OpenRaiser/Intern-Atlas huggingface dataset:
Phase Transition in Unrestricted Random SAT
Venue: arXiv cs.CC 2012
Year: 2012

For random CNF formulae with m clauses, n variables and an unrestricted number of literals per clause the transition from high to low satisfiability can be determined exactly for large n. The critical density m/n turns out to be strongly n-dependent, ccr = ln(2)/(1-p)^^n, where pn is the mean number of positive literals per clause.This is in contrast to restricted random SAT problems (random K-SAT), where the critical ratio m/n is a constant. All transition lines are calculated by the second moment method applied to the number of solutions N of a formula. In contrast to random K-SAT, the method does not fail for the unrestricted model, because long range interactions between solutions are not cut off by disorder.
Clustering and Bayesian network for image of faces classification
Venue: arXiv cs.CV 2012
Year: 2012

In a content based image classification system, target images are sorted by feature similarities with respect to the query (CBIR). In this paper, we propose to use new approach combining distance tangent, k-means algorithm and Bayesian network for image classification. First, we use the technique of tangent distance to calculate several tangent spaces representing the same image. The objective is to reduce the error in the classification phase. Second, we cut the image in a whole of blocks. For each block, we compute a vector of descriptors. Then, we use K-means to cluster the low-level features including color and texture information to build a vector of labels for each image. Finally, we apply five variants of Bayesian networks classifiers (Naïve Bayes, Global Tree Augmented Naïve Bayes (GTAN), Global Forest Augmented Naïve Bayes (GFAN), Tree Augmented Naïve Bayes for each class (TAN), and Forest Augmented Naïve Bayes for each class (FAN) to classify the image of faces using the vector of labels. In order to validate the feasibility and effectively, we compare the results of GFAN to FAN and to the others classifiers (NB, GTAN, TAN). The results demonstrate FAN outperforms than GFAN, NB, GTAN and TAN in the overall classification accuracy.
Smart Antenna for Cellular Mobile Communication
Venue: arXiv cs.NI 2012
Year: 2012

The adoption of smart / adaptive antenna techniques in future wireless systems is expected to have a significant impact on the efficient use of the spectrum, the minimization of the cost of establishing new wireless networks, the optimization of service quality and realization of transparent operation across multi technology wireless networks [1]. This paper presents brief account on smart antenna (SA) system. SAs can place nulls in the direction of interferers via adaptive updating of weights linked to each antenna element. SAs thus cancel out most of the co-channel interference resulting in better quality of reception and lower dropped calls. SAs can also track the user within a cell via direction of arrival algorithms [2]. This paper explains the architecture, evolution and how the smart / adaptive antenna differs from the basic format of antenna. The paper further explains about the radiation pattern of the antenna and why it is highly preferred in its relative field. The capabilities of smart / adaptive antenna are easily employable to Cognitive Radio and OFDMA system.
Mobile Learning Environment System (MLES): The Case of Android-based Learning Application on Undergraduates' Learning
Venue: arXiv cs.CY 2012
Year: 2012

Of late, mobile technology has introduced new, novel environment that can be capitalized to further enrich the teaching and learning process in classrooms. Taking cognizance of this promising setting, a study was undertaken to investigate the impact of such an environment enabled by android platform on the learning process among undergraduates of Sultan Idris Education University, Malaysia; in particular, this paper discusses critical aspects of the design and implementation of the android learning system. Data were collected through a survey involving 56 respondents, and these data were analyzed by using SPSS 12.0. Findings showed that the respondents were very receptive to the interactivity, accessibility, and convenience of the system, but they were quite frustrated with the occasional interruptions due to internet connectivity problems. Overall, the mobile learning system can be utilized as an inexpensive but potent learning tool that complements undergraduates' learning process.
Improving Route Discovery Using Stable Connected Dominating Set in MANETs
Venue: arXiv cs.NI 2012
Year: 2012

A Connected Dominating Set (CDS) based virtual backbone plays an important role in wireless ad hoc networks for efficient routing and broadcasting. Each node in the network can select some of its 1-hop neighbors as Multi Point Relay (MPR) to cover all its 2-hop neighbors. A MPR based CDS is a promising approach for broadcasting. A node in the CDS consumes more energy and the energy depletes quickly than non dominating nodes. Although previous CDS construction algorithms achieve good results in terms of the size of CDS, a minimum size CDS does not necessarily guarantee an optimal network performance from an energy efficient point of view. In this paper, we propose a distributed algorithm for energy efficient stable MPR based CDS construction to extend the lifetime of ad hoc wireless networks by considering energy and velocity of nodes. We have also implemented route discovery protocol to make use of the CDS nodes to relay route request messages. The simulation results show that our algorithm increases the lifetime up to 25% than previous works and 60% reduction in the route request messages during route discovery process.
Automatic facial feature extraction and expression recognition based on neural network
Venue: arXiv cs.CV 2012
Year: 2012

