Search results for "COD"
showing 10 items of 2985 documents
Outage Analysis of Relay-Aided Non-Orthogonal Multiple Access with Partial Relay Selection
2018
Non-Orthogonal multiple access (NOMA) holds promise as a spectrally efficient multiple access scheme for 5G communication networks. This work investigates the performance of NOMA in a dual-hop amplify-and-forward (AF) relaying network, which is subject to Nakagami-$m$ fading. Specifically, we obtain a novel closed-form expression of the outage probability for the near and far users when the partial relay selection (PRS) scheme is used for selecting the best among $N$ intermediate relays. The users are considered to employ selection combining technique in order to combine the relayed and the direct transmission signals for an increased reliability of detection. Then, we evaluate the impact o…
An asynchronous covert channel using spam
2012
AbstractCurrent Internet e-mail facilities are built onto the foundation of standard rules and protocols, which usually allow a considerable amount of “freedom” to their designers. Each of these standards has been defined based on a number of vendor specific implementations, in order to provide common inter-working procedures for cross-vendor communication. Thus, a lot of optional and redundant information is being exchanged during e-mail sessions, which is available to implement versatile covert channel mechanisms.This work exploits this possibility by presenting a simple but effective steganographic scheme that can be used to deploy robust secret communication through spam e-mails. This s…
Different mechanisms underlie implicit visual statistical learning in honey bees and humans
2020
International audience; The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans’ higher cognitive functions. Yet it is an open question whether there is any fundamental difference in how humans and other good visual learner species naturally encode aspects of novel visual scenes. Using the same modified visual statistical learning paradigm and multielement stimuli, we investigated how human adults and honey bees ( Apis mellifera ) encode spontaneously, without dedicated training, various statistical properties of novel visual scenes. We found that, similarly to humans, honey bees automatically develop a comp…
The body talks: Sensorimotor communication and its brain and kinematic signatures
2019
Human communication is a traditional topic of research in many disciplines such as psychology, linguistics and philosophy, all of which mainly focused on language, gestures and deictics. However, these do not constitute the sole channels of communication, especially during online social interaction, where instead an additional critical role may be played by sensorimotor communication (SMC). SMC refers here to (often subtle) communicative signals embedded within pragmatic actions - for example, a soccer player carving his body movements in ways that inform a partner about his intention, or to feint an adversary; or the many ways we offer a glass of wine, rudely or politely. SMC is a natural …
Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests
2016
International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…
An embedded datalogger with a fast acquisition rate for in-vehicle testing and monitoring
2011
A very compact and high performance datalogger for automotive in-vehicle testing is here described. The small logger dimensions and the availability of a CAN interface allows to easily implement multiple and distributed acquisition schemes, very challenging with traditional instrumentation. High acquisition rate, up to 100 Ksps/ch, and low cost was obtained through a very accurate hardware and software design.
Fractional Fourier transform dual random phase encoding of time-varying signals
2008
Optical techniques have shown great potential in the field of information security to encode high-security images. Among several established methods, a double-random phase encryption technique (DRPE) for encoding a primary image into stationary white noise was developed by using the analogy between Fresnel diffraction patterns and the fractional Fourier transform (FrFT-DRPE). In this case, additional keys are obtained through the knowledge of the fractional orders of the FrFTs. In this work we propose an encoding setup for time-varying signals, mainly for short-haul fiber optics link applications, that can be considered as the temporal analogue of the spatial FrFT-DRPE. The behavior of the …
Security Challenges of IoT-Based Smart Home Appliances
2018
The Internet of Things, IoT, and the related security challenges are reaching homes in the form of smart appliances. If the appliances are compromised, they can be used in botnet attacks against Internet services and potentially cause harm to people and property through the local network, for example, by heating up too much or allowing unauthorized access. The aim of this study was to see how secure these devices are against remote and network attacks. Several devices were tested with attacks coming from the same Wi-Fi network to gain various levels of control of the devices. Their security against a Man-in-the-Middle attack was also studied to see differences in the susceptibility to conne…
Word sense disamibiguation combining conceptual distance, frequency and gloss
2004
Word sense disambiguation (WSD) is the process of assigning a meaning to a word based on the context in which it occurs. The absence of sense tagged training data is a real problem for the word sense disambiguation task. We present a method for the resolution of lexical ambiguity which relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a conceptual density formula developed for this purpose. The formula we propose, is a generalised form of the Agirre-Rigau conceptual density measure in which many (parameterised) refinements were introduced and an exhaustive evaluation of all meaningful combinations was performed.…
Interpretable machine learning models for single-cell ChIP-seq imputation
2019
AbstractMotivationSingle-cell ChIP-seq (scChIP-seq) analysis is challenging due to data sparsity. High degree of data sparsity in biological high-throughput single-cell data is generally handled with imputation methods that complete the data, but specific methods for scChIP-seq are lacking. We present SIMPA, a scChIP-seq data imputation method leveraging predictive information within bulk data from ENCODE to impute missing protein-DNA interacting regions of target histone marks or transcription factors.ResultsImputations using machine learning models trained for each single cell, each target, and each genomic region accurately preserve cell type clustering and improve pathway-related gene i…