OpenRaiser/Intern-Atlas huggingface dataset:
Visualization in Connectomics
Venue: arXiv cs.GR 2012
Year: 2012

Connectomics is a field of neuroscience that analyzes neuronal connections. A connectome is a complete map of a neuronal system, comprising all neuronal connections between its structures. The term "connectome" is close to the word "genome" and implies completeness of all neuronal connections, in the same way as a genome is a complete listing of all nucleotide sequences. The goal of connectomics is to create a complete representation of the brain's wiring. Such a representation is believed to increase our understanding of how functional brain states emerge from their underlying anatomical structure. Furthermore, it can provide important information for the cure of neuronal dysfunctions like schizophrenia or autism. In this paper, we review the current state-of-the-art of visualization and image processing techniques in the field of connectomics and describe some remaining challenges.
A comparative study of performance of fpga based mel filter bank & bark filter bank
Venue: arXiv cs.SD 2012
Year: 2012

The sensitivity of human ear is dependent on frequency which is nonlinearly resolved across the audio spectrum .Now to improve the recognition performance in a similar non linear approach requires a front -end design, suggested by empirical evidences. A popular alternative to linear prediction based analysis is therefore filter bank analysis since this provides a much more straightforward route to obtain the desired non-linear frequency resolution. MEL filter bank and BARK filter bank are two popular filter bank analysis techniques. This paper presents FPGA based implementation of MEL filter bank and BARK filter bank with different bandwidths and different signal spectrum ranges. The designs have been implemented using VHDL, simulated and verified using Xilinx 11.1.For each filter bank, the basic building block is implemented in Spartan 3E. A comparative study among these two mentioned filter banks is also done in this paper.
Soil Data Analysis Using Classification Techniques and Soil Attribute Prediction
Venue: arXiv cs.AI 2012
Year: 2012

Agricultural research has been profited by technical advances such as automation, data mining. Today, data mining is used in a vast areas and many off-the-shelf data mining system products and domain specific data mining application soft wares are available, but data mining in agricultural soil datasets is a relatively a young research field. The large amounts of data that are nowadays virtually harvested along with the crops have to be analyzed and should be used to their full extent. This research aims at analysis of soil dataset using data mining techniques. It focuses on classification of soil using various algorithms available. Another important purpose is to predict untested attributes using regression technique, and implementation of automated soil sample classification.
Architecture for real time continuous sorting on large width data volume for fpga based applications
Venue: arXiv cs.AR 2012
Year: 2012

In engineering applications sorting is an important and widely studied problem where execution speed and resources used for computation are of extreme importance, especially if we think about real time data processing. Most of the traditional sorting techniques compute the process after receiving all of the data and hence the process needs large amount of resources for data storage. So, suitable design strategy needs to be adopted if we wish to sort a large amount of data in real time, which essential means higher speed of process execution and utilization of fewer resources in most of the cases. This paper proposes a single chip scalable architecture based on Field Programmable Gate Array(FPGA), for a modified counting sort algorithm where data acquisition and sorting is being done in real time scenario. Our design promises to work efficiently, where data can be accepted in the run time scenario without any need of prior storage of data and also the execution speed of our algorithm is invariant to the length of the data stream. The proposed design is implemented and verified on Spartan 3E(XC3S500E-FG320) FPGA system. The results prove that our design is better in terms of some of the design parameters compared to the existing research works.
Dynamic MPLS with Feedback
Venue: arXiv cs.NI 2012
Year: 2012

Multiprotocol Label Switching (MPLS) fasten the speed of packet forwarding by forwarding the packets based on labels and reduces the use of routing table look up from all routers to label edge routers(LER), where as the label switch routers (LSRs) uses Label Distribution Protocol (LDP) or RSVP (Resource reservation Protocol) for label allocation and Label table for packet forwarding. Dynamic protocol is implemented which carries a Updates packets for the details of Label Switch Paths, along with this feedback mechanism is also introduced which find the shortest path among MPLS network and also feedback is provided which also help to overcome congestion, this feedback mechanism is on a hop by hop basis rather than end to end thus providing a more reliable and much faster and congestion free path for the packets.
A Distributed Optimized Patient Scheduling using Partial Information
Venue: arXiv cs.AI 2012
Year: 2012

A software agent may be a member of a Multi-Agent System (MAS) which is collectively performing a range of complex and intelligent tasks. In the hospital, scheduling decisions are finding difficult to schedule because of the dynamic changes and distribution. In order to face this problem with dynamic changes in the hospital, a new method, Distributed Optimized Patient Scheduling with Grouping (DOPSG) has been proposed. The goal of this method is that there is no necessity for knowing patient agents information globally. With minimal information this method works effectively. Scheduling problem can be solved for multiple departments in the hospital. Patient agents have been scheduled to the resource agent based on the patient priority to reduce the waiting time of patient agent and to reduce idle time of resources.
C-Band VSAT Data Communication System and RF Impairments
Venue: arXiv cs.OH 2012
Year: 2012

This paper is concerned with modelling and simulation of VSAT (very small aperture terminal) data messaging network operating in India at Karnataka with extended C-band. VSATs in Karnataka of KPTCL use VSATS 6.875-6.9465G Hz uplinks and 4.650- 4.7215 GHz downlinks. These frequencies are dedicated to fixed services. The Satellite is Intelsat -3A, the hub has a 7.2 m diameter antenna and uses 350W or 600W TWTA (Travelling wave Tube Amplifier). The VSAT's are 1.2 m with RF power of 1W or 2W depending on their position in the uplink beam with data rate of 64 or 128 K bit/s. The performance of the system is analysed by the error probability called BER (Bit Error Rate) and results are derived from Earth station to hub and hub to Earth station using satellite Transponder as the media of communication channel. The Link budgets are developed for a single one-way satellite link.
Patience of Matrix Games
Venue: arXiv cs.DM 2012
Year: 2012

For matrix games we study how small nonzero probability must be used in optimal strategies. We show that for nxn win-lose-draw games (i.e. (-1,0,1) matrix games) nonzero probabilities smaller than n^{-O(n)} are never needed. We also construct an explicit nxn win-lose game such that the unique optimal strategy uses a nonzero probability as small as n^{-Omega(n)}. This is done by constructing an explicit (-1,1) nonsingular nxn matrix, for which the inverse has only nonnegative entries and where some of the entries are of value n^{Omega(n)}.
Exponential Time Complexity of the Permanent and the Tutte Polynomial
Venue: arXiv cs.CC 2012
Year: 2012

We show conditional lower bounds for well-studied #P-hard problems: (a) The number of satisfying assignments of a 2-CNF formula with n variables cannot be counted in time exp(o(n)), and the same is true for computing the number of all independent sets in an n-vertex graph. (b) The permanent of an n x n matrix with entries 0 and 1 cannot be computed in time exp(o(n)). (c) The Tutte polynomial of an n-vertex multigraph cannot be computed in time exp(o(n)) at most evaluation points (x,y) in the case of multigraphs, and it cannot be computed in time exp(o(n/polylog n)) in the case of simple graphs. Our lower bounds are relative to (variants of) the Exponential Time Hypothesis (ETH), which says that the satisfiability of n-variable 3-CNF formulas cannot be decided in time exp(o(n)). We relax this hypothesis by introducing its counting version #ETH, namely that the satisfying assignments cannot be counted in time exp(o(n)). In order to use #ETH for our lower bounds, we transfer the sparsification lemma for d-CNF formulas to the counting setting.
Optimization of Fuzzy Semantic Networks Based on Galois Lattice and Bayesian Formalism
Venue: arXiv cs.IR 2012
Year: 2012

This paper presents a method of optimization, based on both Bayesian Analysis technical and Galois Lattice of Fuzzy Semantic Network. The technical System we use learns by interpreting an unknown word using the links created between this new word and known words. The main link is provided by the context of the query. When novice's query is confused with an unknown verb (goal) applied to a known noun denoting either an object in the ideal user's Network or an object in the user's Network, the system infer that this new verb corresponds to one of the known goal. With the learning of new words in natural language as the interpretation, which was produced in agreement with the user, the system improves its representation scheme at each experiment with a new user and, in addition, takes advantage of previous discussions with users. The semantic Net of user objects thus obtained by learning is not always optimal because some relationships between couple of user objects can be generalized and others suppressed according to values of forces that characterize them. Indeed, to simplify the obtained Net, we propose to proceed to an Inductive Bayesian Analysis, on the Net obtained from Galois lattice. The objective of this analysis can be seen as an operation of filtering of the obtained descriptive graph.
On the Complexity of Minimum Labeling Alignment of Two Genomes
Venue: arXiv cs.CC 2012
Year: 2012

In this note we investigate the complexity of the Minimum Label Alignment problem and we show that such a problem is APX-hard.
Timely Coordination in a Multi-Agent System
Venue: arXiv cs.MA 2012
Year: 2012

In a distributed algorithm, multiple processes, or agents, work toward a common goal. More often than not, the actions of some agents are dependent on the previous execution (if not also on the outcome) of the actions of other agents. The resulting interdependencies between the timings of the actions of the various agents give rise to the study of methods for timely coordination of these actions. In this work, we formulate and mathematically analyze "Timely-Coordinated Response" - a novel multi-agent coordination problem in which the time difference between each pair of actions may be constrained by upper and/or lower bounds. This problem generalizes coordination problems previously studied by Halpern and Moses and by Ben-Zvi and Moses. We optimally solve timely-coordinated response in two ways: using a generalization of the fixed-point approach of Halpern and Moses, and using a generalization of the "syncausality" approach of Ben-Zvi and Moses. We constructively show the equivalence of the solutions yielded by both approaches, and by combining them, derive strengthened versions of known results for some previously-defined special cases of this problem. Our analysis is conducted under minimal assumptions: we work in a continuous-time model with possibly infinitely many agents. The general results we obtain for this model reduce to stronger ones for discrete-time models with only finitely many agents. In order to distill the properties of such models that are significant to this reduction, we define several classes of naturally-occurring models, which in a sense separate the different results. We present both a more practical optimal solution, as well as a surprisingly simple condition for solvability, for timely coordinated response under these models. Finally, we show how our results generalize the results known for previously-studied special cases of this problem.
Finishing Flows Quickly with Preemptive Scheduling
Venue: arXiv cs.NI 2012
Year: 2012

Today's data centers face extreme challenges in providing low latency. However, fair sharing, a principle commonly adopted in current congestion control protocols, is far from optimal for satisfying latency requirements. We propose Preemptive Distributed Quick (PDQ) flow scheduling, a protocol designed to complete flows quickly and meet flow deadlines. PDQ enables flow preemption to approximate a range of scheduling disciplines. For example, PDQ can emulate a shortest job first algorithm to give priority to the short flows by pausing the contending flows. PDQ borrows ideas from centralized scheduling disciplines and implements them in a fully distributed manner, making it scalable to today's data centers. Further, we develop a multipath version of PDQ to exploit path diversity. Through extensive packet-level and flow-level simulation, we demonstrate that PDQ significantly outperforms TCP, RCP and D3 in data center environments. We further show that PDQ is stable, resilient to packet loss, and preserves nearly all its performance gains even given inaccurate flow information.
Extending Term Suggestion with Author Names
Venue: arXiv cs.IR 2012
Year: 2012

Term suggestion or recommendation modules can help users to formulate their queries by mapping their personal vocabularies onto the specialized vocabulary of a digital library. While we examined actual user queries of the social sciences digital library Sowiport we could see that nearly one third of the users were explicitly looking for author names rather than terms. Common term recommenders neglect this fact. By picking up the idea of polyrepresentation we could show that in a standardized IR evaluation setting we can significantly increase the retrieval performances by adding topical-related author names to the query. This positive effect only appears when the query is additionally expanded with thesaurus terms. By just adding the author names to a query we often observe a query drift which results in worse results.
To Compress or Not To Compress: Processing vs Transmission Tradeoffs for Energy Constrained Sensor Networking
Venue: arXiv cs.NI 2012
Year: 2012

In the past few years, lossy compression has been widely applied in the field of wireless sensor networks (WSN), where energy efficiency is a crucial concern due to the constrained nature of the transmission devices. Often, the common thinking among researchers and implementers is that compression is always a good choice, because the major source of energy consumption in a sensor node comes from the transmission of the data. Lossy compression is deemed a viable solution as the imperfect reconstruction of the signal is often acceptable in WSN. In this paper, we thoroughly review a number of lossy compression methods from the literature, and analyze their performance in terms of compression efficiency, computational complexity and energy consumption. We consider two different scenarios, namely, wireless and underwater communications, and show that signal compression may or may not help in the reduction of the overall energy consumption, depending on factors such as the compression algorithm, the signal statistics and the hardware characteristics, i.e., micro-controller and transmission technology. The lesson that we have learned, is that signal compression may in fact provide some energy savings. However, its usage should be carefully evaluated, as in quite a few cases processing and transmission costs are of the same order of magnitude, whereas, in some other cases, the former may even dominate the latter. In this paper, we show quantitative comparisons to assess these tradeoffs in the above mentioned scenarios. Finally, we provide formulas, obtained through numerical fittings, to gauge computational complexity, overall energy consumption and signal representation accuracy for the best performing algorithms as a function of the most relevant system parameters.
A PAXOS based State Machine Replication System for Anomaly Detection
Venue: arXiv cs.CR 2012
Year: 2012

A number of systems in recent times suffer from attacks like DDoS and Ping of Death. Such attacks result in loss of critical system resources and CPU cycles, as these compromised systems behave in an abnormal manner. The effect of such abnormalities is worse in case of compromised systems handling financial transaction, since it leads to severe monetary losses. In this paper we propose a system that uses the Replicated State Machine approach to detect abnormality in system usage. The suggested system is based on PAXOS algorithm, an algorithm for solving the consensus problem in a network of unreliable processors.
Applying Compression to a Game's Network Protocol
Venue: arXiv cs.IT 2012
Year: 2012

This report presents the results of applying different compression algorithms to the network protocol of an online game. The algorithm implementations compared are zlib, liblzma and my own implementation based on LZ77 and a variation of adaptive Huffman coding. The comparison data was collected from the game TomeNET. The results show that adaptive coding is especially useful for compressing large amounts of very small packets.
A Proof Checking View of Parameterized Complexity
Venue: arXiv cs.CC 2012
Year: 2012

The PCP Theorem is one of the most stunning results in computational complexity theory, a culmination of a series of results regarding proof checking it exposes some deep structure of computational problems. As a surprising side-effect, it also gives strong non-approximability results. In this paper we initiate the study of proof checking within the scope of Parameterized Complexity. In particular we adapt and extend the PCP[n log log n, n log log n] result of Feige et al. to several parameterized classes, and discuss some corollaries.
Combining configuration and recommendation to define an interactive product line configuration approach
Venue: arXiv cs.OH 2012
Year: 2012

This paper is interested in e-commerce for complex configurable products/systems. In e-commerce, satisfying the customer needs is a vital concern. One particular way to achieve this is to offer customers a panel of options among which they can select their preferred ones. While solution exists, they are not adapted for highly complex configurable systems such as product lines. This paper proposes an approach that combines two complementary forms of guidance: configuration and recommendation, to help customers define their own products out of a product line specification. The proposed approach, called interactive configuration supports the combination by organizing the configuration process in a series of partial configurations where decisions are made by the recommendation.
Stego-Image Generator (SIG) - Building Steganography Image Database
Venue: arXiv cs.CR 2012
Year: 2012

Any Universal Steganalysis algorithm developed should be tested with various stego-images to prove its efficiency. This work is aimed to build the stego-image database which is obtained by implementing various RGB Least Significant Bit Steganographic algorithms. Though there are many stego-images sources available on the internet it lacks in the information such as how many rows has been infected by the steganography algorithms, how many bits have been modified and which channel has been affected. These parameters are important for Steganalysis algorithms and it helps to rate its efficiency. Images are chosen from board categories such as animals, nature, person to produce variety of Stego-Image.
Exploiting Particle Swarm Optimization in Multiple Faults Fuzzy Detection
Venue: arXiv cs.NE 2012
Year: 2012

In this paper an on-line multiple faults detection approach is first of all proposed. For efficiency, an optimal design of membership functions is required. Thus, the proposed approach is improved using Particle Swarm Optimization (PSO) technique. The inputs of the proposed approaches are residuals representing the numerical evaluation of Analytical Redundancy Relations. These residuals are generated due to the use of bond graph modeling. The results of the fuzzy detection modules are displayed as a colored causal graph. A comparison between the results obtained by using PSO and those given by the use of Genetic Algorithms (GA) is finally made. The experiments focus on a simulation of the three-tank hydraulic system, a benchmark in the diagnosis domain.
Online open neuroimaging mass meta-analysis
Venue: arXiv cs.DL 2012
Year: 2012

We describe a system for meta-analysis where a wiki stores numerical data in a simple format and a web service performs the numerical computation. We initially apply the system on multiple meta-analyses of structural neuroimaging data results. The described system allows for mass meta-analysis, e.g., meta-analysis across multiple brain regions and multiple mental disorders.
An efficient hierarchical graph based image segmentation
Venue: arXiv cs.CV 2012
Year: 2012

Hierarchical image segmentation provides region-oriented scalespace, i.e., a set of image segmentations at different detail levels in which the segmentations at finer levels are nested with respect to those at coarser levels. Most image segmentation algorithms, such as region merging algorithms, rely on a criterion for merging that does not lead to a hierarchy, and for which the tuning of the parameters can be difficult. In this work, we propose a hierarchical graph based image segmentation relying on a criterion popularized by Felzenzwalb and Huttenlocher. We illustrate with both real and synthetic images, showing efficiency, ease of use, and robustness of our method.
A priori error estimates for compatible spectral discretization of the Stokes problem for all admissible boundary conditions
Venue: arXiv cs.NA 2012
Year: 2012

This paper describes the recently developed mixed mimetic spectral element method for the Stokes problem in the vorticity-velocity-pressure formulation. This compatible discretization method relies on the construction of a conforming discrete Hodge decomposition, that is based on a bounded projection operator that commutes with the exterior derivative. The projection operator is the composition of a reduction and a reconstruction step. The reconstruction in terms of mimetic spectral element basis-functions are tensor-based constructions and therefore hold for curvilinear quadrilateral and hexahedral meshes. For compatible discretization methods that contain a conforming discrete Hodge decomposition, we derive optimal a priori error estimates which are valid for all admissible boundary conditions on both Cartesian and curvilinear meshes. These theoretical results are confirmed by numerical experiments. These clearly show that the mimetic spectral elements outperform the commonly used H(div)-compatible Raviart-Thomas elements.
Computational Asymmetry in Strategic Bayesian Networks
Venue: arXiv cs.GT 2012
Year: 2012

Among the strategic choices made by today's economic actors are choices about algorithms and computational resources. Different access to computational resources may result in a kind of economic asymmetry analogous to information asymmetry. In order to represent strategic computational choices within a game theoretic framework, we propose a new game specification, Strategic Bayesian Networks (SBN). In an SBN, random variables are represented as nodes in a graph, with edges indicating probabilistic dependence. For some nodes, players can choose conditional probability distributions as a strategic choice. Using SBN, we present two games that demonstrate computational asymmetry. These games are symmetric except for the computational limitations of the actors. We show that the better computationally endowed player receives greater payoff.