OpenRaiser/Intern-Atlas huggingface dataset:
Distributed Denial of Service (DDoS) Attacks Detection Mechanism
Venue: arXiv cs.CR 2012
Year: 2012

Pushback is a mechanism for defending against Distributed Denial-of-Service (DDoS) attacks. DDoS attacks are treated as a congestion-control problem, but because most such congestion is caused by malicious hosts not obeying traditional end-to-end congestion control, the problem must be handled by the routers. Functionality is added to each router to detect and preferentially drop packets that probably belong to an attack. Upstream routers are also notified to drop such packets in order that the router's resources be used to route legitimate traffic hence term pushback. Client puzzles have been advocated as a promising countermeasure to DoS attacks in the recent years. In order to identify the attackers, the victim server issues a puzzle to the client that sent the traffic. When the client is able to solve the puzzle, it is assumed to be authentic and the traffic from it is allowed into the server. If the victim suspects that the puzzles are solved by most of the clients, it increases the complexity of the puzzles. This puzzle solving technique allows the traversal of the attack traffic throughout the intermediate routers before reaching the destination. In order to attain the advantages of both pushback and puzzle solving techniques, a hybrid scheme called Router based Pushback technique, which involves both the techniques to solve the problem of DDoS attacks is proposed. In this proposal, the puzzle solving mechanism is pushed back to the core routers rather than having at the victim. The router based client puzzle mechanism checks the host system whether it is legitimate or not by providing a puzzle to be solved by the suspected host.
A New Full Adder Cell for Molecular Electronics
Venue: arXiv cs.ET 2012
Year: 2012

Due to high power consumption and difficulties with minimizing the CMOS transistor size, molecular electronics has been introduced as an emerging technology. Further, there have been noticeable advances in fabrication of molecular wires and switches and also molecular diodes can be used for designing different logic circuits. Considering this novel technology, we use molecules as the active components of the circuit, for transporting electric charge. In this paper, a full adder cell based on molecular electronics is presented. This full adder is consisted of resonant tunneling diodes and transistors which are implemented via molecular electronics. The area occupied by this kind of full adder would be much times smaller than the conventional designs and it can be used as the building block of more complex molecular arithmetic circuits.
Biologically inspired design framework for Robot in Dynamic Environments using Framsticks
Venue: arXiv cs.NE 2012
Year: 2012

Robot design complexity is increasing day by day especially in automated industries. In this paper we propose biologically inspired design framework for robots in dynamic world on the basis of Co-Evolution, Virtual Ecology, Life time learning which are derived from biological creatures. We have created a virtual khepera robot in Framsticks and tested its operational credibility in terms hardware and software components by applying the above suggested techniques. Monitoring complex and non complex behaviors in different environments and obtaining the parameters that influence software and hardware design of the robot that influence anticipated and unanticipated failures, control programs of robot generation are the major concerns of our techniques.
Design and ASIC implementation of DUC/DDC for communication systems
Venue: arXiv cs.AR 2012
Year: 2012

Communication systems use the concept of transmitting information using the electrical distribution network as a communication channel. To enable the transmission data signal modulated on a carrier signal is superimposed on the electrical wires. Typical power lines are designed to handle 50/60 Hz of AC power signal; however they can carry the signals up to 500 KHz frequency. This work aims to aid transmission/reception of an audio signal in the spectrum from 300 Hz to 4000 Hz using PLCC on a tunable carrier frequency in the spectrum from 200 KHz to 500 KHz. For digital amplitude modulation the sampling rate of the carrier and the audio signal has to be matched. Tunable carrier generation can be achieved with Direct Digital Synthesizers at a desired sampling rate. DSP Sample rate conversion techniques are very useful to make the sampling circuits to work on their own sampling rates which are fine for the data/modulated-carrier signal's bandwidth. This also simplifies the complexity of the sampling circuits. Digital Up Conversion (DUC) and Digital Down Conversion (DDC) are DSP sample rate conversion techniques which refer to increasing and decreasing the sampling rate of a signal respectively.
Purging of untrustworthy recommendations from a grid
Venue: arXiv cs.DC 2012
Year: 2012

