OpenRaiser/Intern-Atlas huggingface dataset:
A Multi-View Embedding Space for Modeling Internet Images, Tags, and their Semantics
Venue: arXiv cs.CV 2013
Year: 2013

This paper investigates the problem of modeling Internet images and associated text or tags for tasks such as image-to-image search, tag-to-image search, and image-to-tag search (image annotation). We start with canonical correlation analysis (CCA), a popular and successful approach for mapping visual and textual features to the same latent space, and incorporate a third view capturing high-level image semantics, represented either by a single category or multiple non-mutually-exclusive concepts. We present two ways to train the three-view embedding: supervised, with the third view coming from ground-truth labels or search keywords; and unsupervised, with semantic themes automatically obtained by clustering the tags. To ensure high accuracy for retrieval tasks while keeping the learning process scalable, we combine multiple strong visual features and use explicit nonlinear kernel mappings to efficiently approximate kernel CCA. To perform retrieval, we use a specially designed similarity function in the embedded space, which substantially outperforms the Euclidean distance. The resulting system produces compelling qualitative results and outperforms a number of two-view baselines on retrieval tasks on three large-scale Internet image datasets.
Bringing simulation to implementation: Presentation of a global approach in the design of passive solar buildings under humid tropical climates
Venue: arXiv cs.CE 2013
Year: 2013

In early 1995, a DSM pilot initiative has been launched in the French islands of Guadeloupe and Reunion through a partnership between several public and private partners (the French Public Utility EDF, the University of Reunion Island, low cost housing companies, architects, energy consultants, etc...) to set up standards to improve thermal design of new residential buildings in tropical climates. This partnership led to defining optimized bio-climatic urban planning and architectural designs featuring the use of passive cooling architectural principles (solar shading, natural ventilation) and components, as well as energy efficient systems and technologies. The design and sizing of each architectural component on internal thermal comfort in building has been assessed with a validated thermal and airflow building simulation software (CODYRUN). These technical specifications have been edited in a reference document which has been used to build over 300 new pilot dwellings through the years 1996-1998 in Reunion Island and in Guadeloupe. An experimental monitoring has been made in these first ECODOM dwellings in 1998 and 1999. It will result in experimental validation of impact of the passive cooling strategies on thermal comfort of occupants leading to modify specifications if necessary. The paper present all the methodology used for the elaboration of ECODOM, from the simulations to the experimental results. This follow up is important, as the setting up of the ECODOM standard will be the first step towards the setting up of thermal regulations in the French overseas territories, by the year 2002.
Generating Motion Patterns Using Evolutionary Computation in Digital Soccer
Venue: arXiv cs.AI 2013
Year: 2013

Dribbling an opponent player in digital soccer environment is an important practical problem in motion planning. It has special complexities which can be generalized to most important problems in other similar Multi Agent Systems. In this paper, we propose a hybrid computational geometry and evolutionary computation approach for generating motion trajectories to avoid a mobile obstacle. In this case an opponent agent is not only an obstacle but also one who tries to harden dribbling procedure. One characteristic of this approach is reducing process cost of online stage by transferring it to offline stage which causes increment in agents' performance. This approach breaks the problem into two offline and online stages. During offline stage the goal is to find desired trajectory using evolutionary computation and saving it as a trajectory plan. A trajectory plan consists of nodes which approximate information of each trajectory plan. In online stage, a linear interpolation along with Delaunay triangulation in xy-plan is applied to trajectory plan to retrieve desired action.
Maximum Balanced Subgraph Problem Parameterized Above Lower Bound
Venue: arXiv cs.DS 2013
Year: 2013

We consider graphs without loops or parallel edges in which every edge is assigned + or -. Such a signed graph is balanced if its vertex set can be partitioned into parts $V_1$ and $V_2$ such that all edges between vertices in the same part have sign + and all edges between vertices of different parts have sign $-$ (one of the parts may be empty). It is well-known that every connected signed graph with $n$ vertices and $m$ edges has a balanced subgraph with at least $\frac{m}{2} + \frac{n-1}{4}$ edges and this bound is tight. We consider the following parameterized problem: given a connected signed graph $G$ with $n$ vertices and $m$ edges, decide whether $G$ has a balanced subgraph with at least $\frac{m}{2} + \frac{n-1}{4}+\frac{k}{4}$ edges, where $k$ is the parameter. We obtain an algorithm for the problem of runtime $8^k(kn)^{O(1)}$. We also prove that for each instance $(G,k)$ of the problem, in polynomial time, we can either solve $(G,k)$ or produce an equivalent instance $(G',k')$ such that $k'\le k$ and $|V(G')|=O(k^3)$. Our first result generalizes a result of Crowston, Jones and Mnich (ICALP 2012) on the corresponding parameterization of Max Cut (when every edge of $G$ has sign $-$). Our second result generalizes and significantly improves the corresponding result of Crowston, Jones and Mnich: they showed that $|V(G')|=O(k^5)$.
On Minimizing Data-read and Download for Storage-Node Recovery
Venue: arXiv cs.IT 2013
Year: 2013

