255 research outputs found

    Deep Learning-Based Detector for OFDM-IM

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    This letter presents the first attempt of exploiting deep learning (DL) in the signal detection of orthogonal frequency division multiplexing with index modulation (OFDM-IM) systems. Particularly, we propose a novel DL-based detector termed as DeepIM, which employs a deep neural network with fully connected layers to recover data bits in an OFDM-IM system. To enhance the performance of DeepIM, the received signal and channel vectors are pre-processed based on the domain knowledge before entering the network. Using datasets collected by simulations, DeepIM is first trained offline to minimize the bit error rate (BER) and then the trained model is deployed for the online signal detection of OFDM-IM. Simulation results show that DeepIM can achieve a near-optimal BER with a lower runtime than existing hand-crafted detectors

    Threshold-based wireless-based NOMA systems over log-normal channels: Ergodic outage probability of joint time allocation and power splitting schemes

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    Due to the development of state-of-the-art fifth-generation communication (5G) and Internet-of-Things (IoT), the demands for capacity and throughput of wireless networks have increased significantly. As a promising solution for this, a radio access technique, namely, non-orthogonal multiple access (NOMA) has been investigated. Particularly, in this paper, we analyse the system performance of a joint time allocation and power splitting (JTAPS) protocol for NOMA-based energy harvesting (EH) wireless networks over indoor scenarios, which we modelled with log-normal fading channels. Accordingly, for the performance analysis of such networks, the analytical expression of a metric so-called "ergodic outage probability" was derived. Then, thanks to Monte Carlo simulations done in Matlab, we are able to see how different EH power splitting (PS) and EH time switching (TS) factors influence the ergodic outage probability. Last, but not least, we plot the simulation results along with the theoretical results for comparison studies.Web of Science27

    Achromobacter xylosoxidans respiratory tract infection in cystic fibrosis patients

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    The aims of this study were to evaluate the frequency of Achromobacter xylosoxidans infection in a cohort of cystic fibrosis patients, to investigate antimicrobial sensitivity, to establish possible clonal likeness among strains, and to address the clinical impact of this infection or colonization on the general outcome of these patients. The study was undertaken between January 2004 and December 2008 on 300 patients receiving care at the Regional Cystic Fibrosis Center of the Naples University “Federico II”. Sputum samples were checked for bacterial identification. For DNA fingerprinting, pulsed-field gel electrophoresis (PFGE) was carried out. Fifty-three patients (17.6%) had at least one positive culture for A. xylosoxidans; of these, 6/53 (11.3%) patients were defined as chronically infected and all were co-colonized by Pseudomonas aeruginosa. Of the patients, 18.8% persistently carried multidrug-resistant isolates. Macrorestriction analysis showed the presence of seven major clusters. DNA fingerprinting also showed a genetic relationship among strains isolated from the same patients at different times. The results of DNA fingerprinting indicate evidence of bacterial clonal likeness among the enrolled infected patients. We found no significant differences in the forced expiratory volume in 1 s (FEV1) and body mass index (BMI) when comparing the case group of A. xylosoxidans chronically infected patients with the control group of P. aeruginosa chronically infected patients

    Farm-Level Risk Factors for Fish-Borne Zoonotic Trematode Infection in Integrated Small-Scale Fish Farms in Northern Vietnam

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    BACKGROUND: Northern Vietnam is an endemic region for fish-borne zoonotic trematodes (FZT), including liver and intestinal flukes. Humans acquire the FZT infection by eating raw or inadequately cooked fish. The production of FZT-free fish in aquaculture is a key component in establishing a sustainable program to prevent and control the FZT transmission to humans. Interventions in aquaculture should be based on knowledge of the main risk factors associated with FZT transmission. METHODOLOGY/PRINCIPAL FINDINGS: A longitudinal study was carried out from June 2006 to May 2007 in Nam Dinh province, Red River Delta to investigate the development and risk factors of FZT infections in freshwater cultured fish. A total of 3820 fish were sampled six times at two-month intervals from 96 fish farms. Logistic analysis with repeated measurements was used to evaluate potential risk factors based on information collected through questionnaire interviews with 61 fish farm owners. The results showed that the FZT infections significantly increased from first sampling in June to July 2006 (65%) to sixth sampling in April to May, 2007 (76%). The liver fluke, Clonorchis sinensis and different zoonotic intestinal flukes including Haplochis pumilio, H. taichui, H. yokogawai, Centrocestus formosanus and Procerovum varium were found in sampled fish. Duration of fish cultured (sampling times), mebendazole drug self-medication of household members, presence of snails in the pond, and feeding fish with green vegetation collected outside fish farms all had a significant effect on the development of FZT prevalence in the fish. CONCLUSIONS/SIGNIFICANCE: The FZT prevalence in fish increased by 11 percentage points during a one-year culture period and the risk factors for the development of infection were identified. Results also highlight that the young fish are already highly infected when stocked into the grow-out systems. This knowledge should be incorporated into control programs of FZT transmission in integrated small-scale aquaculture nursery and grow-out systems in Vietnam
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