OpenRaiser/Intern-Atlas huggingface dataset:
Efficient Symbol Detection for the FSO IM/DD System with Automatic and Adaptive Threshold Adjustment: The Multi-level PAM Case
Venue: arXiv cs.IT 2015
Year: 2015

To detect M-ary pulse amplitude modulation signals reliably in an FSO communication system, the receiver requires accurate knowledge about the instantaneous channel attenuation on the signal. We derive here an optimum, symbol-by-symbol receiver that jointly estimates the attenuation with the help of past detected data symbols and detects the data symbols accordingly. Few pilot symbols are required, resulting in high spectral efficiency. Detection can be performed with a very low complexity. From both theoretical analysis and simulation, we show that as the number of the detected data symbols used for estimating the channel attenuation increases, the bit error probability of our receiver approaches that of detection with perfect channel knowledge.
A Dynamic Spectrum Access on SDR for IEEE 802.15.4 networks
Venue: arXiv cs.NI 2015
Year: 2015

Our paper deals with a Dynamic Spectrum Access (DSA) and its implementation on a Software Defined Radio (SDR) for IEEE 802.15.4e Networks. The network nodes select the carrier frequency after Energy-Detection based Spectrum Sensing (SS). To ensure frequency hoping between two nodes in IEEE 802.15.4e Network, we propose a synchronization algorithm. We considerate the IEEE 802.15.4e Network is Secondary User (SU), and all other networks are Primary Users (PUs) in unlicensed 868/915 MHz and 2450 MHz bands of a Cognitive Radio (CR). However, the algorithm and the energy-sensor have been implemented over GNU Radio and Universal Software Radio Peripheral (USRP) SDR. In addition, real packet transmissions have been performed in two cases. In the first case, SU communicates in static carrier-frequency, while in the second case with the implemented DSA. For each case, PU transmitter disturbs SU, which calculates Packet Success Rate (PSR) to measure the robustness of a used DSA. The obtained PSR is improved by 80\% when the SU accomplished DSA rather than a static access.
Socio-Spatial Group Queries for Impromptu Activity Planning
Venue: arXiv cs.DS 2015
Year: 2015

The development and integration of social networking services and smartphones have made it easy for individuals to organize impromptu social activities anywhere and anytime. Main challenges arising in organizing impromptu activities are mostly due to the requirements of making timely invitations in accordance with the potential activity locations, corresponding to the locations of and the relationship among the candidate attendees. Various combinations of candidate attendees and activity locations create a large solution space. Thus, in this paper, we propose Multiple Rally-Point Social Spatial Group Query (MRGQ), to select an appropriate activity location for a group of nearby attendees with tight social relationships. Although MRGQ is NP-hard, the number of attendees in practice is usually small enough such that an optimal solution can be found efficiently. Therefore, we first propose an Integer Linear Programming optimization model for MRGQ. We then design an efficient algorithm, called MAGS, which employs effective search space exploration and pruning strategies to reduce the running time for finding the optimal solution. We also propose to further optimize efficiency by indexing the potential activity locations. A user study demonstrates the strength of using MAGS over manual coordination in terms of both solution quality and efficiency. Experimental results on real datasets show that our algorithms can process MRGQ efficiently and significantly outperform other baseline algorithms, including one based on the commercial parallel optimizer IBM CPLEX.
Noise Robustness of a Combined Phase Retrieval and Reconstruction Method for Phase-Contrast Tomography
Venue: arXiv cs.NA 2015
Year: 2015

Classical reconstruction methods for phase-contrast tomography consist of two stages: phase retrieval and tomographic reconstruction. A novel algebraic method combining the two was suggested by Kostenko et al. (Opt. Express, 21, 12185, 2013) and preliminary results demonstrating improved reconstruction compared to a two-stage method given. Using simulated free-space propagation experiments with a single sample-detector distance, we thoroughly compare the novel method with the two-stage method to address limitations of the preliminary results. We demonstrate that the novel method is substantially more robust towards noise; our simulations point to a possible reduction in counting times by an order of magnitude.
Math Search for the Masses: Multimodal Search Interfaces and Appearance-Based Retrieval
Venue: arXiv cs.IR 2015
Year: 2015

We summarize math search engines and search interfaces produced by the Document and Pattern Recognition Lab in recent years, and in particular the min math search interface and the Tangent search engine. Source code for both systems are publicly available. "The Masses" refers to our emphasis on creating systems for mathematical non-experts, who may be looking to define unfamiliar notation, or browse documents based on the visual appearance of formulae rather than their mathematical semantics.
Investigating Causality in Human Behavior from Smartphone Sensor Data: A Quasi-Experimental Approach
Venue: arXiv cs.CY 2015
Year: 2015

