OpenRaiser/Intern-Atlas huggingface dataset:
Five Modulus Method For Image Compression
Venue: arXiv cs.CV 2012
Year: 2012

Data is compressed by reducing its redundancy, but this also makes the data less reliable, more prone to errors. In this paper a novel approach of image compression based on a new method that has been created for image compression which is called Five Modulus Method (FMM). The new method consists of converting each pixel value in an 8-by-8 block into a multiple of 5 for each of the R, G and B arrays. After that, the new values could be divided by 5 to get new values which are 6-bit length for each pixel and it is less in storage space than the original value which is 8-bits. Also, a new protocol for compression of the new values as a stream of bits has been presented that gives the opportunity to store and transfer the new compressed image easily.
A Decentralized Method for Joint Admission Control and Beamforming in Coordinated Multicell Downlink
Venue: arXiv cs.IT 2012
Year: 2012

In cellular networks, admission control and beamforming optimization are intertwined problems. While beamforming optimization aims at satisfying users' quality-of-service (QoS) requirements or improving the QoS levels, admission control looks at how a subset of users should be selected so that the beamforming optimization problem can yield a reasonable solution in terms of the QoS levels provided. However, in order to simplify the design, the two problems are usually seen as separate problems. This paper considers joint admission control and beamforming (JACoB) under a coordinated multicell MISO downlink scenario. We formulate JACoB as a user number maximization problem, where selected users are guaranteed to receive the QoS levels they requested. The formulated problem is combinatorial and hard, and we derive a convex approximation to the problem. A merit of our convex approximation formulation is that it can be easily decomposed for per-base-station decentralized optimization, namely, via block coordinate decent. The efficacy of the proposed decentralized method is demonstrated by simulation results.
Matching Through Features and Features Through Matching
Venue: arXiv cs.CV 2012
Year: 2012

This paper addresses how to construct features for the problem of image correspondence, in particular, the paper addresses how to construct features so as to maintain the right level of invariance versus discriminability. We show that without additional prior knowledge of the 3D scene, the right tradeoff cannot be established in a pre-processing step of the images as is typically done in most feature-based matching methods. However, given knowledge of the second image to match, the tradeoff between invariance and discriminability of features in the first image is less ambiguous. This suggests to setup the problem of feature extraction and matching as a joint estimation problem. We develop a possible mathematical framework, a possible computational algorithm, and we give example demonstration on finding correspondence on images related by a scene that undergoes large 3D deformation of non-planar objects and camera viewpoint change.
The Universe at Extreme Scale: Multi-Petaflop Sky Simulation on the BG/Q
Venue: arXiv cs.DC 2012
Year: 2012

Remarkable observational advances have established a compelling cross-validated model of the Universe. Yet, two key pillars of this model -- dark matter and dark energy -- remain mysterious. Sky surveys that map billions of galaxies to explore the `Dark Universe', demand a corresponding extreme-scale simulation capability; the HACC (Hybrid/Hardware Accelerated Cosmology Code) framework has been designed to deliver this level of performance now, and into the future. With its novel algorithmic structure, HACC allows flexible tuning across diverse architectures, including accelerated and multi-core systems. On the IBM BG/Q, HACC attains unprecedented scalable performance -- currently 13.94 PFlops at 69.2% of peak and 90% parallel efficiency on 1,572,864 cores with an equal number of MPI ranks, and a concurrency of 6.3 million. This level of performance was achieved at extreme problem sizes, including a benchmark run with more than 3.6 trillion particles, significantly larger than any cosmological simulation yet performed.
A Traveling Salesman Learns Bayesian Networks
Venue: arXiv cs.LG 2012
Year: 2012

Structure learning of Bayesian networks is an important problem that arises in numerous machine learning applications. In this work, we present a novel approach for learning the structure of Bayesian networks using the solution of an appropriately constructed traveling salesman problem. In our approach, one computes an optimal ordering (partially ordered set) of random variables using methods for the traveling salesman problem. This ordering significantly reduces the search space for the subsequent greedy optimization that computes the final structure of the Bayesian network. We demonstrate our approach of learning Bayesian networks on real world census and weather datasets. In both cases, we demonstrate that the approach very accurately captures dependencies between random variables. We check the accuracy of the predictions based on independent studies in both application domains.
A Mathematical Random Number Generator (MRNG)
Venue: arXiv cs.NA 2012
Year: 2012

A novel Mathematical Random Number Generator (MRNG) is presented here. In this case, "mathematical" refers to the fact that to construct that generator it is not necessary to resort to a physical phenomenon, such as the thermal noise of an electronic device, but rather to a mathematical procedure. The MRNG generates binary strings - in principle, as long as desired - which may be considered genuinely random in the sense that they pass the statistical tests currently accepted to evaluate the randomness of those strings. From those strings, the MRNG also generates random numbers expressed in base 10. An MRNG has been installed as a facility on the following web page: http://www.appliedmathgroup.org. This generator may be used for applications in tasks in: a) computational simulation of probabilistic-type systems, and b) the random selection of samples of different populations. Users interested in applications in cryptography can build another MRNG, but they would have to withhold information - specified in section 5 - from people who are not authorized to decode messages encrypted using that resource.
Approaching the Capacity of Large-Scale MIMO Systems via Non-Binary LDPC Codes
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, the application of non-binary low-density parity-check (NBLDPC) codes to MIMO systems which employ hundreds of antennas at both the transmitter and the receiver has been proposed. Together with the well-known low-complexity MMSE detection, the moderate length NBLDPC codes can operate closer to the MIMO capacity, e.g., capacity-gap about 3.5 dB (the best known gap is more than 7 dB). To further reduce the complexity of MMSE detection, a novel soft output detection that can provide an excellent coded performance in low SNR region with 99% complexity reduction is also proposed. The asymptotic performance is analysed by using the Monte Carlo density evolution. It is found that the NBLDPC codes can operate within 1.6 dB from the MIMO capacity. Furthermore, the merit of using the NBLDPC codes in large MIMO systems with the presence of imperfect channel estimation and spatial fading correlation which are both the realistic scenarios for large MIMO systems is also pointed out.
Memoization technique for optimizing functions with stochastic input
Venue: arXiv cs.OH 2012
Year: 2012

In this paper we present a strategy for optimization functions with stochastic input. The main idea is to take advantage of decomposition in combination with a look-up table. Deciding what input values should be used for memoization is determined based on the underlying probability distribution of input variables. Special attention is given to difficulties caused by combinatorial explosion.
Traffic Engineering Based on Effective Envelope Algorithm on Novel Resource Reservation Method over Mobile Internet Protocol Version 6
Venue: arXiv cs.NI 2012
Year: 2012

The first decade of the 21st century has seen tremendous improvements in mobile internet and its technologies. The high traffic volume of services such as video conference and other real-time traffic applications are imposing a great challenge on networks. In the meantime, demand for the use of mobile devices in computation and communication such as smart phones, personal digital assistants, and mobile-enabled laptops has grown rapidly. These services have driven the demand for increasing and guaranteing bandwidth requirements in the network. A direction of this paper is in the case of resource reservation protocol (RSVP) over mobile IPv6 networks. There are numbers of proposed solutions for RSVP and quality of service provision over mobile IPv6 networks, but most of them using advanced resource reservation. In this paper, we propose a mathematical model to determine maximum end-to-end delay bound through intermediate routers along the network. These bounds are sent back to the home agent for further processing. Once the home agent receives maximum end-to-end delay bounds, it calculates cumulative bound and compares this bound with the desired application end-to-end delay bound to make final decision on resource reservation. This approach improves network resource utilization.
Note on the Greedy Parsing Optimality for Dictionary-Based Text Compression
Venue: arXiv cs.DS 2012
Year: 2012

Dynamic dictionary-based compression schemes are the most daily used data compression schemes since they appeared in the foundational papers of Ziv and Lempel in 1977, commonly referred to as LZ77. Their work is the base of Deflate, gZip, WinZip, 7Zip and many others compression software. All of those compression schemes use variants of the greedy approach to parse the text into dictionary phrases. Greedy parsing optimality was proved by Cohn et al. (1996) for fixed length code and unbounded dictionaries. The optimality of the greedy parsing was never proved for bounded size dictionary which actually all of those schemes require. We define the suffix-closed property for dynamic dictionaries and we show that any LZ77-based dictionary, including the bounded variants, satisfy this property. Under this condition we prove the optimality of the greedy parsing as a variant of the proof by Cohn et al.
Cobb Angle Measurement of Scoliosis with Reduced Variability
Venue: arXiv cs.CV 2012
Year: 2012

Cobb angle, which is a measure of spinal curvature is the standard method for quantifying the magnitude of Scoliosis related to spinal deformity in orthopedics. Determining the Cobb angle through manual process is subject to human errors. In this work, we propose a methodology to measure the magnitude of Cobb angle, which appreciably reduces the variability related to its measurement compared to the related works. The proposed methodology is facilitated by using a suitable new improved version of Non-Local Means for image denoisation and Otsus automatic threshold selection for Canny edge detection. We have selected NLM for preprocessing of the image as it is one of the fine states of art for image denoisation and helps in retaining the image quality. Trimmedmean, median are more robust to outliners than mean and following this concept we observed that NLM denoising quality performance can be enhanced by using Euclidean trimmed-mean replacing the mean. To prove the better performance of the Non-Local Euclidean Trimmed-mean denoising filter, we have provided some comparative study results of the proposed denoising technique with traditional NLM and NonLocal Euclidean Medians. The experimental results for Cobb angle measurement over intra observer and inter observer experimental data reveals the better performance and superiority of the proposed approach compared to the related works. MATLAB2009b image processing toolbox was used for the purpose of simulation and verification of the proposed methodology.
Analysis of a randomized approximation scheme for matrix multiplication
Venue: arXiv cs.DS 2012
Year: 2012

This note gives a simple analysis of a randomized approximation scheme for matrix multiplication proposed by Sarlos (2006) based on a random rotation followed by uniform column sampling. The result follows from a matrix version of Bernstein's inequality and a tail inequality for quadratic forms in subgaussian random vectors.
Ranking the Importance of Nodes of Complex Networks by the Equivalence Classes Approach
Venue: arXiv cs.SI 2012
Year: 2012

Identifying the importance of nodes of complex networks is of interest to the research of Social Networks, Biological Networks etc.. Current researchers have proposed several measures or algorithms, such as betweenness, PageRank and HITS etc., to identify the node importance. However, these measures are based on different aspects of properties of nodes, and often conflict with the others. A reasonable, fair standard is needed for evaluating and comparing these algorithms. This paper develops a framework as the standard for ranking the importance of nodes. Four intuitive rules are suggested to measure the node importance, and the equivalence classes approach is employed to resolve the conflicts and aggregate the results of the rules. To quantitatively compare the algorithms, the performance indicators are also proposed based on a similarity measure. Three widely used real-world networks are used as the test-beds. The experimental results illustrate the feasibility of this framework and show that both algorithms, PageRank and HITS, perform well with bias when dealing with the tested networks. Furthermore, this paper uses the proposed approach to analyze the structure of the Internet, and draws out the kernel of the Internet with dense links.
A Revised Classification of Anonymity
Venue: arXiv cs.CR 2012
Year: 2012

This paper primarily addresses the issue of identifying all possible levels of digital anonymity, thereby allowing electronic services and mechanisms to be categorised. For this purpose, we sophisticate the generic idea of anonymity and, filling a niche in the field, bring the scope of trust into the focus of categorisation. One major concern of our work is to propose a novel and universal taxonomy which enables a dynamic, trust-based comparison between systems at an abstract level. On the other hand, our contribution intentionally does not offer an alternative to anonymity metrics, but neither is it concerned with methods of anonymous data retrieval (cf. data-mining techniques). However, for ease of comprehension, it provides a systematic 'application manual' and also presents a lucid overview of the correspondence between the current and related taxonomies. Additionally, as a generalisation of group signatures, we introduce the notion of group schemes.
Improving Computer-Mediated Synchronous Communication of Doctors in Rural Communities through Cloud Computing: A Case Study of Rural Hospitals in South Africa
Venue: arXiv cs.CY 2012
Year: 2012

This paper investigated how doctors in remote rural hospitals in South Africa use computer-mediated tool to communicate with experienced and specialist doctors for professional advice to improve on their clinical practices. A case study approach was used. Ten doctors were purposively selected from ten hospitals in the North West Province. Data was collected using semi-structured open ended interview questions. The interviewees were asked to tell in their own words the average number of patients served per week, processes used in consultation with other doctors, communication practices using computer-mediated tool, transmission speed of the computer-mediated tool and satisfaction in using the computer-mediated communication tool. The findings revealed that an average of 15 consultations per doctor to a specialist doctor per week was done through face to face or through telephone conversation instead of using a computer-mediated tool. Participants cited reasons for not using computer-mediated tool for communication due to slow transmission speed of the Internet and regular down turn of the Internet connectivity, constant electricity power outages and lack of e-health application software to support real time computer-mediated communication. The results led to the recommendation of a hybrid cloud computing architecture for improving communication between doctors in hospitals.
Deterministic Compression with Uncertain Priors
Venue: arXiv cs.IT 2012
Year: 2012

We consider the task of compression of information when the source of the information and the destination do not agree on the prior, i.e., the distribution from which the information is being generated. This setting was considered previously by Kalai et al. (ICS 2011) who suggested that this was a natural model for human communication, and efficient schemes for compression here could give insights into the behavior of natural languages. Kalai et al. gave a compression scheme with nearly optimal performance, assuming the source and destination share some uniform randomness. In this work we explore the need for this randomness, and give some non-trivial upper bounds on the deterministic communication complexity for this problem. In the process we introduce a new family of structured graphs of constant fractional chromatic number whose (integral) chromatic number turns out to be a key component in the analysis of the communication complexity. We provide some non-trivial upper bounds on the chromatic number of these graphs to get our upper bound, while using lower bounds on variants of these graphs to prove lower bounds for some natural approaches to solve the communication complexity question. Tight analysis of communication complexity of our problems and the chromatic number of the underlying graphs remains open.
Optimal Selection of Measurement Configurations for Stiffness Model Calibration of Anthropomorphic Manipulators
Venue: arXiv cs.RO 2012
Year: 2012

The paper focuses on the calibration of elastostatic parameters of spatial anthropomorphic robots. It proposes a new strategy for optimal selection of the measurement configurations that essentially increases the efficiency of robot calibration. This strategy is based on the concept of the robot test-pose and ensures the best compliance error compensation for the test configuration. The advantages of the proposed approach and its suitability for practical applications are illustrated by numerical examples, which deal with calibration of elastostatic parameters of a 3 degrees of freedom anthropomorphic manipulator with rigid links and compliant actuated joints
Industry-oriented Performance Measures for Design of Robot Calibration Experiment
Venue: arXiv cs.RO 2012
Year: 2012

The paper focuses on the accuracy improvement of geometric and elasto-static calibration of industrial robots. It proposes industry-oriented performance measures for the calibration experiment design. They are based on the concept of manipulator test-pose and referred to the end-effector location accuracy after application of the error compensation algorithm, which implements the identified parameters. This approach allows the users to define optimal measurement configurations for robot calibration for given work piece location and machining forces/torques. These performance measures are suitable for comparing the calibration plans for both simple and complex trajectories to be performed. The advantages of the developed techniques are illustrated by an example that deals with machining using robotic manipulator.
Geosocial Graph-Based Community Detection
Venue: arXiv cs.SI 2012
Year: 2012

We apply spectral clustering and multislice modularity optimization to a Los Angeles Police Department field interview card data set. To detect communities (i.e., cohesive groups of vertices), we use both geographic and social information about stops involving street gang members in the LAPD district of Hollenbeck. We then compare the algorithmically detected communities with known gang identifications and argue that discrepancies are due to sparsity of social connections in the data as well as complex underlying sociological factors that blur distinctions between communities.
A Novel Algorithm for Real-time Procedural Generation of Building Floor Plans
Venue: arXiv cs.GR 2012
Year: 2012

Real-time generation of natural-looking floor plans is vital in games with dynamic environments. This paper presents an algorithm to generate suburban house floor plans in real-time. The algorithm is based on the work presented in [1]. However, the corridor placement is redesigned to produce floor plans similar to real houses. Moreover, an optimization stage is added to find a corridor placement with the minimum used space, an approach that is designed to mimic the real-life practices to minimize the wasted spaces in the design. The results show very similar floor plans to the ones designed by an architect.
Low complexity sum rate maximization for single and multiple stream MIMO AF relay networks
Venue: arXiv cs.IT 2012
Year: 2012

A multiple-antenna amplify-and-forward two-hop interference network with multiple links and multiple relays is considered. We optimize transmit precoders, receive decoders and relay AF matrices to maximize the achievable sum rate. Under per user and total relay sum power constraints, we propose an efficient algorithm to maximize the total signal to total interference plus noise ratio (TSTINR). Computational complexity analysis shows that our proposed algorithm for TSTINR has lower complexity than the existing weighted minimum mean square error (WMMSE) algorithm. We analyze and confirm by simulations that the TSTINR, WMMSE and the total leakage interference plus noise (TLIN) minimization models with per user and total relay sum power constraints can only transmit a single data stream for each user. Thus we propose a novel multiple stream TSTINR model with requirement of orthogonal columns for precoders, in order to support multiple data streams and thus utilize higher Degrees of Freedom. Multiple data streams and larger multiplexing gains are guaranteed. Simulation results show that for single stream models, our TSTINR algorithm outperforms the TLIN algorithm generally and outperforms WMMSE in medium to high Signal-to-Noise-Ratio scenarios; the system sum rate significantly benefits from multiple data streams in medium to high SNR scenarios.
Adaptive Control of Enterprise
Venue: arXiv cs.CE 2012
Year: 2012

Modern progress in artificial intelligence permits to realize algorithms of adaptation for critical events (in addition to ERP). A production emergence, an appearance of new competitive goods, a major change in financial state of partners, a radical change in exchange rate, a change in custom and tax legislation, a political and energy crisis, an ecocatastrophe can lead up to a decrease of profit or bankruptcy of enterprise. Therefore it is necessary to assess a probability of threat and to take preventive actions. If a critical event took place, one must estimate restoration expenses and possible consequences as well as to prepare appropriate propositions. This is provided using modern methods of diagnostics, prediction, and decision making as well as an inference engine and semantic analysis. Mathematical methods in use are called in algorithms of adaptation automatically. Because the enterprise is a complex system, to overcome complexity of control it is necessary to apply semantic representations. Such representations are formed from descriptions of events, facts, persons, organizations, goods, operations, scripts on a natural language. Semantic representations permit as well to formulate actual problems and to find ways to resolve these problems.