Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel capacity analysis of 2D barcodes: QR Code and CQR Code-5

This paper presents an encoder and decoder channel capacity study on the QR Code (Quick Response Code) and CQR Code-5 (5-color Colored Quick Response Code) transmission environment. Our work shows that the QR Code and CQR Code-5 data storage and retrieval is an asymmetric and no erasure channel of information transmission, where each two-dimensional barcode channel counts with a maximum number of distinguishable symbols. This channel capacity study uses mutual information theory and consider that the QR Code and CQR Code-5 input symbols are mapped into a sequence that produces the output sequence of each channel. The output sequence has a distribution that depends on the input sequence and the conditional probability of every input and output symbol, where is possible to reconstruct the input symbols at the output with low error probability in function of the software robustness of each two-dimensional barcodes.
Chinese spoken language understanding with conditional random fields

This paper presents a new approach to spoken language understanding tagging for Chinese texts using conditional random fields (CRFs). SLU for spoken dialog system, especially the slot-filling problem is solved as a sequential labeling problem. The experimental results show that this approach has good performance and is feasible for the restricted domain oriented Chinese spoken language understanding.
An experimental estimation of latency sensitivity in multiplayer Quake 3

Quantifying the latency sensitivity of potential customers/players is critical for Internet-based game providers when planning the network placement of their game servers. Two Quake 3 servers were placed at different locations on the Internet in 2001, and instrumented to gather median latency information on every player who played over a multi-month period. Server logfiles showed an active yet distinct player population on each server. The median latency distributions suggest players actively prefer Quake 3 servers less than 150 to 180 milliseconds from the player's location. Quake 3 is often played as a multiplayer, Internet-based, highly interactive "first person shooter" game. Although Quake 3 is nowhere near as popular as games such as half- life: counterstrike, these results provide a useful ball-park indicator of latency sensitivity for this class of highly interactive online games.
A SLA-based interface for security management in cloud and GRID integrations

Cloud Computing is a new computing paradigm. Among the incredible number of challenges in this field two of them are considered of great relevance: SLA management and Security management. The level of trust in such context is very hard to define and is strictly related to the problem of management of SLA in cloud applications and providers. In this paper we will try to show how it is possible, using a cloud-oriented API derived from the mOSAIC project, to build up an SLA-oriented cloud application which enables the management of security features related to user authentication and authorization to an Infrastructure as a Service (IaaS) Cloud Provider. As Cloud Provider we will adopt the perf-Cloud solution, which uses GRID-based solutions for security management and service delivery. So the proposed solution can be used in order to build up easily a SLA-based interface for any GRID system.
SPA Resistant Scalar Multiplication Based on Addition and Tripling Indistinguishable on Elliptic Curve Cryptosystem

This paper analyzes the Symbolic Ternary Form (STF) scalar multiplication algorithm and binary scalar multiplication algorithm computation, compared with binary scalar multiplication algorithm, the efficiency of STF scalar multiplication algorithm is increased by 4.6% in an average, there is a corresponding advantage. For this reason, we improve the structure of STF scalar multiplication algorithm, and make the algorithm perform more "smooth" by constructing points plus (A) and the triple point (T) operation indistinguishable and thus resist the simple power analysis attacks, and propose Highest-weight Symbolic Ternary Form (HSTF), which make a scalar k transform into the highest-weight form, so that every cycle has a fixed pattern to resist SPA attack. With respect to anti-SPA binary scalar multiplication algorithm, the average efficiency enhances 17.7%.
On timing-independent false path identification

This paper is concerned with finding timing-independent false paths that cannot be sensitized under any signal arrival time condition in integrated circuits. Existing techniques regard a path as a true path as long as a vector pair can be found to sensitize it. This is rather pessimistic since such a path might be activated only with illegal states in the circuit and hence it is actually functionally-unsensitizable. In this paper, we develop novel techniques to take the above issue into consideration when identifying false paths, which facilitates us to find much more false paths than conventional techniques. Experimental results on benchmark circuits demonstrate the effectiveness of the proposed methodology.
Group B Streptococcus Induces Neutrophil Recruitment to Gestational Tissues and Elaboration of Extracellular Traps and Nutritional Immunity

Streptococcus agalactiae, or Group B Streptococcus (GBS), is a gram-positive bacterial pathogen associated with infection during pregnancy and is a major cause of morbidity and mortality in neonates. Infection of the extraplacental membranes surrounding the developing fetus, a condition known as chorioamnionitis, is characterized histopathologically by profound infiltration of polymorphonuclear cells (PMNs, neutrophils) and greatly increases the risk for preterm labor, stillbirth, or neonatal GBS infection. The advent of animal models of chorioamnionitis provides a powerful tool to study host-pathogen relationships in vivo and ex vivo. The purpose of this study was to evaluate the innate immune response elicited by GBS and evaluate how antimicrobial strategies elaborated by these innate immune cells affect bacteria. Our work using a mouse model of GBS ascending vaginal infection during pregnancy reveals that clinically isolated GBS has the capacity to invade reproductive tissues and elicit host immune responses including infiltration of PMNs within the choriodecidua and placenta during infection, mirroring the human condition. Upon interacting with GBS, murine neutrophils elaborate DNA-containing extracellular traps, which immobilize GBS and are studded with antimicrobial molecules including lactoferrin. Exposure of GBS to holo- or apo-forms of lactoferrin reveals that the iron-sequestration activity of lactoferrin represses GBS growth and viability in a dose-dependent manner. Together, these data indicate that the mouse model of ascending infection is a useful tool to recapitulate human models of GBS infection during pregnancy. Furthermore, this work reveals that neutrophil extracellular traps ensnare GBS and repress bacterial growth via deposition of antimicrobial molecules, which drive nutritional immunity via metal sequestration strategies.
Inhibition of nucleolar protein nucleolin by electroporation with anti‐nucleolin antibodies results in an increase of the nucleolar size

Electroporation of exponentially growing human larynx epidermoid carcinoma cells (HEp‐2) with a serum against nucleolin, one of the most abundant non‐histone nuclear proteins, has shown, 24 h after electroporation, a significant increase in the size of the nucleolus of these cells compared with normal HEp‐2 cells (non‐electroporated) and electroporated HEp‐2 cells in the absence of antinucleolin serum (P < 0.01). Image analysis evaluation of the different nucleolar components proved a major contribution of the dense fibrillar component to the total nucleolar size in cells electroporated with anti‐nucleolin antibodies, more than that corresponding to the dense fibrillar component in cells from any of the control groups (P < 0.01), indicating that the reported increase in nucleolar size was due to a marked enlargement of the dense fibrillar regions. These results, in agreement with previous biochemical and molecular biology studies, suggest a pivotal role for nucleolin in pre‐rRNA processing and constitute morphological evidence supporting this role. Following nucleolin inhibition, impaired pre‐rRNA processing might result in an accumulation of this molecular species in the dense fibrillar component of the nucleolus, where pre‐rRNA is first present.
Architecting noncooperative networks

In noncooperative networks users make control decisions that optimize their own performance measure. Focusing on routing, we devise two methodologies for architecting noncooperative networks, that improve the overall network performance. These methodologies are motivated by problem settings arising in the provisioning and the run time phases of the network. For either phase, Nash equilibria characterize the operating point of the network. The goal of the provisioning phase is to allocate link capacities that lead to systemwide efficient Nash equilibria. In general, the solution of such design problems is counterintuitive, since adding link capacity might lead to a degradation of user performance. We show that, for systems of parallel links, such paradoxes cannot occur and the optimal solution coincides with the solution in the single-user case. We derive some extensions to general network topologies. During the run time phase, a manager controls the routing of part of the network flow. The manager is aware of the noncooperative behavior of the users and makes its routing decisions based on this information while aiming at improving the overall system performance. We obtain necessary and sufficient conditions for enforcing all equilibrium that coincides with the global systemwide optimum, and indicate that these conditions are met in many cases of interest.
Relationship Queries on Extended Knowledge Graphs

Entity search over text corpora is not geared for relationship queries where answers are tuples of related entities and where a query often requires joining cues from multiple documents. With large knowledge graphs, structured querying on their relational facts is an alternative, but often suffers from poor recall because of mismatches between user queries and the knowledge graph or because of weakly populated relations. This paper presents the TriniT search engine for querying and ranking on extended knowledge graphs that combine relational facts with textual web contents. Our query language is designed on the paradigm of SPO triple patterns, but is more expressive, supporting textual phrases for each of the SPO arguments. We present a model for automatic query relaxation to compensate for mismatches between the data and a user's query. Query answers -- tuples of entities -- are ranked by a statistical language model. We present experiments with different benchmarks, including complex relationship queries, over a combination of the Yago knowledge graph and the entity-annotated ClueWeb'09 corpus.
Exploring Mobile Gaming Revenues: The Price Tag of Impatience, Stress and Release

The mobile gaming industry is growing at a rapid pace. Smartphones, tablets and other mobile devices are new channels to deliver games to customers. However, since the birth of Internet, users have been accustomed to getting things for free. How then are mobile game companies able to make billions € in revenue? What are the main drivers of profitability in this sector? Our objective is to dissect the freemium pricing strategy that is frequently used in the mobile gaming sector. With the help of the case study of Gameloft, we explore the method and the path for converting free into profit by playing with the users' frustration and stress.
Reflective Language Teaching

