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Classtfication and Mathematical Modeling of Human Emotions from EEG Signal
No full textThis thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, March 2016.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 118-125).Cognitive state estimation shows the subjective mental changes with the environmental
constraints which can be used for diagnosis of cognitive behavior. A cognitive model will
support and facilitate the development of affective systems in emotion studies and act as a
unifying platform in physiological research area. In recent years, there has been an increasing
interest in applying techniques from the domains of nonlinear analysis in studying the mental
behavior of a dynamical system from an experimental time series such as EEG signals. A lot
of research has been carried out to study on human brain response while the subject is in
relax or performing different mental task with sustained attention or listening to different
kinds of music, as well as different emotion related activity. High frequency component and
low frequency component contained in a brain signal with different mental activity is proven
as a cognitive factor to human emotion recognition system and can be shown through the
variations of human brain signal. Electroencephalographic (EEG) technology has enabled
effective measurement of human brain activity, as functional and physiological changes
within the brain may be registered by EEG signals from the variations of alpha, beta, delta,
theta frequency bands. The EEG signals are collected from several healthy adult subjects and
processed using signal processing algorithms in C/C++ source code and MATLAB to extract
the effective features to classify the emotional states through the spatial and temporal
analysis, discrete wavelet transform, fast Fourier transform etc. Useful information is
extracted from the processing of EEG signal, and different machine learning algorithm are
used to identify the different brain response from the signals to classify the emotional states
using multiclass support vector machine (MCSVM). The classification of different emotions
is validated using artificial intelligent techniques, i.e. neural network.
The recognition of human emotion plays a vital role in physiological research area but in case
of real-time application and practical hardware implementation of human emotion based
systems a mathematical background of emotions is really needed. Mathematical modeling of
emotional states plays a significant role in this scope which can correlate between human
cognition, emotion and mental behavior. In this work, new approach is proposed to model the
emotional states with mathematical expressions based on wavelet analysis and trust region
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algorithm for the non-linearity and non-stationarity of EEG signal. Daubechies4 wavelet
function ("db4") is applied on different recognized emotional states such as relax, memory,
pleasant, fear, motor action (MA), enjoying music (EM) to extract the wavelet coefficients of
these different states. The emotional states are modeled with different mathematical
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expressions. The brain signals are composed of composite frequency components. So, the
proposed model of the emotional states will be the sum of the sinusoidal functions consisting
the composite frequency components. To model the emotional states the coefficients can be
obtained by trust-region algorithm for non-linear EEG data which can be verified with these
subband wavelet coefficients. The adjusted R- square percentage and the sum of square error
will optimize the performance of proposed model. The higher rate of adjusted R-square
percentage and lower percentage of SSE and RMSE will validate the developed cognitive
model.
To propose a proper mathematical model of the brain signal of different emotional states
proper effective channel is needed to select in order to reduce the feature size without any
performance degradation. In this work a way is develop to propose the effective channel for
emotion classification based on temporal and spectral analysis. The performance of the
proper selected channel is more robust to classify and model the effective emotional states.Monira IslamMaster of Science in Electrical and Electronic Engineerin
Approximate Analytic Solutions of the Inverse Cubic Truly Nonlinear Oscillator by Iterative Method
No full textThis thesis is submitted to the Department of Mathematics, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Mathematics, January 2016.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 43-48).An analytical technique has been developed based on an iteration method to determine
higher-order approximate periodic solutions for nonlinear oscillatory differential equations.
Usually, a set of nonlinear algebraic equations is solved with this method. However,
analytical solutions of these algebraic equations are not always possible, especially in the
case of large oscillations. A new technique based on the Mickens iterative method has been
presented to obtain approximate analytic solutions of the Inverse Cubic Truly Nonlinear
Oscillator. In this thesis, we have adopted the method of Fourier series and utilized truncated
terms in each steps of iteration. The solutions obtained by this method nicely matched with
the exact frequency. Also the obtained solutions are much more accurate than other existing
results and the method is convergent and consistent.Md. Bayezid BostamiMaster of Science in Mathematic
Livelihood Vulnerability Assessment and Local Adaptations against Climate Change in South West Coastal Belt of Bangladesh
No full textThis thesis is submitted to the Department of Civil Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Civil Engineering, November 2016.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 101-104)Bangladesh is widely recognized as one of the most climate vulnerable countries in the world. It experiences frequent natural disasters that cause loss of life, damage to infrastructures and economic assets, and adversely impact on lives and livelihoods, especially of poor and marginal households. Addressing the most vulnerable coastal communities in Bangladesh, this thesis determines the Livelihood Vulnerability Index (LVI) using three methods named as SLVI (Composite index by Sullivan), LVI-IPCC (IPCC approach) and YLVI (Yates approach) to estimate climate change vulnerability in the coastal belt of Bangladesh. Nine villages were considered for this study; they are Laksmikhali village of Morrelganj upazila, Golbunia village of Mongla upazila, and Uttar Rajapur village of Sarankhola upazila, Dash Ani of Bagerhat Sadar upazila, Nalian villalge of Dacope upazila, Bhagba village of Koira upazila, Rajapur village of Rupsa upazila, Baintala village of Assasunni upazila and Herinnagor village of Sayamnagor upazila. The vulnerability of water resource from a gender perspective based on matrix framework is calculated in three villages; Uttar Rajapur village of Sarankhola upazil, Dash Ani of Bagerhat Sadar upazilas and Herinnagor village of Sayamnagor upazila. It also explores people’ perception regarding their vulnerabilities to coastal hazards and investigates the methods that communities apply to cope with different coastal hazards. For LVI determination and investigation of people’s perception regarding hazards, about 100 households were surveyed in each of nine village. Focus Group Discussion (FGD) conducted in three villages to assess vulnerability of water resources.
