No. 9/2019

Online archive of Computer Science and Mathematical Modelling

No. 9/2019

  1. A. Ameljańczyk - Fuzzy set in modeling of patient’s disease states.
    Pages: 5 - 11
    Abstract: The paper concerns the mathematical modeling of patient’s disease states and disease unit patterns for the needs of algorithms supporting medical decisions. Due to the specificity of medical data and assessments in the modeling of patient’s disease states as well as diseases, the fuzzy set methodology was used. The paper presents a number of new characteristics of fuzzy sets allowing to assess the quality of medical diagnosis. In addition, a definition of a multi-aspect fuzzy set is presented, which may be useful in supporting medical diagnostics based on multi-criteria similarity models. The presented results can be used in the construction of algorithms for assessing the patient's state of health and mainly in the construction of algorithms for supporting diagnostic processes.
    Keywords fuzzy set, multi-aspect fuzzy set, fuzzy sets similarity, fuzzy pattern of disease unit, medical diagnosis.
    Full article: PDF icon 5_11_aameljanczyk_csmm_9_2019.pdf
  2. K. Antczak - On regularization properties of artificial datasets for deep learning.
    Pages: 13 - 18
    Abstract: The paper discusses regularization properties of artificial data for deep learning. Artificial datasets allow to train neural networks in the case of a real data shortage. It is demonstrated that the artificial data generation process, described as injecting noise to high-level features, bears several similarities to existing regularization methods for deep neural networks. One can treat this property of artificial data as a kind of “deep” regularization. It is thus possible to regularize hidden layers of the network by generating the training data in a certain way..
    Keywords deep learning, regularization, artificial data.
    Full article: PDF icon 13_18_kantczak_csmm_9_2019.pdf
  3. A. Chojnacki, F. Darnowski - A model of the process of writing and deleting file information on a disk with NTFS.
    Pages: 19 - 25
    Abstract: This paper aims at demonstrating a mathematical model of the process of writing and deleting information about files on a disk, using the contents of the $MFT system file, i.e. in a file generated in the NTFS (New technology File System). The presented model uses the language of control theory, where the state of the system is equal to the state of the disk and the state of the $MFT file, and where control is understood as undertaking the action of writing or deleting. The deterministic nature of the process and its stationarity were assumed. Then, based on the transition function after its specification, we suggest constructing further inverse images of possible prior states at subsequent stages of data writing or deletion. The obtained results form the basis for the implementations developed.
    Keywords hard drive, NTFS, $MFT.
    Full article: PDF icon 19_25_achojnackifdarnowski_csmm_9_2019.pdf
  4. M. Pachnik - Methods of generating test data for carrying out the fuzzing process.
    Pages: 27 - 31
    Abstract: The article presents and compares modern methods of generating test data in the process of automatic software security testing, so called fuzz testing. The publication contains descriptions of methods used, among others, in local, network or web applications, and then compares them and evaluates their effectiveness in the process of ensuring software security. The impact of the quality of test data corpus on the effectiveness of automated security testing has been assessed.
    Keywords fuzzing, test data corpus, security vulnerabilities.
    Full article: PDF icon 27_31_mpachnik_csmm_9_2019.pdf
  5. A. Woźniak, T. Nowicki - The Problem of Effective Deployment Architecture in SOA.
    Pages: 33 - 44
    Abstract: Service Oriented Architecture is popular in many organizations. In particular, it has already deeply rooted in large corporations that need to automate entire business processes and implement them in many systems. It has a unique feature that allows unambiguously indicate service that is to realise business process step. That indication is possible to show directly in BPMN diagram. Thus, it is possible to trace which server has used resources to implement the service and how much of those resources were needed. Therefore, it is possible to build an optimization task that, with limited and unreliable resources, will determine such allocation of components to servers and such an algorithm for assigning tasks to them, so that the processes will work as well as possible. The article presents a model of such an optimization task. This model consists of four layers. The Organization Layer describes the system environment – the types and frequency of initiating business process instances. The Integration Layer describes the business processes and indicates the services that should be performed at every step. The Component Layer describes component characteristics and what services they provide. In Server Layer both: server characteristics and runtime environments necessary for the component to run are described. Finally, the optimization task and evaluation criteria are formulated.
    Keywords SOA deployment, mathematical model, system architecture optimization.
    Full article: PDF icon 33_44_tnowickiawozniak_csmm_9_2019.pdf