OpenRaiser/Intern-Atlas huggingface dataset:
An Intelligent Approach for Dense Urban Area in existing 2G / 2.5G
Venue: arXiv cs.CY 2012
Year: 2012

In the prevailing scenario audio, video, data services (i.e. internet), multimedia and broadcasting etc. are being integrated. Decreasing cell size increases capacity but at the same time increases fluctuation and interference too. The intelligence approach is the only answer in developing countries where frequency and power are scarce resources. In this paper, we have tried to integrate all proven technologies in networking such as in-building network, micro zone, intelligent micro cell, deployment along city streets, tunnels, subway coverage etc. along with adaptive frequency allocation in hierarchical approach with the help of adaptive / intelligent antenna system. A-SDMA approach will further enhance spectral efficiency as well as QoS (Quality of Service). It can be proved beyond doubt that this integrated approach will convert 2G / 2.5G systems capable of handling the prevailing demand at reduced cost. In addition to it, integrated approach will save power and reduce RF pollution. In this paper we have explained the ill effect of cellular growth in terms of health hazard and increased power consumption. We have also suggested ways and means to overcome these problems (spectral density / capacity, QoS, power consumption and RF pollution etc.).
Image-based Vehicle Classification System
Venue: arXiv cs.CV 2012
Year: 2012

Electronic toll collection (ETC) system has been a common trend used for toll collection on toll road nowadays. The implementation of electronic toll collection allows vehicles to travel at low or full speed during the toll payment, which help to avoid the traffic delay at toll road. One of the major components of an electronic toll collection is the automatic vehicle detection and classification (AVDC) system which is important to classify the vehicle so that the toll is charged according to the vehicle classes. Vision-based vehicle classification system is one type of vehicle classification system which adopt camera as the input sensing device for the system. This type of system has advantage over the rest for it is cost efficient as low cost camera is used. The implementation of vision-based vehicle classification system requires lower initial investment cost and very suitable for the toll collection trend migration in Malaysia from single ETC system to full-scale multi-lane free flow (MLFF). This project includes the development of an image-based vehicle classification system as an effort to seek for a robust vision-based vehicle classification system. The techniques used in the system include scale-invariant feature transform (SIFT) technique, Canny's edge detector, K-means clustering as well as Euclidean distance matching. In this project, a unique way to image description as matching medium is proposed. This distinctiveness of method is analogous to the human DNA concept which is highly unique. The system is evaluated on open datasets and return promising results.
Affine Image Registration Transformation Estimation Using a Real Coded Genetic Algorithm with SBX
Venue: arXiv cs.NE 2012
Year: 2012

This paper describes the application of a real coded genetic algorithm (GA) to align two or more 2-D images by means of image registration. The proposed search strategy is a transformation parameters-based approach involving the affine transform. The real coded GA uses Simulated Binary Crossover (SBX), a parent-centric recombination operator that has shown to deliver a good performance in many optimization problems in the continuous domain. In addition, we propose a new technique for matching points between a warped and static images by using a randomized ordering when visiting the points during the matching procedure. This new technique makes the evaluation of the objective function somewhat noisy, but GAs and other population-based search algorithms have been shown to cope well with noisy fitness evaluations. The results obtained are competitive to those obtained by state-of-the-art classical methods in image registration, confirming the usefulness of the proposed noisy objective function and the suitability of SBX as a recombination operator for this type of problem.
A model-driven approach for processing complex events
Venue: arXiv cs.SE 2012
Year: 2012

By adequate employing of complex event processing (CEP), valuable information can be extracted from the underlying complex system and used in controlling and decision situations. An example application area is management of IT systems for maintaining required dependability attributes of services based on the infrastructure. In practice, one usually faces the problem of the vast number of distributed event sources, which makes depicting complex event patterns a non-trivial task. In this paper, I present a novel, model-driven approach to define complex event patterns and directly generate event processing configuration for an open source CEP engine widely used in the industry. One of the key results of my research work is a textual modeling language called Complex Event Description Language (CEDL), which will be presented by its algebraic semantics and some typical examples.
Programming Cloud Resource Orchestration Framework: Operations and Research Challenges
Venue: arXiv cs.DC 2012
Year: 2012

The emergence of cloud computing over the past five years is potentially one of the breakthrough advances in the history of computing. It delivers hardware and software resources as virtualization-enabled services and in which administrators are free from the burden of worrying about the low level implementation or system administration details. Although cloud computing offers considerable opportunities for the users (e.g. application developers, governments, new startups, administrators, consultants, scientists, business analyst, etc.) such as no up-front investment, lowering operating cost, and infinite scalability, it has many unique research challenges that need to be carefully addressed in the future. In this paper, we present a survey on key cloud computing concepts, resource abstractions, and programming operations for orchestrating resources and associated research challenges, wherever applicable.
Decoder for Nonbinary CWS Quantum Codes
Venue: arXiv cs.IT 2012
Year: 2012

