Miracle-dz/UniFAR-FTUs huggingface dataset:
A Thesaurus-Based Semantic Classification of English Collocations

We propose a new method for organizing the numerous collocates into semantic thesaurus categories. The approach introduces a thesaurus-based semantic classification model automatically learning semantic relations for classifying adjective-noun (A-N) and verb-noun (V-N) collocations into different categories. Our model uses a random walk over weighted graph derived from WordNet semantic relation. We compute a semantic label stationary distribution via an iterative graphical algorithm. The performance for semantic cluster similarity and the conformity of semantic labels are both evaluated. The resulting semantic classification establishes as close consistency as human judgments. Moreover, our experimental results indicate that the thesaurus structure is successfully imposed to facilitate grasping concepts of collocations. It might improve the performance of the state-of-art collocation reference tools.
Optimal Anycast Technique for Delay-Sensitive Energy-Constrained Asynchronous Sensor Networks

In wireless sensor networks (WSNs), asynchronous sleep-wake scheduling protocols can be used to significantly reduce energy consumption without incurring the communication overhead for clock synchronization needed for synchronous sleep-wake scheduling protocols. However, these savings could come at a significant cost in delay performance. Recently, researchers have attempted to exploit the inherent broadcast nature of the wireless medium to reduce this delay with virtually no additional energy cost. These schemes are called “anycasting,” where each sensor node forwards the packet to the first node that wakes up among a set of candidate next-hop nodes. In this paper, we develop a delay-optimal anycasting scheme under periodic sleep-wake patterns. Our solution is computationally simple and fully distributed. Furthermore, we show that periodic sleep-wake patterns result in the smallest delay among all wake-up patterns under given energy constraints. Simulation results illustrate the benefit of our proposed schemes over the state of the art.
Separating regular languages with two quantifier alternations

We investigate a famous decision problem in automata theory: separation. Given a class of language C, the separation problem for C takes as input two regular languages and asks whether there exists a third one which belongs to C, includes the first one and is disjoint from the second. Typically, obtaining an algorithm for separation yields a deep understanding of the investigated class C. This explains why a lot of effort has been devoted to finding algorithms for the most prominent classes. Here, we are interested in classes within concatenation hierarchies. Such hierarchies are built using a generic construction process: one starts from an initial class called the basis and builds new levels by applying generic operations. The most famous one, the dot-depth hierarchy of Brzozowski and Cohen, classifies the languages definable in first-order logic. Moreover, it was shown by Thomas that it corresponds to the quantifier alternation hierarchy of first-order logic: each level in the dot-depth corresponds to the languages that can be defined with a prescribed number of quantifier blocks. Finding separation algorithms for all levels in this hierarchy is among the most famous open problems in automata theory. Our main theorem is generic: we show that separation is decidable for the level 3/2 of any concatenation hierarchy whose basis is finite. Furthermore, in the special case of the dot-depth, we push this result to the level 5/2. In logical terms, this solves separation for $\Sigma_3$: first-order sentences having at most three quantifier blocks starting with an existential one.
LEAP MOTION CONTROLLER: THE MOST EFFICIENT TOOL FOR ENHANCING HAND FUNCTIONS

Virtual reality devices, such as the leap motion controller, have been created by the gaming industry for both home and clinical uses. As part of virtual task practice, the leap motion gadget collects and records fine motor abilities of the hand and fingers while controlling a simulated environment that needs coordination. For improved hand function development, it has a more realistic environment design and object tracking. It can also process moving depth using two embedded cameras, providing users with a real-time on-screen hand simulator that is nearly as accurate as genuine hand gestures. The aim of the study is to evaluate the importance of leap motion controller in treatment of various physiotherapeutic disorders. Although the majority of interactive virtual trials have focused on stroke patients, brain development in those with severe and symptomatic brain damage is still normal. Most virtual reality systems are only available to the proximal upper extremities due to the limits of their control mechanisms.
Routing Protocols in Ad-hoc Network

The latest advancement in wireless technology and its applications received a lot of attention. An ad hoc network is one such recent technology, which gives a new paradigm for wireless self-organised networks. Ad hoc networks are simple peer-to peer networks, self- organized and with no fixed infrastructure. Ad-hoc network is a concept in computer communication which means that user wanting to communicate with each other forms a temporary network, without use of centralized administration. Each node in the network acts both as host and router and must therefore willing to forward packet for other node. For this purpose routing protocol is needed. A Mobile Ad-hoc Network (MANET) is a temporary wireless network composed of mobile nodes without any permanent infrastructure. Each node not only operates as an end system, it also acts as a router to forward packets on behalf of other nodes (1). One of the best features of MANET is its flexibility and can configure itself in the fly and thus very suitable for the emergency situation
Soft decision decoding of linear block codes based on ordered statistics in multilevel signaling

| Soft decision decoding of linear block codes based on ordered statistics is discussed in the context of multilevel coding with multistage decoding. Analytical expressions on the ordered statistics and the associated bit error probability have been derived. The result shows tradeo s between error performance and decoding complexity in multilevel signaling including BPSK modulation formats as a special case.
The Rupelian–Chattian transition in the north-western Transylvanian Basin (Romania) revealed by calcareous nannofossils: implications for biostratigraphy and palaeoenvironmental reconstruction

