Search results for "550"

User grouping and power allocation in NOMA systems: a novel semi-supervised reinforcement learning-based solution

2022

Author's accepted manuscript In this paper, we present a pioneering solution to the problem of user grouping and power allocation in non-orthogonal multiple access (NOMA) systems. The problem is highly pertinent because NOMA is a well-recognized technique for future mobile radio systems. The salient and difcult issues associated with NOMA systems involve the task of grouping users together into the prespecifed time slots, which are augmented with the question of determining how much power should be allocated to the respective users. This problem is, in and of itself, NP-hard. Our solution is the frst reported reinforcement learning (RL)-based solution, which attempts to resolve parts of thi…

SleepXAI: An explainable deep learning approach for multi-class sleep stage identification

2022

AbstractExtensive research has been conducted on the automatic classification of sleep stages utilizing deep neural networks and other neurophysiological markers. However, for sleep specialists to employ models as an assistive solution, it is necessary to comprehend how the models arrive at a particular outcome, necessitating the explainability of these models. This work proposes an explainable unified CNN-CRF approach (SleepXAI) for multi-class sleep stage classification designed explicitly for univariate time-series signals using modified gradient-weighted class activation mapping (Grad-CAM). The proposed approach significantly increases the overall accuracy of sleep stage classification …

Using Tsetlin Machine to discover interpretable rules in natural language processing applications

2021

Tsetlin Machines (TM) use finite state machines for learning and propositional logic to represent patterns. The resulting pattern recognition approach captures information in the form of conjunctive clauses, thus facilitating human interpretation. In this work, we propose a TM-based approach to three common natural language processing (NLP) tasks, namely, sentiment analysis, semantic relation categorization and identifying entities in multi-turn dialogues. By performing frequent itemset mining on the TM-produced patterns, we show that we can obtain a global and a local interpretation of the learning, one that mimics existing rule-sets or lexicons. Further, we also establish that our TM base…

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…

Preamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approach

2020

The evolution of Internet of things (IoT) towards massive IoT in recent years has stimulated a surge of traffic volume among which a huge amount of traffic is generated in the form of massive machine type communications. Consequently, existing network infrastructure is facing challenges when handling rapidly growing traffic load, especially under bursty traffic conditions which may more often lead to congestion. By proactively predicting the occurrence of congestion, we can implement necessary means and conceivably avoid congestion. In this paper, we propose a machine learning (ML) based model for predicting successful preamble transmissions at a base station and subsequently forecasting th…

Fall Detection Based on the Instantaneous Doppler Frequency : A Machine Learning Approach

2019

Modern societies are facing an ageing problem which comes with increased cost of healthcare. A major share of this ever-increasing cost is due to fall related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for building of a radio-frequency-based fall detection system. This paper presents an activity simulator that generates the complex channel gain of indoor channels in the presence of one person performing three different activities, namely, slow fall, fast fall, and walking. We built a machine learning framework for activity recognition based on the complex channel gain. We assess the recognition accuracy of three different class…

Increasing sample efficiency in deep reinforcement learning using generative environment modelling

2020

Aircraft-based observations of isoprene-epoxydiol-derived secondary organic aerosol (IEPOX-SOA) in the tropical upper troposphere over the Amazon reg…

2018

During the ACRIDICON-CHUVA field project (September–October 2014; based in Manaus, Brazil) aircraft-based in situ measurements of aerosol chemical composition were conducted in the tropical troposphere over the Amazon using the High Altitude and Long Range Research Aircraft (HALO), covering altitudes from the boundary layer (BL) height up to 14.4 km. The submicron non-refractory aerosol was characterized by flash-vaporization/electron impact-ionization aerosol particle mass spectrometry. The results show that significant secondary organic aerosol (SOA) formation by isoprene oxidation products occurs in the upper troposphere (UT), leading to increased organic aerosol mass concentratio…

Impact of the Asian monsoon on the extratropical lower stratosphere: trace gas observations during TACTS over Europe 2012

2016

Abstract. The transport of air masses originating from the Asian monsoon anticyclone into the extratropical upper troposphere and lower stratosphere (Ex-UTLS) above potential temperatures Θ =  380 K was identified during the HALO aircraft mission TACTS in August and September 2012. In situ measurements of CO, O3 and N2O during TACTS flight 2 on 30 August 2012 show the irreversible mixing of aged stratospheric air masses with younger (recently transported from the troposphere) ones within the Ex-UTLS. Backward trajectories calculated with the trajectory module of CLaMS indicate that these tropospherically affected air masses originate from the Asian monsoon anticyclone. These air masses are …

The novel HALO mini-DOAS instrument: inferring trace gas concentrations from airborne UV/visible limb spectroscopy under all skies using the scaling …

2017

Abstract. We report on a novel six-channel optical spectrometer (further on called mini-DOAS instrument) for airborne nadir and limb measurements of atmospheric trace gases, liquid and solid water, and spectral radiances in the UV/vis and NIR spectral ranges. The spectrometer was developed for measurements from aboard the German High-Altitude and Long-Range (HALO) research aircraft during dedicated research missions. Here we report on the relevant instrumental details and the novel scaling method used to infer the mixing ratios of UV/vis absorbing trace gases from their absorption measured in limb geometry. The uncertainties of the scaling method are assessed in more detail than before for …