scholarly journals rhizoTrak: a flexible open source Fiji plugin for user-friendly manual annotation of time-series images from minirhizotrons

2019 ◽  
Vol 444 (1-2) ◽  
pp. 519-534 ◽  
Author(s):  
Birgit Möller ◽  
Hongmei Chen ◽  
Tino Schmidt ◽  
Axel Zieschank ◽  
Roman Patzak ◽  
...  
Keyword(s):  
Time Series ◽  
Open Source ◽  
Manual Annotation ◽  
User Friendly ◽  
Time Series Images

scholarly journals rhizoTrak: A flexible open source Fiji plugin for user-friendly manual annotation of time-series images from minirhizotrons

2019 ◽  
Author(s):  
Birgit Möller ◽  
Hongmei Chen ◽  
Tino Schmidt ◽  
Axel Zieschank ◽  
Roman Patzak ◽  
...  
Keyword(s):  
Time Series ◽  
Open Source ◽  
Data Exchange ◽  
Time Series Data ◽  
Full Range ◽  
Open Data ◽  
Series Data ◽  
Root Turnover ◽  
User Friendly ◽  
Time Series Images

AbstractBackground and aimsMinirhizotrons are commonly used to study root turnover which is essential for understanding ecosystem carbon and nutrient cycling. Yet, extracting data from minirhizotron images requires intensive annotation effort. Existing annotation tools often lack flexibility and provide only a subset of the required functionality. To facilitate efficient root annotation in minirhizotrons, we present the user-friendly open source tool rhizoTrak.Methods and resultsrhizoTrak builds on TrakEM2 and is publically available as Fiji plugin. It uses treelines to represent branching structures in roots and assigns customizable status labels per root segment. rhizoTrak offers configuration options for visualization and various functions for root annotation mostly accessible via keyboard shortcuts. rhizoTrak allows time-series data import and particularly supports easy handling and annotation of time series images. This is facilitated via explicit temporal links (connectors) between roots which are automatically generated when copying annotations from one image to the next. rhizoTrak includes automatic consistency checks and guided procedures for resolving conflicts. It facilitates easy data exchange with other software by supporting open data formats.ConclusionsrhizoTrak covers the full range of functions required for user-friendly and efficient annotation of time-series images. Its flexibility and open source nature will foster efficient data acquisition procedures in root studies using minirhizotrons.

scholarly journals RhythmicAlly: Your R and Shiny–Based Open-Source Ally for the Analysis of Biological Rhythms

2019 ◽  
Vol 34 (5) ◽  
pp. 551-561 ◽  
Author(s):  
Lakshman Abhilash ◽  
Vasu Sheeba
Keyword(s):  
Time Series ◽  
Open Source ◽  
Time Series Data ◽  
Biological Rhythms ◽  
Series Data ◽  
Biological Time ◽  
Source Program ◽  
Wide Range ◽  
Infradian Rhythms ◽  
User Friendly

Research on circadian rhythms often requires researchers to estimate period, robustness/power, and phase of the rhythm. These are important to estimate, owing to the fact that they act as readouts of different features of the underlying clock. The commonly used tools, to this end, suffer from being very expensive, having very limited interactivity, being very cumbersome to use, or a combination of these. As a step toward remedying the inaccessibility to users who may not be able to afford them and to ease the analysis of biological time-series data, we have written RhythmicAlly, an open-source program using R and Shiny that has the following advantages: (1) it is free, (2) it allows subjective marking of phases on actograms, (3) it provides high interactivity with graphs, (4) it allows visualization and storing of data for a batch of individuals simultaneously, and (5) it does what other free programs do but with fewer mouse clicks, thereby being more efficient and user-friendly. Moreover, our program can be used for a wide range of ultradian, circadian, and infradian rhythms from a variety of organisms, some examples of which are described here. The first version of RhythmicAlly is available on Github, and we aim to maintain the program with subsequent versions having updated methods of visualizing and analyzing time-series data.

MackDroid - An Android based Application to monitor devices

2016 ◽  
Vol 9 ◽  
pp. 1
Author(s):  
Maaz Sirkhot ◽  
Ekta Sirwani ◽  
Aishwarya Kourani ◽  
Akshit Batheja ◽  
Kajal Jethanand Jewani
Keyword(s):  
Operating System ◽  
Open Source ◽  
Vital Role ◽  
Mobile Users ◽  
Android Application ◽  
Web Page ◽  
Technological World ◽  
Monitoring Service ◽  
User Friendly

In this technological world, smartphones can be considered as one of the most far-reaching inventions. It plays a vital role in connecting people socially. The number of mobile users using an Android based smartphone has increased rapidly since last few years resulting in organizations, cyber cell departments, government authorities feeling the need to monitor the activities on certain targeted devices in order to maintain proper functionality of their respective jobs. Also with the advent of smartphones, Android became one of the most popular and widely used Operating System. Its highlighting features are that it is user friendly, smartly designed, flexible, highly customizable and supports latest technologies like IoT. One of the features that makes it exclusive is that it is based on Linux and is Open Source for all the developers. This is the reason why our project Mackdroid is an Android based application that collects data from the remote device, stores it and displays on a PHP based web page. It is primarily a monitoring service that analyzes the contents and distributes it in various categories like Call Logs, Chats, Key logs, etc. Our project aims at developing an Android application that can be used to track, monitor, store and grab data from the device and store it on a server which can be accessed by the handler of the application.

scholarly journals An Interactive WebGIS Framework for Coastal Erosion Risk Management

2021 ◽  
Vol 9 (6) ◽  
pp. 567
Author(s):  
Alessandra Capolupo ◽  
Cristina Monterisi ◽  
Alessandra Saponieri ◽  
Fabio Addona ◽  
Leonardo Damiani ◽  
...  
Keyword(s):  
Open Source ◽  
3D Visualization ◽  
Erosion Risk ◽  
Innovative Strategies ◽  
Web Mapping ◽  
Natural Processes ◽  
Multi Scale ◽  
Interactive Interface ◽  
Multi Temporal ◽  
User Friendly

The Italian coastline stretches over about 8350 km, with 3600 km of beaches, representing a significant resource for the country. Natural processes and anthropic interventions keep threatening its morphology, moulding its shape and triggering soil erosion phenomena. Thus, many scholars have been focusing their work on investigating and monitoring shoreline instability. Outcomes of such activities can be largely widespread and shared with expert and non-expert users through Web mapping. This paper describes the performances of a WebGIS prototype designed to disseminate the results of the Italian project Innovative Strategies for the Monitoring and Analysis of Erosion Risk, known as the STIMARE project. While aiming to include the entire national coastline, three study areas along the regional coasts of Puglia and Emilia Romagna have already been implemented as pilot cases. This WebGIS was generated using Free and Open-Source Software for Geographic information systems (FOSS4G). The platform was designed by combining Apache http server, Geoserver, as open-source server and PostgreSQL (with PostGIS extension) as database. Pure javascript libraries OpenLayers and Cesium were implemented to obtain a hybrid 2D and 3D visualization. A user-friendly interactive interface was programmed to help users visualize and download geospatial data in several formats (pdf, kml and shp), in accordance with the European INSPIRE directives, satisfying both multi-temporal and multi-scale perspectives.

Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images

2012 ◽  
Vol 34 (7) ◽  
pp. 2432-2453 ◽  
Author(s):  
Xuexia Chen ◽  
James E. Vogelmann ◽  
Gyanesh Chander ◽  
Lei Ji ◽  
Brian Tolk ◽  
...  
Keyword(s):  
Time Series ◽  
Irs P6 ◽  
Landsat 5 Tm ◽  
Time Series Images ◽  
Disturbance Detection

Yield Prediction Model for Potato Using Landsat Time Series Images Driven Vegetation Indices

2018 ◽  
Vol 1 (1-2) ◽  
pp. 29-38 ◽  
Author(s):  
Imran Hossain Newton ◽  
A. F. M Tariqul Islam ◽  
A. K. M. Saiful Islam ◽  
G. M. Tarekul Islam ◽  
Anika Tahsin ◽  
...  
Keyword(s):  
Time Series ◽  
Prediction Model ◽  
Vegetation Indices ◽  
Yield Prediction ◽  
Time Series Images
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