Abstract Sediments belonging to the Oligocene Vima Formation (located in the north-western part of the Transylvanian Basin, Romania) have been investigated for calcareous nannofossils content. Biostratigraphically, the sedimentary succession is late Rupelian–Chattian in age, belonging to the NP24 — Sphenolithus distentus and NP25 — Sphenolithus ciperoensis biozones, to CP19a — Cyclicargolithus floridanus and CP19b — Reticulofenestra bisecta Subzones and to the interval from CNO4 — Sphenolithus distentus/Sphenolithus predistentus CRZ to CNO5 — Sphenolithus ciperoensis TZ. The palaeoenvironment of the Fântânele section was reconstructed by means of calcareous nannofossils and statistics. Multivariate statistics were applied to the composition of autochthonous assemblages and the obtained clusters were used to assess the palaeoecological preferences of the nannofossils. We document changes from more stable open-marine regime, with temperate sea-surface temperatures interfering locally with influx of cooler water and enriched cool-nutrient supply for the late Rupelian–earliest Chattian (NP24), to shallower and possibly warmer near-shore marine eutrophic environment, with salinity fluctuations, increased terrigenous material run-off and freshwater influx for the remaining early Chattian (NP25).
E(cid:14)cient Computation of Iceberg Cubes with Complex Measures (cid:3)

It is often too expensive to compute and materialize a complete high-dimensional data cube. Computing an iceberg cube, which contains only aggregates above certain thresholds, is an e(cid:11)ective way to derive nontrivial multi-dimensional aggregations for OLAP and data mining. In this paper, we study e(cid:14)cient methods for computing iceberg cubes with some popularly used complex measures, such as average, and develop a methodology that adopts a weaker but anti-monotonic condition for testing and pruning search space. In particular, for e(cid:14)-cient computation of iceberg cubes with the average measure, we propose a top-k average pruning method and extend two previously studied methods, Apriori and BUC, to Top-k Apriori and Top-k BUC. To further improve the performance, an interesting hypertree structure, called H-tree, is designed and a new iceberg cubing method, called Top-k H-Cubing, is developed. Our performance study shows that Top-k BUC and Top-k H-Cubing are promising candidates for scalable computation, and Top-k H-Cubing has the best performance in many cases.
Multi-Relational Data Mining

An important aspect of data mining algorithms and systems is that they should scale well to large databases. A consequence of this is that most data mining tools are based on machine learning algorithms that work on data in attribute-value format. Experience has proven that such ''single-table'' mining algorithms indeed scale well. The downside of this format is, however, that more complex patterns are simply not expressible in this format and, thus, cannot be discovered. One way to enlarge the expressiveness is to generalize, as in ILP, from one-table mining to multiple table mining, i.e., to support mining on full relational databases. The key step in such a generalization is to ensure that the search space does not explode and that efficiency and, thus, scalability are maintained. In this paper we present a framework and an architecture that provide such a generalization. In this framework the semantic information in the database schema, e.g., foreign keys, are exploited to prune the search space and, in the architecture, database primitives are defined to ensure efficiency. Moreover, the framework induces a canonical generalization of algorithms, i.e., if the generalized algorithms are run on a single table database, they give the same results as their single-table counterparts. The framework is illustrated by the Warmr algorithm, which is a multi-relational generalization of the Apriori algorithm.
Predicate-argument Structure based Textual Entailment Recognition System of KYOTO Team for NTCIR-10 RITE-2

We participated in Japanese tasks of RITE-2 in NTCIR10 (team id: “KYOTO”). Our proposed method regards predicate-argument structure as a basic unit of handling the meaning of text/hypothesis, and performs the matching between text and hypothesis. Our system first performs predicate-argument structure analysis to both a text and a hypothesis. Then, we perform the matching between text and hypothesis. In matching text and hypothesis, widecoverage relations between words/phrases such as synonym and is-a are utilized, which are automatically acquired from a dictionary, Web corpus and Wikipedia.
Software Architecture, Configuration Management, and Configurable Distributed Systems: A Menage a Trois ; CU-CS-849-98

