The paper is organized as follows. In Section 2, we present and recall some notations and some results on primitive words which are used in the sequel. In Section 3, we introduce someoperations where we first construct ww and perform then some small modifications of the second copy yielding ww 0 . We prove that all operations where the edit distance of w and w 0 is 1 preserve primitivity. An analogous result is shown for the edit distance 2 if at least one change of a letter is used. In Section 4, we consider analogous operations as in Section 2, but start from ww R and modify w R . In Section 5 we consider
representation of the genotypes as binary words. Despite reducing such a disruption by using the new operations, the minimality of automata is not preserved by them, thus individuals with the same complexity can be represented by automata with very different number of states and this seems not to be very logical from a biological point of view. For that reason, a representation of the genotypes over which genetic ope- rations preserve the minimality of automata, that is to say, preserve the primitivityofwords (since our genotypes can be represented as binary words), are required. In this Chapter, two different ways of generating primitive words are presented. For the first one, a set ofoperations inspired by biological gene duplication that preserve primitivityofwords is proposed. A large subset of binary primitive words can be obtained by using sequences of these operations as genotypes. For the second one, a characterization of the non-primitive words that provides a relation between primitive words and number theory is proposed. This gives a non-grammatical method to generate the set of all the primitive words. While genetic operations can be directly applied over the sequences of the operationspreservingprimitivity, the application of the genetic operations in the second approach is not as trivial. For that reason, the sequences of the operationspreservingprimitivity will be the representation of the genotypes used to study the complexity during the evolution (now, the minimality of the automata is preserved).
The second line of research, focused on finding relax- ations of DP, has been active since the inception of DP. In , the concept of δ-approximate -indistinguishability is presented (a.k.a. (, δ)-indistinguishability in ). This relaxation allows some additional margin δ to the require- ments in DP. In , the notion of (, δ)-probabilistic differential privacy (a.k.a. (, δ)-pdp) is proposed. Rather than allowing some additional margin, it requires -DP to be satisfied with probability greater than 1 − δ. In other words, the probability that the adversary gains significant information about an individual is, at most, δ. Yet another relaxation is given in , who assume that confidential data become less sensitive over time, which allows relaxing privacy parameters for older data. In , a relaxation is presented that restricts the definition of neighbor data sets: they are no longer data sets differing in any record, but in a record within a certain subset. In , an alternative relaxation of DP, called (µ, τ )- concentrated differential privacy, is proposed. Similarly to (, δ)-pdp, concentrated differential privacy allows the ratio of probabilities to be arbitrarily large with a small probability that is determined by the parameters µ and τ. In all the above relaxations, the accuracy gain is ob- tained by allowing the differentially private condition to be broken: the presence or absence of an individual may leak some information, although not too much or only with
For the proof of the main result we need some general considerations on the so-called nonlinear operators of max-prod kind. Over the set of positive reals, R + , we consider the operations ∨ (maximum) and · , product. Then ( R + , ∨ , · ) has a semiring structure and we call it as Max-Product algebra.
Conducted in these areas, studies have shown that the entire meaningful diversity of lexical semantics does not boil down to the mere representation through certain sets of semantic features (semes) ofsome “essential” features of objects and phenomena of reality. In addition to simply isolating and selecting those subject features that form the basis of direct and immediate lexical nomination, the human brain is able to perform other mental operations, resulting in the formation of lexical meanings that are fundamentally different in their structure and content from the usual reflective-conceptual type (Luchinskaya, Karabulatova, Tkhorik, Zelenskaya & Golubtsov. 2018). The latter are currently characterized as nominative or descriptive. Their originality lies in the fact that they are “directly directed at reality” and “are the immediate mental correlates, mental models of objects, phenomena, their properties, relationships, actions and states.” (Vasiliev L.M. 1990).
Within Knowledge Sharing and Reuse, the field of Onto- logical Engineering (OE) is an active area of research. One of its open research topics is ontology integration. Unfor- tunately, there has been an abusive use of the word in- tegration within the community. Integration designates, not only, the special operations to build ontologies from other ontologies available in some ontology development environments (Farquhar, Fikes & Rice 1997), but also the process of building ontologies from other preexis- tent ontologies (Borst, Akkermans & Top 1997, Dalia- nis & Persson 1997, Gangemi, Pisanelli & Steve 1998, Skuce 1997, Swartout, Patil, Knight & Russ 1997), the set of activities within some methodologies that specify how to build ontologies using other publicly available ontolo- gies (Uschold & King 1995, Gruninger 1996, Fern´andez, G´omez-P´erez & Juristo 1997), the use of ontologies in ap- plications (Bernaras, Laresgoiti & Corera 1996, Uschold, Healy, Williamson, Clark & Woods 1998), just to name a few. Integration in ONIONS (Gangemi et al. 1998), doesn’t mean the same as in the Ontolingua Server (Farquhar, Fikes, Pratt & Rice 1995) or in PhysSys (Borst 1997).
