OpenRaiser/Intern-Atlas huggingface dataset:
Development of a Dual Sensor Heat Control System
Venue: arXiv cs.SY 2012
Year: 2012

Convenience and safeguarding our home appliances have become an important issue when dealing with an advancement and growth of an economy. This research focuses on the design and construction of a Dual Sensor heat-monitoring system. The circuit works by monitoring temperature from an external input and comparing the temperature level with that of a preset temperature value. The power output of the circuit is cut off or switched OFF or an alarm is triggered ON if the temperature of the external input is equal to or, greater than the preset temperature value. The methodology involves the application of linear precision temperature sensors i.e., they generate a voltage that is directly proportional to the temperature. Basically the system is constructed using temperature sensors and comparators. The system is powered using a 12V power supply. The results of the tests showed that the power output of the circuit is switched OFF hence switching OFF the heating device or an alarm is triggered ON when the device exceeded a preset temperature level. The general operation of the system and performance is dependent on the temperature difference between the preset temperature value and external temperature intended to be monitored. The overall system was tested and found perfectly functional.
Understanding the Interaction between Interests, Conversations and Friendships in Facebook
Venue: arXiv cs.SI 2012
Year: 2012

In this paper, we explore salient questions about user interests, conversations and friendships in the Facebook social network, using a novel latent space model that integrates several data types. A key challenge of studying Facebook's data is the wide range of data modalities such as text, network links, and categorical labels. Our latent space model seamlessly combines all three data modalities over millions of users, allowing us to study the interplay between user friendships, interests, and higher-order network-wide social trends on Facebook. The recovered insights not only answer our initial questions, but also reveal surprising facts about user interests in the context of Facebook's ecosystem. We also confirm that our results are significant with respect to evidential information from the study subjects.
Dimensionality Reduction and Classification Feature Using Mutual Information Applied to Hyperspectral Images: A Wrapper Strategy Algorithm Based on Minimizing the Error Probability Using the Inequality of Fano
Venue: arXiv cs.CV 2012
Year: 2012

In the feature classification domain, the choice of data affects widely the results. For the Hyperspectral image, the bands dont all contain the information; some bands are irrelevant like those affected by various atmospheric effects, see Figure.4, and decrease the classification accuracy. And there exist redundant bands to complicate the learning system and product incorrect prediction [14]. Even the bands contain enough information about the scene they may can't predict the classes correctly if the dimension of space images, see Figure.3, is so large that needs many cases to detect the relationship between the bands and the scene (Hughes phenomenon) [10]. We can reduce the dimensionality of hyperspectral images by selecting only the relevant bands (feature selection or subset selection methodology), or extracting, from the original bands, new bands containing the maximal information about the classes, using any functions, logical or numerical (feature extraction methodology) [11][9]. Here we focus on the feature selection using mutual information. Hyperspectral images have three advantages regarding the multispectral images [6],
Optimal Covering with Mobile Sensors in an Unbounded Region
Venue: arXiv cs.DC 2012
Year: 2012

Covering a bounded region with minimum number of homogeneous sensor nodes is a NP-complete problem \cite{Li09}. In this paper we have proposed an {\it id} based distributed algorithm for optimal coverage in an unbounded region. The proposed algorithm guarantees maximum spreading in $O(\sqrt{n})$ rounds without creating any coverage hole. The algorithm executes in synchronous rounds without exchanging any message. We have also explained how our proposed algorithm can achieve optimal energy consumption and handle random sensor node deployment for optimal spreading.
Views over RDF Datasets: A State-of-the-Art and Open Challenges
Venue: arXiv cs.DB 2012
Year: 2012

Views on RDF datasets have been discussed in several works, nevertheless there is no consensus on their definition nor the requirements they should fulfill. In traditional data management systems, views have proved to be useful in different application scenarios such as data integration, query answering, data security, and query modularization. In this work we have reviewed existent work on views over RDF datasets, and discussed the application of existent view definition mechanisms to four scenarios in which views have proved to be useful in traditional (relational) data management systems. To give a framework for the discussion we provided a definition of views over RDF datasets, an issue over which there is no consensus so far. We finally chose the three proposals closer to this definition, and analyzed them with respect to four selected goals.
Feedback from nature: an optimal distributed algorithm for maximal independent set selection
Venue: arXiv cs.DC 2012
Year: 2012

Maximal Independent Set selection is a fundamental problem in distributed computing. A novel probabilistic algorithm for this problem has recently been proposed by Afek et al, inspired by the study of the way that developing cells in the fly become specialised. The algorithm they propose is simple and robust, but not as efficient as previous approaches: the expected time complexity is O(log^2 n). Here we first show that the approach of Afek et al cannot achieve better efficiency than this across all networks, no matter how the probability values are chosen. However, we then propose a new algorithm that incorporates another important feature of the biological system: adapting the probabilities used at each node based on local feedback from neighbouring nodes. Our new algorithm retains all the advantages of simplicity and robustness, but also achieves the optimal efficiency of O(log n) expected time.
Some New Methodologies for Image Hiding using Steganographic Techniques
Venue: arXiv cs.CR 2012
Year: 2012

