OpenRaiser/Intern-Atlas huggingface dataset:
Joint Link Scheduling and Brightness Control for Greening VLC-based Indoor Access Networks
Venue: arXiv cs.NI 2015
Year: 2015

Demands for broadband wireless access services is expected to outstrip the spectrum capacity in the near-term - "spectrum crunch". Deploying additional femotocells to address this challenge is cost-inefficient, due to the backhaul challenge and the exorbitant system maintenance. According to an Alcatel-Lucent report, most of the mobile Internet access traffic happens indoor. Leveraging power line communication and the available indoor infrastructure, visible light communication (VLC) can be utilized with small one-time cost. VLC also facilitates the great advantage of being able to jointly perform illumination and communications, and little extra power beyond illumination is required to empower communications, thus rendering wireless access with small power consumption. In this study, we investigate the problem of minimizing total power consumption of a general multi-user VLC indoor network while satisfying users' traffic demands and maintaining an acceptable level of illumination. We utilize the column generation method to obtain an $ε$-bounded solution. Several practical implementation issues are integrated with the proposed algorithm, including different configurations of light source and ways of resolving the interference among VLC links. Through extensive simulations, we show that our approach reduces the power consumption of the state-of-art VLC-based scheduling algorithms by more than 60\% while maintaining the required illumination.
Secure Routing in Multihop Wireless Ad-hoc Networks with Decode-and-Forward Relaying
Venue: arXiv cs.IT 2015
Year: 2015

In this paper, we study the problem of secure routing in a multihop wireless ad-hoc network in the presence of randomly distributed eavesdroppers. Specifically, the locations of the eavesdroppers are modeled as a homogeneous Poisson point process (PPP) and the source-destination pair is assisted by intermediate relays using the decode-and-forward (DF) strategy. We analytically characterize the physical layer security performance of any chosen multihop path using the end-to-end secure connection probability (SCP) for both colluding and non-colluding eavesdroppers. To facilitate finding an efficient solution to secure routing, we derive accurate approximations of the SCP. Based on the SCP approximations, we study the secure routing problem which is defined as finding the multihop path having the highest SCP. A revised Bellman-Ford algorithm is adopted to find the optimal path in a distributed manner. Simulation results demonstrate that the proposed secure routing scheme achieves nearly the same performance as exhaustive search.
Using consumer behavior data to reduce energy consumption in smart homes
Venue: arXiv cs.CY 2015
Year: 2015

This paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life smart home event data. The performance of the proposed algorithm is compared to existing algorithms regarding completeness/correctness of the results, run times as well as memory consumption and elaborates on the shortcomings of the different solutions. We also present a recommender system based on the developed algorithm that provides recommendations to the users to reduce their energy consumption. The recommender system was deployed to a set of test homes. The test participants rated the impact of the recommendations on their comfort. We used this feedback to adjust the system parameters and make it more accurate during a second test phase.
An Algebraic Geometric Approach to Nivat's Conjecture
Venue: arXiv cs.DM 2015
Year: 2015

We study multidimensional configurations (infinite words) and subshifts of low pattern complexity using tools of algebraic geometry. We express the configuration as a multivariate formal power series over integers and investigate the setup when there is a non-trivial annihilating polynomial: a non-zero polynomial whose formal product with the power series is zero. Such annihilator exists, for example, if the number of distinct patterns of some finite shape D in the configuration is at most the size |D| of the shape. This is our low pattern complexity assumption. We prove that the configuration must be a sum of periodic configurations over integers, possibly with unbounded values. As a specific application of the method we obtain an asymptotic version of the well-known Nivat's conjecture: we prove that any two-dimensional, non-periodic configuration can satisfy the low pattern complexity assumption with respect to only finitely many distinct rectangular shapes D.
Fundamental Results for a Generic Implementation of Barriers using Optical Interconnects
Venue: arXiv cs.DC 2015
Year: 2015

In this report, we report some fundamental results and bounds on the number of messages and storage required to implement barriers using futuristic on-chip optical and RF networks. We prove that it is necessary to maintain a count to at least N (number of threads) in memory, broadcast the barrier id at least once, and if we elect a co-ordinator, we can reduce the number of messages by a factor of O(N ).
An Adaptive Secret Key-directed Cryptographic Scheme for Secure Transmission in Wireless Sensor Networks
Venue: arXiv cs.CR 2015
Year: 2015

