Analysis of common attacks in public-key cryptosystems based on low-density parity-check codes

The security and reliability of a class of public-key cryptosystems against attacks by unauthorized parties, who had acquired partial knowledge of one or more of the private key components and/or of the message, were discussed. The standard statistical mechanical methods of dealing with diluted spin systems with replica symmetric considerations were analyzed. The dynamical transition which defined decryption success in practical situation was studied. The phase diagrams which showed the dynamical threshold as a function of the partial acquired knowledge of the private key were also presented.

Mixed Theories

In the present paper we investigate the life cycles of formalized theories that appear in decision making instruments and science. In few words mixed theories are build in the following steps: Initially a small collection of facts is the kernel of the theory. To express these facts we make a special formalized language. When the collection grows we add some inference rules and thus some axioms to compress the knowledge. The next step is to generalize these rules to all expressions in the formalized language. For these rules we introduce some conclusion procedure. In such a way we make small theories for restricted fields of the knowledge. The most important procedure is the mixing of these partial knowledge systems. In that step we glue the theories together and eliminate the contradictions. The last operation is the most complicated one and some simplifying procedures are proposed.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Importance of knowledge management processes in a project-based organization : a case study of research enterprise

Knowledge Management (KM) is vital factor to successfully undertake projects. The temporary nature of projects necessitates employing useful KM practices for tackling issues such as knowledge leakiness and rework. The Project Management Office (PMO) is a unit within organizations to facilitate and oversee organizational projects. Project Management Maturity Models (PMMM) shows the development of PMOs from immature to mature levels. The existing PMMMs have focused on discussing Project Management (PM) practices, however, the management of project knowledge is yet to be addressed, at various levels of maturity. This research project was undertaken to investigate the mentioned gap for addressing KM practices at the existing PMMMs. Due to the exploratory and inductive nature of this research, qualitative methods were chosen as the research methodology. In total, three cases selected from different industries: research; mining and government organizations, to provide broad categories for research and research questions were examined using the developed framework. This paper presents the partial findings of undertaken investigation of the research organisation with the lowest level of maturity. The result shows that knowledge creation and capturing are the most important processes, while knowledge transferring and reusing are not as important as the other two processes. In addition, it was revealed that provision of “knowledge about client” and “project management knowledge” are the most important types of knowledge that are required at this level of maturity. In conclusion, the outcomes of this paper shall provide powerful guidance to PMOs at lowest level of maturity from KM point of view.

Partial epilepsy syndrome in a Gypsy family linked to 5q31.3-q32

PURPOSE The restricted genetic diversity and homogeneous molecular basis of Mendelian disorders in isolated founder populations have rarely been explored in epilepsy research. Our long-term goal is to explore the genetic basis of epilepsies in one such population, the Gypsies. The aim of this report is the clinical and genetic characterization of a Gypsy family with a partial epilepsy syndrome. METHODS Clinical information was collected using semistructured interviews with affected subjects and informants. At least one interictal electroencephalography (EEG) recording was performed for each patient and previous data obtained from records. Neuroimaging included structural magnetic resonance imaging (MRI). Linkage and haplotype analysis was performed using the Illumina IVb Linkage Panel, supplemented with highly informative microsatellites in linked regions and Affymetrix SNP 5.0 array data. RESULTS We observed an early-onset partial epilepsy syndrome with seizure semiology strongly suggestive of temporal lobe epilepsy (TLE), with mild intellectual deficit co-occurring in a large proportion of the patients. Psychiatric morbidity was common in the extended pedigree but did not cosegregate with epilepsy. Linkage analysis definitively excluded previously reported loci, and identified a novel locus on 5q31.3-q32 with an logarithm of the odds (LOD) score of 3 corresponding to the expected maximum in this family. DISCUSSION The syndrome can be classified as familial temporal lobe epilepsy (FTLE) or possibly a new syndrome with mild intellectual deficit. The linked 5q region does not contain any ion channel-encoding genes and is thus likely to contribute new knowledge about epilepsy pathogenesis. Identification of the mutation in this family and in additional patients will define the full phenotypic spectrum.

Distributed space-time codes for cooperative networks with partial CSI

Design criteria and full-diversity Distributed Space Time Codes (DSTCs) for the two phase transmission based cooperative diversity protocol of Jing-Hassibi and the Generalized Nonorthogonal Amplify and Forward (GNAF) protocol are reported, when the relay nodes are assumed to have knowledge of the phase component of the source to relay channel gains. It is shown that this under this partial channel state information (CSI), several well known space time codes for the colocated MIMO (Multiple Input Multiple Output) channel become amenable for use as DSTCs. In particular, the well known complex orthogonal designs, generalized coordinate interleaved orthogonal designs (GCIODs) and unitary weight single symbol decodable (UW-SSD) codes are shown to satisfy the required design constraints for DSTCs. Exploiting the relaxed code design constraints, we propose DSTCs obtained from Clifford Algebras which have low ML decoding complexity.

