. In this paper, we will present an innovative system that extracts relevant sequences of characters, words and part-of-speech tags from corpora. We will show that the combination of a new association measure (Mutual Expectation) with a new acquisition process (LocalMaxs) proposes an integrated solution to the problems of enticement techniques and global thresholds highlighted by previous researches.
Finding a STAR in a Vehicular Cloud

The strong capabilities that exist in a Vehicular Ad hoc Network (VANET) has given birth to the concept of Vehicular Clouds, in which cloud computing services are hosted by vehicles that have sufficient resources to act as mobile cloud servers. In this paper, we design a system that enables vehicles in a VANET to search for mobile cloud servers that are moving nearby and discover their services and resources. The system depends on RSUs that act as cloud directories with which mobile cloud servers register. The RSUs share their registration data to enable vehicles to discover and consume the services of mobile cloud servers within a certain area. We evaluated the proposed system using the ns2 software and demonstrated through comparing the results to another mechanism the feasibility and efficiency of our system in terms of service discovery and service consuming delays and packet success ratio.
Performance Evaluation of Intrusion Detection System Using Anomaly and Signature Based Algorithms to Reduction False Alarm Rate and Detect Unknown Attacks

With the rapidly growth of technology, used Internet become an important part in human life it used in many sectors of society, communicating over global network, sending or receiving sensitive data is risk because different techniques are used by attackers to intercept and exposed data. As a result, strong security technique is required to guaranteeing the user data. Many methods proposed to improve security issues. Intrusion detection system (IDS) is used to observe unwanted action on network systems and individual computers. However due to opposite effect of using IDS, using individual methods of IDS only misuse or anomaly attacks can be detected. This paper proposed a model that integrates both approaches signature and anomaly based of IDS to reduce obtained alerts and detects new attacks. False alarm rate, accuracy, and detect attacks are the parameters used to evaluate effectiveness of hybrid IDS in addition Knowledge Discovery Data Mining (KDD) CUP 99 dataset and Waikato Environment for Knowledge Analysis (WEKA) program has been used for testing the proposed hybrid IDS.
Distributed data association in smart camera networks

One of the fundamental requirements for visual surveillance with smart camera networks is the correct association of camera's observations with the track of objects under tracking. Most of the current systems are centralized in that the observations on all cameras need to be transmitted to a central server where some data association algorithm is running. In this paper, we propose a distributed data association approach in which the data association inference is achieved by propagation of beliefs of the association variables between neighboring cameras. We also incorporate the distributed inference into distributed EM framework to solve the problem of data association and object appearance learning simultaneously in a complete distributed manner. The proposed method is tested on artificial data and on real world observations collected by a camera networks in an office building.
Different levels of alternative splicing among eukaryotes

Alternative splicing increases transcriptome and proteome diversification. Previous analyses aiming at comparing the rate of alternative splicing between different organisms provided contradicting results. These contradicting results were attributed to the fact that both analyses were dependent on the expressed sequence tag (EST) coverage, which varies greatly between the tested organisms. In this study we compare the level of alternative splicing among eight different organisms. By employing an EST independent approach we reveal that the percentage of genes and exons undergoing alternative splicing is higher in vertebrates compared with invertebrates. We also find that alternative exons of the skipping type are flanked by longer introns compared to constitutive ones, whereas alternative 5′ and 3′ splice sites events are generally not. In addition, although the regulation of alternative splicing and sizes of introns and exons have changed during metazoan evolution, intron retention remained the rarest type of alternative splicing, whereas exon skipping is more prevalent and exhibits a slight increase, from invertebrates to vertebrates. The difference in the level of alternative splicing suggests that alternative splicing may contribute greatly to the mammal higher level of phenotypic complexity, and that accumulation of introns confers an evolutionary advantage as it allows increasing the number of alternative splicing forms.
A soft multiphase segmentation model via Gaussian mixture