Starting from the original code, we need ﬁrst to vectorize the variables that parameterize our inner loop. In our example this is variable i. Since we need to spawn a new procedure in order to launch (possibly) a new thread, we encap- sulate the inner loop in a function call, which receives i as a parameter. Then, the stack allocation scheme automatically vectorizes variable i for us, since now each iteration will possess its own copy of i, independent from the others, and initialized to the value which each iteration would see in a sequential execution. The only problem here consists in working with a language which allows function calls to be made to run in parallel. Later we will explain how we deal with this issue in practice.
single point. Similarly, the Proximity scores were higher for Spanish by nearly 10 percentage points. These overall differences reflect the fact that the children produced more complex forms for Spanish, along with closer approximations to the adult target words, despite the fact that the targets words were longer. The differences in word shapes concerned both the syllable structures ofwords and the preferred syllables. The twin’s English words were equally divided between monosyllables and multisyllables, with a slight preference for monosyllables. Their Spanish words, however, were highly multisyllabic. Secondly, there were differences in syllable preferences. VCV syllables occurred over 10% of the time in Spanish, but not in English. Conversely, CVC syllables were highly used by both children in English, but by neither in Spanish.
Snatches of childhood memories are, then, invoked to try to rebuild the I, but the participation of external witnesses that confirm these protagonists’ existence is also valued, and momentarily solves their inability to recall past moments. Hence the anxiety of these characters to contact others, which is particularly true of the anguished narrator of The Calmative. He sits alone in a quiet harbour and waits for something to happen, while he envisions a very different scene full of hustle and bustle where the dreamed-of contact could be reached: “it would be a sad state of affairs if in that unscandalizable throng I couldn’t achieve a little encounter that would calm me a little, or exchange a few words with a navigator for example, words to carry away with me to my refuge, to add to my collection” (65). May this serve as an illustration of the many other attempts on the part of the protagonist of this story to substantiate that there is an I that others can confirm.
Mollicutes do not differ from prokaryotes in the way they divide, they do binary fission. In the typical binary fis- sion, the cytoplasm division take place at the same time that the genomic replication, but in Mycoplasmas, cyto- plasmic division may be delayed once the genomic replica- tion have occurred, including the formation of multinucle- us filaments. 31 The mechanisms that rules cellular division
Even if the last texts would be the perfect link to move on to comment on the internal senses, we will not address this subject because, despite Aristotle’s concern with the imagination and common sense, he did not leave behind a doctrinal body as such. It can be said that for him there is no series of faculties but a general interior sensibility of which fantasy, or the imagination, is a function which, in turn, conditions both the understanding of the concrete and abstract thinking. In his original works, Aquinas elaborates his own doctrine of internal sensible knowledge based on contributions by Avicena, Averroes and St. Albert Magnus. Mostly, he includes Avicena’s innovations, only to curtail the number of internal senses to four, following the number stipulated by Averroes. 73
From a high level view, there are three general families of methods for achiev- ing network data privacy. The first family encompasses “graph modification” methods. These methods first transform the data by edges or vertices modifi- cations (adding and/or deleting) and then release them. The data is thus made available for unconstrained analysis. The second family encompasses “gener- alization” or “clustering-based” approaches. These methods can be essentially regarded as grouping vertices and edges into partitions called super-vertices and super-edges. The details about individuals can be hidden properly, but the graph may be shrunk considerably after anonymization, which may not be desirable for analysing local structures. The generalized graph, which contains the link struc- tures among partitions as well as the aggregate description of each partition, can still be used to study macro-properties of the original graph. Among others,     and  are interesting approaches to generalization concept. Finally, the third family encompasses “privacy-aware computation” methods, which do not release data, but only the output of an analysis computation. The released output is such that it is very difficult to infer from it any information about an individual input datum. For instance, differential privacy  is a well-known privacy-aware computation approach. Differential private methods refer to al- gorithms which guarantee that individuals are protected under the definition of differential privacy, which imposes a guarantee on the data release mechanism rather than on the data itself. The goal is to provide statistical information about the data while preserving the privacy of users. Interesting works can be found, among others, in ,  and .
One of such settlements, where descendants of Ob chats and Volga Tatars-immigrants live, is the village of Yurt-Akbalyk, Kolyvan dis- trict. Here, meetings were held with the in- digenous people of the village, among whom Mavlyutov Rafyk Shafykovich, born in 1938. He played on the bayan the Siberian-Ta- tar melodies “Zugar Kulmuk”, “Gorodok” (“Tomsk Kane”), widespread among Tomsk Tatars. Also in his performance, the melodies of songs by Tatar composers sounded on the accordion: “Urman Kyzy” by D. Faizi, “Onyt- tyk Bugay” by G. Ilyasov, “Berenche Mhәbbәt” by S. Sadykova. He recalled how in the early 1950s a teacher of mathematics had a phono- graph with gramophone records and students in the whole class at school listened to Tatar songs performed by famous Tatar singers.
