##Connect Me

###Description Link: https://github.com/etzemis/ConnectMe

Users are able to insert a destination, create groups with nearby travellers and move towards their common destinations

##Fat Finger

###Abstract Modern mobile and tablet devices, are operated through a set of multi-finger gestures, which are supposed to produce a natural and seamlessly fluent interaction with the users. Despite the vast evolution of the available ways used to interact with current mobile devices, their fundamental principle has not been alternated; assuming that only 2-dimensional (x-y position) input can be extracted. We introduce Fat Finger, in an attempt to utilize the contact size of the finger touching the screen as an additional (3rd) dimension of input. The aim is to comprehend the capabilities and precision we can acquire, when using contact size as the principal source of input. An experiment implementation was achieved in the form of target selection tasks, aiming to realize the impact of visual feedback, size and position of targets, with the utter target being to set a limit for the maximum perceivable contact size levels. A user study was performed, where users had to precisely hit predefined targets, by alternating the contact size between their finger and the screen. We found that eight (8) is the upper limit of distinguishable contact size levels that users can perceive when visual feedback is supplied, which drops down to three (3) otherwise.

###Abstract We present a study to comparatively evaluate the performance of computer-based 2D and 3D pointing tasks. In our experiments, based on the ISO 9241-9 standard methodology, a Microsoft Kinect device and a mouse were used by seven participants. For the 3D experiments we introduced a novel experiment layout, supplementing the ISO. We examine the pointing devices’ conformance to Fitts’ law and we measure a number of extra parameters that describe more accurately the cursor movement trajectories. Throughput, meas- ured in bits per second is the most important performance measure. For the 2D tasks using Microsoft Kinect, Throughput is almost 39% lower than using the mouse, Target Re-Entry is 10 times up and Missed Clicks count is almost 50% higher. However, for the 3D tasks the mouse has a 9% lower Throughput than the Kinect, while Target Re-Entry and Missed Clicks are almost identical. Our results are also compared to older studies, and we finally show that the Kinect, operated by the user’s hand and voice, is a suitable and effective input method for pointing and clicking, especially in 3D tasks.

#Projects within Courses

##Haskell

Developed a Parser and Interpreter of a Context-Free Grammar using Monads.

##JAVA - RPC, Modularity, Atomicity

Developed a Sever-Client model in JAVA in which all the following aspects were encountered: RPC mechanism, modularity, atomicity, concurrency control and recovery, performance, fault-tolerance and redundancy. Also, distributed protocols for agreement and replication, and large-scale data processing.

##Python - Cluster Architectures Parallelized sequential code for 3 real-life simulation problems with target on increasing computation speed linearly to the number of CPUs used. The techniques used were vectorization, shared memory, and PyPastSet.

##Machine Learning -Built an affine model of data provided by the Sunspot Index Data Center (SIDC) by applying both a linear and a non-linear classification method. The goal was to predict the number of sunspots based on previous observations.

-Performed binary classification using SVMs, Principal Component Analysis and 3-means clustering on the http://archive.ics.uci.edu/ml/datasets/seeds. Classified the 3 image classes using discriminant analysis (LDA) and the nearest neighbor classification.

Developed a Hand-Tracking application in LabVIEW 2011 using Microsoft Kinect. The project concerned: getting the depth image from Kinect, eliminating user’s hand and exporting the 3D hand-coordinates, as it moves. No skeleton-tracking libraries were used.

Developer of an application for mobile phones using JAVA J2ME in which users can play tic-tac-toe and chat with opponents. Web Services (XML, SOAP, and WSDL) and JDBC were used. It developed for the Software development for Telecommunications course.