Our approach may also be seen in the context of classifier combination for string-valued variables. While ensemble methods for structured prediction have been considered in several works (see, e.g., Nguyen and Guo (2007), Cortes et al. (2014), and references therein), a typical assumption in this situation is that the sequences to be combined have equal length, which clearly cannot be expected to hold when, e.g., the outputs of several G2P, transliteration, etc., systems must be combined. In fact, the multiple many-to-many alignment models investigated in this work could act as a preprocess- ing step in this setup, since the alignment precisely serves the functionality of segmenting the strings into equal number of segments/substructures. Of course, combining outputs with varying number of elements is also an issue in machine transla- tion (e.g., Macherey and Och (2007), Heafield et al. (2009)), but, there, the problem is harder due to the potential non-monotonicities in the ordering of elements, which typically necessitates (additional) heuristics. One approach for constructing multi- ple alignments is here progressive multiple align- ment (Feng and Doolittle, 1987) in which a multi- ple (typically one-to-one) alignment is iteratively constructed from successive pairwise alignments (Bangalore et al., 2001). Matusov et al. (2006) apply word reordering and subsequent pairwise monotone one-to-one alignments for MT system combination.
Abstract—Wireless sensor networks (WSNs) have been widely studied in the context of many-to-one communication, in which multiple data sources send messages to a dedicated sink. However, there has been little research in the area of many-to-many communication. Many-to-many communication in WSNs is a growing application area, with examples including fire detection in both natural and urban areas, and the monitoring of heating and air conditioning within buildings. In this paper, we propose a scalable many-to-many routing protocol that makes use of Ant Colony Optimisation (ACO) that is applicable for an arbitrary number of sources and sinks. The protocol aggregates data sent from multiple sources into a single, shared backbone of nodes to reduce the total number of packets sent and so increase network lifetime. Results from simulations using the Cooja Network simulator show that the protocol is able to achieve packet delivery ratios above 95%, with the algorithm becoming more efficient with larger networks, sending fewer packets relative to the size of the networks, as well as involving fewer nodes in routing.
Letter-to-phoneme conversion generally requires aligned training data of letters and phonemes. Typically, the align- ments are limited to one-to-one align- ments. We present a novel technique of training with many-to-many alignments. A letter chunking bigram prediction man- ages double letters and double phonemes automatically as opposed to preprocess- ing with fixed lists. We also apply an HMM method in conjunction with a local classification model to predict a global phoneme sequence given a word. The many-to-many alignments result in significant improvements over the tradi- tional one-to-one approach. Our system achieves state-of-the-art performance on several languages and data sets.
Protocols that have been developed for communication in WSNs with multiple sinks can be found in [5, 28, 21, 3, 39, 41, 48, 6, 13, 24]. The authors of  developed an algorithm where a node chooses a sink in a multi-sink WSN to send its data in such a way that it minimizes energy consumption. A scheme proposed in  performs data collection from many nodes to many sinks, i.e., many-to-many communication. The main idea of the protocol is to reduce the number of redundant transmissions by leveraging neighbourhood information. An algorithm that builds two node-disjoint paths from every node to two different sinks was proposed in . If one of the two paths fails, the other path is used to route the data. In , the authors propose a routing protocol that is using a hexagon-based architecture. The nodes in the network are grouped into hexagons, based on their locations. The routing protocol proposed in , is based on trees. In the protocol, different trees rooted at different sinks are used to forward data. The authors of  have proposed an online algorithm for data collection in WSNs with multiple sinks, where sinks are deployed in a stepwise fashion during network operation. In , the authors present different routing schemes that are based on a logical tree structure, which is built based on the residual energy of each node. One of these schemes uses a secondary sink to maximize the network lifetime. A data reporting algorithm used for object tracking in multi-sinks WSNs was presented in . The algorithm attempted to reduce energy consumption and balance the load among sinks and nodes.
