Search results for: active learning

Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Sanghoon Shim, Jaehwan Jung, Sung-Ah Kim

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As the digital technology develops, studies on the TUI (Tangible User Interface) that links the physical environment utilizing the human senses with the virtual environment through the computer are actively being conducted. In addition, there has been a tremendous advance in computer design making through the use of computer-aided design techniques, which enable optimized decision-making through comparison with machine learning and parallel comparison of alternatives. However, a complex design that can respond to user requirements or performance can emerge through the intuition of the designer, but it is difficult to actualize the emerged design by the designer's ability alone. Ancillary tools such as Gaudí's Sandbag can be an instrument to reinforce and evolve emerged ideas from designers. With the advent of many commercial tools that support 3D objects, designers' intentions are easily reflected in their designs, but the degree of their reflection reflects their intentions according to the proficiency of design tools. This study embodies the environment in which the form can be implemented by the fingers of the most basic designer in the initial design phase of the complex type building design. Leapmotion is used as a sensor to recognize the hand motions of the designer, and it is converted into digital information to realize an environment that can be linked in real time in virtual reality (VR). In addition, the implemented design can be linked with Rhino™, a 3D authoring tool, and its plug-in Grasshopper™ in real time. As a result, it is possible to design sensibly using TUI, and it can serve as a tool for assisting designer intuition.

Keywords: design environment, digital modeling, hand gesture, TUI, virtual reality

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Authors: Popoola Sulaimon Akorede, Muinat A. Agbabiaka-Mustapha

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The Quranic / piazza school where the rudiments of Islam are being imparted from the teaching of Arabic/ Quranic alphabets which later metamorphosized to higher fundamental principles of Islam is the major determinant of the existence of Islam in any part of south western Nigeria. In other words, one can successfully say that where there is a few or non-existence of such schools in that part of the country, the practice of the religion of Islam would be either very low or not existing at all. However, it has been discovered in the modern worlds that several challenges are militating against the development of these schools and among these challenges are poor admission policy, inadequate facilities such as learning environment and instructional materials, curriculum inadequacy and the management and the administration of the schools which failed to change in order to meet the modern contemporary Educational challenges. The focus of this paper therefore is to improve the conditions of these basic Islamic schools through the introduction of quality assurance and integrating accreditation Exercise to improve their status in order to enhance economic empowerment and to further their educational career in the future so that they will be able to compete favourably among the graduates of conventional universities. The scope of this study is limited to only seven (7) states of yorubaland and with only three (3) proprietors/ schools from each state which are Lagos, Oyo, Ogun, Osun, Ekiti, Ondo and parts of Kwara State. The study revealed that quality assurance as well as accreditation exercise are lacking in all the local Arabic/Quranic schools. Suggestions are proffered towards correcting the anomalies in these schools so that they can meet the modern Educational standard.

Keywords: accreditation, quality assurance, Quranic schools, South-western Nigeria

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Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

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This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

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Authors: Kuniko Muramoto, Tadashi Nakamura, Shiro Dan

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On March 11, 2011 the Great East Japan Disaster caused widespread damage. In the aftermath, we searched for ways to provide long-term support and enhanced resilience to affected areas, arriving at the Family Manga Exhibition: an art collection portraying family life. It became a tool for community outreach and intervention, and we implemented support programs by collaborating with local support agencies. This 10-year project has been touring through four prefectures in Tohoku since the disaster struck, bearing witness to the effects of disaster and recovery alike. At this five-year mark, we use a narrative perspective to present our findings and reflect on post-disaster community support. It is important to note that the exhibition’s art does not directly depict the disaster; it portrays stories of anonymous families instead. They stimulate viewers’ memories and remind them of their own family stories. We analyzed viewers' oral and written responses to the exhibition and discovered that family manga as an art form enhances the viewer’s sense of connection to people close to them. We also discovered that the viewers gained more universal perspective on their own situations by viewing the exhibition. Manga, we found, offered a certain safety by enabling the viewers to control how they would interact with the exhibition's content and themes. In addition, the purpose of the project was for us to become witnesses of the disaster and recovery. Supporters of the project became active listeners, functioning as interactive agents who helped forming stories. Voices of the story tellers and the listeners layered upon each other and, as a result, converged into brand new narratives. The essence of traumatic experience is ‘the sense of overwhelming powerlessness and isolation’. When we redefine trauma as ‘broken relationships’, we can say that ‘enhancing relationships’ and ‘weaving relationships’ are what strengthen our resilience. This project used narrative as a modality to fortify the resilience of people involved by enhancing the social capital of bonding, bridging, and linking. The manga exhibition functioned as a tool to achieve this end, suggesting that similar applications are possible. Programs we held in-between manga exhibitions also served to enhance narratives of resiliency in the regions. However, we will save that story for another time. We hope to continue collecting the precious and polyphonic voices of people to present as stories born out of the Great East Japan Disaster. This effort extends beyond the immediately affected area by helping us prepare our resilience for future disasters.

