OpenRaiser/Intern-Atlas huggingface dataset:
Person Re-identification by Saliency Learning
Venue: arXiv cs.CV 2014
Year: 2014

Human eyes can recognize person identities based on small salient regions, i.e. human saliency is distinctive and reliable in pedestrian matching across disjoint camera views. However, such valuable information is often hidden when computing similarities of pedestrian images with existing approaches. Inspired by our user study result of human perception on human saliency, we propose a novel perspective for person re-identification based on learning human saliency and matching saliency distribution. The proposed saliency learning and matching framework consists of four steps: (1) To handle misalignment caused by drastic viewpoint change and pose variations, we apply adjacency constrained patch matching to build dense correspondence between image pairs. (2) We propose two alternative methods, i.e. K-Nearest Neighbors and One-class SVM, to estimate a saliency score for each image patch, through which distinctive features stand out without using identity labels in the training procedure. (3) saliency matching is proposed based on patch matching. Matching patches with inconsistent saliency brings penalty, and images of the same identity are recognized by minimizing the saliency matching cost. (4) Furthermore, saliency matching is tightly integrated with patch matching in a unified structural RankSVM learning framework. The effectiveness of our approach is validated on the VIPeR dataset and the CUHK01 dataset. Our approach outperforms the state-of-the-art person re-identification methods on both datasets.
Towards Defeating the Crossfire Attack using SDN
Venue: arXiv cs.NI 2014
Year: 2014

In this work, we propose online traffic engineering as a novel approach to detect and mitigate an emerging class of stealthy Denial of Service (DoS) link-flooding attacks. Our approach exploits the Software Defined Networking (SDN) paradigm, which renders the management of network traffic more flexible through centralised flow-level control and monitoring. We implement a full prototype of our solution on an emulated SDN environment using OpenFlow to interface with the network devices. We further discuss useful insights gained from our preliminary experiments as well as a number of open research questions which constitute work in progress.
An algorithm for improving Non-Local Means operators via low-rank approximation
Venue: arXiv cs.CV 2014
Year: 2014

We present a method for improving a Non Local Means operator by computing its low-rank approximation. The low-rank operator is constructed by applying a filter to the spectrum of the original Non Local Means operator. This results in an operator which is less sensitive to noise while preserving important properties of the original operator. The method is efficiently implemented based on Chebyshev polynomials and is demonstrated on the application of natural images denoising. For this application, we provide a comprehensive comparison of our method with leading denoising methods.
The myth of the Digital Earth between fragmentation and wholeness
Venue: arXiv cs.CY 2014
Year: 2014

Daring predictions of the proximate future can establish shared discursive frameworks, mobilize capital, and steer complex processes. Among the prophetic visions that encouraged and accompanied the development of new communication technologies was the "Digital Earth," described in a 1998 speech by Al Gore as a high-resolution representation of the planet to share and analyze detailed information about its state. This article traces a genealogy of the Digital Earth as a techno-scientific myth, locating it in a constellation of media futures, arguing that a common subtext of these envisionments consists of a dream of wholeness, an afflatus to overcome perceived fragmentation among humans, and between humans and the Earth.
Distributed Multi-Depot Routing without Communications
Venue: arXiv cs.DC 2014
Year: 2014

We consider and formulate a class of distributed multi-depot routing problems, where servers are to visit a set of requests, with the aim of minimizing the total distance travelled by all servers. These problems fall into two categories: distributed offline routing problems where all the requests that need to be visited are known from the start; distributed online routing problems where the requests come to be known incrementally. A critical and novel feature of our formulations is that communications are not allowed among the servers, hence posing an interesting and challenging question: what performance can be achieved in comparison to the best possible solution obtained from an omniscience planner with perfect communication capabilities? The worst-case (over all possible request-set instances) performance metrics are given by the approximation ratio (offline case) and the competitive ratio (online case). Our first result indicates that the online and offline problems are effectively equivalent: for the same request-set instance, the approximation ratio and the competitive ratio differ by at most an additive factor of 2, irrespective of the release dates in the online case. Therefore, we can restrict our attention to the offline problem. For the offline problem, we show that the approximation ratio given by the Voronoi partition is m (the number of servers). For two classes of depot configurations, when the depots form a line and when the ratios between the distances of pairs of depots are upper bounded by a sublinear function f(m) (i.e., f(m) = o(m)), we give partition schemes with sublinear approximation ratios O(log m) and Θ(f(m)) respectively. We also discuss several interesting open problems in our formulations: in particular, how our initial results (on the two deliberately chosen classes of depots) shape our conjecture on the open problems.
Using Artificial Neural Network Techniques for Prediction of Electric Energy Consumption
Venue: arXiv cs.NE 2014
Year: 2014

