Future Processing

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Future Processing

Future, Poland
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News Article | November 14, 2016
Site: www.realwire.com

Software development specialist takes top industry award against five other worldwide providers Future Processing has been named as Service Provider of the Year at the Global Sourcing Association’s (previously known as National Outsourcing Association) 2016 awards. Based in the heart of Silesia, a hotspot for software development, Future Processing was awarded the award against five other worldwide nominees in recognition of its excellence in the field. Future Processing has worked alongside a multitude of UK companies to provide services and software that is tailored to the needs of the client. The team’s wide range of expertise provides bespoke software to their clients, acting as an extension to the client’s team. GSA’s Service Provider of the Year recognises the development of both initial and ongoing business value to clients, continuous service innovation and the demonstrable commitment to the development and future of the industry. The award was presented to Future Processing at a ceremony at London’s Intercontinental last night to a crowd of 400 attendees. “I am delighted that Future Processing has been acknowledged with such a prestigious award” said Jaroslaw Czaja, CEO and founder of Future Processing. “It’s brilliant recognition not just for our team, but for Poland as world leader in delivering digital solutions. Our focus is to continue to deliver business value to our clients, because ultimately, it’s the most important element in outsourcing projects. We would like to extend our thanks to our customers and will continue our innovative approach to deliver worldwide IT solutions.” About Future Processing Future Processing is an experienced Polish company that specialises in providing offshore software development services, mostly for European companies located in the UK and Scandinavia. Based in the heart of Silesia, it is at the hub of European software innovation, and employs and nurtures much of the technical talent that is available from the region. Customers include Staffcare, Parkeon, ista and Allocate Software. For more information, please visit www.future-processing.com For the latest information on Future Processing:


Cwiek M.,Future Processing | Nalepa J.,Silesian University of Technology
GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference | Year: 2014

This paper presents a fast genetic algorithm (GA) for solving the flexible job shob scheduling problem (FJSP). The FJSP is an extension of a classical NP-hard job shop scheduling problem. Here, we combine the active schedule constructive crossover (ASCX) with the generalized order crossover (GOX). Also, we show how to divide a population of solutions in the high-low fit selection scheme in order to guide the search efficiently. An initial experimental study indicates high convergence capabilities of the proposed GA.


Nalepa J.,Silesian University of Technology | Szymanek J.,Future Processing | Hayball M.P.,TexRAD Ltd | Brown S.J.,Cambridge Computed Imaging | And 3 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

    Heterogeneity is a well-recognized feature of malignancy associated with increased tumor aggression and treatment resistance. Texture analysis (TA) of images of various modalities, including, among others, CT, MRI or PET, can be applied to quantify the tumor heterogeneity and to extract useful information from images acquired in routine clinical practice without additional radiation or expense of further procedures. In this paper, we elaborate on the filtration-based approach to TA applied for extracting features from large sets of simulated images reflecting various clinical circumstances. The areas under receiver operating characteristic curves were used to assess the diagnostic performance of the derived biomarkers. We present and discuss their discriminative abilities in identifying heterogeneity and classifying images with simulated lesions of various characteristics and localized density variations. © Springer International Publishing Switzerland 2014.


Nalepa J.,Future Processing | Nalepa J.,Silesian University of Technology | Szymanek J.,Future Processing | Kawulok M.,Future Processing | Kawulok M.,Silesian University of Technology
Communications in Computer and Information Science | Year: 2015

In this paper, we propose a real-time algorithm for counting people from depth image sequences acquired using the Kinect sensor. Counting people in public vehicles became a vital research topic. Information on the passenger flow plays a pivotal role in transportation databases. It helps the transport operators to optimize their operational costs, providing that the data are acquired automatically and with sufficient accuracy. We show that our algorithm is accurate and fast as it allows 16 frames per second to be processed. Thus, it can be used either in real-time to process traffic information on the fly, or in the batch mode for analyzing very large databases of previously acquired image data. © Springer International Publishing Switzerland 2015.


Pawelczyk K.,Future Processing | Kawulok M.,Future Processing | Kawulok M.,Silesian University of Technology
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

In this paper we explore the possibilities of recognizing head orientation based on the appearance of the nose. We demonstrate that the features extracted from that region possess high discriminating power with regards to the head orientation. Extensive experimental validation study, performed using the benchmark data, confirmed high effectiveness of the proposed approach compared with the baseline techniques that rely on the analysis of the entire facial region. © Springer International Publishing Switzerland 2014.


Nalepa J.,Future Processing | Nalepa J.,Silesian University of Technology | Kawulok M.,Silesian University of Technology
Proceedings - 2013 IEEE International Symposium on Multimedia, ISM 2013 | Year: 2013

This paper introduces a new parallel algorithm (PA) for fast hand shape classification. This problem is challenging as a hand is characterized by a high number of degrees of freedom. Our objective is to design and implement a robust algorithm suitable for real-time applications. We show how the analysis time can be decreased, together with the increase of the classification accuracy, by the means of parallelization. Also, we propose to combine the shape contexts approach with the appearance-based techniques to increase the efficacy of the PA. An extensive experimental study confirms the effectiveness of the proposed PA compared with other state-of-the-art methods. © 2013 IEEE.


Radlak K.,Silesian University of Technology | Frackiewicz M.,Silesian University of Technology | Szczepanski M.,Silesian University of Technology | Kawulok M.,Silesian University of Technology | Czardybon M.,Future Processing
Proceedings - Frontiers in Education Conference, FIE | Year: 2015

In this paper, we present Adaptive Vision Studio (AVS) - a novel tool for creating image processing and analysis algorithms. AVS has been applied in post-graduate computer vision course for students of Automatic Control and Biotechnology at Silesian University of Technology. This software is a powerful environment with ready-for-use image analysis filters for computer vision experts as well as for engineers, who are beginners in this field. AVS has been published as a freeware version for noncommercial and educational purposes recommended for students and engineers, who want to learn how to develop complex image processing algorithms. Lite version of AVS is freely available at https://adaptive-vision.com. © 2015 IEEE.


Boryczka U.,University of Silesia | Dworak K.,Future Processing | Dworak K.,University of Silesia
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

This paper presents how techniques such as evolutionary algorithms (EAs) can optimize complex cryptanalysis processes. The main goal of this article is to introduce a special algorithm, which allows executing an effective cryptanalysis attack on a ciphertext encoded with a classic transposition cipher. In this type of cipher, the plaintext letters are modified by permutation. The most well-known problem, which is often solved with optimization techniques operating on a set of permutations, is the Travelling Salesman Problem (TSP). The mentioned algorithm uses a specially prepared function of assessment of the individuals with a set of genetic operators, used in the case of TSP problem. © Springer International Publishing Switzerland 2014.


Dworak K.,Future Processing | Dworak K.,University of Silesia | Boryczka U.,University of Silesia
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015

Nowadays, information security is based on ciphers and cryptographic systems. What evaluates the quality of such security measures is cryptanalysis. This paper presents a new cryptanalysis attack aimed at a ciphertext generated with the use of the SDES (Simplified Data Encryption Standard). The attack was carried out with a modified version of the BPSO (Binary Particle Swarm Optimization) algorithm. A well-adjusted version of this method can have a positive effect on the quality of the results obtained in a given period of time. © Springer International Publishing Switzerland 2015.

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