Machine Learning-based Indoor Positioning Systems Using Multi-Channel Information

The received signal strength indicator (RSSI) is a metric of the power measured by a sensor in a receiver. Many indoor positioning technologies use RSSI to locate objects in indoor environments. Their positioning accuracy is significantly affected by reflection and absorption from walls, and by non-stationary objects such as doors and people. Therefore, it is necessary to increase transceivers in the environment to reduce positioning errors. This paper proposes an indoor positioning technology that uses the machine learning algorithm of channel state information (CSI) combined with fingerprinting. The experimental results showed that the proposed method outperformed traditional RSSI-based localization systems in terms of average positioning accuracy up to 6.13% and 54.79% for random forest (RF) and back propagation neural networks (BPNN), respectively

Machine Learning-based Indoor Positioning Systems Using Multi-Channel Information

The received signal strength indicator (RSSI) is a metric of the power measured by a sensor in a receiver. Many indoor positioning technologies use RSSI to locate objects in indoor environments. Their positioning accuracy is significantly affected by reflection and absorption from walls, and by non-stationary objects such as doors and people. Therefore, it is necessary to increase transceivers in the environment to reduce positioning errors. This paper proposes an indoor positioning technology that uses the machine learning algorithm of channel state information (CSI) combined with fingerprinting. The experimental results showed that the proposed method outperformed traditional RSSI-based localization systems in terms of average positioning accuracy up to 6.13% and 54.79% for random forest (RF) and back propagation neural networks (BPNN), respectively

An Adaptive Load Balance and Handoff Management Strategy for Hierarchical Infrastructure Networks

Hierarchical cellular networks that employ microcells with overlaying macrocells have been proposed to increase the traffic-carrying capacity and circuit quality. Variations in the traffic loads among cells will lessen the traffic-carrying capacity. Moreover, the handoff procedure usually takes place when the call crosses the cell boundary. An ineffective management will increase the system overheads, such as channel switch, data switch, and even network switch. The invetigation proposes an effective load balance and handoff management strategy. This strategy are implemented to solve traffic-adaption problem that can enhance the traffic-carrying capacity for variations in traffic. For the management of handoff procedure, our strategy considers the mobility of mobile hosts and the bandwidth utilization in macrocells. It can descrease the number of handoffs and, accordingly, lessen the system overhead. Furthermore, the simulation results are presented to confirm the efficiency of the proposed strategy

Performance of Energy Efficient Relaying for Cluster-Based Wireless Sensor Networks

This paper proposes a novel energy efficient data relaying scheme to improve energy efficiency for cluster-based wireless sensor networks (WSNs). In order to reduce the energy dissipation of transmitting sensing data at each sensor, the fixed clustering algorithm uniformly divides the sensing area into clusters where the cluster head is deployed to the centered of the cluster area. Moreover, to perform energy efficient data relaying fixed clustering (EERFC), the cluster head is deployed as close to the sink as possible. Simulation results show that proposed EERFC definitely reduces the energy consumption of the sensors and it can further efficiently relay the cluster data

Signal-averaged electrocardiography as a noninvasive tool for evaluating the ventricular substrate in patients with nonischemic cardiomyopathy: reassessment of an old tool

IntroductionSignal-averaged electrocardiography (SAECG) provides diagnostic and prognostic information regarding cardiac diseases. However, its value in other nonischemic cardiomyopathies (NICMs) remains unclear. This study aimed to investigate the role of SAECG in patients with NICM.Methods and resultsThis retrospective study included consecutive patients with NICM who underwent SAECG, biventricular substrate mapping, and ablation for ventricular arrhythmia (VA). Patients with baseline ventricular conduction disturbances were excluded. Patients who fulfilled at least one SAECG criterion were categorized into Group 1, and the other patients were categorized into Group 2. Baseline and ventricular substrate characteristics were compared between the two groups. The study included 58 patients (39 men, mean age 50.4 ± 15.5 years), with 34 and 24 patients in Groups 1 and 2, respectively. Epicardial mapping was performed in eight (23.5%) and six patients (25.0%) in Groups 1 and 2 (p = 0.897), respectively. Patients in Group 1 had a more extensive right ventricular (RV) low-voltage zone (LVZ) and scar area than those in Group 2. Group 1 had a larger epicardial LVZ than Group 2. Epicardial late potentials were more frequent in Group 1 than in Group 2. There were more arrhythmogenic foci within the RV outflow tract in Group 1 than in Group 2. There was no significant difference in long-term VA recurrence.ConclusionIn our NICM population, a positive SAECG was associated with a larger RV endocardial scar, epicardial scar/late potentials, and a higher incidence of arrhythmogenic foci in the RV outflow tract

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Widespread divergence of the CEACAM/PSG genes in vertebrates and humans suggests sensitivity to selection

In mammals, carcinoembryonic antigen cell adhesion molecules (CEACAMs) and pregnancy-specific glycoproteins (PSGs) play important roles in the regulation of pathogen transmission, tumorigenesis, insulin signaling turnover, and fetal–maternal interactions. However, how these genes evolved and to what extent they diverged in humans remain to be investigated specifically. Based on syntenic mapping of chordate genomes, we reveal that diverging homologs with a prototypic CEACAM architecture–including an extracellular domain with immunoglobulin variable and constant domain-like regions, and an intracellular domain containing ITAM motif–are present from cartilaginous fish to humans, but are absent in sea lamprey, cephalochordate or urochordate. Interestingly, the CEACAM/PSG gene inventory underwent radical divergence in various vertebrate lineages: from zero in avian species to dozens in therian mammals. In addition, analyses of genetic variations in human populations showed the presence of various types of copy number variations (CNVs) at the CEACAM/PSG locus. These copy number polymorphisms have 3–80% frequency in select populations, and encompass single to more than six PSG genes. Furthermore, we found that CEACAM/PSG genes contain a significantly higher density of nonsynonymous single nucleotide polymorphism (SNP) compared to the chromosome average, and many CEACAM/PSG SNPs exhibit high population differentiation. Taken together, our study suggested that CEACAM/PSG genes have had a more dynamic evolutionary history in vertebrates than previously thought. Given that CEACAM/PSGs play important roles in maternal–fetal interaction and pathogen recognition, these data have laid the groundwork for future analysis of adaptive CEACAM/PSG genotype-phenotypic relationships in normal and complicated pregnancies as well as other etiologies.Chia Lin Chang, Jenia Semyonov, Po Jen Cheng, Shang Yu Huang, Jae Il Park, Huai-Jen Tsai, Cheng-Yung Lin, Frank Grützner, Yung Kuei Soong, James J. Cai, Sheau Yu Teddy Hs

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe