snu-aidas/HVMap-dataset huggingface dataset:
KEGGgraph: a graph approach to KEGG PATHWAY in R and bioconductor

MOTIVATION
KEGG PATHWAY is a service of Kyoto Encyclopedia of Genes and Genomes (KEGG), constructing manually curated pathway maps that represent current knowledge on biological networks in graph models. While valuable graph tools have been implemented in R/Bioconductor, to our knowledge there is currently no software package to parse and analyze KEGG pathways with graph theory.


RESULTS
We introduce the software package KEGGgraph in R and Bioconductor, an interface between KEGG pathways and graph models as well as a collection of tools for these graphs. Superior to existing approaches, KEGGgraph captures the pathway topology and allows further analysis or dissection of pathway graphs. We demonstrate the use of the package by the case study of analyzing human pancreatic cancer pathway.


AVAILABILITY
KEGGgraph is freely available at the Bioconductor web site (http://www.bioconductor.org). KGML files can be downloaded from KEGG FTP site (ftp://ftp.genome.jp/pub/kegg/xml).
Attribute reduction in decision-theoretic rough set models

Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequences. They can be distinguished not only from the syntax measures such as confidence, coverage and generality, but also the semantic measures such as decision-monotocity, cost and risk. The classification rules can be evaluated locally for each individual rule, or globally for a set of rules. Both the two types of classification rules can be generated from, and interpreted by, a decision-theoretic model, which is a probabilistic extension of the Pawlak rough set model. As an important concept of rough set theory, an attribute reduct is a subset of attributes that are jointly sufficient and individually necessary for preserving a particular property of the given information table. This paper addresses attribute reduction in decision-theoretic rough set models regarding different classification properties, such as: decisionmonotocity, confidence, coverage, generality and cost. It is important to note that many of these properties can be truthfully reflected by a single measure c in the Pawlak rough set model. On the other hand, they need to be considered separately in probabilistic models. A straightforward extension of the c measure is unable to evaluate these properties. This study provides a new insight into the problem of attribute reduction. Crown Copyright 2008 Published by Elsevier Inc. All rights reserved.
Semantics Extraction from Images

An overview of the state-of-the-art on semantics extraction from images is presented. In this survey, we present the relevant approaches in terms of content representation as well as in terms of knowledge representation. Knowledge can be represented in either implicit or explicit fashion while the image is represented in different levels, namely, low-level, intermediate and semantic level. For each combination of knowledge and image representation, a detailed discussion is addressed that leads to fruitful conclusions for the impact of each approach. 1 Semantics extraction basic pipeline Semantics extraction refers to digital data interpretation from a human point of view. In the case that the digital data correspond to images, this usually entails an appearance-based inference using color, texture and/or shape information along with a type of context inference (or representation) that can combine and transform these machine-extracted evidence into what we call a scene description. Following Biederman et al. [1] definitions of context in a visual scene, we can derive three types of context for real-world scene annotation problems: (i) semantic context which encodes the probability of a certain category to be present in a scene (e.g category “streets” has high probability to coexist with category “building” in the same scene ); (ii) spatial context which encodes the spatial relations of categories (e.g sky is usually above grass in a scene) and (iii) scale context which encodes the relative object size (category “human” is expected to occupy a small region in a scene which includes the“building” category). The research goals in semantics extraction are mostly a function of the granularity of the semantics in question. The goal could be the extraction of a single or multiple semantics of the entire image (e.g. indoor/outdoor setting), or the extraction of the semantics for different objects in an image. In the latter case, the semantics could be generic (e.g. a vehicle) or specific (e.g. a motorbike). Those goals make it clear that semantics extraction is not a new research area. Depending on the goal, the task of semantics extraction can be considered as a categorization, classification, recognition and understanding task that all share in common the effort for solving the semantic gap. As stated in [2], “Despite intensive recent research, the automatic establishment of a correspondence between
Stakeholder participation for sustainable waste management

Inadequate environmental sanitation in many cities is a major cause of diseases and is a drain on the economy by way of lost workdays, cost of treatment and cleanup activities. Municipal authorities and policymakers need to act fast to address this issue. Sustainable waste management provides a comprehensive inter-disciplinary framework for addressing the problems of managing urban solid waste, in the resource constrained developing countries where quality of such services are poor and costs are high often with no effective means of recovering them. Upgrading the coverage of waste management and services and increasing their efficiency is a precondition for improving the environmental quality of cities. This paper highlights the fact that the involvement and participation of all the stakeholders such as the waste generators, waste processors, formal and informal agencies, non-governmental organisations and financing institutions is a key factor for the sustainable waste management. r 2005 Elsevier Ltd. All rights reserved.
HILOG: A Foundation for Higher-Order Logic Programming

D We describe a novel logic, called HiLog, and show that it provides a more suitable basis for logic programming than does traditional predicate logic. HiLog has a higher-order syntax and allows arbitrary terms to appear in places where predicates, functions, and atomic formulas occur in predicate calculus. But its semantics is first-order and admits a sound and complete proof procedure. Applications of HiLog are discussed, including DCG grammars, higher-order and modular logic programming, and deductive databases. a
Practical Implementations of Arithmetic Coding 1

We provide a tutorial on arithmetic coding, showing how it provides nearly optimal data compression and how it can be matched with almost any probabilistic model. We indicate the main disadvantage of arithmetic coding, its slowness, and give the basis of a fast, space-e cient, approximate arithmetic coder with only minimal loss of compression e ciency. Our coder is based on the replacement of arithmetic by table lookups coupled with a new deterministic probability estimation scheme. Index terms : Data compression, arithmetic coding, adaptive modeling, analysis of algorithms, data structures, low precision arithmetic. A similar version of this paper appears in Image and Text Compression, James A. Storer, ed., Kluwer Academic Publishers, Norwell, MA, 1992, 85{112. A shortened version of this paper appears in the proceedings of the International Conference on Advances in Communication and Control (COMCON 3), Victoria, British Columbia, Canada, October 16{18, 1991. Support was provided in part by NASA Graduate Student Researchers Program grant NGT{ 50420 and by a National Science Foundation Presidential Young Investigators Award grant with matching funds from IBM. Additional support was provided by a Universities Space Research Association/CESDIS associate membership. Support was provided in part by National Science Foundation Presidential Young Investigator Award CCR{9047466 with matching funds from IBM, by NSF research grant CCR{9007851, by Army Research O ce grant DAAL03{91{G{0035, and by the O ce of Naval Research and the Defense Advanced Research Projects Agency under contract N00014{91{J{4052ARPA Order No. 8225. Additional support was provided by a Universities Space Research Association/CESDIS associate membership.
Mutual information and minimum mean-square error in multiuser Gaussian channels

1. Introduction Due to the lack of explicit closed form expressions of the mutual information for binary inputs, which were provided only for the BPSK and QPSK for the single input single output (SISO) case, [1], [2], [3], it is of particular importance to address connections between information theory and estimation theory for the multiuser case. Connections between information theory and estimation theory dates back to the work of Duncan, in [4] who showed that for the continuous-time additive white Gaussian noise (AWGN) channel, the filtering minimum mean squared error (causal estimation) is twice the input-output mutual information for any underlying signal distribution. Recently, Guo, Shamai, and Verdu have illuminated intimate connections between information theory and estimation theory in a seminal paper, [1]. In particular, Guo et al. have shown that in the classical problem of information transmission through the conventional AWGN channel, the derivative of the mutual information with respect to the SNR is equal to the smoothing minimum mean squared error (noncausal estimation); a relationship that holds for scalar, vector, discrete-time and continuous-time channels regardless of the input statistics. There have been extensions of these results to the case of mismatched input distributions in the scalar Gaussian channel in [5] and [6]. However, the fundamental relation between the derivative of the mutual information and the MMSE, known as I-MMSE identity, and defined for point to point channels with any noise or input distributions in [1] is not anymore suitable for the multiuser case. Therefore, in this paper, we revisit the connections between the mutual information and the MMSE for the multiuser setup. We generalize the I-MMSE relation to the multiuser case. In particular, we prove that the derivative of the mutual information with respect to the signal to noise ratio (SNR) is equal to the minimum mean squared error (MMSE) plus a covariance induced due to the interference, quantified by a term with respect to the cross correlation of the users inputs' estimates, their channels, and their precoding matrices. Further, we capitalize on this unveiled multiuser I-MMSE relation to derive the components of the multiuser mutual information. In particular, we derive the derivative of the conditinal and non-conditional mutual information with respect to the SNR. Further extensions of this result allows a generalization of the relations of linear vector Gaussian channels in [7] to multiuser channels. In particular, [8], [9] generalize the I-MMSE relation to the per-user gradient …
Differentiating optic disc edema from optic nerve head drusen on optical coherence tomography.

OBJECTIVE
To assess optical coherence tomography in differentiating optic disc edema (ODE) due to papilledema and other optic neuropathies from optic nerve head drusen (ONHD).


METHODS
Optical coherence tomographic images from 60 subjects (20 with ODE, 20 with ONHD, and 20 control subjects) were assessed qualitatively and quantitatively. Qualitative criteria for ODE included an elevated optic nerve head with smooth internal contour and subretinal hyporeflective space (SHYPS) with recumbent "lazy V" pattern. Optic nerve head drusen displayed a "lumpy-bumpy" internal optic nerve contour and a rapid decline in SHYPS thickness. Quantitative comparisons included retinal nerve fiber layer and SHYPS thickness.


