OpenRaiser/Intern-Atlas huggingface dataset:
Full-Duplex Cloud Radio Access Networks: An Information-Theoretic Viewpoint
Venue: arXiv cs.IT 2014
Year: 2014

The conventional design of cellular systems prescribes the separation of uplink and downlink transmissions via time-division or frequency-division duplex. Recent advances in analog and digital domain self-interference interference cancellation challenge the need for this arrangement and open up the possibility to operate base stations, especially low-power ones, in a full-duplex mode. As a means to cope with the resulting downlink-to-uplink interference among base stations, this letter investigates the impact of the Cloud Radio Access Network (C-RAN) architecture. The analysis follows an information theoretic approach based on the classical Wyner model. The analytical results herein confirm the significant potential advantages of the C-RAN architecture in the presence of full-duplex base stations, as long as sufficient fronthaul capacity is available and appropriate mobile station scheduling, or successive interference cancellation at the mobile stations, is implemented.
Scheduling algorithm to select $k$ optimal programme slots in television channels: A graph theoretic approach
Venue: arXiv cs.DM 2014
Year: 2014

In this paper, it is shown that all programmes of all television channels can be modelled as an interval graph. The programme slots are taken as the vertices of the graph and if the time duration of two {programme slots} have non-empty intersection, the corresponding vertices are considered to be connected by an edge. The number of viewers of a programme is taken as the weight of the vertex. A set of programmes that are mutually exclusive in respect of time scheduling is called a session. We assume that a company sets the objective of selecting the popular programmes in $k$ parallel sessions among different channels so as to make its commercial advertisement reach the maximum number of viewers, that is, a company selects $k$ suitable programme slots simultaneously for advertisement. The aim of the paper is, therefore, to {help} the companies to select the programme slots, which are mutually exclusive with respect to the time schedule of telecasting time, in such a way that the total number of viewers of the selected programme in $k$ parallel slots rises to the optimum level. It is shown that the solution of this problem is obtained by solving the maximum weight $k$-colouring problem on an interval {graph}. An algorithm is designed to solve this just-in-time optimization problem using $O(kMn^2)$ time, where $n$ and $M$ represent the total number of programmes of all channels and the upper bound of the viewers of all programmes of all channels respectively. The problem considered in this paper is a daily life problem which is modeled by $k$-colouring problem on interval graph.
Reference Receiver Based Digital Self-Interference Cancellation in MIMO Full-Duplex Transceivers
Venue: arXiv cs.IT 2014
Year: 2014

In this paper we propose and analyze a novel self-interference cancellation structure for in-band MIMO full-duplex transceivers. The proposed structure utilizes reference receiver chains to obtain reference signals for digital self-interference cancellation, which means that all the transmitter-induced nonidealities will be included in the digital cancellation signal. To the best of our knowledge, this type of a structure has not been discussed before in the context of full-duplex transceivers. First, we will analyze the overall achievable performance of the proposed cancellation scheme, while also providing some insight into the possible bottlenecks. We also provide a detailed formulation of the actual cancellation procedure, and perform an analysis into the effect of the received signal of interest on self-interference coupling channel estimation. The achieved performance of the proposed reference receiver based digital cancellation procedure is then assessed and verified with full waveform simulations. The analysis and waveform simulation results show that under practical transmitter RF/analog impairment levels, the proposed reference receiver based cancellation architecture can provide substantially better self-interference suppression than any existing solution, despite deploying only low-complexity linear digital processing.
The Eve of 3D Printing in Telemedicine: State of the Art and Future Challenges
Venue: arXiv cs.OH 2014
Year: 2014

3D printing has raised a lot of attention from fields outside the manufacturing one in the last years. In this paper, we will illustrate some recent advances of 3D printing technology, applied to the field of telemedicine and remote patient care. The potentiality of this technology will be detailed without lab examples. Some crucial aspect such as the regulation of these devices and the need of some standards will also be discussed. The purpose of this paper is to present some of the most promising applications of such technology.
Covering Folded Shapes
Venue: arXiv cs.CG 2014
Year: 2014

Can folding a piece of paper flat make it larger? We explore whether a shape $S$ must be scaled to cover a flat-folded copy of itself. We consider both single folds and arbitrary folds (continuous piecewise isometries $S\rightarrow R^2$). The underlying problem is motivated by computational origami, and is related to other covering and fixturing problems, such as Lebesgue's universal cover problem and force closure grasps. In addition to considering special shapes (squares, equilateral triangles, polygons and disks), we give upper and lower bounds on scale factors for single folds of convex objects and arbitrary folds of simply connected objects.
The Past and the Future of Holocaust Research: From Disparate Sources to an Integrated European Holocaust Research Infrastructure
Venue: arXiv cs.DL 2014
Year: 2014

