OpenRaiser/Intern-Atlas huggingface dataset:
Design, Implementation and Evaluation of MTBDD based Fuzzy Sets and Binary Fuzzy Relations
Venue: arXiv cs.DS 2014
Year: 2014

For fast and efficient analysis of large sets of fuzzy data, elimination of redundancies in the memory representation is needed. We used MTBDDs as the underlying data-structure to represent fuzzy sets and binary fuzzy relations. This leads to elimination of redundancies in the representation, less computations, and faster analyses. We have also extended a BDD package (BuDDy) to support MTBDDs in general and fuzzy sets and relations in particular. Different fuzzy operations such as max, min and max-min composition were implemented based on our representation. Effectiveness of our representation is shown by applying it on fuzzy connectedness and image segmentation problem. Compared to a base implementation, the running time of our MTBDD based implementation was faster (in our test cases) by a factor ranging from 2 to 27. Also, when the MTBDD based data-structure was employed, the memory needed to represent the final results was improved by a factor ranging from 37.9 to 265.5.
CloudPowerCap: Integrating Power Budget and Resource Management across a Virtualized Server Cluster
Venue: arXiv cs.DC 2014
Year: 2014

In many datacenters, server racks are highly underutilized. Rack slots are left empty to keep the sum of the server nameplate maximum power below the power provisioned to the rack. And the servers that are placed in the rack cannot make full use of available rack power. The root cause of this rack underutilization is that the server nameplate power is often much higher than can be reached in practice. To address rack underutilization, server vendors are shipping support for per-host power caps, which provide a server-enforced limit on the amount of power that the server can draw. Using this feature, datacenter operators can set power caps on the hosts in the rack to ensure that the sum of those caps does not exceed the rack's provisioned power. While this approach improves rack utilization, it burdens the operator with managing the rack power budget across the hosts and does not lend itself to flexible allocation of power to handle workload usage spikes or to respond to changes in the amount of powered-on server capacity in the rack. In this paper we present CloudPowerCap, a practical and scalable solution for power budget management in a virtualized environment. CloudPowerCap manages the power budget for a cluster of virtualized servers, dynamically adjusting the per-host power caps for hosts in the cluster. We show how CloudPowerCap can provide better use of power than per-host static settings, while respecting virtual machine resource entitlements and constraints.
Accelerating motif finding in DNA sequences with multicore CPUs
Venue: arXiv cs.CE 2014
Year: 2014

Motif discovery in DNA sequences is a challenging task in molecular biology. In computational motif discovery, Planted (l, d) motif finding is a widely studied problem and numerous algorithms are available to solve it. Both hardware and software accelerators have been introduced to accelerate the motif finding algorithms. However, the use of hardware accelerators such as FPGAs needs hardware specialists to design such systems. Software based acceleration methods on the other hand are easier to implement than hardware acceleration techniques. Grid computing is one such software based acceleration technique which has been used in acceleration of motif finding. However, drawbacks such as network communication delays and the need of fast interconnection between nodes in the grid can limit its usage and scalability. As using multicore CPUs to accelerate CPU intensive tasks are becoming increasingly popular and common nowadays, we can employ it to accelerate motif finding and it can be a faster method than grid based acceleration. In this paper, we have explored the use of multicore CPUs to accelerate motif finding. We have accelerated the Skip-Brute Force algorithm on multicore CPUs parallelizing it using the POSIX thread library. Our method yielded an average speed up of 34x on a 32-core processor compared to a speed up of 21x on a grid based implementation of 32 nodes.
Illumination,Expression and Occlusion Invariant Pose-Adaptive Face Recognition System for Real-Time Applications
Venue: arXiv cs.CV 2014
Year: 2014

Face recognition in real-time scenarios is mainly affected by illumination, expression and pose variations and also by occlusion. This paper presents the framework for pose adaptive component-based face recognition system. The framework proposed deals with all the above mentioned issues. The steps involved in the presented framework are (i) facial landmark localisation, (ii) facial component extraction, (iii) pre-processing of facial image (iv) facial pose estimation (v) feature extraction using Local Binary Pattern Histograms of each component followed by (vi) fusion of pose adaptive classification of components. By employing pose adaptive classification, the recognition process is carried out on some part of database, based on estimated pose, instead of applying the recognition process on the whole database. Pre-processing techniques employed to overcome the problems due to illumination variation are also discussed in this paper. Component-based techniques provide better recognition rates when face images are occluded compared to the holistic methods. Our method is simple, feasible and provides better results when compared to other holistic methods.
Sparse Principal Component Analysis via Rotation and Truncation
Venue: arXiv cs.LG 2014
Year: 2014

