FEATURE EXTRACTION AND CLASSIFICATION THROUGH ENTROPY MEASURES

Entropy is a universal concept that represents the uncertainty of a series of random events. The notion \u201centropy" is differently understood in different disciplines. In physics, it represents the thermodynamical state variable; in statistics it measures the degree of disorder. On the other hand, in computer science, it is used as a powerful tool for measuring the regularity (or complexity) in signals or time series. In this work, we have studied entropy based features in the context of signal processing. The purpose of feature extraction is to select the relevant features from an entity. The type of features depends on the signal characteristics and classification purpose. Many real world signals are nonlinear and nonstationary and they contain information that cannot be described by time and frequency domain parameters, instead they might be described well by entropy. However, in practice, estimation of entropy suffers from some limitations and is highly dependent on series length. To reduce this dependence, we have proposed parametric estimation of various entropy indices and have derived analytical expressions (when possible) as well. Then we have studied the feasibility of parametric estimations of entropy measures on both synthetic and real signals. The entropy based features have been finally employed for classification problems related to clinical applications, activity recognition, and handwritten character recognition. Thus, from a methodological point of view our study deals with feature extraction, machine learning, and classification methods. The different versions of entropy measures are found in the literature for signals analysis. Among them, approximate entropy (ApEn), sample entropy (SampEn) followed by corrected conditional entropy (CcEn) are mostly used for physiological signals analysis. Recently, entropy features are used also for image segmentation. A related measure of entropy is Lempel-Ziv complexity (LZC), which measures the complexity of a time-series, signal, or sequences. The estimation of LZC also relies on the series length. In particular, in this study, analytical expressions have been derived for ApEn, SampEn, and CcEn of an auto-regressive (AR) models. It should be mentioned that AR models have been employed for maximum entropy spectral estimation since many years. The feasibility of parametric estimates of these entropy measures have been studied on both synthetic series and real data. In feasibility study, the agreement between numeral estimates of entropy and estimates obtained through a certain number of realizations of the AR model using Montecarlo simulations has been observed. This agreement or disagreement provides information about nonlinearity, nonstationarity, or nonGaussinaity presents in the series. In some classification problems, the probability of agreement or disagreement have been proved as one of the most relevant features. VII After feasibility study of the parametric entropy estimates, the entropy and related measures have been applied in heart rate and arterial blood pressure variability analysis. The use of entropy and related features have been proved more relevant in developing sleep classification, handwritten character recognition, and physical activity recognition systems. The novel methods for feature extraction researched in this thesis give a good classification or recognition accuracy, in many cases superior to the features reported in the literature of concerned application domains, even with less computational costs

Context-Aware System for Indoor Localization

User location is an important information to provide personalized service in any domain of interest. In this paper, we present a context-aware system to find location of a user at office domain. Hence, smartphone of the user transmits Wi-Fi signal and our system identifies the user by matching MAC address of the smartphone. Wi-Fi signal strength is used to calculate the distance of user from office room. Additionally, PIR sensor value and office time are used to increase localization accuracy as well as minimize the conflict of user location. Raspberry pi 3, a low-cost embedded platform, is used to collect and process sensed information, generate low-level context, and reason user location from available contexts. Demonstration result of our system shows an excellent performance within our domain of interest

Low Computational Cost for Sample Entropy

Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regularity/complexity of a time series. On the other hand, it is a computationally expensive method which may require a large amount of time when used in long series or with a large number of signals. The computationally intensive part is the similarity check between points in m dimensional space. In this paper, we propose new algorithms or extend already proposed ones, aiming to compute Sample Entropy quickly. All algorithms return exactly the same value for Sample Entropy, and no approximation techniques are used. We compare and evaluate them using cardiac inter-beat (RR) time series. We investigate three algorithms. The first one is an extension of the kd-trees algorithm, customized for Sample Entropy. The second one is an extension of an algorithm initially proposed for Approximate Entropy, again customized for Sample Entropy, but also improved to present even faster results. The last one is a completely new algorithm, presenting the fastest execution times for specific values of m, r, time series length, and signal characteristics. These algorithms are compared with the straightforward implementation, directly resulting from the definition of Sample Entropy, in order to give a clear image of the speedups achieved. All algorithms assume the classical approach to the metric, in which the maximum norm is used. The key idea of the two last suggested algorithms is to avoid unnecessary comparisons by detecting them early. We use the term unnecessary to refer to those comparisons for which we know a priori that they will fail at the similarity check. The number of avoided comparisons is proved to be very large, resulting in an analogous large reduction of execution time, making them the fastest algorithms available today for the computation of Sample Entropy

SERUM VITAMIN E, C AND A LEVEL IN LUNG CANCER: A CASE CONTROL STUDY

Lung cancer is a leading cause of cancer death worldwide, causing approximately 1.2 million deaths per year. Lung cancer is prevalent in smokers. It is documented that smoking induces oxidative stress, which is thought to be associated with the aetiology of carcinogenesis. A case control cross sectional study was conducted on sixty lung cancer patients and sixty smokers as cohort control. Serum levels of antioxidant vitamin E, C and A among the case and control subjects were estimated. It was observed that vitamin E value among the study population did not alter (15.67±3.67μmol/L vs. 14.66±3.88μmol/L). It was within normal range. Conversely, there was significantly high serum concentrations of vitamin C and A in the lung cancer patients as compared to those in the smoker controls (48.26±6.81versus 16.65±4.46μmol/L; 2.76±0.32 versus 1.60±0.35μmol/L respectively)

A CONVENTIONAL SYNTHESIS APPROACH TO PREPARE LEAD SULFIDE (PbS) NANOPARTICLES VIA SOLVOTHERMAL METHOD

We are describing a new optimized method for the preparation of single-sized crystalline lead sulphide (PbS) nanoparticles (NPs). The optimized solvothermal method uses a mixture of octadecene and oleic acid as a reaction media and MBTS as a reducing agent. Systematic investigation was performed on various synthesis parameters, such as acid to lead (Pb) and lead to sulphur(S) feed molar ratios, feed amounts of various phosphine compounds, reducing agent, total concentrations of reaction media, growth temperature, as well as different sulphur source compounds. We optimized the amount of 2,2-dithiobis(benzothiazole) (MBTS) in the reaction mixture to produce about 100 nm size and spherical shape zinc blade type PbS NPs. A broad UV absorption spectrum was observed when the MBTS amount was increased in the reaction mixture. The excellent organic solvent dispersion properties, along with near-IR emission spectrum window make these NPs a great choice in optoelectronics applications, especially for photovoltaic devices

Identification of density and breeding places of Aedes mosquito and prevalence of dengue in Rajshahi city corporation of Bangladesh

Background: There are various varieties of habitats that have specific characteristics of water for the breeding of mosquito. A house-to-house cross-sectional entomological survey used to be carried out at per domestic area to become aware of larval breeding sites. Aedes aeygypti used to be primary vector and Aedes albopictus used to be predominant species in container-breeding habitats. Most breeding habitats have been category into excessive stage of larval density. Turbidity, pH, TOC, magnesium, calcium and sodium is amongst the characteristics that indicates a significant difference with larval density and species composition respectively. This study personal based entomological research and funding carried out by corresponding author. Students of zoology department of Rajshahi university involved in this research. Students were working as a research assistant for this study. Aim of this study was to assess determination of prevalence, density and breeding place of Aedes mosquito in Rajshahi city corporation. Methods: This observational study carried out 30 wards in Rajshahi city corporation areas have been surveyed in department of communicable diseases control, director general of health services, Dhaka, Bangladesh. Duration of study 3 years. Total 3 surveys were conducted in each year; pre monsoon, monsoon and post monsoon total 9 surveys conducted by this 3 years survey period. Data entered in MS excel and statistical analysis done by SPSS trial version. Results: This study shows that according to breeding area of 2020-2022. Here, total surveyed household were 8100. Total positive Wet container were 474 and positive place were 473 in these three years survey. Conclusions: Aedes aegypti and Aedes albopictus are properly established inside urban places. Meteorological variables additionally affected mosquito populations. Characteristics of mosquito breeding area can affect larval density and give impact quality of life