Abstract—Privacy protection in published data sets is of crucial importance, and anonymisation is one well-known technique for privacy protection that has been successfully used in practice. However, existing anonymisation frameworks have in mind spe- cific data structures (i.e., tabular data) and, because of this, these frameworks are difficult to apply in the case of RDF data. This paper presents an RDF anonymisation framework that has been developed to address the particularities of the RDF specification. Such framework includes an anonymisation model for RDF data, a set of anonymisation operations for the implementation of such model, and a metric for measuring precision and distortion of anonymised RDF data. Furthermore, this paper presents a use case of the proposed RDF anonymisation framework.
Bag of Keypoints (BKP) Un enfoque para extraer caracter´ısticas visuales muy utiliza- do en categorizaci´on visual es el de BKP . Con este enfoque primero se encuentran porciones de la imagen que presentan caracter´ısticas que pueden ser igualmente detec- tadas bajo variaci´on de escala, iluminaci´on o ruido (puntos de inter´es). Generalmente se caracterizan por ser zonas de gran contraste en la imagen. En nuestro trabajo utilizamos el algoritmo SURF  para encontrar estos puntos de inter´es. Cada uno se caracteriza mediante un vector que contiene informaci´on del mismo (posici´on, orientaci´on, entre otras). Posteriormente se entrena una t´ecnica de clustering para agrupar los puntos de inter´es en un diccionario de porciones de im´agenes seg´un sus vectores de caracter´ısti- cas, en una cantidad definida de clusters. En nuestro caso el tama˜no del diccionario es de 800 grupos y se obtuvo aplicando la t´ecnica de clusterizaci´on KMeans a los vec- tores descriptivos de los puntos de inter´es. Luego se analizan todas las im´agenes para obtener un histograma de aparici´on de cada punto de inter´es en cada imagen nueva. Este histograma se calcula para cada imagen sobre los distintos clusters, por lo que ten- dr´a 800 intervalos para nuestro caso. Finalmente se devuelven estos histogramas como vectores de caracter´ısticas. En nuestro caso entonces la cantidad de variables del vector de caracter´ısticas por imagen es de n = 800.
WPS profiles foresee a hierarchy of profiles: process concept, generic profile and implementation profile. Process concepts provide a documentation of what an operation does (purpose, methodology, properties) typically in form of HTML documents (OGC 2015b). Concepts can form a hierarchy by themselves as different subtypes ofoperations exist. For example, Euclidean distance buffer and geodesic distance buffer are both subtypes of a buffer operation. Generic profiles provide identifiers for operations, add the abstract interfaces to operations, and describe how operations work. They will contribute to resolving naming heterogeneity and may add details on the process mechanics, such as computational precision (Müller 2015). The implementation profile extends the generic profile with data exchange formats and non-functional parameters such as size limitations for inputs.
Like MHS and DOIDFH, FPFS uses a directory hashing [34, 93] approach, preserving the locality at a directory level, and keeping cache directory’s contents on a single server (at least, for small directories). However, different to MHS and DOIDFH, which use a global directory identifier assigned on creation time, FPFS assigns identifiers to directories by applying a hash function on the dirnames, so any member of the cluster can independently calculate the ID without extra conversion tables. FPFS also adopts some LH’s techniques, like pathname hashing to distribute metadata, dual-entry ACLs, and lazy migrations, although they are only applied on directories. This is an important difference with respect to file hashing techniques, since a rename does not produce a massive migration of file data; only directory objects are migrated. Permission changes do not produce a massive update of files’ ACLs either, because a file’s permissions are directly derived from its own ACL and its directory’s. FPFS also uses a hashing function  that minimizes metadata migration on cluster changes, and handles links in a more straightforward and efficient way.
Divide-and-conquer and recursive algorithms are considered specially suited for multiprocessor parallel computers. In fact, matrix multiplication is inherently good for shared memory multiprocessors because there is not data dependence. Matrices A and B are accessed only for reading to calculate every element of matrix C, and no element of matrix C has any relation (from the processing point of view) with any other element of the same matrix C. Unfortunately, networks of workstations used for parallel computing are not shared memory architectures, and implementations of divide-and-conquer and recursive algorithms are far from optimal in networks of workstations. The main reason for the loss of performance is found in the need of a shared (uniform) memory view of a distributed and loosely coupled memory architecture.