In this paper, an approach to the problem of automatic facial feature extraction from a still frontal posed image and classification and recognition of facial expression and hence emotion and mood of a person is presented. Feed forward back propagation neural network is used as a classifier for classifying the expressions of supplied face into seven basic categories like surprise, neutral, sad, disgust, fear, happy and angry. For face portion segmentation and localization, morphological image processing operations are used. Permanent facial features like eyebrows, eyes, mouth and nose are extracted using SUSAN edge detection operator, facial geometry, edge projection analysis. Experiments are carried out on JAFFE facial expression database and gives better performance in terms of 100% accuracy for training set and 95.26% accuracy for test set.
Publishing Identifiable Experiment Code And Configuration Is Important, Good and Easy
Venue: arXiv cs.RO 2012
Year: 2012

We argue for the value of publishing the exact code, configuration and data processing scripts used to produce empirical work in robotics. In particular, we recommend publishing a unique identifier for the code package in the paper itself, as a promise to the reader that this is the relavant code. We review some recent discussion of best practice for reproducibility in various professional organisations and journals, and discuss the current reward structure for publishing code in robotics, along with some ideas for improvement.
Coordinated Home Energy Management for Real-Time Power Balancing
Venue: arXiv cs.SY 2012
Year: 2012

This paper proposes a coordinated home energy management system (HEMS) architecture where the distributed residential units cooperate with each other to achieve real-time power balancing. The economic benefits for the retailer and incentives for the customers to participate in the proposed coordinated HEMS program are given. We formulate the coordinated HEMS design problem as a dynamic programming (DP) and use approximate DP approaches to efficiently handle the design problem. A distributed implementation algorithm based on the convex optimization based dual decomposition technique is also presented. Our focus in the current paper is on the deferrable appliances, such as Plug-in (Hybrid) Electric Vehicles (PHEV), in view of their higher impact on the grid stability. Simulation results shows that the proposed coordinated HEMS architecture can efficiently improve the real-time power balancing.
An Overview of Video Allocation Algorithms for Flash-based SSD Storage Systems
Venue: arXiv cs.MM 2012
Year: 2012

Despite the fact that Solid State Disk (SSD) data storage media had offered a revolutionary property storages community, but the unavailability of a comprehensive allocation strategy in SSDs storage media, leads to consuming the available space, random writing processes, time-consuming reading processes, and system resources consumption. In order to overcome these challenges, an efficient allocation algorithm is a desirable option. In this paper, we had executed an intensive investigation on the SSD-based allocation algorithms that had been proposed by the knowledge community. An explanatory comparison had been made between these algorithms. We reviewed these algorithms in order to building advanced knowledge armature that would help in inventing new allocation algorithms for this type of storage media.
Vision-Based Cooperative Estimation of Averaged 3D Target Pose under Imperfect Visibility
Venue: arXiv cs.SY 2012
Year: 2012

This paper investigates vision-based cooperative estimation of a 3D target object pose for visual sensor networks. In our previous works, we presented an estimation mechanism called networked visual motion observer achieving averaging of local pose estimates in real time. This paper extends the mechanism so that it works even in the presence of cameras not viewing the target due to the limited view angles and obstructions in order to fully take advantage of the networked vision system. Then, we analyze the averaging performance attained by the proposed mechanism and clarify a relation between the feedback gains in the algorithm and the performance. Finally, we demonstrate the effectiveness of the algorithm through simulation.
Fast emergency paths schema to overcome transient link failures in ospf routing
Venue: arXiv cs.NI 2012
Year: 2012

A reliable network infrastructure must be able to sustain traffic flows, even when a failure occurs and changes the network topology. During the occurrence of a failure, routing protocols, like OSPF, take from hundreds of milliseconds to various seconds in order to converge. During this convergence period, packets might traverse a longer path or even a loop. An even worse transient behaviour is that packets are dropped even though destinations are reachable. In this context, this paper describes a proactive fast rerouting approach, named Fast Emergency Paths Schema (FEP-S), to overcome problems originating from transient link failures in OSPF routing. Extensive experiments were done using several network topologies with different dimensionality degrees. Results show that the recovery paths, obtained by FEPS, are shorter than those from other rerouting approaches and can improve the network reliability by reducing the packet loss rate during the routing protocols convergence caused by a failure.
SecureSMART: A Security Architecture for BFT Replication Libraries
Venue: arXiv cs.CR 2012
Year: 2012