Due to imprecision and uncertainties in predicting real world problems, artificial neural network (ANN) techniques have become increasingly useful for modeling and optimization. This paper presents an artificial neural network approach for forecasting electric energy consumption. For effective planning and operation of power systems, optimal forecasting tools are needed for energy operators to maximize profit and also to provide maximum satisfaction to energy consumers. Monthly data for electric energy consumed in the Gaza strip was collected from year 1994 to 2013. Data was trained and the proposed model was validated using 2-Fold and K-Fold cross validation techniques. The model has been tested with actual energy consumption data and yields satisfactory performance.
Predicting Node Degree Centrality with the Node Prominence Profile
Venue: arXiv cs.SI 2014
Year: 2014

Centrality of a node measures its relative importance within a network. There are a number of applications of centrality, including inferring the influence or success of an individual in a social network, and the resulting social network dynamics. While we can compute the centrality of any node in a given network snapshot, a number of applications are also interested in knowing the potential importance of an individual in the future. However, current centrality is not necessarily an effective predictor of future centrality. While there are different measures of centrality, we focus on degree centrality in this paper. We develop a method that reconciles preferential attachment and triadic closure to capture a node's prominence profile. We show that the proposed node prominence profile method is an effective predictor of degree centrality. Notably, our analysis reveals that individuals in the early stage of evolution display a distinctive and robust signature in degree centrality trend, adequately predicted by their prominence profile. We evaluate our work across four real-world social networks. Our findings have important implications for the applications that require prediction of a node's future degree centrality, as well as the study of social network dynamics.
End-to-End Reliability-aware Scheduling for Wireless Sensor Networks
Venue: arXiv cs.NI 2014
Year: 2014

Wireless Sensor Networks (WSN) are gaining popularity as a flexible and economical alternative to field-bus installations for monitoring and control applications. For mission-critical applications, communication networks must provide end-to-end reliability guarantees, posing substantial challenges for WSN. Reliability can be improved by redundancy, and is often addressed on the MAC layer by re-submission of lost packets, usually applying slotted scheduling. Recently, researchers have proposed a strategy to optimally improve the reliability of a given schedule by repeating the most rewarding slots in a schedule incrementally until a deadline. This Incrementer can be used with most scheduling algorithms but has scalability issues which narrows its usability to offline calculations of schedules, for networks that are rather static. In this paper, we introduce SchedEx, a generic heuristic scheduling algorithm extension which guarantees a user-defined end-to-end reliability. SchedEx produces competitive schedules to the existing approach, and it does that consistently more than an order of magnitude faster. The harsher the end-to-end reliability demand of the network, the better SchedEx performs compared to the Incrementer. We further show that SchedEx has a more evenly distributed improvement impact on the scheduling algorithms, whereas the Incrementer favors schedules created by certain scheduling algorithms.
The Gain of Network Coding in Wireless Sensor Networking
Venue: arXiv cs.NI 2014
Year: 2014

Wireless Sensor Networks have some well known features such as low battery consumption, changing topology awareness, open environment, non reliable radio links, etc.In this paper, we investigate the benefits of Network Coding Wireless Sensor networking, especially resiliency.One of our main concern is the resiliency in Wireless Sensor Networks.We have seen that resiliency could be described as a multi dimensional metric \cite{5478822,erdene2011enhancing,6423640} taking parameters such as Average Delivery Ratio, Delay Efficiency, Energy Efficiency, Average Throughput and Delivery Fairness into account.Resiliency can then be graphically represented as a kiviat diagram created by the previous weighted parameters.In order to introduce these metrics, previous works have been leaded on the Random Gradient Based Routing, which proved good resiliency in malicious environment.We look for seeing the improvements in term of resiliency, when adding network coding in the Random Gradient Based Routing with malicious nodes.
Integrating goals after prioritization and evaluation-A Goal-oriented requirements engineering method
Venue: arXiv cs.SE 2014
Year: 2014

Decision support system in Requirements engineering plays an important role in software development life cycle. The relationship between functional and non-functional requirements often plays a crucial role in resolving conflicts or arriving at decisions in requirements engineering phase. Goal-Oriented Requirements Engineering (GORE) methods make a good attempt of addressing these aspects which are helpful in decision support. We propose a GORE method - Integrating goals after prioritization and evaluation (IGAPE). The method is semi-formal in nature thereby ensuring active stakeholder participation. In this paper we elaborate the various steps of IGAPE method. The output of IGAPE is then given as input to a decision support system which makes use of Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Integration of IGAPE with AHP and TOPSIS will clearly provide a rationale for various decisions which are arrived at during the requirements engineering phase. The method is illustrated for an e-commerce application and is validated by expert analysis approach.
Impact of User Pairing on 5G Non-Orthogonal Multiple Access
Venue: arXiv cs.IT 2014
Year: 2014

