Problems

Project 1: Multi-frame denoising of still images Company: MM Solutions AD A sequence of 8 images are captured quickly one-by-one while camera is held in hand and unintentional hand shake is present. When capturing in low light conditions (<20Lux), the images appear blurred and noisy because the camera uses long exposure (1/15..1/5 sec) and high gain (ISO). The target is to combine multiple frames to produce an image with less noise and less (ideally no) blur. The processing algorithm should not be too computationally expensive. As usual in the image processing, the target is to get a good looking image, rather than removing the noise and the blur to achieve the ground-truth latent image. So any brain-hacking tricks are acceptable. Good-looking image means: no unnatural artifacts. Better little less sharpness than having artifacts (e.g. ringing). little high-frequency noise (up to STD about 1-2 for 8-bit image) creates an impression of sharper image the brain is extremely sensitive to the quality of straight edges and less sensitive to noise, present in image areas with fine details (grass, leaves). Full description: download.

Project 2: Optimal cutting problem Company: STOBET ltd. We have a large piece of steel sheet with dimensions X=1500 mm, Y=12000 mm. In this big sheet we have to locate maximum number of small plates of given profiles. The contour of the plates can be square, rectangle, trapeze, any non crossing closed polyline, consisting of line segments only. The dimensions of the plates are given by the coordinates of the vertices of the polylines as follows: Plate 1 : (X1, Y1; X2, Y2; X3, Y3) Plate 2 : (X1, Y1; X2, Y2; X3, Y3; X4, Y4; X5, Y5) ....................... Plate N : (X1, Y1; X2, Y2; X3, Y3; X4, Y4) The numbers K1, K2, . . . , KN of the pieces of plates with given profile, which must be situated on the steel sheet, are given. In the process of optimization some plates can be rotated for best fit. The aim is to locate maximum small plates in the given big steel sheet. A distance for cutting must be left between the plates. This distance is about 5 mm. Full description: download.

Project 3: Authenticity Management Algorithm for Digital Images Company: Adastra Bulgaria An Android application is used for taking pictures. Those pictures need to be digitally signed in order to verify their authenticity later. The task is to create an algorithm which adds a digital watermark to an image and a corresponding algorithm which verifies if a given image is watermarked by the original algorithm. The following conditions must be met: The algorithm must be able to detect if the image has been tampered with – e.g. re-saving, cropping, resizing, editing small parts of the image in a photo-editing software, copying and moving regions, etc. There should be no visibly discernible difference between the original image and the watermarked image. Watermark verification should not require the original image. The watermark embedded in an image generated by using a particular marking key must be detected only by providing the corresponding information to the verification algorithm. All other side information provided to the verification algorithm should fail to detect the mark. The insertion of a mark by unauthorised parties should be difficult. The watermark should be capable of being embedded in the compressed domain. Full description: download.

Project 4: Laboratory calibration of a MEMS rate gyro sensor Company: BG Drilling Solutions ltd. Calibration is essential for providing the maximum of sensor specification. It includes calculation of couple parameters (constants) used to normalize measured data and more often include bias (offset), sensitivity (scale factor) and misalignment. Here we will focus on gyroscopes calibration. 3D gyroscopes measure the angular velocity in inertial space around three perpendicular sensitivity axes. Thus, it allows for the orientation of an object to be determined. In general, the orientation of a rigid body is the position of its coordinate system observed relative to a reference coordinate system with the same origin. The orientation can be described by a rotation that would move the rigid body’s coordinate system, which is initially aligned with the reference coordinate system, to its new position. When working with gyroscope measurements, we consider the gyroscope as the rigid body and the inertial space coordinate system as the reference system. The measured angular velocity determines the rotation required to move the sensor to its new position. There are several methodologies that provide solution for the problem of mutual calibration of MEMS sensors – gyroscopes. Those methods, however are quite complex and computationally expensive, require very expensive test equipment, long time for development and assume some initial calibration of the sensors. A simple and quick solution for laboratory-based calibration is needed, that to be used as a quick calibration, followed by a high-precision calibration, which should cover the temperature and aging deviations of the calibration parameters. Full description: download.

Project 5: Future Cyber Attacks Modelling & Forecasting Company: TechnoLogica Ltd. Modern digital world is constantly presenting new challenges, resulting from cyber-physical clashes. One of the greatest problems in the present context is adequately to react towards new threats and expected attacks in the evolving modern world. Both social and technological system components have to be studied in this sense. A useful approach in support of the problem general coping is fusing expert, observation and reference data in weighted graph-based analytical models. Fur- ther, these however have to be adequately assessed and studied from multiple cyberattack dynamic perspective. Five key steps towards solving the problems could be defined: Selection of typical cyberattacks for further exploration in accordance with future digital space threats evolution prognosis; Models definition for the selected cyberattacks in a suitable future explo- ration context; Multicriteria selection for models overall holistic assessment; Software working environments selection and models machine prototyping; Numerical simulations of the developed models and results discussion. Full description: download.

Project 6: Post-Processing for Beam Elements: Calculating the Second Order Work and Strain Energy Company: Gruner Modern design of excavation pits includes often the simulation of the problem using Finite Element (FE) models. Primary objective for this kind of models is to predict deformations of the excavation pit support and the surroundings. As a secondary objective, it would be very useful to know, if the modelled structure is near to a failure state or not. For this kind of modelling task, usually a commercial software FE package is used as a black-box model with no access to the source code and no option for altering the algorithms included in the code. This is the case because this kind of software packages are widely known, well tested and accepted by the professional engineer community. To model excavation pits and especially their support usually a plain-strain analysis is performed where beam elements are employed. The software package used by the company (Plaxis), and this FE code is widely used in geotechnical engineering. This software package provides a beam element based on Mindlin’s theory of plates. A well-known criterion for failure (bifurcation in the solution) for models using elasto-plastic formulation is the Hill’s failure criterion based on the second order work. Unfortunately, the software package Plaxis does not calculate the second order work. Furthermore, it only provides a small set of output variables at the element nodes. The objective is to calculate the second order work for this kind of beam elements as a post-processing after finishing the FE-simulation based only on the nodal variables provided in the programs output. The output provided at each node: total nodal displacements in direction x total nodal displacements in direction y total nodal rotation Normal force extrapolated to the node Shear force extrapolated to the node Bending moment extrapolated to the node Full description: download.

Project 7: Mathematical Model of Residential Storage Water-heating System Company: Melissa Climate An electric water heater consists of: an inner steel tank, that holds the water being heated, insulation that surrounds the tank so as to decrease the amount of heat loss, pipe to allow cold water to enter the tank, pipe to allow hot water to leave the tank, thermostat that reads and controls the temperature of the water inside the tank, heating element that heats the water by means of electricity and other components for safety and maintenance. Water temperature inside the heater is controlled by the mechanical thermostat. The temperature may usually be set by the user somewhere in between 40 and 70˚C. A microcontroller is used to gather realtime information from a water heater. The information is collected by different sensors and consists of data about: current temperature of the cold water pipe, temperature of the hot water pipe, environment temperature (home temperature), electric current and voltage. Important notice – the temperature sensors of the cold and hot water pipes are installed ONTO the pipe itself. There is significant temperature loss depending on the pipe diameter, material and others. The task is to create model of the dynamics of the water heater: The water heater model should simulate the temperature variations over time. For the model we can assume that the user has set the mechanical thermostat to 70˚C. The model should take into account that the temperature in the tank is updated by: Energy input from the heater; Heat loss through the insulation; Heat loss due to cold and hot water mixture when consuming hot water; Unknown consumption of hot water throughout the day. The water heater model should be validated against measured data. Measured data and more information can be found at seemelissa.com/esgi2016 Full description: download.