Sparse principal component analysis (sparse PCA) aims at finding a sparse basis to improve the interpretability over the dense basis of PCA, meanwhile the sparse basis should cover the data subspace as much as possible. In contrast to most of existing work which deal with the problem by adding some sparsity penalties on various objectives of PCA, in this paper, we propose a new method SPCArt, whose motivation is to find a rotation matrix and a sparse basis such that the sparse basis approximates the basis of PCA after the rotation. The algorithm of SPCArt consists of three alternating steps: rotate PCA basis, truncate small entries, and update the rotation matrix. Its performance bounds are also given. SPCArt is efficient, with each iteration scaling linearly with the data dimension. It is easy to choose parameters in SPCArt, due to its explicit physical explanations. Besides, we give a unified view to several existing sparse PCA methods and discuss the connection with SPCArt. Some ideas in SPCArt are extended to GPower, a popular sparse PCA algorithm, to overcome its drawback. Experimental results demonstrate that SPCArt achieves the state-of-the-art performance. It also achieves a good tradeoff among various criteria, including sparsity, explained variance, orthogonality, balance of sparsity among loadings, and computational speed.
Corrections to the results derived in "A Unified Approach to Algorithms Generating Unrestricted and Restricted Integer Compositions and Integer Partitions"'; and a comparison of four restricted integer composition generation algorithms
Venue: arXiv cs.DS 2014
Year: 2014

In this note, I discuss results on integer compositions/partitions given in the paper "A Unified Approach to Algorithms Generating Unrestricted and Restricted Integer Compositions and Integer Partitions". I also experiment with four different generation algorithms for restricted integer compositions and find the algorithm designed in the named paper to be pretty slow, comparatively. Some of my comments may be subjective.
Ant Colony based Feature Selection Heuristics for Retinal Vessel Segmentation
Venue: arXiv cs.NE 2014
Year: 2014

Features selection is an essential step for successful data classification, since it reduces the data dimensionality by removing redundant features. Consequently, that minimizes the classification complexity and time in addition to maximizing its accuracy. In this article, a comparative study considering six features selection heuristics is conducted in order to select the best relevant features subset. The tested features vector consists of fourteen features that are computed for each pixel in the field of view of retinal images in the DRIVE database. The comparison is assessed in terms of sensitivity, specificity, and accuracy measurements of the recommended features subset resulted by each heuristic when applied with the ant colony system. Experimental results indicated that the features subset recommended by the relief heuristic outperformed the subsets recommended by the other experienced heuristics.
Finding Eyewitness Tweets During Crises
Venue: arXiv cs.CL 2014
Year: 2014

Disaster response agencies have started to incorporate social media as a source of fast-breaking information to understand the needs of people affected by the many crises that occur around the world. These agencies look for tweets from within the region affected by the crisis to get the latest updates of the status of the affected region. However only 1% of all tweets are geotagged with explicit location information. First responders lose valuable information because they cannot assess the origin of many of the tweets they collect. In this work we seek to identify non-geotagged tweets that originate from within the crisis region. Towards this, we address three questions: (1) is there a difference between the language of tweets originating within a crisis region and tweets originating outside the region, (2) what are the linguistic patterns that can be used to differentiate within-region and outside-region tweets, and (3) for non-geotagged tweets, can we automatically identify those originating within the crisis region in real-time?
Hierarchical Recovery in Compressive Sensing
Venue: arXiv cs.IT 2014
Year: 2014

A combinatorial approach to compressive sensing based on a deterministic column replacement technique is proposed. Informally, it takes as input a pattern matrix and ingredient measurement matrices, and results in a larger measurement matrix by replacing elements of the pattern matrix with columns from the ingredient matrices. This hierarchical technique yields great flexibility in sparse signal recovery. Specifically, recovery for the resulting measurement matrix does not depend on any fixed algorithm but rather on the recovery scheme of each ingredient matrix. In this paper, we investigate certain trade-offs for signal recovery, considering the computational investment required. Coping with noise in signal recovery requires additional conditions, both on the pattern matrix and on the ingredient measurement matrices.
Credible Autocoding of Convex Optimization Algorithms
Venue: arXiv cs.SY 2014
Year: 2014

The efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. There is a considerable body of mathematical proofs on on-line optimization programs which can be leveraged to assist in the development and verification of their implementation. In this paper, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the level of the code, thereby making it accessible for the formal methods community. The running example used in this paper is a generic semi-definite programming (SDP) solver. Semi-definite programs can encode a wide variety of optimization problems and can be solved in polynomial time at a given accuracy. We describe a top-to-down approach that transforms a high-level analysis of the algorithm into useful code annotations. We formulate some general remarks about how such a task can be incorporated into a convex programming autocoder. We then take a first step towards the automatic verification of the optimization program by identifying key issues to be adressed in future work.
Vehicle as a Resource (VaaR)
Venue: arXiv cs.NI 2014
Year: 2014

