Визуализация оценки мониторинга состояния биобъектов с помощью метода "Лица Чернова"

The article is about the usage of pictogtaphics of Chernoff faces. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff faces themselves can be plotted on a standard X-Y graph. The main aim of the article is to find the right way how to treat the person with different diseases. It can be useful for all medical workforce who somehow connected with such a problem. Also the written article can help young programmers and students of medical universities with their scientific papers

Моделирование поведения биологичеческой системы

The article is about the usage of pictogtaphics of Chernoff faces. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff faces themselves can be plotted on a standard X-Y graph. The main aim of the article is to find the right way howto treat the person with different diseases. It can be useful for all medical workforce who somehow connected with such a problem. Also the written article can help young programmers and students of medical universities with their scientific papers

Визуализация многомерных медицинских данных с помощью пиктографиков "лица Чернова"

The article is about the usage of pictogtaphics of Chernoff faces. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff faces themselves can be plotted on a standard X-Y graph. The main aim of the article is to find the right way how to treat the person from asthma. It can be useful for all medical workforce who somehow connected with such a problem. Also the written article can help young programmers and students of medical universities with their scientific papers

UTILIZING CHERNOFF FACES IN MODELING RESPONSES IN THE EVALUATION OF TRIMESTER SCHEME IMPLEMENTATION

This study uses Chernoff faces to model the responses of students, faculty, and administration staff of a teacher education institution in Manila, Philippines, to the implementation of an Outcomes-Based Teacher Education Curriculum (OBTEC) trimester scheme. Chernoff faces provide a valuable representation to model responses because people are used to studying and reacting to faces. This study used a quantitative research method by analyzing cross-sectional data from the study of the OBTEC trimester scheme. A total of 322 participants were selected through convenience sampling and given a 15-item survey in which possible responses ranged from 1 (strongly disagree) to 6 (strongly agree). The administrators were found to give a generally favorable rating (overall mean = 4.56 agree; overall SD = 0.45) to the OBTEC trimester scheme. The statements most highly rated by the administrators pertain to the success of OBTEC in integrating pedagogical content knowledge training with outcomes-based education, preparation of the students for the teaching profession, and consistency with the K to 12 curriculum. These responses are characterized by the structure of the face, the width of the mouth, and the height of the face, respectively. The most negative aspects of the OBTEC trimester scheme, according to the students, are characterized by hair height, nose width, and a hair style of thin hair that points downward. Chernoff faces were found to be a simple, yet powerful tool to model responses in the evaluation of the OBTEC trimester scheme

Computational steering of a multi-objective genetic algorithm using a PDA

The execution process of a genetic algorithm typically involves some trial-and-error. This is due to the difficulty in setting the initial parameters of the algorithm – especially when little is known about the problem domain. The problem is magnified when applied to multi-objective optimisation, as care is needed to ensure that the final population of candidate solutions is representative of the trade-off surface. We propose a computational steering system that allows the engineer to interact with the optimisation routine during execution. This interaction can be as simple as monitoring the values of some parameters during the execution process, or could involve altering those parameters to influence the quality of the solutions produce by the optimisation process

Application of methods for central statistical monitoring in clinical trials

Background On-site source data verification is a common and expensive activity, with little evidence that it is worthwhile. Central statistical monitoring (CSM) is a cheaper alternative, where data checks are performed by the coordinating centre, avoiding the need to visit all sites. Several publications have suggested methods for CSM; however, few have described their use in real trials. Methods R-programs were created to check data at either the subject level (7 tests within 3 programs) or site level (9 tests within 8 programs) using previously described methods or new ones we developed. These aimed to find possible data errors such as outliers, incorrect dates, or anomalous data patterns; digit preference, values too close or too far from the means, unusual correlation structures, extreme variances which may indicate fraud or procedural errors and under-reporting of adverse events. The methods were applied to three trials, one of which had closed and has been published, one in follow-up, and a third to which fabricated data were added. We examined how well the methods work, discussing their strengths and limitations. Results The R-programs produced simple tables or easy-to-read figures. Few data errors were found in the first two trials, and those added to the third were easily detected. The programs were able to identify patients with outliers based on single or multiple variables. They also detected (1) fabricated patients, generated to have values too close to the multivariate mean, or with too low variances in repeated measurements, and (2) sites which had unusual correlation structures or too few adverse events. Some methods were unreliable if applied to centres with few patients or if data were fabricated in a way which did not fit the assumptions used to create the programs. Outputs from the R-programs are interpreted using examples. Limitations Detecting data errors is relatively straightforward; however, there are several limitations in the detection of fraud: some programs cannot be applied to small trials or to centres with few patients (<10) and data falsified in a manner which does not fit the program’s assumptions may not be detected. In addition, many tests require a visual assessment of the output (showing flagged participants or sites), before data queries are made or on-site visits performed. Conclusions CSM is a worthwhile alternative to on-site data checking and may be used to limit the number of site visits by targeting only sites which are picked up by the programs. We summarise the methods, show how they are implemented and that they can be easy to interpret. The methods can identify incorrect or unusual data for a trial subject, or centres where the data considered together are too different to other centres and therefore should be reviewed, possibly through an on-site visit

