Epileptic Seizure Detection And Prediction From Electroencephalogram Using Neuro-Fuzzy Algorithms

This dissertation presents innovative approaches based on fuzzy logic in epileptic seizure detection and prediction from Electroencephalogram (EEG). The fuzzy rule-based algorithms were developed with the aim to improve quality of life of epilepsy patients by utilizing intelligent methods. An adaptive fuzzy logic system was developed to detect seizure onset in a patient specific way. Fuzzy if-then rules were developed to mimic the human reasoning and taking advantage of the combination in spatial-temporal domain. Fuzzy c-means clustering technique was utilized for optimizing the membership functions for varying patterns in the feature domain. In addition, application of the adaptive neuro-fuzzy inference system (ANFIS) is presented for efficient classification of several commonly arising artifacts from EEG. Finally, we present a neuro-fuzzy approach of seizure prediction by applying the ANFIS. Patient specific ANFIS classifier was constructed to forecast a seizure followed by postprocessing methods. Three nonlinear seizure predictive features were used to characterize changes prior to seizure. The nonlinear features used in this study were similarity index, phase synchronization, and nonlinear interdependence. The ANFIS classifier was constructed based on these features as inputs. Fuzzy if-then rules were generated by the ANFIS classifier using the complex relationship of feature space provided during training. In this dissertation, the application of the neuro-fuzzy algorithms in epilepsy diagnosis and treatment was demonstrated by applying the methods on different datasets. Several performance measures such as detection delay, sensitivity and specificity were calculated and compared with results reported in literature. The proposed algorithms have potentials to be used in diagnostics and therapeutic applications as they can be implemented in an implantable medical device to detect a seizure, forecast a seizure, and initiate neurostimulation therapy for the purpose of seizure prevention or abortion

A Fuzzy Logic System for Seizure Onset Detection in Intracranial EEG

We present a multistage fuzzy rule-based algorithm for epileptic seizure onset detection. Amplitude, frequency, and entropy-based features were extracted from intracranial electroencephalogram (iEEG) recordings and considered as the inputs for a fuzzy system. These features extracted from multichannel iEEG signals were combined using fuzzy algorithms both in feature domain and in spatial domain. Fuzzy rules were derived based on experts' knowledge and reasoning. An adaptive fuzzy subsystem was used for combining characteristics features extracted from iEEG. For the spatial combination, three channels from epileptogenic zone and one from remote zone were considered into another fuzzy subsystem. Finally, a threshold procedure was applied to the fuzzy output derived from the final fuzzy subsystem. The method was evaluated on iEEG datasets selected from Freiburg Seizure Prediction EEG (FSPEEG) database. A total of 112.45 hours of intracranial EEG recordings was selected from 20 patients having 56 seizures was used for the system performance evaluation. The overall sensitivity of 95.8% with false detection rate of 0.26 per hour and average detection latency of 15.8 seconds was achieved

IDENTIFICATION OF CAUSES OF DEMAND VARIATION AND ITS IMPACT ON SALES VOLUME - AN EXPLORATORY STUDY IN PROCESSED FOOD INDUSTRY IN BANGLADESH

Demand variation is a key issue in processed food industry, because demands for processed food products vary daily. The organizations in this situation face challenges to meet customer demand. Their products have a definite shelf life and prone to be obsolete. Obsolete products are totally wastes. So, there exists a producer risk. This study has been conducted with the aim of identifying the root causes of demand variation and its impact on sales volume. For this purpose an exploratory study involving two food processing organizations and their forty eight points of sales had been performed. Each food item has different causes and consequences for demand variation. In this regard, three food items having limited shelf life had been selected to find out the causes of their demand variation. The study identified eleven causes and twelve consequences such as special occasion, duration of shelf life, wrong forecasting and so on. Then some root causes are figured out that dominates over others. The impacts of these causes on sales volume are also shown with six months demand data. The research concludes with the level of impact of the significant causes like price, occasion. Lastly some recommendations are mentioned to minimize those root causes of demand variation

BaDLAD: A Large Multi-Domain Bengali Document Layout Analysis Dataset

While strides have been made in deep learning based Bengali Optical Character Recognition (OCR) in the past decade, the absence of large Document Layout Analysis (DLA) datasets has hindered the application of OCR in document transcription, e.g., transcribing historical documents and newspapers. Moreover, rule-based DLA systems that are currently being employed in practice are not robust to domain variations and out-of-distribution layouts. To this end, we present the first multidomain large Bengali Document Layout Analysis Dataset: BaDLAD. This dataset contains 33,695 human annotated document samples from six domains - i) books and magazines, ii) public domain govt. documents, iii) liberation war documents, iv) newspapers, v) historical newspapers, and vi) property deeds, with 710K polygon annotations for four unit types: text-box, paragraph, image, and table. Through preliminary experiments benchmarking the performance of existing state-of-the-art deep learning architectures for English DLA, we demonstrate the efficacy of our dataset in training deep learning based Bengali document digitization models

Bans of WHO Class I Pesticides in Bangladesh –Suicide Prevention without Hampering Agricultural Output

Pesticide self-poisoning is a major problem in Bangladesh. Over the past 20-years, the Bangladesh government has introduced pesticide legislation and banned highly hazardous pesticides (HHPs) from agricultural use. We aimed to assess the impacts of pesticide bans on suicide and on agricultural production.We obtained data on unnatural deaths from the Statistics Division of Bangladesh Police, and used negative binomial regression to quantify changes in pesticide suicides and unnatural deaths following removal of WHO Class I toxicity HHPs from agriculture in 2000. We assessed contemporaneous trends in other risk factors, pesticide usage and agricultural production in Bangladesh from 1996 to 2014.Mortality in hospital from pesticide poisoning fell after the 2000 ban: 15.1% vs 9.5%, relative reduction 37.1% [95% confidence interval (CI) 35.4 to 38.8%]. The pesticide poisoning suicide rate fell from 6.3/100 000 in 1996 to 2.2/100 000 in 2014, a 65.1% (52.0 to 76.7%) decline. There was a modest simultaneous increase in hanging suicides [20.0% (8.4 to 36.9%) increase] but the overall incidence of unnatural deaths fell from 14.0/100 000 to 10.5/100 000 [25.0% (18.1 to 33.0%) decline]. There were 35 071 (95% CI 25 959 to 45 666) fewer pesticide suicides in 2001 to 2014 compared with the number predicted based on trends between 1996 to 2000. This reduction in rate of pesticide suicides occurred despite increased pesticide use and no change in admissions for pesticide poisoning, with no apparent influence on agricultural output.Strengthening pesticide regulation and banning WHO Class I toxicity HHPs in Bangladesh were associated with major reductions in deaths and hospital mortality, without any apparent effect on agricultural output. Our data indicate that removing HHPs from agriculture can rapidly reduce suicides without imposing substantial agricultural costs

Measuring routine childhood vaccination coverage in 204 countries and territories, 1980-2019 : a systematic analysis for the Global Burden of Disease Study 2020, Release 1

Background Measuring routine childhood vaccination is crucial to inform global vaccine policies and programme implementation, and to track progress towards targets set by the Global Vaccine Action Plan (GVAP) and Immunization Agenda 2030. Robust estimates of routine vaccine coverage are needed to identify past successes and persistent vulnerabilities. Drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020, Release 1, we did a systematic analysis of global, regional, and national vaccine coverage trends using a statistical framework, by vaccine and over time. Methods For this analysis we collated 55 326 country-specific, cohort-specific, year-specific, vaccine-specific, and dosespecific observations of routine childhood vaccination coverage between 1980 and 2019. Using spatiotemporal Gaussian process regression, we produced location-specific and year-specific estimates of 11 routine childhood vaccine coverage indicators for 204 countries and territories from 1980 to 2019, adjusting for biases in countryreported data and reflecting reported stockouts and supply disruptions. We analysed global and regional trends in coverage and numbers of zero-dose children (defined as those who never received a diphtheria-tetanus-pertussis [DTP] vaccine dose), progress towards GVAP targets, and the relationship between vaccine coverage and sociodemographic development. Findings By 2019, global coverage of third-dose DTP (DTP3; 81.6% [95% uncertainty interval 80.4-82 .7]) more than doubled from levels estimated in 1980 (39.9% [37.5-42.1]), as did global coverage of the first-dose measles-containing vaccine (MCV1; from 38.5% [35.4-41.3] in 1980 to 83.6% [82.3-84.8] in 2019). Third- dose polio vaccine (Pol3) coverage also increased, from 42.6% (41.4-44.1) in 1980 to 79.8% (78.4-81.1) in 2019, and global coverage of newer vaccines increased rapidly between 2000 and 2019. The global number of zero-dose children fell by nearly 75% between 1980 and 2019, from 56.8 million (52.6-60. 9) to 14.5 million (13.4-15.9). However, over the past decade, global vaccine coverage broadly plateaued; 94 countries and territories recorded decreasing DTP3 coverage since 2010. Only 11 countries and territories were estimated to have reached the national GVAP target of at least 90% coverage for all assessed vaccines in 2019. Interpretation After achieving large gains in childhood vaccine coverage worldwide, in much of the world this progress was stalled or reversed from 2010 to 2019. These findings underscore the importance of revisiting routine immunisation strategies and programmatic approaches, recentring service delivery around equity and underserved populations. Strengthening vaccine data and monitoring systems is crucial to these pursuits, now and through to 2030, to ensure that all children have access to, and can benefit from, lifesaving vaccines. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Response of the rhizobial-mycorrhizal-lentil symbiosis to arsenic

