Machine Learning

This dataset is from apache access log server. It contains: ip address, datetime, gmt, request, status, size, user agent, country, label. The dataset show malicious activity in IP address, request, and so on. You can analyze more as intrusion detection parameter.

Paper: http://jtiik.ub.ac.id/index.php/jtiik/article/view/4107

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4276 Views

This dataset is in support of my Research paper 'Design of 6-DoF Combat Quadcopter'.

Preprint:   

The system is basic, on existing designs.It is very simple for any graduate,degree holder.

 

Related Claim : Novel ß Non-Linear Theory

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1225 Views

This is an open-access page. All content can be freely downloaded after sign-up. This webpage has datasets of 'Computational Biology' and Novel ß-Bio models for Woman/Females with clinical investigation in simulation, proposed by me as Self-Claimed advancements .

I. Computational Biology Research Papers

These papers are like tutorial papers explored and based on known theory, and do not contain my 100% original work. To freely download, pls. click on title.  

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1759 Views

This is a two-part open-access page -'Data:B-Bio Models-1 and 'Data:B-Bio Models-2'. This webpage contains datasets and models, with clinical investigation in simulation, proposed by me which are Self-Claimed advancements. All the content can be freely downloaded after sign-up. 

I. Novel B-Bio Models  

To freely download, pls. click on title.  Make sure you have read My ORCid, Disclaimer and Legal Disclosure Statement.

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3346 Views

The detection of settlements without electricity challenge track (Track DSE) of the 2021 IEEE GRSS Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), Hewlett Packard Enterprise, SolarAid, and Data Science Experts, aims to promote research in automatic detection of human settlements deprived of access to electricity using multimodal and multitemporal remote sensing data.

Last Updated On: 
Thu, 01/06/2022 - 03:33
Citation Author(s): 
Colin Prieur, Hana Malha, Frederic Ciesielski, Paul Vandame, Giorgio Licciardi, Jocelyn Chanussot, Pedram Ghamisi, Ronny Hänsch, Naoto Yokoya

A medium-scale synthetic 4D Light Field video dataset for depth (disparity) estimation. From the open-source movie Sintel. The dataset consists of 24 synthetic 4D LFVs with 1,204x436 pixels, 9x9 views, and 20–50 frames, and has ground-truth disparity values, so that can be used for training deep learning-based methods. Each scene was rendered with a clean pass after modifying the production file of Sintel with reference to the MPI Sintel dataset.

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2246 Views

This dataset contains RF signals from drone remote controllers (RCs) of different makes and models. The RF signals transmitted by the drone RCs to communicate with the drones are intercepted and recorded by a passive RF surveillance system, which consists of a high-frequency oscilloscope, directional grid antenna, and low-noise power amplifier. The drones were idle during the data capture process. All the drone RCs transmit signals in the 2.4 GHz band. There are 17 drone RCs from eight different manufacturers and ~1000 RF signals per drone RC, each spanning a duration of 0.25 ms. 

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16440 Views

This dataset is composed of side channel information (e.g., temperatures, voltages, utilization rates) from computing systems executing benign and malicious code.  The intent of the dataset is to allow aritificial intelligence tools to be applied to malware detection using side channel information.

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1000 Views

The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable forestall of visual impairment. One challenge that limits the adoption of computer-aided diagnosis tool by ophthalmologists is the number of sight-threatening rare pathologies, such as central retinal artery occlusion or anterior ischemic optic neuropathy, and others are usually ignored.

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26465 Views

Predicting energy consumption is currently a key challenge for the energy industry as a whole.  Predicting the consumption in a certain area is massively complicated due to the sudden changes in the way that energy is being consumed and generated at the current point in time. However, this prediction becomes extremely necessary to minimise costs and to enable adjusting (automatically) the production of energy and better balance the load between different energy sources.

Last Updated On: 
Wed, 12/23/2020 - 12:16
Citation Author(s): 
Isaac Triguero

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