Search results for "computer.software_genre"

Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

2017

Abstract Objectives This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. Methods We combine Benford’s Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the conte…

A Hierarchical Detection and Response System to Enhance Security Against Lethal Cyber-Attacks in UAV Networks

2018

International audience; Unmanned aerial vehicles (UAVs) networks have not yet received considerable research attention. Specifically, security issues are a major concern because such networks, which carry vital information, are prone to various attacks. In this paper, we design and implement a novel intrusion detection and response scheme, which operates at the UAV and ground station levels, to detect malicious anomalies that threaten the network. In this scheme, a set of detection and response techniques are proposed to monitor the UAV behaviors and categorize them into the appropriate list (normal, abnormal, suspect, and malicious) according to the detected cyber-attack. We focus on the m…

Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series

2015

Abstract This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the research object. The fuzzy time series model combines the fuzzy theory and the time series theory, thus this model can solve the fuzzy data in stock index futures prices. This paper establishes a multivariate model and improves the accuracy of computation. By combing traditional fuzzy time series models and rough set method, we use fuzzy c-mean algorithm to make the data into discrete. Further more, we deal with the rules in mature modules of the rough set and then refine the rules using data mining algor…

Visualizing Time Series State Changes with Prototype Based Clustering

2009

Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concentrate only for the indentification of normal and abnormal operational states. We present a new method for visualizing operational states and overall order of the transitions between them. This method is implemented to a visualization tool which helps the user to see the overall development of operational states allowing to find causes for abnormal behaviour. In the end visualization tool is tested in practice with real time series data collected from gear unit.

An efficient adaptive strategy for searching in peer-to-peer networks

2005

One of the main technical challenges in Peer-to-Peer (P2P) networks is how to efficiently locate desired resources. Although structured systems, based on distributed hash tables, can achieve fair effectiveness, they are not suitable for widely deployed Internet applications. In fact, this kind of systems shows many severe limitations, such as ignoring the autonomous nature of peers, and supporting only weakly semantic functions. Unstructured P2P networks are more attractive for real applications, since they can avoid both the limitations of centralized systems, and the drawbacks of structured approaches. However, their search algorithms are usually based on inefficient flooding schemes, tha…

Machine learning of reverse transcription signatures of variegated polymerases allows mapping and discrimination of methylated purines in limited tra…

2020

AbstractReverse transcription (RT) of RNA templates containing RNA modifications leads to synthesis of cDNA containing information on the modification in the form of misincorporation, arrest, or nucleotide skipping events. A compilation of such events from multiple cDNAs represents an RT-signature that is typical for a given modification, but, as we show here, depends also on the reverse transcriptase enzyme. A comparison of 13 different enzymes revealed a range of RT-signatures, with individual enzymes exhibiting average arrest rates between 20 and 75%, as well as average misincorporation rates between 30 and 75% in the read-through cDNA. Using RT-signatures from individual enzymes to trai…

93. Structural brain abnormalities in attention-deficit/hyperactivity disorder: A voxel-based MRI study in adult patients

2009

Priming index of the Spanish word fragments from the Dasí, Soler, and Ruiz (2004) database

2007

Word-fragment completion is a frequently used test in implicit memory research. A database of 196 Spanish fragments was recently published (Dasi, Soler, & Ruiz, 2004) in which the fragments were described for indices, such as difficulty, familiarity, frequency, number of meanings, and so on (www.psychonomic.org/archive). In this work, a new index, thepriming index, is described for the same 196 fragments. This index is calculated for each fragment by subtracting the difficulty index (the proportion of correct completion when the fragment is not studied) from the proportion of correct completion when the fragment is studied, and it means the capacity of an item to be primed. In order to dete…

Dosage individualization of erythropoietin using a profile-dependent support vector regression

2003

The external administration of recombinant human erythropoietin is the chosen treatment for those patients with secondary anemia due to chronic renal failure in periodic hemodialysis. The objective of this paper is to carry out an individualized prediction of the EPO dosage to be administered to those patients. The high cost of this medication, its side-effects and the phenomenon of potential resistance which some individuals suffer all justify the need for a model which is capable of optimizing dosage individualization. A group of 110 patients and several patient factors were used to develop the models. The support vector regressor (SVR) is benchmarked with the classical multilayer percept…

Legibility of Text and Pictograms in Variable Message Signs: Can Single-Word Messages Outperform Pictograms?

2018

The current research shows the advantage of single-word messages in the particular case of variable message signs (VMSs) with a high aspect ratio.Early studies on traffic sign design proposed that pictorial information would advantage equivalent text messages in static signs.We used a driving simulator to present individually 36 VMSs, showing six words (e.g., "congestion") and six danger signs (e.g., congestion traffic sign). In Experiment 1, 18 drivers read aloud the text or orally identified the pictograms as soon as they could correctly do it. In Experiment 2, a different sample of 18 drivers gave a motor response, according to the meaning of the message. We analyzed the legibility dista…