scholarly journals Inexpensive monitoring of flying insect activity and abundance using wildlife cameras

2021 ◽  
Author(s):  
Jesse R A Wallace ◽  
Therese Reber ◽  
Brendan Beaton ◽  
David Dreyer ◽  
Eric J Warrant
Keyword(s):  
Large Scale ◽  
Performance Metrics ◽  
Image Annotation ◽  
List Type ◽  
Weather Factors ◽  
Wingbeat Frequency ◽  
Flying Insects ◽  
Monitoring Programs ◽  
Insect Activity ◽  
Wildlife Cameras

AbstractThe ability to measure flying insect activity and abundance is important for ecologists, conservationists and agronomists alike. However, existing methods are laborious and produce data with low temporal resolution (e.g. trapping and direct observation), or are expensive, technically complex, and require vehicle access to field sites (e.g. radar and lidar entomology).We propose a method called “camfi” for long-term non-invasive monitoring of the activity and abundance of low-flying insects using images obtained from inexpensive wildlife cameras, which retail for under USD$100 and are simple to operate. We show that in certain circumstances, this method facilitates measurement of wingbeat frequency, a diagnostic parameter for species identification. To increase usefulness of our method for very large monitoring programs, we have developed and implemented a tool for automatic detection and annotation of flying insect targets based on the popular Mask R-CNN framework. This tool can be trained to detect and annotate insects in a few hours, taking advantage of transfer learning.We demonstrate the utility of the method by measuring activity levels and wingbeat frequencies in Australian Bogong moths Agrotis infusa in the Snowy Mountains of New South Wales, and find that these moths have a mean wingbeat frequency of 48.6 Hz (SE = 1.4), undertake dusk flights in large numbers, and that the intensity of their dusk flights is modulated by daily weather factors. Validation of our tool for automatic image annotation gives baseline performance metrics for comparisons with future annotation models. The tool performs well on our test set, and produces annotations which can be easily modified by hand if required. Training completed in less than 2 h on a single machine, and inference took on average 1.15 s per image on a laptop.Our method will prove invaluable for ongoing efforts to understand the behaviour and ecology of the iconic Bogong moth, and can easily be adapted to other flying insects. The method is particularly suited to studies on low-flying insects in remote areas, and is suitable for very large-scale monitoring programs, or programs with relatively low budgets.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

scholarly journals Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Experimental Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Smart Cities ◽  
Field Tests ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Real Field

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.

scholarly journals Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

2021 ◽  
Vol 11 (8) ◽  
pp. 3623
Author(s):  
Omar Said ◽  
Amr Tolba
Keyword(s):  
Packet Loss ◽  
Large Scale ◽  
Performance Metrics ◽  
Medical System ◽  
Healthcare Data ◽  
High Altitude Platforms ◽  
Wide Range ◽  
Simulation Results ◽  
Healthcare Architecture ◽  
The Internet Of Things

Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

scholarly journals EyeHealer: A large-scale anterior eye segment dataset with eye structure and lesion annotations

2021 ◽  
Author(s):  
Wenjia Cai ◽  
Jie Xu ◽  
Ke Wang ◽  
Xiaohong Liu ◽  
Wenqin Xu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Image Annotation ◽  
Clinical Care ◽  
Significant Proportion ◽  
Anterior Segment ◽  
Future Research ◽  
Learning Models ◽  
Anterior Eye Segment ◽  
Segmentation Models

Abstract Anterior segment eye diseases account for a significant proportion of presentations to eye clinics worldwide, including diseases associated with corneal pathologies, anterior chamber abnormalities (e.g. blood or inflammation) and lens diseases. The construction of an automatic tool for the segmentation of anterior segment eye lesions will greatly improve the efficiency of clinical care. With research on artificial intelligence progressing in recent years, deep learning models have shown their superiority in image classification and segmentation. The training and evaluation of deep learning models should be based on a large amount of data annotated with expertise, however, such data are relatively scarce in the domain of medicine. Herein, the authors developed a new medical image annotation system, called EyeHealer. It is a large-scale anterior eye segment dataset with both eye structures and lesions annotated at the pixel level. Comprehensive experiments were conducted to verify its performance in disease classification and eye lesion segmentation. The results showed that semantic segmentation models outperformed medical segmentation models. This paper describes the establishment of the system for automated classification and segmentation tasks. The dataset will be made publicly available to encourage future research in this area.

scholarly journals Opportunistic Large Array Propagation Models: A Comprehensive Survey

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Performance Metrics ◽  
Experimental Studies ◽  
Cooperative Transmission ◽  
Analytical Models ◽  
Future Research ◽  
Large Array ◽  
Propagation Models ◽  
Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

scholarly journals Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP

2020 ◽  
Vol 13 (7) ◽  
pp. 3383-3438 ◽  
Author(s):  
Veronika Eyring ◽  
Lisa Bock ◽  
Axel Lauer ◽  
Mattia Righi ◽  
Manuel Schlund ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Evaluation Tool ◽  
The Earth ◽  
And Performance ◽  
Earth System Models