Several research projects have shown that Byzantine fault tolerance (BFT) is practical today in terms of performance. Deficiencies in other aspects might still be an obstacle to a more wide-spread deployment in real-world applications. One of these aspects is an over-all security architecture beyond the low-level protocol. This paper proposes the security architecture SecureSMART, which provides dynamic key distribution, internal and external integrity and confidentiality measures, as well as mechanisms for availability and access control. For this purpose, it implements security mechanism among clients, nodes and an external trust center.
Noise based logic: why noise? A comparative study of the necessity of randomness out of orthogonality
Venue: arXiv cs.OH 2012
Year: 2012

Although noise-based logic shows potential advantages of reduced power dissipation and the ability of large parallel operations with low hardware and time complexity the question still persist: is randomness really needed out of orthogonality? In this Letter, after some general thermodynamical considerations, we show relevant examples where we compare the computational complexity of logic systems based on orthogonal noise and sinusoidal signals, respectively. The conclusion is that in certain special-purpose applications noise-based logic is exponentially better than its sinusoidal version: its computational complexity can be exponentially smaller to perform the same task.
Reduced-Complexity Column-Layered Decoding and Implementation for LDPC Codes
Venue: arXiv cs.IT 2012
Year: 2012

Layered decoding is well appreciated in Low-Density Parity-Check (LDPC) decoder implementation since it can achieve effectively high decoding throughput with low computation complexity. This work, for the first time, addresses low complexity column-layered decoding schemes and VLSI architectures for multi-Gb/s applications. At first, the Min-Sum algorithm is incorporated into the column-layered decoding. Then algorithmic transformations and judicious approximations are explored to minimize the overall computation complexity. Compared to the original column-layered decoding, the new approach can reduce the computation complexity in check node processing for high-rate LDPC codes by up to 90% while maintaining the fast convergence speed of layered decoding. Furthermore, a relaxed pipelining scheme is presented to enable very high clock speed for VLSI implementation. Equipped with these new techniques, an efficient decoder architecture for quasi-cyclic LDPC codes is developed and implemented with 0.13um CMOS technology. It is shown that a decoding throughput of nearly 4 Gb/s at maximum of 10 iterations can be achieved for a (4096, 3584) LDPC code. Hence, this work has facilitated practical applications of column-layered decoding and particularly made it very attractive in high-speed, high-rate LDPC decoder implementation.
Detecting lateral genetic material transfer
Venue: arXiv cs.NE 2012
Year: 2012

The bioinformatical methods to detect lateral gene transfer events are mainly based on functional coding DNA characteristics. In this paper, we propose the use of DNA traits not depending on protein coding requirements. We introduce several semilocal variables that depend on DNA primary sequence and that reflect thermodynamic as well as physico-chemical magnitudes that are able to tell apart the genome of different organisms. After combining these variables in a neural classificator, we obtain results whose power of resolution go as far as to detect the exchange of genomic material between bacteria that are phylogenetically close.
Multiuser Switched Diversity Scheduling Schemes
Venue: arXiv cs.IT 2012
Year: 2012

Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions.
Learning to Rank Query Recommendations by Semantic Similarities
Venue: arXiv cs.AI 2012
Year: 2012

Logs of the interactions with a search engine show that users often reformulate their queries. Examining these reformulations shows that recommendations that precise the focus of a query are helpful, like those based on expansions of the original queries. But it also shows that queries that express some topical shift with respect to the original query can help user access more rapidly the information they need. We propose a method to identify from the query logs of past users queries that either focus or shift the initial query topic. This method combines various click-based, topic-based and session based ranking strategies and uses supervised learning in order to maximize the semantic similarities between the query and the recommendations, while at the same diversifying them. We evaluate our method using the query/click logs of a Japanese web search engine and we show that the combination of the three methods proposed is significantly better than any of them taken individually.
Leveraging Usage Data for Linked Data Movie Entity Summarization
Venue: arXiv cs.AI 2012
Year: 2012

Novel research in the field of Linked Data focuses on the problem of entity summarization. This field addresses the problem of ranking features according to their importance for the task of identifying a particular entity. Next to a more human friendly presentation, these summarizations can play a central role for semantic search engines and semantic recommender systems. In current approaches, it has been tried to apply entity summarization based on patterns that are inherent to the regarded data. The proposed approach of this paper focuses on the movie domain. It utilizes usage data in order to support measuring the similarity between movie entities. Using this similarity it is possible to determine the k-nearest neighbors of an entity. This leads to the idea that features that entities share with their nearest neighbors can be considered as significant or important for these entities. Additionally, we introduce a downgrading factor (similar to TF-IDF) in order to overcome the high number of commonly occurring features. We exemplify the approach based on a movie-ratings dataset that has been linked to Freebase entities.
Simultaneous Object Detection, Tracking, and Event Recognition
Venue: arXiv cs.CV 2012
Year: 2012

