Search results for: environmental features

Authors: Ebru Turgal, Beyza Doganay Erdogan

Abstract:

Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

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Authors: Forouzan Salehi Fergeni

Abstract:

Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

Procedia PDF Downloads 113

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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Authors: Zelalem Fantahun

Abstract:

Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: E. Osorio Schmied

Abstract:

Architects commonly attempt a depiction of organic forms when their works are inspired by nature, regardless of the building site. Nevertheless it is also possible to try matching structures with natural scenery, by applying a phenomenological approach in terms of spatial operations, regarding perceptions from nature through architectural aspects such as protection, views, and orientation. This method acknowledges a relationship between place and space, where intentions towards tangible facts then become design statements. Although spaces resulting from such a process may present an effective response to the environment, they can also offer further outcomes beyond the realm of form. The hypothesis is that, in addition to recognising a bond between architecture and nature, it is also plausible to associate such perceptions with the inner ambient of buildings, by analysing features such as daylight. The case study of a single-family house in a rainforest near Valdivia, Chilean Patagonia is presented, with the intention of addressing the above notions through a discussion of the actual effects of inhabiting a place by way of a series of insights, including a revision of diagrams and photographs that assist in understanding the implications of this design practice. In addition, figures based on post-occupancy behaviour and daylighting performance relate both architectural and environmental issues to a decision-making process motivated by the observation of nature.

Keywords: architecture, design statements, nature, perception

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Authors: Rahaf Suleiman Altallaa

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City planning involves making plans, organizing and dealing with the cities urban areas. It attempts to organize socio-spatial relationships at exceptional ranges of governance Urban planning offers the social, monetary and environmental effects of defining spatial obstacles and the influence on the spatial distribution of resources. The dreams and methods of reaching such dissemination vary extensively traditionally and geographically and are often challenged through traditional strategies that expose the political nature of application interventions and the bounds of technical know-how claims. Space, network, argument, and postcolonial debates address how present-day socio-spatial organization is formed, what needs to or should not trade, and the way it underscores whether or not a good plan will contribute to a given situation. Inside the absence of an agreed-upon technical justification for the planning exercise, the planning idea has a tendency to focus on normative processes, positioning making plans as an area for participatory democracy.

Keywords: environmental governance, environmental planning, environmental management, sustainable competitiveness, sustainability

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Authors: Ashique Mahmud, MD. Ataul Gani Osmani, Shoria Sharmin

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In the first quarter of the twenty-first century, the most substantial global concern is environmental contamination, and it has gained the prioritization of both the national and international community. Keeping in mind this crucial fact, this study conducted different statistical and econometrical methods to identify whether the gross national income of the country has a significant impact on electricity production from nonrenewable sources and different air pollutants like carbon dioxide, nitrous oxide, and methane emissions. Besides, the primary objective of this research was to analyze whether the environmental Kuznets curve hypothesis holds for the examined variables. After analyzing different statistical properties of the variables, this study came to the conclusion that the environmental Kuznets curve hypothesis holds for gross national income and carbon dioxide emission in Bangladesh in the short run as well as the long run. This study comes to this conclusion based on the findings of ordinary least square estimations, ARDL bound tests, short-run causality analysis, the Error Correction Model, and other pre-diagnostic and post-diagnostic tests that have been employed in the structural model. Moreover, this study wants to demonstrate that the outline of gross national income and carbon dioxide emissions is in its initial stage of development and will increase up to the optimal peak. The compositional effect will then force the emission to decrease, and the environmental quality will be restored in the long run.

Keywords: environmental Kuznets curve hypothesis, carbon dioxide emission in Bangladesh, gross national income in Bangladesh, autoregressive distributed lag model, granger causality, error correction model

Procedia PDF Downloads 133

Authors: Bencherif Kada

Abstract:

In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

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Authors: Ramona Zharfpeykan

Abstract:

The concept of sustainability is generally considered as a key topic in many countries, and sustainability reporting is becoming an important tool for companies to communicate their sustainability plans and performance to their stakeholders. There have been various studies on factors that may influence sustainability reporting in companies. This study examines the possible effect of some of the organisational factors on corporate sustainability reporting. The organisational factors included in this study are a company’s type (public or private), industry, and size as well as managers’ perception of the level of importance of indicators in reporting these indicators. A survey was conducted from 240 Australian and New Zealand companies in various industries. They were asked about their perception of the importance of sustainability indicators in their performance and if they report these indicators. The GRI indicators used to develop the survey. A multiple regression model was developed using reporting strategy score as dependent and type, size, industry categorisation, and managers’ perception of the level of importance of the GRI indicators as independent factors. The results show that among all the factors included in the model, size of a company and the perception of managers of the level of importance of environmental and labour practice indicators can affect the sustainability scores of these companies.

Keywords: sustainability reporting, global reporting initiative, sustainability reporting strategy, organisational features

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Authors: Nazanin Forouz

Abstract:

The textile industry faces increasing criticism due to its resource-intensive nature and the negative environmental and societal impacts associated with the manufacturing, use, and disposal of clothes. To address these concerns, there is a growing desire to transition towards a circular economy for textiles, implementing recycling concepts and technologies to protect resources, the environment, and people. While existing recycling processes have focused on chemical and mechanical reuse of textile fibers, bio-based processes have received limited attention beyond end-of-life composting. However, bio-based technologies hold great promise for circularizing the textile life cycle and reducing environmental impacts.

Keywords: textile industry, circular economy, bio-based processes, recycling, environmental impacts

Procedia PDF Downloads 79

Authors: Manuela Nayantara Jeyaraj, Senuri Sucharitharathna, Chathurika Senarath, Yasanthy Kanagaraj, Indraka Udayakumara

Abstract:

PostgreSQL is an Object Relational Database Management System (ORDBMS) that has been in existence for a while. Despite the superior features that it wraps and packages to manage database and data, the database community has not fully realized the importance and advantages of PostgreSQL. Hence, this research tends to focus on provisioning a better environment of development for PostgreSQL in order to induce the utilization and elucidate the importance of PostgreSQL. PostgreSQL is also known to be the world’s most elementary SQL-compliant open source ORDBMS. But, users have not yet resolved to PostgreSQL due to the facts that it is still under the layers and the complexity of its persistent textual environment for an introductory user. Simply stating this, there is a dire need to explicate an easy way of making the users comprehend the procedure and standards with which databases are created, tables and the relationships among them, manipulating queries and their flow based on conditions in PostgreSQL to help the community resolve to PostgreSQL at an augmented rate. Hence, this research under development within the context tends to initially identify the dominant features provided by PostgreSQL over its competitors. Following the identified merits, an analysis on why the database community holds a hesitance in migrating to PostgreSQL’s environment will be carried out. These will be modulated and tailored based on the scope and the constraints discovered. The resultant of the research proposes a system that will serve as a designing platform as well as a learning tool that will provide an interactive method of learning via a visual editor mode and incorporate a textual editor for well-versed users. The study is based on conjuring viable solutions that analyze a user’s cognitive perception in comprehending human computer interfaces and the behavioural processing of design elements. By providing a visually draggable and manipulative environment to work with Postgresql databases and table queries, it is expected to highlight the elementary features displayed by Postgresql over any other existent systems in order to grasp and disseminate the importance and simplicity offered by this to a hesitant user.

Keywords: cognition, database, PostgreSQL, text-editor, visual-editor

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Authors: Indira Sinha

Abstract:

According to the Oxford Advanced Learner's English Dictionary of Current English, environment is the complex of physical, chemical and biotic factors that act upon an organism or an ecological community and ultimately determines its form and survival. It is defined as conditions and circumstances which are affecting people's lives. The meaning of environmental degradation is the degradation of the environment through depletion of resources such as air, water and soil and the destruction of ecosystems and extinction of wildlife. Globalization is a significant feature of recent world history. The aim of this phenomenon is to integrate societies, economies and cultures through a common link of trading policies, technology and communication. Undoubtedly it has opened up the world economy at a very high speed but at the same time it has an adverse impact on the environment. The purpose of the present study is to investigate the impact of globalization on the environmental conditions. An overview of what the forces of globalization have in store for the environment with constructing large number of industries and destroying large forests lands will be given in this paper. The forces of globalization have created many serious environmental problems like high temperature, extinction of many species of plant and animal and outlet of poisonous chemicals from industries. The revelation of this study is that in case of developing economics these problems are more critical. In developing countries like India many factories are built with less environmental regulations, while developed economies maintain positive environmental practices. The present study is a micro level study which aims to employ a combination of theoretical, descriptive, empirical and analytical approach in addition to the time tested case method.