RESULTS
Optical coherence tomography differentiated ODE from ONHD qualitatively (sensitivity, 63%; specificity, 63%) and quantitatively (sensitivity, 80%; specificity, 90%). Respective differences in mean retinal nerve fiber layer thickness between ODE and ONHD were significant (P < .002) superiorly (206.8 vs 121.7 microm), nasally (176.3 vs 78.6 microm), inferiorly (247.2 vs 153.8 microm), and temporally (180.0 vs 85.5 microm). Respective differences in mean SHYPS thickness between ODE and ONHD were significant (P < .001) at radii of 0.75 mm (512.1 vs 274.4 microm), 1.5 mm (291.4 vs 103.0 microm), and 2.0 mm (145.5 vs 60.7 microm).


CONCLUSION
Optical coherence tomography can differentiate ODE from ONHD, particularly when the nasal retinal nerve fiber layer and SHYPS thickness at the 2.0-mm radius are greater than 86 microm and 127 microm, respectively.
Trajectory planning and tracking of ball and plate system using hierarchical fuzzy control scheme

Ball and plate system is the extension of traditional ball and beam system. In this paper, a trajectory planning and tracking problem of ball and plate system is put forward to proof-test diverse control schemes. Firstly, we derive the mathematical model of the ball and plate system in detail. Then a hierarchical fuzzy control scheme is proposed to deal with this problem. Our scheme is composed of three levels. The lowest level is a TS type fuzzy tacking controller; the middle level is a fuzzy supervision controller that takes actions in extreme situations; and the top level is a fuzzy planning controller that determines the desired trajectory. In order to optimize the ball’s moving trajectory, the genetic algorithm is introduced to adjust the output membership functions of the fuzzy planning controller. Simulation results have shown that the hierarchical fuzzy control scheme can control the ball from a point to another without hitting the obstacles and in the least time. c © 2003 Elsevier B.V. All rights reserved.
CORPORATE SOCIAL RESPONSIBILITY IN EMERGING MARKETS

Purpose: This paper analyses CSR initiatives in emerging markets from developed-countriesbased multinational companies (MNCs). Methods: The analysis is based on eight case studies with data collected through in-depth interviews with senior managers of the companies representing 85% of the Spanish foreign investments in Latin America. Results: The results show that CSR initiatives from these companies seem to be guided by Instrumental Theories as they use these initiatives as a strategic tool to achieve economic objectives, seek a positive relation between them and their financial performance, and use them to strengthen their reputation. Conclusions: The findings tend to indicate that Instrumental Theories of CSR seem to apply for Western MNCs operating in emerging markets.
The peculiarities of knowledge management processes in SMEs: the case of Singapore

Purpose – The objectives of this study are two-fold. The first is to examine the peculiarities of KM processes that are unique in SMEs from three perspectives, namely knowledge creation, knowledge sharing and knowledge reuse. Secondly, to identify enablers and impediments of these KM processes that influence the competitiveness of SMEs. Design/methodology/approach – The study adopted a case study approach involving 21 participants comprising management staff and front-line employees from four Singaporean SMEs. Findings – The SME owner, rather than the employees, was found to be the key source and creator of knowledge and the sole driver of the KM processes. In SMEs, knowledge creation takes the form of innovative customized solutions to meet customers’ needs; knowledge sharing occurs through cross functionality, overlapping roles, and facilitated by close physical proximity in open workspaces; and knowledge reuse is often made tacitly, where common knowledge is prevalently embedded within the KM processes of SMEs. The enablers of knowledge creation process rested largely on the owner’s innovativeness, creativity and ability to acquire knowledge of the industry. Knowledge sharing processes are enabled by the awareness of roles, mutual respect and the level of trust among employees within the SME while knowledge reuse is fostered by close proximity of employees and the willingness and openness of the owner to impart his knowledge. The lack of the above enablement factors mentioned will hinder these KM processes. Research limitations/implications – The study is limited by the fact that data was collected from four SMEs in Singapore. Furthermore, only a small sample of staff from these SMEs was interviewed. Hence the findings need to be interpreted in light of such a scope. Practical implications – For SMEs, this research provides perspectives on the factors influencing KM processes, in particular, the importance of the owners’ knowledge and leadership, the flexibility and adaptability of the organization, and open culture to enable the capitalization of its knowledge assets to survive and stay competitive. For practitioners, this paper reinforces the importance of the management owners’ innovativeness, initiatives and support, and the level of social interaction and high level of trusts among employees in the SMEs to as enablers to effective KM processes in SMEs. Originality/value – To deepen on-going knowledge management research on SMEs, this paper provides insights and rich context to the distinctness of KM processes in SMEs.
Informal social communication.
Stuttering in relation to anxiety, temperament, and personality: review and analysis with focus on causality.

UNLABELLED
Anxiety and emotional reactions have a central role in many theories of stuttering, for example that persons who stutter would tend to have an emotionally sensitive temperament. The possible relation between stuttering and certain traits of temperament or personality were reviewed and analyzed, with focus on temporal relations (i.e., what comes first). It was consistently found that preschool children who stutter (as a group) do not show any tendencies toward elevated temperamental traits of shyness or social anxiety compared with children who do not stutter. Significant group differences were, however, repeatedly reported for traits associated with inattention and hyperactivity/impulsivity, which is likely to reflect a subgroup of children who stutter. Available data is not consistent with the proposal that the risk for persistent stuttering is increased by an emotionally reactive temperament in children who stutter. Speech-related social anxiety develops in many cases of stuttering, before adulthood. Reduction of social anxiety in adults who stutter does not in itself appear to result in significant improvement of speech fluency. Studies have not revealed any relation between the severity of the motor symptoms of stuttering and temperamental traits. It is proposed that situational variability of stuttering, related to social complexity, is an effect of interference from social cognition and not directly from the emotions of social anxiety. In summary, the studies in this review provide strong evidence that persons who stutter are not characterized by constitutional traits of anxiety or similar constructs.


EDUCATIONAL OBJECTIVES
This paper provides a review and analysis of studies of anxiety, temperament, and personality, organized with the objective to clarify cause and effect relations. Readers will be able to (a) understand the importance of effect size and distribution of data for interpretation of group differences; (b) understand the role of temporal relations for interpretation of cause and effect; (c) discuss the results of studies of anxiety, temperament and personality in relation to stuttering; and (d) discuss situational variations of stuttering and the possible role of social cognition.
A quad 25Gb/s 270mW TIA in 0.13µm BiCMOS with <0.15dB crosstalk penalty

The push for 100Gb/s optical transport and beyond necessitates electronic components at higher speed and integration level in order to drive down cost, complexity and size of transceivers [1-2]. This requires parallel multi-channel optical transceivers each operating at 25Gb/s and beyond. Due to variations in the output power of transmitters and in some cases different optical paths the parallel receivers have to operate at different input optical power levels. This trend places increasing strain to the acceptable inter-channel crosstalk in integrated multi-channel receivers [3]. Minimizing this cross-talk penalty when all channels are operational is becoming increasingly important in ultra-high throughput optical links.
Bilateral Back-Projection for Single Image Super Resolution

In this paper, a novel algorithm for single image super resolution is proposed. Back-projection [1] can minimize the reconstruction error with an efficient iterative procedure. Although it can produce visually appealing result, this method suffers from the chessboard effect and ringing effect, especially along strong edges. The underlining reason is that there is no edge guidance in the error correction process. Bilateral filtering can achieve edge-preserving image smoothing by adding the extra information from the feature domain. The basic idea is to do the smoothing on the pixels which are nearby both in space domain and in feature domain. The proposed bilateral back-projection algorithm strives to integrate the bilateral filtering into the back-projection method. In our approach, the back-projection process can be guided by the edge information to avoid across-edge smoothing, thus the chessboard effect and ringing effect along image edges are removed. Promising results can be obtained by the proposed bilateral back-projection method efficiently.
A framework and theory for cyber security assessments

Information system security risk, defined as the product of the monetary losses associated with security incidents and the probability that they occur, is a suitable decision criterion when considering different information system architectures. This paper describes how probabilistic relational models can be used to specify architecture metamodels so that security risk can be inferred from metamodel-instantiations. A probabilistic relational model contains classes, attributes, and class-relationships. It can be used to specify architectural metamodels similar to class diagrams in the Unified Modeling Language. In addition, a probabilistic relational model makes it possible to associate a probabilistic dependency model to the attributes of classes in the architectural metamodel. This paper proposes a set of abstract classes that can be used to create probabilistic relational models so that they enable inference of security risk from instantiated architecture models. If an architecture metamodel is created by specializing the abstract classes proposed in this paper, the instantiations of the metamodel will generate a probabilistic dependency model that can be used to calculate the security risk associated with these instantiations. The abstract classes make it possible to derive the dependency model and calculate security risk from an instance model that only specifies assets and their relationships to each other. Hence, the person instantiating the architecture metamodel is not required to assess complex security attributes to quantify security risk using the instance model. Paper A: A probabilistic relational model for security risk analysis
A Language and Program for Complex Bayesian Modelling

http://www.jstor.org A Language and Program for Complex Bayesian Modelling Author(s): W. R. Gilks, A. Thomas and D. J. Spiegelhalter Source: Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 43, No. 1, Special Issue: Conference on Practical Bayesian Statistics, 1992 (3) (1994), pp. 169-177 Published by: for the Wiley Royal Statistical Society Stable URL: http://www.jstor.org/stable/2348941 Accessed: 19-08-2014 17:40 UTC