Abstract. The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of Earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility. It consists of (1) an easy-to-install, well-documented Python package providing the core functionalities (ESMValCore) that performs common preprocessing operations and (2) a diagnostic part that includes tailored diagnostics and performance metrics for specific scientific applications. Here we describe large-scale diagnostics of the second major release of the tool that supports the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). ESMValTool v2.0 includes a large collection of diagnostics and performance metrics for atmospheric, oceanic, and terrestrial variables for the mean state, trends, and variability. ESMValTool v2.0 also successfully reproduces figures from the evaluation and projections chapters of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and incorporates updates from targeted analysis packages, such as the NCAR Climate Variability Diagnostics Package for the evaluation of modes of variability, the Thermodynamic Diagnostic Tool (TheDiaTo) to evaluate the energetics of the climate system, as well as parts of AutoAssess that contains a mix of top–down performance metrics. The tool has been fully integrated into the Earth System Grid Federation (ESGF) infrastructure at the Deutsches Klimarechenzentrum (DKRZ) to provide evaluation results from CMIP6 model simulations shortly after the output is published to the CMIP archive. A result browser has been implemented that enables advanced monitoring of the evaluation results by a broad user community at much faster timescales than what was possible in CMIP5.

scholarly journals In Vivo CRISPR Screens Identify E3 Ligase Cop1 as a Modulator of Macrophage Infiltration and Cancer Immunotherapy Target

2020 ◽  
Author(s):  
Xiaoqing Wang ◽  
Collin Tokheim ◽  
Binbin Wang ◽  
Shengqing Stan Gu ◽  
Qin Tang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Cancer Cells ◽  
Cancer Immunotherapy ◽  
Tumor Immunity ◽  
Large Scale ◽  
Integrated Approach ◽  
Immune Checkpoint Blockade ◽  
Macrophage Infiltration ◽  
List Type

SUMMARYDespite remarkable clinical efficacies of immune checkpoint blockade (ICB) in cancer treatment, ICB benefits in triple-negative breast cancer (TNBC) remain limited. Through pooled in vivo CRISPR knockout (KO) screens in syngeneic TNBC mouse models, we found that inhibition of the E3 ubiquitin ligase Cop1 in cancer cells decreases the secretion of macrophage-associated chemokines, reduces tumor macrophage infiltration, and shows synergy in anti-tumor immunity with ICB. Transcriptomics, epigenomics, and proteomics analyses revealed Cop1 functions through proteasomal degradation of the C/ebpδ protein. Cop1 substrate Trib2 functions as a scaffold linking Cop1 and C/ebpδ, which leads to polyubiquitination of C/ebpδ. Cop1 inhibition stabilizes C/ebpδ to suppress the expression of macrophage chemoattractant genes. Our integrated approach implicates Cop1 as a target for improving cancer immunotherapy efficacy by regulating chemokine secretion and macrophage levels in the TNBC tumor microenvironment.HighlightsLarge-scale in vivo CRISPR screens identify new immune targets regulating the tumor microenvironmentCop1 knockout in cancer cells enhances anti-tumor immunityCop1 modulates chemokine secretion and macrophage infiltration into tumorsCop1 targets C/ebpδ degradation via Trib2 and influences ICB response

scholarly journals Screening and potent applicability analysis of commonly used pesticides against desert locust: an integrative entomo-informatics approach

2020 ◽  
Author(s):  
Anik Banik ◽  
Md. Fuad Mondal ◽  
Md. Mostafigur Rahman Khan ◽  
Sheikh Rashel Ahmed ◽  
Md. Mehedi Hasan
Keyword(s):  
Binding Affinity ◽  
Large Scale ◽  
Schistocerca Gregaria ◽  
Indian Subcontinent ◽  
Locusta Migratoria ◽  
Field Trials ◽  
The Other ◽  
List Type ◽  
Agricultural Pesticides ◽  
Global Threat

AbstractThe locust problem is a global threat for food security. Locusts can fly and migrate overseas within a zip and creating a large-scale devastation to the diversified agro-ecosystem. GIS based analysis showed the recent movement of locusts, among them Schistocerca gregaria and Locusta migratoria are predominant in Indian subcontinent and are found more notorious and devastating one. This devastation needs to be stopped to save human race from food deprivation. In our study, we screened some commonly used agricultural pesticides and strongly recommended three of them viz. biphenthrin, diafenthiuron and silafluofen which might be potential to control the desert locusts based on their binding affinity towards the locust’s survival proteins. Our phylogenetic analysis reveals that these three recommended pesticides might also show potency to the other locust species as well as they are also way safer than the other commercially available pesticides. These proposed pesticide’s bioactive analogs from fungus and bacteria may also show efficacy as next generation controlling measures of locust as well as different kind of pests. These recommended pesticides are expected to be highly effective against locusts and needs to bring forward by the entomologists’ by performing experimental field trials.HighlightsGIS map unmasked the 2020 migratory pattern of locusts which now predominant towards Indian subcontinent.Biphenthrin, diafenthiuron and silafluofen showed maximum binding affinity.Biphenthrin and diafenthiuron were relatively safer than silafluofen.Bioactive analogs from fungus and bacteria could be an alternative to control locusts.Pesticides inhibition hotspots for desert locusts were unrevealed.

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