Search results for "computer.software_genre"
showing 10 items of 3858 documents
Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry
2019
[EN] Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty-seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (S…
On the complementarity of holistic and analytic approaches to performance assessment scoring.
2019
BACKGROUND A holistic approach to performance assessment recognizes the theoretical complexity of multifaceted critical thinking (CT), a key objective of higher education. However, issues related to reliability, interpretation, and use arise with this approach. AIMS AND METHOD Therefore, we take an analytic approach to scoring students' written responses on a performance assessment. We focus on the complementarity of holistic and analytic approaches and on whether theoretically developed analytical scoring rubrics can produce sub-scores that may measure the 'whole' performance in a holistic assessment. SAMPLE We use data from the Wind Turbines performance assessment, developed in the iPAL p…
Normative data on the familiarity and difficulty of 196 Spanish word fragments
2005
In this article, normative data on the familiarity and difficulty of 196 single-solution Spanish word fragments are presented. The database includes the following indices: difficulty, familiarity, frequency, number of meanings, number of letters given in the fragment, first and/or last letters given, and ratio of letters to blanks. A factor analysis was performed on difficulty, and two factors were obtained. Frequency, familiarity, and number of meanings loaded highly on the first factor, which we consider to measure lexical processes, whereas number of letters in the fragment, first and/or last letters given, and ratio of letters to blanks loaded highly on the second factor, which we judge…
Clinical validation of a virtual environment for normalizing eating patterns in eating disorders
2013
The purpose of the present study was to examine the clinical validation of a Virtual Reality Environment (VRE) designed to normalize eating patterns in Eating Disorders (ED). The efficacy of VR in eliciting emotions, sense of presence and reality of the VRE were explored in 22 ED patients and 37 healthy eating individuals. The VRE (non-immersive) consisted of a kitchen room where participants had to eat a virtual pizza. In order to assess the sense of presence and reality produced by the VRE, participants answered seven questions with a Likert scale (0-10) during the experience, and then filled out the Reality Judgment and Presence Questionnaire (RJPQ) and ITC-Sense of Presence Inventory (I…
A Graph-Grammar Approach to Represent Causal, Temporal and Other Contexts in an Oncological Patient Record
1996
AbstractThe data of a patient undergoing complex diagnostic and therapeutic procedures do not only form a simple chronology of events, but are closely related in many ways. Such data contexts include causal or temporal relationships, they express inconsistencies and revision processes, or describe patient-specific heuristics. The knowledge of data contexts supports the retrospective understanding of the medical decision-making process and is a valuable base for further treatment. Conventional data models usually neglect the problem of context knowledge, or simply use free text which is not processed by the program. In connection with the development of the knowledge-based system THEMPO (The…
Pseudonyms for Cancer Registries
1996
AbstractIn order to conform to the rigid German legislation on data privacy and security we developed a new concept of data flow and data storage for population-based cancer registries. A special trusted office generates a pseudonym for each case by a cryptographic procedure. This office also handles the notification of cases and communicates with the reporting physicians. It passes pseudonymous records to the registration office for permanent storage. The registration office links the records according to the pseudonyms. Starting from a requirements analysis we show how to construct the pseudonyms; we then show that they meet the requirements. We discuss how the pseudonyms have to be prote…
Quantifying stenosis in renal arteriograms: a fuzzy syntactic analysis.
1999
AbstractThe introduction of fuzzy logic improves a system for the automatic quantification of renal artery lesions seen in digital subtraction angiograms. A two-step approach has been followed. An earlier system based on non-fuzzy syntactic analysis provided a clear symbolic description of the stenotic lesions. Although this system worked correctly, it did not take into account the variability and uncertainty inherent to image processing and to knowledge on the reference diameter. This system has been improved by the introduction of fuzzy logic in the representation of the reference diameter. It provides a description of the stenosis in terms of fuzzy quantities. To illustrate the benefits …
State of the Art Literature Review on Network Anomaly Detection
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory
2018
Advanced Persistent Threat(APT) attacks are a major concern for the modern societal digital infrastructures due to their highly sophisticated nature. The purpose of these attacks varies from long period espionage in high level environment to causing maximal destruction for targeted cyber environment. Attackers are skilful and well funded by governments in many cases. Due to sophisticated methods it is highly important to study proper countermeasures to detect these attacks as early as possible. Current detection methods under-performs causing situations where an attack can continue months or even years in a targeted environment. We propose a novel method for analysing APT attacks through OO…
State of the Art Literature Review on Network Anomaly Detection with Deep Learning
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…