Miracle-dz/UniFAR-FTUs huggingface dataset:
Auto Recognition of Person Names from Chinese Texts Based on Support Vector Machines

Based on the characteristics of person names in Chinese texts,a method of automatic recognition of Chinese person names using support vector machines(SVMs) is proposed.The character itself,character-based POS tag,the information whether a character appears in a last names table,the probability of a character’s occurrence in person names and context information are extracted as the features of the vectors.Each sample is represented by a long binary vector,and thus a training set is established.The machine learning models of automatic identification of person names are obtained by testing polynomial Kernel functions.The results show that the models are efficient in identifying person names from Chinese texts.The recall,precision and F-measure are up to 92.14%,96.43% and 94.24% respectively in open test.
A Transaction Cost Perspective of Alliance Portfolio Diversity

Alliance portfolio diversity (APD) helps firms access diverse capabilities and knowledge. APD can also increase transaction costs, but it is unknown whether and how transaction cost theory’s (TCT’s) insights about hierarchical integration operate at the portfolio level. We adapt TCT to the portfolio level to suggest that the transaction costs from APD encourage integration into alliance partners’ industries, and we introduce the concept of shared‐specific investments to pinpoint one source of transaction costs within portfolios and predict which industries will be integrated. Using data from 1996–2013 on S&P 500 firms, we find evidence in support of our theorising. Juxtaposing results with other theoretical perspectives suggests that TCT offers complementary insights about which activities to perform in the firm versus the alliance portfolio.
Approximate outage probability expressions for evaluating cooperative communications

Cooperative communication systems have emerged as a signiflcant concept to im- prove reliability and throughput in wireless systems. Some existing cooperative diversity protocol are shown to increase the diversity order, allowing single-antenna nodes to cooperate and achieve performance like a real MIMO system. In this paper, we focus on improving the precision of analysis of Amplify-and-Forward (AF), Decode-and-Forward (DF) in terms of outage probabil- ity. Especially, we derive some approximate expressions of outage probability for these three relaying protocols. The approximate expressions are proved to be better than some existing ones, in other words our approximations are much closer to the truth value. In our research, we use the outage probabilities calculated by Monte Carlo Method (MCM) as the reference for the reason that they are the nearest to the truth value. We show analytically and experimen- tally that our expressions are better than some existing approximate expressions in low Signal to Noise Ratios (SNR) as well. The simulation results and our analysis can prove the accuracy and concision of the expressions. Besides, the approximate expressions are useful to the analysis of outage probability when we investigate the performance of relaying protocols.
Tracing the Sources of South Australian Economic Slumps

This article quantitatively investigates economic fluctuations in South Australia from 1990&#8211;2014. In particular, the study applies the business cycle accounting method to decompose the economic fluctuations into their sources. The main findings suggest that the low efficiency wedge was the primary source of South Australian economic slumps. Moreover, it is shown that infrastructural and R&amp;D expenditures are important factors in explaining the variation of the efficiency wedge. This conforms with the fact that the South Australian Government is keen to support its development through the economic stimulus plan. Trade openness may also be a contributor.
System Design A Practical Guide With Specc

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SAMENSPRAAK. ACQUIRING AND IMPLEMENTING PHONETIC KNOWLEDGE

This is the slightly adapted English version of my farewell lecture that I presented in Dutch on June 3rd, 2005 when I formally retired from the University of Amsterdam. It gives a good overview of the cooperative work I did between 1982 and 2005 with my colleague staff members, post-docs and Ph.D. students. Samenspraak, the first word in my title, is a Dutch word implying both speaking as well as working together. The emphasis in this contribution is on acquiring phonetic knowledge via phonetics research, via speech databases, as well as in studying phonetics as a student, in order to apply and implement that knowledge in efficient speech communication, in basic research and in specific applications, as well as to improve efficient training in phonetics.
The Design and Implementation of SLIC Superpixel Algorithm

The concept of superpixel firstly appeared in the research of image segmentation, Superpixel algorithms are designed to segment an image into a series of blocks, all these blocks are comprised of a number of pixels. By composing a superpixel network instead of making a pixel network, we can deal with every superpixel as a separate entity. By this means, we reduce the time complexity of the original algorithms which deal with pixels one by one. And always we could get better results via improved algorithms aimed at superpixels. The essence of superpixel segmentation is an abstraction of basic information in an image. One of the best superxiel segmentation algorithm is SLIC algorithm, we will introduce it and implement it by C programming language.
Patent content analysis method based on LDA topic model

Topic model is an effective modeling method for extracting implied themes in large- scale text. In this paper,Latent Dirichlet Allocation( LDA) topic model is introduced to patent content analysis for patent theme extraction,which solves the problems in previous patent subject classification,such problems as too rough classifications,lack of time- effectiveness and scientific nature,etc. And then,based on the original LDA model,an extended institution- topic model is developed in this paper.By joint modeling of patent subject and object,the internal relationships between patent themes and corresponding institutions is identified. Finally,a case study is carried out in the LTE technology of the telecommunication industry,and it is found out that these models can be used effectively for patent subject classification and identifying competition situation of patent subjects under each corresponding theme.
The limited politicization of European integration in Italy: lacking issue clarity and weak voter responses

Abstract This article analyzes the politicization of European integration in Italy. Has the euro crisis catalyzed a new electoral supply, which may have been matched by voters’ responses? After the crisis, Italian parties have increased their entrepreneurial efforts to prime EU issues into the political debate, trying to win over votes. This pattern may have led to a full politicization of European integration. To study the transformations in party strategies and voting behavior, I analyze the fluctuations in EU issue entrepreneurship and EU issue voting between 2009 and 2014. The findings reveal mixed results: parties have actually developed new strategies on EU issues, but without significantly changing voter preferences along the pro/anti-European dimension.
A protective mechanism using variable-instruction-sets encryption for Java applications in mobile terminal platforms

In some mobile terminal platforms, such as Android, OMS (Open Mobile System), etc, the compiled Java application files could be easily decompiled, so the security of source codes in Java application is a problem. In this paper, we analyze traditional protective methods for Java application files. Then a class-loading mechanism using variable-instruction-sets encryption is raised. Variable-instruction-sets encryption is a highly reliable and efficient algorithm which is applied on instruction level. Test results on prototype machine show that this mechanism is effective.
Real Time Violence Detection in Video

We propose a Violent Flow (ViF) variation using Horn-Schunck instead of Iterative Reweighted Least Squares (IRLS) as optical flow algorithm and Support Vector Machine (SVM) as a classifier, we evaluated the performance in different datasets. In Hockey dataset Horn-Schunck had a better performance, but in Movies and Crowded datasets IRLS was better. We also evaluated the computational cost processing two frames, Horn-Schunck had a very low cost of 0.25 seconds against 7.80 seconds of IRLS enabling its use in real time.
Associative activation during interrupted task performance: a mixed methods approach to understanding the overall quality effects of interruptions

ABSTRACT The objectives of this research were to (1) explore whether goal-activation models of procedurally based interrupted task performance can be applied to content production, and if not, (2) develop a new theoretical account, and (3) provide support for that theory. Experiment 1 found that interruptions during planning resulted in less developed plans, and that available theoretical models could not account for performance. Experiment 2 leveraged Verbal Protocol Analysis to explore the cognitive mechanisms underlying interrupted task performance on a content production task. We found support for a combination of processes: (1) cues and environmental context, and (2) task activation levels. These results suggested a spreading activation account of interrupted task performance. Experiment 3 provided further support for spreading activation by comparing short and long interruptions. These results have broad implications for moving our understanding of interrupted task performance forward by expanding our understanding to non-procedural task performance.
Identification of New Genes Related to Virulence of Xanthomonas axonopodis Pv. Citri during Citrus Host Interactions

A mutant library of the bacterium Xanthomonas citri subsp. citri strain 306 pathotype A (Xac), the causative agent of most aggressive Asiatic type A citrus canker, was screened regarding altered canker symptoms after inoculations into Citrus sinensis and Citrus limonia host leaves. Twenty-six mutants have shown phenotypic virulence changes and have respectively knocked out gene identified by sequencing. In vivo growth curves were obtained for nine mutants to quantify how the mutations could affect pathogen’s adaptability to growth inside and attack host plant infected tissue. Among identified genes in mutated strains, we could find those that until now had not been reported as being involved in Xac adaptation and/or virulence, such as predicted to encode for xylose repressor-like protein (XACΔxylR), Fe-S oxidoredutase (XACΔaslB), helicase IV (XACΔhelD), ubiquinol cytochrome c oxidoreductase iron-sulfur subunit (XACΔpetA), chromosome partitioning protein (XACΔparB) and cell division protein FtsB (XACΔftsB), in addition to genes predicted to encode for hypothetical proteins. The new genes found in this study as being relevant to adaptation and virulence, improve the understanding of Xac fitness during citrus plant attack and canker symptoms development.
Knowledge Reduction Algorithms in Cloud Computing

Knowledge reduction is one of the important research issues in rough set theory.Classical knowledge reduction algorithms assume all the datasets can be loaded into the main memory,which are infeasible for large-scale datasets.Massive data with high dimensions makes attribute reduction a challenging task.To this end,the concepts and properties of discernibility and indiscernibility object pairs are given in terms of the discernibility and indiscernibility of the attribute(s). The relationship between discernibility matrix and them is illustrated in detail.Then,an algorithm of computing equivalence classes is designed for large-scale data in data parallel,and the corresponding knowledge reduction algorithms are proposed in cloud computing.Finally,three parallelism strategies are implemented and discussed.The experimental results demonstrate that knowledge reduction algorithms in cloud computing can scale well and efficiently process massive datasets on commodity computers.
Cenit : Système de détection semi-automatique des néologismes

Les langues evoluent a un rythme accelere, donc la detection manuelle des neologismes devient encore moins pratique. Cet article decrit Cenit, un systeme de veille neologique qui vise a identifier des neologismes dans les domaines specialises. Le systeme utilise une strategie fondee sur l'exploitation de corpus. Nous exposons les composants et les divers stades de traitement
A new two-phase scatternet formation algorithm for bluetooth wireless personal area networks

A Bluetooth multi-hop personal area network can be formed by interconnecting one or more piconets into a scatternet. A Bluetooth scatternet is an ad hoc network in which the devices move randomly and organize themselves. The scatternet is attractive because it can extend the Bluetooth radio range and improve the network capacity. The current Bluetooth specification [1] only defines the scatternet but does not address how the scatternet is formed. To reduce the high load on the master nodes and bridge nodes, a twophase scatternet formation (TPSF) [8] algorithm has been proposed in which a control scatternet is created for the control traffic in the first phase and an on-demand scatternet is created for the data traffic in the second phase. In TPSF, route information for the ondemand scatternet on each node is discovered only when the node initially accesses the network. The original TPSF does not consider the support of mobility. In this thesis, we propose a new scheme which is called TPSF+ for the on-demand scatternet formation in the second phase of TPSF. In TPSF+, route information is discovered when a communication session is required between the two nodes. Consequently, the on-demand scatternet can be formed with much higher success ratio when the slaves randomly move around the master after accessing the network. We also propose to use PM_ADDR (Parked Member Address) instead of BD_ADDR (Bluetooth Device Address) during route discovery in order to reduce the time of the route discovery process. Furthermore, to reduce the hop distance of the on-demand scatternet, we limit the number of hops in each piconet in the control scatternet. Based on the simulation results, we show that our scheme can improve network performance greatly in terms of aggregate throughput and end-to-end delay even with the consideration of packet collisions. With the slaves randomly moving around the master, TPSF+ achieves much better performance in terms of a higher successful path connection ratio. TABLE OF CONTENTS Abstract ii List of Tables vii List of Figures viii Acknowledgements x Chapter
Predicting Endpoint of Goal-Directed Motion in Modern Desktop Interfaces using Motion Kinematics

Researchers who study pointing facilitation have identified the ability to identify–during motion–the likely target of a user’s pointing gesture, as a necessary precursor to pointing facilitation in modern computer interfaces. To address this need, we develop and analyze how an understanding of the underlying characteristics of motion can enhance our ability to predict the target or endpoint of a goal-directed movement in graphical user interfaces. Using established laws of motion and an analysis of users’ kinematic profiles, we demonstrate that the initial 90% of motion is primarly balistic and submovements are limited to the last 10% of gesture movement. Through experimentation, we demonstrate that target constraint and the intended use of a target has either a minimal effect on the motion profile or affects the last 10% of motion. Therefore, we demonstrate that any technique that models the intial 90% of gesture motion will not be affected by target constraint or intended use. Given, these results, we develop a technique to model the initial ballistic motion to predict user endpoint by adopting principles from the minimum jerk principle. Based on this principle, we derive an equation to model the initial ballistic phase of movement in order to predict movement distance and direction. We demonstrate through experimentation that we can successfully model pointing motion to identify a region of likely targets on the computer display. Next, we characterize the effects of target size and target distance on prediction accuracy. We demonstrate that there exists a linear relationship between prediction accuracy and target distance and that this relationship can be leveraged to create a probabilistic model for each target on the computer display. We then demonstrate how these probabilities could be used to enable pointing facilitation in modern computer interfaces. Finally, we demonstrate that the results from our evaluation of our technique are supported by the current motor control literature. In addition, we show that our technique provides optimal accuracy for any optimal accuracy when prediction of motion endpoint is performed using only the ballistic components of motion and before 90% of motion distance.
Assessing Conflict Driven Food Security in Rakhine, Myanmar with Multisource Imagery

Recent conflict along the border of Bangladesh and Myanmar has amplified a food security crisis and access to the region remains challenging. Moderate-resolution satellite remote sensing offers an approach to complement more traditional food insecurity hot spot assessment across Rakhine, Myanmar; however, conflict creates unique signals that are not agroclimatologically driven and need to be considered. Time series radar and optical data cubes were built and used to assess for deviations across space and time for rice paddy production areas based on established techniques. Ultimately, the Sentinel-1 radar was more helpful compared to fused Landsat-7 and -8 and Sentinel-2 data cubes that were substantially impacted by cloud cover during key growth stages. Anecdotal reporting, very high resolution (VHR) imagery, and expert knowledge were used to support operational analyses routines in an attempt to characterize rice into failed, abandoned, and cultivated classes across 2016 to 2018 seasons. Accuracy assessment using co-timed VHR showed overall accuracy (%) of 86.5, 87.5, and 91.0 for 2016, 2017, and 2018, respectively. Nearly one-third of rice production was characterized as failed or abandoned in any given year. Qualitative analyses showed paddy failure was often adjacent to conflict events. The moderate-resolution imagery and automated routines offer complementing metrics that can be used to help guide food security assessments. In regions where climate change, migration, and conflict coincide, decision support tools will need to evolve and continue to integrate human perspectives.
Context-Aware Coherence Protocols for Future Processors

The semiconductor industry is experiencing a shift from "computation-bound design" to "communication-bound design. " Many future systems will use one or many chip multiprocessors (CMPs) and support shared memory, as CMP-based systems can provide high-performance, cost-effective computing for workloads with abundant thread-level parallelism. One of the biggest challenges in CMP designs is to employ efficient cache coherence protocols to maintain coherence. Most commercial products implement directory-based protocols to maintain coherence. Directory-based protocols avoid the bandwidth and electrical limits of a centralized interconnect by tracking the global coherence state of cache lines via a directory structure. Directory-based protocols are preferred in future systems due to their ability to exploit arbitrary point-to-point interconnects. However, existing directory-based protocols are not optimum in specific contexts. For example, existing protocols cannot optimize the coherence traffic according to the sharing patterns shown in the applications or the varying latency, bandwidth needs of different coherence messages, which leads to suboptimal performance and extra power consumption. To overcome these limitations of conventional directory-based protocols, we propose two cache coherence protocols that optimize the coherence traffic based on context knowledge. After automatically detecting a stable producer-consumer pattern in an application, our sharing pattern-aware coherence protocol uses directory delegation to delegate the "home directory" of a cache line to the producer node, thereby converting 3-hop coherence operations into 2-hop operations. Then, the producer employs speculative updates to push the data to where it might soon be consumed. When the producer correctly predicts when and where to send updates, these 3-hop misses become local misses, effectively eliminating the impact of remote memory latency. Our interconnect-aware protocol can exploit a heterogenous interconnect comprised of wires with varying latency, bandwidth, and energy characteristics. By intelligently mapping critical messages to wires optimized for delay and noncritical messages to wires optimized for low power, our interconnect-aware protocol can achieve performance improvement and power reduction at the same time. We demonstrate the performance advantage of the proposed mechanisms through architecture-level simulation. The producer-consumer sharing-aware protocol reduces the average remote miss rate by 40%, reduces network traffic by 15%, and improves performance by 21% on seven benchmark programs that exhibit producerconsumer sharing using a cycle-accurate simulator of a future 16-node SGI multiprocessor. The interconnect-aware protocol yields a performance improvement of 11% and energy reduction of 22% on a set of scientific and commercial benchmarks for a future 16-core CMP system.
Developing a Coordinated Youth Housing Stability Program for Juvenile Courts

Homeless youth engaging in street survival behaviors are at higher risk of justice involvement. Advocates for reducing youth homelessness have called on the juvenile justice system and allied system partners to minimize the legal consequences of these behaviors and to improve systemic responses to identifying and reducing homelessness. The current study used a community-based participatory approach to develop a model for reducing homelessness from within the juvenile justice system. This mixed methods study leveraged a research-practice partnership between university researchers and a midsized county court in Washington State to examine data from local juvenile filings in 2017, (n=555), statewide juvenile court data from 2016-17, (n=6,791/6,866), and qualitative data from workgroup meetings. Prevalence statistics suggest 20-50 percent of the youth filed in juvenile court had at least one prior episode of running away or being kicked out of the home. Key qualitative findings included tensions around the role of probation in addressing youth homelessness, the need for better methods of identification, and a lack of intensive family-based services targeted at preventing housing instability. The resulting juvenile court based model for addressing youth homelessness is presented and lessons learned from the researchpractice partnership are discussed.