The major components indices of Livelihood Vulnerability Index (LVI) such as Socio-demographic profile, Livelihood strategies, Social network, Health, Food, Water, Natural disaster and climate variability were calculated based on survey data.
The calculated results showed that Morrelganj may be more vulnerable in terms of social networks, Mongla may be more vulnerable in terms of food security, Sarankhola may be more vulnerable in terms of water resources, and Dacope may be more vulnerable in terms of health facility and Assasunni may be more vulnerable in terms of livelihood strategies while Sayamnagor may be more vulnerable in terms of two major vulnerability components; socio demographic profile and natural disaster and climate variability. The overall Livelihood Vulnerability Index (LVI) based on three methods is found higher for Sayamnagor compared to others district. The obtained scores of SLVI, LVI-IPCC and YLVI are, Morrelganj: 0.348, -0.020 and 0.340, Mongla: 0.345, -0.18 and 0.351, Sarankhola: 0.367, 0.001 and 0.406, Dacope: 0.396, 0.009 and 0.473, Koira: 0.365,-0.017 and 0.361, Assasunni: 0.383, 0.008 and 0.444, Sayamnagor: 0.401, 0.04 and 0.544, Bagerhat Sadar: 0.306, -0.016 and 0.253, Rupsa: 0.322 -0.015 and 0.274, respectively. It can be noted that the vulnerability score for SLVI ranges from 0 to 1. That of LVI-IPCC and YLVI ranged from -1 to +1 and 0 to 1, respectively.
In this study, it is observed that for the LVI-IPCC approach, although the contributing factors (exposure, sensitivity and adaptive capacity) individually show variations in their indices from one village to another, no major variation is observed for total livelihood index. However, the designed SLVI and YLVI shows variation among the studied nine villages. Therefore, it can be concluded that SLVI and YLVI approaches are suitable for community or district level whereas the LVI-IPCC is suitable for regional level evaluation.
Vulnerability of water resources based on matrix framework from a gender view point shows that Sayamnagor is more vulnerable to climate change induced disaster events whereas in Bagerhat Sadar and Sarankhola is more vulnerable to climate associated gradual changes. In Sayamnagor, the total vulnerability is greater than the specific vulnerability due to average seasonal change and smaller than disaster induced vulnerability. On the contrary, Sarankhola and Bagerhat Sadar show that the specific vulnerability due to average seasonal change is greater than total vulnerability and the specific vulnerability due to average change in induced disaster events is smaller than total vulnerability. However, the overall water resource vulnerability is higher in Sayamnagor (2.21) than Sarankhola (2.03) and Bagerhat Sadar (1.04).
The people’ perception regarding their vulnerabilities to coastal hazards and their coping strategies show that people perceived an increase in both the intensity of hazards and their vulnerabilities. In spite of having a number of socio-economic and location factors enhancing their vulnerabilities, the community is creating their ways to cope with these hazards. For different aspects of life like food and shelter, water supply, sanitation, and health, communities are found to apply different coping methods that vary with the types of hazards. According to the people’ perceptions, the most prevalent coastal hazards in the study areas are cyclone, flood, and tidal surge. In case of shelter system, there are more kacha houses in Dacope upazila than Morrelganj, Mongla, Sarankhola, Koira, Assasunni, Bagerhat Sadar and Rupsa. Therefore Dacope is more vulnerable in case of existing housing pattern. In case of water supply system during natural hazard, Sayamnagor, Dacope and Assasunni is found more vulnerable compared to other areas as more than 70% of water sources were found to be unusable due to the hazard. In case of sanitation system, people from Sayamnagor use more unhygienic latrine (about 58%) than Morrelganj, Mongla, Sarankhola, Dacope, Koira, Assasunni, Bagerhat Sadar and Rupsa. In this case, the sanitation system of Sayamnagor became more unusable than Morrelganj, Mongla, Sarankhola, Dacope, Koira, Assasunni, Bagerhat Sadar and Rupsa. In case of health impact, people are suffered from various kinds of diseases due to the impact of natural hazards. Diarrhea, dysentery and Skin diseases are the most prevalent disease during disaster. Before starting hazards, taking preventive measure for health problem is not common in the study areas. It is observed that more than 80% people do not stock emergency medicine before hazards starting. On the other hand, generally in every locality of the surveyed area, as a preparation for natural hazards, the households store dry food such as chira-muri, gur (molasses) and chal (rice), dal (pulse), tel (oil), nun (salt) etc.