Security and memory management are the major demands for electronics devices like ipods, cell phones, pmps, iphones and digital cameras. In this paper, we have suggested a high level of security mechanism by considering the concept of steganography along with the principle of cryptography. Four different methods that can save a considerable amount of memory space have been discussed. Based on these methods, we have constructed secured stego image creator and secured multi image viewer in Microsoft platform so as to provide high level of security and using less memory space for storage of image files in the above said electronic devices
Dynamic Frequency Management in 802.11-based Multi-Radio Wireless Networks
Venue: arXiv cs.NI 2012
Year: 2012

Efficient channel selection is essential in 802.11 mesh deployments, for minimizing contention and interference among co-channel devices and thereby supporting a plurality of QoS-sensitive applications. A few protocols have been proposed for frequency allocation in such networks, however they do not address the problem end-to-end. In this paper, we present a general formulation of the channel selection problem taking into account the performance of both mesh-access and mesh-backhaul. Moreover, we propose ARACHNE, a routing-aware channel selection protocol for wireless mesh networks. ARACHNE is distributed in nature, and motivated by our measurements on a wireless testbed. The main novelty of our protocol comes from adopting a metric that captures the end-to-end link loads across different routes in the network. ARACHNE prioritizes the assignment of low-interference channels to links that (a) need to serve high-load aggregate traffic and/or (b) already suffer significant levels of contention and interference. Our protocol takes into account the number of potential interfaces (radios) per device, and allocates these interfaces in a manner that efficiently utilizes the available channel capacity. We evaluate ARACHNE through extensive, tracedriven simulations and we show that approaches the optimal channel selection. We observe that our protocol improves the total network throughput, as compared to three other representative channel allocation approaches in literature.
Intelligent Algorithm for Optimum Solutions Based on the Principles of Bat Sonar
Venue: arXiv cs.NE 2012
Year: 2012

This paper presents a new intelligent algorithm that can solve the problems of finding the optimum solution in the state space among which the desired solution resides. The algorithm mimics the principles of bat sonar in finding its targets. The algorithm introduces three search approaches. The first search approach considers a single sonar unit (SSU) with a fixed beam length and a single starting point. In this approach, although the results converge toward the optimum fitness, it is not guaranteed to find the global optimum solution especially for complex problems; it is satisfied with finding 'acceptably good' solutions to these problems. The second approach considers multisonar units (MSU) working in parallel in the same state space. Each unit has its own starting point and tries to find the optimum solution. In this approach the probability that the algorithm converges toward the optimum solution is significantly increased. It is found that this approach is suitable for complex functions and for problems of wide state space. In the third approach, a single sonar unit with a moment (SSM) is used in order to handle the problem of convergence toward a local optimum rather than a global optimum. The momentum term is added to the length of the transmitted beams. This will give the chance to find the best fitness in a wider range within the state space. In this paper a comparison between the proposed algorithm and genetic algorithm (GA) has been made. It showed that both of the algorithms can catch approximately the optimum solutions for all of the testbed functions except for the function that has a local minimum, in which the proposed algorithm's result is much better than that of the GA algorithm. On the other hand, the comparison showed that the required execution time to obtain the optimum solution using the proposed algorithm is much less than that of the GA algorithm.
OSNAP: Faster numerical linear algebra algorithms via sparser subspace embeddings
Venue: arXiv cs.DS 2012
Year: 2012

An "oblivious subspace embedding (OSE)" given some parameters eps,d is a distribution D over matrices B in R^{m x n} such that for any linear subspace W in R^n with dim(W) = d it holds that Pr_{B ~ D}(forall x in W ||B x||_2 in (1 +/- eps)||x||_2) > 2/3 We show an OSE exists with m = O(d^2/eps^2) and where every B in the support of D has exactly s=1 non-zero entries per column. This improves previously best known bound in [Clarkson-Woodruff, arXiv:1207.6365]. Our quadratic dependence on d is optimal for any OSE with s=1 [Nelson-Nguyen, 2012]. We also give two OSE's, which we call Oblivious Sparse Norm-Approximating Projections (OSNAPs), that both allow the parameter settings m = Õ(d/eps^2) and s = polylog(d)/eps, or m = O(d^{1+gamma}/eps^2) and s=O(1/eps) for any constant gamma>0. This m is nearly optimal since m >= d is required simply to no non-zero vector of W lands in the kernel of B. These are the first constructions with m=o(d^2) to have s=o(d). In fact, our OSNAPs are nothing more than the sparse Johnson-Lindenstrauss matrices of [Kane-Nelson, SODA 2012]. Our analyses all yield OSE's that are sampled using either O(1)-wise or O(log d)-wise independent hash functions, which provides some efficiency advantages over previous work for turnstile streaming applications. Our main result is essentially a Bai-Yin type theorem in random matrix theory and is likely to be of independent interest: i.e. we show that for any U in R^{n x d} with orthonormal columns and random sparse B, all singular values of BU lie in [1-eps, 1+eps] with good probability. Plugging OSNAPs into known algorithms for numerical linear algebra problems such as approximate least squares regression, low rank approximation, and approximating leverage scores implies faster algorithms for all these problems.
Asymmetries of Men and Women in Selecting Partner
Venue: arXiv cs.CY 2012
Year: 2012

This paper investigates human dynamics in a large online dating site with 3,000 new users daily who stay in the system for 3 months on the average. The daily activity is also quite large such as 500,000 massage transactions, 5,000 photo uploads, and 20,000 votes. The data investigated has 276, 210 male and 483, 963 female users. Based on the activity that they made, there are clear distinctions between men and women in their pattern of behavior. Men prefer lower, women prefer higher qualifications in their partner.
On the Number of Unbordered Factors
Venue: arXiv cs.FL 2012
Year: 2012

We illustrate a general technique for enumerating factors of k-automatic sequences by proving a conjecture on the number f(n) of unbordered factors of the Thue-Morse sequence. We show that f(n) <= n for n >= 4 and that f(n) = n infinitely often. We also give examples of automatic sequences having exactly 2 unbordered factors of every length.
Use of PSO in Parameter Estimation of Robot Dynamics; Part Two: Robustness
Venue: arXiv cs.RO 2012
Year: 2012

In this paper, we analyze the robustness of the PSO-based approach to parameter estimation of robot dynamics presented in Part One. We have made attempts to make the PSO method more robust by experimenting with potential cost functions. The simulated system is a cylindrical robot; through simulation, the robot is excited, samples are taken, error is added to the samples, and the noisy samples are used for estimating the robot parameters through the presented method. Comparisons are made with the least squares, total least squares, and robust least squares methods of estimation.
Lyapunov Method Based Online Identification of Nonlinear Systems Using Extreme Learning Machines
Venue: arXiv cs.SY 2012
Year: 2012

Extreme Learning Machine (ELM) is an emerging learning paradigm for nonlinear regression problems and has shown its effectiveness in the machine learning community. An important feature of ELM is that the learning speed is extremely fast thanks to its random projection preprocessing step. This feature is taken advantage of in designing an online parameter estimation algorithm for nonlinear dynamic systems in this paper. The ELM type random projection and a nonlinear transformation in the hidden layer and a linear output layer is considered as a generalized model structure for a given nonlinear system and a parameter update law is constructed based on Lyapunov principles. Simulation results on a DC motor and Lorentz oscillator show that the proposed algorithm is stable and has improved performance over the online-learning ELM algorithm.
Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and with bounds
Venue: arXiv cs.CV 2012
Year: 2012

Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with cleverly engineered algorithms. In this work we attempt to learn this mapping directly with plain multi layer perceptrons (MLP) applied to image patches. We will show that by training on large image databases we are able to outperform the current state-of-the-art image denoising methods. In addition, our method achieves results that are superior to one type of theoretical bound and goes a large way toward closing the gap with a second type of theoretical bound. Our approach is easily adapted to less extensively studied types of noise, such as mixed Poisson-Gaussian noise, JPEG artifacts, salt-and-pepper noise and noise resembling stripes, for which we achieve excellent results as well. We will show that combining a block-matching procedure with MLPs can further improve the results on certain images. In a second paper, we detail the training trade-offs and the inner mechanisms of our MLPs.
Embedding grayscale halftone pictures in QR Codes using Correction Trees
Venue: arXiv cs.IT 2012
Year: 2012

Barcodes like QR Codes have made that encoded messages have entered our everyday life, what suggests to attach them a second layer of information: directly available to human receiver for informational or marketing purposes. We will discuss a general problem of using codes with chosen statistical constrains, for example reproducing given grayscale picture using halftone technique. If both sender and receiver know these constrains, the optimal capacity can be easily approached by entropy coder. The problem is that this time only the sender knows them - we will refer to these scenarios as constrained coding. Kuznetsov and Tsybakov problem in which only the sender knows which bits are fixed can be seen as a special case, surprisingly approaching the same capacity as if both sides would know the constrains. We will analyze Correction Trees to approach analogous capacity in the general case - use weaker: statistical constrains, what allows to apply them to all bits. Finding satisfying coding is similar to finding the proper correction in error correction problem, but instead of single ensured possibility, there are now statistically expected some. While in standard steganography we hide information in the least important bits, this time we create codes resembling given picture - hide information in the freedom of realizing grayness by black and white pixels using halftone technique. We will also discuss combining with error correction and application to rate distortion problem.
Different Operating Systems Compatible for Image Prepress Process in Color Management: Analysis and Performance Testing
Venue: arXiv cs.CV 2012
Year: 2012

