Challenges in video based object detection in maritime scenario using computer vision

This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here

DotAligner:Identification and clustering of RNA structure motifs

Abstract The diversity of processed transcripts in eukaryotic genomes poses a challenge for the classification of their biological functions. Sparse sequence conservation in non-coding sequences and the unreliable nature of RNA structure predictions further exacerbate this conundrum. Here, we describe a computational method, DotAligner, for the unsupervised discovery and classification of homologous RNA structure motifs from a set of sequences of interest. Our approach outperforms comparable algorithms at clustering known RNA structure families, both in speed and accuracy. It identifies clusters of known and novel structure motifs from ENCODE immunoprecipitation data for 44 RNA-binding proteins

Point Defects and Localized Excitons in 2D WSe2

Identifying the point defects in 2D materials is important for many applications. Recent studies have proposed that W vacancies are the predominant point defect in 2D WSe2, in contrast to theoretical studies, which predict that chalcogen vacancies are the most likely intrinsic point defects in transition metal dichalcogenide semiconductors. We show using first principles calculations, scanning tunneling microscopy (STM) and scanning transmission electron microscopy experiments, that W vacancies are not present in our CVD-grown 2D WSe2. We predict that O-passivated Se vacancies (O_Se) and O interstitials (Oins) are present in 2D WSe2, because of facile O2 dissociation at Se vacancies, or due to the presence of WO3 precursors in CVD growth. These defects give STM images in good agreement with experiment. The optical properties of point defects in 2D WSe2 are important because single photon emission (SPE) from 2D WSe2 has been observed experimentally. While strain gradients funnel the exciton in real space, point defects are necessary for the localization of the exciton at length scales that enable photons to be emitted one at a time. Using state-of-the-art GW-Bethe-Salpeter-equation calculations, we predict that only Oins defects give localized excitons within the energy range of SPE in previous experiments, making them a likely source of previously observed SPE. No other point defects (O_Se, Se vacancies, W vacancies and Se_W antisites) give localized excitons in the same energy range. Our predictions suggest ways to realize SPE in related 2D materials and point experimentalists toward other energy ranges for SPE in 2D WSe2

Treatment of cervical intraepithelial lesions

Precancerous cervical lesions precede the development of invasive cervical cancer by 10–20 years, making cervical cancer preventable if these lesions are detected and effectively treated. Treatment has evolved in the last few decades and now includes ablative options that can be performed in lower‐resource settings where surgical excision is not feasible or routinely available. Gas‐based cryotherapy, which freezes cervical tissue to induce localized necrosis, is the most commonly used ablative treatment. However, its implementation in low‐resource settings is difficult because the refrigerant gas can be difficult to procure and transport, and is expensive. New cryotherapy devices that do not require an external supply of gas appear promising. Thermal coagulation, which burns cervical tissue to induce necrosis, has become more widely available in the last few years owing to its portability and the feasibility of using battery‐powered devices. These two ablative treatments successfully eradicate 75%–85% of high‐grade cervical lesions and have minor adverse effects

Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data

RNA-sequencing has become the gold standard for whole-transcriptome gene expression quanti cation. Multiple algorithms have been developed to derive gene counts from sequencing reads. While a number of benchmarking studies have been conducted, the question remains how individual methods perform at accurately quantifying gene expression levels from RNA-sequencing reads. We performed an independent benchmarking study using RNA-sequencing data from the well established MAQCA and MAQCB reference samples. RNA-sequencing reads were processed using five workflows (Tophat-HTSeq, Tophat-Cuflinks, STAR-HTSeq, Kallisto and Salmon) and resulting gene expression measurements were compared to expression data generated by wet-lab validated qPCR assays for all protein coding genes. All methods showed high gene expression correlations with qPCR data. When comparing gene expression fold changes between MAQCA and MAQCB samples, about 85% of the genes showed consistent results between RNA-sequencing and qPCR data. Of note, each method revealed a small but speci c gene set with inconsistent expression measurements. A significant proportion of these method-specific inconsistent genes were reproducibly identified in independent datasets. These genes were typically smaller, had fewer exons, and were lower expressed compared to genes with consistent expression measurements. We propose that careful validation is warranted when evaluating RNA-seq based expression profiles for this specific gene set

Prevalence of headache among handheld cellular telephone users in Singapore: a community study.

We carried out a cross-sectional community study in Singapore to determine the prevalence of specific central nervous system (CNS) symptoms among hand-held cellular telephone (HP) users compared to nonusers and to study the association of risk factors and CNS symptoms among HP users. A total of 808 men and women between 12 and 70 years of age, who lived in one community, were selected using one-stage cluster random sampling and responses to a structured questionnaire. The prevalence of HP users was 44.8%. Headache was the most prevalent symptom among HP users compared to non-HP users, with an adjusted prevalence rate ratio of 1.31 [95% confidence interval, 1.00-1.70]. There is a significant increase in the prevalence of headache with increasing duration of usage (in minutes per day). Prevalence of headache was reduced by more than 20% among those who used hand-free equipment for their cellular telephones as compared to those who never use the equipment. The use of HPs is not associated with a significant increase of CNS symptoms other than headache

Packet Reception Probabilities in Vehicular Communications Close to Intersections

Vehicular networks allow vehicles to share information and are expected to be an integral part of future intelligent transportation systems (ITS). To guide and validate the design process, analytical expressions of key performance metrics such as packet reception probabilities and throughput are necessary, in particular for accident-prone scenarios such as intersections. In this paper, we present a procedure to analytically determine the packet reception probability and throughput of a selected link, taking into account the relative increase in the number of vehicles (i.e., possible interferers) close to an intersection. We consider both slotted Aloha and CSMA/CA MAC protocols, and show how the procedure can be used to model different propagation environments of practical relevance. The procedure is validated for a selected set of case studies at low traffic densities

Characterization and Control of Conservative and Nonconservative Network Dynamics

Diffusion processes are instrumental to describe the movement of a continuous quantity in a generic network of interacting agents. Here, we present a probabilistic framework for diffusion in networks and study in particular two classes of agent interactions depending on whether the total network quantity follows a conservation law. Focusing on asymmetric interactions between agents, we define how the dynamics of conservative and non-conservative networks relate to the weighted in-degree and out-degree Laplacians. For uncontrolled networks, we define the convergence behavior of our framework, including the case of variable network topologies, as a function of the eigenvalues and eigenvectors of the weighted graph Laplacian. In addition, we study the control of the network dynamics by means of external controls and alterations in the network topology. For networks with exogenous controls, we analyze convergence and provide a method to measure the difference between conservative and non-conservative network dynamics based on the comparison of their respective attainability domains. In order to construct a network topology tailored for a desired behavior, we propose a Markov decision process (MDP) that learns specific network adjustments through a reinforcement learning algorithm. The presented network control and design schemes enable the alteration of the dynamic and stationary network behavior in conservative and non-conservative networks

An objective based classification of aggregation techniques for wireless sensor networks

Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented