49 research outputs found
STARTING UP A NEW B2C BUSINESS
No full textEveryone who wanted to start their own businesses faced with the problem of lack of information on how to start a new business in general, and about the features of doing business in a particular area.
The thesis reveals questions about what steps need to be taken to launch a premium burger restaurant on the Helsinki market, and moreover the research considers the reasonability of its launch.
To find out the state of the market and the industry as a whole, the author conducts two types of research, namely: the researcher conducts two qualitative interviews with the founders of successful premium burger restaurant chains in Helsinki and beyond, and also the writer conducts a quantitative market segmentation survey to define target customers for the new restaurant.
In conclusion, the author of the thesis creates a viable business plan on the basis of conducted researches and knowledge gained during university studies. Currently, the company is on the stage of development and the management team searches for funding to start the restaurant
BlogForever D2.6: Data Extraction Methodology
No full textThis report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform
The Matrix Method of Representation, Analysis and Classification of Long Genetic Sequences
No full textThe article is devoted to a matrix method of comparative analysis of long nucleotide sequences by means of presenting each sequence in the form of three digital binary sequences. This method uses a set of symmetries of biochemical attributes of nucleotides. It also uses the possibility of presentation of every whole set of N-mers as one of the members of a Kronecker family of genetic matrices. With this method, a long nucleotide sequence can be visually represented as an individual fractal-like mosaic or another regular mosaic of binary type. In contrast to natural nucleotide sequences, artificial random sequences give non-regular patterns. Examples of binary mosaics of long nucleotide sequences are shown, including cases of human chromosomes and penicillins. The obtained results are then discussed
Hypothesis of Cyclic Structures of Pre- and Consciousness as a Transition in Neuron-like Graphs to a Special Type of Symmetry
No full textWe study the proposed statistical kinetic model for describing the pre- and consciousness structures based on the cognitive neural networks. The method of statistics of the growth graph systems and a possible transition to symmetric structures (a kind of phase transition) is applied. With the complication of a random Erdőos-Rényi (ER) graph during the percolation transition from the tree structure to the large cluster structures is obtained. In the evolutionary model two classes of algorithms have been developed. The differences between the cycle parameters in the obtained neural network models can reach thousands or more times. This is due to the tree-like architecture of the neural graph, which mimics the columnar structures of the neocortex. These cluster and cyclic structures can be interpreted as the primary elements of consciousness and as a necessary condition for the effect of consciousness itself. The comparison with other known theoretical mainly statistical models of consciousness is discussed. The presented results are promising in neurocomputer interfaces, man-machine systems and artificial intelligence systems
An Optimization Algorithm of Synthesizing a Feed-Forward Neural Network to Determine a Human Functional State Using Stabilometry Data
No full textBalance is crucial to an individual\u27s quality of life and functional performance. Stability measurement analysis and balance assessment rely on center-of-pressure coordinates and numerical data. Although machine learning algorithms have been applied to analyze stabilization measurements, accurately determining an individual\u27s balance stability remains a challenge despite promising results. This study assesses the efficacy of a classification model—specifically, artificial neural networks (ANNs) utilizing an evolutionary algorithm (EA)—trained on three stability indicators to evaluate human health status. The methodology involved enhancing the learning process of artificial neural networks (ANNs) by dividing the hidden layers into multiple ANNs based on the number of neurons, optimizing them using an evolutionary algorithm, and then combining them to formulate new optimal hidden layers. This method expedited the optimization process and determined optimal designs. This study illustrates that optimal learning phases enhance the selection of appropriate artificial neural network architectures for distinguishing between healthy and diseased conditions, attaining accuracy rates of 99% to 100% for the A-indicator, 98% to 100% for the AW-indicator, and 97% to 100% for the AXY-indicator. The findings demonstrate that the integration of evolutionary algorithms and artificial neural networks markedly enhances predictive accuracy in healthcare, necessitating additional research to corroborate these results
Computer Visualization of Julia Sets for Maps beyond Complex Analyticity
No full textUsing the computer program creating Julia sets for two-dimensional maps we have made computer animation showing how Julia sets for the Peckham map alters when the parameter of the map is changing. The Peckham map is a one-parameter map which includes the complex map z=z^2+c, and is nonanalytical for other values of the parameter. Computer animation of Julia fractal sets allows seeing how patterns typical for complex maps gradually destroy
Spectral Decomposition of Mappings of Molecular Genetic Information in the System Basis of Single Nucleotide Functions
No full textThis paper presents and visualizes examples of large amounts of genetic information using a new class of cognitive computer graphics algorithms. These algorithms are related to the semiotics of perception and allow the interpretation of those properties of nucleotide sequences that are difficult to perceive by simple reading or by standard means of statistical analysis. This article summarizes previously presented algorithms for visualizing long nucleic acids based on the primary Hadamard–Walsh function system. The described methods allow us to produce one-dimensional mappings of nucleic acids by levels corresponding to their scale-integral physicochemical parameters and construct a spectral decomposition of the nucleotide composition. An example of the spectral decomposition of parametric representations of molecular genetic structures is given. In addition, a multiscale composition of genetic functional mappings visualizing the structural features of nucleic acids is discussed
Parametric Multispectral Mappings and Comparative Genomics
No full textThis article describes new algorithms that allow for viewing genetic sequences in the form of their multispectral images. We presented examples of the construction of such mappings with a demonstration of the practical problems of comparative genomics. New DNA visualization tools seem promising, thanks to their informativeness and representativeness. The research illustrates how a novel sort of multispectral mapping, based on decomposition in several parametric spaces, can be created for comparative genetics. This appears to be a crucial step in the investigation of the genetic coding phenomenon and in practical activities, such as forensics, genetic testing, genealogical analysis, etc. The article gives examples of multispectral parametric sets for various types of coordinate systems. We build mappings using binary sub-alphabets of purine/pyrimidine and keto/amino. We presented 2D and 3D renderings in different characteristic spaces: structural, integral, cyclic, spherical, and third-order spherical. This research is based on the method previously developed by the author for visualizing genetic information based on new molecular genetic algorithms. One of the types of mappings, namely two-dimensional, is an object of discrete geometry, a symmetrical square matrix of high dimension. The fundamental properties of symmetry, which are traced on these mappings, allow us to speak about the close connection between the phenomenon of genetic coding and symmetry when using the developed mathematical apparatus for representing large volumes of complexly organized molecular genetic information
