Search results for "Machine"
showing 10 items of 2592 documents
Design of wave energy converter (WEC): A prototype installed in Sicily
2015
The purpose of this work is to describe a possibility of installation of a wave converter in Sicily, in the Mediterranean Sea. In this paper we present the design of buoyant electrical generator, in particular, wave linear permanent magnet generator which can make wave energy converted to electrical energy.
Characterisation of nonoriented electric alloys under nonconventional conditions
1996
The variations of magnetic and loss characteristics of nonoriented cobalt-iron and silicon-iron sheets have been investigated using an Epstein frame. Cobalt-iron alloys have been tested under sinusoidal magnetic flux density with respect to frequency and temperature. Both kinds of alloys have also been investigated with respect to frequency, time constant wavefront and temperature under trapezoidal flux density. The qualitative behaviour is identical under both flux density conditions for all these alloys. These investigations have made it possible to model the variations of iron losses with experimental parameters, except the temperature. These quantitative evolutions differ with alloy and…
Prefiltering for pattern recognition using wavelet transform and neural networks
2003
Publisher Summary Neural networks are built from simple units interlinked by a set of weighted connections. Generally, these units are organized in layers. Each unit of the first layer (input layer) corresponds to a feature of a pattern that is to be analyzed. The units of the last layer (output layer) produce a decision after the propagation of information. Before feeding the computational data to neural networks, the signal must undergo a preprocessing in order to (1) define the initial transformation to represent the measured signal, (2) retain important features for class discrimination and discard that is irrelevant, and (3) reduce the volume of data to be processed, for example, data …
Online Web Bot Detection Using a Sequential Classification Approach
2019
A significant problem nowadays is detection of Web traffic generated by automatic software agents (Web bots). Some studies have dealt with this task by proposing various approaches to Web traffic classification in order to distinguish the traffic stemming from human users' visits from that generated by bots. Most of previous works addressed the problem of offline bot recognition, based on available information on user sessions completed on a Web server. Very few approaches, however, have been proposed to recognize bots online, before the session completes. This paper proposes a novel approach to binary classification of a multivariate data stream incoming on a Web server, in order to recogn…
Efficient on-the-fly Web bot detection
2021
Abstract A large fraction of traffic on present-day Web servers is generated by bots — intelligent agents able to traverse the Web and execute various advanced tasks. Since bots’ activity may raise concerns about server security and performance, many studies have investigated traffic features discriminating bots from human visitors and developed methods for automated traffic classification. Very few previous works, however, aim at identifying bots on-the-fly, trying to classify active sessions as early as possible. This paper proposes a novel method for binary classification of streams of Web server requests in order to label each active session as “bot” or “human”. A machine learning appro…
Application of neural network to predict purchases in online store
2016
A key ability of competitive online stores is effective prediction of customers’ purchase intentions as it makes it possible to apply personalized service strategy to convert visitors into buyers and increase sales conversion rates. Data mining and artificial intelligence techniques have proven to be successful in classification and prediction tasks in complex real-time systems, like e-commerce sites. In this paper we proposed a back-propagation neural network model aiming at predicting purchases in active user sessions in a Web store. The neural network training and evaluation was performed using a set of user sessions reconstructed from server log data. The proposed neural network was abl…
Identifying legitimate Web users and bots with different traffic profiles — an Information Bottleneck approach
2020
Abstract Recent studies reported that about half of Web users nowadays are intelligent agents (Web bots). Many bots are impersonators operating at a very high sophistication level, trying to emulate navigational behaviors of legitimate users (humans). Moreover, bot technology continues to evolve which makes bot detection even harder. To deal with this problem, many advanced methods for differentiating bots from humans have been proposed, a large part of which relies on supervised machine learning techniques. In this paper, we propose a novel approach to identify various profiles of bots and humans which combines feature selection and unsupervised learning of HTTP-level traffic patterns to d…
Restricted Decontamination for the Imbalanced Training Sample Problem
2003
The problem of imbalanced training data in supervised methods is currently receiving growing attention. Imbalanced data means that one class is much more represented than the others in the training sample. It has been observed that this situation, which arises in several practical domains, may produce an important deterioration of the classification accuracy, in particular with patterns belonging to the less represented classes. In the present paper, we report experimental results that point at the convenience of correctly downsizing the majority class while simultaneously increasing the size of the minority one in order to balance both classes. This is obtained by applying a modification o…
CN2-R: Faster CN2 with randomly generated complexes
2011
Among the rule induction algorithms, the classic CN2 is still one of the most popular ones; a great amount of enhancements and improvements to it is to witness this. Despite the growing computing capacities since the algorithm was proposed, one of the main issues is resource demand. The proposed modification, CN2-R, substitutes the star concept of the original algorithm with a technique of randomly generated complexes in order to substantially improve on running times without significant loss in accuracy.
On the discrete linear ill‐posed problems
1999
An inverse problem of photo‐acoustic spectroscopy of semiconductors is investigated. The main problem is formulated as the integral equation of the first kind. Two different regularization methods are applied, the algorithms for defining regularization parameters are given. Diskrečiųjų blogai sąlygotų uždavinių klausimu Santrauka Darbe nagrinejamas foto‐akustines spektroskopijos puslaidininkiuose uždavinys, kuriame i vertinami nešeju difuzijos ir rekombinacijos procesai. Reikia atstatyti šaltinio funkcija f(x), jei žinoma antrosios eiles difuzijos lygtis ir atitinkamos kraštines salygos. Naudojantis matavimu, atliktu ivairiuose dažniuose, rezultatais sprendžiamas atvirkštinis uždavinys, kel…