Accelerometric-based Features as Surrogate of Tinetti test

INTRODUCTION Risk of falling is estimated by visual inspection of patient\u2019s movements using clinical scales, e.g., Tinetti test, Berg Balance Scale, Timed Up & Go etc. However, a continuous evaluation of such risk requires both subject hospitalization and expert clinical personnel. We believe that continuous automatic monitoring of the fall risk would provide rapid intervention as well as a reduction of the health care system costs. The main goal of this study is then to determine whether features extracted from low cost accelerometric signals can predict the physician assessments during a Tinetti test. METHODS Thirty-seven subjects were enrolled at the rehabilitation and medical research center INRCA (Istituto Nazionale Riposo e Cura Anziani), Casatenovo, Italy. Subjects using breathing supports, walkers and crutches were excluded from the study. All participants signed the informed consent. The median population age at time of the test was 75 (IQR = 81 - 70) years. 3D-axis accelerometric signals were collected using a wearable device (\ub18g, 12 bits, sampling rate 50 Hz, Geneactiv, Activinsights Limited, UK) positioned at the chest using an elastic band. Each subject underwent a Tinetti test divided in 8 motor tasks [2]. The Tinetti score was assigned by an expert physician and used as gold standard. For the present study only 4 items of the full test were considered (two for balance and two for gait): 1) Rise from the chair (score 0=unable, 1=able with arms, 2=able); 2) Immediate standing balance (score 0=unsteady, 1=steady with supports, 2=steady); 3) Step symmetry (score 0=asymmetric, 1=symmetric); and 4) Step continuity (score 0=discontinuous, 1=continuous). Features were extracted from the accelerometric signals. Sit to Stand Time and Balance after Standing (standard deviation of the vector magnitude within 5s after standing) were computed for the balance part. Step Symmetry and Step Regularity were determined on the vertical axis during walking phase as in [1]. ROC analysis was used to test features\u2019 power in classifying the score assigned to each item by the physician. The area under the ROC curve (AUC) was computed for each combination of scores. RESULTS Proportion and age of people with high risk of falling (Tinetti score 64 18) were not statistically different to those with low risk (0.46 vs 0.54; median age 76 vs 74; p > 0.05). Male proportion was higher than that of female (0.78 vs 0.22; p 0.79) while Sit to Stand Time, Balance after Standing and Step Symmetry were sufficiently predictive (AUC > 0.60). Table 1. Area under the ROC curve for each feature. AUC was computed only when the number of subjects for each score was at least 5 (NS=number of subjects < 5). Test Item Feature Score 0 vs 1 0 vs 2 1 vs 2 1) Rise from the chair Sit to Stand Time NS NS 0.68 2) Immediate standing balance Balance after Standing NS 0.64 NS 3) Step symmetry Step Symmetry 0.60 - - 4) Step continuity Step Regularity 0.79 - - DISCUSSION Accelerometric-based features can provide useful information on the body movements as well as correctly classify the physician\u2019s item assessments. REFERENCES [1] Moe-Nilssen R, Helbostad JL. J Biomech 2004; 37:121\u2013126 [2] Rivolta MW, et al. EMBC 2015; 6935-6938

Deposition of Aluminum-Doped ZnO Films by ICP-Assisted Sputtering

Inductively coupled plasma (ICP) assisted DC sputter deposition was used for the deposition of Al-doped ZnO (AZO or ZnO:Al) thin films. With increasing ICP RF power, film properties including deposition rate, crystallinity, transparency, and resistivity were improved. To understand the plasma-surface interaction, several plasma diagnostics were performed. Heat fluxes to the substrate were measured by thermal probes, number densities of sputtered metallic atom species were measured by absorption spectroscopy using hollow cathode lamps (HCL) and light emitting diodes (LEDs), and neutral gas temperatures were measured by external cavity diode laser (ECDL) absorption spectroscopy. As a result, it was revealed that the high-density ICP heated the substrate through a high heat flux to the substrate, resulting in a high-quality film deposition without the need for intentional substrate heating. The heat flux to the substrate was predominantly contributed by the plasma charged species, not by the neutral Ar atoms which were also significantly heated in the ICP. The substrate position where the highest quality films were obtained was found to coincide with the position where the substrate heat flux took the maximum value

Quantifying primaquine effectiveness and improving adherence: a round table discussion of the APMEN Vivax Working Group.

The goal to eliminate malaria from the Asia-Pacific by 2030 will require the safe and widespread delivery of effective radical cure of malaria. In October 2017, the Asia Pacific Malaria Elimination Network Vivax Working Group met to discuss the impediments to primaquine (PQ) radical cure, how these can be overcome and the methodological difficulties in assessing clinical effectiveness of radical cure. The salient discussions of this meeting which involved 110 representatives from 18 partner countries and 21 institutional partner organizations are reported. Context specific strategies to improve adherence are needed to increase understanding and awareness of PQ within affected communities; these must include education and health promotion programs. Lessons learned from other disease programs highlight that a package of approaches has the greatest potential to change patient and prescriber habits, however optimizing the components of this approach and quantifying their effectiveness is challenging. In a trial setting, the reactivity of participants results in patients altering their behaviour and creates inherent bias. Although bias can be reduced by integrating data collection into the routine health care and surveillance systems, this comes at a cost of decreasing the detection of clinical outcomes. Measuring adherence and the factors that relate to it, also requires an in-depth understanding of the context and the underlying sociocultural logic that supports it. Reaching the elimination goal will require innovative approaches to improve radical cure for vivax malaria, as well as the methods to evaluate its effectiveness