OpenRaiser/Intern-Atlas huggingface dataset:
Opportunistic Network Decoupling With Virtual Full-Duplex Operation in Multi-Source Interfering Relay Networks
Venue: arXiv cs.IT 2016
Year: 2016

We introduce a new achievability scheme, termed opportunistic network decoupling (OND), operating in virtual full-duplex mode. In the scheme, a novel relay scheduling strategy is utilized in the $K\times N\times K$ channel with interfering relays, consisting of $K$ source--destination pairs and $N$ half-duplex relays in-between them. A subset of relays using alternate relaying is opportunistically selected in terms of producing the minimum total interference level, thereby resulting in network decoupling. As our main result, it is shown that under a certain relay scaling condition, the OND protocol achieves $K$ degrees of freedom even in the presence of interfering links among relays. Numerical evaluation is also shown to validate the performance of the proposed OND. Our protocol basically operates in a fully distributed fashion along with local channel state information, thereby resulting in a relatively easy implementation.
Three Tiers Neighborhood Graph and Multi-graph Fusion Ranking for Multi-feature Image Retrieval: A Manifold Aspect
Venue: arXiv cs.CV 2016
Year: 2016

Single feature is inefficient to describe content of an image, which is a shortcoming in traditional image retrieval task. We know that one image can be described by different features. Multi-feature fusion ranking can be utilized to improve the ranking list of query. In this paper, we first analyze graph structure and multi-feature fusion re-ranking from manifold aspect. Then, Three Tiers Neighborhood Graph (TTNG) is constructed to re-rank the original ranking list by single feature and to enhance precision of single feature. Furthermore, we propose Multi-graph Fusion Ranking (MFR) for multi-feature ranking, which considers the correlation of all images in multiple neighborhood graphs. Evaluations are conducted on UK-bench, Corel-1K, Corel-10K and Cifar-10 benchmark datasets. The experimental results show that our TTNG and MFR outperform than other state-of-the-art methods. For example, we achieve competitive results N-S score 3.91 and precision 65.00% on UK-bench and Corel-10K datasets respectively.
The End of effective Law Enforcement in the Cloud? To encypt, or not to encrypt
Venue: arXiv cs.CR 2016
Year: 2016

With an exponentially increasing usage of cloud services, the need for forensic investigations of virtual space is equally in constantly increasing demand, which includes as a very first approach, the gaining of access to it as well as the data stored. This is an aspect that faces a number of challenges, stemming not only from the technical difficulties and peculiarities, but equally covers the interaction with an emerging line of businesses offering cloud storage and services. Beyond the forensic aspects, it also covers to an ever increasing amount the non-forensic considerations, such as the availability of logs and archives, legal and data protection considerations from a global perspective and the clashes in between, as well as the ever competing interests between law enforcement to seize evidence which is non-physical, and businesses who need to be able to continue to operate and provide their hosted services, even if law enforcement seek to collect evidence. The trend post-Snowden has been unequivocally towards default encryption, and driven by market leaders such as Apple, motivated to a large extent by the perceived demands for privacy of the consumer. The central question to be explored in this paper is to what extent this trend towards default encryption will have a negative impact on law enforcement investigations and possibilities, and will at the end attempt to provide a solution, which takes into account the needs of both law enforcement, but also of the service providers. It is hoped that the recommendations from this paper will be able to have an impact in the ability for law enforcement to continue with their investigations in an efficient manner, whilst also safeguarding the ability for business to thrive and continue to develop and offer new and innovative solutions, which do not put law enforcement at risk.
Perceptual uniform descriptor and Ranking on manifold: A bridge between image representation and ranking for image retrieval
Venue: arXiv cs.CV 2016
Year: 2016

Incompatibility of image descriptor and ranking is always neglected in image retrieval. In this paper, manifold learning and Gestalt psychology theory are involved to solve the incompatibility problem. A new holistic descriptor called Perceptual Uniform Descriptor (PUD) based on Gestalt psychology is proposed, which combines color and gradient direction to imitate the human visual uniformity. PUD features in the same class images distributes on one manifold in most cases because PUD improves the visual uniformity of the traditional descriptors. Thus, we use manifold ranking and PUD to realize image retrieval. Experiments were carried out on five benchmark data sets, and the proposed method can greatly improve the accuracy of image retrieval. Our experimental results in the Ukbench and Corel-1K datasets demonstrated that N-S score reached to 3.58 (HSV 3.4) and mAP to 81.77% (ODBTC 77.9%) respectively by utilizing PUD which has only 280 dimension. The results are higher than other holistic image descriptors (even some local ones) and state-of-the-arts retrieval methods.
Internet of Things Cloud: Architecture and Implementation
Venue: arXiv cs.NI 2016
Year: 2016