The thesis focused on the response of the rhizobial-mycorrhizal-lentil symbiosis to arsenic as an environmental contaminant.  This was instigated by the concern over the arsenic contaminated irrigation water problem in South East Asia, and in particularly, its impact on Bangladesh agriculture.  This led to a holistic approach to the study, by investigating the effect of inoculation with Rhizobium leguminosarum and the AM fungus Glomus mosseae, as well as application of superphosphate and rock phosphate, on lentil growth, nitrogenase activity and nutrient uptake (especially N and P) in the presence of arsenic contaminated irrigation water.  Positive effects of mycorrhizal inoculation on lentil (Lens culinaris L.) growth, nitrogen fixation and P nutrition were observed, along with reduced uptake of As in roots, shoots and pods.  Decreased plant growth, nitrogen fixation, nutrient uptake, mycorrhizal infection and increased uptake of arsenic in root, shoot and pods were observed due to application of arsenate contaminated irrigation water.  The use of a lux based bacterial biosensor test demonstrated that mycorrhizal inoculation reduced arsenic bioavailability in soil and that most of the toxicity was associated with the colloidal and fine particulate soil fraction.  When rock phosphate was applied, an increase of P uptake only was observed.  In contrast, superphosphate increased both P and As uptake and decreased mycorrhizal infection and activity. In summary, this thesis has shown that mycorrhizal inoculation appears to offer great potential as an effective tool contributing to crop management for technique in minimisation of the total intake of As by human and livestock.  The observed decreased in uptake of As into pods of mycorrhizal lentil has particularly important potential implications for human health.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Analyzing the gap between Swedish governmental export support programs and cleantech firm’s expectations

Given the present situation of environmental problems, clean technologies or cleantech is considered a way of reaching global sustainability and at the same time also seen as an engine of economic growth and fulfilling commitments to social and environmental welfare. Under this background, Swedish cleantech sector have not achieved that much commercial success yet that they are supposed to be while maintaining a reputation of top technological innovative country. The Swedish cleantech sector is dominated by small medium-sized firms (SMEs) and often limited to resources at their disposition. Thus, the Swedish government has designed various policies and export support programs to promote this sector but somehow firms could not reach up to them. Hence, it has become necessary to study the Swedish cleantech firms in order to analyze the existing gap. The purpose of this study is to run an investigation about individual cleantech firms and analyze how they are experiencing Swedish governmental export support programs. On the other hand, this study has also tried to find out what firms really expect from these programs so that it will help to reduce the gap. Based on the study of four cases and one independent interview, the study has shown two different scenarios. In one hand, micro level SMEs specially which are in initial phase of their internationalization process cannot reach up to governmental export support programs due to high acquiring cost and inflexible pre-requirements. On the other hand, small level SMEs which are in mature phase of their internationalization process have faced completely reverse experience than initial phase micro firms but not satisfied with the provided service quality. The study has also revealed that firms with relatively new technology face problems to get support from governmental agencies due to uncertain market performance. The study has further showed, this is not always the high acquiring cost and inflexible conditions, participation in governmental export support programs is also depend on firm’s owns mindset and their business strategy. So, in order to reduce the gap between Swedish governmental export support programs and cleantech firms’ expectations, the studied firms have suggested to implement a proper business model that fits into each type of firms’ needs based on their position in the internationalization process, create a separate institution or agency and Science Park that only deals with cleantech firms issues, and co-operation among the different state cleantech firms and the universities

Foreign exchange rate exposure and its determinants : firm and industry level analysis

Financial theory predicts that a change in an exchange rate should affect the value of a firm or an industry. To a large extent, past research has not supported this theory. which is surprising especially after considering the substantial exchange ratc fluctuations over the last three' decades. This study extends previous research on the foreign exchange rate exposure using a sample of 364 UK nonfinancial companies over the period from January 1981 to December 2001. The impact of the changes (realised and unexpected) in exchange rates on firms' or industries' stock returns is examined. In addition, the movements in bilateral, equally weighted and trade-weighted exchange rate indices arc considered. The findings indicate that a higher percentage ofUK firms and industries arc exposed to contemporaneous exchange rate changes than those reported in previous studies. UK firms' and industries' stock returns are more affected by changes in the ECU. EQW. US$ and JPY exchange rate, and less significantly to the basket of 20 countries' currencies relative to the British pound exchange rate. There is alsO evidence of significant lagged exchange rate exposure. This lagged exchange rate exposure is consistent with findings in previous studies that some market inefficiencies may exist in incorporating exchange rate changes into the returns of firms and industries. This also means that there is possible mispricing of the: exchange rate to firm value relationship by the market. This study also segregates firms and industries based on various variables that might affect their exchange rate exposure. These variables arc divided into two main groups: foreign involvement variables and hedging variables. The results indicate that the extent of firms' foreign activity has an impact on their exchange rate exposure. These findings imply that restructuring foreign operations can reduce firms' exchange rate exposure. The results also reveal that hedging policies are important detenninants of the exchange rate exposure.EThOS - Electronic Theses Online ServiceGBUnited Kingdo