Intelligent vehicles are considered key enablers for intelligent transportation systems. They are equipped with resources/components to enable services for vehicle occupants, other vehicles on the road, and third party recipients. In-vehicle sensors, communication modules, and on-board units with computing and storage capabilities allow the intelligent vehicle to work as a mobile service provider of sensing, data storage, computing, cloud, data relaying, infotainment, and localization services. In this paper, we introduce the concept of Vehicle as a Resource (VaaR) and shed light on the services a vehicle can potentially provide on the road or parked. We anticipate that an intelligent vehicle can be a significant service provider in a variety of situations, including emergency scenarios.
Effect of Social Media on Website Popularity: Differences between Public and Private Universities in Indonesia
Venue: arXiv cs.CY 2014
Year: 2014

Social media has become something that is important to enhance social networking and sharing of information through the website. Social media have not only changed social networking, they provide a valuable tool for social organization, activism, political, healthcare and even academic relations in the university. The researchers conducted present study with objectives to a). examine the academic use of social media by universities, b). measure the popularity and visibility of social media owned by universities. This study was delimited to the universities in Indonesia. The population of the study consisted both on public and private universities. The sample size comprised totally of 264 universities that their ranks included both in Webometrics and 4ICU in July 2012 edition. The social media which was examined included Facebook, Twitter, Flicker, LinkedIn, Youtube, Wikipeda, Blogs, social network community owned by the university and Open Course Ware. This study used an approach for data collection and measurement: by using Alexa and Majestic SEO. Data analysis using the Pearson Chi-square for social media ownership that using data ordinal and independent t test for examining effects of social media on website popularity. The study revealed that majority of the social media users used Facebook, then followed by Twitter. There are also most significant differences for result of popularity by Alexa Rank and visibility by Majestic SEO in universities whether used social media or no.
A Galois-Connection between Myers-Briggs' Type Indicators and Szondi's Personality Profiles
Venue: arXiv cs.CE 2014
Year: 2014

We propose a computable Galois-connection between Myers-Briggs' Type Indicators (MBTIs), the most widely-used personality measure for non-psychiatric populations (based on C.G. Jung's personality types), and Szondi's personality profiles (SPPs), a less well-known but, as we show, finer personality measure for psychiatric as well as non-psychiatric populations (conceived as a unification of the depth psychology of S. Freud, C.G. Jung, and A. Adler). The practical significance of our result is that our Galois-connection provides a pair of computable, interpreting translations between the two personality spaces of MBTIs and SPPs: one concrete from MBTI-space to SPP-space (because SPPs are finer) and one abstract from SPP-space to MBTI-space (because MBTIs are coarser). Thus Myers-Briggs' and Szondi's personality-test results are mutually interpretable and inter-translatable, even automatically by computers.
On the Ordered List Subgraph Embedding Problems
Venue: arXiv cs.DS 2014
Year: 2014

In the (parameterized) Ordered List Subgraph Embedding problem (p-OLSE) we are given two graphs $G$ and $H$, each with a linear order defined on its vertices, a function $L$ that associates with every vertex in $G$ a list of vertices in $H$, and a parameter $k$. The question is to decide if we can embed (one-to-one) a subgraph $S$ of $G$ of $k$ vertices into $H$ such that: (1) every vertex of $S$ is mapped to a vertex from its associated list, (2) the linear orders inherited by $S$ and its image under the embedding are respected, and (3) if there is an edge between two vertices in $S$ then there is an edge between their images. If we require the subgraph $S$ to be embedded as an induced subgraph, we obtain the Ordered List Induced Subgraph Embedding problem (p-OLISE). The p-OLSE and p-OLISE problems model various problems in Bioinformatics related to structural comparison/alignment of proteins. We investigate the complexity of p-OLSE and p-OLISE with respect to the following structural parameters: the width $Δ_L$ of the function $L$ (size of the largest list), and the maximum degree $Δ_H$ of $H$ and $Δ_G$ of $G$. In terms of the structural parameters under consideration, we draw a complete complexity landscape of p-OLSE and p-OLISE (and their optimization versions) with respect to the computational frameworks of classical complexity, parameterized complexity, and approximation.
Online Social Media and Police in India: Behavior, Perceptions, Challenges
Venue: arXiv cs.CY 2014
Year: 2014