Smartphones have become an indispensable part of our daily life. Their improved sensing and computing capabilities bring new opportunities for human behavior monitoring and analysis. Most work so far has been focused on detecting correlation rather than causation among features extracted from smartphone data. However, pure correlation analysis does not offer sufficient understanding of human behavior. Moreover, causation analysis could allow scientists to identify factors that have a causal effect on health and well-being issues, such as obesity, stress, depression and so on and suggest actions to deal with them. Finally, detecting causal relationships in this kind of observational data is challenging since, in general, subjects cannot be randomly exposed to an event. In this article, we discuss the design, implementation and evaluation of a generic quasi-experimental framework for conducting causation studies on human behavior from smartphone data. We demonstrate the effectiveness of our approach by investigating the causal impact of several factors such as exercise, social interactions and work on stress level. Our results indicate that exercising and spending time outside home and working environment have a positive effect on participants stress level while reduced working hours only slightly impact stress.
Adapting Improved Upper Confidence Bounds for Monte-Carlo Tree Search
Venue: arXiv cs.AI 2015
Year: 2015

The UCT algorithm, which combines the UCB algorithm and Monte-Carlo Tree Search (MCTS), is currently the most widely used variant of MCTS. Recently, a number of investigations into applying other bandit algorithms to MCTS have produced interesting results. In this research, we will investigate the possibility of combining the improved UCB algorithm, proposed by Auer et al. (2010), with MCTS. However, various characteristics and properties of the improved UCB algorithm may not be ideal for a direct application to MCTS. Therefore, some modifications were made to the improved UCB algorithm, making it more suitable for the task of game tree search. The Mi-UCT algorithm is the application of the modified UCB algorithm applied to trees. The performance of Mi-UCT is demonstrated on the games of $9\times 9$ Go and $9\times 9$ NoGo, and has shown to outperform the plain UCT algorithm when only a small number of playouts are given, and rougly on the same level when more playouts are available.
Analysis of Network Coding Schemes for Differential Chaos Shift Keying Communication System
Venue: arXiv cs.IT 2015
Year: 2015

In this paper we design network coding schemes for Differential Chaos Shift Keying (DCSK) modulation. In this work, non-coherent chaos-based communication system is used due to its simplicity and robustness to multipath propagation effects, while dispensing with any channel state information knowledge at the receiver. We propose a relay network using network coding and DCSK, where we first present a Physical layer Network Coding (PNC) scheme with two users, $\mathcal{A}$ and $\mathcal{B}$, sharing the same spreading code and bandwidth, while synchronously transmitting their signals to the relay node $\mathcal{R}$. We show that the main drawback of this design in multipath channels is the high level of interference in the resultant signal, which severely degrades the system performance. Hence, in order to address this problem, we propose two coding schemes, which separate the users' signals in the frequency or the time domains. We show also in this paper that the performance of the Analog Network Coding (ANC) with DCSK modulation suffers from the same interference problem as the PNC scheme. We present the analytical bit error rate performance for multipath Rayleigh fading channel for the different scenarios and we analyse these schemes in terms of complexity, throughput and link spectral efficiency.
Refinement Type Inference via Horn Constraint Optimization
Venue: arXiv cs.PL 2015
Year: 2015

We propose a novel method for inferring refinement types of higher-order functional programs. The main advantage of the proposed method is that it can infer maximally preferred (i.e., Pareto optimal) refinement types with respect to a user-specified preference order. The flexible optimization of refinement types enabled by the proposed method paves the way for interesting applications, such as inferring most-general characterization of inputs for which a given program satisfies (or violates) a given safety (or termination) property. Our method reduces such a type optimization problem to a Horn constraint optimization problem by using a new refinement type system that can flexibly reason about non-determinism in programs. Our method then solves the constraint optimization problem by repeatedly improving a current solution until convergence via template-based invariant generation. We have implemented a prototype inference system based on our method, and obtained promising results in preliminary experiments.
Sparse 3D convolutional neural networks
Venue: arXiv cs.CV 2015
Year: 2015

We have implemented a convolutional neural network designed for processing sparse three-dimensional input data. The world we live in is three dimensional so there are a large number of potential applications including 3D object recognition and analysis of space-time objects. In the quest for efficiency, we experiment with CNNs on the 2D triangular-lattice and 3D tetrahedral-lattice.
Coordination protocol for inter-operator spectrum sharing based on spectrum usage favors
Venue: arXiv cs.NI 2015
Year: 2015

Currently, mobile network operators are allocated spectrum bands on an exclusive basis. While this approach facilitates interference control, it may also result in low spectrum utilization efficiency. Inter-operator spectrum sharing is a potential method to enhance spectrum utilization. In order to realize it, a protocol to coordinate the actions of operators is needed. We propose a spectrum sharing protocol which is distributed in nature, it does not require operator-specific information exchange and it incurs minimal communication overhead between the operators. Operators are still free to decide whether they share spectrum or not as the protocol is based on the book keeping of spectrum usage favors, asked and received by the operators. We show that operators can enhance their QoS in comparison with traditional orthogonal spectrum allocation while also maintaining reciprocity i.e. no operator benefits over the other in the long run. We demonstrate the usability of the proposed protocol in an indoor deployment scenario with frequent network load variations as expected to have in small cell deployments.
Factors Influencing the Adoption of Cloud Incident Handling Strategy: A Preliminary Study in Malaysia
Venue: arXiv cs.CY 2015
Year: 2015

This study seeks to understand the factors influencing the adoption of an incident handling strategy by organisational cloud service users. We propose a conceptual model that draws upon the Situation Awareness (SA) model and Protection Motivation Theory (PMT) to guide this research. 40 organisational cloud service users in Malaysia were surveyed. We also conduct face-to-face interviews with participants from four of the organisations. Findings from the study indicate that four PMT factors (Perceived Vulnerability, Self-Efficacy, Response Efficacy, and Perceived Severity) have a significantly influence on the adoption of cloud incident handling strategy within the organisations. We, therefore, suggest a successful adoption cloud incident handling strategy by organisational cloud service users involves the nexus between these four PMT factors. We also outline future research required to validate the model.
Resource Allocation in Full-Duplex Communications for Future Wireless Networks
Venue: arXiv cs.IT 2015
Year: 2015

The recent significant progress in realizing full-duplex~(FD) systems has opened up a promising avenue for improving quality of service (QoS) and quality of experience (QoE) in future wireless networks. There is an urgent need to address the diverse set of challenges regarding different aspects of FD network design, theory, and development. In addition to the self-interference cancelation signal processing algorithms, network protocols such as resource management are also essential in the practical design and implementation of FD wireless networks. This article aims to present the latest development and future directions of resource allocation in different full duplex systems by exploring the network resources in different domains, including power, space, frequency, and device dimensions. Four representative application scenarios are considered: FD MIMO networks, FD cooperative networks, FD OFDMA cellular networks, and FD heterogeneous networks. Resource management problems and novel algorithms in these systems are presented, and key open research directions are discussed.
SocIoS API: A data aggregator for accessing user generated content from online social networks
Venue: arXiv cs.SE 2015
Year: 2015

Following the boost in popularity of online social networks, both enterprises and researchers looked for ways to access the social dynamics information and user generated content residing in these spaces. This endeavor, however, presented several challenges caused by the heterogeneity of data and the lack of a common way to access them. The SocIoS framework tries to address these challenges by providing tools that operate on top of multiple popular social networks allowing uniform access to their data. It provides a single access point for aggregating data and functionality from the networks, as well as a set of analytical tools for exploiting them. In this paper we present the SocIoS API, an abstraction layer on top of the social networks exposing operations that encapsulate the functionality of their APIs. Currently, the component provides support for seven social networks and is flexible enough to allow for the seamless addition of more.
Improving Computer-aided Detection using Convolutional Neural Networks and Random View Aggregation
Venue: arXiv cs.CV 2015
Year: 2015

Automated computer-aided detection (CADe) in medical imaging has been an important tool in clinical practice and research. State-of-the-art methods often show high sensitivities but at the cost of high false-positives (FP) per patient rates. We design a two-tiered coarse-to-fine cascade framework that first operates a candidate generation system at sensitivities of $\sim$100% but at high FP levels. By leveraging existing CAD systems, coordinates of regions or volumes of interest (ROI or VOI) for lesion candidates are generated in this step and function as input for a second tier, which is our focus in this study. In this second stage, we generate $N$ 2D (two-dimensional) or 2.5D views via sampling through scale transformations, random translations and rotations with respect to each ROI's centroid coordinates. These random views are used to train deep convolutional neural network (ConvNet) classifiers. In testing, the trained ConvNets are employed to assign class (e.g., lesion, pathology) probabilities for a new set of $N$ random views that are then averaged at each ROI to compute a final per-candidate classification probability. This second tier behaves as a highly selective process to reject difficult false positives while preserving high sensitivities. The methods are evaluated on three different data sets with different numbers of patients: 59 patients for sclerotic metastases detection, 176 patients for lymph node detection, and 1,186 patients for colonic polyp detection. Experimental results show the ability of ConvNets to generalize well to different medical imaging CADe applications and scale elegantly to various data sets. Our proposed methods improve CADe performance markedly in all cases. CADe sensitivities improved from 57% to 70%, from 43% to 77% and from 58% to 75% at 3 FPs per patient for sclerotic metastases, lymph nodes and colonic polyps, respectively.
A Practical Set-Membership Proof for Privacy-Preserving NFC Mobile Ticketing
Venue: arXiv cs.CR 2015
Year: 2015

To ensure the privacy of users in transport systems, researchers are working on new protocols providing the best security guarantees while respecting functional requirements of transport operators. In this paper, we design a secure NFC m-ticketing protocol for public transport that preserves users' anonymity and prevents transport operators from tracing their customers' trips. To this end, we introduce a new practical set-membership proof that does not require provers nor verifiers (but in a specific scenario for verifiers) to perform pairing computations. It is therefore particularly suitable for our (ticketing) setting where provers hold SIM/UICC cards that do not support such costly computations. We also propose several optimizations of Boneh-Boyen type signature schemes, which are of independent interest, increasing their performance and efficiency during NFC transactions. Our m-ticketing protocol offers greater flexibility compared to previous solutions as it enables the post-payment and the off-line validation of m-tickets. By implementing a prototype using a standard NFC SIM card, we show that it fulfils the stringent functional requirement imposed by transport operators whilst using strong security parameters. In particular, a validation can be completed in 184.25 ms when the mobile is switched on, and in 266.52 ms when the mobile is switched off or its battery is flat.
A Survey of Arabic Dialogues Understanding for Spontaneous Dialogues and Instant Message
Venue: arXiv cs.CL 2015
Year: 2015

Building dialogues systems interaction has recently gained considerable attention, but most of the resources and systems built so far are tailored to English and other Indo-European languages. The need for designing systems for other languages is increasing such as Arabic language. For this reasons, there are more interest for Arabic dialogue acts classification task because it a key player in Arabic language understanding to building this systems. This paper surveys different techniques for dialogue acts classification for Arabic. We describe the main existing techniques for utterances segmentations and classification, annotation schemas, and test corpora for Arabic dialogues understanding that have introduced in the literature
Tight Cutoffs for Guarded Protocols with Fairness
Venue: arXiv cs.LO 2015
Year: 2015

Guarded protocols were introduced in a seminal paper by Emerson and Kahlon (2000), and describe systems of processes whose transitions are enabled or disabled depending on the existence of other processes in certain local states. We study parameterized model checking and synthesis of guarded protocols, both aiming at formal correctness arguments for systems with any number of processes. Cutoff results reduce reasoning about systems with an arbitrary number of processes to systems of a determined, fixed size. Our work stems from the observation that existing cutoff results for guarded protocols i) are restricted to closed systems, and ii) are of limited use for liveness properties because reductions do not preserve fairness. We close these gaps and obtain new cutoff results for open systems with liveness properties under fairness assumptions. Furthermore, we obtain cutoffs for the detection of global and local deadlocks, which are of paramount importance in synthesis. Finally, we prove tightness or asymptotic tightness for the new cutoffs.
Codes for Partially Stuck-at Memory Cells
Venue: arXiv cs.IT 2015
Year: 2015

In this work, we study a new model of defect memory cells, called partially stuck-at memory cells, which is motivated by the behavior of multi-level cells in non-volatile memories such as flash memories and phase change memories. If a cell can store the $q$ levels $0, 1, \dots, q-1$, we say that it is partially stuck-at level $s$, where $1 \leq s \leq q-1$, if it can only store values which are at least $s$. We follow the common setup where the encoder knows the positions and levels of the partially stuck-at cells whereas the decoder does not. Our main contribution in the paper is the study of codes for masking $u$ partially stuck-at cells. We first derive lower and upper bounds on the redundancy of such codes. The upper bounds are based on two trivial constructions. We then present three code constructions over an alphabet of size $q$, by first considering the case where the cells are partially stuck-at level $s=1$. The first construction works for $u<q$ and is asymptotically optimal if $u+1$ divides $q$. The second construction uses the reduced row Echelon form of matrices to generate codes for the case $u\geq q$, and the third construction solves the case of arbitrary $u$ by using codes which mask binary stuck-at cells. We then show how to generalize all constructions to arbitrary stuck levels. Furthermore, we study the dual defect model in which cells cannot reach higher levels, and show that codes for partially stuck-at cells can be used to mask this type of defects as well. Lastly, we analyze the capacity of the partially stuck-at memory channel and study how far our constructions are from the capacity.
Mesh Router Nodes placement in Rural Wireless Mesh Networks
Venue: arXiv cs.NI 2015
Year: 2015

The problem of placement of mesh router nodes in Wireless Mesh Networks is known to be a NP hard problem. In this paper, the problem is addressed under a constraint of network model tied to rural regions where we usually observe low density and sparse population. We consider the area to cover as decomposed into a set of elementary areas which can be required or optional in terms of coverage and where a node can be placed or not. We propose an effective algorithm to ensure the coverage. This algorithm is based on metropolis approach. We evaluated the proposed algorithm on an instance network. A close to 100 percent coverage with an optimal number of routers showed the efficiency of our approach for the mesh router node placement problem