In grid computing, trust has massive significance. There is lot of research to propose various models in providing trusted resource sharing mechanisms. The trust is a belief or perception that various researchers have tried to correlate with some computational model. Trust on any entity can be direct or indirect. Direct trust is the impact of either first impression over the entity or acquired during some direct interaction. Indirect trust is the trust may be due to either reputation gained or recommendations received from various recommenders of a particular domain in a grid or any other domain outside that grid or outside that grid itself. Unfortunately, malicious indirect trust leads to the misuse of valuable resources of the grid. This paper proposes the mechanism of identifying and purging the untrustworthy recommendations in the grid environment. Through the obtained results, we show the way of purging of untrustworthy entities.
A simulation model for the lifetime of wireless sensor networks
Venue: arXiv cs.NI 2012
Year: 2012

In this paper we present a model for the lifetime of wireless sensor networks. The model takes into consideration several parameters such as the total number of sensors, network size, percentage of sink nodes, location of sensors, the mobility of sensors, and power consumption. A definition of the life time of the network based on three different criteria is introduced; percentage of available power to total power, percentage of alive sensors to total sensors, and percentage of alive sink sensors to total sink sensors. A Matlab based simulator is developed for the introduced model. A number of wireless sensor networks scenarios are presented and discussed.
A Lower Bound for Shallow Partitions
Venue: arXiv cs.CG 2012
Year: 2012

Let P be a planar n-point set. A k-partition of P is a subdivision of P into n/k parts of roughly equal size and a sequence of triangles such that each part is contained in a triangle. A line is k-shallow if it has at most k points of P below it. The crossing number of a k-partition is the maximum number of triangles in the partition that any k-shallow line intersects. We give a lower bound of Omega(log (n/k)/loglog(n/k)) for this crossing number, answering a 20-year old question of Matousek.
Actor Garbage Collection in Distributed Systems using Graph Transformation
Venue: arXiv cs.PL 2012
Year: 2012

A lot of research work has been done in the area of Garbage collection for both uniprocessor and distributed systems. Actors are associated with activity (thread) and hence usual garbage collection algorithms cannot be applied for them. Hence a separate algorithm should be used to collect them. If we transform the active reference graph into a graph which captures all the features of actors and looks like passive reference graph then any passive reference graph algorithm can be applied for it. But the cost of transformation and optimization are the core issues. An attempt has been made to walk through these issues.
A New Design Technique of Reversible BCD Adder Based on NMOS With Pass Transistor Gates
Venue: arXiv cs.OH 2012
Year: 2012

In this paper, we have proposed a new design technique of BCD Adder using newly constructed reversible gates are based on NMOS with pass transistor gates, where the conventional reversible gates are based on CMOS with transmission gates. We also compare the proposed reversible gates with the conventional CMOS reversible gates which show that the required number of Transistors is significantly reduced.
A New Order-theoretic Characterisation of the Polytime Computable Functions
Venue: arXiv cs.CC 2012
Year: 2012

We propose a new order, the small polynomial path order (sPOP* for short). The order sPOP* provides a characterisation of the class of polynomial time computable function via term rewrite systems. Any polynomial time computable function gives rise to a rewrite system that is compatible with sPOP*. On the other hand any function defined by a rewrite system compatible with sPOP* is polynomial time computable. Technically sPOP* is a tamed recursive path order with product status. Its distinctive feature is the precise control provided. For any rewrite system that is compatible with sPOP* that makes use of recursion up to depth d, the (innermost) runtime complexity is bounded from above by a polynomial of degree d.
Sparse Reward Processes
Venue: arXiv cs.LG 2012
Year: 2012