The common internal structure and algorithmic organization of object detection, detection-based tracking, and event recognition facilitates a general approach to integrating these three components. This supports multidirectional information flow between these components allowing object detection to influence tracking and event recognition and event recognition to influence tracking and object detection. The performance of the combination can exceed the performance of the components in isolation. This can be done with linear asymptotic complexity.
Video In Sentences Out
Venue: arXiv cs.CV 2012
Year: 2012

We present a system that produces sentential descriptions of video: who did what to whom, and where and how they did it. Action class is rendered as a verb, participant objects as noun phrases, properties of those objects as adjectival modifiers in those noun phrases,spatial relations between those participants as prepositional phrases, and characteristics of the event as prepositional-phrase adjuncts and adverbial modifiers. Extracting the information needed to render these linguistic entities requires an approach to event recognition that recovers object tracks, the track-to-role assignments, and changing body posture.
An Empirical Study of Spam and Prevention Mechanisms in Online Video Chat Services
Venue: arXiv cs.CR 2012
Year: 2012

Recently, online video chat services are becoming increasingly popular. While experiencing tremendous growth, online video chat services have also become yet another spamming target. Unlike spam propagated via traditional medium like emails and social networks, we find that spam propagated via online video chat services is able to draw much larger attention from the users. We have conducted several experiments to investigate spam propagation on Chatroulette - the largest online video chat website. We have found that the largest spam campaign on online video chat websites is dating scams. Our study indicates that spam carrying dating or pharmacy scams have much higher clickthrough rates than email spam carrying the same content. In particular, dating scams reach a clickthrough rate of 14.97%. We also examined and analysed spam prevention mechanisms that online video chat websites have designed and implemented. Our study indicates that the prevention mechanisms either harm legitimate user experience or can be easily bypassed.
The DoF Region of the Multiple-Antenna Time Correlated Interference Channel with Delayed CSIT
Venue: arXiv cs.IT 2012
Year: 2012

We consider the time-correlated multiple-antenna interference channel where the transmitters have (i) delayed channel state information (CSI) obtained from a latency-prone feedback channel as well as (ii) imperfect current CSIT, obtained e.g. from prediction on the basis of these past channel samples. We derive the degrees of freedom (DoF) region for the two-user multiple-antenna interference channel under such conditions. The proposed DoF achieving scheme exploits a particular combination of the space-time alignment protocol designed for fully outdated CSIT feedback channels (initially developed for the broadcast channel by Maddah-Ali et al, later extended to the interference channel by Vaze et al. and Ghasemi et al.) together with the use of simple zero-forcing (ZF) precoders. The essential ingredient lies in the quantization and feedback of the residual interference left after the application of the initial imperfect ZF precoder. Our focus is on the MISO setting albeit extensions to certain MIMO cases are also considered.
Technical Report: Observability of a Linear System under Sparsity Constraints
Venue: arXiv cs.IT 2012
Year: 2012

Consider an n-dimensional linear system where it is known that there are at most k<n non-zero components in the initial state. The observability problem, that is the recovery of the initial state, for such a system is considered. We obtain sufficient conditions on the number of the available observations to be able to recover the initial state exactly for such a system. Both deterministic and stochastic setups are considered for system dynamics. In the former setting, the system matrices are known deterministically, whereas in the latter setting, all of the matrices are picked from a randomized class of matrices. The main message is that, one does not need to obtain full n observations to be able to uniquely identify the initial state of the linear system, even when the observations are picked randomly, when the initial condition is known to be sparse.
Looking at a digital research data archive - Visual interfaces to EASY
Venue: arXiv cs.DL 2012
Year: 2012

In this paper we explore visually the structure of the collection of a digital research data archive in terms of metadata for deposited datasets. We look into the distribution of datasets over different scientific fields; the role of main depositors (persons and institutions) in different fields, and main access choices for the deposited datasets. We argue that visual analytics of metadata of collections can be used in multiple ways: to inform the archive about structure and growth of its collection; to foster collections strategies; and to check metadata consistency. We combine visual analytics and visual enhanced browsing introducing a set of web-based, interactive visual interfaces to the archive's collection. We discuss how text based search combined with visual enhanced browsing enhances data access, navigation, and reuse.