Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantics of Connectives Guides Referential Expectations in Discourse: An Eye-Tracking Study of Dutch and Russian

This study aims to establish whether connectives can create referential expectations in discourse, and, if so, what these expectations are based on: connective semantics or frequency distributions in language use. This was tested by comparing the processing of the connectives “and” and “but” in Dutch and Russian by means of an eye-tracking experiment using the visual world paradigm. A corpus study showed that in terms of frequency distributions, the Russian connectives are very similar to the Dutch connectives (“and” more often introduces reference maintenance and “but” more often introduces reference shift). In terms of semantics, the two languages are different, because only the Russian connectives are specified for maintenance/shift. The experimental results indicate that only Russian connectives are informative about referential development of discourse. Irrespective of frequency distributions, connectives are only used as processing instructions for referential development if reference maintenance or shift is specified in their semantics.
Information Retrieval and Web Search

§ Web crawling isn’t feasible with one machine § All of the above steps distributed § Malicious pages § Spam pages § Spider traps – incl dynamically generated § Even non-malicious pages pose challenges § Latency/bandwidth to remote servers vary § Webmasters’ stipulations § How “deep” should you crawl a site’s URL hierarchy? § Site mirrors and duplicate pages § Politeness – don’t hit a server too often Sec. 20.1. 1
Trilinos users guide.

The Trilinos Project is an effort to facilitate the design, development, integration and ongoing support of mathematical software libraries. A new software capability is introduced into Trilinos as a package. A Trilinos package is an integral unit usually developed by a small team of experts in a particular algorithms area such as algebraic preconditioners, nonlinear solvers, etc. The Trilinos Users Guide is a resource for new and existing Trilinos users. Topics covered include how to configure and build Trilinos, what is required to integrate an existing package into Trilinos and examples of how those requirements can be met, as well as what tools and services are available to Trilinos packages. Also discussed are some common practices that are followed by many Trilinos package developers. Finally, a snapshot of current Trilinos packages and their interoperability status is provided, along with a list of supported computer platforms.
A dynamic multiscale viscosity algorithm for shock capturing in Runge Kutta Discontinuous Galerkin methods

In order to improve the performance of higher-order Discontinuous Galerkin finite element solvers, a shock capturing procedure has been developed for hyperbolic equations. The Dynamic Multiscale Viscosity method, originally presented by Oberai and Wanderer [8, 9] in a Fourier Galerkin context, is adapted to the Discontinuous Galerkin discretization. The notions of diffusive model term, artificial viscosities, and the Germano identity are introduced. A general technique for the evaluation of the multiscale model term's parameters is then presented. This technique is used to perform efficient shock capturing on an one-dimensional stationary Burgers' equation with 1-parameter and 2-parameter model terms. Corresponding numerical results are shown. Thesis Supervisor: Jaime Peraire Title: Professor of Aeronautics and Astronautics
Towards an event annotated corpus of Polish

Towards an event annotated corpus of Polish The paper presents a typology of events built on the basis of TimeML specification adapted to Polish language. Some changes were introduced to the definition of the event categories and a motivation for event categorization was formulated. The event annotation task is presented on two levels – ontology level (language independent) and text mentions (language dependant). The various types of event mentions in Polish text are discussed. A procedure for annotation of event mentions in Polish texts is presented and evaluated. In the evaluation a randomly selected set of documents from the Corpus of Wroclaw University of Technology (called KPWr) was annotated by two linguists and the annotator agreement was calculated. The evaluation was done in two iterations. After the first evaluation we revised and improved the annotation procedure. The second evaluation showed a significant improvement of the agreement between annotators. The current work was focused on annotation and categorisation of event mentions in text. The future work will be focused on description of event with a set of attributes, arguments and relations.
Distributed data as a choice in PetaBricks

Traditionally, programming for large computer systems requires programmers to hand place the data and computation across all system components such as memory, processors, and GPUs. As each system can have sufficiently different compositions, the application partitioning, as well as algorithms and data structures, has to be different for each system. Thus, hardcoding the partitioning not only is difficult but also makes the programs not performance portable. PetaBricks solves this problem by allowing programmers to specify multiple algorithmic choices to compute the outputs, and let the system decide how to apply these choices. Since PetaBricks can determine optimized computation order and data placement with auto-tuning, programmers do not need to modify the programs when migrating to a new system. In this thesis, we address the problem of automatically partitioning PetaBricks programs across a cluster of distributed memory machines. It is complicated to decide which algorithm to use, where to place data, and how to distribute computation. We simplify the decision by auto-tuning data placement, and moving computation to where the most data is. Another problem is using distributed data and scheduler can be costly. In order to eliminate distributed overhead, we generate multiple versions of code for different types of data access, and automatically switch to run a shared memory version when the data is local to achieve better performance. To show that the system can scale, we run PetaBricks benchmark on an 8-node system, with a total of 96 cores, and a 64-node system, with a total of 512 cores. We compare the performance with a non-distributed version of PetaBricks, and, in some cases, we get linear speedups. Thesis Supervisor: Saman Amarasinghe Title: Professor of Computer Science and Engineering
LFA-1 dynamics on the membrane of leukocytes : a single dye tracing study