Software architecture, configuration management, and configurable distributed systems are three areas of research that until now have evolved separately. Contributions in each field have focused on their respective area of concern. However, as solutions in the three fields tend to center around some notion of a system model, it is worthwhile to investigate their relationship in detail. In particular, the large amount of overlap among the system models developed in each area, combined with the complementary nature of the differences among them, suggests that an approach based on a common system model is viable. In this paper, we illustrate the benefits of using such a unified system model, identify the commonalities and differences among the existing system models, and present some of our initial experiments that we believe will lead to the development of a single system model that is usable in all three fields. This work was supported in part by the Air Force Material Command, Rome Laboratory, and the Advanced Research Projects Agency under Contract Number F30602-94-C-0253. The content of the information does not necessarily reflect the position or the policy of the Government and no official endorsement should be inferred.
Computer-Aided Design

• We study how the superimposed mesh structure would influence the Finite Element Method (FEM)-based image registration process. • We propose a mesh generation algorithm based on how the mesh will influence the registration process, using the discrete Centroidal Voronoi Tessellation idea. • We present a parallel algorithm to compute and update the mesh structure efficiently during image registration.
Bulletin of the Technical Committee on Data Engineering March 2009

Recently the cloud computing paradigm has been receiving si gnificant excitement and attention in the media and blogosphere. To some, cloud computing seems to be l ittle more than a marketing umbrella, encompassing topics such as distributed computing, grid co mputing, utility computing, and softwareas-a-service, that have already received significant resea rch focus and commercial implementation. Nonetheless, there exist an increasing number of large comp anies that are offering cloud computing infrastructure products and services that do not entirely r semble the visions of these individual component topics. In this article we discuss the limitations and opportunitie s of deploying data management issues on these emerging cloud computing platforms (e.g., Amazon Web Services). We speculate that large scale data analysis tasks, decision support systems, and applica tion specific data marts are more likely to take advantage of cloud computing platforms than operation l, transactional database systems (at least initially). We present a list of features that a DBMS designe d for large scale data analysis tasks running on an Amazon-style offering should contain. We then discuss some currently available open source and commercial database options that can be used to perform such analysis tasks, and conclude that none of these options, as presently architected, match the requisi te features. We thus express the need for a new DBMS, designed specifically for cloud computing environmen ts.
Stock assessment of the Gulf of Maine -- Georges Bank Atlantic herring complex, 2003

Gulf of Maine-Georges Bank Atlantic herring complex. Some data were preliminary (i.e. 2002 landings) at the time of the meeting and all analyses were completed with these data. Two assessments were presented at the meeting, a forward projection analysis (Chapter 10) and an ADAPT assessment (Chapter 14). The review committee did not reject either assessment; therefore, the results of both approaches are contained in this document. However, much progress was made on many other facets of the status of the herring complex. For example, both counties agreed that an assessment of the overall complex was warranted, that historic tagging information was still relevant, that multiple research survey time-series should be used in the analysis, and that the new acoustics results should be used. Du 10 au 14 février 2003, le Comité d'évaluation des ressources transfrontalières (CERT) s'est réuni au Centre des conférences de la Station biologique de St. Andrews, située à St. Andrews (N.-B.), au Canada, pour évaluer le complexe de stocks de hareng du golfe du Maine et du banc Georges. Même si certaines données étaient préliminaires (prises pour 2002), toutes les analyses ont été effectuées. Deux évaluations ont été présentées, une analyse selon un modèle à projection prospective (chapitre 10) et une évaluation selon un modèle ADAPT (chapitre 14). Le comité d'examen ne les ayant pas rejetées, les résultats sont ici présentés. En outre, de grands progrès ont été réalisés au titre de nombreux autres aspects de l'état de ce complexe de stocks. Par exemple, les deux pays ont convenu qu'une évaluation de l'ensemble du complexe était justifiée, que les données historiques d'étiquetage étaient encore pertinentes, que l'analyse devait reposer sur des séries chronologiques multiples de données de relevé de recherche et que les résultats des nouveaux relevés acoustiques
Phase transition properties of clustered travelling salesman problem instances generated with evolutionary computation

This paper introduces a generator that creates problem instances for the Euclidean symmetric travelling salesman problem. To fit real world problems, we look at maps consisting of clustered nodes. Uniform random sampling methods do not result in maps where the nodes are spread out to form identifiable clusters. To improve upon this, we propose an evolutionary algorithm that uses the layout of nodes on a map as its genotype. By optimising the spread until a set of constraints is satisfied, we are able to produce better clustered maps, in a more robust way. When varying the number of clusters in these maps and, when solving the Euclidean symmetric travelling salesman person using Chained Lin-Kernighan, we observe a phase transition in the form of an easy-hard-easy pattern.
The virtual organizing process—A critical tool for enterprise competitiveness in the information era