ABSTRACT: Many-to-many data linkage is a vital job in many areas, yet only a handful of former publications have addressed this subject. Besides, while customarily data linkage is performed among substances of the same sort, it is great degree important to create linkage mechanism between matching substances of different sorts as well. In this paper, we propose many-to-many data linkage technique that connects substances of various natures. The proposed strategy depends on a Multiple Clustering Tree (MCCT) that connects entities of various sorts to get a reasonable and justifiable relationship. We propose to utilize the Least Probable Intersection (LPI) technique to assemble the MCCT tree. This tree shall be a clustering tree whose inner nodes are set of records (i.e. cluster) from first substance and outer nodes are set of records (i.e. cluster) from second substance. The proposed technique gives better and preferable linkage results over past methodologies.
ABSTRACT: Data linkage is a process performed among entities of the same type or different type. It is necessary to develop the data linkage techniques for different types as well. In this paper, we propose a many-to-many data linkage and it is used to perform link between matching entities of different types. The proposed method is based on One-Class Clustering Tree (OCCT) for implementing many-to-many data linkage. The OCCT is built in such a way that it is easy to understand and can be transformed into association rules. The inner node consists of features from the first data set. The leaves of the tree represent features from the second data set that is matching with the first data set entities. The proposed method uses maximum-likelihood estimation for pre-pruning process which is used to create One-Class Clustering Tree effectively. Threshold value is used for decision making either the record pair is match or non-match. KEYWORDS: clustering; data linkage; decision tree; prepruning.
There are many research projects that have defined methods for members of a communication group to establish a group key by each member of the group providing a piece of the key. Some of these include one-way accumulators [BdM93], Group Diffie-Hellman [STW96], key agreement for dynamic peer groups [STW00], tree based Group Diffie-Hellman [KPT00], and algorithms based on zero knowledge proof of identity [FFS87]. Many of these approaches are depend on a reliable communication system, or for the authentication to be performed outside of the protocol they define. These requirements were not acceptable for this project.
the model and features to the needs of each lan- guage, but it is suboptimal for theoretical and prac- tical reasons. Theoretically, the study of linguistic typology tells us that many languages share mor- phological, phonological, and syntactic phenomena (Bender, 2011); therefore, the mainstream approach misses an opportunity to exploit relevant supervi- sion from typologically related languages. Practi- cally, it is inconvenient to deploy or distribute NLP tools that are customized for many different lan- guages because, for each language of interest, we need to configure, train, tune, monitor, and occasion- ally update the model. Furthermore, code-switching or code-mixing (mixing more than one language in the same discourse), which is pervasive in some gen- res, in particular social media, presents a challenge for monolingually-trained NLP models (Barman et al., 2014). 2
MANY is a system combination software (Bar- rault, 2010) based on the decoding of a lattice made of several Confusion Networks (CN). This is a widespread approach in MT system combina- tion (Rosti et al., 2007; Shen et al., 2008; Karakos et al., 2008; Rosti et al., 2009). MANY can be decomposed in two main modules. The first one is the alignment module which actually is a modi- fied version of TERp (Snover et al., 2009). Its role is to incrementally align the hypotheses against a backbone in order to create a confusion network. Those confusion networks are then connected to- gether to create a lattice. This module uses dif- ferent costs (which corresponds to a match, an in- sertion, a deletion, a substitution, a shift, a syn- onym and a stem) to compute the best alignment and incrementally build a confusion network. In the case of confusion network, the match (substi- tution, synonyms, and stems) costs are considered when the word in the hypothesis matches (is a sub- stitution, a synonyms or a stems of) at least one word of the considered confusion sets in the CN.
We consider spinless fermions on a finite one-dimensional lattice, interacting via nearest-neighbor repulsion and subject to a strong electric field. In the noninteracting case, due to Wannier-Stark localization, the single-particle wave functions are exponentially localized even though the model has no quenched disorder. We show that this system remains localized in the presence of interactions and exhibits physics analogous to models of conventional many-body localization (MBL). In particular, the entanglement entropy grows logarithmically with time after a quench, albeit with a slightly different functional form from the MBL case, and the level statistics of the many-body energy spectrum are Poissonian. We moreover predict that a quench experiment starting from a charge-density wave state would show results similar to those of Schreiber et al. [Science 349 , 842 (2015)].
This paper provides an analysis of the representation of various grammatical phenomena in both constituency structure and dependency structure (hereafter c-structure and d-structure), including agreement, case marking, and word order in transitive sentences, as well as three theoretical constructs, and the interface between the form of a sentence and its meaning. There is a crucial structural relationship for all of these phenomena in both constituency grammar and dependency grammar, but only the version used in dependency grammar is fully reliable. This insight evokes the following question: Why do linguists working with constituency grammars think that so many nodes are necessary? Upon examination, the extra nodes succeed only in confusing our understanding of syntactic phenomena.
The double-slit experiment (see Brukner & Zeilinger, 2002; Donati, Missiroli, & Pozzi, 1973) demonstrates the intriguing interference phenomenon of light and matter particles. Many researchers after Schrödinger offered alternative inter- pretations: the many-worlds interpretation (1956/1973, 1957; see also Osnaghi, Freitas, & Freire Jr., 2009; Rubin, 2001, 2005; Deutsch, 1997). In the many- worlds interpretation consciousness plays a less critical role than that in Copen- hagen interpretation since here the observer and the observed system are entan- gled, forming an integrated quantum system. The state of one subsystem is cor- related with that of the other subsystem, and quantum decoherence leads to the splitting of many worlds. For the integrated system, the interaction between the observed and observing subsystems causes the total wave function to decom- pose, and all possible states really exist in different branches. Therefore, each branch of the many worlds represents a reality (DeWitt, 1970, 1971; Wallace, 2003), in contrast to the Copenhagen interpretation in which only one branch is real and exists. Furthermore, each consciousness of reality is aware of the exis- tence of its corresponding consciousness in other realities, via theory and evi- dence, because there is physical contact among all branches via interference. Here I argue that the many-worlds theory could be further developed to reveal its empirical implications, which are of great value not only to science, but also to philosophy, theology, and society.
Mantel is intent on staying fairly true to what is known about Cromwell and his life, such as information gleaned from Cavendish’s book on Thomas Wolsey.(4) She also hints at events or attributes that the knowledgeable reader will enjoy but the neophyte might miss unknowingly. So when it is suggested that Anne Boleyn has a ‘deformity’, many readers may be unaware that she has been attributed to having, among other things, six fingers on one hand – an improbability given Henry’s superstitious nature that nonetheless has brought about much discussion, including an essay in a medical publication.(5) The king of England’s trip to the Field of Cloth of Gold near Calais in June 1520 to meet with the king of France is mentioned several times but without the visually interesting story of Henry VIII being thrown to the ground in a wrestling match by his regal cousin Francis I: fodder for further character development of a Tudor king Mantel portrays as paranoid, constantly hunting and bedding, and doubting of his abilities and his future. Those aware of these inside stories will gain a greater embellishment of the world of Thomas Cromwell and how he acts and reacts within it.