This paper developed a new soft multiphase segmentation model. Different from most maximum-likelihood based and Bayesian-estimation based methods, the proposed model introduced a geometrical constraint- “the length term” into the model which makes the model more rigorous in analysis while still flexible in implementation. Moreover, the model used mixed Gaussian with different parameters for different patterns. As a result, it is more robust to noise. The experiments demonstrated its high efficiency.
Alcohol and the Developing Brain: Neuroanatomical Studies

One of the distinguishing features of prenatal alcohol exposure is impaired cognitive and behavioral function resulting from damage to the central nervous system. Information available from the small number of autopsied cases in humans indicates that the offspring of mothers who abused alcohol during pregnancy have various neuroanatomical alterations ranging from gross reductions in brain size to cellular alterations. Recent neuroimaging technology provides the most powerful tool for assessing the neurotoxic effects of fetal alcohol exposure in living organisms and for exploring the relationship between behavioral dysfunction and brain damage at the regional level. Recently, animal research has suggested that the damaging effects of alcohol exposure during brain development could be prevented or attenuated by various pharmacological manipulations or by complex motor training. These promising findings provide directions for developing future prevention or intervention strategies.
An Efficient Web Query Optimization Algorithm Based on LDA and MA

With the explosive growth in the Web documents, retrieving document from the large-scale document database has become one of the most active research fields in data mining communities. Thus, developing an efficient document query optimization algorithm to retrieval Web document is of great importance. An efficient document query optimization algorithm based on linear discriminant analysis(LDA) and memetic algorithm(MA) is proposed in this paper. The experimental results demonstrate that the proposed algorithm achieves much better performance than other conventional document query optimization algorithms.
Evaluation of Online Dialogue Policy Learning Techniques

The number of applied Dialogue Systems is ever increasing in several service providing and other applications as a way to efficiently and inexpensively serve large numbers of customers. A DS that employs some form of adaptation to the environment and its users is called an Adaptive Dialogue System (ADS). A significant part of the research community has lately focused on ADS and many existing or novel techniques are being applied to this problem. One of the most promising techniques is Reinforcement Learning (RL) and especially online RL. This paper focuses on online RL techniques used to achieve adaptation in Dialogue Management and provides an evaluation of various such methods in an effort to aid the designers of ADS in deciding which method to use. To the best of our knowledge there is no other work to compare online RL techniques on the dialogue management problem.
Sub-Nyquist Sampling: Bridging Theory and Practice

Sampling theory encompasses all aspects related to the conversion of continuous-time signals to discrete streams of numbers. The famous Shannon-Nyquist theorem has become a landmark in the development of digital signal processing. In modern applications, an increasingly number of functions is being pushed forward to sophisticated software algorithms, leaving only those delicate finely-tuned tasks for the circuit level. In this paper, we review sampling strategies which target reduction of the ADC rate below Nyquist. Our survey covers classic works from the early 50's of the previous century through recent publications from the past several years. The prime focus is bridging theory and practice, that is to pinpoint the potential of sub-Nyquist strategies to emerge from the math to the hardware. In that spirit, we integrate contemporary theoretical viewpoints, which study signal modeling in a union of subspaces, together with a taste of practical aspects, namely how the avant-garde modalities boil down to concrete signal processing systems. Our hope is that this presentation style will attract the interest of both researchers and engineers in the hope of promoting the sub-Nyquist premise into practical applications, and encouraging further research into this exciting new frontier.
Notes on Packet Marking for IP Traceback

Distributed Denial of Service (DDoS) attack is among the hardest network security problems to address. Recently, several countermeasures are proposed, among which, PPM (probabilistic packet marking) pioneered by Savage et al. is promising. In this paper, a brief review of countermeasures to DDoS is given and then an analysis on some of the packet marking schemes is provided. Some modifications are further provided. One modification to the basic PPM scheme can reduce its computation remarkably.
Dependence of ionized and total Ca in squid axons on Nao-free or high- Ko conditions