Leukocytes have the ability to rapidly switch their adhesion in response to the cell’s physiological environment. How these cells modulate their adhesiveness during the different stages of their life cycle, has been a central question for decades in immunology. Adhesion regulation has its origin at the molecular scale, where processes are dynamic, heterogenous and tightly orchestrated. To unravel these unanswered questions it is therefore of utter importance to probe biological processes in a time-dependent manner on a molecular scale. With the development of Single Particle Tracking and ultimately Single Dye Tracing, it is now possible to follow the mobility of individual biomolecules on the plasma membrane of living cells. Observation of mobility of individual biomolecules does not only provide information about the local micro-environment of the probed biomolecules, but it also gives complementary insight into the processes at work at the nanolevel. The aim of this research has been to investigate the lateral mobility of one of the most important receptors involved in cell adhesion in the immune system: the integrin receptor LFA-1 (lymphocyte function-associated antigen 1; �Ls2; CD11a/CD18). By using single molecule techniques we have been able to deepen our understanding of LFA-1 mobility and its consequences for LFA-1 affinity and avidity regulation on THP-1 monocytes and immature dendritic cells (imDCs).
A 50 GHz broad-band monolithic GaAs/AlAs resonant tunneling diode trigger circuit

This paper describes the design, circuit simulation, fabrication and testing of a 50 GHz trigger circuit using GaAs/AlAs resonant tunneling diodes. A new trigger circuit was designed to eliminate the 180/spl deg/ phase splitter used in a previous complementary input trigger circuit. Our monolithic approach, integrated GaAs/AlAs resonant tunneling diodes (in a back-to-back configuration) and a 50 /spl Omega/ coplanar waveguide, minimized the parasitic circuit elements and internal reflections from the package thus achieving high frequency operation. The circuit was able to trigger on input sinusoidal waves of input powers of -3 dBm up to 50 GHz with time jitter of less than 1 ps rms over the entire measured frequency range from 5 to 50 GHz. The upper limit of 50 GHz was imposed by our measurement system. >
SECURED CONTENT DISTRIBUTION NETWORK USING OPTIMIZED RSA

Securing data is becoming a crucial need for most internet-based applications. Whereas the problem of data confidentiality has been widely investigated, the problem of how to ensure that data, when moving among different parties, are modified only according to the stated policies has been so far not deeply investigated. At present data security is an area where corporates spend huge amount to ensure that their data and their client’s data are not tampered with. This paper proposes an approach that addresses data integrity and confidentiality in content adaptation and caching by intermediaries. This approach permits multiple intermediaries to simultaneously perform content services on different portions of the data. To enforce authenticity and integrity, standard cryptographic primitives such as public keys generated using optimized RSA are used for digitally signing the data. The optimized RSA approach reduces the processing time, computational overheads and key storage requirements which are the major drawbacks of RSA. The protocol defined for this project supports decentralized proxy, key management and flexible delegation of services. The experimental results show that this approach is efficient and minimizes the amount of data transmitted across the network. Ultimately, this provides a trusted way of transporting data without causing a performance hit.
Intermediate Spoofing Strategies and Countermeasures

Intermediate spoofing can impact most off-the-shelf Global Navigation Satellite Systems (GNSS) receivers, therefore low cost detection of such spoofing is very important to protect the reliability of the GNSS receivers used in critical safety and financial applications. This paper presents two strategies to analyze attacks by intermediate spoofing attackers to identify the weaknesses of such attacks. The analyses lead to a code and carrier phase consistency detection method with simulation results showing that this method can indicate the receiver when spoofing has occurred. The method can be used by most receivers, is inexpensive, and requires only a small software upgrade.
Security Enhanced Communications in Cognitive Networks

With the advent of ubiquitous computing and Internet of Things (IoT), potentially billions of devices will create a broad range of data services and applications, which will require the communication networks to efficiently manage the increasing complexity. Cognitive network has been envisioned as a new paradigm to address this challenge, which has the capability of reasoning, planning and learning by incorporating cutting edge technologies including knowledge representation, context awareness, network optimization and machine learning. Cognitive network spans over the entire communication system including the core network and wireless links across the entire protocol stack. Cognitive Radio Network (CRN) is a part of cognitive network over wireless links, which endeavors to better utilize the spectrum resources. Core network provides a reliable backend infrastructure to the entire communication system. However, the CR communication and core network infrastructure have attracted various security threats, which become increasingly severe in pace with the growing complexity and adversity of the modern Internet. The focus of this dissertation is to exploit the security vulnerabilities of the state-of-the-art cognitive communication systems, and to provide detection, mitigation and protection mechanisms to allow security enhanced cognitive communications including wireless communications in CRNs and wired communications in core networks. In order to provide secure and reliable communications in CRNs: first, we incorporate security mechanisms into fundamental CRN functions, such as secure spectrum sensing techniques that will ensure trustworthy reporting of spectrum reading. Second, as no security mechanism can completely prevent all potential threats from entering CRNs, we design a systematic passive monitoring framework, SpecMonitor, based on unsupervised machine learning methods to strategically monitor the network traffic and operations in order to detect abnormal and malicious behaviors. Third, highly capable cognitive radios allow more sophisticated reactive jamming attack, which imposes a serious threat to CR communications. By exploiting MIMO interference cancellation techniques, we propose jamming resilient CR communication mechanisms to survive in the presence of reactive jammers. Finally, we focus on protecting the core network from botnet threats by applying cognitive technologies to detect network-wide Peer-to-Peer (P2P) botnets, which leads to the design of a data-driven botnet detection system, called PeerClean. In all the four research thrusts, we present thorough security analysis, extensive simulations and testbed evaluations based on real-world implementations. Our results demonstrate that the proposed defense mechanisms can effectively and efficiently counteract sophisticated yet powerful attacks. To my beloved wife, Luna Le Lu, and my parents Yaqin Chen and Shifu Yan
Actinide Coordination and Organometallic Complexes with Multidentate Polyamido Ligands

Abstract Amido-based ligand sets have found considerable use in the active and growing area of actinide chemistry, forming highly reactive and unusual actinide-containing complexes as a result of their strong π-donation capabilities and ease of steric and electronic tuning. This review will focus on the use of multidentate multi-amido based ligands with thorium and uranium centres including diamido, diamido-donor and triamido-amine ligand frameworks. Actinide complexes of related nitrogen-based multidentate ligand sets such as amidinates, β-diketimides, poly(pyrazolyl)borate and polypyrrolide ligands will also be surveyed. For each ligand the synthesis and reactivity of noteworthy complexes are described and where appropriate, potential applications have also been presented.
Sparse Incremental Delta-Bar-Delta for System Identification

Metalearning algorithm learns the base learning algorithm, targeted for improving the performance of the learning system. The incremental delta-bar-delta (IDBD) algorithm is such a metalearning algorithm. On the other hand, sparse algorithms are gaining popularity due to their good performance and wide applications. In this paper, we propose a sparse IDBD algorithm by taking the sparsity of the systems into account. Thenorm penalty is contained in the cost function of the standard IDBD, which is equivalent to adding a zero attractor in the iterations, thus can speed up convergence if the system of interest is indeed sparse. Simulations demonstrate that the proposed algorithm is superior to the competing algorithms in sparse system identification.
A blind steganography method based on histograms on video files

Abstract Several techniques of data embedding and data hiding have been proposed and developed especially during the last two decades due to continually increasing needs of secure communication. Still image, audio and video files are the most promising digital mediums for steganography applications. However, video files have a vast potential for embedding secret data compared to other alternatives in terms of storage size. Selecting the most appropriate pixels is of great importance in the procedure of embedding secret data into video files. Unsuccessful pixel selection can trigger some negative spatial and/or temporal awareness, which eventually causes an ineffective data embedding process. In this paper, we have proposed and developed an effective blind steganography method, which uses an appropriate pixel selection mechanism, based on histogram techniques. The method we have proposed proves its success by means of perceptibility of the secret data in both spatial and temporal domains.
Fortuna: Cryptographically Secure Pseudo-Random Number Generation In Software And Hardware

Fortuna is a pseudo-random number generation algorithm, recently published by Ferguson and Schneier, The algorithm is specifically designed to be cryptographically secure from known attacks. This paper presents a software implementation of Fortuna on a PC, including acquisition of entropy from commonly available sources, and statistical analysis of the results. Using an FPGA, which offers increased security, hardware implementation aspects are also studied and contrasted with the software version
Named entity recognition from scratch on social media