We present a decoder for nonbinary CWS quantum codes using the structure of union codes. The decoder runs in two steps: first we use a union of stabilizer codes to detect a sequence of errors, and second we build a new code, called union code, that allows to correct the errors.
Vie Physarale: Evaluation of Roman roads with slime mould
Venue: arXiv cs.CG 2012
Year: 2012

Roman Empire is renowned for sharp logical design and outstanding building quality of its road system. Many roads built by Romans are still use in continental Europe and UK. The Roman roads were built for military transportations with efficiency in mind, as straight as possible. Thus the roads make an ideal test-bed for developing experimental laboratory techniques for evaluating man-made transport systems using living creatures. We imitate development of road networks in Iron Age Italy using slime mould Physarum polycephalum. We represent ten Roman cities with oat flakes, inoculate the slime mould in Roma, wait till slime mould spans all flakes-cities with its network of protoplasmic tubes, and analyse structures of the protoplasmic networks. We found that most Roman roads, apart of those linking Placentia to Bononia and Genua to Florenzia are represented in development of Physarum polycephalum. Transport networks developed by Romans and by slime mould show strong affinity of planar proximity graphs, and particular minimum spanning tree. Based on laboratory experiments we reconstructed a speculative sequence of road development in Iron Age Italy.
Robust Nonnegative Matrix Factorization via $L_1$ Norm Regularization
Venue: arXiv cs.LG 2012
Year: 2012

Nonnegative Matrix Factorization (NMF) is a widely used technique in many applications such as face recognition, motion segmentation, etc. It approximates the nonnegative data in an original high dimensional space with a linear representation in a low dimensional space by using the product of two nonnegative matrices. In many applications data are often partially corrupted with large additive noise. When the positions of noise are known, some existing variants of NMF can be applied by treating these corrupted entries as missing values. However, the positions are often unknown in many real world applications, which prevents the usage of traditional NMF or other existing variants of NMF. This paper proposes a Robust Nonnegative Matrix Factorization (RobustNMF) algorithm that explicitly models the partial corruption as large additive noise without requiring the information of positions of noise. In practice, large additive noise can be used to model outliers. In particular, the proposed method jointly approximates the clean data matrix with the product of two nonnegative matrices and estimates the positions and values of outliers/noise. An efficient iterative optimization algorithm with a solid theoretical justification has been proposed to learn the desired matrix factorization. Experimental results demonstrate the advantages of the proposed algorithm.
Energy Efficient Geographical Load Balancing via Dynamic Deferral of Workload
Venue: arXiv cs.NI 2012
Year: 2012

With the increasing popularity of Cloud computing and Mobile computing, individuals, enterprises and research centers have started outsourcing their IT and computational needs to on-demand cloud services. Recently geographical load balancing techniques have been suggested for data centers hosting cloud computation in order to reduce energy cost by exploiting the electricity price differences across regions. However, these algorithms do not draw distinction among diverse requirements for responsiveness across various workloads. In this paper, we use the flexibility from the Service Level Agreements (SLAs) to differentiate among workloads under bounded latency requirements and propose a novel approach for cost savings for geographical load balancing. We investigate how much workload to be executed in each data center and how much workload to be delayed and migrated to other data centers for energy saving while meeting deadlines. We present an offline formulation for geographical load balancing problem with dynamic deferral and give online algorithms to determine the assignment of workload to the data centers and the migration of workload between data centers in order to adapt with dynamic electricity price changes. We compare our algorithms with the greedy approach and show that significant cost savings can be achieved by migration of workload and dynamic deferral with future electricity price prediction. We validate our algorithms on MapReduce traces and show that geographic load balancing with dynamic deferral can provide 20-30% cost-savings.
Introducing convex layers to the Traveling Salesman Problem
Venue: arXiv cs.OH 2012
Year: 2012