The level of intracellular Ca in squid axons (both ionized and total Ca) was studied as a function of the experimental variables [Na]i, [Na]o, pHi, cyanide, and depolarization. Ionized Ca was measured by following the light emission of aequorin while total Ca was measured by the atomic absorption analysis of samples of axoplasm. Aequorin glow is known to be increased either by the application of Nao-free solutions or by depolarization produced by external solutions containing greater than normal K concentrations. The present results show that if [Na]i is low, the depolarization that is brought about by solutions with elevated [K] leads to a resting light emission that is decreased rather than increased, as is the case when [Na]i is high. In axons where [Na]i is varied, a comparison of the increments in light emission produced by the application first of Na-free and then of high-K solutions shows that they have an identical dependence on [Na]i, with a half-activation of Ca entry produced by an [Na]i of 25-30 mM. Changes in pHi affect the aequorin signal produced by depolarization, with acidification reducing and alkanization increasing the response. Cyanide did not greatly affect the size of the signal resulting from either Nao removal or that from depolarization.
Cysteine Cathepsin Activity Regulation by Glycosaminoglycans

Cysteine cathepsins are a group of enzymes normally found in the endolysosomes where they are primarily involved in intracellular protein turnover but also have a critical role in MHC II-mediated antigen processing and presentation. However, in a number of pathologies cysteine cathepsins were found to be heavily upregulated and secreted into extracellular milieu, where they were found to degrade a number of extracellular proteins. A major role in modulating cathepsin activities play glycosaminoglycans, which were found not only to facilitate their autocatalytic activation including at neutral pH, but also to critically modulate their activities such as in the case of the collagenolytic activity of cathepsin K. The interaction between cathepsins and glycosaminoglycans will be discussed in more detail.
Does the web extend the mind?

Under what conditions does the Web count as a part of your own mind? We iterate the conditions upon which cognitive extension and integration can be upheld, and inspect these in light of the Web. We also argue that this ability to integrate the mind into media such as the Web is inherently social, insofar as it involves interaction. Also, there are many cases where external media like the Web are not actually cognitively integrated, but simply serve as a way to co-ordinate intelligent problem-solving via distributed cognition. Yet distributed cognition should not be underestimated, as it is precisely distributed cognition that can solve problems that an individual human may be unable to solve by themselves, and can serve as a stepping stone to a wider kind of cognitive integration: collective intelligence. Finally, we define collective intelligence as cognitive integration combined with distributed cognition.
Convergence of the Generalized Alternating Projection Algorithm for Compressive Sensing

The convergence of the generalized alternating projection (GAP) algorithm is studied in this paper to solve the compressive sensing problem $\yv = \Amat \xv + \epsilonv$. By assuming that $\Amat\Amat\ts$ is invertible, we prove that GAP converges linearly within a certain range of step-size when the sensing matrix $\Amat$ satisfies restricted isometry property (RIP) condition of $\delta_{2K}$, where $K$ is the sparsity of $\xv$. The theoretical analysis is extended to the adaptively iterative thresholding (AIT) algorithms, for which the convergence rate is also derived based on $\delta_{2K}$ of the sensing matrix. We further prove that, under the same conditions, the convergence rate of GAP is faster than that of AIT. Extensive simulation results confirm the theoretical assertions.
TV commercial detection using audiovisual features and support vector machine

Automatic detection of commercials is a important step of commercial management, and has multiple potential applications in TV video content analysis. In this paper, we transform the problem of commercial detection to commercial shot detection, and propose a novel method to fuse audio and visual features to detect commercial blocks. An intermediate feature POIM (Program-oriented Informative Images) is introduced, which contains the information of product or program. The contextual features for each shot are generated with time expansion from POIM image probability and other basic audiovisual features. And then, these contextual features are utilized to predict the probabilities of commercial shot using SVM (Support Vector Machine) classifier. Experiments get promising performance on a database from TV channels in China.
Prioritizing Unit Test Creation for Test-Driven Maintenance of Legacy Systems

