Latest Experiments with GDV Technique in Agronomy

We have recorded coronas of ripe apples as a follow up to last year’s study [6]. The results indicate that we are unable to detect differences between organically and conventionally grown apples of very similar standard quality. We are, however, able to pick up differences between plants grown using different fertilization schemes

Search versus Knowledge: An Empirical Study of Minimax on KRK

This article presents the results of an empirical experiment designed to gain insight into what is the effect of the minimax algorithm on the evaluation function. The experiment’s simulations were performed upon the KRK chess endgame. Our results show that dependencies between evaluations of sibling nodes in a game tree and an abundance of possibilities to commit blunders present in the KRK endgame are not sufficient to explain the success of the minimax principle in practical game-playing as was previously believed. The article shows that minimax in combination with a noisy evaluation function introduces a bias into the backed-up evaluations and argues that this bias is what masked the effectiveness of the minimax in previous studies

Information Stored in Coronas of Fruits and Leaves

We recorded coronas of apple tree leaves and fruits in order to monitor and compare their state under different conditions. The results of our study show that coronas of leaves and fruits give useful information about the health status of plants and about the sort. At the same time we have to conclude that for time being we were not able to extract any useful information for differentiation between organically and conventionally grown plants and for assessing vitality of apple trees grown from various rootstocks

Machine learning from coronas using parametrization of images

We were interested to develop an algorithm for detection of coronas of people in altered states of consciousness (two-classes problem). Such coronas are known to have rings (double coronas), special branch-like structure of streamers and/or curious spots. We used several approaches to parametrization of images and various machine learning algorithms. We compared results of computer algorithms with the human expert’s accuracy. Results show that computer algorithms can achieve the same or even better accuracy than that of human experts

GDV images: Current research and results

We use statistical analysis and machine learning to interpret the GDV coronas of fruits and human’s fingers in order to verify two hypotheses: (A) the GDV images contain useful information about the object/patient and (B) the human bioelectromagnetic field can be influenced by some outside factors. We performed several independent studies, three of which we here briefly describe: (a) recording coronas of berries of different grapevines, (b) detecting the influence of drinking the tap water from ordinary glass and energetic glass K2000, and (c) detecting the influence of natural energy source in Tunjice near Kamnik, Slovenia on the human bioelectromagnetic field. All three studies, as well as some other studies described elsewhere, gave significant results and therefore support both hypotheses

Ugotavljanje efekta različnih majic na posnetke koron prstov s Kirlianovo kamero

Naloga obravnava analizo koron prstov s pomočjo tehnike Gas Discharge Visualization (GDV), Kirlianove kamere in z njo povezane programske opreme. Na primeru študije ugotavljanja efekta različnih majic na posnetke koron prstov s Kirlianovo kamero poskušamo podpreti področje kirlianografije z metodami strojnega učenja in statistike. V okviru te študije je bilo posnetih 187 ljudi, ki so nosili štiri različne majice ali pa so bili v kontrolni skupini. Rezultati študije kažejo pomembne razlike med zdravilnimi in navadnimi majicami ter kontrolno skupino. Naloga nadalje pokaže, da GDV posnetki koron prstov vsebujejo koristne informacije o zdravstvenem stanju človeka. Opisane so ugotovitve glede vpliva nekaterih dejavnikov na GDV posnetke in ugotovitve o medsebojni povezanosti nekaterih GDV parametrov. Naloga vsebuje tudi nasvete za snemanje s kamero, delo z ljudmi in nasvete o tem, kako in katere GDV parametre je smiselno uporabljati pri različnih vrstah analize koron prstov. Dotakne se še problema, kako upoštevati različne pomembnosti sprememb pri GDV parametrih in nakaže nekaj možnih rešitev

Vizualizacija in analiza bioelektromagnetnega polja človeka

Peer in sod. [1] so predstavili prototip programa za vizualizacijo bioelektromagnetnega polja človeka s pomočjo Kirlianove kamere Crown-TV. Prototip je takrat predstavljal zametek vizualizacijskega modula za ekspertni sistem za postavljanje diagnoze iz slik, ki jih posname Kirlianova kamera. V preteklem letu se je delo uspešno nadaljevalo in pričujoči članek predstavlja končni izdelek vizualizacijskega modula s polno funkcionalnostjo, ki ga je na podlagi prej omenjenega prototipa v okviru svoje diplomske naloge izdelal Pirc [2]. Predvsem so poudarjene razlike in dopolnitve vgrajene v končno verzijo programa. V drugem delu članka pa je opisan naslednji korak izgradnje ekspertnega sistema – modul za opis in analizo koron z numeričnimi parametri. V tem delu so tudi opisane nekatere nove možnosti kakor tudi potrebe, ki so se pojavile v preteklem letu

GDV technique and machine learning: Current research and results

We use machine learning to analyze GDV images of leaves of apple trees and human fingers. We are interested in two hypotheses: 1. GDV images of plant leaves contain information about plant condition, 2. Human bioelectromagnetic field can be influenced by outside factors, such as vitalized water from special glasses. We performed four independent studies: (a) analyzing coronas of apple leaves, (b) detecting the effect of K2000 glasses on human BEM field, (c) detecting the effect of mobile phones on human BEM field and (d) detecting the effect of energized orbs on human BEM field

Machine learning and GDV images: current research and results

We use machine learning to interpret the GDV coronas of human's fingers in order to verify three hypotheses: 1. The GDV images contain useful information about the object/patient, 2. The map of coronas of fingers according to Chinese medicine does make sense, and 3. The human bioelectric field can be influenced by some outside factors, such as special T-shirts. We performed three independent studies: (a) recording coronas of apple skin, in order to verify if we can obtain any useful information for distinguishing the sort, age and the sun/shadow part of the apple, (b) detecting the state of menstrual cycle for females, and (c) detecting of the influence of different T-shirts on human's bioelectric field

Clinical course of HER-2 positive breast cancer patients

Breast cancer is the most frequent cancer in women. The course and efficiency of breast cancer treatment are influenced by several factors. The expression of HER-2 protein and HER-2 gene is gaining in strength in breast cancer management. The aim of our study was to compare the course of HER-2 positive with HER-2 negative disease. In median time of 2.5 years DFS (disease-free-survival) of patients with HER-2 positive tumours was 76.1%, and 93.4% for patients with HER-2 negative disease. HER-2 status was the strongest prognostic factor for DFS (