Knowledge and understanding of households’ vulnerability acquired from such study may provide government and other relevant agencies with critical information for proper distribution of relief materials. Households’ local adaptation strategies for resilience help them in implementing non-structural mitigation measures, which also benefit overall development through capacity building. Furthermore, households with low levels of human, financial, social and physical capital are found to have less capacity to meet the challenges of a disaster. Moreover, this study will help the development organizations, policymakers and public health practitioners with a practical tool to understand demographic, social and health factors contributing to climate vulnerability at the district or community level.Md. Bellal HossenMaster of Science in Civil Engineerin
Simulation of pre-monsoon rainfall Over Bangladesh using high Resolution wrf-arw model
No full textThis thesis is submitted to the Department of Physics, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Physics, September 2017.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 84-87).In the present study, the Weather Research and Forecast (WRF-ARW V3.5.1) model have
been used to simulate the pre-monsoon rainfall during 2010–2014 for all the meteorological
station points of Bangladesh. The initial and boundary conditions are drawn from the global
operational analysis and forecast products of National Center for Environmental Prediction
(NCEP-GFS) available for the public at 1°×1o resolution. The model is configured in single
domain, 6 km horizontal grid spacing with 161×183 grids in the east-west and north-south
directions and 28 vertical levels. For the simulation of pre-monsoon rainfall, WSM6-class
graupel scheme coupled with Kain-Fritsch (KF) cumulus parameterization (CP) scheme has
been used. Initially, the model is run 107 days for long term prediction starting with the initial condition of 0000 UTC of 17 February up to 0000 UTC of 01 June for the period 2010-2014. The model is also run for 72 hours with every day at 0000 UTC initial conditions for 94 days for the prediction of 24, 48 and 72 hours lead time rainfall in the pre-monsoon season of 2014. In this research, convective and non-convective rainfall have been simulated at 3 hourly interval then made daily and monthly total rainfall data for 24, 48, 72 hour and 107 days during the studied period. We have compared this data with the observed rainfall at 33 meteorological stations of BMD and TRMM rainfall. From this research it has been found that the 107 days predicted and TRMM rainfall is much lower than that of observed rainfall. The simulated rainfall at different stations for 24, 48 and 72 hours for the month of March, April and May are good agreement with the observed rainfall. The long term predictions of simulated rainfall are also matched with BMD observed rainfall. From the rainfall distribution the maximum rainfalls have been found in the northeastern region and also obtain in the southeastern region and the minimum rainfalls have been found in the west, northwest and southwestern regions of Bangladesh. From the rainfall distribution pattern the maximum Correlation coefficient (CC) has been shown at southern and southeastern regions and the minimum CC’s has been found in the northern, northwest
and southwestern regions of the country. From this study, it has been analyzed that where the rainfall is maximum there the RMSE, MAE and CC is also maximum and vice versa. Finally, it has been observed that WRF-ARW model is suitable for the prediction of pre-monsoon rainfall.Taslima KhatunMaster of Science in Physic
Microstrip Patch Antenna with Dual Equilateral Triangular Cut Resonators Structure for WLAN Application
No full textThis thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, February, 2016.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 68-70).The necessity for wireless communication and its esoteric nature is enlarging during the two
decades. In future, it is deduced to be more challenging and elaborate with evolution of different
types of patch antenna with different structures. Nowadays, smaller size of electronic equipment
demand same size antenna element in order to place properly in the wireless devices without
changing the radiation properties of antenna. Antenna plays an important role in WLAN
communication system because it performance depend upon the quality of wireless
communication. Providing of a quality service for the recently increased demand in WLAN is a
core level concern as usually for antenna and communication devices. The WLAN is used in our
everyday life applications such as notebooks, mobile phones, routers etc. To meet the daily
increasing needs, antennas used in WLAN applications are noteworthy factor. With respect to
performance, a low cost feed network with miniaturization in size is also very important to carry
out in terms of antenna design. This thesis work focuses mostly on design and analysis of
microstrip patch antenna using split ring resonator structure as well as effects of triangular cut
resonator structure made on patch antenna to improve the return loss, gain and directivity. We
present characteristics of microstrip patch antennas on Roger RT/Duroid 5880 substrates loaded
with complementary equilateral triangular cut split-ring resonators (CETCSRRs) and study the
various effects of design parameters like size of resonator, number of resonator, location of
resonator and orientation between two resonators for WLAN applications. The proposed
antennas are designed using CST 2014 microwave studio. The simulated results represent that
the CTCSRR loaded patch antenna achieves better performance in terms of gain, directivity and
return loss. The radiation properties of a rectangular patch antenna with triangular split ring
resonator structure designed on Roger RT/Duroid 5880Sunanda RoyMaster of Science in Electrical and Electronic Engineerin