Non-orthogonal multiple access (NOMA) represents a paradigm shift from conventional orthogonal multiple access (MA) concepts, and has been recognized as one of the key enabling technologies for 5G systems. In this paper, the impact of user pairing on the performance of two NOMA systems, NOMA with fixed power allocation (F-NOMA) and cognitive radio inspired NOMA (CR-NOMA), is characterized. For FNOMA, both analytical and numerical results are provided to demonstrate that F-NOMA can offer a larger sum rate than orthogonal MA, and the performance gain of F-NOMA over conventional MA can be further enlarged by selecting users whose channel conditions are more distinctive. For CR-NOMA, the quality of service (QoS) for users with the poorer channel condition can be guaranteed since the transmit power allocated to other users is constrained following the concept of cognitive radio networks. Because of this constraint, CR-NOMA has different behavior compared to F-NOMA. For example, for the user with the best channel condition, CR-NOMA prefers to pair it with the user with the second best channel condition, whereas the user with the worst channel condition is preferred by F-NOMA.
Performance Enhancement of Routers in Networks-on-Chip Using Dynamic Virtual Channels Allocation
Venue: arXiv cs.AR 2014
Year: 2014

This study proposes a new router architecture to improve the performance of dynamic allocation of virtual channels. The proposed router is designed to reduce the hardware complexity and to improve power and area consumption, simultaneously. In the new structure of the proposed router, all of the controlling components have been implemented sequentially inside the allocator router modules. This optimizes communications between the controlling components and eliminates the most of hardware overloads of modular communications. Eliminating additional communications also reduces the hardware complexity. In order to show the validity of the proposed design in real hardware resources, the proposed router has been implemented onto a Field-Programmable Gate Array (FPGA). Since the implementation of a Network-on-Chip (NoC) requires certain amount of area on the chip, the suggested approach is also able to reduce the demand of hardware resources. In this method, the internal memory of the FPGA is used for implementing control units. This memory is faster and can be used with specific patterns. The use of the FPGA memory saves the hardware resources and allows the implementation of NoC based FPGA.
Integrating Heterogeneous Building and Periphery Data Models at the District Level: The NIM Approach
Venue: arXiv cs.SE 2014
Year: 2014

Integrating existing heterogeneous data models for buildings, neighbourhoods and periphery devices into a common data model that can be used by all participants, such as users, services or sensors is a cumbersome task. Usually new extended standards emerge or ontologies are used to define mappings between concrete data models. Within the COOPERaTE project a neighbourhood information model (NIM) has been developed to address interoperability and allow for various kinds of data to be stored and exchanged. The implementation of the NIM follows a meta model based approach, allowing for runtime extension and for easily integrating heterogeneous data models via a mapping DSL and code generation of adaptation components.
Algorithmic Rationality: Game Theory with Costly Computation
Venue: arXiv cs.GT 2014
Year: 2014

We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer hold. Nevertheless, we can use the framework to provide psychologically appealing explanations of observed behavior in well-studied games (such as finitely repeated prisoner's dilemma and rock-paper-scissors). Furthermore, we provide natural conditions on games sufficient to guarantee that equilibria exist.
Fast Product-Matrix Regenerating Codes
Venue: arXiv cs.DC 2014
Year: 2014

Distributed storage systems support failures of individual devices by the use of replication or erasure correcting codes. While erasure correcting codes offer a better storage efficiency than replication for similar fault tolerance, they incur higher CPU consumption, higher network consumption and higher disk I/Os. To address these issues, codes specific to storage systems have been designed. Their main feature is the ability to repair a single lost disk efficiently. In this paper, we focus on one such class of codes that minimize network consumption during repair, namely regenerating codes. We implement the original Product-Matrix Regenerating codes as well as a new optimization we propose and show that the resulting optimized codes allow achieving 790 MB/s for encoding in typical settings. Reported speeds are significantly higher than previous studies, highlighting that regenerating codes can be used with little CPU penalty.
Road Detection via On--line Label Transfer
Venue: arXiv cs.CV 2014
Year: 2014

