Search results for "Hard"

Arc routing problems: A review of the past, present, and future

2020

[EN] Arc routing problems (ARPs) are defined and introduced. Following a brief history of developments in this area of research, different types of ARPs are described that are currently relevant for study. In addition, particular features of ARPs that are important from a theoretical or practical point of view are discussed. A section on applications describes some of the changes that have occurred from early applications of ARP models to the present day and points the way to emerging topics for study. A final section provides information on libraries and instance repositories for ARPs. The review concludes with some perspectives on future research developments and opportunities for emergin…

Improvement of Energy Efficiency for Indoor Lighting in a Big Shopping Center

2018

As the progressive diffusion of shopping centers in Italy, the paper analysis the potential energy savings in the indoor lighting plant, thanks to new technologies as LED lamps and Building Automation System. The case study, applied to a big shopping mall in the middle of Italy, shows great results, thanks to the high efficiency of LED technology, high number of operating hours and the implementation of a control system. An economic and environmental evaluation is reported.

TP53 codon 72 polymorphism and cervical cancer

2009

Background Cervical cancer is caused primarily by human papillomaviruses (HPV). The polymorphism rs1042522 at codon 72 of the TP53 tumour-suppressor gene has been investigated as a genetic cofactor. More than 80 studies were done between 1998 and 2006, after it was initially reported that women who are homozygous for the arginine allele had a risk for cervical cancer seven times higher than women who were heterozygous for the allele. However, results have been inconsistent. Here we analyse pooled data from 49 studies to determine whether there is an association between TP53 codon 72 polymorphism and cervical cancer.Methods Individual data on 7946 cases and 7888 controls from 49 different st…

Über die frühen Werke von Carl Gotthard Graß in der Akademischen Bibliothek der Universität Lettlands, über die Freundschaft, Antiquarismus in der Ge…

2020

Multilanguage Semantic Interoperability in Distributed Applications

2013

JOSI is a software framework that tries to simplify the development of such kinds of applications both by providing the possibility of working on models for representing such semantic information and by offering some implementations of such models that can be easily used by software developers without any knowledge about semantic models and languages. This software library allows the representation of domain models through Java interfaces and annotations and then to use such a representation for automatically generating an implementation of domain models in different programming languages (currently Java and C++). Moreover, JOSI supports the interoperability with other applications both by …

Error-Based Interference Detection in WiFi Networks

2017

In this paper we show that inter-technology interference can be recognized by commodity WiFi devices by monitoring the statistics of receiver errors. Indeed, while for WiFi standard frames the error probability varies during the frame reception in different frame fields (PHY, MAC headers, payloads) protected with heterogeneous coding, errors may appear randomly at any point during the time the demodulator is trying to receive an exogenous interfering signal. We thus detect and identify cross-technology interference on off-the-shelf WiFi cards by monitoring the sequence of receiver errors (bad PLCP, bad PCS, invalid headers, etc.) and develop an Artificial Neural Network (ANN) to recognize t…

DeepEva: A deep neural network architecture for assessing sentence complexity in Italian and English languages

2021

Abstract Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (e.g., lexical, syntactical, morphological) to measure the grade of comprehensibility of a text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it can support the research on Automatic Text Simplification (ATS), a research area that deals with the study of new methods for transforming a text by changing its lexicon and structure to meet specific reader needs. In this paper, we illustrate an ATE approach named De…

Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation

2019

Abstract Recent advances in intrusion detection systems based on machine learning have indeed outperformed other techniques, but struggle with detecting multiple classes of attacks with high accuracy. We propose a method that works in three stages. First, the ExtraTrees classifier is used to select relevant features for each type of attack individually for each (ELM). Then, an ensemble of ELMs is used to detect each type of attack separately. Finally, the results of all ELMs are combined using a softmax layer to refine the results and increase the accuracy further. The intuition behind our system is that multi-class classification is quite difficult compared to binary classification. So, we…

Prediction of surface treatment effects on the tribological performance of tool steels using artificial neural networks

2019

The present paper discussed the development of a reliable and robust artificial neural network (ANN) capable of predicting the tribological performance of three highly alloyed tool steel grades. Experimental results were obtained by performing plane-contact sliding tests under non-lubrication conditions on a pin-on-disk tribometer. The specimens were tested both in untreated state with different hardening levels, and after surface treatment of nitrocarburizing. We concluded that wear maps via ANN modeling were a user-friendly approach for the presentation of wear-related information, since they easily permitted the determination of areas under steady-state wear that were appropriate for use…

Support Tool for the Combined Software/Hardware Design of On-Chip ELM Training for SLFF Neural Networks

2016

Typically, hardware implemented neural networks are trained before implementation. Extreme learning machine (ELM) is a noniterative training method for single-layer feed-forward (SLFF) neural networks well suited for hardware implementation. It provides fixed-time learning and simplifies retraining of a neural network once implemented, which is very important in applications demanding on-chip training. This study proposes the data flow of a software support tool in the design process of a hardware implementation of on-chip ELM learning for SLFF neural networks. The software tool allows the user to obtain the optimal definition of functional and hardware parameters for any application, and e…