Keywords: globalization, trade policies, environmental degradation, developing economies, large industries

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Authors: Narjes Tahmasbi

Abstract:

Burnout is considered a work-related syndrome made from a person’s recognition of a gap between expecting success in professional performance and less satisfying reality. Teaching, as one of the most stressful jobs in the world, creates a sense of burnout that disturbs the competency of teachers’ personal and professional features, and it can be dangerous for themselves as well as their students. Recently, there has been growing research on the different effects of burnout; however, it is necessary to investigate the causes of this issue, especially in universities. This study aims to investigate the causes and recommended solutions to burnout in the teaching careers of university professors. The participants of the study were 5 EFL university professors from an institution of higher education in Shiraz, Iran. The current study used a qualitative design. Data were obtained from an interview with all participants. The participants were asked to answer 8 questions that were made through a semi-instructional interview. The results of the interview with the participants indicated that there were 4 main reasons that cause burnout in teachers: lack of student motivation, environmental factors, interpersonal problems, and financial problems. Recommended solutions were different according to the different personalities, creativity, and experiences of participants. The discussion of each of the causes of burnout represents how these categories cause burnout, and the discussion of each of the solutions shows how a teacher can handle burnout.

Keywords: burnout, EFL teachers, reasons, solutions, work-related syndrome

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

Abstract:

One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Prashansa Singh, Manjot Kaur, Rohit Bajaj

Abstract:

The proliferation of wireless sensor networks and Internet of Things (IoT) devices in the quickly changing digital landscape has highlighted the urgent need for strong security solutions that can handle these systems’ limited resources. A key solution to this problem is the emergence of ultralightweight security protocols, which provide strong security features while respecting the strict computational, energy, and memory constraints imposed on these kinds of devices. This in-depth analysis explores the field of ultralightweight security protocols, offering a thorough examination of their evolution, salient features, and the particular security issues they resolve. We carefully examine and contrast different protocols, pointing out their advantages and disadvantages as well as the compromises between resource limitations and security resilience. We also study these protocols’ application domains, including the Internet of Things, RFID systems, and wireless sensor networks, to name a few. In addition, the review highlights recent developments and advancements in the field, pointing out new trends and possible avenues for future research. This paper aims to be a useful resource for researchers, practitioners, and developers, guiding the design and implementation of safe, effective, and scalable systems in the Internet of Things era by providing a comprehensive overview of ultralightweight security protocols.

Keywords: wireless sensor network, machine-to-machine, MQTT broker, server, ultralightweight, TCP/IP

Procedia PDF Downloads 47

Authors: M. S. Belashov, A. V. Benin, Lin Hong, Sh. Sh. Nazarova, O. B. Sabirova, A. M. Uzdin, Lin Hong

Abstract:

The features of calculating structures for the action of weak earthquakes are analyzed. Earthquakes with a recurrence of 30 years and 50 years are considered. In the first case, the structure is to operate normally without damage after the earthquake. In the second case, damages are allowed that do not affect the possibility of the structure operation. Three issues are emphasized: setting elastic and damping characteristics of reinforced concrete, formalization of limit states, and combinations of loads. The dependence of damping on the reinforcement coefficient is estimated. When evaluating limit states, in addition to calculations for crack resistance and strength, a human factor, i.e., the possibility of panic among people, was considered. To avoid it, it is proposed to limit a floor-by-floor speed level in certain octave ranges. Proposals have been developed for estimating the coefficients of the combination of various loads with the seismic one. As an example, coefficients of combinations of seismic and ice loads are estimated. It is shown that for strong actions, the combination coefficients for different regions turn out to be close, while for weak actions, they may differ.