Test-Driven Development (TDD) is a software development practice that prescribes writing unit tests before writing implementation code. Recent studies have shown that TDD practices can significantly reduce the number of pre-release defects. However, most TDD research thus far has focused on new development. We investigate the adaptation of TDD-like practices for already implemented code, in particular legacy systems. We call this adaptation of TDD-like practices for already implemented code ``Test-Driven Maintenance'' (TDM). In this paper, we present an approach that assists software development and testing managers, who employ TDM, utilize the limited resources they have for testing legacy systems efficiently. The approach leverages the development history of the project to generate a prioritized list of functions that managers should focus their unit test writing resources on. The list is updated dynamically as the development of the legacy system progresses. To evaluate our approach, we conduct a case study on a large commercial legacy software system. Our findings suggest that heuristics based on the function size, modification frequency and bug fixing frequency should be used to prioritize the unit test writing of legacy systems.
Characterizing the Roles of Cryphonectria parasitica RNA-Dependent RNA Polymerase-Like Genes in Antiviral Defense, Viral Recombination and Transposon Transcript Accumulation

An inducible RNA-silencing pathway, involving a single Dicer protein, DCL2, and a single Argonaute protein, AGL2, was recently shown to serve as an effective antiviral defense response in the chestnut blight fungus Cryphonectria parasitica. Eukaryotic RNA-dependent RNA polymerases (RdRPs) are frequently involved in transcriptional and posttranscriptional gene silencing and antiviral defense. We report here the identification and characterization of four RdRP genes (rdr1–4) in the C. parasitica genome. Sequence relationships with other eukaryotic RdRPs indicated that RDR1 and RDR2 were closely related to QDE-1, an RdRP involved in RNA silencing (“quelling”) in Neurospora crassa, whereas RDR3 was more closely related to the meiotic silencing gene SAD-1 in N. crassa. The RdRP domain of RDR4, related to N. crassa RRP-3 of unknown function, was truncated and showed evidence of alternative splicing. Similar to reports for dcl2 and agl2, the expression levels for rdr3 and rdr4 increased after hypovirus CHV-1/EP713 infection, while expression levels of rdr1 and rdr2 were unchanged. The virus-responsive induction patterns for rdr3 and rdr4 were altered in the Δdcl2 and Δagl2 strains, suggesting some level of interaction between rdr3 and rdr4 and the dcl2/agl2 silencing pathway. Single rdr gene knockouts Δrdr1–4, double knockouts Δrdr1/2, Δrdr2/3, Δrdr1/3, and a triple knockout, Δrdr1/2/3, were generated and evaluated for effects on fungal phenotype, the antiviral defense response, viral RNA recombination activity and transposon expression. None of the single or multiple rdr knockout strains displayed any phenotypic differences from the parental strains with or without viral infection or any significant changes in viral RNA accumulation or recombination activity or transposon RNA accumulation, indicating no detectable contribution by the C. parasitica rdr genes to these processes.
Optimal resource allocation scheme in femtocell networks using Bacterial Foraging Optimization

The femtocell network has currently been considered as one of the most promising networking technologies. Nevertheless, due to dense deployment, interference generated by nearby femto base station (FBS) is expected to significantly degrade the signal to interference plus noise ratio (SINR) of femto users (FUEs). Ineffective resource block combination is one of the culprits behind the reduction in performance of each FUE. Therefore, appropriate resource block allocation becomes critical in reducing interference while improving SINR, resulting in better system performance. Bacteria Foraging Optimization (BFO) is proposed to select the most appropriate combination of resource block for FUE, leading to the decrease in the amount of interference in femtocell network. The simulation results illustrate that the proposed algorithm is capable of enhancing the SINR in comparison with random allocation scheme.
Statistical Identification of Pleonastic Pronouns