In this paper, we will propose convex layers to the Traveling Salesman Problem (TSP). Firstly, we will focus on human performance on the TSP. Experimental data shows that untrained humans appear to have the ability to perform well in the TSP. On the other hand, experimental data also supports the hypothesis of convex hull i.e. human relies on convex hull to search for the optimal tour for the TSP. Secondly, from the paper published by Bonabeau, Dorigo and Theraulaz, social insect behavior would be able to help in some of the optimizing problems, especially the TSP. Thus, we propose convex layers to the TSP based on the argument that, by the analogy to the social insect behavior, untrained humans' cognition should be able to help in the TSP. Lastly, we will use Tour Improvement algorithms on convex layers to search for an optimal tour for a 13-cities problem to demonstrate the idea.
Decode-and-Forward Based Differential Modulation for Cooperative Communication System with Unitary and Non-Unitary Constellations
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we derive a maximum likelihood (ML) decoder of the differential data in a decode-and-forward (DF) based cooperative communication system utilizing uncoded transmissions. This decoder is applicable to complex-valued unitary and non-unitary constellations suitable for differential modulation. The ML decoder helps in improving the diversity of the DF based differential cooperative system using an erroneous relaying node. We also derive a piecewise linear (PL) decoder of the differential data transmitted in the DF based cooperative system. The proposed PL decoder significantly reduces the decoding complexity as compared to the proposed ML decoder without any significant degradation in the receiver performance. Existing ML and PL decoders of the differentially modulated uncoded data in the DF based cooperative communication system are only applicable to binary modulated signals like binary phase shift keying (BPSK) and binary frequency shift keying (BFSK), whereas, the proposed decoders are applicable to complex-valued unitary and non-unitary constellations suitable for differential modulation under uncoded transmissions. We derive a closedform expression of the uncoded average symbol error rate (SER) of the proposed PL decoder with M-PSK constellation in a cooperative communication system with a single relay and one source-destination pair. An approximate average SER by ignoring higher order noise terms is also derived for this set-up. It is analytically shown on the basis of the derived approximate SER that the proposed PL decoder provides full diversity of second order. In addition, we also derive approximate SER of the differential DF system with multiple relays at asymptotically high signal-to-noise ratio of the source-relay links.
Physical Unclonable Function (PUF) Based Random Number Generator
Venue: arXiv cs.CR 2012
Year: 2012

Physical Unclonable Functions (PUFs) are widely used to generate random Numbers. In this paper we propose a new architecture in which an Arbiter Based PUF has been employed as a nonlinear function in Nonlinear Feedback Shift Register (NFSR) to generate true random numbers. The rate of producing the output bit streams is 10 million bits per second. The proposed RNG is able to pass all NIST tests and the entropy of the output stream is 7.999837 bits per byte. The proposed circuit has very low resource usage of 193 Slices that makes it suitable for lightweight applications.
Synthesising Choreographies from Local Session Types (extended version)
Venue: arXiv cs.PL 2012
Year: 2012

Designing and analysing multiparty distributed interactions can be achieved either by means of a global view (e.g. in choreography-based approaches) or by composing available computational entities (e.g. in service orchestration). This paper proposes a typing systems which allows, under some conditions, to synthesise a choreography (i.e. a multiparty global type) from a set of local session types which describe end-point behaviours (i.e. local types).
Modeling Relational Data via Latent Factor Blockmodel
Venue: arXiv cs.DS 2012
Year: 2012

In this paper we address the problem of modeling relational data, which appear in many applications such as social network analysis, recommender systems and bioinformatics. Previous studies either consider latent feature based models but disregarding local structure in the network, or focus exclusively on capturing local structure of objects based on latent blockmodels without coupling with latent characteristics of objects. To combine the benefits of the previous work, we propose a novel model that can simultaneously incorporate the effect of latent features and covariates if any, as well as the effect of latent structure that may exist in the data. To achieve this, we model the relation graph as a function of both latent feature factors and latent cluster memberships of objects to collectively discover globally predictive intrinsic properties of objects and capture latent block structure in the network to improve prediction performance. We also develop an optimization transfer algorithm based on the generalized EM-style strategy to learn the latent factors. We prove the efficacy of our proposed model through the link prediction task and cluster analysis task, and extensive experiments on the synthetic data and several real world datasets suggest that our proposed LFBM model outperforms the other state of the art approaches in the evaluated tasks.
An efficient solver for volumetric scattering based on fast spherical harmonics transforms
Venue: arXiv cs.NA 2012
Year: 2012

The Helmholtz equation arises in the study of electromagnetic radiation, optics, acoustics, etc. In spherical coordinates, its general solution can be written as a spherical harmonic series which satisfies the radiation condition at infinity, ensuring that the wave is outgoing. The boundary condition at infinity is hard to enforce with a finite element method since a suitable approximation needs to be made within reasonable distance from scatterers. Luckily, the Helmholtz equation can be represented as a Lippmann-Schwinger integral equation which removes the necessity of the boundary approximations and its Green's function can be expanded as a spherical harmonic series which leads to our numerical scheme based on spherical harmonic polynomial transform. In this paper, we present an efficient solver for the Helmholtz equation which costs $O(N\log N)$ operations, where $N$ is the number of the discretization points. We use the fast spherical harmonic transforms which are originally developed in \cite{suda}. The convergence order of the method is tied to the global regularity of the solution. At the lower end, it is second order accurate for discontinuous material properties. The order increases with increasing regularity leading to spectral convergence for globally smooth solutions.
Application Independent Energy Efficient Data Aggregation in Wireless Sensor Networks
Venue: arXiv cs.NI 2012
Year: 2012

Wireless Sensor networks are dense networks of small, low-cost sensors, which collect and disseminate environmental data and thus facilitate monitoring and controlling of physical environment from remote locations with better accuracy. The major challenge is to achieve energy efficiency during the communication among the nodes. This paper aims at proposing a solution to schedule the node's activities to reduce the energy consumption. We propose the construction of a decentralized lifetime maximizing tree within clusters. We aim at minimizing the distance of transmission with minimization of energy consumption. The sensor network is distributed into clusters based on the close proximity of the nodes. Data transfer among the nodes is done with a hybrid technique of both TDMA/ FDMA which leads to efficient utilization of bandwidth and maximizing throughput.
Solution regions in the parameter space of a 3-RRR decoupled robot for a prescribed workspace
Venue: arXiv cs.RO 2012
Year: 2012

This paper proposes a new design method to determine the feasible set of parameters of translational or position/orientation decoupled parallel robots for a prescribed singularity-free workspace of regular shape. The suggested method uses Groebner bases to define the singularities and the cylindrical algebraic decomposition to characterize the set of parameters. It makes it possible to generate all the robot designs. A 3-RRR decoupled robot is used to validate the proposed design method.
Cooperative Cognitive Networks: Optimal, Distributed and Low-Complexity Algorithms
Venue: arXiv cs.IT 2012
Year: 2012

This paper considers the cooperation between a cognitive system and a primary system where multiple cognitive base stations (CBSs) relay the primary user's (PU) signals in exchange for more opportunity to transmit their own signals. The CBSs use amplify-and-forward (AF) relaying and coordinated beamforming to relay the primary signals and transmit their own signals. The objective is to minimize the overall transmit power of the CBSs given the rate requirements of the PU and the cognitive users (CUs). We show that the relaying matrices have unit rank and perform two functions: Matched filter receive beamforming and transmit beamforming. We then develop two efficient algorithms to find the optimal solution. The first one has linear convergence rate and is suitable for distributed implementation, while the second one enjoys superlinear convergence but requires centralized processing. Further, we derive the beamforming vectors for the linear conventional zero-forcing (CZF) and prior zero-forcing (PZF) schemes, which provide much simpler solutions. Simulation results demonstrate the improvement in terms of outage performance due to the cooperation between the primary and cognitive systems.
Effect of Thread Level Parallelism on the Performance of Optimum Architecture for Embedded Applications
Venue: arXiv cs.AR 2012
Year: 2012

According to the increasing complexity of network application and internet traffic, network processor as a subset of embedded processors have to process more computation intensive tasks. By scaling down the feature size and emersion of chip multiprocessors (CMP) that are usually multi-thread processors, the performance requirements are somehow guaranteed. As multithread processors are the heir of uni-thread processors and there isn't any general design flow to design a multithread embedded processor, in this paper we perform a comprehensive design space exploration for an optimum uni-thread embedded processor based on the limited area and power budgets. Finally we run multiple threads on this architecture to find out the maximum thread level parallelism (TLP) based on performance per power and area optimum uni-thread architecture.
Watersheds, waterfalls, on edge or node weighted graphs
Venue: arXiv cs.CV 2012
Year: 2012

We present an algebraic approach to the watershed adapted to edge or node weighted graphs. Starting with the flooding adjunction, we introduce the flooding graphs, for which node and edge weights may be deduced one from the other. Each node weighted or edge weighted graph may be transformed in a flooding graph, showing that there is no superiority in using one or the other, both being equivalent. We then introduce pruning operators extract subgraphs of increasing steepness. For an increasing steepness, the number of never ascending paths becomes smaller and smaller. This reduces the watershed zone, where catchment basins overlap. A last pruning operator called scissor associates to each node outside the regional minima one and only one edge. The catchment basins of this new graph do not overlap and form a watershed partition. Again, with an increasing steepness, the number of distinct watershed partitions contained in a graph becomes smaller and smaller. Ultimately, for natural image, an infinite steepness leads to a unique solution, as it is not likely that two absolutely identical non ascending paths of infinite steepness connect a node with two distinct minima. It happens that non ascending paths of a given steepness are the geodesics of lexicographic distance functions of a given depth. This permits to extract the watershed partitions as skeletons by zone of influence of the minima for such lexicographic distances. The waterfall hierarchy is obtained by a sequence of operations. The first constructs the minimum spanning forest which spans an initial watershed partition. The contraction of the trees into one node produces a reduced graph which may be submitted to the same treatment. The process is iterated until only one region remains. The union of the edges of all forests produced constitutes a minimum spanning tree of the initial graph.