OpenRaiser/Intern-Atlas huggingface dataset:
Multi-Application Resource Allocation with Users Discrimination in Cellular Networks
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we consider resource allocation optimization problem in cellular networks for different types of users running multiple applications simultaneously. In our proposed model, each user application is assigned a utility function that represents the application type running on the user equipment (UE). The network operators assign a subscription weight to each UE based on its subscription. Each UE assigns an application weight to each of its applications based on the instantaneous usage percentage of the application. Additionally, UEs with higher priority assign applications target rates to their applications. Our objective is to allocate the resources optimally among the UEs and their applications from a single evolved node B (eNodeB) based on a utility proportional fairness policy with priority to real-time application users. A minimum quality of service (QoS) is guaranteed to each UE application based on the UE subscription weight, the UE application weight and the UE application target rate. We propose a two-stage rate allocation algorithm to allocate the eNodeB resources among users and their applications. Finally, we present simulation results for the performance of our rate allocation algorithm.
Multi-user protocols with access control for computational privacy in public clouds
Venue: arXiv cs.CR 2014
Year: 2014

Computational privacy is a property of cryptographic system that ensures the privacy of data being processed at an untrusted server. Fully Homomorphic Encryption Schemes (FHE) promise to provide such property. Contemporary FHE schemes are suited for applications that have single user and server. In reality many of the cloud applications involve multiple users with various degrees of trust and the server need not necessarily be aware of it too. We present a Complementary Key Pairs technique and protocols based on that to scale any generic FHE schemes to multi user scenarios. We also use such technique along with FHE to show how attribute based access control can be achieved while server being oblivious of the same. We analyze the protocols and their security. Our protocols don't make any assumptions on how FHE scheme itself works.
Energy Efficiency of Cross-Tier Base Station Cooperation in Heterogeneous Cellular Networks
Venue: arXiv cs.IT 2014
Year: 2014

Heterogeneous cellular networks (HetNets) are to be deployed for future wireless communication to meet the ever-increasing mobile traffic demand. However, the dense and random deployment of small cells and their uncoordinated operation raise important concerns about energy efficiency. Base station (BS) cooperation is set to play a key role in managing interference in the HetNets. In this paper, we consider BS cooperation in the downlink HetNets where BSs from different tiers within the respective cooperative clusters jointly transmit the same data to a typical user, and further optimize the energy efficiency performance. First, based on the proposed clustering model, we derive the spatial average rate using tools from stochastic geometry. Furthermore, we formulate a power minimization problem with a minimum spatial average rate constraint and derive an approximate result of the optimal received signal strength (RSS) thresholds. Building upon these results, we effectively address the problem of how to design appropriate RSS thresholds, taking into account the trade-off between spatial average rate and energy efficiency. Simulations show that our proposed clustering model is more energy-saving than the geometric clustering model, and under our proposed clustering model, deploying a two-tier HetNet is significantly more energy-saving compared to a macro-only network.
Communication Complexity of the Fast Multipole Method and its Algebraic Variants
Venue: arXiv cs.DC 2014
Year: 2014

A combination of hierarchical tree-like data structures and data access patterns from fast multipole methods and hierarchical low-rank approximation of linear operators from H-matrix methods appears to form an algorithmic path forward for efficient implementation of many linear algebraic operations of scientific computing at the exascale. The combination provides asymptotically optimal computational and communication complexity and applicability to large classes of operators that commonly arise in scientific computing applications. A convergence of the mathematical theories of the fast multipole and H-matrix methods has been underway for over a decade. We recap this mathematical unification and describe implementation aspects of a hybrid of these two compelling hierarchical algorithms on hierarchical distributed-shared memory architectures, which are likely to be the first to reach the exascale. We present a new communication complexity estimate for fast multipole methods on such architectures. We also show how the data structures and access patterns of H-matrices for low-rank operators map onto those of fast multipole, leading to an algebraically generalized form of fast multipole that compromises none of its architecturally ideal properties.
MOOCdb: Developing Standards and Systems to Support MOOC Data Science
Venue: arXiv cs.IR 2014
Year: 2014

We present a shared data model for enabling data science in Massive Open Online Courses (MOOCs). The model captures students interactions with the online platform. The data model is platform agnostic and is based on some basic core actions that students take on an online learning platform. Students usually interact with the platform in four different modes: Observing, Submitting, Collaborating and giving feedback. In observing mode students are simply browsing the online platform, watching videos, reading material, reading book or watching forums. In submitting mode, students submit information to the platform. This includes submissions towards quizzes, homeworks, or any assessment modules. In collaborating mode students interact with other students or instructors on forums, collaboratively editing wiki or chatting on google hangout or other hangout venues. With this basic definitions of activities, and a data model to store events pertaining to these activities, we then create a common terminology to map Coursera and edX data into this shared data model. This shared data model called MOOCdb becomes the foundation for a number of collaborative frameworks that enable progress in data science without the need to share the data.
Perceptual Quality of Video with Periodic Frame Rate and Quantization Variation-Subjective Studies and Analytical Modeling
Venue: arXiv cs.MM 2014
Year: 2014

In networked video applications, the frame rate (FR) and quantization stepsize (QS) of a compressed video are often adapted in response to the changes of the available bandwidth. It is important to understand how do the variation of FR and QS and their variation pattern affect the video quality. In this paper, we investigate the impact of temporal variation of FR and QS on the perceptual video quality. Among all possible variation patterns, we focus on videos in which two FR's (or QS's) alternate over a fixed interval. We explore the human responses to such variation by conducting subjective evaluation of test videos with different variation magnitudes and frequencies. We further analyze statistical significance of the impact of variation magnitude, variation frequency, video content, and their interactions. By analyzing the subjective ratings, we propose two models for predicting the quality of video with alternating FR and QS, respectively, The proposed models have simple mathematical forms with a few content-dependent parameters. The models fit the measured data very well using parameters determined by least square fitting with the measured data. We further propose some guidelines for adaptation of FR and QS based on trends observed from subjective test results.
Stochastically timed predicate-based communication primitives for autonomic computing
Venue: arXiv cs.PL 2014
Year: 2014

Predicate-based communication allows components of a system to send messages and requests to ensembles of components that are determined at execution time through the evaluation of a predicate, in a multicast fashion. Predicate-based communication can greatly simplify the programming of autonomous and adaptive systems. We present a stochastically timed extension of the Software Component Ensemble Language (SCEL) that was introduced in previous work. Such an extension raises a number of non-trivial design and formal semantics issues with different options as possible solutions at different levels of abstraction. We discuss four of these options, of which two in more detail. We provide a formal semantics definition and an illustration of the use of the language modeling a bike sharing system, together with some preliminary analysis of the system performance.
RuleCNL: A Controlled Natural Language for Business Rule Specifications
Venue: arXiv cs.SE 2014
Year: 2014

Business rules represent the primary means by which companies define their business, perform their actions in order to reach their objectives. Thus, they need to be expressed unambiguously to avoid inconsistencies between business stakeholders and formally in order to be machine-processed. A promising solution is the use of a controlled natural language (CNL) which is a good mediator between natural and formal languages. This paper presents RuleCNL, which is a CNL for defining business rules. Its core feature is the alignment of the business rule definition with the business vocabulary which ensures traceability and consistency with the business domain. The RuleCNL tool provides editors that assist end-users in the writing process and automatic mappings into the Semantics of Business Vocabulary and Business Rules (SBVR) standard. SBVR is grounded in first order logic and includes constructs called semantic formulations that structure the meaning of rules.
A composable language for action models
Venue: arXiv cs.LO 2014
Year: 2014

Action models are semantic structures similar to Kripke models that represent a change in knowledge in an epistemic setting. Whereas the language of action model logic embeds the semantic structure of an action model directly within the language, this paper introduces a language that represents action models using syntactic operators inspired by relational actions. This language admits an intuitive description of the action models it represents, and we show in several settings that it is sufficient to represent any action model up to a given modal depth and to represent the results of action model synthesis, and give a sound and complete axiomatisation in some of these settings.
Linear time Constructions of some $d$-Restriction Problems
Venue: arXiv cs.DM 2014
Year: 2014

We give new linear time globally explicit constructions for perfect hash families, cover-free families and separating hash functions.
From XML Schema to JSON Schema: Translation with CHR
Venue: arXiv cs.DB 2014
Year: 2014

Despite its rising popularity as data format especially for web services, the software ecosystem around the JavaScript Object Notation (JSON) is not as widely distributed as that of XML. For both data formats there exist schema languages to specify the structure of instance documents, but there is currently no opportunity to translate already existing XML Schema documents into equivalent JSON Schemas. In this paper we introduce an implementation of a language translator. It takes an XML Schema and creates its equivalent JSON Schema document. Our approach is based on Prolog and CHR. By unfolding the XML Schema document into CHR constraints, it is possible to specify the concrete translation rules in a declarative way.
An extended target tracking model with multiple random matrices and unified kinematics
Venue: arXiv cs.SY 2014
Year: 2014

This paper presents a model for tracking of extended targets, where each target is represented by a given number of elliptic subobjects. A gamma Gaussian inverse Wishart implementation is derived, and necessary approximations are suggested to alleviate the data association complexity. A simulation study shows the merits of the model compared to previous work on the topic.
Fault-Tolerant, but Paradoxical Path-Finding in Physical and Conceptual Systems
Venue: arXiv cs.SE 2014
Year: 2014

We report our initial investigations into reliability and path-finding based models and propose future areas of interest. Inspired by broken sidewalks during on-campus construction projects, we develop two models for navigating this "unreliable network." These are based on a concept of "accumulating risk" backward from the destination, and both operate on directed acyclic graphs with a probability of failure associated with each edge. The first serves to introduce and has faults addressed by the second, more conservative model. Next, we show a paradox when these models are used to construct polynomials on conceptual networks, such as design processes and software development life cycles. When the risk of a network increases uniformly, the most reliable path changes from wider and longer to shorter and narrower. If we let professional inexperience--such as with entry level cooks and software developers--represent probability of edge failure, does this change in path imply that the novice should follow instructions with fewer "back-up" plans, yet those with alternative routes should be followed by the expert?
Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency
Venue: arXiv cs.CV 2014
Year: 2014

This paper addresses the problem of semantic part parsing (segmentation) of cars, i.e.assigning every pixel within the car to one of the parts (e.g.body, window, lights, license plates and wheels). We formulate this as a landmark identification problem, where a set of landmarks specifies the boundaries of the parts. A novel mixture of graphical models is proposed, which dynamically couples the landmarks to a hierarchy of segments. When modeling pairwise relation between landmarks, this coupling enables our model to exploit the local image contents in addition to spatial deformation, an aspect that most existing graphical models ignore. In particular, our model enforces appearance consistency between segments within the same part. Parsing the car, including finding the optimal coupling between landmarks and segments in the hierarchy, is performed by dynamic programming. We evaluate our method on a subset of PASCAL VOC 2010 car images and on the car subset of 3D Object Category dataset (CAR3D). We show good results and, in particular, quantify the effectiveness of using the segment appearance consistency in terms of accuracy of part localization and segmentation.
Optimization Methods for Convolutional Sparse Coding
Venue: arXiv cs.CV 2014
Year: 2014

Sparse and convolutional constraints form a natural prior for many optimization problems that arise from physical processes. Detecting motifs in speech and musical passages, super-resolving images, compressing videos, and reconstructing harmonic motions can all leverage redundancies introduced by convolution. Solving problems involving sparse and convolutional constraints remains a difficult computational problem, however. In this paper we present an overview of convolutional sparse coding in a consistent framework. The objective involves iteratively optimizing a convolutional least-squares term for the basis functions, followed by an L1-regularized least squares term for the sparse coefficients. We discuss a range of optimization methods for solving the convolutional sparse coding objective, and the properties that make each method suitable for different applications. In particular, we concentrate on computational complexity, speed to ε convergence, memory usage, and the effect of implied boundary conditions. We present a broad suite of examples covering different signal and application domains to illustrate the general applicability of convolutional sparse coding, and the efficacy of the available optimization methods.
Music and Vocal Separation Using Multi-Band Modulation Based Features
Venue: arXiv cs.SD 2014
Year: 2014

The potential use of non-linear speech features has not been investigated for music analysis although other commonly used speech features like Mel Frequency Ceptral Coefficients (MFCC) and pitch have been used extensively. In this paper, we assume an audio signal to be a sum of modulated sinusoidal and then use the energy separation algorithm to decompose the audio into amplitude and frequency modulation components using the non-linear Teager-Kaiser energy operator. We first identify the distribution of these non-linear features for music only and voice only segments in the audio signal in different Mel spaced frequency bands and show that they have the ability to discriminate. The proposed method based on Kullback-Leibler divergence measure is evaluated using a set of Indian classical songs from three different artists. Experimental results show that the discrimination ability is evident in certain low and mid frequency bands (200 - 1500 Hz).
FrameNet CNL: a Knowledge Representation and Information Extraction Language
Venue: arXiv cs.CL 2014
Year: 2014

The paper presents a FrameNet-based information extraction and knowledge representation framework, called FrameNet-CNL. The framework is used on natural language documents and represents the extracted knowledge in a tailor-made Frame-ontology from which unambiguous FrameNet-CNL paraphrase text can be generated automatically in multiple languages. This approach brings together the fields of information extraction and CNL, because a source text can be considered belonging to FrameNet-CNL, if information extraction parser produces the correct knowledge representation as a result. We describe a state-of-the-art information extraction parser used by a national news agency and speculate that FrameNet-CNL eventually could shape the natural language subset used for writing the newswire articles.
A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations
Venue: arXiv cs.CV 2014
Year: 2014

Automated Lymph Node (LN) detection is an important clinical diagnostic task but very challenging due to the low contrast of surrounding structures in Computed Tomography (CT) and to their varying sizes, poses, shapes and sparsely distributed locations. State-of-the-art studies show the performance range of 52.9% sensitivity at 3.1 false-positives per volume (FP/vol.), or 60.9% at 6.1 FP/vol. for mediastinal LN, by one-shot boosting on 3D HAAR features. In this paper, we first operate a preliminary candidate generation stage, towards 100% sensitivity at the cost of high FP levels (40 per patient), to harvest volumes of interest (VOI). Our 2.5D approach consequently decomposes any 3D VOI by resampling 2D reformatted orthogonal views N times, via scale, random translations, and rotations with respect to the VOI centroid coordinates. These random views are then used to train a deep Convolutional Neural Network (CNN) classifier. In testing, the CNN is employed to assign LN probabilities for all N random views that can be simply averaged (as a set) to compute the final classification probability per VOI. We validate the approach on two datasets: 90 CT volumes with 388 mediastinal LNs and 86 patients with 595 abdominal LNs. We achieve sensitivities of 70%/83% at 3 FP/vol. and 84%/90% at 6 FP/vol. in mediastinum and abdomen respectively, which drastically improves over the previous state-of-the-art work.
A multi-level soft frequency reuse technique for wireless communication systems
Venue: arXiv cs.IT 2014
Year: 2014

A multi-level soft frequency reuse (ML-SFR) scheme and a resource allocation methodology are proposed for wireless communication systems in this letter. In the proposed ML-SFR scheme, there are 2N power density limit levels, achieving better interference pattern and further improving the cell edge and overall data rate, compared to the traditional 2-level SFR scheme. The detailed design of an 8-level SFR scheme is demonstrated. Numeral results show that the cell edge spectrum efficiency is increased to 5 times of that of reuse 1 and the overall spectrum efficiency is improved by 31%. ML-SFR can be utilized in the current 4G system and would be a candidate key technology for future 5G systems.
A new approach for formal behavioral modeling of protection services in antivirus systems
Venue: arXiv cs.SE 2014
Year: 2014

Formal method techniques provides a suitable platform for the software development in software systems. Formal methods and formal verification is necessary to prove the correctness and improve performance of software systems in various levels of design and implementation, too. Security Discussion is an important issue in computer systems. Since the antivirus applications have very important role in computer systems security, verifying these applications is very essential and necessary. In this paper, we present four new approaches for antivirus system behavior and a behavioral model of protection services in the antivirus system is proposed. We divided the behavioral model in to preventive behavior and control behavior and then we formal these behaviors. Finally by using some definitions we explain the way these behaviors are mapped on each other by using our new approaches.
Rendezvous of Distance-aware Mobile Agents in Unknown Graphs
Venue: arXiv cs.DS 2014
Year: 2014

We study the problem of rendezvous of two mobile agents starting at distinct locations in an unknown graph. The agents have distinct labels and walk in synchronous steps. However the graph is unlabelled and the agents have no means of marking the nodes of the graph and cannot communicate with or see each other until they meet at a node. When the graph is very large we want the time to rendezvous to be independent of the graph size and to depend only on the initial distance between the agents and some local parameters such as the degree of the vertices, and the size of the agent's label. It is well known that even for simple graphs of degree $Δ$, the rendezvous time can be exponential in $Δ$ in the worst case. In this paper, we introduce a new version of the rendezvous problem where the agents are equipped with a device that measures its distance to the other agent after every step. We show that these \emph{distance-aware} agents are able to rendezvous in any unknown graph, in time polynomial in all the local parameters such the degree of the nodes, the initial distance $D$ and the size of the smaller of the two agent labels $l = \min(l_1, l_2)$. Our algorithm has a time complexity of $O(Δ(D+\log{l}))$ and we show an almost matching lower bound of $Ω(Δ(D+\log{l}/\logΔ))$ on the time complexity of any rendezvous algorithm in our scenario. Further, this lower bound extends existing lower bounds for the general rendezvous problem without distance awareness.
Isogeometric Boundary Element Method with Hierarchical Matrices
Venue: arXiv cs.NA 2014
Year: 2014

In this work we address the complexity problem of the isogeometric Boundary Element Method by proposing a collocation scheme for practical problems in linear elasticity and the application of hierarchical matrices. For mixed boundary value problems, a block system of matrices similar to Galerkin formulations is constructed allowing an effective application of that matrix format. We introduce a strategy for the geometric bisection of surfaces based on NURBS patches. The approximation of system matrices is carried out by means of kernel interpolation. Numerical results are shown that prove the success of the formulation.