The Internet of Things (IoT), which enables common objects to be intelligent and interactive, is considered the next evolution of the Internet. Its pervasiveness and abilities to collect and analyze data which can be converted into information have motivated a plethora of IoT applications. For the successful deployment and management of these applications, cloud computing techniques are indispensable since they provide high computational capabilities as well as large storage capacity. This paper aims at providing insights about the architecture, implementation and performance of the IoT cloud. Several potential application scenarios of IoT cloud are studied, and an architecture is discussed regarding the functionality of each component. Moreover, the implementation details of the IoT cloud are presented along with the services that it offers. The main contributions of this paper lie in the combination of the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT) servers to offer IoT services in the architecture of the IoT cloud with various techniques to guarantee high performance. Finally, experimental results are given in order to demonstrate the service capabilities of the IoT cloud under certain conditions.
Optimizations and Heuristics to improve Compression in Columnar Database Systems
Venue: arXiv cs.DB 2016
Year: 2016

In-memory columnar databases have become mainstream over the last decade and have vastly improved the fast processing of large volumes of data through multi-core parallelism and in-memory compression thereby eliminating the usual bottlenecks associated with disk-based databases. For scenarios, where the data volume grows into terabytes and petabytes, keeping all the data in memory is exorbitantly expensive. Hence, the data is compressed efficiently using different algorithms to exploit the multi-core parallelization technologies for query processing. Several compression methods are studied for compressing the column array, post Dictionary Encoding. In this paper, we will present two novel optimizations in compression techniques - Block Size Optimized Cluster Encoding and Block Size Optimized Indirect Encoding - which perform better than their predecessors. In the end, we also propose heuristics to choose the best encoding amongst common compression schemes.
A Model for the Adoption Process of Information System Security Innovations in Organisations: A Theoretical Perspective
Venue: arXiv cs.CY 2016
Year: 2016

In this paper, we develop a theoretical model for the adoption process of Information System Security innovations in organisations. The model stemmed from the Diffusion of Innovation theory (DOI), the Technology Acceptance Model (TAM), the Theory of Planned Behaviour (TPB) and the Technology-Organisation-Environment (TOE) framework. The model portrays Information System Security adoption process progressing in a sequence of stages. The study considers the adoption process from the initiation stage until the acquisition of innovation as an organisational level judgement while the process of innovation assimilation and integration is assessed in terms of the user behaviour within the organisation. The model also introduces several factors that influence the Information System Security innovation adoption. By merging the organisational adoption and user acceptance of innovation in a single depiction, this research contributes to IS security literature a more comprehensive model for IS security adoption in organisation, compare to any of the past representations.
FPGA Implementation of High Speed Reconfigurable Filter Bank for Multi-standard Wireless Communication Receivers
Venue: arXiv cs.IT 2016
Year: 2016

In next generation wireless communication system, wireless transceivers should be able to handle wideband input signals compromising of multiple communication standards.Such multi-standard wireless communication receivers (MWCRs) need filter bank to extract the desired signal of interest from wideband input spectrum and bring it to the baseband for further signal processing tasks such as spectrum sensing, modulation classification,demodulation etc.In MWCRs,rather any wireless receivers, modulated filter banks, such as Discrete Fourier Transform Filter Banks (DFTFB), are preferred due to their advantages such as lower area, delay and power requirements. To support multi-standard operation, reconfigurable DFTFB (RDFTFB) was proposed by integrating DFTFB with the coefficient decimation method. In this paper, an efficient high speed implementation of RDFTFB on Virtex-7 field programmable gate arrays (FPGA) has been proposed.The proposed approach minimizes the critical path delay between clocked registers thereby leading to significant improvement in the maximum operating frequency of the RDFTFB. Numerically, the proposed implementation leads to 89.7% improvement in the maximum frequency at which RDFTFB can be clocked.Furthermore,proposed implementation leads to 18.5% reduction in the dynamic power consumption.
Efficient Coded Cooperative Networks with Energy Harvesting and Wireless Power Transfer
Venue: arXiv cs.IT 2016
Year: 2016

The optimum off-line energy management scheme for multi-user multi-relay networks employing energy harvesting and wireless energy transfer is studied. Specifically, the users are capable of harvesting and transferring energy to each other over consecutive transmissions, though they have no fixed energy supplies. Meanwhile, network coding for the users' messages is conducted at the relays to enable cooperative transmission with source nodes in independent but not necessarily identically distributed (i.n.i.d.) Nakagami-$m$ fading channels. Therefore, a simultaneous two level cooperation, i.e., information-level and energy-level cooperation is conducted. The problem of energy efficiency (EE) maximization under constraints of the energy causality and a predefined outage probability threshold is formulated and shown to be non-convex. By exploiting fractional and geometric programming, a convex form-based iterative algorithm is developed to solve the problem efficiently. Close-to-optimal power allocation and energy cooperation policies across consecutive transmissions are found. Moreover, the effects of relay locations and wireless energy transmission efficiency are investigated and the performance comparison with the current state of solutions demonstrates that the proposed policies can manage the harvested energy more efficiently.
Structural characterization of Cayley graphs
Venue: arXiv cs.DM 2016
Year: 2016

We show that the directed labelled Cayley graphs coincide with the rooted deterministic vertex-transitive simple graphs. The Cayley graphs are also the strongly connected deterministic simple graphs of which all vertices have the same cycle language, or just the same elementary cycle language. Under the assumption of the axiom of choice, we characterize the Cayley graphs for all group subsets as the deterministic, co-deterministic, vertex-transitive simple graphs.
A data-driven model for influenza transmission incorporating media effects
Venue: arXiv cs.SI 2016
Year: 2016

Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza, however quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of "big data" coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study we combine an online data set comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.
Bounds on Traceability Schemes
Venue: arXiv cs.IT 2016
Year: 2016

The Stinson-Wei traceability scheme (known as traceability scheme) was proposed for broadcast encryption as a generalization of the Chor-Fiat-Naor traceability scheme (known as traceability code). Cover-free family was introduced by Kautz and Singleton in the context of binary superimposed code. In this paper, we find a new relationship between a traceability scheme and a cover-free family, which strengthens the anti-collusion strength from $t$ to $t^2$, that is, a $t$-traceability scheme is a $t^2$-cover-free family. Based on this interesting discovery, we derive new upper bounds for traceability schemes. By using combinatorial structures, we construct several infinite families of optimal traceability schemes which attain our new upper bounds. We also provide a constructive lower bound for traceability schemes, the size of which has the same order with our general upper bound. Meanwhile, we consider parent-identifying set system, an anti-collusion key-distributing scheme requiring weaker conditions than traceability scheme but stronger conditions than cover-free family. A new upper bound is also given for parent-identifying set systems.
Matched filter detection with dynamic threshold for cognitive radio networks
Venue: arXiv cs.IT 2016
Year: 2016

-In cognitive radio networks, spectrum sensing aims to detect the unused spectrum channels in order to use the radio spectrum more efficiently. Various methods have been proposed in the past, such as energy, feature detection, and matched filter. These methods are characterized by a sensing threshold, which plays an important role in the sensing performance. Most of the existing techniques used a static threshold. However, the noise is random, and, thus the threshold should be dynamic. In this paper, we suggest an approach with an estimated and dynamic sensing threshold to increase the efficiency of the sensing detection. The matched filter method with dynamic threshold is simulated and its results are compared to those of other existing techniques. Keywords-cognitive radio networks; spectrum sensing; energy detection; matched filter detection; autocorrelation based sensing; estimated dynamic threshold
Deep learning for detection of bird vocalisations
Venue: arXiv cs.SD 2016
Year: 2016

This work focuses on reliable detection of bird sound emissions as recorded in the open field. Acoustic detection of avian sounds can be used for the automatized monitoring of multiple bird taxa and querying in long-term recordings for species of interest for researchers, conservation practitioners, and decision makers. Recordings in the wild can be very noisy due to the exposure of the microphones to a large number of audio sources originating from all distances and directions, the number and identity of which cannot be known a-priori. The co-existence of the target vocalizations with abiotic interferences in an unconstrained environment is inefficiently treated by current approaches of audio signal enhancement. A technique that would spot only bird vocalization while ignoring other audio sources is of prime importance. These difficulties are tackled in this work, presenting a deep autoencoder that maps the audio spectrogram of bird vocalizations to its corresponding binary mask that encircles the spectral blobs of vocalizations while suppressing other audio sources. The procedure requires minimum human attendance, it is very fast during execution, thus suitable to scan massive volumes of data, in order to analyze them, evaluate insights and hypotheses, identify patterns of bird activity that, hopefully, finally lead to design policies on biodiversity issues.
Reactive Collision Avoidance using Evolutionary Neural Networks
Venue: arXiv cs.NE 2016
Year: 2016

Collision avoidance systems can play a vital role in reducing the number of accidents and saving human lives. In this paper, we introduce and validate a novel method for vehicles reactive collision avoidance using evolutionary neural networks (ENN). A single front-facing rangefinder sensor is the only input required by our method. The training process and the proposed method analysis and validation are carried out using simulation. Extensive experiments are conducted to analyse the proposed method and evaluate its performance. Firstly, we experiment the ability to learn collision avoidance in a static free track. Secondly, we analyse the effect of the rangefinder sensor resolution on the learning process. Thirdly, we experiment the ability of a vehicle to individually and simultaneously learn collision avoidance. Finally, we test the generality of the proposed method. We used a more realistic and powerful simulation environment (CarMaker), a camera as an alternative input sensor, and lane keeping as an extra feature to learn. The results are encouraging; the proposed method successfully allows vehicles to learn collision avoidance in different scenarios that are unseen during training. It also generalizes well if any of the input sensor, the simulator, or the task to be learned is changed.
Optimizing the placement of tap positions and guess and determine cryptanalysis with variable sampling
Venue: arXiv cs.IT 2016
Year: 2016

In this article an optimal selection of tap positions for certain LFSR-based encryption schemes is investigated from both design and cryptanalytic perspective. Two novel algorithms towards an optimal selection of tap positions are given which can be satisfactorily used to provide (sub)optimal resistance to some generic cryptanalytic techniques applicable to these schemes. It is demonstrated that certain real-life ciphers (e.g. SOBER-t32, SFINKS and Grain-128), employing some standard criteria for tap selection such as the concept of full difference set, are not fully optimized with respect to these attacks. These standard design criteria are quite insufficient and the proposed algorithms appear to be the only generic method for the purpose of (sub)optimal selection of tap positions. We also extend the framework of a generic cryptanalytic method called Generalized Filter State Guessing Attacks (GFSGA), introduced in [26] as a generalization of the FSGA method, by applying a variable sampling of the keystream bits in order to retrieve as much information about the secret state bits as possible. Two different modes that use a variable sampling of keystream blocks are presented and it is shown that in many cases these modes may outperform the standard GFSGA mode. We also demonstrate the possibility of employing GFSGA-like attacks to other design strategies such as NFSR-based ciphers (Grain family for instance) and filter generators outputting a single bit each time the cipher is clocked. In particular, when the latter scenario is considered, the idea of combining GFSGA technique and algebraic attacks appears to be a promising unified cryptanalytic method against NFSR-based stream ciphers.
WS4A: a Biomedical Question and Answering System based on public Web Services and Ontologies
Venue: arXiv cs.CL 2016
Year: 2016

This paper describes our system, dubbed WS4A (Web Services for All), that participated in the fourth edition of the BioASQ challenge (2016). We used WS4A to perform the Question and Answering (QA) task 4b, which consisted on the retrieval of relevant concepts, documents, snippets, RDF triples, exact answers and ideal answers for each given question. The novelty in our approach consists on the maximum exploitation of existing web services in each step of WS4A, such as the annotation of text, and the retrieval of metadata for each annotation. The information retrieved included concept identifiers, ontologies, ancestors, and most importantly, PubMed identifiers. The paper describes the WS4A pipeline and also presents the precision, recall and f-measure values obtained in task 4b. Our system achieved two second places in two subtasks on one of the five batches.
An Empirical Comparison of Formalisms for Modelling and Analysis of Dynamic Reconfiguration of Dependable Systems
Venue: arXiv cs.SE 2016
Year: 2016

This paper uses a case study to evaluate empirically three formalisms of different kinds for their suitability for the modelling and analysis of dynamic reconfiguration of dependable systems. The requirements on an ideal formalism for dynamic software reconfiguration are defined. The reconfiguration of an office workflow for order processing is described, and the requirements on the reconfiguration of the workflow are defined. The workflow is modelled using the Vienna Development Method ($\mathrm{VDM}$), conditional partial order graphs ($\mathrm{CPOGs}$), and the basic Calculus of Communicating Systems for dynamic process reconfiguration (basic $\mathrm{CCS^{dp}}$), and verification of the reconfiguration requirements is attempted using the models. The formalisms are evaluated according to their ability to model the reconfiguration of the workflow, to verify the requirements on the workflow's reconfiguration, and to meet the requirements on an ideal formalism.
Detection of Faults in Power System Using Wavelet Transform and Independent Component Analysis
Venue: arXiv cs.SY 2016
Year: 2016

Uninterruptible power supply is the main motive of power utility companies that motivate them for identifying and locating the different types of faults as quickly as possible to protect the power system prevent complete power black outs using intelligent techniques. Thus, the present research work presents a novel method for detection of fault disturbances based on Wavelet Transform (WT) and Independent Component Analysis (ICA). The voltage signal is taken offline under fault conditions and is being processed through wavelet and ICA for detection. The time-frequency resolution from WT transform detects the fault initiation instant in the signal. Again, a performance index is calculated from independent component analysis under fault condition which is used to detect the fault disturbance in the voltage signal. The proposed approach is tested to be robust enough under various operating scenarios like without noise, with 20-dB noise and variation in frequency. Further, the detection study is carried out using a performance index, energy content, by applying the existing Fourier transform (FT), short time Fourier transform (STFT) and the proposed wavelet transform. Fault disturbances are detected if the energy calculated in each scenario is greater than the corresponding threshold value. The fault detection study is simulated in MATLAB/Simulink for a typical power system.