Preface 1. Reflective Language Teaching 2. Self-Reflection 3. Teacher Beliefs and Practices 4. Teacher Narrative 5. Teacher Metaphors and Maxims 6. Classroom Communication 7. Reflecting On Teaching Young Learners 8. Action Research 9. Teaching Journals 10. Teacher Development Groups 11. Classroom Observations 12. Collegial Friendships 13. Concept Mapping 14. Online Reflection 15. Professional Development Through Reflective Practice 16. The Importance of Reflective Practice For Effective Teaching References Index
Splusplus: A Feature-Rich Two-stage Classifier for Sentiment Analysis of Tweets

This paper describes our sentiment classification system submitted to SemEval-2015 Task 10. In the message-level polarity classification subtask, we obtain the highest macroaveraged F1-scores on three out of six testing sets. Specifically, we build a two-stage classifier to predict the sentiment labels for tweets, which enables us to design different features for subjective/objective classification and positive/negative classification. In addition to n-grams, lexicons, word clusters, and twitter-specific features, we develop several deep learning methods to automatically extract features for the message-level sentiment classification task. Moreover, we propose a polarity boosting trick which improves the performance of our system.
Drift velocity estimation of ionospheric disturbance using GPS observations

The Ground-Based Augmentation System (GBAS) based on the global positioning system (GPS) is used for positioning accuracy improvement of the aircraft landing. However, the ionospheric irregularity can cause irregular electron density that affects the accuracy of GBAS system. In this work, we analyze the drift velocity of ionospheric irregularity or plasma bubble phenomenon by using the correlation time of slant total electron content (STEC) from two GPS receivers that are located near Suvarnabhumi airport, Thailand. The data on September 1st, 2011 with the plasma bubble occurrence is analyzed. The result shows the drift velocity of plasma bubbles is about 108 meterspersecond (m/s).
GOtoGene: A Method for Determining the Functional Similarity among Gene Products

We present in this paper novel techniques that determine the semantic relationships among genes and gene products. We implemented these techniques in a middleware system called GOtoGene, which resides between user application and Gene Ontology database. Given a set S of genes, GOtoGene would return another set S' of genes, where each gene in S' is semantically related to each gene in S. The framework of GOtoGene refines the concept of Lowest Common Ancestor by defining the concept of Semantically Relevant Lowest Common Ancestor using the concept of existence dependency. We evaluated GOtoGene experimentally and compared it with three other methods. Results showed marked improvement.
Whiskered tori with prefixed frequencies and Lyapunov spectrum

A classical mechanics problemthe existence of whiskered tori for an almost integrable Hamiltonian systemis analyzed with techniques reminiscent of the quantum field theoryfollowing the strategy developed in recent worksThe system consists of a collection of rotators interacting with a pendulum via a small potential depending only on the angle variablesThe proof of the existence of the stable and unstable manifolds (‘whiskers’) of the rotators invariant tori corresponding to dio- phantine rotation numbers is simplified by setting the Lyapunov spectrum to prefixed values via the introductionin the Hamiltonian functionof‘counterterms7 depending on the strength of the interaction; this is a feature usual in quantum field theoryand emphasizes the analogy between the field theory and the KAM framework pointed out already in the mentioned works
Control of humanoid robot via motion-onset visual evoked potentials

This paper investigates controlling humanoid robot behavior via motion-onset specific N200 potentials. In this study, N200 potentials are induced by moving a blue bar through robot images intuitively representing robot behaviors to be controlled with mind. We present the individual impact of each subject on N200 potentials and discuss how to deal with individuality to obtain a high accuracy. The study results document the off-line average accuracy of 93% for hitting targets across over five subjects, so we use this major component of the motion-onset visual evoked potential (mVEP) to code people's mental activities and to perform two types of on-line operation tasks: navigating a humanoid robot in an office environment with an obstacle and picking-up an object. We discuss the factors that affect the on-line control success rate and the total time for completing an on-line operation task.
Listener-Inspired Automated Music Playlist Generation

The objective of this PhD research is to deepen the understanding of how people listen to music and construct playlists. We believe that further insights into such mechanisms can lead to enhanced music recommendations. We research on the exploitation of user-generated data in the context of on-line music services, since it constitutes a rich and increasing source of information of user behavior. The research carried out so far has centered on the scenario of producing a single artist recommendation. Concretely, in this paper we show how to mitigate the cold-start problem for new artists, elaborating on our findings on the combined effect of users' listening histories and users' tagging activity. As future research, we will investigate how improved techniques to exploit user-generated data can also be applied to the task of producing sequential recommendations, like playlists. We are particulary interested in creating music playlists similarly as users would do, and in finding mechanisms to make such music streams adapt to users' feedback on-line.
A Validation And Performance Evaluation Tool for ProtoNoC

Simulating a NoC at the RTL level can be extremely complex, the simulation of a relatively small NoC, such as a 4 times 4 mesh, can involve observing thousands of wires on a standard HDL simulator. The facilities of JHDL to extend the simulator environment together with the possibility to fully analyze the runtime object model of the circuit offers a great opportunity to develop modules that address complex features like high level validation and performance evaluation. We present a developed tool that allows defining a NoC architecture models with some flexibility. Traffic generation processes described with high level language can be added to the model. Simulation can be used to validate the system operation on realistic conditions and get accurate values of expected performance
Feasibility Testing of the Alert for AFib Intervention

Improving early detection and treatment of atrial fibrillation (AF) is critical because untreated AF is a major contributor to stroke and heart failure. We sought to generate knowledge about the feasibility of conducting a randomized controlled trial to test the effect of the Alert for AFib intervention on knowledge, attitudes, and beliefs about treatment-seeking for signs and symptoms of AF. Adults ≥65 years old (96% White) at risk for developing AF were randomized to receive the Alert for AFib intervention (n = 40) or an attention control session (n = 40). Feasibility goals for recruitment, participant retention, adherence, perceived satisfaction and burden, and intervention fidelity were met. From baseline to study completion, knowledge (p = .005) and attitudes (p < .001) about treatment-seeking improved more in the intervention group compared with the control group. Results support testing the effectiveness of the Alert for AFib intervention in a large trial.
Spike-and-Slab Approximate Message-Passing Recovery for 1-D Piecewise-Constant Signals

This paper proposes a fast AMP algorithm for solving a compressed sensing (CS) recovery problem which includes signal sparsity in finite difference (FD). The proposed AMP algorithm, named ssAMP-1D, is fully scalable, providing low-computationality and phase transition (PT) competitive to the state-of-the-art performance. The key behind the ssAMP1D construction is based on a sum-product rule over a factor graph consisting of two types of the factor nodes: the “s-factors” describing the FD sparsity, the “m-factor” being related to the CS measurement generation. In the sum-product setup, we have imposed the spike-and-slab prior on each s-factor for the FD sparsifying task, mimicking sparsity enhancing ability of the l0minimization. The ssAMP-1D algorithm is derived from the sumproduct rule where the Gaussian approximation with the large system limit and the first-order approximation are applied to the message update with the m-factors, and a proposed method is used to simplify the message update with the s-factors. Extensive empirical results confirm the state-of-the-art performance of the proposed ssAMP-1D, in both PT performance and CPU runtime, compared to the recent algorithms: the existing two AMPs, TVAMP and GrAMPA, and the two non-AMPs, EFLA and TV-CP.
Browsing the Web Using Stacked Three-Dimensional Sunbursts to Visualize Term Co-Occurrences and Multimedia Content

We present a novel visualization approach that extends the Sunburst technique to the third dimension, which allows for encoding additional data in the height of each arc segment. By stacking a number of such 3D-Sunbursts, we build a user interface for browsing collections of web pages. We apply techniques for web content indexing of multimedia data (text, audio, image, video) and text analysis to create a UI where each layer of the Sunburst stack represents a specific multimedia content type. We call this user interface the Co-Occurrence Browser (COB) and demonstrate its usability on a collection of web pages related to music artists.
Querying the Linking File System

The Linking File System (LiFS) is an experimental file system being developed by UC Santa Cruz. It allows users to define relational links between files with a semantic meaning. This paper explores the possibilities of a query language to find information in LiFS, while taking advantage of links. The results show that a very powerful language can be defined and implemented. The implementation uses rules to “walk” the directory structure to search for files. This style of searching is very inefficient in larger file systems, even when the search is restricted to a small subdirectory. A new searching idea will be needed to implement this query language efficiently.
Comparative performance of TCP variants on self-similar traffic

Network traffic of Internet will continue to expand in terms of both volume and users, and transmission control protocol (TCP) is accounting for more than 90% the Internet traffic. In addition to this, it is well known that Internet traffic exhibits self-similarity, which cannot be described by traditional Markovian models such as the Poisson process. In this paper we focus on experimental quantitative comparisons of four TCP variants namely Tahoe, NewReno, Vegas, and SACK running over self-similar traffic. With the aid of network simulator, NS2, aggregated network traffic of self-similarity behavior is simulated and will act as the background traffic. The impact of one TCP microflow will be observed, and data analysis such packets dropped, packets retransmitted, throughput, and the behavior of the data received over time is analyzed. In measuring the degree of self-similarity we employed optimization method to determine Hurst parameter, H. From our analysis, Vegas out performed other TCP variants at high traffic load and all TCP variants tend to demonstrate self-similar traffic flow even though initially the departure rate of TCP packets is constant.