We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained during execution of one task has value for the execution of another task. Consequently, the agent is intrinsically motivated to explore its environment beyond the degree necessary to solve the current task it has at hand. We develop a decision theoretic setting that generalises standard reinforcement learning tasks and captures this intuition. More precisely, we consider a multi-stage stochastic game between a learning agent and an opponent. We posit that the setting is a good model for the problem of life-long learning in uncertain environments, where while resources must be spent learning about currently important tasks, there is also the need to allocate effort towards learning about aspects of the world which are not relevant at the moment. This is due to the fact that unpredictable future events may lead to a change of priorities for the decision maker. Thus, in some sense, the model "explains" the necessity of curiosity. Apart from introducing the general formalism, the paper provides algorithms. These are evaluated experimentally in some exemplary domains. In addition, performance bounds are proven for some cases of this problem.
Autonomous Cleaning of Corrupted Scanned Documents - A Generative Modeling Approach
Venue: arXiv cs.CV 2012
Year: 2012

We study the task of cleaning scanned text documents that are strongly corrupted by dirt such as manual line strokes, spilled ink etc. We aim at autonomously removing dirt from a single letter-size page based only on the information the page contains. Our approach, therefore, has to learn character representations without supervision and requires a mechanism to distinguish learned representations from irregular patterns. To learn character representations, we use a probabilistic generative model parameterizing pattern features, feature variances, the features' planar arrangements, and pattern frequencies. The latent variables of the model describe pattern class, pattern position, and the presence or absence of individual pattern features. The model parameters are optimized using a novel variational EM approximation. After learning, the parameters represent, independently of their absolute position, planar feature arrangements and their variances. A quality measure defined based on the learned representation then allows for an autonomous discrimination between regular character patterns and the irregular patterns making up the dirt. The irregular patterns can thus be removed to clean the document. For a full Latin alphabet we found that a single page does not contain sufficiently many character examples. However, even if heavily corrupted by dirt, we show that a page containing a lower number of character types can efficiently and autonomously be cleaned solely based on the structural regularity of the characters it contains. In different examples using characters from different alphabets, we demonstrate generality of the approach and discuss its implications for future developments.
A remark on the Restricted Isometry Property in Orthogonal Matching Pursuit
Venue: arXiv cs.IT 2012
Year: 2012

This paper demonstrates that if the restricted isometry constant $δ_{K+1}$ of the measurement matrix $A$ satisfies $$ δ_{K+1} < \frac{1}{\sqrt{K}+1}, $$ then a greedy algorithm called Orthogonal Matching Pursuit (OMP) can recover every $K$--sparse signal $\mathbf{x}$ in $K$ iterations from $A\x$. By contrast, a matrix is also constructed with the restricted isometry constant $$ δ_{K+1} = \frac{1}{\sqrt{K}} $$ such that OMP can not recover some $K$-sparse signal $\mathbf{x}$ in $K$ iterations. This result positively verifies the conjecture given by Dai and Milenkovic in 2009.
SparseDTW: A Novel Approach to Speed up Dynamic Time Warping
Venue: arXiv cs.DB 2012
Year: 2012

We present a new space-efficient approach, (SparseDTW), to compute the Dynamic Time Warping (DTW) distance between two time series that always yields the optimal result. This is in contrast to other known approaches which typically sacrifice optimality to attain space efficiency. The main idea behind our approach is to dynamically exploit the existence of similarity and/or correlation between the time series. The more the similarity between the time series the less space required to compute the DTW between them. To the best of our knowledge, all other techniques to speedup DTW, impose apriori constraints and do not exploit similarity characteristics that may be present in the data. We conduct experiments and demonstrate that SparseDTW outperforms previous approaches.
Throughput Scaling Of Convolution For Error-Tolerant Multimedia Applications
Venue: arXiv cs.MM 2012
Year: 2012

Convolution and cross-correlation are the basis of filtering and pattern or template matching in multimedia signal processing. We propose two throughput scaling options for any one-dimensional convolution kernel in programmable processors by adjusting the imprecision (distortion) of computation. Our approach is based on scalar quantization, followed by two forms of tight packing in floating-point (one of which is proposed in this paper) that allow for concurrent calculation of multiple results. We illustrate how our approach can operate as an optional pre- and post-processing layer for off-the-shelf optimized convolution routines. This is useful for multimedia applications that are tolerant to processing imprecision and for cases where the input signals are inherently noisy (error tolerant multimedia applications). Indicative experimental results with a digital music matching system and an MPEG-7 audio descriptor system demonstrate that the proposed approach offers up to 175% increase in processing throughput against optimized (full-precision) convolution with virtually no effect in the accuracy of the results. Based on marginal statistics of the input data, it is also shown how the throughput and distortion can be adjusted per input block of samples under constraints on the signal-to-noise ratio against the full-precision convolution.
Delay Sensitive Communications over Cognitive Radio Networks
Venue: arXiv cs.SY 2012
Year: 2012

Supporting the quality of service of unlicensed users in cognitive radio networks is very challenging, mainly due to dynamic resource availability because of the licensed users' activities. In this paper, we study the optimal admission control and channel allocation decisions in cognitive overlay networks in order to support delay sensitive communications of unlicensed users. We formulate it as a Markov decision process problem, and solve it by transforming the original formulation into a stochastic shortest path problem. We then propose a simple heuristic control policy, which includes a threshold-based admission control scheme and and a largest-delay-first channel allocation scheme, and prove the optimality of the largest-delay-first channel allocation scheme. We further propose an improved policy using the rollout algorithm. By comparing the performance of both proposed policies with the upper-bound of the maximum revenue, we show that our policies achieve close-to-optimal performance with low complexities.
Empirical Confirmation (and Refutation) of Presumptions on Software
Venue: arXiv cs.SE 2012
Year: 2012

Code metrics are easy to define, but not so easy to justify. It is hard to prove that a metric is valid, i.e., that measured numerical values imply anything on the vaguely defined, yet crucial software properties such as complexity and maintainability. This paper employs statistical analysis and tests to check some "believable" presumptions on the behavior of software and metrics measured for this software. Among those are the reliability presumption implicit in the application of any code metric, and the presumption that the magnitude of change in a software artifact is correlated with changes to its version number. Putting a suite of 36 metrics to the trial, we confirm most of the presumptions. Unexpectedly, we show that a substantial portion of the reliability of some metrics can be observed even in random changes to architecture. Another surprising result is that Boolean-valued metrics tend to flip their values more often in minor software version increments than in major increments.
Fractal and Multi-Scale Fractal Dimension analysis: a comparative study of Bouligand-Minkowski method
Venue: arXiv cs.CV 2012
Year: 2012

Shape is one of the most important visual attributes to characterize objects, playing a important role in pattern recognition. There are various approaches to extract relevant information of a shape. An approach widely used in shape analysis is the complexity, and Fractal Dimension and Multi-Scale Fractal Dimension are both well-known methodologies to estimate it. This papers presents a comparative study between Fractal Dimension and Multi-Scale Fractal Dimension in a shape analysis context. Through experimental comparison using a shape database previously classified, both methods are compared. Different parameters configuration of each method are considered and a discussion about the results of each method is also presented.
Assessing the Value of 3D Reconstruction in Building Construction
Venue: arXiv cs.HC 2012
Year: 2012

3-dimensional (3D) reconstruction is an emerging field in image processing and computer vision that aims to create 3D visualizations/ models of objects/ scenes from image sets. However, its commercial applications and benefits are yet to be fully explored. In this paper, we describe ongoing work towards assessing the value of 3D reconstruction in the building construction domain. We present preliminary results from a user study, where our objective is to understand the use of visual information in building construction in order to determine problems with the use of visual information and identify potential benefits and scenarios for the use of 3D reconstruction.
Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
Venue: arXiv cs.IT 2012
Year: 2012

