Miracle-dz/UniFAR-FTUs huggingface dataset:
Textual fingerprints of risk of war

We compute the rate of textual signals of risk of war recognizable in series of consecutive political speeches about a disputed issue serious enough to entail an international conflict. The speeches concern Iran's nuclear program. We trace textual signals forewarning of risks of war that reactions to this affair lead to. The thrust of the textual analysis rests on the interplay of affiliation and power words in continuous texts, following D. C. McClelland's model for anticipating wars. The speeches are those of Iranian President Mahmoud Ahmadinejad, US Secretary of State Hillary R. Clinton, Iranian Grand Ayatollah Ali Khamenei, and Israeli Prime Minister Benjamin Netanyahu. Prefiguring a military confrontation before it occurs involves structuring information from unstructured data. Despite such imperfect knowledge, by the end of January 2012, our results show a receding risk of war on the Iranian side, but an increasing risk on the American one, while remaining ambiguous on the Israeli one. © The Author 2013. Published by Oxford University Press on behalf of ALLC. All rights reserved.
Revisiting Circuit Clogging Attacks on Tor

Tor is a popular anonymity-providing network used by over 500,000 users daily. The Tor network is made up of volunteer relays. To anonymously connect to a server, a user first creates a circuit, consisting of three relays, and routes traffic through these proxies before connecting to the server. The client is thus hidden from the server through three Tor proxies. If the three Tor proxies used by the client could be identified, the anonymity of the client would be reduced. One particular way of identifying the three Tor relays in a circuit is to perform a circuit clogging attack. This attack requires the client to connect to a malicious server (malicious content, such as an advertising frame, can be hosted on a popular server). The malicious server alternates between sending bursts of data and sending little traffic. During the burst period, the three relays used in the circuit will take longer to relay traffic due to the increase in processing time for the extra messages. If Tor relays are continuously monitored through network latency probes, an increase in network latency indicates that this Tor relay is likely being used in that circuit. We show, through experiments on the real Tor network, that the Tor relays in a circuit can be identified. A detection scheme is also proposed for clients to determine whether a circuit clogging attack is happening. The costs for both the attack and the detection mechanism are small and feasible in the current Tor network.
Online Oversampling of Anomaly Detection with Principal Component Analysis

Data mining is process of discovering patterns in large data set. Outlier detection is an important issue in data mining and has been studied in different research areas. Anomaly (or outlier) detection aims to identify a small group of instance which deviates remarkably from existing data. Similarly we observe that adding (or removing) an abnormal data instance will affect the principal direction of the resulting data than removing (or adding) a normal data one does. Existing system online over-sampling principal component analysis (osPCA) algorithm to address this problem, aim at detecting the presence of outliers from a large amount of data via an online updating technique. In PCA normal data with multiclustering structure and data in an extremely high dimensional space. It is typically not easy to use linear models. Such as PCA, to estimate the data distribution. If there exists multiple data clusters. To overcome these problems and support multiple data clusters. We propose Independent Component analysis (ICA) technique to array processing and data analysis, which aiming at recovering unobserved samples from oversampled dataset from observed data samples for outlier detection exploiting only the assumption of mutual independence between the signals. The experiments with KDD Cup 1999 data set to assess the perform of our system. It shows that existing data system verify the feasibility of our proposed method in terms of both accuracy and efficiency.
Fabrication of low loss polyimide optical waveguides using thin-film multichip module process technology

Polyimides containing fluorine are attractive for integrated optics since the introduction of fluorine increases the optical transparency in the visible and near infrared spectrum. Polyimides are easily integrated with silicon or GaAs optical devices, can be spin-coated on a number of substrates and are resistant to chemical etchants, solvents and package assembly temperatures. Photosensitive polyimides are being widely used as dielectrics in multichip module fabrication because they offer a combination of good electrical and mechanical properties and low cost processing relative to non-photosensitive polyimides. In this paper, a simple, wet chemical patterning process for the fabrication of low loss waveguides using photosensitive polyimides is described. Optically transparent, fluorinated polyimides are modified by copolymerizing a low concentration of photocrosslinking groups into the backbone. The polyimides can then be patterned into channel, ribs, or Y branches by UV exposure through a photomask followed by wet chemical development. Sidewall smoothness and sidewall profiles can be controlled by varying exposure and development conditions. <<ETX>>
Rethinking the peer review process

Computer-support for peer review has been mostly limited to facilitating traditional reviewing processes and remedying scalability issues. My research aims to inform the design of future scientific peer review processes and the systems that support them by analyzing current practices in peer review, suggesting guidelines for the design of future peer-review processes and the systems that support them, and exploring the design space of interfaces to support the primary tasks in the peer review process (e.g. opinion measurement interfaces).
Research on SCKM algorithm based on the parallel clustering

As an effective method in dealing with the massive data, the serial processing, aiming to obtain the useful information quickly, cannot satisfy our calculation requirements with high-performance. However, both distributed computing and parallel computing are good choices in calculating high-volume data with high-performance. As a parallel computing framework based on memory computing large data, Spark was of great concern as soon as it was proposed. This paper, based on the limitations of k-medoids algorithm which is sensitive to the center point and requires a large number of iterations in the process of calculating the new center point, puts forward a parallel algorithm named Canopy-Kmedoids within the platform of Spark. The algorithm obtains the K center points by the Canopy algorithm. By analyzing the performance of parallel operators and the advantage of using Spark to have good performance for iterative computation. In addition, this method reduces the frequency of reading or writing the shuffle and disk, which effectively overcomes the shortcomings of k-medoids. The experimental results show that the parallel algorithm achieves a relative ideal speedup ratio and can handle the massive data efficiently as well.
outputs Semantic process mining tools : core building blocks Conference Item

Process mining aims at discovering new knowledge based on information hidden in event logs. Two important enablers for such analysis are powerful process mining techniques and the omnipresence of event logs in today's information systems. Most information systems supporting (structured) business processes (e.g. ERP, CRM, and workflow systems) record events in some form (e.g. transaction logs, audit trails, and database tables). Process mining techniques use event logs for all kinds of analysis, e.g., auditing, performance analysis, process discovery, etc. Although current process mining techniques/tools are quite mature, the analysis they support is somewhat limited because it is purely based on labels in logs. This means that these techniques cannot benefit from the actual semantics behind these labels which could cater for more accurate and robust analysis techniques. Existing analysis techniques are purely syntax oriented, i.e., much time is spent on filtering, translating, interpreting, and modifying event logs given a particular question. This paper presents the core building blocks necessary to enable semantic process mining techniques/tools. Although the approach is highly generic, we focus on a particular process mining technique and show how this technique can be extended and implemented in the ProM framework tool.
Mechanisms of intracortical I‐wave facilitation elicited with paired‐pulse magnetic stimulation in humans

In order to elucidate the mechanisms underlying intracortical I‐wave facilitation elicited by paired‐pulse magnetic stimulation, we compared intracortical facilitation of I1‐waves with that of I3‐waves using single motor unit and surface electromyographic (EMG) recordings from the first dorsal interosseous muscle (FDI). We used a suprathreshold first stimulus (S1) and a subthreshold second stimulus (S2). In most experiments, both stimuli induced currents in the same direction. In others, S1 induced posteriorly directed currents and S2 induced anteriorly directed currents. When both stimuli induced anteriorly directed currents (I1‐wave effects), an interstimulus interval (ISI) of 1.5 ms resulted in extra facilitation of the responses to S1 alone. The latency of this effect was equivalent to that of the I2‐wave from S1. When S1 evoked posteriorly directed currents (I3‐wave recruitment), facilitation occurred at a latency corresponding to the I3‐wave from S1. This facilitation occurred at an ISI of 1.5 ms when both S1 and S2 flowed posteriorly, and at an ISI of approximately 3.5 ms when S1 was posteriorly and S2 was anteriorly directed. Based on these findings, we propose the following mechanisms for intracortical I‐wave facilitation. When S1 and S2 induce currents in the same direction, facilitation is produced by summation between excitatory postsynaptic potentials (EPSPs) elicited by S1 and subliminal depolarization of interneurones elicited by S2 directly. When S1 and S2 induce currents in the opposite direction, facilitation is produced by the same mechanism as above or by temporal and spatial summation of EPSPs elicited by two successive stimuli at interneurones or corticospinal neurones of the motor cortex.
An efficient on-the-fly encoding algorithm for binary and finite field LDPC codes

We present a general framework on prototype structures for efficiently encoding low density parity check codes on-the-fly. The encoding algorithm is applicable to finite field based codes and can handle a wide range of high code rates and large block lengths. This structure can be used particularly in data storage and multimedia applications with increased code rate and throughput requirements. We also establish the necessary and sufficient conditions for the existence of such encoders.
CCNA2 Is a Prognostic Biomarker for ER+ Breast Cancer and Tamoxifen Resistance

Identification of effective prognostic biomarkers and targets are of crucial importance to the management of estrogen receptor positive (ER+) breast cancer. CCNA2 (also known as CyclinA2) belongs to the highly conserved cyclin family and is significantly overexpressed in various cancer types. In this study, we demonstrated that CCNA2 had significant predictive power in distant metastasis free survival, disease free survival, recurrence free survival and overall survival of ER+ breast cancer patients. We also found that CCNA2 was closely associated with tamoxifen resistance. In addition, gene set enrichment analysis (GSEA) revealed that its expression was positively associated with genes overexpressed in endocrine therapy resistant samples. Finally, though CCNA2-Drug interaction network, we demonstrated the interactions between CCNA2 and several available cancer drugs. Overall, we suggest that CCNA2 is a biomarker for the prognosis of ER+ breast cancer and monitoring of tamoxifen efficacy. It's also a promising target for developing new strategies to prevent or even reverse tamoxifen resistance. Moreover, CCNA2 expression may help monitoring tamoxifen efficacy and directing personalized therapies. Nevertheless, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed before its application in clinical settings.
Employment, Hours of Work and the Optimal Taxation of Low Income Families

The optimal design of low income support is examined using a structural labour supply model. The approach incorporates unobserved heterogeneity, fixed costs of work, childcare costs and the detailed non-convexities of the tax and transfer system. The analysis considers purely Pareto improving reforms and also optimal design under social welfare functions with different degrees of inequality aversion. We explore the gains from tagging and also examine the case for the use of hours-contingent payments. Using the tax schedule for lone parents in the UK as our policy environment, the results point to a reformed non-linear tax schedule with tax credits only optimal for low earners. The results also suggest a welfare improving role for tagging according to child age and for hours-contingent payments, although the case for the latter is mitigated when hours cannot be monitored or recorded accurately by the tax authorities.
Robustness and device independence of verifiable blind quantum computing

Recent advances in theoretical and experimental quantum computing bring us closer to scalable quantum computing devices. Thismakes the need for protocols that verify the correct functionality of quantumoperations timely and has led to the field of quantumverification. In this paper we address key challenges tomake quantum verification protocols applicable to experimental implementations. We prove the robustness of the single server verifiable universal blind quantumcomputing protocol of Fitzsimons andKashefi (2012 arXiv:1203.5217) in themost general scenario. This includes the case where the purification of the deviated input state is in the hands of an adversarial server. The proved robustness property allows the composition of this protocol with a device-independent state tomography protocol that we give, which is based on the rigidity of CHSHgames as proposed by Reichardt et al (2013Nature 496 456–60). The resulting composite protocol has lower round complexity for the verification of entangled quantum servers with a classical verifier and, as we show, can bemade fault tolerant.
The Shirley Analyzer

* Cotton Technologist, Research and Testing Divisions, Cotton and Fiber Branch, Food Distribution Administration, U. S. Department of Agriculture. The problem of waste in cotton, its removal in the manufacturing processes, and its effect on cost and quality of cotton textiles is so well known in the industry that no discussion is required here. The very importance of this subject, however, stamps it as one worthy of extensive research. Such investigations, however, have been hampered somewhat by lack of equipment for separating lint from trash. Cotton mill cleaning equipment not only re-
Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models

New methods that exploit sparse structures arising in smart grid networks are proposed for the state estimation problem when data injection attacks are present. First, construction strategies for unobservable sparse data injection attacks on power grids are proposed for an attacker with access to all network information and nodes. Specifically, novel formulations for the optimization problem that provide a flexible design of the trade-off between performance and false alarm are proposed. In addition, the centralized case is extended to a distributed framework for both the estimation and attack problems. Different distributed scenarios are proposed depending on assumptions that lead to the spreading of the resources, network nodes and players. Consequently, for each of the presented frameworks a corresponding optimization problem is introduced jointly with an algorithm to solve it. The validity of the presented procedures in real settings is studied through extensive simulations in the IEEE test systems.
Enhanced technique for cylindrical object diameter measurement via low-cost and innovated rotational non-intrusive sensor

Precise tree diameter estimation for a lightweight and intelligent vehicle such as unmanned aerial vehicle (UAV) in a commercial farm is still an unresolved problem. A lot of UAVs and the ground vehicles (UGV) are navigated across the farm by relying on the aided of the vision sensor as well as laser scanner. All of these methods require an extremely massive image computation, bulky package dimension and some of the components are pricey. This paper evaluates the morphological technique of an innovated infrared scanner technique for cylindrical object diameter measurement which is fundamentally comprised of a low-cost infrared sensor and digital servo motor. Filter algorithm, compensating for the ascertained midpoint of the object was also developed and tested. The method is tested on three different poles with diameters of 9 cm, 11.4 cm and 16.4 cm. It is found that the filtered method, compensating for midpoint data, reduced the error to 82.92% for 9 cm, 30.37% for 11.4 cm and 6.30% for 16.4 cm, respectively.
Segmented SLAM in three‐dimensional environments

Simultaneous localization and mapping (SLAM) has been shown to be feasible in many small, two‐dimensional, structured domains. The next challenge is to develop real‐time SLAM methods that enable robots to explore large, three‐dimensional, unstructured environments and allow subsequent operation in these environments over long periods of time. To circumvent the scale limitations inherent in SLAM, the world can be divided up into more manageable pieces. SLAM can be formulated on these pieces by using a combination of metric submaps and a topological map of the relationships between submaps. The contribution of this paper is a real‐time, three‐dimensional SLAM approach that combines an evidence grid–based volumetric submap representation, a robust Rao–Blackwellized particle filter, and a topologically flexible submap segmentation framework and map representation. We present heuristic methods for deciding how to segment the world and for reconstructing large‐scale metric maps for the purpose of closing loops. We demonstrate our method on a mobile robotic platform operating in large, three‐dimensional environments. © 2009 Wiley Periodicals, Inc.
The correlation between blue straggler and binary fractions in the core of Galactic globular clusters

Context. Blue stragglers stars (BSSs) are thought to form in globular clusters by two main formation channels: $i)$ mergers induced by stellar collisions; and $ii)$ coalescence or mass transfer between companions in binary systems. The detailed study of the BSS properties is therefore crucial for understanding the binary evolution mechanisms and the complex interplay between dynamics and stellar evolution in dense stellar systems. Aims. We present the first comparison between the BSS specific frequency and the binary fraction in the core of a sample of Galactic globular clusters, with the aim of investigating the relative efficiency of the two proposed formation mechanisms. Methods. We derived the frequency of BSSs in the core of thirteen low-density Galactic globular clusters by using deep ACS@HST observations and investigated its correlation with the binary fraction and various other cluster parameters. Results. We observed a correlation between the BSS specific frequency and the binary fraction. The significance of the correlation increases by including a further dependence on the cluster's central velocity dispersion. Conclusions. We conclude that the unperturbed evolution of primordial binaries could be the dominant BSS formation process, at least in low-density environments.
Hybrid optical network architectures: bringing packets and circuits together

In recent years hybrid optical network architectures, which employ two or more network technologies simultaneously, were proposed. They aim at improving the overall network design by combining the advantages of different technologies while avoiding their disadvantages. In order to structure this developing research field, we classify such hybrid architectures based on the degree of interaction and integration of the network technologies. Also, we discuss the three classes and their main representatives regarding key characteristics, performance benefits, and realization complexity. Finally, we highlight two hybrid architectures and show their key benefits compared to the respective non-hybrid architectures through a dimensioning case study
Intelligent agent in electronic commerce-XMLFinder

E-commerce is a rapidly growing area on the Internet. There are various types of online shopping sites that help consumers find products to purchase. The intelligent agent is among the most promising technologies in recommender systems and CBR (case-based reasoning) is a highly effective mechanism for developing intelligent agents. We introduce an intelligent agent based on CBR that we developed, XMLFinder, which recommends products to users. We describe its three-tier architecture, in which XML documents take a key role in each tier, and a methodology that combines the long-term and short-term user profiles to adjust the weights according to user preferences. In this manner, it allows the efficient determination of products that meet the user's requirements.
Looking Behind the Scenes of Syntactic Dependency Corpus Annotation: Towards a Motivated Annotation Schema of Surface-Syntax in Spanish

Over the last decade, the prominence of statistical NLP applications that use syntactic rather than only word-based shallow clues increased very significantly. This prominence triggered the creation of large scale treebanks, i.e., corpora annotated with syntactic structures. However, a look at the annotation schemata used across these treebanks raises some issues. Thus, it is often unclear how the set of syntactic relation labels has been obtained and how it can be organized so as to allow for different levels of granularity in the annotation. Furthermore, it appears questionable that despite the linguistic insight that syntax is very much language-specific, multilingual treebanks often draw upon the same schemata, with little consideration of the syntactic idiosyncrasies of the languages involved. Our objective is to detail the procedure for establishing an annotation schema for surfacesyntactic annotation of Spanish verbal relations and present a restricted set of easy-to-use criteria which facilitate the decision process of the annotators, but which can also accommodate for the elaboration of a more or a less fine-grained tagset. The procedure has been tested on a Spanish 3,500 sentence corpus, a fragment of the AnCora newspaper corpus.