Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin

This thesis presents a novel analysis and classification of human radiation wave for gender and body segments recognition. The human body has been shown to emit radiation into space surrounding their body. The research study frequency radiations at 23 points of the human body segregated into body segments of Chakra, Left, Right, Upper body, Torso, Arm and Lower body. Initially, the characteristics of frequency radiation are examined using statistical tools to find the correlations between variables. Multivariate analysis of variance (MANOVA) is employed to compare the differences of frequency radiation characteristics between genders. Then, the classification algorithm of k-nearest neighbor (KNN) is employed to discriminate between genders, and between body segments. The classifiers are evaluated through analysis of the performance indicators applied in medical research of accuracy, precision, sensitivity and specificity in receiver operating characteristics (ROC) analysis. The findings obtained from this research show that the wave radiation characteristics of a male and a female human body are different. The proposed technique is able to distinguish gender and classify body segments, and it is justified using MANOVA statistical tests

Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin

This thesis presents a novel analysis and classification of human radiation wave for gender and body segments recognition. The human body has been shown to emit radiation into space surrounding their body. The research study frequency radiations at 23 points of the human body segregated into body segments of Chakra, Left, Right, Upper body, Torso, Arm and Lower body. Initially, the characteristics of frequency radiation are examined using statistical tools to find the correlations between variables. Multivariate analysis of variance (MANOVA) is employed to compare the differences of frequency radiation characteristics between genders. Then, the classification algorithm of A:-nearest neighbor (KNN) is employed to discriminate between genders, and between body segments. The classifiers are evaluated through analysis of the performance indicators applied in medical research of accuracy, precision, sensitivity and specificity in receiver operating characteristics (ROC) analysis. The findings obtained from this research show that the wave radiation characteristics of a male and a female human body are different. The proposed technique is able to distinguish gender and classify body segments, and it is justified using MANOVA statistical tests. The individual features of gender differences using analysis of variance forms a significant outcome on 13 points that are located close to the forehead, left and right side of abdomen, palms, arms, shoulders and head. In KNN classification, the outcomes for the classifiers are consistent with the MANOVA. For gender recognition, the classifiers have successfully differentiated male from female human body, and achieving a performance of 100% for accuracy, sensitivity and specificity. For body segment recognition, the classifiers are also able to distinguish between the body segments producing 100% accuracy in classifying of Chakra, Left and Right, whilst 93.75% accuracy is obtained in classifying of Upper body, Torso, Arm and Lower body. The sensitivity and specificity computed for body segment recognition are found to be more than 80% indicating a good classification performance. The outcomes of this study demonstrate that a male and a female human body, and also the different body segments, have different frequency radiation characteristics. The finding offers new opportunities in research and application based on human body radiation such as biometrics and surveillance systems

Statistical feature analysis of EEG signals for calmness index establishment

Electroencephalographic (EEG) signals are very closely related to psychophysiological. The EEG signals displayed few responses which can be categorized. This article discussed the use of statistics over the EEG features which confirm the different mental characteristics. Two different type of stimulus was given named as relaxed state and non-relaxed state. Asymmetry index was computed as the EEG features via the alpha waves and was extracted during the relaxed state and the non-relaxed state. The EEG features were clustered to a group of three, four and five using Fuzzy C-Means. During the relaxed state, the alpha wave showed a higher response as compared to the non-relaxed state. This is observed by using the mean relative energy between the relaxed state and non-relaxed state. To ensure which EEG features in the clusters showed a significant difference, p < .05, a statistical test was used. Wilcoxon Signed Ranks test is the best-statistical test to verify the selected clusters as it is suitable to analyze the small sample of data. Wilcoxon Signed Ranks test used a hypothesis testing which using the same method as paired sample t-test. The advantage in using Wilcoxon Signed Ranks test is that, it uses the median to get the difference between two samples of data. Analytical results showed that the data features of four clusters and three clusters give a significant difference, thus the obtained results can be used to further up the study. The Wilcoxon Signed Ranks test results confirmed that the proposed technique has potential in establishing the calmness index

Identification of Risk Factors for Scoliosis in Elementary School Children Using Machine Learning

Scoliosis is an abnormal curvature of the spine and often diagnosed in childhood or early adolescence. In this study, the risk factors for scoliosis in elementary school children is investigate based on age, backpack weight and gender. There are 260 children participated in this study from aged 7 up to 12 years old. Scoliometer is used to measure the angle of trunk rotation (ATR) on Adam Forward Bending Test. Statistical analysis of analysis of variance (ANOVA) is used to determine the characteristic difference of ATR readings on the risk factors for scoliosis. Significant results with P-value less than 0.001 are found among ATR readings on a linear combination of risk factors for scoliosis of age and backpack weight. Then, the risk factors for scoliosis are classified among elementary school children using Decision Tree and K-Nearest Neighbor. The classification results shown that both Decision Tree method produced highest classification percentage up to 98.08%. This finding indicates that age and backpack weight are significant as the risk factors for scoliosis