Keywords: weak earthquake, frequent earthquake, damage, limit state, reinforcement, crack resistance, strength resistance, a floor-by-floor velocity, combination coefficients

Procedia PDF Downloads 71

Authors: Bencherif Kada

Abstract:

In forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects, and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction and area of an object, etc.) and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants and bare soils. Texture attributes seem to provide no useful information while spatial attributes of shape, compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, biodiversity, shrublands

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Authors: Abdulkarim Yusuf

Abstract:

Motivation: A crucial but difficult goal for governments and policymakers in Nigeria in recent years has been the sustainability of economic growth. This goal must be accomplished by regulating or lowering greenhouse gas emissions, which calls for switching to a low- or zero-carbon production system. The lack of in-depth empirical studies on the environmental impact of socioeconomic variables on Nigeria and a number of unresolved issues from earlier research is what led to the current study. Objective: This study fills an important empirical gap by investigating the existence of an Environmental Kuznets Curve hypothesis and the long and short-run dynamic impact of socioeconomic variables on ecological sustainability in Nigeria. Data and method: Annual time series data covering the period 1980 to 2020 and the Autoregressive Distributed Lag technique in the presence of structural breaks were adopted for this study. Results: The empirical findings support the existence of the environmental Kuznets curve hypothesis for Nigeria in the long and short run. Energy consumption and total import exacerbate environmental deterioration in the long and short run, whereas total export improves environmental quality in the long and short run. Financial development, which contributed to a conspicuous decrease in the level of environmental destruction in the long run, escalated it in the short run. In contrast, urbanization caused a significant increase in environmental damage in the long run but motivated a decrease in biodiversity loss in the short run. Implications: The government, policymakers, and all energy stakeholders should take additional measures to ensure the implementation and diversification of energy sources to accommodate more renewable energy sources that emit less carbon in order to promote efficiency in Nigeria's production processes and lower carbon emissions. In order to promote the production and trade of environmentally friendly goods, they should also revise and strengthen environmental policies. With affordable, dependable, and sustainable energy use for higher productivity and inclusive growth, Nigeria will be able to achieve its long-term development goals of good health and wellbeing.

Keywords: economic growth, energy consumption, environmental degradation, environmental Kuznets curve, urbanization, Nigeria

Procedia PDF Downloads 36

Authors: Chanhyuck Jeon, Jongho Park, Jinwoong Choi, Sungnam Hong, Sun-Kyu Park

Abstract:

Many industries put emphasis on environmentally-friendliness as environmental problems are on the rise all over the world. Among themselves, the Modular Bridge research is going on. Also performing cross-section optimization and duration reducing, this research aims at developing the modular bridge with Environment-Friendliness and economic feasibility. However, the difficulty lies in verifying environmental effectiveness because there are no field applications of the modular bridge until now. Therefore, this thesis is categorized according to the form of the modular bridge superstructure and assessed CO₂ emission quantification per work types and materials according to each form to verify the environmental effectiveness of the modular bridge.

Keywords: modular bridge, CO2 emission, environmentally friendly, quantification, carbon emission factor, LCA (Life Cycle Assessment)

Procedia PDF Downloads 542

Authors: S. Tireche, A. Tairi abdelaziz

Abstract:

Environmental damage has increased steadily in recent decades: Depletion of natural resources, destruction of the ozone layer, greenhouse effect, degradation of the quality of life, land use etc. New terms have emerged as: "Prevention rather than cure" or "polluter pays" falls within the principles of common sense, their practical implementation still remains fragmented. Among the avenues to be explored, one of the most promising is certainly one that focuses on product design. Indeed, where better than during the design phase, can reduce the source of future impacts on the environment? What choices or those of design, they influence more on the environmental characteristics of products? The most currently recognized at the international level is the analysis of the life cycle (LCA) and Life Cycle Assessment, subject to International Standardization (ISO 14040-14043). LCA provides scientific and objective assessment of potential impacts of the product or service, considering its entire life cycle. This approach makes it possible to minimize impacts to the source in pollution prevention. It is widely preferable to curative approach, currently majority in the industrial crops, led mostly by a report of pollution. The "product" is to reduce the environmental impacts of a given product, taking into account all or part of its life cycle. Currently, there are emerging tools, known as eco-design. They are intended to establish an environmental profile of the product to improve its environmental performance. They require a quantity sufficient information on the product for each phase of its life cycle: raw material extraction, manufacturing, distribution, usage, end of life (recycling or incineration or deposit) and all stages of transport. The assessment results indicate the sensitive points of the product studied, points on which the developer must act.