CHERNOFF FACES: SUATU METODE PENGELOMPOKAN OBYEK SECARA GRAFIS

Penulisan ini bertujuan untuk memberikan solusi alternatif dalarn rnenjawab permasaiahan, bagairnana rnelakukan klasifikasi obyek-obyek pengamatan dalarn analisis kelompok. Untuk mendapatkan kelompok dengan anggota yang sesuai dapat dilakukan dengan rnetode Chernoff races. Pada rnetode ini data observasi diirnplementasikan dalam bentuk-bentuk garnbar wajah. Kernudian wajah-wajah dipisahkan ke dalam dua kelornpok sedernikian hingga wajah-wajah dalam satu kelornpok berbeda jauh bentuknya dengan wajah-wajah dalam kelornpok lain. Selanjutnya wajah-wajah yang rnerniliki perbedaan bentuk yang rnenonjol dalarn suatu ke\ompok dipisahkan rnenjadi kelornpok baru. Dernikian seterusnya hingga tidak ada perbedaan bentuk yang rnenonjol dalarn tiap-tiap kelornpok. Hasil pernbahasan dari penulisan ini adalah rnetode Chernoff Faces dapat digunakan dalarn proses klasifikasi obyek-obyek pengarnatan pada analisis kelornpok. Hasil dari proses pengelornpokan dengan rnenggunakan rnetode Chernoff Faces dan algoritma K-rnean tidak selalu sarna

Alternatív tematikus ábrázolási módszerek a kartográfiában = Alternative methods of thematic representation in cartography

A kutatás során megvizsgáltunk két kevésbé ismert tematikus ábrázolási módszert: a Chernoff-arcokat és a torzított kartogram módszert. Először a nemzetközi szinten elért eredményeket vizsgáltuk, mivel ebben a témában alig volt magyar kutatás az utóbbi 40 évben. Az elméleti kutatás eredményeként két honlap született: - „A torzított kartogram-térképek világa” - „A Chernoff-arcok adatábrázolási módszer alkalmazási lehetőségei az iskolai kartográfiában” Mind a két honlap bemutatja a gyakorlati eredményeket is: a Magyarországról készített torzított kartogram-térképeket illetve a Chernoff módszerrel kapcsolatos iskolai felmérés eredményeit. A Chernoff kutatást nemzetközi együttműködésben, argentin szakemberekkel végeztük el. A kutatás e részét egy kétoldalú együttműködési pályázat támogatásával valósítottuk meg. Ez a pályázat kizárólag a szakemberek cseréjét támogatta, a felmérés végrehajtását jelen OTKA pályázat biztosította. A kutatási eredményeket a már megemlített két honlapban, hat konferencián kiadott kiadványokban (összesen kilenc előadás és poszter) és két szakfolyóiratcikkben ismertettük 2008 és 2010 között. A nemzetközi szinten bemutatott eredmények indították el újabb nemzetközi kutatások megszervezését. Jelenleg a Chernoff kutatást a bécsi Műszaki Egyetem Geoinformatikai és Térképészeti Intézetével folytatjuk egy kétoldalú projekt keretében, de további projekteket is tervezünk, például a holland Faculty of Geo-Information Science and Earth Observation (ITC). | In this research were analyzed two less known methods of thematic representation: the Chernoff faces and the cartograms. First we studied the results reached at the international level, because there was only little Hungarian research on this theme during the last 40 years. As result of the theoretical research, two websites were created in Hungarian language: - „The world of cartograms” - „Possibilities of use of the Chernoff faces in school cartography” Both websites include the practical results: the cartograms made about Hungary, and the results of the school survey related to the Chernoff faces. The Chernoff research was made in international collaboration with Argentine specialists. This part of the research was realized with the support of the bilateral agreement. This agreement supported only the exchange of specialists; the survey was financed by the present OTKA project. The results of the research were published in the two websites mentioned above, in six conference proceedings (presenting a total of nine papers and posters) and two articles in scientific reviews between 2008 and 2010. The results presented in international events motivated the initiation of new international research. At present, the Chernoff research is followed in the frame of a bilateral project with the Institute for Geoinformatics and Cartography at Vienna University of Technology. New projects are also planned, e.g. with the Faculty of Geo-Information Science and Earth Observation (ITC) in the Netherlands

Emoji and Chernoff - A Fine Balancing Act or are we Biased?

We seek to answer the question on whether different geometrical attributes within a glyph can bias interpretation of data. We focus on a specific visual encoding, the Emoji, and evaluate its effectiveness at encoding multidimensional features. Given the anthropomorphic nature of the encoding we seek to quantify the amount of bias the encoding itself introduces, and use this to balance the Emoji glyph to remove that bias. We perform our analysis by comparing Emoji with Chernoff faces, of which they can be seen as direct descendant. Results shed light on how this new approach of feature tuning in glyph design can influence overall effectiveness of novel multidimensional encodings