Discovering injective episodes with general partial orders

Frequent episode discovery is a popular framework for temporal pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Currently algorithms exist for episode discovery only when the associated partial order is total order (serial episode) or trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with unrestricted partial orders when the associated event-types are unique. These algorithms can be easily specialized to discover only serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that frequency alone is not a sufficient measure of interestingness in the context of partial order mining. We propose a new interestingness measure for episodes with unrestricted partial orders which, when used along with frequency, results in an efficient scheme of data mining. Simulations are presented to demonstrate the effectiveness of our algorithms.

Towards a knowledge of chytrids. Part 3. Spirospora paradoxa nov.gen. - nov.spec. [Translation from: Archiv fur Protistenkunde 54 510-528 [pages 522-525 and plate 28 only], 1926]

This partial translation of the original paper provides morphological observations on the fungus Spirospora paradoxa. Illustrations are included here.

Partial characterization of the hemolytic activity of the nematocyst venom from the jellyfish Cyanea nozakii Kishinouye

Using a recently developed technique to extract jellyfish venom from nematocysts, the present study investigated the hemolytic activity of Cyanea nozakii Kishinouye nematocyst venom on chicken erythrocytes. Venom extract caused a significant concentration-dependent hemolytic effect. The extract could retain its activity at -80 degrees C but was unstable when kept at 4 degrees C and -20 degrees C for 2 days. The hemolytic activity was inhibited by heating within the range of 37-100 degrees C. The extract was active over a pH range of 5.0-8.63 and the pH optima for the extract was 7.8. Incubation of the venom with sphingomyelin specially inhibited hemolytic activity by up to 70%. Cu2+ and Mn2+ greatly reduced the hemolytic activity while Mg2+, Sr2+ and Ba2+ produced a relatively low inhibiting effect on the hemolytic activity. Treatment with Ca2+ induced a concentration-dependent increase in the hemolytic activity. In the presence of 5 mM EDTA, all the hemolytic activity was lost, however, the venom containing 1.5 mM EDTA was stable in the long-term storage. PLA(2) activity was also found in the nematocyst venom of C. nozakii. These characteristics provide us a fundamental knowledge in the C. nozakii nematocyst venom which would benefit future research. (C) 2010 Published by Elsevier Ltd.

Computer System for Visual Recognition Using Active Knowledge

A system for visual recognition is described, with implications for the general problem of representation of knowledge to assist control. The immediate objective is a computer system that will recognize objects in a visual scene, specifically hammers. The computer receives an array of light intensities from a device like a television camera. It is to locate and identify the hammer if one is present. The computer must produce from the numerical "sensory data" a symbolic description that constitutes its perception of the scene. Of primary concern is the control of the recognition process. Control decisions should be guided by the partial results obtained on the scene. If a hammer handle is observed this should suggest that the handle is part of a hammer and advise where to look for the hammer head. The particular knowledge that a handle has been found combines with general knowledge about hammers to influence the recognition process. This use of knowledge to direct control is denoted here by the term "active knowledge". A descriptive formalism is presented for visual knowledge which identifies the relationships relevant to the active use of the knowledge. A control structure is provided which can apply knowledge organized in this fashion actively to the processing of a given scene.

The Use of Equality in Deduction and Knowledge Representation

This report describes a system which maintains canonical expressions for designators under a set of equalities. Substitution is used to maintain all knowledge in terms of these canonical expressions. A partial order on designators, termed the better-name relation, is used in the choice of canonical expressions. It is shown that with an appropriate better-name relation an important engineering reasoning technique, propagation of constraints, can be implemented as a special case of this substitution process. Special purpose algebraic simplification procedures are embedded such that they interact effectively with the equality system. An electrical circuit analysis system is developed which relies upon constraint propagation and algebraic simplification as primary reasoning techniques. The reasoning is guided by a better-name relation in which referentially transparent terms are preferred to referentially opaque ones. Multiple description of subcircuits are shown to interact strongly with the reasoning mechanism.

Deriving explanations from partial temporal information

The representation and manipulation of natural human understanding of temporal phenomena is a fundamental field of study in Computer Science, which aims both to emulate human thinking, and to use the methods of human intelligence to underpin engineering solutions. In particular, in the domain of Artificial Intelligence, temporal knowledge may be uncertain and incomplete due to the unavailability of complete and absolute temporal information. This paper introduces an inferential framework for deriving logical explanations from partial temporal information. Based on a graphical representation which allows expression of both absolute and relative temporal knowledge in incomplete forms, the system can deliver a verdict to the question if a given set of statements is temporally consistent or not, and provide understandable logical explanation of analysis by simplified contradiction and rule based reasoning.

Globalising knowledge

The technology enablers of Friedman’s Flat World have made enormous differences to knowledge creation and sharing. The disaggregation of supply chains has been followed by the partial disaggregation of knowledge supply chains as some knowledge producers set up innovation centres in various locations around the world. But there is considerable evidence that instead of a flat world distribution of knowledge production there are hubs of innovation and knowledge creation developing in a relatively limited number of locations around the world. This paper discusses this clustering effect and looks at some of the possible explanations. In particular it looks at the human and social aspects of knowledge creation and sharing that resist distance and are starting to be taken into account in the design of technological approaches to knowledge management.