Image computing has become a real catchphrase over the past few years and the interpretations of the meaning of the term vary greatly. The Imagecomputing market is currently rapidly evolving with high growth prospects and almost daily announcements of new devices and application platforms, which results in an increasing diversification of devices, operating system and development platforms. Compared to more traditional information technology markets like the one of desktop computing, mobile computing is much less consolidated and neither standards nor even industry standards have yet been established. There are various platforms and interfaces which may be used to perform the desired tasks through the device. We have tried to compare the various mobile operating systems and their trade-offs.
Secret-Key Agreement Capacity over Reciprocal Fading Channels: A Separation Approach
Venue: arXiv cs.IT 2012
Year: 2012

Fundamental limits of secret-key agreement over reciprocal wireless channels are investigated. We consider a two-way block-fading channel where the channel gains in the forward and reverse links between the legitimate terminals are correlated. The channel gains between the legitimate terminals are not revealed to any terminal, whereas the channel gains of the eavesdropper are revealed to the eavesdropper. We propose a two-phase transmission scheme, that reserves a certain portion of each coherence block for channel estimation, and the remainder of the coherence block for correlated source generation. The resulting secret-key involves contributions of both channel sequences and source sequences, with the contribution of the latter becoming dominant as the coherence period increases. We also establish an upper bound on the secret-key capacity, which has a form structurally similar to the lower bound. Our upper and lower bounds coincide in the limit of high signal-to-noise-ratio (SNR) and large coherence period, thus establishing the secret-key agreement capacity in this asymptotic regime. Numerical results indicate that the proposed scheme achieves significant gains over training-only schemes, even for moderate SNR and small coherence periods, thus implying the necessity of randomness-sharing in practical secret-key generation systems.
Inverse problems in approximate uniform generation
Venue: arXiv cs.CC 2012
Year: 2012

We initiate the study of \emph{inverse} problems in approximate uniform generation, focusing on uniform generation of satisfying assignments of various types of Boolean functions. In such an inverse problem, the algorithm is given uniform random satisfying assignments of an unknown function $f$ belonging to a class $\C$ of Boolean functions, and the goal is to output a probability distribution $D$ which is $ε$-close, in total variation distance, to the uniform distribution over $f^{-1}(1)$. Positive results: We prove a general positive result establishing sufficient conditions for efficient inverse approximate uniform generation for a class $\C$. We define a new type of algorithm called a \emph{densifier} for $\C$, and show (roughly speaking) how to combine (i) a densifier, (ii) an approximate counting / uniform generation algorithm, and (iii) a Statistical Query learning algorithm, to obtain an inverse approximate uniform generation algorithm. We apply this general result to obtain a poly$(n,1/\eps)$-time algorithm for the class of halfspaces; and a quasipoly$(n,1/\eps)$-time algorithm for the class of $\poly(n)$-size DNF formulas. Negative results: We prove a general negative result establishing that the existence of certain types of signature schemes in cryptography implies the hardness of certain inverse approximate uniform generation problems. This implies that there are no {subexponential}-time inverse approximate uniform generation algorithms for 3-CNF formulas; for intersections of two halfspaces; for degree-2 polynomial threshold functions; and for monotone 2-CNF formulas. Finally, we show that there is no general relationship between the complexity of the "forward" approximate uniform generation problem and the complexity of the inverse problem for a class $\C$ -- it is possible for either one to be easy while the other is hard.
Annotations, Collaborative Tagging, and Searching Mathematics in E-Learning
Venue: arXiv cs.IR 2012
Year: 2012

This paper presents a new framework for adding semantics into e-learning system. The proposed approach relies on two principles. The first principle is the automatic addition of semantic information when creating the mathematical contents. The second principle is the collaborative tagging and annotation of the e-learning contents and the use of an ontology to categorize the e-learning contents. The proposed system encodes the mathematical contents using presentation MathML with RDFa annotations. The system allows students to highlight and annotate specific parts of the e-learning contents. The objective is to add meaning into the e-learning contents, to add relationships between contents, and to create a framework to facilitate searching the contents. This semantic information can be used to answer semantic queries (e.g., SPARQL) to retrieve information request of a user. This work is implemented as an embedded code into Moodle e-learning system.
Algorithm for Missing Values Imputation in Categorical Data with Use of Association Rules
Venue: arXiv cs.LG 2012
Year: 2012

This paper presents algorithm for missing values imputation in categorical data. The algorithm is based on using association rules and is presented in three variants. Experimental shows better accuracy of missing values imputation using the algorithm then using most common attribute value.