Vision-based road detection is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. The major challenges of road detection are dealing with shadows and lighting variations and the presence of other objects in the scene. Current road detection algorithms characterize road areas at pixel level and group pixels accordingly. However, these algorithms fail in presence of strong shadows and lighting variations. Therefore, we propose a road detection algorithm based on video alignment. The key idea of the algorithm is to exploit the similarities occurred when a vehicle follows the same trajectory more than once. In this way, road areas are learned in a first ride and then, this road knowledge is used to infer areas depicting drivable road surfaces in subsequent rides. Two different experiments are conducted to validate the proposal on different video sequences taken at different scenarios and different daytime. The former aims to perform on-line road detection. The latter aims to perform off-line road detection and is applied to automatically generate the ground-truth necessary to validate road detection algorithms. Qualitative and quantitative evaluations prove that the proposed algorithm is a valid road detection approach.
Bach in 2014: Music Composition with Recurrent Neural Network
Venue: arXiv cs.AI 2014
Year: 2014

We propose a framework for computer music composition that uses resilient propagation (RProp) and long short term memory (LSTM) recurrent neural network. In this paper, we show that LSTM network learns the structure and characteristics of music pieces properly by demonstrating its ability to recreate music. We also show that predicting existing music using RProp outperforms Back propagation through time (BPTT).
Uniformity is weaker than semi-uniformity for some membrane systems
Venue: arXiv cs.CC 2014
Year: 2014

We investigate computing models that are presented as families of finite computing devices with a uniformity condition on the entire family. Examples of such models include Boolean circuits, membrane systems, DNA computers, chemical reaction networks and tile assembly systems, and there are many others. However, in such models there are actually two distinct kinds of uniformity condition. The first is the most common and well-understood, where each input length is mapped to a single computing device (e.g. a Boolean circuit) that computes on the finite set of inputs of that length. The second, called semi-uniformity, is where each input is mapped to a computing device for that input (e.g. a circuit with the input encoded as constants). The former notion is well-known and used in Boolean circuit complexity, while the latter notion is frequently found in literature on nature-inspired computation from the past 20 years or so. Are these two notions distinct? For many models it has been found that these notions are in fact the same, in the sense that the choice of uniformity or semi-uniformity leads to characterisations of the same complexity classes. In other related work, we showed that these notions are actually distinct for certain classes of Boolean circuits. Here, we give analogous results for membrane systems by showing that certain classes of uniform membrane systems are strictly weaker than the analogous semi-uniform classes. This solves a known open problem in the theory of membrane systems. We then go on to present results towards characterising the power of these semi-uniform and uniform membrane models in terms of NL and languages reducible to the unary languages in NL, respectively.
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Venue: arXiv cs.NE 2014
Year: 2014

In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long short-term memory (LSTM) unit and a recently proposed gated recurrent unit (GRU). We evaluate these recurrent units on the tasks of polyphonic music modeling and speech signal modeling. Our experiments revealed that these advanced recurrent units are indeed better than more traditional recurrent units such as tanh units. Also, we found GRU to be comparable to LSTM.
Call Admission Control based on Adaptive Bandwidth Allocation for Wireless Networks
Venue: arXiv cs.MM 2014
Year: 2014

Provisioning of Quality of Service (QoS) is a key issue in any multi-media system. However, in wireless systems, supporting QoS requirements of different traffic types is more challenging due to the need to minimize two performance metrics - the probability of dropping a handover call and the probability of blocking a new call. Since QoS requirements are not as stringent for non-real-time traffic types, as opposed to real-time traffic, more calls can be accommodated by releasing some bandwidth from the already admitted non-real-time traffic calls. If we require that such a released bandwidth to accept a handover call ought to be larger than the bandwidth to accept a new call, then the resulting probability of dropping a handover call will be smaller than the probability of blocking a new call. In this paper we propose an efficient Call Admission Control (CAC) that relies on adaptive multi-level bandwidth-allocation scheme for non-real-time calls. The scheme allows reduction of the call dropping probability along with increase of the bandwidth utilization. The numerical results show that the proposed scheme is capable of attaining negligible handover call dropping probability without sacrificing bandwidth utilization.
Run-Length Encoded Nondeterministic KMP and Suffix Automata
Venue: arXiv cs.FL 2014
Year: 2014

We present a novel bit-parallel representation, based on the run-length encoding, of the nondeterministic KMP and suffix automata for a string $P$ with at least two distinct symbols. Our method is targeted to the case of long strings over small alphabets and complements the method of Cantone et al. (2012), which is effective for long strings over large alphabets. Our encoding requires $O((σ+ m)\lceil ρ/ w\rceil)$ space and allows one to simulate the automata on a string in time $O(\lceil ρ/ w\rceil)$ per transition, where $σ$ is the alphabet size, $m$ is the length of $P$, $ρ$ is the length of the run-length encoding of $P$ and $w$ is the machine word size in bits. The input string can be given in either unencoded or run-length encoded form.