FIELD: A Software Tool That Integrates Harvester Data and Allometric Equations for a Dynamic Estimation of Forest Harvesting Residues

On an international comparison basis, Australia’s utilisation of forest residues remains very low. While there are numerous factors contributing to this low utilisation, this is greatly explained by the limited timely and accurate data on availability, quality, and location of residues generated during harvesting operations. This manuscript reports on the development and testing of a new freeware tool called FIELD (Forest Inventory Electronic Live Data), which supports the real-time monitoring and estimation of forestry harvesting residues. As inputs, FIELD uses StanForD pri files and geo-location data extracted from the harvester’s onboard computer in combination with locally developed species-specific allometric equations. Using a case study, this paper describes how FIELD works operationally and illustrates the range of support features that the tool can provide to decision-makers by producing real-time data on the availability, quality, and location of harvesting residues. In addition, it is discussed how the tool can contribute to supporting decisions during forest operations associated with the feasibility of residue utilisation in specific site conditions. Our results show that it is possible to estimate the availability of harvesting residues at geo-located sites dynamically, although further testing of the tool is required for a more accurate estimation and monitoring of harvesting residues.

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Model Driven Engineering for Quality of Service Management

Journal of Database Management ◽

10.4018/jdm.2016100102 ◽

2016 ◽

Vol 27 (4) ◽

pp. 24-38 ◽

Cited By ~ 1

Author(s):

Salwa M'barek ◽

Leila Baccouche ◽

Henda Ben Ghezala

Keyword(s):

Quality Of Service ◽

Real Time ◽

Service Management ◽

Software Tool ◽

Model Driven Engineering ◽

Time Data ◽

Arrival Times ◽

Model Driven ◽

Real Time Data

Real-time applications managing a large number of real-time data require the use of Real-time Database Management Systems (RTDBMS) to meet temporal constraints of both real-time data and transactions. However, a RTDBMS has a dynamic workload and may be frequently overloaded since the arrival times and workloads of user transactions are unpredictable. Therefore, Quality of Service management solutions have been proposed to guarantee the stability of RTDBMS even during unpredictable overload periods. While effective, the design and reuse of these solutions is challenging because they are not formally modeled and there is no tool neither a methodology that helps us design such solutions. To address these issues, the authors propose a design framework based on the Model-Driven Engineering approach providing a modeling architecture, a strategic methodology and a software tool to support modeling and reusing such solutions. The framework is implemented and tested for a real Qos management solution.

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Instantaneous Disturbance Index for Power Distribution Networks

Sensors ◽

10.3390/s21041348 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1348

Author(s):

María Dolores Borrás-Talavera ◽

Juan Carlos Bravo ◽

César Álvarez-Arroyo

Keyword(s):

Power Systems ◽

Real Time ◽

Power Quality ◽

Power Distribution ◽

Distribution Networks ◽

Accurate Estimation ◽

Time Data ◽

Power Distribution Networks ◽

Disturbance Index ◽

The Impact

The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From any of these points of view, an instantaneous characterization of power quality (PQ) aspects becomes an important task. For this purpose, a wavelet-based power quality indices (PQIs) are introduced in this paper. An instantaneous disturbance index (ITD(t)) and a Global Disturbance Ratio index (GDR) are defined to integrally reflect the PQ level in Power Distribution Networks (PDN) under steady-state and/or transient conditions. With only these two indices it is possible to quantify the effects of non-stationary disturbances with high resolution and precision. These PQIs offer an advantage over other similar because of the suitable choice of mother wavelet function that permits to minimize leakage errors between wavelet levels. The wavelet-based algorithms which give rise to these PQIs can be implemented in smart sensors and used for monitoring purposes in PDN. The applicability of the proposed indices is validated by using a real-time experimental platform. In this emulated power system, signals are generated and real-time data are analyzed by a specifically designed software. The effectiveness of this method of detection and identification of disturbances has been proven by comparing the proposed PQIs with classical indices. The results confirm that the proposed method efficiently extracts the characteristics of each component from the multi-event test signals and thus clearly indicates the combined effect of these events through an accurate estimation of the PQIs.

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Design and Implementation of Reliability Analysis Tool using Real Time Data

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l3060.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 3210-3213

Keyword(s):

Real Time ◽

Software Reliability ◽

Web Application ◽

Research Work ◽

Software Tool ◽

Security Level ◽

Data Sets ◽

Analysis Tool ◽

Time Data ◽

Design And Testing

To estimate the reliability of software numerous statistical methods are in practice. To accomplish the software reliability prediction in more accurate way there is a huge demand for data sets. The data sets that can be acquired as a result of testing the software can be used for predicting the reliability. The research work focuses on creating a layer of software design and testing method namely web software testing. The main purpose is to collect the erroneous data from real time. The reliability of software can be measured in different aspects like traffic handling capability when there are a greater number of users, the security level for cracking the passwords and the possibility of different combinations of errors that occurs when inputting the data. This proposed software tool will read the software description, and will generate test patterns according to the input types and collects testing results, predicting the software reliability in real time and suggesting the possible ways to improve the software. For designing purpose PHP for web application will be used to give the testing results.

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Real-Time Data Center Transient Analysis

ASME 2011 Pacific Rim Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Systems, MEMS and NEMS: Volume 2 ◽

10.1115/ipack2011-52088 ◽

2011 ◽

Cited By ~ 3

Author(s):

Xuanhang Simon Zhang ◽

James W. VanGilder

Keyword(s):

Real Time ◽

Data Center ◽

Data Centers ◽

Software Tool ◽

Cooling Capacity ◽

Time Data ◽

Total Load ◽

Cooling Performance ◽

Water Storage Tank ◽

Chilled Water

A software tool was developed to predict the transient cooling performance of data centers and to explore various alternatives in real-time for data center design and management purposes. Cooling performance can be affected by factors such as room architecture, rack population and layout, connections between cooler fans and UPSs, chilled water pumps and UPSs, the size of the chilled water storage tank, etc. The available transient cooling runtime is mainly dictated by the system stored cooling capacity and the total load in the data center. This paper discusses the transient response of data centers to different design and failure scenarios and details a comprehensive and efficient approach for simulating this performance.

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Ambulatory Assessment

European Psychologist ◽

10.1027/1016-9040.14.2.109 ◽

2009 ◽

Vol 14 (2) ◽

pp. 109-119 ◽

Cited By ~ 66

Author(s):

Ulrich W. Ebner-Priemer ◽

Timothy J. Trull

Keyword(s):

Real Time ◽

Clinical Psychology ◽

Real Life ◽

Ambulatory Assessment ◽

Computer Assisted ◽

Affective Valence ◽

Time Data ◽

Physiological Processes ◽

Context Specific ◽

Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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