OpenRaiser/Intern-Atlas huggingface dataset:
Fuzzy soft rough K-Means clustering approach for gene expression data
Venue: arXiv cs.LG 2012
Year: 2012

Clustering is one of the widely used data mining techniques for medical diagnosis. Clustering can be considered as the most important unsupervised learning technique. Most of the clustering methods group data based on distance and few methods cluster data based on similarity. The clustering algorithms classify gene expression data into clusters and the functionally related genes are grouped together in an efficient manner. The groupings are constructed such that the degree of relationship is strong among members of the same cluster and weak among members of different clusters. In this work, we focus on a similarity relationship among genes with similar expression patterns so that a consequential and simple analytical decision can be made from the proposed Fuzzy Soft Rough K-Means algorithm. The algorithm is developed based on Fuzzy Soft sets and Rough sets. Comparative analysis of the proposed work is made with bench mark algorithms like K-Means and Rough K-Means and efficiency of the proposed algorithm is illustrated in this work by using various cluster validity measures such as DB index and Xie-Beni index.
Relationship-aware sequential pattern mining
Venue: arXiv cs.DB 2012
Year: 2012

Relationship-aware sequential pattern mining is the problem of mining frequent patterns in sequences in which the events of a sequence are mutually related by one or more concepts from some respective hierarchical taxonomies, based on the type of the events. Additionally events themselves are also described with a certain number of taxonomical concepts. We present RaSP an algorithm that is able to mine relationship-aware patterns over such sequences; RaSP follows a two stage approach. In the first stage it mines for frequent type patterns and {\em all} their occurrences within the different sequences. In the second stage it performs hierarchical mining where for each frequent type pattern and its occurrences it mines for more specific frequent patterns in the lower levels of the taxonomies. We test RaSP on a real world medical application, that provided the inspiration for its development, in which we mine for frequent patterns of medical behavior in the antibiotic treatment of microbes and show that it has a very good computational performance given the complexity of the relationship-aware sequential pattern mining problem.
Design of a Smart Embedded Uninterrupted Power Supply System for Personal Computers
Venue: arXiv cs.SY 2012
Year: 2012

Digital equipment such as computers, telecommunication systems and instruments use microprocessors that operate at high frequencies allowing them to carry out millions or even billions of operations per second. A disturbance in the electrical supply lasting just a few milliseconds can affect thousands or millions of basic operations. The result may be malfunctioning and loss of data with dangerous or costly consequences (e.g. loss of production). That is why many loads, called sensitive or critical loads, require a supply that is protected. Many manufacturers of sensitive equipment specify very strict tolerances, much stricter than those in the distribution system for the supply of their equipment, one example being Computer Business Equipment Manufacturers Association for computer equipment against distribution system disturbances. The design of this uninterrupted power supply (UPS) for personal computer (PC) is necessitated due to a need for enhanced portability in the design of personal computer desktop workstations. Apart from its original functionality as a backup source of power, this design incorporates the unit within the system unit casing, thereby reducing the number of system components available. Also, the embedding of this unit removes the untidiness of connecting wires and makes the whole computer act like a laptop. Not to be left out is the choice of a microcontroller as an important part of the circuitry. This has eliminated the weight and space-consuming components that make up an original design. The singular use of this microcontroller places the UPS under the class of an advanced technology device.
Synchronization of a class of cyclic discrete-event systems describing legged locomotion
Venue: arXiv cs.SY 2012
Year: 2012

It has been shown that max-plus linear systems are well suited for applications in synchronization and scheduling, such as the generation of train timetables, manufacturing, or traffic. In this paper we show that the same is true for multi-legged locomotion. In this framework, the max-plus eigenvalue of the system matrix represents the total cycle time, whereas the max-plus eigenvector dictates the steady-state behavior. Uniqueness of the eigenstructure also indicates uniqueness of the resulting behavior. For the particular case of legged locomotion, the movement of each leg is abstracted to two-state circuits: swing and stance (leg in flight and on the ground, respectively). The generation of a gait (a manner of walking) for a multiple legged robot is then achieved by synchronizing the multiple discrete-event cycles via the max-plus framework. By construction, different gaits and gait parameters can be safely interleaved by using different system matrices. In this paper we address both the transient and steady-state behavior for a class of gaits by presenting closed-form expressions for the max-plus eigenvalue and max-plus eigenvector of the system matrix and the coupling time. The significance of this result is in showing guaranteed robustness to perturbations and gait switching, and also a systematic methodology for synthesizing controllers that allow for legged robots to change rhythms fast.
CODYRUN, outil de simulation et d'aide à la conception thermo-aéraulique de bâtiments
Venue: arXiv cs.CE 2012
Year: 2012

This article presents the CODYRUN software developped by University of La Réunion. It is a multizone thermal software, with detailled airflow and humidity transfer calculations. One of its specific aspects is that it constitutes a research tool, a design tool used by the lab and professionnals and also a teaching tool. After a presentation of the multiple model aspect, some details of the tree modules associated to physical phenomenons are given. Elements of validation are exposed in next paraghaph, and then a few details of the front end.
Time-variant Linear reduction model approximation : application to thermal and airflow building simulation
Venue: arXiv cs.CE 2012
Year: 2012

Considering the natural ventilation, the thermal behavior of buildings can be described by a linear time varying model. In this paper, we describe an implementation of model reduction of linear time varying systems. We show the consequences of the model reduction on computing time and accuracy. Finally, we compare experimental measures and simulation results using the initial model or the reduced model. The reduced model shows negligible difference in accuracy, and the computing time shortens.
Weather sequences for predicting HVAC system behaviour in residential units located in tropical climates
Venue: arXiv cs.CE 2012
Year: 2012

The purpose of our research deals with the description of a methodology for the definition of specific weather sequences and their influence on the energy needs of HVAC system. We'll apply the method on the tropical Reunion Island. The methodological approach based on a detailed analysis of weather sequences leads to a classification of climatic situations that can be applied to the site. These sequences have been used to simulate buildings and air handling systems thanks to a thermal simulation code, CODYRUN. Results bring to the light how necessary it is to have coherent meteorological data for this kind of simulation.
Prior-free Auctions for Budgeted Agents
Venue: arXiv cs.GT 2012
Year: 2012

We consider prior-free auctions for revenue and welfare maximization when agents have a common budget. The abstract environments we consider are ones where there is a downward-closed and symmetric feasibility constraint on the probabilities of service of the agents. These environments include position auctions where slots with decreasing click-through rates are auctioned to advertisers. We generalize and characterize the envy-free benchmark from Hartline and Yan (2011) to settings with budgets and characterize the optimal envy-free outcomes for both welfare and revenue. We give prior-free mechanisms that approximate these benchmarks. A building block in our mechanism is a clinching auction for position auction environments. This auction is a generalization of the multi-unit clinching auction of Dobzinski et al. (2008) and a special case of the polyhedral clinching auction of Goel et al. (2012). For welfare maximization, we show that this clinching auction is a good approximation to the envy-free optimal welfare for position auction environments. For profit maximization, we generalize the random sampling profit extraction auction from Fiat et al. (2002) for digital goods to give a 10.0-approximation to the envy-free optimal revenue in symmetric, downward-closed environments. The profit maximization question is of interest even without budgets and our mechanism is a 7.5-approximation which improving on the 30.4 bound of Ha and Hartline (2012).
Influence Analysis in the Blogosphere
Venue: arXiv cs.SI 2012
Year: 2012

In this paper we analyze influence in the blogosphere. Recently, influence analysis has become an increasingly important research topic, as online communities, such as social networks and e-commerce sites, playing a more and more significant role in our daily life. However, so far few studies have succeeded in extracting influence from online communities in a satisfactory way. One of the challenges that limited previous researches is that it is difficult to capture user behaviors. Consequently, the influence among users could only be inferred in an indirect and heuristic way, which is inaccurate and noise-prone. In this study, we conduct an extensive investigation in regard to influence among bloggers at a Japanese blog web site, BIGLOBE. By processing the log files of the web servers, we are able to accurately extract the activities of BIGLOBE members in terms of writing their blog posts and reading other member's posts. Based on these activities, we propose a principled framework to detect influence among the members with high confidence level. From the extracted influence, we conduct in-depth analysis on how influence varies over different topics and how influence varies over different members. We also show the potentials of leveraging the extracted influence to make personalized recommendation in BIGLOBE. To our best knowledge, this is one of the first studies that capture and analyze influence in the blogosphere in such a large scale.
The Kernel-SME Filter for Multiple Target Tracking
Venue: arXiv cs.SY 2012
Year: 2012

We present a novel method called Kernel-SME filter for tracking multiple targets when the association of the measurements to the targets is unknown. The method is a further development of the Symmetric Measurement Equation (SME) filter, which removes the data association uncertainty of the original measurement equation with the help of a symmetric transformation. The underlying idea of the Kernel-SME filter is to construct a symmetric transformation by means of mapping the measurements to a Gaussian mixture. This transformation is scalable to a large number of targets and allows for deriving a Gaussian state estimator that has a cubic time complexity in the number of targets.
Tangent Bundle Manifold Learning via Grassmann&Stiefel Eigenmaps
Venue: arXiv cs.LG 2012
Year: 2012