The European Holocaust Research Infrastructure (EHRI) has been set up by the European Union to create a sustainable complex of services for researchers. EHRI will bring together information about dispersed collections, based on currently more than 20 partner organisations in 13 countries and many other archives. EHRI, which brings together historians, archivists and specialists in digital humanities, strives to develop innovative on-line tools for finding, researching and sharing knowledge about the Holocaust. While connecting information about Holocaust collections, it strives to create tools and approaches applicable to other digital archival projects. The paper describes its current progress and collaboration across the disciplines involved.
Exact Probability Distribution versus Entropy
Venue: arXiv cs.IT 2014
Year: 2014

The problem addressed concerns the determination of the average number of successive attempts of guessing a word of a certain length consisting of letters with given probabilities of occurrence. Both first- and second-order approximations to a natural language are considered. The guessing strategy used is guessing words in decreasing order of probability. When word and alphabet sizes are large, approximations are necessary in order to estimate the number of guesses. Several kinds of approximations are discussed demonstrating moderate requirements concerning both memory and CPU time. When considering realistic sizes of alphabets and words (100) the number of guesses can be estimated within minutes with reasonable accuracy (a few percent). For many probability distributions the density of the logarithm of probability products is close to a normal distribution. For those cases it is possible to derive an analytical expression for the average number of guesses. The proportion of guesses needed on average compared to the total number decreases almost exponentially with the word length. The leading term in an asymptotic expansion can be used to estimate the number of guesses for large word lengths. Comparisons with analytical lower bounds and entropy expressions are also provided.
Tighter Bounds for Makespan Minimization on Unrelated Machines
Venue: arXiv cs.DS 2014
Year: 2014

We consider the problem of scheduling $n$ jobs to minimize the makespan on $m$ unrelated machines, where job $j$ requires time $p_{ij}$ if processed on machine $i$. A classic algorithm of Lenstra et al. yields the best known approximation ratio of $2$ for the problem. Improving this bound has been a prominent open problem for over two decades. In this paper we obtain a tighter bound for a wide subclass of instances which can be identified efficiently. Specifically, we define the feasibility factor of a given instance as the minimum fraction of machines on which each job can be processed. We show that there is a polynomial-time algorithm that, given values $L$ and $T$, and an instance having a sufficiently large feasibility factor $h \in (0,1]$, either proves that no schedule of mean machine completion time $L$ and makespan $T$ exists, or else finds a schedule of makespan at most $T + L/h < 2T$. For the restricted version of the problem, where for each job $j$ and machine $i$, $p_{ij} \in \{p_j, \infty\}$, we show that a simpler algorithm yields a better bound, thus improving for highly feasible instances the best known ratio of $33/17 + ε$, for any fixed $ε>0$, due to Svensson.
Reversible and Irreversible Data Hiding Technique
Venue: arXiv cs.CR 2014
Year: 2014

Steganography (literally meaning covered writing) is the art and science of embedding secret message into seemingly harmless message. Stenography is practice from olden days where in ancient Greece people used wooden blocks to inscribe secret data and cover the date with wax and write normal message on it. Today stenography is used in various field like multimedia, networks, medical, military etc. With increasing technology trends steganography is becoming more and more advanced where people not only interested on hiding messages in multimedia data (cover data) but also at the receiving end they are willing to obtain original cover data without any distortion after extracting secret message. This paper will discuss few irreversible data hiding techniques and also, some recently proposed reversible data hiding approach using images.
Statistical Model Checking for Biological Applications
Venue: arXiv cs.LO 2014
Year: 2014

In this paper we survey recent work on the use of statistical model checking techniques for biological applications. We begin with an overview of the basic modelling techniques for biochemical reactions and their corresponding stochastic simulation algorithm - the Gillespie algorithm. We continue by giving a brief description of the relation between stochastic models and continuous (ordinary differential equation) models. Next we present a literature survey, divided in two general areas. In the first area we focus on works addressing verification of biological models, while in the second area we focus on papers tackling the parameter synthesis problem. We conclude with some open problems and directions for further research.
Application of Modified Multi Model Predictive Control Algorithm to Fluid Catalytic Cracking Unit
Venue: arXiv cs.SY 2014
Year: 2014

This paper presents a modified multi model predictive control algorithm for the control of riser outlet temperature and regenerator temperature for the fluid catalytic cracking unit (FCCU). The models of the fluid catalytic cracking unit are estimated using subspace identification (N4SID) algorithm. The PRBS signal is applied as an input signal to estimate the FCCU models. Since the estimated model does not give 100% fit; especially for nonlinear systems having more than one operating conditions, multi-model approach is proposed. In multi model, more than one model of FCCU used in MPC design. The main advantages of proposed method are that it can handle hard input and output constraints and it can be used for multi input multi output processes (MIMO) without increasing the complexity in control design. MATLAB/Simulink is used to estimate the models of FCCU and simulate the results for the controller. The simulation results show that the proposed algorithm provides better result for both reference tracking and disturbance rejection.
Signalling Storms in 3G Mobile Networks
Venue: arXiv cs.NI 2014
Year: 2014

We review the characteristics of signalling storms that have been caused by certain common apps and recently observed in cellular networks, leading to system outages. We then develop a mathematical model of a mobile user's signalling behaviour which focuses on the potential of causing such storms, and represent it by a large Markov chain. The analysis of this model allows us to determine the key parameters of mobile user device behaviour that can lead to signalling storms. We then identify the parameter values that will lead to worst case load for the network itself in the presence of such storms. This leads to explicit results regarding the manner in which individual mobile behaviour can cause overload conditions on the network and its signalling servers, and provides insight into how this may be avoided.
Distributed Compressive CSIT Estimation and Feedback for FDD Multi-user Massive MIMO Systems
Venue: arXiv cs.IT 2014
Year: 2014

To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel state information must be obtained at the transmitter side (CSIT). However, conventional CSIT estimation approaches are not suitable for FDD massive MIMO systems because of the overwhelming training and feedback overhead. In this paper, we consider multi-user massive MIMO systems and deploy the compressive sensing (CS) technique to reduce the training as well as the feedback overhead in the CSIT estimation. The multi-user massive MIMO systems exhibits a hidden joint sparsity structure in the user channel matrices due to the shared local scatterers in the physical propagation environment. As such, instead of naively applying the conventional CS to the CSIT estimation, we propose a distributed compressive CSIT estimation scheme so that the compressed measurements are observed at the users locally, while the CSIT recovery is performed at the base station jointly. A joint orthogonal matching pursuit recovery algorithm is proposed to perform the CSIT recovery, with the capability of exploiting the hidden joint sparsity in the user channel matrices. We analyze the obtained CSIT quality in terms of the normalized mean absolute error, and through the closed-form expressions, we obtain simple insights into how the joint channel sparsity can be exploited to improve the CSIT recovery performance.
Maximum Throughput of a Secondary User Cooperating with an Energy-Aware Primary User
Venue: arXiv cs.NI 2014
Year: 2014

This paper proposes a cooperation protocol between a secondary user (SU) and a primary user (PU) which dedicates a free frequency subband for the SU if cooperation results in energy saving. Time is slotted and users are equipped with buffers. Under the proposed protocol, the PU releases portion of its bandwidth for secondary transmission. Moreover, it assigns a portion of the time slot duration for the SU to relay primary packets and achieve a higher successful packet reception probability at the primary receiver. We assume that the PU has three states: idle, forward, and retransmission states. At each of these states, the SU accesses the channel with adaptive transmission parameters. The PU cooperates with the SU if and only if the achievable average number of transmitted primary packets per joule is higher than the number of transmitted packets per joule when it operates alone. The numerical results show the beneficial gains of the proposed cooperative cognitive protocol.
Introduction to Dynamic Unary Encoding
Venue: arXiv cs.IT 2014
Year: 2014

Dynamic unary encoding takes unary encoding to the next level. Every n-bit binary string is an encoding of dynamic unary and every n-bit binary string is encodable by dynamic unary. By utilizing both forms of unary code and a single bit of parity information dynamic unary encoding partitions 2^n non-negative integers into n sets of disjoint cycles of n-bit elements. These cycles have been employed as virtual data sets, binary transforms and as a mathematical object. Characterization of both the cycles and of the cycle spectrum is given. Examples of encoding and decoding algorithms are given. Examples of other constructs utilizing the principles of dynamic unary encoding are presented. The cycle as a mathematical object is demonstrated.
On the Total Variation Distance of Labelled Markov Chains
Venue: arXiv cs.LO 2014
Year: 2014

Labelled Markov chains (LMCs) are widely used in probabilistic verification, speech recognition, computational biology, and many other fields. Checking two LMCs for equivalence is a classical problem subject to extensive studies, while the total variation distance provides a natural measure for the "inequivalence" of two LMCs: it is the maximum difference between probabilities that the LMCs assign to the same event. In this paper we develop a theory of the total variation distance between two LMCs, with emphasis on the algorithmic aspects: (1) we provide a polynomial-time algorithm for determining whether two LMCs have distance 1, i.e., whether they can almost always be distinguished; (2) we provide an algorithm for approximating the distance with arbitrary precision; and (3) we show that the threshold problem, i.e., whether the distance exceeds a given threshold, is NP-hard and hard for the square-root-sum problem. We also make a connection between the total variation distance and Bernoulli convolutions.
Heterogeneity-aware Fault Tolerance using a Self-Organizing Runtime System
Venue: arXiv cs.OS 2014
Year: 2014

Due to the diversity and implicit redundancy in terms of processing units and compute kernels, off-the-shelf heterogeneous systems offer the opportunity to detect and tolerate faults during task execution in hardware as well as in software. To automatically leverage this diversity, we introduce an extension of an online-learning runtime system that combines the benefits of the existing performance-oriented task mapping with task duplication, a diversity-oriented mapping strategy and heterogeneity-aware majority voter. This extension uses a new metric to dynamically rate the remaining benefit of unreliable processing units and a memory management mechanism for automatic data transfers and checkpointing in the host and device memories.
Resource-Aware Replication on Heterogeneous Multicores: Challenges and Opportunities
Venue: arXiv cs.DC 2014
Year: 2014

Decreasing hardware feature sizes and increasing heterogeneity in multicore hardware require software that can adapt to these platforms' properties. We implemented ROMAIN, an OS service providing redundant multithreading on top of the FIASCO.OC microkernel to address the increasing unreliability of hardware. In this paper we review challenges and opportunities for ROMAIN to adapt to such multicore platforms in order to decrease execution overhead, resource requirements, and vulnerability against faults.
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm
Venue: arXiv cs.SI 2014
Year: 2014

Information spreads across social and technological networks, but often the network structures are hidden from us and we only observe the traces left by the diffusion processes, called cascades. Can we recover the hidden network structures from these observed cascades? What kind of cascades and how many cascades do we need? Are there some network structures which are more difficult than others to recover? Can we design efficient inference algorithms with provable guarantees? Despite the increasing availability of cascade data and methods for inferring networks from these data, a thorough theoretical understanding of the above questions remains largely unexplored in the literature. In this paper, we investigate the network structure inference problem for a general family of continuous-time diffusion models using an $l_1$-regularized likelihood maximization framework. We show that, as long as the cascade sampling process satisfies a natural incoherence condition, our framework can recover the correct network structure with high probability if we observe $O(d^3 \log N)$ cascades, where $d$ is the maximum number of parents of a node and $N$ is the total number of nodes. Moreover, we develop a simple and efficient soft-thresholding inference algorithm, which we use to illustrate the consequences of our theoretical results, and show that our framework outperforms other alternatives in practice.
Haskell for OCaml programmers
Venue: arXiv cs.PL 2014
Year: 2014

This introduction to Haskell is written to optimize learning by programmers who already know OCaml.
Be In The Know: Connecting News Articles to Relevant Twitter Conversations
Venue: arXiv cs.SI 2014
Year: 2014

In the era of data-driven journalism, data analytics can deliver tools to support journalists in connecting to new and developing news stories, e.g., as echoed in micro-blogs such as Twitter, the new citizen-driven media. In this paper, we propose a framework for tracking and automatically connecting news articles to Twitter conversations as captured by Twitter hashtags. For example, such a system could alert journalists about news that get a lot of Twitter reaction, so that they can investigate those conversations for new developments in the story, promote their article to a set of interested consumers, or discover general sentiment towards the story. Mapping articles to appropriate hashtags is nevertheless very challenging, due to different language styles used in articles versus tweets, the streaming aspect of news and tweets, as well as the user behavior when marking certain tweet-terms as hashtags. As a case-study, we continuously track the RSS feeds of Irish Times news articles and a focused Twitter stream over a two months period, and present a system that assigns hashtags to each article, based on its Twitter echo. We propose a machine learning approach for classifying and ranking article-hashtag pairs. Our empirical study shows that our system delivers high precision for this task.
Clonal-Based Cellular Automata in Bioinformatics
Venue: arXiv cs.CE 2014
Year: 2014

This paper aims at providing a survey on the problems that can be easily addressed by clonalbased cellular automata in bioinformatics. Researchers try to address the problems in bioinformatics independent of each problem. None of the researchers has tried to relate the major problems in bioinformatics and find a solution using common frame work. We tried to find various problems in bioinformatics which can be addressed easily by clonal based cellular automata. Extensive literature survey is conducted. We have considered some papers in various journals and conferences for conduct of our research. This paper provides intuition towards relating various problems in bioinformatics logically and tries to attain a common frame work with respect to clonal based cellular automata classifier for addressing the same.