Keywords: eco design, impact, life cycle analysis (LCA), sustainability

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

Abstract:

This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: cruise behavior, customer activities, on-board environmental factors, on-board experience, user or customer satisfaction

Procedia PDF Downloads 156

Authors: Elena Kovalevich, Irina Tomasheva

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The research relevance is caused by the importance of studying features of cross-cultural communication in the system of intensive language contacts, on the one hand, and on the other – by the need of control over the language situation as cross-cultural contacts often reflect emotionally intense reality, destructive for national culture and language and also for health and mentality of the individual. The objective consists in systematization of requirements imposed by the globalized society on ethics, aesthetics and emotive component of cross-cultural communication under conditions of language hybridization of modern Russian-speaking society. Problems connected with establishing the criteria differentiating eco-friendly and eco-unfriendly communication; identifying the specifics of the eco-unfriendly communication containing language hybrids; justifying the negative impact of language hybridization on ethics and esthetics of cross-cultural communication are considered, taking into account the category of emotivity. The study makes a contribution to the development of key problems of modern linguistics connected with exploration of basics in the theory of language personality, ecology of language, emotive linguistics. The results can be used by specialists in the fields of sociolinguistics, cross-cultural communication, the national language policy.

Keywords: cross-cultural communication, eco-linguistics, ethics and aesthetics, emotivity, language hybrids

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Authors: Şakir Bingöl, Bayram İslamoğlu, Ebubekir Furkan Tepeli, Fatih Mehmet Karakule, Fatih Küçük, Merve Sena Arpacık, Mustafa Taha Kabar, Muhammet Metin Molak, Osman Emre Turan, Ömer Faruk Yesir, Sıla İnanır

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This study introduces an IoT-based real-time safety system for mining, addressing global safety challenges. The wearable device, seamlessly integrated into miners' jackets, employs LoRa technology for communication and offers real-time monitoring of vital health and environmental data. Unique features include an LCD panel for immediate information display and sound-based location tracking for emergency response. The methodology involves sensor integration, data transmission, and ethical testing. Validation confirms the system's effectiveness in diverse mining scenarios. The study calls for ongoing research to adapt the system to different mining contexts, emphasizing its potential to significantly enhance safety standards in the industry.

Keywords: mining safety, internet of things, wearable technology, LoRa, RFID tracking, real-time safety system, safety alerts, safety measures

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Authors: Hasan Mahmud Reza

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Extensive studies of the human umbilical cord, both basic and translational, over the last three decades have unveiled a plethora of information. The cord lining harbors at least two phenotypically different multipotent stem cells: mesenchymal stem cells (MSCs) and cord lining epithelial stem cells (CLECs). These cells exhibit a mixed genetic profiling of both embryonic and adult stem cells, hence display a broader stem features than cells from other sources. We have observed that umbilical cord-derived cells are immunologically privileged and non-tumorigenic by animal study. These cells are ethically acceptable, thus provides a significant advantage over other stem cells. The high proliferative capacity, viability, differentiation potential, and superior harvest of these cells have made them better candidates in comparison to contemporary adult stem cells. Following 30 replication cycles, these cells have been observed to retain their stemness, with their phenotype and karyotype intact. Transplantation of bioengineered CLEC sheets in limbal stem cell-deficient rabbit eyes resulted in regeneration of clear cornea with phenotypic expression of the normal cornea-specific epithelial cytokeratin markers. The striking features of low immunogenicity protecting self along with co-transplanted allografts from rejection largely define the transplantation potential of umbilical cord-derived stem cells.

Keywords: cord lining epithelial stem cells, mesenchymal stem cell, regenerative medicine, umbilical cord

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Masoud Sheidai, Fahimeh Koohdar, Hashem Sharifi

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Juglans regia (L.) commonly known as Persian walnut of the genus Juglans L. (Juglandaceae) is one of the most important cultivated plant species due to its high-quality wood and edible nuts. The genetic diversity analysis is essential for conservation and management of tree species. Persian walnut is native from South-Eastern Europe to North-Western China through Tibet, Nepal, Northern India, Pakistan, and Iran. The species like Persian walnut, which has a wide range of geographical distribution, should harbor extensive genetic variability to adapt to environmental fluctuations they face. We aimed to study the population genetic structure of seven Persian walnut populations including three wild and four cultivated populations by using ISSR (Inter simple sequence repeats) and SRAP (Sequence related amplified polymorphism) molecular markers. We also aimed to compare the genetic variability revealed by ISSR neutral multilocus marker and rDNA ITS sequences. The studied populations differed in morphological features as the samples in each population were clustered together and were separate from the other populations. Three wild populations studied were placed close to each other. The mantel test after 5000 times permutation performed between geographical distance and morphological distance in Persian walnut populations produced significant correlation (r = 0.48, P = 0.002). Therefore, as the populations become farther apart, they become more divergent in morphological features. ISSR analysis produced 47 bands/ loci, while we obtained 15 SRAP bands. Gst and other differentiation statistics determined for these loci revealed that most of the ISSR and SRAP loci have very good discrimination power and can differentiate the studied populations. AMOVA performed for these loci produced a significant difference (< 0.05) supporting the above-said result. AMOVA produced significant genetic difference based on ISSR data among the studied populations (PhiPT = 0.52, P = 0.001). AMOVA revealed that 53% of the total variability is due to among population genetic difference, while 47% is due to within population genetic variability. The results showed that both multilocus molecular markers and ITS sequences can differentiate Persian walnut populations. The studied populations differed genetically and showed isolation by distance (IBD). ITS sequence based MP and Bayesian phylogenetic trees revealed that Iranian walnut cultivars form a distinct clade separated from the cultivars studied from elsewhere. Almost all clades obtained have high bootstrap value. The results indicated that a combination of multilpcus and sequencing molecular markers can be used in genetic differentiation of Persian walnut.

Keywords: genetic diversity, population, molecular markers, genetic difference

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Authors: Mitchell T. Grothaus, Cory Grigsby, Timothy S. Hare

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This study aims to determine if there is a relationship between elevated cancer risks in eastern Kentucky and the environmental effects of black shale. Previous research shows that black shale formations, such as those in eastern Kentucky contain high levels of toxic elements including arsenic and radon compared to average rocks and sediment. Similarly, the population of eastern Kentucky has higher rates of many health conditions, including lung cancer and cardiovascular disease, than surrounding regions. These poor health outcomes are typically explained in relation to social, economic, behavioral, and healthcare factors. The rates of many conditions, however, have not decreased as these factors improve with regional development. Black shale is known to affect environmental conditions such as by increasing radiation levels and heavy metal toxicity. We are mapping the effects of black shale through monitoring radiation, microbes, and chemical standards of water sources. In this presentation, we report on our measuring pH, dissolved oxygen, total dissolved solids, conductivity, temperature, and discharge and comparison with water quality standards from the Kentucky Department for Environmental Protection. The conditions of water sources combined with an environmental survey of the surrounding areas provide a greater understanding of why the people in eastern Kentucky face the current health issues.

Keywords: black shale, eastern Kentucky, environmental impact, water quality

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Authors: Stephen Anim, Emmanuel O. Sarpong, Daniel Apaak

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This study investigates the relationship between morphological predictors and running ability, emphasizing gender-specific variations among male and female athletes in Cape Coast Metropolis (CCM), Ghana. The dynamic interplay between an athlete's physique and their performance capabilities holds particular relevance in the realm of sports science, influencing training methodologies and talent identification processes. The research aims to contribute comprehensive insights into the morphological determinants of running proficiency, with a specific focus on the local athletic community in Cape Coast Metropolis. Utilizing a correlational research design, a thorough analysis of morphological features, encompassing 22 morphological features including body weight, 6 measurements related to body length, 7 body girth, and knee diameter, and 7 skinfold measurements against 50m dash, among male and female athletes, was conducted. The study involved 420 athletes both male (N=210) and female (N=210) aged 16-22 from 10 Senior High Schools (SHS) in the Cape Coast Metropolis, providing a representative sample of the local athletic community. The collected data were statistically analysed using means and standard deviation, and stepwise multiple regression to determine how morphological variables contribute to and predict running proficiency outcomes. The investigation revealed that athletes from Senior High Schools (SHS) in Cape Coast Metropolis (CCM) exhibit well-developed physiques and sufficient fitness levels suitable for overall athletic performance, taking into account gender differences. Moreover, the findings suggested that approximately 77% of running ability could be attributed to morphological factors, leading to diverse predictive models for male and female athletes within SHS in CCM, Ghana. Consequently, these formulated equations hold promise for predicting running ability among young athletes, particularly in the context of SHS environments.

Keywords: body fat, body girth, body length, morphological features, running ability, senior high school

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