One of the ultimate goals of Manifold Learning (ML) is to reconstruct an unknown nonlinear low-dimensional manifold embedded in a high-dimensional observation space by a given set of data points from the manifold. We derive a local lower bound for the maximum reconstruction error in a small neighborhood of an arbitrary point. The lower bound is defined in terms of the distance between tangent spaces to the original manifold and the estimated manifold at the considered point and reconstructed point, respectively. We propose an amplification of the ML, called Tangent Bundle ML, in which the proximity not only between the original manifold and its estimator but also between their tangent spaces is required. We present a new algorithm that solves this problem and gives a new solution for the ML also.
An Algorithm for Finding Convex Hulls of Planar Point Sets
Venue: arXiv cs.CG 2012
Year: 2012

This paper presents an alternate choice of computing the convex hulls (CHs) for planar point sets. We firstly discard the interior points and then sort the remaining vertices by x- / y- coordinates separately, and later create a group ofquadrilaterals (e-Quads) recursively according to the sequences ofthe sorted lists of points. Finally, the desired CH is built based on a simple polygon derived from all e-Quads. Besides the preprocessing for original planar point sets, this algorithm has another mechanism of discarding interior point when form e-Quads and assemble the simple polygon. Compared with three popular CH algorithms, the proposed algorithm can generate CHs faster thanthe three but has a penalty in space cost.
Green WSUS
Venue: arXiv cs.OH 2012
Year: 2012

The new era of information and communication technology (ICT) calls for a greater understanding of the environmental impacts of recent technology. With increasing energy cost and growing environmental concerns, green IT is receiving more and more attention. Network and system design play a crucial role in both computing and telecommunication systems. Significant part of this energy cost goes to system update by downloading regularly patches and bug fixes to solve security problems and to assure that the operating system and other systems function properly. This paper describes a new design of Windows Server Update Services (WSUS), system responsible of downloads of the mentioned patches and updates from Microsoft Update website and then distributes them to computers on a network. The general idea behind our proposed design is simple. Instead of the periodical check done by the WSUS servers to ensure update form Microsoft main servers, we rather propose to reverse the scenario in order to reduce energy consumption. In the proposed design, the Microsoft main server(s) sends signal to all WSUS servers to inform them about new updates. Once the signal received, WSUS can contact the main server to start downloading.
On The Optimization of Dijkstras Algorithm
Venue: arXiv cs.DS 2012
Year: 2012

In this paper, we propose some amendment on Dijkstras algorithm in order to optimize it by reducing the number of iterations. The main idea is to solve the problem where more than one node satisfies the condition of the second step in the traditional Dijkstras algorithm. After application of the proposed modifications, the maximum number of iterations of Dijkstras algorithm is less than the number of the graphs nodes.
Learning Joint Query Interpretation and Response Ranking
Venue: arXiv cs.IR 2012
Year: 2012

Thanks to information extraction and semantic Web efforts, search on unstructured text is increasingly refined using semantic annotations and structured knowledge bases. However, most users cannot become familiar with the schema of knowledge bases and ask structured queries. Interpreting free-format queries into a more structured representation is of much current interest. The dominant paradigm is to segment or partition query tokens by purpose (references to types, entities, attribute names, attribute values, relations) and then launch the interpreted query on structured knowledge bases. Given that structured knowledge extraction is never complete, here we use a data representation that retains the unstructured text corpus, along with structured annotations (mentions of entities and relationships) on it. We propose two new, natural formulations for joint query interpretation and response ranking that exploit bidirectional flow of information between the knowledge base and the corpus.One, inspired by probabilistic language models, computes expected response scores over the uncertainties of query interpretation. The other is based on max-margin discriminative learning, with latent variables representing those uncertainties. In the context of typed entity search, both formulations bridge a considerable part of the accuracy gap between a generic query that does not constrain the type at all, and the upper bound where the "perfect" target entity type of each query is provided by humans. Our formulations are also superior to a two-stage approach of first choosing a target type using recent query type prediction techniques, and then launching a type-restricted entity search query.
Image Steganography based on a Parameterized Canny Edge Detection Algorithm
Venue: arXiv cs.CR 2012
Year: 2012

Steganography is the science of hiding digital information in such a way that no one can suspect its existence. Unlike cryptography which may arouse suspicions, steganography is a stealthy method that enables data communication in total secrecy. Steganography has many requirements, the foremost one is irrecoverability which refers to how hard it is for someone apart from the original communicating parties to detect and recover the hidden data out of the secret communication. A good strategy to guaranteeirrecoverability is to cover the secret data not usinga trivial method based on a predictable algorithm, but using a specific random pattern based on a mathematical algorithm. This paper proposes an image steganography technique based on theCanny edge detection algorithm.It is designed to hide secret data into a digital image within the pixels that make up the boundaries of objects detected in the image. More specifically, bits of the secret data replace the three LSBs of every color channel of the pixels detected by the Canny edge detection algorithm as part of the edges in the carrier image. Besides, the algorithm is parameterized by three parameters: The size of the Gaussian filter, a low threshold value, and a high threshold value. These parameters can yield to different outputs for the same input image and secret data. As a result, discovering the inner-workings of the algorithm would be considerably ambiguous, misguiding steganalysts from the exact location of the covert data. Experiments showed a simulation tool codenamed GhostBit, meant to cover and uncover secret data using the proposed algorithm. As future work, examining how other image processing techniques such as brightness and contrast adjustment can be taken advantage of in steganography with the purpose ofgiving the communicating parties more preferences tomanipulate their secret communication.
A Model of OpenEHR Based Electronic Medical Record In Indonesia
Venue: arXiv cs.CY 2012
Year: 2012

For the realization of the vision and mission of Healthy Indonesia 2015, we need a health service with a broad and comprehensive scope.To provide health services, it can be realized by creating an integrated information system applications such as creating an electronic medical record that has the ability to process and store patient medical data. The specifications used medical record is an open specification contained in OpenEHR that includes information and service model for electronic medical records, demographics, and the archetype which allows software developers taking the logical structure as a universal functional interface, so it can facilitate the process of information by the recipient. It is because of using the interface with appropriate-purposed data presentation and data on computer screen of the same users. The purpose of this paper is to create an electronic website for the medical record by using OpenEHR specifications for easy accessing, processing and storing the medical records by the actors that play a role in the data processing of medical records. With this application it is expected to be useful for data processing and health information gathering, thus to improve the quality of services that will impact the improved performance of the hospital management. The improved performance of the hospital management will become a supporter of the vision and mission Healthy Indonesia 2015.
Localized Algorithm of Community Detection on Large-Scale Decentralized Social Networks
Venue: arXiv cs.SI 2012
Year: 2012

Despite the overwhelming success of the existing Social Networking Services (SNS), their centralized ownership and control have led to serious concerns in user privacy, censorship vulnerability and operational robustness of these services. To overcome these limitations, Distributed Social Networks (DSN) have recently been proposed and implemented. Under these new DSN architectures, no single party possesses the full knowledge of the entire social network. While this approach solves the above problems, the lack of global knowledge for the DSN nodes makes it much more challenging to support some common but critical SNS services like friends discovery and community detection. In this paper, we tackle the problem of community detection for a given user under the constraint of limited local topology information as imposed by common DSN architectures. By considering the Personalized Page Rank (PPR) approach as an ink spilling process, we justify its applicability for decentralized community detection using limited local topology information.Our proposed PPR-based solution has a wide range of applications such as friends recommendation, targeted advertisement, automated social relationship labeling and sybil defense. Using data collected from a large-scale SNS in practice, we demonstrate our adapted version of PPR can significantly outperform the basic PR as well as two other commonly used heuristics. The inclusion of a few manually labeled friends in the Escape Vector (EV) can boost the performance considerably (64.97% relative improvement in terms of Area Under the ROC Curve (AUC)).
Existence of Oscillations in Cyclic Gene Regulatory Networks with Time Delay
Venue: arXiv cs.SY 2012
Year: 2012

This paper is concerned with conditions for the existence of oscillations in gene regulatory networks with negative cyclic feedback, where time delays in transcription, translation and translocation process are explicitly considered. The primary goal of this paper is to propose systematic analysis tools that are useful for a broad class of cyclic gene regulatory networks, and to provide novel biological insights. To this end, we adopt a simplified model that is suitable for capturing the essence of a large class of gene regulatory networks. It is first shown that local instability of the unique equilibrium state results in oscillations based on a Poincare-Bendixson type theorem. Then, a graphical existence condition, which is equivalent to the local instability of a unique equilibrium, is derived. Based on the graphical condition, the existence condition is analytically presented in terms of biochemical parameters. This allows us to find the dimensionless parameters that primarily affect the existence of oscillations, and to provide biological insights. The analytic conditions and biological insights are illustrated with two existing biochemical networks, Repressilator and the Hes7 gene regulatory networks.