Search results for: q-rung orthopair fuzzy sets

Authors: Kraiem Khadija, Hamadi Kallali, Naceur Jedidi

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Constructed wetland systems are eco-technology recognized as environmentally friendly and emerging innovative solutions remediation as these systems are cost-effective and sustainable wastewater treatment systems. The performance of these biological system is affected by various factors such as plant, substrate, wastewater type, hydraulic loading rate, hydraulic retention time, water depth, and operation mood. The objective of this study was to to assess the alters of plant species on pollutants reduction and enrichment of anammox and nitrifing denitrifing bacteria in a modified vertical flow (VFCW) constructed wetland. This tests were carried out using three modified vertical constructed wetlands with a surface of 0.23 m² and depth 80 cm. It was a saturated vertical constructed wetland at the bottom. The saturation zone is maintained by the siphon structure at the outlet. The VFCW (₁) system was unplanted, VFCW (₂) planted with Typha angustofolia, and VFCW(₃) planted with Phragmites australis. The experimental units were fed with domestic wastewater and were operated by batch mode during 8 months at an average hydraulic loading rate around 20 cm day− 1. The operation cycle was two days feeding and five days rest. Results indicated that plants presence improved the removal efficiency; the removal rates of organic matter (85.1–90.9%; COD and 81.8–88.9%; BOD5), nitrogen (54.2–73%; NTK and 66–77%; NH4 -N) were higher by 10.7–30.1% compared to the unplanted vertical constructed wetland. On the other hand, the plant species had no significant effect on removal efficiency of COD, The removal of COD was similar in VFCW (₂) and VFCW (₃) (p > 0.05), attaining average removal efficiencies of 88.7% and 85.2%, respectively. Whereas it had a significant effect on NTK removal (p > 0.05), with an average removal rate of 72% versus 51% for VFCW (₂) and VFCW (₃), respectively. Among the three sets of vertical flow constructed wetlands, the VFCW(₂) removed the highest percent of total streptococcus, fecal streptococcus total coliforms, fecal coliforms, E. coli as 59, 62, 52, 63, and 58%, respectively. The presence and the plant species alters the community composition and abundance of the bacteria. The abundance of bacteria in the planted wetland was much higher than that in the unplanted one. VFCW(₃) had the highest relative abundance of nitrifying bacteria such as Nitrosospira (18%), Nitrosospira (12%), and Nitrobacter (8%). Whereas the vertical constructed wetland planted with typha had larger number of denitrifying species, with relative abundances of Aeromonas (13%), Paracoccus (11%), Thauera (7%), and Thiobacillus (6%). However, the abundance of nitrifying bacteria was very lower in this system than VFCW(₂). Interestingly, the presence of Thypha angustofolia species favored the enrichment of anammox bacteria compared to unplanted system and system planted with phragmites australis. The results showed that the middle layer had the most accumulation of anammox bacteria, which the anaerobic condition is better and the root system is moderate. Vegetation has several characteristics that make it an essential component of wetlands, but its exact effects are complex and debated.

Keywords: wastawater, constructed wetland, anammox, removal

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Authors: Waheed O. Majekodunmi

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Climate change is a real global phenomenon and an unquestionable threat to our quest for a healthy and livable planet. It is now regarded as potentially the most monumental environmental challenge people and the planet will be confronted with over the next centuries. Expectedly, climate change mitigation was one of the central themes of COP 28. Despite contributing the least to climate change, Africa is and remains the hardest hit by the negative consequences of climate change including poor growth performance. Currently, it is being hypothesized that the high level of vulnerability and exposure to climate-related disasters, low adaptive capacity against global warming and high mitigation costs of climate change across the continent could be linked to the recent abysmal economic performance of African countries, especially in oil-producing countries where greenhouse gas emissions, is potentially more prevalent. This paper examines the impact of climate change on the economic performance of selected oil-producing countries in Africa using evidence from Nigeria, Algeria and Angola. The objective of the study is to determine whether or not climate change influences the economic performance of oil-producing countries in Africa by examining the nexus between economic growth and climate-related variables. The study seeks to investigate the effect of climate change on the pace of economic growth in African oil-producing countries. To achieve the research objectives, this study utilizes a quantitative approach by using historical and current secondary data sets to determine the relationship between climate-related variables and economic growth variables in the selected countries. The study employed numbers, percentages, tables and trend graphs to explain the trends or common patterns between climate change, economic growth and determinants of economic growth: governance effectiveness, infrastructure, macroeconomic stability and regulatory efficiency. Results from the empirical analysis of data show that the trends of economic growth and climate-related variables in the selected oil-producing countries are in the opposite directions as the increasing share of renewable energy sources in total energy consumption and the reduction in greenhouse gas emissions per capita in the oil-producing countries did not translate to higher economic growth. Further findings show that annual surface temperatures in the selected countries do not share similar trends with the food imports ratio and GDP per capita annual growth rate suggesting that climate change does not impact significantly agricultural productivity and economic growth in oil-producing countries in Africa. Annual surface temperature was also found to not share a similar pattern with governance effectiveness, macroeconomic stability and regulatory efficiency reinforcing the claim that some economic growth variables are independent of climate change. The policy implication of this research is that oil-producing African countries need to focus more on improving the macroeconomic environment and streamlining governance and institutional processes to boost their economic performance before considering the adoption of climate change adaptation and mitigation strategies.

Keywords: climate change, climate vulnerability, economic growth, greenhouse gas emissions per capita, oil-producing countries, share of renewable energy in total energy consumption

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Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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Authors: Jara Kaye S. Villanueva, M. Rosario Concepcion O. Ang

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For the past few years, Philippines has depended most of its energy source on oil, coal, and fossil fuel. According to the Department of Energy (DOE), the dominance of coal in the energy mix will continue until the year 2020. The expanding energy needs in the country have led to increasing efforts to promote and develop renewable energy. This research is a part of the government initiative in preparation for renewable energy development and expansion in the country. The Philippine Renewable Energy Resource Mapping from Light Detection and Ranging (LiDAR) Surveys is a three-year government project which aims to assess and quantify the renewable energy potential of the country and to put them into usable maps. This study focuses on the site suitability analysis of the four renewable energy sources – biomass (coconut, corn, rice, and sugarcane), hydro, solar, and wind energy. The site assessment is a key component in determining and assessing the most suitable locations for the construction of renewable energy power plants. This method maximizes the use of both the technical methods in resource assessment, as well as taking into account the environmental, social, and accessibility aspect in identifying potential sites by utilizing and integrating two different methods: the Multi-Criteria Decision Analysis (MCDA) method and Geographic Information System (GIS) tools. For the MCDA, Analytical Hierarchy Processing (AHP) is employed to determine the parameters needed for the suitability analysis. To structure these site suitability parameters, various experts from different fields were consulted – scientists, policy makers, environmentalists, and industrialists. The need to have a well-represented group of people to consult with is relevant to avoid bias in the output parameter of hierarchy levels and weight matrices. AHP pairwise matrix computation is utilized to derive weights per level out of the expert’s gathered feedback. Whereas from the threshold values derived from related literature, international studies, and government laws, the output values were then consulted with energy specialists from the DOE. Geospatial analysis using GIS tools translate this decision support outputs into visual maps. Particularly, this study uses Euclidean distance to compute for the distance values of each parameter, Fuzzy Membership algorithm which normalizes the output from the Euclidean Distance, and the Weighted Overlay tool for the aggregation of the layers. Using the Natural Breaks algorithm, the suitability ratings of each of the map are classified into 5 discrete categories of suitability index: (1) not suitable (2) least suitable, (3) suitable, (4) moderately suitable, and (5) highly suitable. In this method, the classes are grouped based on the best groups similar values wherein each subdivision are set from the rest based on the big difference in boundary values. Results show that in the entire Philippine area of responsibility, biomass has the highest suitability rating with rice as the most suitable at 75.76% suitability percentage, whereas wind has the least suitability percentage with score 10.28%. Solar and Hydro fall in the middle of the two, with suitability values 28.77% and 21.27%.

Keywords: site suitability, biomass energy, hydro energy, solar energy, wind energy, GIS

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Authors: Kimberly M. Cacciato, Steven J. Singer, Allison R. Shapiro, Julianna F. Kamenakis

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This study examines the dynamics of communication among researchers and participants who have various levels of hearing, use multiple languages, have various disabilities, and who come from different social strata. This qualitative methodological study focuses on the strategies employed in an ethnographic research study examining the communication choices of six sets of parents who have Deaf-Disabled children. The participating families varied in their communication strategies and preferences including the use of American Sign Language (ASL), visual-gestural communication, multiple spoken languages, and pidgin forms of each of these. The research team consisted of two undergraduate students proficient in ASL and a Deaf principal investigator (PI) who uses ASL and speech as his main modes of communication. A third Hard-of-Hearing undergraduate student fluent in ASL served as an objective facilitator of the data analysis. The team created reflexive journals by audio recording, free writing, and responding to team-generated prompts. They discussed interactions between the members of the research team, their evolving relationships, and various social and linguistic power differentials. The researchers reflected on communication during data collection, their experiences with one another, and their experiences with the participating families. Reflexive journals totaled over 150 pages. The outside research assistant reviewed the journals and developed follow up open-ended questions and prods to further enrich the data. The PI and outside research assistant used NVivo qualitative research software to conduct open inductive coding of the data. They chunked the data individually into broad categories through multiple readings and recognized recurring concepts. They compared their categories, discussed them, and decided which they would develop. The researchers continued to read, reduce, and define the categories until they were able to develop themes from the data. The research team found that the various communication backgrounds and skills present greatly influenced the dynamics between the members of the research team and with the participants of the study. Specifically, the following themes emerged: (1) students as communication facilitators and interpreters as barriers to natural interaction, (2) varied language use simultaneously complicated and enriched data collection, and (3) ASL proficiency and professional position resulted in a social hierarchy among researchers and participants. In the discussion, the researchers reflected on their backgrounds and internal biases of analyzing the data found and how social norms or expectations affected the perceptions of the researchers in writing their journals. Through this study, the research team found that communication and language skills require significant consideration when working with multiple and complex communication modes. The researchers had to continually assess and adjust their data collection methods to meet the communication needs of the team members and participants. In doing so, the researchers aimed to create an accessible research setting that yielded rich data but learned that this often required compromises from one or more of the research constituents.

Keywords: American Sign Language, complex communication, deaf-disabled, methodology

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Authors: Pratap Chandra Pati, Prabina Rajib, Parama Barai

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The traditional finance theory neglects the role of sentiment factor in asset pricing. However, the behavioral approach to asset-pricing based on noise trader model and limit to arbitrage includes investor sentiment as a priced risk factor in the assist pricing model. Investor sentiment affects stock more that are vulnerable to speculation, hard to value and risky to arbitrage. It includes small stocks, high volatility stocks, growth stocks, distressed stocks, young stocks and non-dividend-paying stocks. Since the introduction of Chicago Board Options Exchange (CBOE) volatility index (VIX) in 1993, it is used as a measure of future volatility in the stock market and also as a measure of investor sentiment. CBOE VIX index, in particular, is often referred to as the ‘investors’ fear gauge’ by public media and prior literature. The upward spikes in the volatility index are associated with bouts of market turmoil and uncertainty. High levels of the volatility index indicate fear, anxiety and pessimistic expectations of investors about the stock market. On the contrary, low levels of the volatility index reflect confident and optimistic attitude of investors. Based on the above discussions, we investigate whether market-wide fear levels measured volatility index is priced factor in the standard asset pricing model for the Indian stock market. First, we investigate the performance and validity of Fama and French three-factor model and Carhart four-factor model in the Indian stock market. Second, we explore whether India volatility index as a proxy for fearful market-based sentiment indicators affect the cross section of stock returns after controlling for well-established risk factors such as market excess return, size, book-to-market, and momentum. Asset pricing tests are performed using monthly data on CNX 500 index constituent stocks listed on the National stock exchange of India Limited (NSE) over the sample period that extends from January 2008 to March 2017. To examine whether India volatility index, as an indicator of fear sentiment, is a priced risk factor, changes in India VIX is included as an explanatory variable in the Fama-French three-factor model as well as Carhart four-factor model. For the empirical testing, we use three different sets of test portfolios used as the dependent variable in the in asset pricing regressions. The first portfolio set is the 4x4 sorts on the size and B/M ratio. The second portfolio set is the 4x4 sort on the size and sensitivity beta of change in IVIX. The third portfolio set is the 2x3x2 independent triple-sorting on size, B/M and sensitivity beta of change in IVIX. We find evidence that size, value and momentum factors continue to exist in Indian stock market. However, VIX index does not constitute a priced risk factor in the cross-section of returns. The inseparability of volatility and jump risk in the VIX is a possible explanation of the current findings in the study.

Keywords: India VIX, Fama-French model, Carhart four-factor model, asset pricing

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Authors: Arkadiusz P. Wójcik, Tetsuya Sato, Shin-Ichiro Shima, Mateusz Malanowski

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Over the last decades, new technologies have significantly changed the way information is transmitted and stored. Renewable energy sources have become prevalent and affordable. Cooperation of the Information and Communication Technology industry and Renewable Energy industry makes it possible to create a next generation, decentralized power grid. In this context, the study seeks to identify the wider benefits to the local Japanese economy as a result of the development of a decentralised electricity market. Our general approach aims to integrate an economic analysis (monetary appraisal of costs and benefits to society) with externalities that are not quantifiable in monetary terms (e.g. social impact, environmental impact). The study also highlights opportunities and sets out recommendations for the citizens of the island and the local government. The simulation is the scientific basis for economic impact analysis. Various types of sources of energy have been taken into account: residential wind farm, residential wind turbine, solar farm, residential solar panels and private solar farms. Analysis of local geographic and economic conditions allowed creating a customized business model. Very often farmers on Awaji Island are using crop cycle. During each cycle, one part of the field is resting and replenishing nutrients. In the next year another part of the field is resting. Portable solar panels could be freely set up in this part of the field. At the end of the crop cycle, portable solar panels would be moved to the next resting part. Because of spacious area, for a single household 500 square meters of portable solar panels has been proposed and simulated. The devised simulation shows that the Rate of Return on Investment for solar panels, which are on the island, could reach up to 37.21%. Supposing that about 20% of households install solar panels they could produce 49.11% of the electric energy consumed by households on the island. The analysis shows that rest of the energy supply can be produced by currently existing one huge solar farm and two wind farms to meet 97.59% of demand on electricity for households on the island. Although there are more than 7,000 agricultural fields on the island, young people tend to avoid agricultural work and prefer to move from the island to big cities, live there in little mansions and work until late night. The business model proposed in this study could increase farmer’s monthly income by ¥200,000 - ¥300,000 (1,600 euro – 2,400 euro). Young people could work less and have a higher standard of living than in a city. Creation of a decentralized electricity market can unlock significant benefits in other industries (e.g. electric vehicles), providing a welcome boost to economic growth, jobs and quality of life.

Keywords: digital twin, Matlab, model-based systems engineering, simulink, smart grid, systems engineering

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Anna Solovyeva, Ivan Levakin, Nickolai Galaktionov, Olga Podgornaya

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Animals that reproduce asexually were thought to have the same genotypes within generations for a long time. However, some refuting examples were found, and mobile genetic elements (MGEs) or transposons are considered to be the most probable source of genetic instability. Dispersed nature and the ability to change their genomic localization enables MGEs to be efficient mutators. Hence the study of MGEs genomic impact requires an appropriate object which comprehends both representative amounts of various MGEs and options to evaluate the genomic influence of MGEs. Animals that reproduce asexually seem to be a decent model to study MGEs impact in genomic variability. We found a small marine trematode Himasthla elongata (Himasthlidae) to be a good model for such investigation as it has a small genome size, diverse MGEs and parthenogenetic stages in the lifecycle. In the current work, clonal diversity of cercaria was traced with an AFLP (Amplified fragment length polymorphism) method, diverse zones from electrophoretic patterns were cloned, and the nature of the fragments explored. Polymorphic patterns of individual cercariae AFLP-based fingerprints are enriched with retrotransposons of different families. The bulk of those sequences are represented by open reading frames of non-Long Terminal Repeats containing elements(non-LTR) yet Long-Terminal Repeats containing elements (LTR), to a lesser extent in variable figments of AFLP array. The CR1 elements expose both in polymorphic and conservative patterns are remarkably more frequent than the other non-LTR retrotransposons. This data was confirmed with shotgun sequencing-based on Illumina HiSeq 2500 platform. Individual cercaria of the same clone (i.e., originated from a single miracidium and inhabiting one host) has a various distribution of MGE families detected in sequenced AFLP patterns. The most numerous are CR1 and RTE-Bov retrotransposons, typical for trematode genomes. Also, we identified LTR-retrotransposons of Pao and Gypsy families among DNA transposons of CMC-EnSpm, Tc1/Mariner, MuLE-MuDR and Merlin families. We detected many of them in H. elongata transcriptome. Such uneven MGEs distribution in AFLP sequences’ sets reflects the different patterns of transposons spreading in cercarial genomes as transposons affect the genome in many ways (ectopic recombination, gene structure interruption, epigenetic silencing). It is considered that they play a key role in the origins of trematode clonal polymorphism. The authors greatly appreciate the help received at the Kartesh White Sea Biological Station of the Russian Academy of Sciences Zoological Institute. This work is funded with RSF 19-74-20102 and RFBR 17-04-02161 grants and the research program of the Zoological Institute of the Russian Academy of Sciences (project number AAAA-A19-119020690109-2).

Keywords: AFLP, clonal polymorphism, Himasthla elongata, mobile genetic elements, NGS

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Authors: S. J. Kim, Y. J. Yoo

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Slack-tide sampling was carried out at seven stations at high and low tides for a tidal cycle, in summer (7, 8, 9) and fall (10), 2016 to determine the differences of water quality according to tides in Masan Bay. The data were analyzed by Pearson correlation and factor analysis. The mixing state of all the water quality components investigated is well explained by the correlation with salinity (SAL). Turbidity (TURB), dissolved silica (DSi), nitrite and nitrate nitrogen (NNN) and total nitrogen (TN), which find their way into the bay from the streams and have no internal source and sink reaction, showed a strong negative correlation with SAL at low tide, indicating the property of conservative mixing. On the contrary, in summer and fall, dissolved oxygen (DO), hydrogen sulfide (H2S) and chemical oxygen demand with KMnO4 (CODMn) of the surface and bottom water, which were sensitive to an internal source and sink reaction, showed no significant correlation with SAL at high and low tides. The remaining water quality parameters showed a conservative or a non-conservative mixing pattern depending on the mixing characteristics at high and low tides, determined by the functional relationship between the changes of the flushing time and the changes of the characteristics of water quality components of the end-members in the bay. Factor analysis performed on the concentration difference data sets between high and low tides helped in identifying the principal latent variables for them. The concentration differences varied spatially and temporally. Principal factors (PFs) scores plots for each monitoring situation showed high associations of the variations to the monitoring sites. At sampling station 1 (ST1), temperature (TEMP), SAL, DSi, TURB, NNN and TN of the surface water in summer, TEMP, SAL, DSi, DO, TURB, NNN, TN, reactive soluble phosphorus (RSP) and total phosphorus (TP) of the bottom water in summer, TEMP, pH, SAL, DSi, DO, TURB, CODMn, particulate organic carbon (POC), ammonia nitrogen (AMN), NNN, TN and fecal coliform (FC) of the surface water in fall, TEMP, pH, SAL, DSi, H2S, TURB, CODMn, AMN, NNN and TN of the bottom water in fall commonly showed up as the most significant parameters and the large concentration differences between high and low tides. At other stations, the significant parameters showed differently according to the spatial and temporal variations of mixing pattern in the bay. In fact, there is no estuary that always maintains steady-state flow conditions. The mixing regime of an estuary might be changed at any time from linear to non-linear, due to the change of flushing time according to the combination of hydrogeometric properties, inflow of freshwater and tidal action, And furthermore the change of end-member conditions due to the internal sinks and sources makes the occurrence of concentration difference inevitable. Therefore, when investigating the water quality of the estuary, it is necessary to take a sampling method considering the tide to obtain average water quality data.

Keywords: conservative mixing, end-member, factor analysis, flushing time, high and low tide, latent variables, non-conservative mixing, slack-tide sampling, spatial and temporal variations, surface and bottom water

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Authors: Emilia Pietiläinen, Heikki Kyröläinen, Tommi Vasankari, Matti Santtila, Tiina Luukkaala, Kai Parkkola

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Working in the military sets special demands on physical fitness, however, reduced physical activity levels among employees in the Finnish Defence Forces (FDF), a trend also being seen among the working-age population in Finland, is leading to reduced physical fitness levels and increased risk of cardiovascular and metabolic diseases, something which also increases human resource costs. Therefore, the aim of the present study was to develop an eHealth intervention using accelerometer- smartphone app feedback technique, telephone counseling and physical activity recordings to increase physical activity of the personnel and thereby improve their health. Specific aims were to reduce stress, improve quality of sleep and mental and physical performance, ability to work and reduce sick leave absences. Employees from six military brigades around Finland were invited to participate in the study, and finally, 260 voluntary participants were included (66 women, 194 men). The participants were randomized into intervention (156) and control groups (104). The eHealth intervention group used accelerometers measuring daily physical activity and duration and quality of sleep for six months. The accelerometers transmitted the data to smartphone apps while giving feedback about daily physical activity and sleep. The intervention group participants were also encouraged to exercise for two hours a week during working hours, a benefit that was already offered to employees following existing FDF guidelines. To separate the exercise done during working hours from the accelerometer data, the intervention group marked this exercise into an exercise diary. The intervention group also participated in telephone counseling about their physical activity. On the other hand, the control group participants continued with their normal exercise routine without the accelerometer and feedback. They could utilize the benefit of being able to exercise during working hours, but they were not separately encouraged for it, nor was the exercise diary used. The participants were measured at baseline, after the entire intervention period, and six months after the end of the entire intervention. The measurements included accelerometer recordings, biochemical laboratory tests, body composition measurements, physical fitness tests, and a wide questionnaire focusing on sociodemographic factors, physical activity and health. In terms of results, the primary indicators of effectiveness are increased physical activity and fitness, improved health status, and reduced sick leave absences. The evaluation of the present scientific reach is based on the data collected during the baseline measurements. Maintenance of the studied outcomes is assessed by comparing the results of the control group measured at the baseline and a year follow-up. Results of the study are not yet available but will be presented at the conference. The present findings will help to develop an easy and cost-effective model to support the health and working capability of employees in the military and other workplaces.

Keywords: accelerometer, health, mobile applications, physical activity, physical performance

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Authors: Aline Woine, Moïra Mikolajczak, Virginie Dardier, Isabelle Roskam

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Background information: Becoming a parent is said to be the happiest event one can ever experience in one’s life. This popular (and almost absolute) truth–which no reasonable and decent human being would ever dare question on pain of being singled out as a bad parent–contrasts with the nuances that reality offers. Indeed, while many parents do thrive in their parenting role, some others falter and become progressively overwhelmed by their parenting role, ineluctably caught in a spiral of exhaustion. Parental burnout (henceforth PB) sets in when parental demands (stressors) exceed parental resources. While it is now generally acknowledged that PB affects the parent’s behavior in terms of neglect and violence toward their offspring, little is known about the impact that the syndrome might have on the children’s internalized (anxious and depressive symptoms, somatic complaints, etc.) and/or externalized (irritability, violence, aggressiveness, conduct disorder, oppositional disorder, etc.) behaviors. Furthermore, at the time of writing, to our best knowledge, no research has yet tested the reverse effect, namely, that of the child's internalized and/or externalized behaviors on the onset and/or maintenance of parental burnout symptoms. Goals and hypotheses: The present pioneering research proposes to fill an important gap in the existing literature related to PB by investigating the bidirectional effect between PB and the child’s internalized and/or externalized behaviors. Relying on a cross-lagged longitudinal study with three waves of data collection (4 months apart), our study tests a transactional model with bidirectional and recursive relations between observed variables and at the three waves, as well as autoregressive paths and cross-sectional correlations. Methods: As we write this, wave-two data are being collected via Qualtrics, and we expect a final sample of about 600 participants composed of French-speaking (snowball sample) and English-speaking (Prolific sample) parents. Structural equation modeling is employed using Stata version 17. In order to retain as much statistical power as possible, we use all available data and therefore apply the maximum likelihood with a missing value (mlmv) as the method of estimation to compute the parameter estimates. To limit (in so far is possible) the shared method variance bias in the evaluation of the child’s behavior, the study relies on a multi-informant evaluation approach. Expected results: We expect our three-wave longitudinal study to show that PB symptoms (measured at T1) raise the occurrence/intensity of the child’s externalized and/or internalized behaviors (measured at T2 and T3). We further expect the child’s occurrence/intensity of externalized and/or internalized behaviors (measured at T1) to augment the risk for PB (measured at T2 and T3). Conclusion: Should our hypotheses be confirmed, our results will make an important contribution to the understanding of both PB and children’s behavioral issues, thereby opening interesting theoretical and clinical avenues.

Keywords: exhaustion, structural equation modeling, cross-lagged longitudinal study, violence and neglect, child-parent relationship

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Elaine Y. L. Ng

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Elizabeth Gilbert’s (2006) biography Eat, Pray, Love describes her travels to Italy, India, and Indonesia after a painful divorce. The author’s experiences with love, loss, search for happiness, and meaning have resonated with a huge readership. As regards the translation of Gilbert’s (2006) Eat, Pray, Love into Chinese, it was first translated by a Taiwanese translator He Pei-Hua and published in Taiwan in 2007 by Make Boluo Wenhua Chubanshe with the fairly catching title “Enjoy! Traveling Alone.” The same translation was translocated to China, republished in simplified Chinese characters by Shanxi Shifan Daxue Chubanshe in 2008 and renamed in China, entitled “To Be a Girl for the Whole Life.” Later on, the same translation in simplified Chinese characters was reprinted by Hunan Wenyi Chubanshe in 2013. This study employs Munday’s (2002) systemic model for descriptive translation studies to investigate the translation of Gilbert’s (2006) Eat, Pray, Love into Chinese by the Taiwanese translator Hu Pei-Hua. It employs an interdisciplinary approach, combining systemic functional linguistics and corpus stylistics with sociohistorical research within a descriptive framework to study the translator’s discursive presence in the text. The research consists of three phases. The first phase is to locate the target text within its socio-cultural context. The target-text context concerning the para-texts, readers’ responses, and the publishers’ orientation will be explored. The second phase is to compare the source text and the target text for the categorization of translation shifts by using the methodological tools of systemic functional linguistics and corpus stylistics. The investigation concerns the rendering of mental clauses and speech and thought presentation. The final phase is an explanation of the causes of translation shifts. The linguistic findings are related to the extra-textual information collected in an effort to ascertain the motivations behind the translator’s choices. There exist sets of possible factors that may have contributed to shaping the textual features of the given translation within a specific socio-cultural context. The study finds that the translator generally reproduces the mental clauses and speech and thought presentation closely according to the original. Nevertheless, the language of the translation has been widely criticized to be unidiomatic and stiff, losing the elegance of the original. In addition, the several Chinese translations of the given text produced by one Taiwanese and two Chinese publishers are basically the same. They are repackaged slightly differently, mainly with the change of the book cover and its captions for each version. By relating the textual findings to the extra-textual data of the study, it is argued that the popularity of the Chinese translation of Gilbert’s (2006) Eat, Pray, Love may not be attributed to the quality of the translation. Instead, it may have to do with the way the work is promoted strategically by the social media manipulated by the four e-bookstores promoting and selling the book online in China.

Keywords: chinese translation of eat pray love, corpus stylistics, motivations for translation shifts, systemic approach to translation studies

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Authors: Sukhvinder Kaur, Ashok Agarwal

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Background: For the first time in 2009, India was able to generate estimates of HIV incidence (the number of new HIV infections per year). Analysis of epidemic projections helped in revealing that the number of new annual HIV infections in India had declined by more than 50% during the last decade (GOI Ministry of Health and Family Welfare, 2010). Then, National AIDS Control Organisation (NACO) planned to scale up its efforts in generating projections through epidemiological analysis and modelling by taking recent available sources of evidence such as HIV Sentinel Surveillance (HSS), India Census data and other critical data sets. Recently, NACO generated current round of HIV estimates-2012 through globally recommended tool “Spectrum Software” and came out with the estimates for adult HIV prevalence, annual new infections, number of people living with HIV, AIDS-related deaths and treatment needs. State level prevalence and incidence projections produced were used to project consequences of the epidemic in spectrum. In presence of HIV estimates generated at state level in India by NACO, USIAD funded PIPPSE project under the leadership of NACO undertook the estimations and projections to district level using same Spectrum software. In 2011, adult HIV prevalence in one of the high prevalent States, Maharashtra was 0.42% ahead of the national average of 0.27%. Considering the heterogeneity of HIV epidemic between districts, two districts of Maharashtra – Thane and Mumbai were selected to estimate and project the number of People-Living-with-HIV/AIDS (PLHIV), HIV-prevalence among adults and annual new HIV infections till 2017. Methodology: Inputs in spectrum included demographic data from Census of India since 1980 and sample registration system, programmatic data on ‘Alive and on ART (adult and children)’,‘Mother-Baby pairs under PPTCT’ and ‘High Risk Group (HRG)-size mapping estimates’, surveillance data from various rounds of HSS, National Family Health Survey–III, Integrated Biological and Behavioural Assessment and Behavioural Sentinel Surveillance. Major Findings: Assuming current programmatic interventions in these districts, an estimated decrease of 12% points in Thane and 31% points in Mumbai among new infections in HRGs and migrants is observed from 2011 by 2017. Conclusions: Project also validated decrease in HIV new infection among one of the high risk groups-FSWs using program cohort data since 2012 to 2016. Though there is a decrease in HIV prevalence and new infections in Thane and Mumbai, further decrease is possible if appropriate programme response, strategies and interventions are envisaged for specific target groups based on this evidence. Moreover, evidence need to be validated by other estimation/modelling techniques; and evidence can be generated for other districts of the state, where HIV prevalence is high and reliable data sources are available, to understand the epidemic within the local context.

Keywords: HIV sentinel surveillance, high risk groups, projections, new infections

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Authors: Paulina Clara Appiah, Kofi Issah, Timothy Letsa, Kennedy Nartey, Amanua Chinbuah, Adoma Dwomo-Fokuo, Jacqeline G. Asibey

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Background: The Every Newborn Action Plan provides evidence–based interventions to end preventable deaths in high burden countries. Brong Ahafo Region is one of ten regions in Ghana with less than half of its district hospitals having sick newborn units. Facility-based neonatal care is not prioritized and under-funded, and there is also inadequate knowledge and competence to manage the sick. The aim of this intervention was to make available in–patient care for sick newborns in all 19 district hospitals through the strengthening of facility-based systems. Methods: With the development and dissemination of the National Newborn Strategy and Action Plan 2014-2018, the country was able to attract PATH which provided the region with basic resuscitation equipment, supported hospital providers’ capacity building in Helping Babies Breathe, Essential Care of Every Baby, Infection Prevention and Management and held a symposia on managing the sick newborn. Newborn advocacy was promoted through newborn champions at the facility and community levels. Hospital management was then able to mobilize resources from communities, corporate organizations and from internally generated funds; created or expanded sick newborn care units and provided essential medicines and equipment. Kangaroo Mother Care was initiated in 6 hospitals. Pediatric specialist outreach services initiated comprised telephone consultations, teaching ward rounds and participating in perinatal death audits meetings. Newborn data capture and management was improved through the provision and training on the use of standard registers provided from the national level. Results: From February 2015 to November 2017, hospitals with sick newborn units increased from 7 to 19 (37%-100%). 180 pieces each of newborn ventilation bags and masks size 0, 1 and penguin suction bulbs were distributed to the hospitals, in addition to 20 newborn mannequin sets and 90 small clinical reminder posters. 802 providers (96.9%) were trained in resuscitation, of which 96% were successfully followed up in 6 weeks, 91% in 6 months and 80% in 12 months post-training. 53 clinicians (65%) were trained and mentored to manage sick newborns. 56 specialist teaching ward rounds were conducted. Data completeness improved from 92.6% - 99.9%. Availability of essential medicines improved from 11% to 100%. Number of hospital cots increased from 116 to 248 (214%). Cot occupancy rate increased from 57.4% to 92.5%. Hospitals with phototherapy equipment increased from 0 to 12 (63%). Hospitals with incubators increased from 1 to 12 (5%-63%). Newborn deaths among admissions reduced from 6.3% to 5.4%. Conclusion: Access to in-patient care increased significantly. Newborn advocacy successfully mobilized resources required for strengthening facility –based systems.

Keywords: facility-based systems, Ghana, in-patient care, newborn advocacy

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Authors: Jyoti Sahu, Vinay A. Juvekar

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Electrolytes are often used to bring about salting-in and salting-out of organic molecules and polymers (e.g. polyethylene glycols/proteins) from the aqueous solutions. For quantification of these phenomena, a thermodynamic model which can accurately predict activity coefficient of electrolyte as a function of temperature is needed. The thermodynamics models available in the literature contain a large number of empirical parameters. These parameters are estimated using lower/upper critical solution temperature of the solution in the electrolyte/organic molecule at different temperatures. Since the number of parameters is large, inaccuracy can bethe creep in during their estimation, which can affect the reliability of prediction beyond the range in which these parameters are estimated. Cloud point of solution is related to its free energy through temperature and composition derivative. Hence, the Cloud point measurement can be used for accurate estimation of the temperature and composition dependence of parameters in the model for free energy. Hence, if we use a two pronged procedure in which we first use cloud point of solution to estimate some of the parameters of the thermodynamic model and determine the rest using osmotic coefficient data, we gain on two counts. First, since the parameters, estimated in each of the two steps, are fewer, we achieve higher accuracy of estimation. The second and more important gain is that the resulting model parameters are more sensitive to temperature. This is crucial when we wish to use the model outside temperatures window within which the parameter estimation is sought. The focus of the present work is to prove this proposition. We have used electrolyte (NaCl/Na2CO3)-water-organic molecule (Iso-propanol/ethanol) as the model system. The model of Robinson-Stokes-Glukauf is modified by incorporating the temperature dependent Flory-Huggins interaction parameters. The Helmholtz free energy expression contains, in addition to electrostatic and translational entropic contributions, three Flory-Huggins pairwise interaction contributions viz., and (w-water, p-polymer, s-salt). These parameters depend both on temperature and concentrations. The concentration dependence is expressed in the form of a quadratic expression involving the volume fractions of the interacting species. The temperature dependence is expressed in the form .To obtain the temperature-dependent interaction parameters for organic molecule-water and electrolyte-water systems, Critical solution temperature of electrolyte -water-organic molecules is measured using cloud point measuring apparatus The temperature and composition dependent interaction parameters for electrolyte-water-organic molecule are estimated through measurement of cloud point of solution. The model is used to estimate critical solution temperature (CST) of electrolyte water-organic molecules solution. We have experimentally determined the critical solution temperature of different compositions of electrolyte-water-organic molecule solution and compared the results with the estimates based on our model. The two sets of values show good agreement. On the other hand when only osmotic coefficients are used for estimation of the free energy model, CST predicted using the resulting model show poor agreement with the experiments. Thus, the importance of the CST data in the estimation of parameters of the thermodynamic model is confirmed through this work.

Keywords: concentrated electrolytes, Debye-Hückel theory, interaction parameters, Robinson-Stokes-Glueckauf model, Flory-Huggins model, critical solution temperature

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Authors: Komal Rathore, Kiesha Pierre, Kyle Cogswell, Aaron Driscoll, Andres Tejada Martinez, Gita Iranipour, Luke Mulford, Aydin Sunol

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Modeling of Biological Wastewater Treatment Plants requires several parameters for kinetic rate expressions, thermo-physical properties, and hydrodynamic behavior. The kinetics and associated mechanisms become complex due to several biological processes taking place in wastewater treatment plants at varying times and spatial scales. A dynamic process model that incorporated the complex model for activated sludge kinetics was developed using the BioWin software platform for an Advanced Wastewater Treatment Plant in Valrico, Florida. Due to the extensive number of tunable parameters, an experimental design was employed for judicious selection of the most influential parameter sets and their bounds. The model was tuned using both the influent and effluent plant data to reconcile and rectify the forecasted results from the BioWin Model. Amount of mixed liquor suspended solids in the oxidation ditch, aeration rates and recycle rates were adjusted accordingly. The experimental analysis and plant SCADA data were used to predict influent wastewater rates and composition profiles as a function of time for extended periods. The lumped dynamic model development process was coupled with Computational Fluid Dynamics (CFD) modeling of the key units such as oxidation ditches in the plant. Several CFD models that incorporate the nitrification-denitrification kinetics, as well as, hydrodynamics was developed and being tested using ANSYS Fluent software platform. These realistic and verified models developed using BioWin and ANSYS were used to plan beforehand the operating policies and control strategies for the biological wastewater plant accordingly that further allows regulatory compliance at minimum operational cost. These models, with a little bit of tuning, can be used for other biological wastewater treatment plants as well. The BioWin model mimics the existing performance of the Valrico Plant which allowed the operators and engineers to predict effluent behavior and take control actions to meet the discharge limits of the plant. Also, with the help of this model, we were able to find out the key kinetic and stoichiometric parameters which are significantly more important for modeling of biological wastewater treatment plants. One of the other important findings from this model were the effects of mixed liquor suspended solids and recycle ratios on the effluent concentration of various parameters such as total nitrogen, ammonia, nitrate, nitrite, etc. The ANSYS model allowed the abstraction of information such as the formation of dead zones increases through the length of the oxidation ditches as compared to near the aerators. These profiles were also very useful in studying the behavior of mixing patterns, effect of aerator speed, and use of baffles which in turn helps in optimizing the plant performance.

Keywords: computational fluid dynamics, flow-sheet simulation, kinetic modeling, process dynamics

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Authors: Hanan Begali, Shahi Dost, Annett Ziegler, Markus Cornberg, Maria-Esther Vidal, Anke R. M. Kraft

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Chronic hepatitis B virus (HBV) infection can be treated with nucleot(s)ide analog (NA), for example, which inhibits HBV replication. However, they have hardly any influence on the functional cure of HBV, which is defined by hepatitis B surface antigen (HBsAg) loss. NA needs to be taken life-long, which is not available for all patients worldwide. Additionally, NA-treated patients are still at risk of developing cirrhosis, liver failure, or hepatocellular carcinoma (HCC). Although each patient has the same components of the immune system, immune responses vary between patients. Therefore, a deeper understanding of the immune response against HBV in different patients is necessary to understand the parameters leading to HBV cure and to use this knowledge to optimize HBV therapies. This requires seamless integration of an enormous amount of diverse and fine-grained data from viral markers, e.g., hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg). The data integration system relies on the assumption that profiling human immune systems requires the analysis of various variables (e.g., demographic data, treatments, pre-existing conditions, immune cell response, or HLA-typing) rather than only one. However, the values of these variables are collected independently. They are presented in a myriad of formats, e.g., excel files, textual descriptions, lab book notes, and images of flow cytometry dot plots. Additionally, patients can be identified differently in these analyses. This heterogeneity complicates the integration of variables, as data management techniques are needed to create a unified view in which individual formats and identifiers are transparent when profiling the human immune systems. The proposed study (HBsRE) aims at integrating heterogeneous data sets of 87 chronically HBV-infected patients, e.g., clinical data, immune cell response, and HLA-typing, with knowledge encoded in biomedical ontologies and open-source databases into a knowledge-driven framework. This new technique enables us to harmonize and standardize heterogeneous datasets in the defined modeling of the data integration system, which will be evaluated in the knowledge graph (KG). KGs are data structures that represent the knowledge and data as factual statements using a graph data model. Finally, the analytic data model will be applied on top of KG in order to develop a deeper understanding of the immune profiles among various patients and to evaluate factors playing a role in a holistic profile of patients with HBsAg level loss. Additionally, our objective is to utilize this unified approach to stratify patients for new effective treatments. This study is developed in the context of the project “Transforming big data into knowledge: for deep immune profiling in vaccination, infectious diseases, and transplantation (ImProVIT)”, which is a multidisciplinary team composed of computer scientists, infection biologists, and immunologists.

Keywords: chronic hepatitis B infection, immune response, knowledge graphs, ontology

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Authors: Ife Elegbeleye, Nnditshedzeni Eric, Regina Maphanga, Femi Elegbeleye, Femi Agunbiade

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The global potential of other renewable energy sources such as wind, hydroelectric, bio-mass, and geothermal is estimated to be approximately 13 %, with hydroelectricity constituting a larger percentage. Sunlight provides by far the largest of all carbon-neutral energy sources. More energy from the sunlight strikes the Earth in one hour (4.3 × 1020 J) than all the energy consumed on the planet in a year (4.1 × 1020 J), hence, solar energy remains the most abundant clean, renewable energy resources for mankind. Photovoltaic (PV) devices such as silicon solar cells, dye sensitized solar cells are utilized for harnessing solar energy. Polyene-diphenylaniline organic molecules are important sets of molecules that has stirred many research interest as photosensitizers in TiO₂ semiconductor-based dye sensitized solar cells (DSSCs). The advantages of organic dye molecule over metal-based complexes are higher extinction coefficient, moderate cost, good environmental compatibility, and electrochemical properties. The polyene-diphenylaniline organic dyes with basic configuration of donor-π-acceptor are affordable, easy to synthesize and possess chemical structures that can easily be modified to optimize their photocatalytic and spectral properties. The enormous interest in polyene-diphenylaniline dyes as photosensitizers is due to their fascinating spectral properties which include visible light to near infra-red-light absorption. In this work, density functional theory approach via GPAW software, Avogadro and ASE were employed to study the effect of methoxy functionalized group on the spectral properties of polyene-diphenylaniline dyes and their photons absorbing characteristics in the visible region to near infrared region of the solar spectrum. Our results showed that the two-phenyl based complexes D5 and D7 exhibits maximum absorption peaks at 750 nm and 850 nm, while D9 and D11 with methoxy group shows maximum absorption peak at 800 nm and 900 nm respectively. The highest absorption wavelength is notable for D9 and D11 containing additional polyene and methoxy groups. Also, D9 and D11 chromophores with the methoxy group shows lower energy gap of 0.98 and 0.85 respectively than the corresponding D5 and D7 dyes complexes with energy gap of 1.32 and 1.08. The analysis of their electron injection kinetics ∆Ginject into the band gap of TiO₂ shows that D9 and D11 with the methoxy group has higher electron injection kinetics of -2.070 and -2.030 than the corresponding polyene-diphenylaniline complexes without the addition of polyene group with ∆Ginject values of -2.820 and -2.130 respectively. Our findings suggest that the addition of functionalized group as an extension of the organic complexes results in higher light harvesting efficiencies and bathochromic shift of the absorption spectra to higher wavelength which suggest higher current densities and open circuit voltage in DSSCs. The study suggests that the photocatalytic properties of organic chromophores/complexes with donor-π-acceptor configuration can be enhanced by the addition of functionalized groups.

Keywords: renewable energy resource, solar energy, dye sensitized solar cells, polyene-diphenylaniline organic chromophores

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Authors: B. K. Kanungo, Monika Thakur, Minati Baral

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8-hydroxyquinoline, (8HQ), experiences a renaissance due to its utility as a building block in metallosupramolecular chemistry and its versatile use of its derivatives in various fields of analytical chemistry, materials science, and pharmaceutics. It forms stable complexes with a variety of metal ions. Assembly of more than one such unit to form a polydentate chelator enhances its coordinating ability and the related properties due to the chelate effect resulting in high stability constant. Keeping in view the above, a nonadentate chelator N-[3,5-bis(8-hydroxyquinoline-2-amido)cyclohexyl]-8-hydroxyquinoline-2-carboxamide, (TACH2OX), containing a central cis,cis-1,3,5-triaminocyclohexane appended to three 8-hydroxyquinoline at 2-position through amide linkage is developed, and its solution thermodynamics, photophysical and Density Functional Theory (DFT) studies were undertaken. The synthesis of TACH2OX was carried out by condensation of cis,cis-1,3,5-triaminocyclohexane, (TACH) with 8‐hydroxyquinoline‐2‐carboxylic acid. The brown colored solid has been fully characterized through melting point, infrared, nuclear magnetic resonance, electrospray ionization mass and electronic spectroscopy. In solution, TACH2OX forms protonated complexes below pH 3.4, which consecutively deprotonates to generate trinegative ion with the rise of pH. Nine protonation constants for the ligand were obtained that ranges between 2.26 to 7.28. The interaction of the chelator with two trivalent metal ion Fe3+ and Al3+ were studied in aqueous solution at 298 K. The metal-ligand formation constants (ML) obtained by potentiometric and spectrophotometric method agree with each other. The protonated and hydrolyzed species were also detected in the system. The in-silico studies of the ligand, as well as the complexes including their protonated and deprotonated species assessed by density functional theory technique, gave an accurate correlation with each observed properties such as the protonation constants, stability constants, infra-red, nmr, electronic absorption and emission spectral bands. The nature of electronic and emission spectral bands in terms of number and type were ascertained from time-dependent density functional theory study and the natural transition orbitals (NTO). The global reactivity indices parameters were used for comparison of the reactivity of the ligand and the complex molecules. The natural bonding orbital (NBO) analysis could successfully describe the structure and bonding of the metal-ligand complexes specifying the percentage of contribution in atomic orbitals in the creation of molecular orbitals. The obtained high value of metal-ligand formation constants indicates that the newly synthesized chelator is a very powerful synthetic chelator. The minimum energy molecular modeling structure of the ligand suggests that the ligand, TACH2OX, in a tripodal fashion firmly coordinates to the metal ion as hexa-coordinated chelate displaying distorted octahedral geometry by binding through three sets of N, O- donor atoms, present in each pendant arm of the central tris-cyclohexaneamine tripod.

Keywords: complexes, DFT, formation constant, TACH2OX

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Authors: Gideon Nyuimbe Gasu

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Sub Saharan Africa is at a critical point, experiencing rapid population growth, particularly in urban areas and young growing force. At the same time, the growing risk of catastrophic global climate change threatens to weaken food production system, increase intensity and frequency of drought, flood, and fires and undermine gains on development and poverty reduction. Although the region has the lowest per capital greenhouse gas emission level in the world, it will need to join global efforts to address climate change, including action to avoid significant increases and to encourage a green economy. Thus, there is a need for the concept of 'greening the economy' as was prescribed at Rio Summit of 1992. Renewable energy is one of the criterions to achieve this laudable goal of maintaining a green economy. There is need to address climate change while facilitating continued economic growth and social progress as energy today is critical to economic growth. Fossil fuels remain the major contributor of greenhouse gas emission. Thus, cleaner technologies such as carbon capture storage, renewable energy have emerged to be commercially competitive. This paper sets out to examine how to achieve a low carbon economy with minimal emission of carbon dioxide and other greenhouse gases which is one of the outcomes of implementing a green economy. Also, the paper examines the different renewable energy sources such as nuclear, wind, hydro, biofuel, and solar voltaic as a panacea to the looming climate change menace. Finally, the paper assesses the different renewable energy and energy efficiency as a propeller to generating new sources of income and jobs and in turn reduces carbon emission. The research shall engage qualitative, evaluative and comparative methods. The research will employ both primary and secondary sources of information. The primary sources of information shall be drawn from the sub Saharan African region and the global environmental organizations, energy legislation, policies and related industries and the judicial processes. The secondary sources will be made up of some books, journal articles, commentaries, discussions, observations, explanations, expositions, suggestions, prescriptions and other material sourced from the internet on renewable energy as a panacea to climate change. All information obtained from these sources will be subject to content analysis. The research result will show that the entire planet is warming as a result of the activities of mankind which is clear evidence that the current development is fundamentally unsustainable. Equally, the study will reveal that a low carbon development pathway in the sub Saharan African region should be embraced to minimize emission of greenhouse gases such as using renewable energy rather than coal, oil, and gas. The study concludes that until adequate strategies are devised towards the use of renewable energy the region will continue to add and worsen the current climate change menace and other adverse environmental conditions.

Keywords: carbon dioxide, climate change, legislation/law, renewable energy

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Authors: Justyna P. Majewska, Szymon M. Truskolaski

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The growing importance of digitalized services in the so-called new economy, including the e-sports industry, can be observed recently. Various demographic or technological changes lead consumers to modify their needs, not regarding the services themselves but the method of their application (attracting customers, forms of payment, new content, etc.). In the case of leisure-related to competitive spectating activities, there is a growing need to participate in events whose content is not sports competitions but computer games challenge – e-sport. The literature in this area so far focuses on determining the number of e-sport fans with elements of a simple statistical description (mainly concerning demographic characteristics such as age, gender, place of residence). Meanwhile, the development of the industry is influenced by a combination of many different, intertwined demographic, personality and psychosocial characteristics of customers, as well as the characteristics of their environment. Therefore, there is a need for a deeper recognition of the determinants of the behavioral patterns upon selecting digitalized services by customers, which, in the absence of available large data sets, can be achieved by using econometric simulations – multi-agent modeling. The cognitive aim of the study is to reveal internal and external determinants of behavioral patterns of customers taking into account various variants of economic development (the pace of digitization and technological development, socio-demographic changes, etc.). In the paper, an agent-based model with heterogeneous agents (characteristics of customers themselves and their environment) was developed, which allowed identifying a three-stage development scenario: i) initial interest, ii) standardization, and iii) full professionalization. The probabilities regarding the transition process were estimated using the Method of Simulated Moments. The estimation of the agent-based model parameters and sensitivity analysis reveals crucial factors that have driven a rising trend in e-sport spectating and, in a wider perspective, the development of digitalized services. Among the psychosocial characteristics of customers, they are the level of familiarization with the rules of games as well as sports disciplines, active and passive participation history and individual perception of challenging activities. Environmental factors include general reception of games, number and level of recognition of community builders and the level of technological development of streaming as well as community building platforms. However, the crucial factor underlying the good predictive power of the model is the level of professionalization. While in the initial interest phase, the entry barriers for new customers are high. They decrease during the phase of standardization and increase again in the phase of full professionalization when new customers perceive participation history inaccessible. In this case, they are prone to switch to new methods of service application – in the case of e-sport vs. sports to new content and more modern methods of its delivery. In a wider context, the findings in the paper support the idea of a life cycle of services regarding methods of their application from “traditional” to digitalized.

Keywords: agent-based modeling, digitalized services, e-sport, spectators motives

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Authors: Md. Wasiul Islam, Md. Jamius Shams Sowrov

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The Sundarbans is the largest single tract of mangrove forest in the world. This is located in the southwest corner of Bangladesh. This is a unique ecosystem which is a great breeding and nursing ground for a great biodiversity. It supports the livelihood of about 3.5 million coastal dwellers and also protects the coastal belt and inland areas from various natural calamities. Historically, the management of the Sundarbans was controlled by the Bangladesh Forest Department following top-down approach without the involvement of local communities. Such fence and fining-based blue-print approach was not effective to protect the forest which caused Sundarbans to degrade severely in the recent past. Fifty percent of the total tree cover has been lost in the last 30 years. Therefore, local multi-stakeholder based bottom-up co-management approach was introduced at some of the parts of the Sundarbans in 2006 to improve the biodiversity status by enhancing the protection level of the forest. Various co-management organizations were introduced under co-management approach where the local community people could actively involve in various activities related to the management and welfare of the Sundarbans including the decision-making process to achieve the goal. From this backdrop, the objective of the study was to assess the performance of co-management organizations to facilitate sustainable management of the Sundarbans mangrove forests. The qualitative study followed face-to-face interview to collect data using two sets of semi-structured questionnaires. A total of 40 respondents participated in the research that was from eight villagers under two forest ranges. 32 representatives from the local communities as well as 8 official representatives involved in co-management approach were interviewed using snowball sampling technique. The study shows that the co-management approach improved governance system of the Sundarbans through active participation of the local community people and their interactions with the officials via the platform of co-management organizations. It facilitated accountability and transparency system to some extent through following some formal and informal rules and regulations. It also improved the power structure of the management process by fostering local empowerment process particularly the women. Moreover, people were able to learn from their interactions with and within the co-management organizations as well as interventions improved environmental awareness and promoted social learning. The respondents considered good governance as the most important factor for achieving the goal of sustainable management and biodiversity conservation of the Sundarbans. The success of co-management planning process also depends on the active and functional participation of different stakeholders including the local communities where co-management organizations were considered as the most functional platform. However, the governance system was also facing various challenges which resulted in barriers to the sustainable management of the Sundarbans mangrove forest. But still there were some members involved in illegal forest operations and created obstacles against sustainable management of the Sundarbans. Respondents recommended greater patronization from the government, financial and logistic incentives for alternative income generation opportunities with effective participatory monitoring and evaluation system to improve sustainable management of the Sundarbans.

Keywords: Bangladesh, co-management approach, co-management organizations, governance, Sundarbans, sustainable management

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Authors: Juhi Sah

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Habitat is characterized by the inter-dependency of environmental elements. Anthropocentric development approach is increasing our vulnerability towards natural hazards. Hence, manmade interventions should have a higher level of sensitivity towards the natural settings. Sensitivity towards the environment can be assessed by the behavior of the stakeholders involved. This led to the establishment of a hypothesis: there exists a legitimate relationship between the behavioral sciences, land use evolution and environment conservation, in the planning process. An attempt has been made to establish this relationship by reviewing the existing set of knowledge and case examples pertaining to the three disciplines under inquiry. Understanding the scarce & deteriorating nature of fresh-water reserves of earth and experimenting the above concept, a case study of a growing urban center's river flood plain is selected, in a developing economy, India. Cases of urban flooding in Chennai, Delhi and other mega cities of India, imposes a high risk on the unauthorized settlement, on the floodplains of the rivers. The issue addressed here is the encroachment of floodplains, through psychological enlightenment and modification through knowledge building. The reaction of an individual or society can be compared to a cognitive process. This study documents all the stakeholders' behavior and perception for their immediate natural environment (water body), and produce various land uses suitable along a river in an urban settlement as per different stakeholder's perceptions. To assess and induce morally responsible behavior in a community (small scale or large scale), tools of psychological inquiry is used for qualitative analysis. The analysis will deal with varied data sets from two sectors namely: River and its geology, Land use planning and regulation. Identification of a distinctive pattern in the built up growth, river ecology degradation, and human behavior, by handling large quantum of data from the diverse sector and comments on the availability of relevant data and its implications, has been done. Along the whole river stretch, condition and usage of its bank vary, hence stakeholder specific survey questionnaires have been prepared to accurately map the responses and habits of the rational inhabitants. A conceptual framework has been designed to move forward with the empirical analysis. The classical principle of virtues says "virtue of a human depends on its character" but another concept defines that the behavior or response is a derivative of situations and to bring about a behavioral change one needs to introduce a disruption in the situation/environment. Owing to the present trends, blindly following the results of data analytics and using it to construct policy, is not proving to be in favor of planned development and natural resource conservation. Thus behavioral assessment of the rational inhabitants of the planet is also required, as their activities and interests have a large impact on the earth's pre-set systems and its sustenance.

Keywords: behavioral assessment, flood plain encroachment, land use planning, river sustenance

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Gabriel Malgaresi, Sara Borazjani, Hadi Madani, Pavel Bedrikovetsky

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Suspension-Colloidal flow in porous media occurs in numerous engineering fields, such as industrial water treatment, the disposal of industrial wastes into aquifers with the propagation of contaminants and low salinity water injection into petroleum reservoirs. The main effects are particle mobilization and captured by the porous rock, which can cause pore plugging and permeability reduction which is known as formation damage. Various factors such as fluid salinity, pH, temperature, and rock properties affect particle detachment. Formation damage is unfavorable specifically near injection and production wells. One way to control formation damage is pre-treatment of the rock with nanoparticles. Adsorption of nanoparticles on fines and rock surfaces alters zeta-potential of the surfaces and enhances the attachment force between the rock and fine particles. The main objective of this study is to develop a two-stage mathematical model for (1) flow and adsorption of nanoparticles on the rock in the pre-treatment stage and (2) fines migration and permeability reduction during the water production after the pre-treatment. The model accounts for adsorption and desorption of nanoparticles, fines migration, and kinetics of particle capture. The system of equations allows for the exact solution. The non-self-similar wave-interaction problem was solved by the Method of Characteristics. The analytical model is new in two ways: First, it accounts for the specific boundary and initial condition describing the injection of nanoparticle and production from the pre-treated porous media; second, it contains the effect of nanoparticle sorption hysteresis. The derived analytical model contains explicit formulae for the concentration fronts along with pressure drop. The solution is used to determine the optimal injection concentration of nanoparticle to avoid formation damage. The mathematical model was validated via an innovative laboratory program. The laboratory study includes two sets of core-flood experiments: (1) production of water without nanoparticle pre-treatment; (2) pre-treatment of a similar core with nanoparticles followed by water production. Positively-charged Alumina nanoparticles with the average particle size of 100 nm were used for the rock pre-treatment. The core was saturated with the nanoparticles and then flushed with low salinity water; pressure drop across the core and the outlet fine concentration was monitored and used for model validation. The results of the analytical modeling showed a significant reduction in the fine outlet concentration and formation damage. This observation was in great agreement with the results of core-flood data. The exact solution accurately describes fines particle breakthroughs and evaluates the positive effect of nanoparticles in formation damage. We show that the adsorbed concentration of nanoparticle highly affects the permeability of the porous media. For the laboratory case presented, the reduction of permeability after 1 PVI production in the pre-treated scenario is 50% lower than the reference case. The main outcome of this study is to provide a validated mathematical model to evaluate the effect of nanoparticles on formation damage.

Keywords: nano-particles, formation damage, permeability, fines migration

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Authors: Abha Gupta, Deepak K. Mishra

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Food security issue in India has surrounded over availability and accessibility of cereal which is regarded as the only food group to check hunger and improve nutrition. Significance of fruits, vegetables, meat and other food products have totally been neglected given the fact that they provide essential nutrients to the body. There is a need to shift the emphasis from cereal-based approach to a more diverse diet so that aim of achieving food security may change from just reducing hunger to an overall health. This paper attempts to analyse how far dietary diversity level has been achieved across different socio-economic groups in India. For this purpose, present paper sets objectives to determine (a) percentage share of different food groups to total food expenditure and consumption by background characteristics (b) source of and preference for all food items and, (c) diversity of diet across socio-economic groups. A cross sectional survey covering 304 households selected through proportional stratified random sampling was conducted in six villages of Aligarh district of Uttar Pradesh, India. Information on amount of food consumed, source of consumption and expenditure on food (74 food items grouped into 10 major food groups) was collected with a recall period of seven days. Per capita per day food consumption/expenditure was calculated through dividing consumption/expenditure by household size and number seven. Food variety score was estimated by giving 0 values to those food groups/items which had not been eaten and 1 to those which had been taken by households in last seven days. Addition of all food group/item score gave result of food variety score. Diversity of diet was computed using Herfindahl-Hirschman index. Findings of the paper show that cereal, milk, roots and tuber food groups contribute a major share in total consumption/expenditure. Consumption of these food groups vary across socio-economic groups whereas fruit, vegetables, meat and other food consumption remain low and same. Estimation of dietary diversity show higher concentration of diet due to higher consumption of cereals, milk, root and tuber products and dietary diversity slightly varies across background groups. Muslims, Scheduled caste, small farmers, lower income class, food insecure, below poverty line and labour families show higher concentration of diet as compared to their counterpart groups. These groups also evince lower mean intake of number of food item in a week due to poor economic constraints and resultant lower accessibility to number of expensive food items. Results advocate to make a shift from cereal based diet to dietary diversity which not only includes cereal and milk products but also nutrition rich food items such as fruits, vegetables, meat and other products. Integrating a dietary diversity approach in food security programmes of the country would help to achieve nutrition security as hidden hunger is widespread among the Indian population.

Keywords: dietary diversity, food Security, India, socio-economic groups

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Authors: Anna Carolina De Paula Sermarini, Rodrigo Flora Calili

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Energy Efficiency (EE) needs investments, new technologies, greater awareness and management on the side of citizens and organizations, and more planning. However, this issue is usually remembered and discussed only in moments of energy crises, and opportunities are missed to take better advantage of the potential of EE in the various sectors of the economy. In addition, there is little concern about the subject among the less favored classes, especially in low-income communities. Accordingly, this article presents suggestions for public policies that aim to increase EE for low-income housing and communities based on international and national experiences. After reviewing the literature, eight policies were listed, and to evaluate them; a multicriteria decision model was developed using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods, combined with fuzzy logic. Nine experts analyzed the policies according to 9 criteria: economic impact, social impact, environmental impact, previous experience, the difficulty of implementation, possibility/ease of monitoring and evaluating the policies, expected impact, political risks, and public governance and sustainability of the sector. The results found in order of preference are (i) Incentive program for equipment replacement; (ii) Community awareness program; (iii) EE Program with a greater focus on low income; (iv) Staggered and compulsory certification of social interest buildings; (v) Programs for the expansion of smart metering, energy monitoring and digitalization; (vi) Financing program for construction and retrofitting of houses with the emphasis on EE; (vii) Income tax deduction for investment in EE projects in low-income households made by companies; (viii) White certificates of energy for low-income. First, the policy of equipment substitution has been employed in Brazil and the world and has proven effective in promoting EE. For implementation, efforts are needed from the federal and state governments, which can encourage companies to reduce prices, and provide some type of aid for the purchase of such equipment. In second place is the community awareness program, promoting socio-educational actions on EE concepts and with energy conservation tips. This policy is simple to implement and has already been used by many distribution utilities in Brazil. It can be carried out through bids defined by the government in specific areas, being executed by third sector companies with public and private resources. Third on the list is the proposal to continue the Energy Efficiency Program (which obliges electric energy companies to allocate resources for research in the area) by suggesting the return of the mandatory investment of 60% of the resources in projects for low income. It is also relatively simple to implement, requiring efforts by the federal government to make it mandatory, and on the part of the distributors, compliance is needed. The success of the suggestions depends on changes in the established rules and efforts from the interested parties. For future work, we suggest the development of pilot projects in low-income communities in Brazil and the application of other multicriteria decision support methods to compare the results obtained in this study.

Keywords: energy efficiency, low-income community, public policy, multicriteria decision making

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Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

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Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

Procedia PDF Downloads 162