We consider the problem of efficient recovery of the data stored in any individual node of a distributed storage system, from the rest of the nodes. Applications include handling failures and degraded reads. We measure efficiency in terms of the amount of data-read and the download required. To minimize the download, we focus on the minimum bandwidth setting of the 'regenerating codes' model for distributed storage. Under this model, the system has a total of n nodes, and the data stored in any node must be (efficiently) recoverable from any d of the other (n-1) nodes. Lower bounds on the two metrics under this model were derived previously; it has also been shown that these bounds are achievable for the amount of data-read and download when d=n-1, and for the amount of download alone when d<n-1. In this paper, we complete this picture by proving the converse result, that when d<n-1, these lower bounds are strictly loose with respect to the amount of read required. The proof is information-theoretic, and hence applies to non-linear codes as well. We also show that under two (practical) relaxations of the problem setting, these lower bounds can be met for both read and download simultaneously.
Formal Verification, Engineering and Business Value
Venue: arXiv cs.SE 2013
Year: 2013

How to apply automated verification technology such as model checking and static program analysis to millions of lines of embedded C/C++ code? How to package this technology in a way that it can be used by software developers and engineers, who might have no background in formal verification? And how to convince business managers to actually pay for such a software? This work addresses a number of those questions. Based on our own experience on developing and distributing the Goanna source code analyzer for detecting software bugs and security vulnerabilities in C/C++ code, we explain the underlying technology of model checking, static analysis and SMT solving, steps involved in creating industrial-proof tools.
Formal Model-Driven Engineering: Generating Data and Behavioural Components
Venue: arXiv cs.SE 2013
Year: 2013

Model-driven engineering is the automatic production of software artefacts from abstract models of structure and functionality. By targeting a specific class of system, it is possible to automate aspects of the development process, using model transformations and code generators that encode domain knowledge and implementation strategies. Using this approach, questions of correctness for a complex, software system may be answered through analysis of abstract models of lower complexity, under the assumption that the transformations and generators employed are themselves correct. This paper shows how formal techniques can be used to establish the correctness of model transformations used in the generation of software components from precise object models. The source language is based upon existing, formal techniques; the target language is the widely-used SQL notation for database programming. Correctness is established by giving comparable, relational semantics to both languages, and checking that the transformations are semantics-preserving.
A Timed Calculus for Mobile Ad Hoc Networks
Venue: arXiv cs.LO 2013
Year: 2013

We develop a timed calculus for Mobile Ad Hoc Networks embodying the peculiarities of local broadcast, node mobility and communication interference. We present a Reduction Semantics and a Labelled Transition Semantics and prove the equivalence between them. We then apply our calculus to model and study some MAC-layer protocols with special emphasis on node mobility and communication interference. A main purpose of the semantics is to describe the various forms of interference while nodes change their locations in the network. Such interference only occurs when a node is simultaneously reached by more than one ongoing transmission over the same channel.
CloudSVM : Training an SVM Classifier in Cloud Computing Systems
Venue: arXiv cs.LG 2013
Year: 2013

In conventional method, distributed support vector machines (SVM) algorithms are trained over pre-configured intranet/internet environments to find out an optimal classifier. These methods are very complicated and costly for large datasets. Hence, we propose a method that is referred as the Cloud SVM training mechanism (CloudSVM) in a cloud computing environment with MapReduce technique for distributed machine learning applications. Accordingly, (i) SVM algorithm is trained in distributed cloud storage servers that work concurrently; (ii) merge all support vectors in every trained cloud node; and (iii) iterate these two steps until the SVM converges to the optimal classifier function. Large scale data sets are not possible to train using SVM algorithm on a single computer. The results of this study are important for training of large scale data sets for machine learning applications. We provided that iterative training of splitted data set in cloud computing environment using SVM will converge to a global optimal classifier in finite iteration size.
Classifier Fusion Method to Recognize Handwritten Kannada Numerals
Venue: arXiv cs.CV 2013
Year: 2013

Optical Character Recognition (OCR) is one of the important fields in image processing and pattern recognition domain. Handwritten character recognition has always been a challenging task. Only a little work can be traced towards the recognition of handwritten characters for the south Indian languages. Kannada is one such south Indian language which is also one of the official language of India. Accurate recognition of Kannada characters is a challenging task because of the high degree of similarity between the characters. Hence, good quality features are to be extracted and better classifiers are needed to improve the accuracy of the OCR for Kannada characters. This paper explores the effectiveness of feature extraction method like run length count (RLC) and directional chain code (DCC) for the recognition of handwritten Kannada numerals. In this paper, a classifier fusion method is implemented to improve the recognition rate. For the classifier fusion, we have considered K-nearest neighbour (KNN) and Linear classifier (LC). The novelty of this method is to achieve better accuracy with few features using classifier fusion approach. Proposed method achieves an average recognition rate of 96%.
Cross-Layer Strategies for Throughput Maximization in Data Aggregating Wireless Networks
Venue: arXiv cs.NI 2013
Year: 2013

We consider a data aggregating wireless network where all nodes have data to send to a single destination node, the sink. We consider a linear placement of nodes with the sink at one end. The nodes communicate directly to the sink (single hop transmission) and we assume that the nodes are scheduled one at a time by a central scheduler (possibly the sink). The wireless nodes are power limited and our network objective (notion of fairness) is to maximize the minimum throughput of the nodes subject to the node power constraints. In this work, we consider network designs that permit adapting node transmission time, node transmission power and node placements, and study cross- layer strategies that seek to maximize the network throughput. Using simulations, we characterize the performance of the dif- ferent strategies and comment on their applicability for various network scenarios.
Applying Strategic Multiagent Planning to Real-World Travel Sharing Problems
Venue: arXiv cs.AI 2013
Year: 2013

Travel sharing, i.e., the problem of finding parts of routes which can be shared by several travellers with different points of departure and destinations, is a complex multiagent problem that requires taking into account individual agents' preferences to come up with mutually acceptable joint plans. In this paper, we apply state-of-the-art planning techniques to real-world public transportation data to evaluate the feasibility of multiagent planning techniques in this domain. The potential application value of improving travel sharing technology has great application value due to its ability to reduce the environmental impact of travelling while providing benefits to travellers at the same time. We propose a three-phase algorithm that utilises performant single-agent planners to find individual plans in a simplified domain first, then merges them using a best-response planner which ensures resulting solutions are individually rational, and then maps the resulting plan onto the full temporal planning domain to schedule actual journeys. The evaluation of our algorithm on real-world, multi-modal public transportation data for the United Kingdom shows linear scalability both in the scenario size and in the number of agents, where trade-offs have to be made between total cost improvement, the percentage of feasible timetables identified for journeys, and the prolongation of these journeys. Our system constitutes the first implementation of strategic multiagent planning algorithms in large-scale domains and provides insights into the engineering process of translating general domain-independent multiagent planning algorithms to real-world applications.
Usable Speech Assignment for Speaker Identification under Co-Channel Situation
Venue: arXiv cs.SD 2013
Year: 2013

Usable speech criteria are proposed to extract minimally corrupted speech for speaker identification (SID) in co-channel speech. In co-channel speech, either speaker can randomly appear as the stronger speaker or the weaker one at a time. Hence, the extracted usable segments are separated in time and need to be organized into speaker streams for SID. In this paper, we focus to organize extracted usable speech segment into a single stream for the same speaker by speaker assignment system. For this, we develop model-based speaker assignment method based on posterior probability and exhaustive search algorithm. Evaluation of this method is performed on TIMIT database. The system is evaluated on co-channel speech and results show a significant improvement.
A Poisson Hidden Markov Model for Multiview Video Traffic
Venue: arXiv cs.MM 2013
Year: 2013

Multiview video has recently emerged as a means to improve user experience in novel multimedia services. We propose a new stochastic model to characterize the traffic generated by a Multiview Video Coding (MVC) variable bit rate source. To this aim, we resort to a Poisson Hidden Markov Model (P-HMM), in which the first (hidden) layer represents the evolution of the video activity and the second layer represents the frame sizes of the multiple encoded views. We propose a method for estimating the model parameters in long MVC sequences. We then present extensive numerical simulations assessing the model's ability to produce traffic with realistic characteristics for a general class of MVC sequences. We then extend our framework to network applications where we show that our model is able to accurately describe the sender and receiver buffers behavior in MVC transmission. Finally, we derive a model of user behavior for interactive view selection, which, in conjunction with our traffic model, is able to accurately predict actual network load in interactive multiview services.
Employing functional interactions for characterization and detection of sparse complexes from yeast PPI networks
Venue: arXiv cs.CE 2013
Year: 2013

Over the last few years, several computational techniques have been devised to recover protein complexes from the protein interaction (PPI) networks of organisms. These techniques model "dense" subnetworks within PPI networks as complexes. However, our comprehensive evaluations revealed that these techniques fail to reconstruct many 'gold standard' complexes that are "sparse" in the networks (only 71 recovered out of 123 known yeast complexes embedded in a network of 9704 interactions among 1622 proteins). In this work, we propose a novel index called Component-Edge (CE) score to quantitatively measure the notion of "complex derivability" from PPI networks. Using this index, we theoretically categorize complexes as "sparse" or "dense" with respect to a given network. We then devise an algorithm SPARC that selectively employs functional interactions to improve the CE scores of predicted complexes, and thereby elevates many of the "sparse" complexes to "dense". This empowers existing methods to detect these "sparse" complexes. We demonstrate that our approach is effective in reconstructing significantly many complexes missed previously (104 recovered out of the 123 known complexes or ~47% improvement).
Algebraic Logic, I Quantifier Theories and Completeness Theorems
Venue: arXiv cs.LO 2013
Year: 2013

Algebraic logic studies algebraic theories related to proposition and first-order logic. A new algebraic approach to first-order logic is sketched in this paper. We introduce the notion of a quantifier theory, which is a functor from the category of a monad of sets to the category of Boolean algebras, together with a uniquely determined system of quantifiers. A striking feature of this approach is that Cayley's Completeness Theorem and Godel's Completeness Theorem can be stated and proved in a much simpler fashion for quantifier theories. Both theorems are due to Halmos for polyadic algebras. We also present a simple transparent treatment of ultraproducts of models of a quantifier theory.
A Quality and Cost Approach for Comparison of Small-World Networks
Venue: arXiv cs.SI 2013
Year: 2013

We propose an approach based on analysis of cost-quality tradeoffs for comparison of efficiency of various algorithms for small-world network construction. A number of both known in the literature and original algorithms for complex small-world networks construction are shortly reviewed and compared. The networks constructed on the basis of these algorithms have basic structure of 1D regular lattice with additional shortcuts providing the small-world properties. It is shown that networks proposed in this work have the best cost-quality ratio in the considered class.
Joint localization and clock synchronization for wireless sensor networks
Venue: arXiv cs.IT 2013
Year: 2013

A fully-asynchronous network with one target sensor and a few anchors (nodes with known locations) is considered. Localization and synchronization are traditionally treated as two separate problems. In this paper, localization and synchronization is studied under a unified framework. We present a new model in which time-stamps obtained either via two-way communication between the nodes or with a broadcast based protocol can be used in a simple estimator based on least-squares (LS) to jointly estimate the position of the target node as well as all the unknown clock-skews and clock-offsets. The Cramér-Rao lower bound (CRLB) is derived for the considered problem and is used as a benchmark to analyze the performance of the proposed estimator.
Power-Efficient System Design for Cellular-Based Machine-to-Machine Communications
Venue: arXiv cs.IT 2013
Year: 2013

The growing popularity of Machine-to-Machine (M2M) communications in cellular networks is driving the need to optimize networks based on the characteristics of M2M, which are significantly different from the requirements that current networks are designed to meet. First, M2M requires large number of short sessions as opposed to small number of long lived sessions required by the human generated traffic. Second, M2M constitutes a number of battery operated devices that are static in locations such as basements and tunnels, and need to transmit at elevated powers compared to the traditional devices. Third, replacing or recharging batteries of such devices may not be feasible. All these differences highlight the importance of a systematic framework to study the power and energy optimal system design in the regime of interest for M2M, which is the main focus of this paper. For a variety of coordinated and uncoordinated transmission strategies, we derive results for the optimal transmit power, energy per bit, and the maximum load supported by the base station, leading to the following design guidelines: (i) frequency division multiple access (FDMA), including equal bandwidth allocation, is sum-power optimal in the asymptotically low spectral efficiency regime, (ii) while FDMA is the best practical strategy overall, uncoordinated code division multiple access (CDMA) is almost as good when the base station is lightly loaded, (iii) the value of optimization within FDMA is in general not significant in the regime of interest for M2M.
Hybridization of Evolutionary Algorithms
Venue: arXiv cs.NE 2013
Year: 2013

Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized. In this chapter, the hybridization of the three elements of the evolutionary algorithms is discussed: the objective function, the survivor selection operator and the parameter settings. As an objective function, the existing heuristic function that construct the solution of the problem in traditional way is used. However, this function is embedded into the evolutionary algorithm that serves as a generator of new solutions. In addition, the objective function is improved by local search heuristics. The new neutral selection operator has been developed that is capable to deal with neutral solutions, i.e. solutions that have the different representation but expose the equal values of objective function. The aim of this operator is to directs the evolutionary search into a new undiscovered regions of the search space. To avoid of wrong setting of parameters that control the behavior of the evolutionary algorithm, the self-adaptation is used. Finally, such hybrid self-adaptive evolutionary algorithm is applied to the two real-world NP-hard problems: the graph 3-coloring and the optimization of markers in the clothing industry. Extensive experiments shown that these hybridization improves the results of the evolutionary algorithms a lot. Furthermore, the impact of the particular hybridizations is analyzed in details as well.