With the extensive amount of textual data flowing through social media platforms, the interest in Information Extraction (IE) on such textual data has increased. Named Entity Recognition (NER) is one of the basic problems of IE. State-of-the-art solutions for NER face an adaptation problem to informal texts from social media platforms. In this study, we addressed this generalization problem with the NLP from scratch idea that has been shown to be successful for several NLP tasks on formal text. Experimental results have shown that word embeddings can be successfully used for NER on informal text.
Model-Based Software Quality Assurance with the Architecture Analysis and Design Language

Model-based software quality assurance (MB-SQA) provides a rigorous framework for the verification and validation of software systems through the systematic modeling and analysis of formal architecture representations. This paper describes the results of applying an MB-SQA practice framework that utilizes the Architecture Analysis and Design Language (AADL) to JPL’s Mission Data System (MDS) reference architecture. The MDS is a unified reference architecture for space mission flight, ground, and test systems. In the case study, the AADL assurance practice framework and several AADL-based analyses were applied to the evaluation of critical quality attributes of the MDS reference architecture as well as an MDS adaptation for the control of a heated camera. The results of the case study demonstrate the utility of the practice framework and the AADL-based analyses in addressing (1) the modeling of key MDS architectural themes and (2) quality assurance with respect to performance, particularly flow latency.
Providing Distinguish Access Levels to Encrypted Cloud Databases

Outsourcing sensitive and crucial data in the hands of a cloud provider should come with the guarantee of security and seamless availability for data at rest, in motion, and in use. Several alternatives exist for storage services, while data confidentiality solutions for the database as a service paradigm are still immature. We propose a novel architecture that integrates cloud database services with data confidentiality and the possibility of executing concurrent operations on encrypted data. This is the first solution supporting geographically distributed clients to connect directly to an encrypted cloud database, and to execute concurrent and independent operations including those modifying the database structure. The proposed architecture has the further advantage of eliminating intermediate proxies that limit the elasticity, availability, and scalability properties that are intrinsic in cloud-based solutions. The efficacy of the proposed architecture is evaluated through theoretical analyses and extensive experimental results based on a prototype implementation subject to the TPC-C standard benchmark for different numbers of clients and network latencies.
Abstraction and simulation for strategic design-space exploration in reconfigurable computing

Due to recent trends in computing that favor device technologies and applications exploiting explicit parallelism to achieve greater performance, reconfigurable computing (RC) systems consisting of highly parallel applications executing on platforms featuring reconfigurable devices such as FPGAs are becoming an increasingly important option for accelerating applications in high-performance and embedded computing. Unfortunately, the time and difficulty associated with developing applications for RC platforms is often prohibitive, making it difficult to exploit the potential gains in performance and power savings that RC can offer. In order to facilitate RC productivity, better concepts and tools are needed to allow designers to plan and analyze their designs before coding a specific (and possibly fruitless) implementation, a process we call formulation. The research presented here defines a formal framework and presents a set of techniques to address the need for better RC formulation, which includes (1) a script-based discrete-event simulation framework for rapid analysis of RC systems, (2) an abstract modeling language for conveniently representing RC systems that can be integrated with existing prediction and analysis methods, and (3) an algorithm for automated scheduling and partitioning of applications onto scalable RC platforms. Case studies show the simulation framework to provide performance prediction results across multiple applications and platforms with errors of less than 10% and in a fraction of the time that traditional functional simulators require. The abstract modeling framework is demonstrated in modeling a number of RC systems and serves as an effective interface to the simulation framework. The automated scheduling algorithm for scalable RC systems efficiently provides users with near-optimal partitions and schedules of heterogeneous tasks graphs mapped to potentially large-scale distributed RC-based clusters. Combined, these techniques allow RC designers to efficiently model, analyze, and document their designs early in the development process, which is projected to provide large improvements in overall productivity and thus expand the usage of RC technologies.
A hybrid differential evolution algorithm for a two-stage flow shop on batch processing machines with arbitrary release times and blocking

Batch processing machines (BPMs) have important applications in a variety of industrial systems. This paper considers the problem of scheduling two BPMs in a flow shop with arbitrary release times and blocking such that the makespan is minimised. The problem is formulated as a mixed integer programming model. Subsequently, a hybrid discrete differential evolution (HDDE) algorithm is proposed. In the algorithm, individuals in the population are first represented as discrete job sequences, and mutation and crossover operators are applied based on the representation. Second, after using the first-fit rule to form batches, a novel least idle/blocking time heuristic is developed to schedule the batches in the flow shop. Furthermore, an effective local search technique is embedded in the algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by comparing its results to a commercial solver (CPLEX), a genetic algorithm and a simulated annealing algorithm. Computational experiments demonstrate the superiority of the HDDE algorithm in terms of solution quality, robustness and run time.