Search results for "Prediction."
showing 10 items of 490 documents
RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets.
2019
Background MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. Methods We performed three RIP-Chip experiments using either anti-AGO2 or anti-GW182 antibodies and compiled a data set made up of the miRNA and mRNA expression profiles of three samples for each experiment. Specifically, we analyzed the input sample, the immunoprecipita…
Toll-quality digital secraphone
2002
This paper describes the design and performance of a secraphone that, when plugged between any conventional telephone set and the public telephone network, protects the speech information travelling through the PSTN. The device has a transparent operating mode that does not alter the signal and a secure mode, accessed upon request of any of the speakers, that encrypts the speech with digital techniques, assuring privacy against unwanted listeners. At the transmission branch, voice is sampled, coded with a CELP scheme at 9600 bps (with a slow mode at 7200 bps), encrypted with a proprietary algorithm and interfaced to the line with a V.32 modem chip set. The keys for encryption are establishe…
Contextual neural-network based spectrum prediction for cognitive radio
2015
Cognitive radio is the technique of effective electromagnetic spectrum usage important for future wireless communication including 5G networks. Neural networks are nature-inspired computational models used to solve cognitive radio prediction problems. This paper presents the use of contextual Sigma-if neural network in prediction of channel states for cognitive radio. Our results indicate that Sigma-if neural network confirms better predictions than Multilayer Perceptron (MLP) network and decreases sensing time for the benefit of the increase of the effectiveness of e-m spectrum usage.
A Spline Collocation Scheme for the Spherical Shallow Water Equations
1999
A Predictive Approach for the Efficient Distribution of Agent-Based Systems on a Hybrid-Cloud
2018
International audience; Hybrid clouds are increasingly used to outsource non-critical applications to public clouds. However, the main challenge within such environments, is to ensure a cost-efficient distribution of the systems between the resources that are on/off premises. For Multi Agent Systems (MAS), this challenge is deepened due to irregular workload progress and intensive communication between the agents, which may result in high computing and data transfer costs. Thus, in this paper we propose a generic framework for adaptive cost-efficient deployment of MAS with a special focus on hybrid clouds. The framework is based mainly on the use of a performance evaluation process that con…
Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.
2007
Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…
CRISPR sequences are sometimes erroneously translated and can contaminate public databases with spurious proteins containing spaced repeats
2020
© The Author(s) 2020.
Measurement, Prediction, and Control of Individual Heart Rate Responses to Exercise-Basics and Options for Wearable Devices.
2018
The use of wearable devices or "wearables" in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the p…
What should I do next? Using shared representations to solve interaction problems
2011
Studies on how “the social mind” works reveal that cognitive agents engaged in joint actions actively estimate and influence another’s cognitive variables and form shared representations with them. (How) do shared representations enhance coordination? In this paper, we provide a probabilistic model of joint action that emphasizes how shared representations help solving interaction problems. We focus on two aspects of the model. First, we discuss how shared representations permit to coordinate at the level of cognitive variables (beliefs, intentions, and actions) and determine a coherent unfolding of action execution and predictive processes in the brains of two agents. Second, we discuss th…
Student Performance Prediction Based on Blended Learning
2021
Contribution: This article explored blended learning by implementing a student-centered teaching method based on the flipped classroom and small private online course (SPOC). The impact of general online learning behavior on student performance was analyzed. This work is practical and provides enlightenment for learning analysis and individualized teaching in blended learning. Background: Providing individualized teaching in a large class is an effective way to improve teaching quality, but the traditional teaching method makes it difficult for teachers to learn about each student’s learning situation. Blended learning offers the possibility of individualized teaching for teachers. The comb…