calls the “Corporate Food Regime”. This is characterised by a world of liberal trade, that essentially couples northern grain production to southern fruit, vegetable and seafood production, coordinated by trans-national corporations, with the rules set by international finance (such as the world bank, as well as private institutions) and the World Trade Organisation. With stringent intellectual property rights, the mergers of corporations into few centres of power, the efficient concentration of production into fewer areas of “comparative advantage” and global sets of standards, this food regime has created a “world farm”. The downside of this is that producers who cannot comply with certification schemes or compete on the global market face greater insecurity. In this way, the corporate food regime may undermine access to food for the poorest and most vulnerable. There is much to ponder in McKeon’s book. The key thesis is that globalisation and the neo-liberal free-market is why our global food system is so dysfunctional. As an example of why this is so, take the example of “large scale land acquisitions” (or “land-grabbing”). In SSA, following independence many new states nationalised communal land; and, especially where customary land-tenure is weak, governments can raise income by leasing the national land. This is often for the benefit of the international market (to supply richer rather than poorer nations). Furthermore, as populations expand, people are constrained from expanding on to the nationally-owned land. The end result is that, as populations grow in SSA, land is passed down in ever smaller parcels (this is also discussed by Smith & Naylor in ), creating a vicious circle of impoverishment and food insecurity.
Aspiration was, as we have seen, a key term of Cameronism (who made frequent references to Britain being an ‘Aspiration Nation’) and was also a key word used in 2016 by the more Blairite candidates for Labour leadership, particularly Liz Kendall. 13 It is a very good example of how a core neoliberal word – aspiration – has been taken up by Corbynism and re-articulated: for ‘all’ rather than the individual; or as the election slogan put it, for the many, not the few. Whereas Cameron and Kendall used aspiration to advocate ‘equality of opportunity’ in the form of individualization and privatization, Corbynite ‘aspiration for all’ involves the public ownership of schools, strengthening teachers’ trade union representation, strengthening workers’ rights and collective success. This work of re-articulating ‘meritocratic feeling’ away from individualism and into mutuality has been a key part of its successful politics.
For each language, the top ten search hits are collected for 30,000 queries using Yahoo's or Bing's API. Recently for Swedish, Norwegian and Indonesian, we used Bing since its terms and conditions allowed us to send more queries per day. Table 3 gives some statistics of URL collection. We found that Google gave more hits than Yahoo or Bing, particularly for languages that have non-ASCII characters. The reason for this may not be the diﬀerence in index size. Google normalises many non-UTF8 encoding pages to UTF8 encoding and then indexes on them whereas Ya- hoo and Bing do less normalisation and more often index the words in the encoding of the page itself. We veriﬁed this for Telugu. http://www.eenadu.net is a widely-used Telugu news site which uses non-UTF8 encoding. We re- stricted the search hits to this news site and for the unicode query ÍŒ¢“Ÿ¿-¦Ç¦Õ (a famous politician) we got 9930 Google search hits, 14 Yahoo hits and 10 Bing hits. We also ran the query with the original encoding. There were 0 Google hits, 2670 Yahoo hits and 1440 Bing hits. This shows that Yahoo and Bing also indexed Eenadu but did not normalise the encoding. Since we use UTF8 queries, Google would serve our purposes better for Telugu. But for licensing and usability reasons, we have used Yahoo or Bing to date. For Indian languages, to collect data in other encodings we gen- erated queries in diﬀerent encodings apart from UTF8 by converting the UTF8 seeds using encoding mappings. While collecting the URLs, we store the query, page size and MIME type, as provided in the search engine output.
Effectiveness of Statistical Significance Test. Since there is no gold data available, to test the ability of the significance tests to re- move potentially uninformative relationships, we evaluated a ran- domly chosen set of statistically non-significant relationships. For instance, many relationships between the fare tax for taxi trips and di ff erent attributes from the Weather, 311, and 911 data sets were found not to be statistically significant. This indicates that, even though some of these relationship have |τ| > 0.60, they are mostly random and coincidental. In fact, the tax charged in taxi trip fares does not have anything to do with di ff erent weather conditions, let alone with 311 and 911 complaints. Other examples of spurious re- lationships pruned by our framework include: mileage of taxi trips (Taxi) and number of injured pedestrians (Vehicle Collisions), hav- ing τ = 0.90; number of bike trips (Citi Bike) and number of tweets (Twitter), having τ = 0.87; and number of 311 complaints and av- erage speed (Tra ffi c Speed), having τ = 0.76.