The term virtual enterprise has generated considerable confusion because of its rather liberal interpretation. This paper argues that the successful establishment of a virtual enterprise is mainly dependent on the virtual organizing processes of an enterprise's strategies ( VOPES), rather than on the actual manifested transformation of the whole into a single virtual organization. A three-dimensional dynamic framework for VOPES is pre­ sented, with the aim of providing a coherent model for positioning the various virtual organizing strategies, and at the same time giving VOPES dynamic tendencies towards market negotiation, co-operation, co-ordination and collaboration. To achieve a com­ petitive advantage, the top management of an enterprise operating in an intense informa­ tion environment can organize their enterprise virtually by using the three-dimensional framework of: virtual customer relationship, virtual outsourcing, and virtual knowledge and expertise. The generic IT architecture of VOPES is also described and discussed. 1 F et al.: The virtual organizing process—A critical tool for enterprise com Published by CSUSB ScholarWorks, 2003 Journal of International Technology & Information Management Volume 12, Number I
A General Technique to Train Language Models on Language Models

We show that under certain conditions, a language model can be trained on the basis of a second language model. The main instance of the technique trains a finite automaton on the basis of a probabilistic context-free grammar, such that the Kullback-Leibler distance between grammar and trained automaton is provably minimal. This is a substantial generalization of an existing algorithm to train an n-gram model on the basis of a probabilistic context-free grammar.
Image Registration

In this paper we present a technique for fully automatic, real-time 3D SPECT (Single Photon Emitting Computed Tomography) and 2D ultrasound image registration. We use this technique in the context of kidney lesion diagnosis. Our registration algorithm allows a physician to perform an ultrasound exam after a SPECT image has been acquired and see in real time the registration of both modalities. An automatic segmentation algorithm has been implemented in order to display in 3D the positions of the acquired US images with respect to the organs.
Matrix Expansions for Computing the Discrete Hartley Transform

Abstract— A new fast algorithm for computing the discrete Hartley transform (DHT) is presented, which is base d on the expansion of the transform matrix. The algorithm presents a better performance, in terms of multiplicative complexity, than previously known fast Hartley transform algorithms. A detailed description of the computation of DHTs with blocklengths 8 and 12 is shown. The algorithm is very attractive for blocklengths N ≥ 128.
Nonsinking Organic Matter Production in the California Current

Productive eastern boundary upwelling systems such as the California Current Ecosystem (CCE) are important regions for supporting both local and remote food webs. Several studies have reported on the temporal and spatial variability of primary production and gravitational export in the CCE. However, few studies have quantified the partitioning of net primary and new production into other reservoirs of detrital organic matter. This study tested the hypothesis that nonsinking detrital reservoirs are an exportable reservoir of new production in the CCE with samples collected by the California Cooperative Oceanic Fisheries Investigation survey between 2008 and 2010. Water column gradients in nitrate (NO3−) and total organic carbon (TOC; which excludes sinking particulate organic carbon) were used to estimate potential rates of new production (PNew) and TOC production (PTOC), respectively. The PTOC:PNew varied between 0.16 and 0.56 and often increased with indicators of enhanced autotrophic production. At times, surface stratification was also correlated with elevated PTOC:PNew. In the most productive, inshore region, PTOC exceeded previously reported sinking export rates, which identified TOC as a quantitatively significant repository of exportable carbon in the CCE. However the sum of PTOC and sinking export for these productive regions was less than both PNew and oxygen‐based estimates of net community production. These results imply that nonsinking reservoirs alone are not sufficient to explain observed imbalances between production and export for the most productive CCE regions.
Qualia structures and their impact on the concrete noun categorization task

Automatic acquisition of qualia structures is one of the directions in information extraction that has received a great attention lately. We consider such information as a possible input for the word-space models and investigate its impact on the categorization task. We show that the results of the categorization are mostly inﬂuenced by the formal role while the other roles have not contributed discriminative features for this task. The best results on 3-way clustering are achieved by using the formal role alone (entropy 0.00, purity 1.00), the best performance on 6-way clustering is yielded by a combination of the formal and the agentive roles (entropy 0.09, purity 0.91).
BIOINFORMATICS APPLICATIONS NOTE

Summary: We present metabolite pathway enrichment analysis (MPEA) for the visualization and biological interpretation of metabolite data at the system level. Our tool follows the concept of gene set enrichment analysis (GSEA) and tests whether metabolites involved in some predeﬁned pathway occur towards the top (or bottom) of a ranked query compound list. In particular, MPEA is designed to handle many-to-many relationships that may occur between the query compounds and metabolite annotations. For a demonstration, we analysed metabolite proﬁles of 14 twin pairs with differing body weights. MPEA found signiﬁcant pathways from data that had no signiﬁcant individual query compounds, its results were congruent with those discovered from transcriptomics data and it detected more pathways than the competing metabolic pathway method did. Availability: The web server and source code of MPEA are available at http: