The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper investigates the performance of cognitive radio network (CogNet). An interference cancellation scheme employed at secondary transmitter is first discussed based on the cancellation of cross interference from secondary transmitter to primary receiver. Then, we derive the expressions of the probability density function (PDF) and cumulative distribution function (CDF) of the received SNRs...
We consider a prediction problem with multiple output responses based on an ensemble of multivariate regression trees. The selection of the optimal ensemble is formulated as a multi-objective optimization problem and solved using genetic algorithms. We illustrate the application of our approach on drug sensitivity prediction problem where the proposed methodology outperforms regular multivariate random...
Modeling sensitivity to anti-cancer drugs is a significant challenge in the area of systems medicine. Majority of current approaches generate a deterministic predictive model for each drug based on the genetic characterization of the cell lines and ignores the relationship between different drug sensitivities during model generation. In this article, we approach the problem of modeling the relationship...
Solving the haplotype assembly problem by optimizing the commonly used minimum error correction criterion is known to be NP-hard. For this reason, suboptimal heuristics are often used in practice. In this paper, we propose a novel method for optimal haplotype assembly that is based on depth-first branch-and-bound search of the solution space. Our scheme is inspired by the sphere decodng algorithms...
Although Duchenne muscular dystrophy (DMD), the most common single-gene lethal disorder, is caused by a homogeneous biochemical defect in all patients, substantial patient-patient variety in disease progression is observed. The loss of ambulation (LoA) is a functional milestone of DMD progression and the age at LoA is often used as an indication of disease severity. But as age at LoA is not always...
Accurate prediction of exons locations in deoxyri-bonucleic acid (DNA) sequences is an important issue for geneticists. Time-domain periodogram (TDP) and average magnitude difference function (AMDF) are two time-domain approaches previously proposed for this purpose. These two approaches employ a second-order infinite impulse response (IIR) resonant filter as a preprocessing stage so as to emphasize...
We have created a new mobile video database that models distortions caused by network impairments. In particular, we simulate stalling events and startup delays in over-the-top (OTT) mobile streaming videos. We describe the way we simulated diverse stalling events to create a corpus of distorted videos and the human study we conducted to obtain subjective scores. We also analyzed the ratings to understand...
Mode switching is one of the most important features of device-to-device (D2D) communications since it can bring more freedoms for potential D2D pairs. In this paper, we investigate optimal D2D mode switching to maximize the network spectrum-efficiency (SE). We formulate the optimal SE problems in three D2D transmission modes, dedicated mode, reusing mode and cellular mode, while guaranteeing the...
Distributed learning is an effective approach to mitigate the data communications in machine learning when the data is stored in a distributed manner, particularly in the era of big data. In the distributed learning procedure, learners can send intermediate computation results instead of raw data, thus reducing the communication cost. In this paper, the communication requirement for distributed learning...
In this paper, a design for a cognitive MAC protocol based on Primary User (PU) feedback exploitation is proposed. A queuing approach is adopted and an infinite-state Partially Observable Markov Decision Process (POMDP) framework is proposed where the states represent the number of packets in the primary queue. The primary user quality of service (QoS) guarantee is defined through a primary queue...
Transcriptome assembly techniques provide a valuable opportunity to learn more about non-model organisms. We present transcriptome assemblies for Pacific whiteleg shrimp (Litopenaeus vannamei), a species of great importance in global mariculture, that lacks solid transcriptome and genome references. We examine the new Pacific whiteleg transcriptome assemblies via multiple metrics, and compare the...
We have devised a method to optimize Golomb-Rice coding of frequency spectra, aiming at its use in frequency domain audio coder, using spectral envelopes extracted by linear predictive coding (LPC) from amplitude spectra instead of conventional power spectra according to theoretical investigations. This optimization improves the efficiency of the Golomb-Rice coding by allocating Rice parameter at...
In the field of seismic interpretation, univariate data-based maps are commonly used by interpreters, especially for fault detection. In these maps, the contrast between target regions and the background is one of the main factors that affect the accuracy of interpretation. Since univariate data-based maps are not capable of providing a high-contrast representation, to overcome this issue, we turn...
In this paper, we derive the distributed observable state from first principles. In particular, we extend the estimation setup to a distributed framework where in addition to the state and sensing, we also have communication among the sensors. We consider that each sensor estimates the entire state-vector to recover its unobservability. Combining the estimates at all of the sensors we arrive at the...
Crowdsensing has been widely recognized as a promising paradigm for numerous applications in mobile networks. To realize the full benefit of crowdsensing, one fundamental challenge is to incentivize users to participate. In this paper, we leverage social trust assisted reciprocity (STAR), a synergistic marriage of social trust and reciprocity, to develop an incentive mechanism in order to stimulate...
Poor visibility due to haze poses a challenge for driving and can significantly compromise safety. In this paper, we present an algorithm and an implementation that assists the driver by providing an electronic view that improves visibility via haze removal. Our optimized implementation on the Texas Instruments TMS320DM6446EVM DSP based evaluation board provides full Dl video resolution and frame...
Consider a network where each agent has a private composite function (e.g. the sum of a smooth and a non-smooth function). The problem we address here is to And a minimize! of the aggregate cost (the sum of the agents functions) in a distributed manner. In this paper, we combine recent results on primal-dual optimization and coordinate descent to propose an asynchronous distributed algorithm for composite...
A new approach to perform the acquisition and the reconstruction of spatially super-resolved hyperspectral images is presented. The proposed hyperspectral sensing strategy is based on acquiring several low-resolved grayscale images following a specific acquisition scheme which takes profit from different spectral dependent blurring kernels. The proposed model describes how output grayscale pixels...
The problem of transmitting a remote source via multiple agents to a single destination is considered with secrecy constraints. In particular, noisy versions of a source are observed by multiple agents who then encode and transmit their observations to a decoder over dedicated noisy channel. The decoder should be able to reconstruct the remote source within a certain distortion limit. In addition,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.