This paper surveys recent advances in the area of very large MIMO systems. With very large MIMO, we think of systems that use antenna arrays with an order of magnitude more elements than in systems being built today, say a hundred antennas or more. Very large MIMO entails an unprecedented number of antennas simultaneously serving a much smaller number of terminals. The disparity in number emerges as a desirable operating condition and a practical one as well. The number of terminals that can be simultaneously served is limited, not by the number of antennas, but rather by our inability to acquire channel-state information for an unlimited number of terminals. Larger numbers of terminals can always be accommodated by combining very large MIMO technology with conventional time- and frequency-division multiplexing via OFDM. Very large MIMO arrays is a new research field both in communication theory, propagation, and electronics and represents a paradigm shift in the way of thinking both with regards to theory, systems and implementation. The ultimate vision of very large MIMO systems is that the antenna array would consist of small active antenna units, plugged into an (optical) fieldbus.
A Spiking Neural Learning Classifier System
Venue: arXiv cs.NE 2012
Year: 2012

Learning Classifier Systems (LCS) are population-based reinforcement learners used in a wide variety of applications. This paper presents a LCS where each traditional rule is represented by a spiking neural network, a type of network with dynamic internal state. We employ a constructivist model of growth of both neurons and dendrites that realise flexible learning by evolving structures of sufficient complexity to solve a well-known problem involving continuous, real-valued inputs. Additionally, we extend the system to enable temporal state decomposition. By allowing our LCS to chain together sequences of heterogeneous actions into macro-actions, it is shown to perform optimally in a problem where traditional methods can fail to find a solution in a reasonable amount of time. Our final system is tested on a simulated robotics platform.
Capacity Region of Multiple Access Channel with States Known Noncausally at One Encoder and Only Strictly Causally at the Other Encoder
Venue: arXiv cs.IT 2012
Year: 2012

We consider a two-user state-dependent multiaccess channel in which the states of the channel are known non-causally to one of the encoders and only strictly causally to the other encoder. Both encoders transmit a common message and, in addition, the encoder that knows the states non-causally transmits an individual message. We find explicit characterizations of the capacity region of this communication model in both discrete memoryless (DM) and memoryless Gaussian cases. In particular the capacity region analysis demonstrates the utility of the knowledge of the states only strictly causally at the encoder that sends only the common message in general. More specifically, in the DM setting we show that such a knowledge is beneficial and increases the capacity region in general. In the Gaussian setting, we show that such a knowledge does not help, and the capacity is same as if the states were completely unknown at the encoder that sends only the common message. The analysis also reveals optimal ways of exploiting the knowledge of the state only strictly causally at the encoder that sends only the common message when such a knowledge is beneficial. The encoders collaborate to convey to the decoder a lossy version of the state, in addition to transmitting the information messages through a generalized Gel'fand-Pinsker binning. Particularly important in this problem are the questions of 1) optimal ways of performing the state compression and 2) whether or not the compression indices should be decoded uniquely. We show that both compression à-la noisy network coding, i.e., with no binning and non-unique decoding, and compression using Wyner-Ziv binning with backward decoding and non-unique or unique decoding are optimal.
Simulating Special but Natural Quantum Circuits
Venue: arXiv cs.CC 2012
Year: 2012

We identify a sub-class of BQP that captures certain structural commonalities among many quantum algorithms including Shor's algorithms. This class does not contain all of BQP (e.g. Grover's algorithm does not fall into this class). Our main result is that any algorithm in this class that measures at most O(log n) qubits can be simulated by classical randomized polynomial time algorithms. This does not dequantize Shor's algorithm (as the latter measures n qubits) but our work also highlights a new potentially hard function for cryptographic applications. Our main technical contribution is (to the best of our knowledge) a new exact characterization of certain sums of Fourier-type coefficients (with exponentially many summands).