Analysis of ROBECO data by neural networks

Our task was to find a model for classifying ROBECO clients into four classes according to their degree of satisfaction. Each client was represented by a vector of 30 variables, which could be split into two groups: variables related to the specific client and socio-geographical variables characterizing the area in which the client lived. The original set contained 21, 90, 288, and 146 vectors from group 1, 2, 3, and 4 respectively. Additionally, an independent validation set was provided with 3, 12, 48 and 32 vectors from corresponding groups.Neural network; Classification; Client satisfaction;

Towards Data Mining in Large and Fully Distributed Peer-To-Peer Overlay Networks

The Internet, which is becoming a more and more dynamic, extremely heterogeneous network has recently became a platform for huge fully distributed peer-to-peer overlay networks containing millions of nodes typically for the purpose of information dissemination and file sharing. This paper targets the problem of analyzing data which are scattered over a such huge and dynamic set of nodes, where each node is storing possibly very little data but where the total amount of data is immense due to the large number of nodes. We present distributed algorithms for effectively calculating basic statistics of data using the recently introduced newscast model of computation and we demonstrate how to implement basic data mining algorithms based on these techniques. We will argue that the suggested techniques are efficient, robust and scalable and that they preserve the privacy of data

From Xception to NEXcepTion: New Design Decisions and Neural Architecture Search

In this paper, we present a modified Xception architecture, the NEXcepTion network. Our network has significantly better performance than the original Xception, achieving top-1 accuracy of 81.5% on the ImageNet validation dataset (an improvement of 2.5%) as well as a 28% higher throughput. Another variant of our model, NEXcepTion-TP, reaches 81.8% top-1 accuracy, similar to ConvNeXt (82.1%), while having a 27% higher throughput. Our model is the result of applying improved training procedures and new design decisions combined with an application of Neural Architecture Search (NAS) on a smaller dataset. These findings call for revisiting older architectures and reassessing their potential when combined with the latest enhancements.Comment: Accepted at ICPRAM 2023 for a 20 minutes oral presentatio

Wartość obrazowania dyfuzyjnego MR za pomocą aparatu niskopolowego w ostrym okresie udaru niedokrwiennego mózgowia

Background: Early detection of ischemic changes in the brain is significant for prompt initiation of suitable, especially thrombolytic, treatment. Until recently, the essential diagnostic method was computerized tomography (CT), despite its limited value in detecting and assessing ischemic area extent. CT perfusion, magnetic resonance (MR) perfusion, and diffusion MR (DWI, diffusion weighted imaging) are currently considered the most sensitive methods. Until recently, DWI was available only in modern, high-field MR units (1.5-3 Tesla). The aim of our study was to evaluate the usefulness of low-field DWI performed with a modern low-field MR system (with appropriate software) in patients with early ischemic stroke. Material/Methods: Forty patients with clinically diagnosed ischemic stroke were examined 1-12 hours after onset of symptoms. In all patients, non-contrast CT followed by DWI was performed. The time between both studies did not exceed 30 minutes. After 2 weeks, follow-up MR (FLAIR, T2 and Tl-weighted images) was performed in 36 patients. Results: Foci of increased signal intensity, localized in the cerebral hemispheres and posterior fossa, were detected on the DWI images of 30 patients. Follow-up MR studies confirmed ischemic lesions in 24 cases. Among the 10 patients in whom ischemic changes had not been diagnosed in DWI examination, the follow-up MR revealed such in 4 cases. The sensitivity, specificity, and accuracy of DWI were calculated as 87.5%, 50% and 78%, respectively. Conclusions: DWI examination with a low-field MR system enables efficient detection of brain lesions in the early stage of ischemic stroke

The development of the advanced web shop based on purchase history

The goal of thesis is to develop a typical web shop application with some additional functionality. This functionality enables web shop customers to browse products in a more efficient way and thus makes shop more profitable. For this purpose, we developed a specific mechanism that handles product presentation in customer adapted way. First we describe technologies used for development. Programing language C# is presented shortly as well as some other frameworks (ASP.net, Entity framework,), libraries (LINQ) and other web technologies (HTML, CSS, AJAX). For storing and manipulating data a database with tables in MS SQL database is created. Furthermore we take a look at requirements, idea and logic of solution. We present solution design and present how specific functionality behaves in case of different user types. We present a solution analysis where a comparison with other similar solutions and user tests are shown. Finally we discuss problems during the development and possibilities about the future improvements

Process evaluation of a web-based intervention aimed at empowerment of disability benefit claimants

<p>Abstract</p> <p>Background</p> <p>The objective of this process evaluation study was to gain insight into the reach, compliance, appreciation, usage barriers, and users' perceived effectiveness of a web-based intervention <url>http://www.wiagesprek.nl</url>. This intervention was aimed at empowerment of disability claimants, prior to the assessment of disability by an insurance physician.</p> <p>Methods</p> <p>Reach was determined by registering claimants exposed to the study's invitation brochures, and by comparing trial participant characteristics with non-participants and nationwide claimant data. Compliance was registered by analyzing weblogs, which were automatically collected during the period of the trial. This made it possible to analyze individual use of the intervention. Appreciation, usage barriers, and users' perceived effectiveness were assessed using an online questionnaire that was sent to participants from the intervention group, 6 weeks after enrolment.</p> <p>Results</p> <p>Only 9% of the target population enrolled in the internet program. Because of selective enrolment, more females, higher educated claimants, and less ethnical minorities were reached. Compliance was ambiguous: out of the 123 participants randomized into the intervention group, a significant proportion (33%) did not use the intervention at all, while, at the same time, many participants (32%) used the intervention for more than two hours (i.e. in approximately two weeks). Overall satisfaction with the intervention was good. Claimants perceived the intervention most effective in increasing knowledge, while also a fair amount of users perceived the intervention effective in gaining right expectations or being able to communicate better with their physician.</p> <p>Conclusions</p> <p>The uptake of the intervention <url>http://www.wiagesprek.nl</url> was disappointing. Specifically, the poor reach and compliance of the intervention resulted in a small proportion of the target population using the intervention as intended. Improvements in the implementation process are desirable to increase the reach and compliance and, thereby possibly, the impact of the intervention.</p> <p>Trial registration</p> <p><a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1414">NTR-1414</a></p