Identification of Risk Factors for Scoliosis in Elementary School Children Using Machine Learning

Scoliosis is an abnormal curvature of the spine and often diagnosed in childhood or early adolescence. In this study, the risk factors for scoliosis in elementary school children is investigate based on age, backpack weight and gender. There are 260 children participated in this study from aged 7 up to 12 years old. Scoliometer is used to measure the angle of trunk rotation (ATR) on Adam Forward Bending Test. Statistical analysis of analysis of variance (ANOVA) is used to determine the characteristic difference of ATR readings on the risk factors for scoliosis. Significant results with P-value less than 0.001 are found among ATR readings on a linear combination of risk factors for scoliosis of age and backpack weight. Then, the risk factors for scoliosis are classified among elementary school children using Decision Tree and K-Nearest Neighbor. The classification results shown that both Decision Tree method produced highest classification percentage up to 98.08%. This finding indicates that age and backpack weight are significant as the risk factors for scoliosis

Heat exposure assessment among warship technicians in machinery room

Some warship compartments are undoubtedly considered severe hot environment due to high-temperature values produced by rotating machinery. Besides, it also depended on the external conditions such as weather and design of the warship, which contributes to high-temperature in specific compartments. Such inconvenient situations which related to space, noise, vibration and poor air quality inside the warship compartment further increase high prevalence risk to the associated technicians. Thus, this study was to examine the awareness state among technicians regarding the heat exposure they faced in machinery room during the daily routine and to propose an action plan to increase awareness state among technicians regarding heat exposure in the workplace. The variables that have been chosen in the study were knowledge awareness, personal influences, environmental influences, interpersonal influences and management influences. The statistical analysis technique was applied in the study by using The Pearson-correlation coefficient. Result shows that the environmental impacts and management authorities have a significant positive relationship with awareness state among technicians

Investigation of human electromagnetic radiation characteristic for kidney disease patients

The human body is shown to have their own radiation that emits at certain frequencies into the space surround the body. The purpose of this paper is to investigate the characteristic of human electromagnetic radiation among kidney disease patients and non-kidney disease participants. The body radiation frequencies are measured using body radiation wave detector at twenty-two points of the human body. The properties of human electromagnetic radiation are evaluated using statistical analysis of dependent t-test of Wilcoxon Signed Rank test and independent t-test of Mann-Whitney U test. Significant results with the Sig. value below 0.05 are shown in lower body, torso, chakra, arm and upper body, thus indicates the characteristic differences of human electromagnetic radiation frequency between kidney disease patients and non-kidney disease participants

Frequency dependence of electroluminescence measurement in LDPE

A good insulator for high voltage cable has low dielectric loss, reasonable flexibility and thermo-mechanically stable. However, prolonged application of electrical stresses on the cable will degraded the cable; physically and morphologically. Electrical degradation in high voltage cable can be detected using electroluminescence (EL) method. Electroluminescence is a phenomenon that occurs when the atoms of a material are being excited due to the application of and external high electrical stresses. There are several external factors that affect the behaviour of electroluminescence emission such as, applied voltage, applied frequency, ageing of material and types of materials. In this paper, the EL measurement is employed to determine the effect of applied frequency on virgin LDPE at fixed and varying applied voltage. It can be observed that EL emission increases as applied frequency increases with increasing voltage applied. However, interesting EL behaviour is observed when varying frequency is applied from 10 Hz to 100 Hz

A comparison study of radioactivity and radiation hazard index between legal and illegal cigarettes

Radioactive nuclide which emits radiation and damages biological tissue is found in the cigarette. Illegal cigarettes are reported to contain higher toxic levels of the nuclide as compared to the legal cigarettes. Therefore, this study aims to compare the radioactive elements, concentration, radiation dose and Radiation Hazard Index (RHI) of the legal and illegal cigarettes. The natural radionuclides of Uranium-238 (238U), Thorium-232 (232Th) and Potassium-40 (40K) of six legal cigarette brands and six illegal cigarette brands were measured using a High Purity Germanium (HPGe) detector-based gamma spectroscopy system. The radioactive elements that were detected by gamma spectrometer were Lead-214 (214P) and Bismuth-214 (214Bi) from 238U decay series, Bismuth-212 (212Bi) and Actinium-228 (228Ac) from 232Th decay series and 40K. The activity and concentration of 238U for legal cigarettes were significantly higher than illegal cigarettes (p < 0.01). On the contrary, a significantly high value of activity and concentration of 40K element of illegal cigarettes were recorded when compared with legal cigarettes (p < 0.001). The mean value of RHI for both illegal and legal cigarette samples were calculated and found to be higher than the safe limit of unity (1). However, the statistical test to compare the RHI of internal hazard index (Hin) and external hazard index (Hex) between illegal and legal cigarettes was not significant. To conclude, both legal and illegal cigarettes were subjected to a high radiation exposure, which could have negative effects to health