This is the protein PDB dataset for the article "Novel Algorithm for Improved Protein Classification Using Graph Similarity". This dataset consists of 9 classes of proteins.

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README.txt for simulation files IEEE_Collaboration_N_entities_2021.mdl and IEEE_2_Platforms_federation_SF_2021.mdl

This is a README.txt for the model published on the paper titled:

Improving IoT Federation Resiliency with Distributed Ledger Technology, 2021, Elo T, et al.

This readme describes how to replicate the main simulation results from the paper using a Vensim

model file. The model file has been generated using the Vensim DSS Macintosh Version

8.0.7 Double Precision x64.

README.txt for simulation files IEEE_Collaboration_N_entities_2021.mdl and IEEE_2_Platforms_federation_SF_2021.mdl

This is a README.txt for the model published on the paper titled:

Improving IoT Federation Resiliency with Distributed Ledger Technology, 2021, Elo T, et al.

This readme describes how to replicate the main simulation results from the paper using a Vensim

model file. The model file has been generated using the Vensim DSS Macintosh Version

8.0.7 Double Precision x64.

To replicate the results of the 2 member federation do the following:

Open the provided model file (“2_Platforms_federation_SF_2021.mdl”) with Vensim DSS Macintosh Version 8.0.7 Double Precision x64, or similar

Push "Simulate".

You obtain the base case result graph of Figure 4 (leftmost sub picture).

Right click “fixes effect on harm multiplier” from the model.

Push “Equation”.

Edit the value in “Equations”. It reads: “1”.

Change it to “0.96”.

Push “OK”.

Push "Simulate".

You obtain the middle case result graph of Figure 4 (middle sub picture).

Right click “fixes effect on harm multiplier” from the model.

Push “Equation”.

Edit the value in “Equations”. It reads: “0.96”.

Change it to “0.92”.

Push “OK”.

Push "Simulate".

You obtain the middle case result graph of Figure 4 (rightmost sub picture).

To replicate the results of the associated paper do the following:

Open the provided model file (“IEEE_Collaboration_N_entities_2021.mdl”) with Vensim DSS Macintosh Version 8.0.7 Double Precision x64, or similar

Push “Simulate” to obtain the baseline simulation for the federation of 10 members

To obtain the spread graph around this push “Sensitivity”

Input “0.119935” to the “Minimum”. Input “0.119939” to the “Maximum”.

Choose “RANDOM_UNIFORM” as “Distribution”.

Input “500” to “number of rounds”.

Push “Parameter”

Choose “fixes effect on harm multiplier”. Push OK.

Push “Next”.

Answer “Yes” to the question: “Do you want to incorporate your current editing?”

Choose “Finnish” at “Savelist control” dialog.

Push Select All button from simulation setup control.

Push Finish button in the same dialog.

A Sensitivity Simulation begins.

After the run you return to model view. Then:

Choose “Federation health” from the model by left clicking it.

Choose Sensitivity Graph from the left button menu.

A Window appears replicating the result for Fig. 7 of the publication.

To replicate the results of the 3 member federation do the following:

Open the provided model file (“IEEE_Collaboration_N_entities_2021.mdl”) with Vensim DSS Macintosh Version 8.0.7 Double Precision x64, or similar

Right click “fixes effect on harm multiplier” from the model.

Push “Equation”.

Edit the value in “Equations”. It reads: “0.119935”.

Change it to “0.5”.

Push “OK”.

Push “Subscripts”.

Push “Edit…”.

Edit the value in “Equations”. It currently reads: “(f1-f10)”.

Change it to “(f1-f3)” to simulate a three member federation.

Push “OK”.

Push “Close” in “Subscript Control” dialog.

Push simulate to get a new baseline for a three member federation.

Push “Sensitivity”.

Check that “Number of” reads “500”.

Select the simulation setup line from "Currently active parameters".

Push "Modify Selected".

Input “0.500” to the “Minimum”.

Input “0.502” to the “Maximum”.

Check that “Distribution” is “RANDOM_UNIFORM”.

Push “Parameter”.

Choose “fixes effect on harm multiplier”. Push OK.

Push “Next”.

Answer “Yes” to the question: “Do you want to incorporate your current editing?”

Choose “Finnish” at “Savelist control” dialog.

A Sensitivity Simulation begins.

This simulation is visible faster due to 3 member federation being much more simple to simulate that the 10 member federation.

Choose “Federation health” from the model by left clicking it.

Choose Sensitivity Graph from the left button menu.

A Window appears replicating the result for Fig. 6 of the publication.

To replicate the results of the 3 member federation do the following:

Open the provided model file (“IEEE_Collaboration_N_entities_2021.mdl”) with Vensim DSS Macintosh Version 8.0.7 Double Precision x64, or similar

Push “Subscripts”.

Push “Edit…”.

Edit the value in “Equations”. It currently reads: “(f1-f10)”.

Change it to “(f1-f5)” to simulate a three member federation.

Push “OK”.

Push “Close” in “Subscript Control” dialog.

Right click “initial success” from the model.

Push “Equation”.

Edit the value in “Equations”. It reads: “50”.

Input a vector from Table 3: "100,50,50,5,5".

Push “Close”.

Right click “fixes effect on harm multiplier” from the model.

Push “Equation”.

Edit the value in “Equations”. It reads: “0.119935”.

Change it to “0.2”.

Push “OK”.

To obtain the spread graph around this push “Sensitivity”

Input “0.20” to the “Minimum”. Input “0.26” to the “Maximum”.

Choose “RANDOM_UNIFORM” as “Distribution”.

Input “500” to “number of rounds”.

Push “Parameter”

Choose “fixes effect on harm multiplier”. Push OK.

Push “Next”.

Answer “Yes” to the question: “Do you want to incorporate your current editing?”

Choose “Finnish” at “Savelist control” dialog.

Push Select All button from simulation setup control.

Push Finish button in the same dialog.

A Sensitivity Simulation begins.

After the run you return to model view. Then:

Choose “Federation health” from the model by left clicking it.

Choose Sensitivity Graph from the left button menu.

A Window appears replicating the result for Fig. 8 of the publication.

IEEE_Collaboration_N_entities_qualitative_with_DLT_2021.png:

This model is qualitative so only a graphical presentation as a bitmap is given.

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Many companies, e.g., Facebook and YouTube, use the REST architecture and provide REST APIs to their clients. Likeany other software systems, REST APIs need maintenance and must evolve to improve and stay relevant. Antipatterns—poor designpractices—hinder this maintenance and evolution. Although the literature defines many antipatterns and proposes approaches for their(automatic) detection, theircorrectiondid not receive much attention.

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A Course on Literature Searching/Compiling/Understanding for Support of Research/Projects

Unzip file to see supplementary materials.

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This dataset contains the ontologies and instruments developed in the MIIDAS Project

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<p>The dataset comprises 2035 images from 14 different software architectural patterns (100+ images each), viz., Broker, Client Server, Microkernel, Repository, Publisher-Subscriber, Peer-to-Peer, Event Bus, Model View Controller, REST, Layered, Presentation Abstraction Controller, Microservices, and Space-based patterns.</p>

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A qualitative and quantitative extension of the chaotic models used to generate self-similar traffic with long-range dependence (LRD) is presented by means of the formulation of a model that considers the use of piecewise affine onedimensional maps. Based on the disaggregation of the temporal series generated, a valid explanation of the behavior of the values of Hurst exponent is proposed and the feasibility of their control from the parameters of the proposed model is shown.

fGn series used for simulations in the article "Sobre la Generación de Tráfico Autosimilar con Dependencia de Largo Alcance Empleando Mapas Caóticos Unidimensionales Afines por Tramos (Versión Extendida)", "On the Generation of Self-similar with Long-range Dependent Traffic Using Piecewise Affine Chaotic One-dimensional Maps (Extended Version)". Available at:

https://arxiv.org/abs/2104.04135.

https://easychair.org/publications/preprint/Xwx3.

They should be used in MATLAB R2009a.

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This dataset contains (1) the Simulink model of a three-phase photovoltaic power system with passive anti-islanding protections like over/under current (OUC), over/under voltage (OUV), over/under frequency (OUF), rate of change of frequency (ROCOF), and dc-link voltage and (2) the results in the voltage source converter and the point of common coupling of the photovoltaic system during islanding operation mode and detection times of analyzed anti-islanding methods.

The anti-islanding protection relays are included in the "Relay Protection Bus B20 (20 kV)" subsystem.

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This article explores the required amount of time series points from a high-speed computer network to accurately estimate the Hurst exponent. The methodology consists in designing an experiment using estimators that are applied to time series addresses resulting from the capture of high-speed network traffic, followed by addressing the minimum amount of point required to obtain in accurate estimates of the Hurst exponent.

fGn series used for simulations in the article "Preliminaries on the Accurate Estimation of the Hurst Exponent Using Time Series". Available at:

https://arxiv.org/abs/2103.02091.

https://www.techrxiv.org/articles/preprint/Preliminaries_on_the_Accurate....

https://easychair.org/publications/preprint/RQsp.

They should be used in Selfis01b.

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