Search results for " Detection"

A new simple chromo-fluorogenic probe for NO2 detection in air.

2015

[EN] A new chromo-fluorogenic probe, consisting of a biphenyl derivative containing both a silylbenzyl ether and a N,N-dimethylamino group, for NO2 detection in the gas phase has been developed. A clear colour change from colourless to yellow together with an emission quenching was observed when the probe reacted with NO2. A limit of detection to the naked eye of about 0.1 ppm was determined and the system was successfully applied to the detection of NO2 in realistic atmospheric conditions.

One Dimensional Convolutional Neural Networks for Seizure Onset Detection Using Long-term Scalp and Intracranial EEG

2021

Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial electroencephalogram (iEEG) has attracted widespread attention in recent two decades. The accurate and rapid detection of seizures not only reflects the efficiency of the algorithm, but also greatly reduces the burden of manual detection during long-term electroencephalogram (EEG) recording. In this work, a stacked one-dimensional convolutional neural network (1D-CNN) model combined with a random selection and data augmentation (RS-DA) strategy is proposed for seizure onset detection. Firstly, we segmented the long-term EEG signals using 2-sec sliding windows. Then, the 2-sec interictal and ictal segments w…

Large-scale nonlinear dimensionality reduction for network intrusion detection

2017

International audience; Network intrusion detection (NID) is a complex classification problem. In this paper, we combine classification with recent and scalable nonlinear dimensionality reduction (NLDR) methods. Classification and DR are not necessarily adversarial, provided adequate cluster magnification occurring in NLDR methods like $t$-SNE: DR mitigates the curse of dimensionality, while cluster magnification can maintain class separability. We demonstrate experimentally the effectiveness of the approach by analyzing and comparing results on the big KDD99 dataset, using both NLDR quality assessment and classification rate for SVMs and random forests. Since data involves features of mixe…

On Application-Layer DDoS Attack Detection in High-Speed Encrypted Networks

2016

Application-layer denial-of-service attacks have become a serious threat to modern high-speed computer networks and systems. Unlike network-layer attacks, application-layer attacks can be performed by using legitimate requests from legitimately connected network machines which makes these attacks undetectable for signature-based intrusion detection systems. Moreover, the attacks may utilize protocols that encrypt the data of network connections in the application layer making it even harder to detect attacker’s activity without decrypting users network traffic and violating their privacy. In this paper, we present a method which allows us to timely detect various applicationlayer attacks ag…

Cyber security of vehicle CAN bus

2019

There are currently many research projects underway concerning the intelligent transport system (ITS), with the intent to develop a variety of communication solutions between vehicles, roadside stations and services. In the near future, the roll-out of 5G networks will improve short-range vehicle-to-vehicle traffic and vehicle-to-infrastructure communications. More extensive services can be introduced due to almost non-delayed response time. Cyber security is central for the usability of the services and, most importantly, for car safety. The Controller Area Network (CAN) is an automation bus that was originally designed for real-time data transfer of distributed control systems to cars. La…

Ultrasensitive and highly specific detection of iodine ions using zirconium (IV)-enhanced oxidation

2022

Nuclear energy has significantly promoted the development of human society. However, nuclear pollution caused by nuclear accidents can lead to significant hazards to the environment and human health. As a major radioactive product, radioactive iodine (mainly existing as I−) detection has attracted significant attentions. In this study, zirconium(IV) is used to enhance the oxidation of environmental I− to form I2. Subsequently, the generated I2 oxidizes the chemical chromogenic substrate 3,3′,5,5′-tetramethylbenzidine, which is used for I− detection and realizes an ultralow limit of detection (LoD) of 0.176 nM. The LoD of our method, to the best of our knowledge, is the lowest among those of…

In-Field LAMP Detection of Flavescence Dorée Phytoplasma in Crude Extracts of the Scaphoideus titanus Vector

2022

One of the most destructive diseases affecting grapevine in Europe is caused by Flavescence Dorée phytoplasma (FDp), which belongs to the 16Sr-V group and is a European Union quarantine pathogen. Although many molecular techniques such as loop-mediated isothermal amplification (LAMP) are widely used for the rapid detection of FDp in infected grapevine plants, there is no developed isothermal amplification assay for FDp detection in the insect vectors that are fundamental for the spread of the disease. For this reason, a simple in-field real-time LAMP protocol was optimized and developed for the specific detection of FDp in the insect vector Scaphoideus titanus. The LAMP assay was optimized …

Usability and acceptability of a fall monitoring system

2017

Falls and injurious falls affect one third of the older people. Those experiencing a fall might be unable to call for help remaining unattended for a long time. Pain, hypothermia and dehydration are common consequences. Additionally, ensuing fear of falling may reduce physical activity leading to functional decline and possibly institutionalization. Monitoring fall events the CONFIDENCE system could summon emergency assistance automatically thus reducing the negative consequences of falls. This thesis is part of the European FP7 project “Ubiquitous care system to support independent living” (CONFIDENCE) which developed a fall monitoring system based on three-dimensional (3D) localization of…

Knowledge discovery using diffusion maps

2013

Anomaly detection in wireless sensor networks

2016

Wireless Sensor Network can be defined as a network of integrated sensors responsible for environmental sensing, data processing and communication with other sensors and the base station while consuming low power. Today, WSNs are being used in almost every part of life. The cost effective nature of WSNs is beneficial for environmental monitoring, production facilities and security monitoring. At the same time WSNs are vulnerable to security breaches, attacks and information leakage. Anomaly detection techniques are used to detect such activities over the network that do not conform to the normal behavior of the network communication. Supervised Machine learning approach is one way to detect…