Police agencies across the globe are increasingly using Online Social Media (OSM) to acquire intelligence and connect with citizens. Developed nations have well thought of strategies to use OSM for policing. However, developing nations like India are exploring and evolving OSM as a policing solution. India, in recent years, experienced many events where rumors and fake content on OSM instigated communal violence. In contrast to traditional media (e.g. television and print media) used by Indian police departments, OSM offers velocity, variety, veracity and large volume of information. These introduce new challenges for police like platforms selection, secure usage strategy, developing trust, handling offensive comments, and security / privacy implication of information shared through OSM. Success of police initiatives on OSM to maintain law and order depends both on their understanding of OSM and citizen's acceptance / participation on these platforms. This study provides multidimensional understanding of behavior, perceptions, interactions, and expectation regarding policing through OSM. First, we examined recent updates from four different police pages- Delhi, Bangalore, Uttar Pradesh and Chennai to comprehend various dimensions of police interaction with citizens on OSM. Second, we conducted 20 interviews with IPS officers (Indian Police Service) and 17 interviews with citizens to understand decision rationales and expectation gaps between two stakeholders (police and citizens); this was followed up with 445 policemen surveys and 204 citizen surveys. We also present differences between police expectations of Indian and police departments in developed countries.
Parsing using a grammar of word association vectors
Venue: arXiv cs.CL 2014
Year: 2014

This paper was was first drafted in 2001 as a formalization of the system described in U.S. patent U.S. 7,392,174. It describes a system for implementing a parser based on a kind of cross-product over vectors of contextually similar words. It is being published now in response to nascent interest in vector combination models of syntax and semantics. The method used aggressive substitution of contextually similar words and word groups to enable product vectors to stay in the same space as their operands and make entire sentences comparable syntactically, and potentially semantically. The vectors generated had sufficient representational strength to generate parse trees at least comparable with contemporary symbolic parsers.
A study of risk management in cloud computing bank
Venue: arXiv cs.DC 2014
Year: 2014

Cloud computing apparently helps in reducing costs and providing the scheduling optimal level. In practice however it may confront the problem of unavailability of resources. Taking into consideration the cloud computing bank with its somehow commercial nature, the resources unavailability, such as liquidity risk, remains. In this paper, an attempt to show through a solution so far applied in economy, how would it be possible to predict such a liquidity risk in cloud computing bank. The proposed solution can especially be adapted to stock management. To reduce the risk we will also make use of a method inspired from physics based on the fluids mechanics; it is an application of Bernoulli's theorem called Torricelli. The resource bank will be considered as a reservoir of liquid, and the availability of resources then will depend on the liquid flow velocity and the replacement.
A Hybrid Feature Selection Method to Improve Performance of a Group of Classification Algorithms
Venue: arXiv cs.LG 2014
Year: 2014

In this paper a hybrid feature selection method is proposed which takes advantages of wrapper subset evaluation with a lower cost and improves the performance of a group of classifiers. The method uses combination of sample domain filtering and resampling to refine the sample domain and two feature subset evaluation methods to select reliable features. This method utilizes both feature space and sample domain in two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure by information gain, wrapper subset evaluation and genetic search to find the optimal feature space. Experiments carried out on different types of datasets from UCI Repository of Machine Learning databases and the results show a rise in the average performance of five classifiers (Naive Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods with a lower cost.
A Delay-Constrained Protocol with Adaptive Mode Selection for Bidirectional Relay Networks
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, we consider a bidirectional relay network with half-duplex nodes and block fading where the nodes transmit with a fixed transmission rate. Thereby, user 1 and user 2 exchange information only via a relay node, i.e., a direct link between both users is not present. Recently in [1], it was shown that a considerable gain in terms of sum throughput can be obtained in bidirectional relaying by optimally selecting the transmission modes or, equivalently, the states of the nodes, i.e., the transmit, the receive, and the silent states, in each time slot based on the qualities of the involved links. To enable adaptive transmission mode selection, the relay has to be equipped with two buffers for storage of the data received from the two users. However, the protocol proposed in [1] was delay-unconstrained and provides an upper bound for the performance of practical delay-constrained protocols. In this paper, we propose a heuristic but efficient delay-constrained protocol which can approach the performance upper bound reported in [1], even in cases where only a small average delay is permitted. In particular, the proposed protocol does not only take into account the instantaneous qualities of the involved links for adaptive mode selection but also the states of the queues at the buffers. The average throughput and the average delay of the proposed delay-constrained protocol are evaluated by analyzing the Markov chain of the states of the queues.
Turing: Then, Now and Still Key
Venue: arXiv cs.AI 2014
Year: 2014

This paper looks at Turing's postulations about Artificial Intelligence in his paper 'Computing Machinery and Intelligence', published in 1950. It notes how accurate they were and how relevant they still are today. This paper notes the arguments and mechanisms that he suggested and tries to expand on them further. The paper however is mostly about describing the essential ingredients for building an intelligent model and the problems related with that. The discussion includes recent work by the author himself, who adds his own thoughts on the matter that come from a purely technical investigation into the problem. These are personal and quite speculative, but provide an interesting insight into the mechanisms that might be used for building an intelligent system.