This paper describes an algorithm to identify pleonastic pronouns using statistical techniques. The training step uses a coreference annotated corpus of English and focuses on a set of pronouns such as it. As far as we know, there is no corpus with a pleonastic annotation. The main idea of the algorithm was then to recast the definition of pleonastic pronouns as pronouns that never occur in a coreference chain. We integrated this algorithm in an existing coreference solver (Bj¨orkelund and Nugues, 2011) and we measured the overall performance gains brought by the pleonastic it removal. We observed an improvement of 0.42 from 59.15 of the CoNLL score. The complete system (Stamborg et al., 2012) participated in the CoNLL 2012 shared task (Pradhan et al., 2012), where it obtained the 4th rank. (Less)
Who Elected the Bankers?: Surveillance and Control in the World Economy

1. Global Markets and National Politics2. The Political Economy of International Capital Mobility3. The League of Nations and Roots of Multilateral Oversight4. The Transformation of Economic Oversight in the League5. Global Aspirations and the Early International Monetary Fund6. The Reinvention of Multilateral Economic Surveillance7. The Political Foundations of Global MarketsNotes Selected Bibliography Index
Economic Comparisons of Alternative and Conventional Production Technologies for Eggplant in Southern Georgia

Environmental concerns about pesticide usage in traditional production systems are prompting vegetable producers to consider alternative systems. Research results from a multi-year study on eggplant in southern Georgia compare two alternative production technologies to the conventional rye cover crop technology. Alternative technologies utilize beneficial insect principles as substitutes for conventional pesticide controls. Using field data, eggplant production budgets are developed to generate net return estimates under each system. Cost reductions achieved by using alternative technologies are not sufficient to offset the reduced yields and returns generated from these technologies. Cash input requirements for alternative systems suggest potential for limited resource producers.
Stabilization of Networked Control System with Packet Dropouts

— Time delays in exchange of information and packet dropoutsare very common in NCS (Feedback control systems with communications networks for data exchange). Owing to the occurrence of such time delays and packet dropouts, the NCS systems are uncertain and time-varying. Also these time dealys and packet dropouts may result in degartion of the NCS performance and instability.This paper presents a new design of a state-feedback controller usingLyapunov stability criterion in terms of LMI conditions for the time varying uncertain NCS. Further, the LMI condition is used to guarantee the stability of the NCS. Results are included to demonstrate this presented approach to stabilization of NCS.
The stellar population of the star-forming region G61.48+0.09

Context. We present the results of a near-infrared photometric and spectroscopic study of the star-forming region G61.48+0.09. Aims. The purpose of this study is to characterize the stellar content of the cluster and to determine its distance, extinction, age, and mass. Methods. The stellar population was studied by using color–magnitude diagrams to select twenty promising cluster members, for which follow-up spectroscopy was done. The observed spectra allowed a spectral classification of the stars. Results. Two stars have emission lines, twelve are G-type stars, and six are late-O or early-B stars. Conclusions. The cluster’s extinction varies from AKS = 0. 9t oAKS = 2.6, (or AV ∼ 8t oAV ∼ 23). G61.48+0.09 is a star-forming region located at 2.5 ± 0.4 kpc. The cluster is younger than 10 Myr and has a minimum stellar mass of 1.5 ± 0.5 × 10 3 M� . H owever, the actual total mass of the cluster remains undetermined, as we cannot see its whole stellar content.
Emotional Automaticity Is a Matter of Timing

There has been a long controversy concerning whether the amygdala's response to emotional stimuli is automatic or dependent on attentional load. Using magnoencephalography and an advanced beamformer source localization technique, we found that amygdala automaticity was a function of time: while early amygdala responding to emotional stimuli (40–140 ms) was unaffected by attentional load, later amygdala response (280–410 ms), subsequent to frontoparietal cortex activity, was modulated by attentional load.