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In today’s context, it is essential to develop technologies to help older patients with neurocognitive disorders communicate better with their caregivers. Research in Brain Computer Interface, especially in thought-to-text translation has been carried out in several languages like Chinese, Japanese and others. However, research of this nature has been hindered in India due to scarcity of datasets in vernacular languages, including Malayalam. Malayalam is a South Indian language, spoken primarily in the state of Kerala by bout 34 million people.

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The Deepfake face detection task involves a facial image of unknown authenticity for testing. While most deepfake detection methods take only the image as input, our literature demonstrates that conditioning the deepfake detector on identity—i.e., knowing whose deepfake face the picture might be—can enhance detection performance. Existing deepfake detection datasets, such as FaceForensics++ and DFDC, do not include identity information for authentic and deepfake faces.

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401 Views

An understanding of local walking context plays an important role in the analysis of gait in humans and in the high level control systems of robotic prostheses. Laboratory analysis on its own can constrain the ability of researchers to properly assess clinical gait in patients and robotic prostheses to function well in many contexts, therefore study in diverse walking environments is warranted. A ground-truth understanding of the walking terrain is traditionally identified from simple visual data.

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This data set contains: 

- Training dataset: 271 CT-scans of inner ears used for optimization and training of the model. 

- Validation dataset: 70 CT-scans of inner ears used for external validation. 

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The dataset contained walking data of 41 volunteers, including 20 women and 21 men. Each volunteer walked on asphalt and SLATE roads for six times, each time for less than one minute. In addition, the dataset also included gait data on stairs and stairs. The data acquisition frequency is 100HZ, and a total of four sensors are used to collect data. The sensor numbered 001 is located on the left knee, the sensor numbered 001 is located on the right wrist, the sensor numbered 003 is located on the left ankle, and the sensor 004 is located on the back of the waist.

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In the realm of real-time communications, WebRTC-based multimedia applications are increasingly prevalent as these can be smoothly integrated within Web browsing sessions. The browsing experience is then significantly improved with respect to scenarios where browser add-ons and/or plug-ins are used; still, the end user's Quality of Experience (QoE) in WebRTC sessions may be affected by network impairments, such as delays and losses.

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121 Views

AnonTool - an open-source implementation of Anonymization API.

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Loceva - an evaluation tool for 802.11-based positioning systems.

Loceva is an evaluation tool for 802.11-based positioning systems. Loceva uses trace files generated by Loctrace to evaluate different kinds of positioning algorithms. A large number of state-of-the-art positioning algorithms are supported by Loceva. Loceva contains a lot of filters and generators to set up different scenarios and enable emulation.

Lastmodified :

2007-12-05

Dataname :

tools/analyze/location/loceva

File :

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To investigate whether a large-scale Bluetooth worm outbreak is viable in practice, we conducted controlled experiments and we gathered traces of Bluetooth activity in different urban environments to determine the feasibility of a worm infection 

date/time of measurement start: 2005-11-16

date/time of measurement end: 2005-11-26 

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Wireless contacts trace collected at the University Politehnica of Bucharest in the spring of 2012, using an application entitled HYCCUPS Tracer (http://hyccups.hpc.pub.ro), with the purpose of collecting contextual data from Android smartphones. It was run in the background and collected availability and mobile interaction information such as usage statistics, user activity, battery statistics, or sensor data, but it also gathered information about a device's encounters with other nodes or with wireless access points.

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