Wireless Sensor Networks (WSNs) are memory and bandwidth limited networks whose main goals are to maximize the network lifetime and minimize the energy consumption and transmission cost. To achieve these goals, dif ferent techniques of compression and clustering have been used. However, security is an open and major issue in WSNs for which different approaches are used, both in centralized and distributed WSNs' environments. This paper presents an adaptive cryptographic scheme for secure transmission of various sensitive parameters, sensed by wireless sensors to the fusion center for further processing in WSNs such as military networks. The proposed method encrypts the sensitive captured data of sensor nodes using various encryption procedures (bitxor operation, bits shuffling, and secret key based encryption) and then sends it to the fusion center. At the fusion center, the received encrypted data is decrypted for taking further necessary actions. The experimental results with complexity analysis, validate the effectiveness and feasibility of the proposed method in terms of security in WSNs.
Analog Multiple Descriptions: A Zero-Delay Source-Channel Coding Approach
Venue: arXiv cs.IT 2015
Year: 2015

This paper extends the well-known source coding problem of multiple descriptions, in its general and basic setting, to analog source-channel coding scenarios. Encoding-decoding functions that optimally map between the (possibly continuous valued) source and the channel spaces are numerically derived. The main technical tool is a non-convex optimization method, namely, deterministic annealing, which has recently been successfully used in other mapping optimization problems. The obtained functions exhibit several interesting structural properties, map multiple source intervals to the same interval in the channel space, and consistently outperform the known competing mapping techniques.
Interface Between Market and Science
Venue: arXiv cs.HC 2015
Year: 2015

At the beginning, programming was inspired by the search of the best solutions. At that time some fundamental stones like famous languages and object oriented and structured programming were laid. It was found later that applications could generate huge profits; after it marketing departments started to decide what was right and wrong. Programs are ruled by developers but declared user-friendly; millions of users are going mad trying to get the needed results from these applications. Research goes on and new results can be opposite to business view. History shows that not science has to adjust to business, but eventually business will have to adapt to the results of the research work.
CVC: The Contourlet Video Compression algorithm for real-time applications
Venue: arXiv cs.MM 2015
Year: 2015

Nowadays, real-time video communication over the internet through video conferencing applications has become an invaluable tool in everyone's professional and personal life. This trend underlines the need for video coding algorithms that provide acceptable quality on low bitrates and can support various resolutions inside the same stream in order to cope with limitations on computational resources and network bandwidth. In this work, a novel scalable video coding algorithm based on the contourlet transform is presented. The algorithm utilizes both lossy and lossless methods in order to achieve compression. One of its most notable features is that due to the transform utilised, it does not suffer from blocking artifacts that occur with many widely adopted compression algorithms. The proposed algorithm takes advantage of the vast computational capabilities of modern GPUs, in order to achieve real-time performance and provide satisfactory encoding and decoding times at relatively low cost, making it suitable for applications like video conferencing. Experiments show that the proposed algorithm performs satisfactorily in terms of compression ratio and speed, while it outperforms standard methods in terms of perceptual quality on lower bitrates.
Online Vision- and Action-Based Object Classification Using Both Symbolic and Subsymbolic Knowledge Representations
Venue: arXiv cs.AI 2015
Year: 2015

If a robot is supposed to roam an environment and interact with objects, it is often necessary to know all possible objects in advance, so that a database with models of all objects can be generated for visual identification. However, this constraint cannot always be fulfilled. Due to that reason, a model based object recognition cannot be used to guide the robot's interactions. Therefore, this paper proposes a system that analyzes features of encountered objects and then uses these features to compare unknown objects to already known ones. From the resulting similarity appropriate actions can be derived. Moreover, the system enables the robot to learn object categories by grouping similar objects or by splitting existing categories. To represent the knowledge a hybrid form is used, consisting of both symbolic and subsymbolic representations.
Automatic Taxonomy Extraction from Query Logs with no Additional Sources of Information
Venue: arXiv cs.CL 2015
Year: 2015

Search engine logs store detailed information on Web users interactions. Thus, as more and more people use search engines on a daily basis, important trails of users common knowledge are being recorded in those files. Previous research has shown that it is possible to extract concept taxonomies from full text documents, while other scholars have proposed methods to obtain similar queries from query logs. We propose a mixture of both lines of research, that is, mining query logs not to find related queries nor query hierarchies, but actual term taxonomies that could be used to improve search engine effectiveness and efficiency. As a result, in this study we have developed a method that combines lexical heuristics with a supervised classification model to successfully extract hyponymy relations from specialization search patterns revealed from log missions, with no additional sources of information, and in a language independent way.
Discretizations of isometries
Venue: arXiv cs.DM 2015
Year: 2015

This paper deals with the dynamics of discretizations of isometries of $\mathbf R^n$, and more precisely the density of the successive images of $\mathbf Z^n$ by the discretizations of a generic sequence of isometries. We show that this density tends to 0 as the time goes to infinity. Thus, in general, all the information of a numerical image will be lost by applying many times a naive algorithm of rotation.
A Primer on Neural Network Models for Natural Language Processing
Venue: arXiv cs.CL 2015
Year: 2015

Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results. This tutorial surveys neural network models from the perspective of natural language processing research, in an attempt to bring natural-language researchers up to speed with the neural techniques. The tutorial covers input encoding for natural language tasks, feed-forward networks, convolutional networks, recurrent networks and recursive networks, as well as the computation graph abstraction for automatic gradient computation.
Rank Aggregation: New Bounds for MCx
Venue: arXiv cs.DM 2015
Year: 2015

The rank aggregation problem has received significant recent attention within the computer science community. Its applications today range far beyond the original aim of building metasearch engines to problems in machine learning, recommendation systems and more. Several algorithms have been proposed for these problems, and in many cases approximation guarantees have been proven for them. However, it is also known that some Markov chain based algorithms (MC1, MC2, MC3, MC4) perform extremely well in practice, yet had no known performance guarantees. We prove supra-constant lower bounds on approximation guarantees for all of them. We also raise the lower bound for sorting by Copeland score from 3/2 to 2 and prove an upper bound of 11, before showing that in particular ways, MC4 can nevertheless be seen as a generalization of Copeland score.
Design and Analysis of a Single-Camera Omnistereo Sensor for Quadrotor Micro Aerial Vehicles (MAVs)
Venue: arXiv cs.CV 2015
Year: 2015

We describe the design and 3D sensing performance of an omnidirectional stereo-vision system (omnistereo) as applied to Micro Aerial Vehicles (MAVs). The proposed omnistereo model employs a monocular camera that is co-axially aligned with a pair of hyperboloidal mirrors (folded catadioptric configuration). We show that this arrangement is practical for performing stereo-vision when mounted on top of propeller-based MAVs characterized by low payloads. The theoretical single viewpoint (SVP) constraint helps us derive analytical solutions for the sensor's projective geometry and generate SVP-compliant panoramic images to compute 3D information from stereo correspondences (in a truly synchronous fashion). We perform an extensive analysis on various system characteristics such as its size, catadioptric spatial resolution, field-of-view. In addition, we pose a probabilistic model for uncertainty estimation of the depth from triangulation for skew back-projection rays. We expect to motivate the reproducibility of our solution since it can be adapted (optimally) to other catadioptric-based omnistereo vision applications.
Prospect Pricing in Cognitive Radio Networks
Venue: arXiv cs.GT 2015
Year: 2015

Advances in cognitive radio networks have primarily focused on the design of spectrally agile radios and novel spectrum sharing techniques that are founded on Expected Utility Theory (EUT). In this paper, we consider the development of novel spectrum sharing algorithms in such networks taking into account human psychological behavior of the end-users, which often deviates from EUT. Specifically, we consider the impact of end-user decision making on pricing and management of radio resources in a cognitive radio enabled network when there is uncertainty in the Quality of Service (QoS) guarantees offered by the Service Provider (SP). Using Prospect Theory (a Nobel-Prize-winning behavioral economic theory that captures human decision making and its deviation from EUT), we design data pricing and channel allocation algorithms for use in cognitive radio networks by formulating a game theoretic analysis of the interplay between the price offerings, bandwidth allocation by the SP and the service choices made by end-users. We show that, when the end-users under-weight the service guarantee, they tend to reject the offer which results in under-utilization of radio resources and revenue loss. We propose prospect pricing, a pricing mechanism that can make the system robust to decision making and improve radio resource management. We present analytical results as well as preliminary human subject studies with video QoS.
Łukasiewicz μ-calculus
Venue: arXiv cs.LO 2015
Year: 2015

The paper explores properties of the Łukasiewicz μ-calculus, or Łμ for short, an extension of Łukasiewicz logic with scalar multiplication and least and greatest fixed-point operators (for monotone formulas). We observe that Łμ terms, with $n$ variables, define monotone piecewise linear functions from $[0, 1]^n$ to $[0, 1]$. Two effective procedures for calculating the output of Łμ terms on rational inputs are presented. We then consider the Łukasiewicz modal μ-calculus, which is obtained by adding box and diamond modalities to Łμ. Alternatively, it can be viewed as a generalization of Kozen's modal μ-calculus adapted to probabilistic nondeterministic transition systems (PNTS's). We show how properties expressible in the well-known logic PCTL can be encoded as Łukasiewicz modal μ-calculus formulas. We also show that the algorithms for computing values of Łukasiewicz μ-calculus terms provide automatic (albeit impractical) methods for verifying Łukasiewicz modal μ-calculus properties of finite rational PNTS's.
Efficient Hand Articulations Tracking using Adaptive Hand Model and Depth map
Venue: arXiv cs.CV 2015
Year: 2015

Real-time hand articulations tracking is important for many applications such as interacting with virtual / augmented reality devices or tablets. However, most of existing algorithms highly rely on expensive and high power-consuming GPUs to achieve real-time processing. Consequently, these systems are inappropriate for mobile and wearable devices. In this paper, we propose an efficient hand tracking system which does not require high performance GPUs. In our system, we track hand articulations by minimizing discrepancy between depth map from sensor and computer-generated hand model. We also initialize hand pose at each frame using finger detection and classification. Our contributions are: (a) propose adaptive hand model to consider different hand shapes of users without generating personalized hand model; (b) improve the highly efficient frame initialization for robust tracking and automatic initialization; (c) propose hierarchical random sampling of pixels from each depth map to improve tracking accuracy while limiting required computations. To the best of our knowledge, it is the first system that achieves both automatic hand model adjustment and real-time tracking without using GPUs.
Cyclic Codes from Two-Prime Generalized Cyclotomic Sequences of Order 6
Venue: arXiv cs.IT 2015
Year: 2015

Cyclic codes have wide applications in data storage systems and communication systems. Employing two-prime Whiteman generalized cyclotomic sequences of order 6, we construct several classes of cyclic codes over the finite field GF}(q) and give their generator polynomials. And we also calculate the minimum distance of some cyclic codes and give lower bounds of the minimum distance for some other cyclic codes.
Learning about End-User Development for Smart Homes by "Eating Our Own Dog Food"
Venue: arXiv cs.HC 2015
Year: 2015

SPOK is an End-User Development Environment that permits people to monitor, control, and configure smart home services and devices. SPOK has been deployed for more than 4 months in the homes of 5 project team members for testing and refinement, prior to longitudinal experiments in the homes of families not involved in the project. This article reports on the lessons learned in this initial deployment.
RAID: A Relation-Augmented Image Descriptor
Venue: arXiv cs.GR 2015
Year: 2015

As humans, we regularly interpret images based on the relations between image regions. For example, a person riding object X, or a plank bridging two objects. Current methods provide limited support to search for images based on such relations. We present RAID, a relation-augmented image descriptor that supports queries based on inter-region relations. The key idea of our descriptor is to capture the spatial distribution of simple point-to-region relationships to describe more complex relationships between two image regions. We evaluate the proposed descriptor by querying into a large subset of the Microsoft COCO database and successfully extract nontrivial images demonstrating complex inter-region relations, which are easily missed or erroneously classified by existing methods.
On The Evolution Of User Support Topics in Computational Science and Engineering Software
Venue: arXiv cs.OH 2015
Year: 2015

We investigate ten years of user support emails in the large-scale solver library PETSc in order to identify changes in user requests. For this purpose we assign each email thread to one or several categories describing the type of support request. We find that despite several changes in hardware architecture as well programming models, the relative share of emails for the individual categories does not show a notable change over time. This is particularly remarkable as the total communication volume has increased four-fold in the considered time frame, indicating a considerable growth of the user base. Our data also demonstrates that user support cannot be substituted with what is often referred to as 'better documentation' and that the involvement of core developers in user support is essential.
Deconstructing Bataknese Gorga Computationally
Venue: arXiv cs.CG 2015
Year: 2015

The carved and painted decorations in traditional Batak houses and buildings, gorga, are the source of their exoticism. There are no identical patterns of the ornaments within Batak houses and the drawings are closely related to the way ancient Batak capture the dynamicity of the growing 'tree of life', one of central things within their cosmology and mythology. The survey of ornaments of Batak houses and buildings in Northern Sumatera Indonesia has made us possible to observe the complex pattern. The fractal dimensions of the geometrical shapes in gorga are calculated and they are conjectured into 1.5-1.6, between the dimensional of a line and a plane. The way gorga is drawn is captured by using some modification to the turtle geometry of L-System model, a popular model to model the dynamics of growing plants. The result is a proposal to see Bataknese gorga as one of traditional heritage that may enrich the studies to the generative art.
Cross-Device Tracking: Matching Devices and Cookies
Venue: arXiv cs.LG 2015
Year: 2015

The number of computers, tablets and smartphones is increasing rapidly, which entails the ownership and use of multiple devices to perform online tasks. As people move across devices to complete these tasks, their identities becomes fragmented. Understanding the usage and transition between those devices is essential to develop efficient applications in a multi-device world. In this paper we present a solution to deal with the cross-device identification of users based on semi-supervised machine learning methods to identify which cookies belong to an individual using a device. The method proposed in this paper scored third in the ICDM 2015 Drawbridge Cross-Device Connections challenge proving its good performance.