Keywords: community, manga, narrative, resilience

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Authors: Ritwik Dutta, Marylin Wolf

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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

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Authors: Adekeye Joshua Temitope

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“Transgender” presents a complexion of ambiguity in the African context and it remains a contested topography in the discourse of sexual identity. The casts and stigmatisations towards transgender unveils vital facts and intricacies often ignored in the academic communities; the problems and oppressions of given sex/gender system, the constrain of monogamy and ignorance of fluidity of human sexuality thereby generating dual discords of “enforced heterosexual” and “unavoidable homosexual.” The African culture voids transgender movements and perceive same-sex sexual behavior as “taboo or bad habits” and this provide reasonable explanations for the failure of asserting for the sexual rights in GLBT movement in most discourse on sexuality in the African context. However, we could not deny the real existence of active flowing and fluidity of human sexuality even though its variants could be latent. The incessant consciousness of the existence of transgender practices in Africa either in form of bisexual desire or bisexual behavior with or without sexual identity, including people who identify themselves as bisexual opens up the vision for us to reconsider and reexamine what constitutes such ambiguity and controversy of transgender identity at present time. The notion of identity politics in gay, lesbian, and transgender community has its complexity and debates in its historical development. This paper analyses the representation of the historical trajectory of transgender practices by presenting the dynamic transition of how people cognize transgender practices under different historical conditions since the understanding of historical transition of bisexual practices would be very crucial and meaningful for gender/sexuality liberation movement at present time and in the future. The paper did a juxtaposition of the trajectories of bisexual practices between Anglo-American world and Africa, as it has certain similarities and differences within diverse historical complexities. The similar condition is the emergence of gay identity under the influence of capitalism but within different cultural context. Therefore, the political economy of each cultural context plays very important role in understanding the formation of sexual identities historically and its development and influence for the GLBT movement afterwards and in the future. By reexamining Kinsey’s categorization and applying Klein’s argument on individual’s sexual orientation this paper is poised to break the given and fixed connection among sexual behavior/sexual orientation/sexual identity, on the other hand to present the potential fluidity of human sexuality by reconsidering and reexamining the present given sex/gender system in our world. The paper concludes that it is obligatory for the essentialist and exclusionary trend at this historical moment since gay and lesbian communities in Africa need to clearly demonstrate and voice for themselves under the nuances of gender/sexuality liberation.

Keywords: heterosexual, homosexual, identity politics, queer politics, transgender

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Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

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Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: Jareeluk Ratanaphan

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The purposed of this research were; 1. To survey the teacher’s needs on knowledge about special education management for special needs student 2. Development of distance training packages for teacher on special education management for special needs student 3. to study the effects of using the packages on trainee’s achievement 4. to study the effects of using the packages on trainee’s opinion on the distance training packages. The design of the experiment was research and development. The research sample for survey were 86 teachers, and 22 teachers for study the effects of using the packages on achievement and opinion. The research instrument comprised: 1) training packages on special education management for special needs student 2) achievement test 3) questionnaire. Mean, percentage, standard deviation, t-test and content analysis were used for data analysis. The findings of the research were as follows: 1. The teacher’s needs on knowledge about teaching for a learner with learning disability, mental retardation, autism, physical and health impairment and research in special education. 2. The package composed of special education management for special needs student document and manual of distance training packages. The document consisted by the name of packages, the explanation for the educator, content’s structure, concept, objectives, content and activities. Manual of distance training packages consisted by the explanation about a document, objectives, explanation about using the package, training schedule, and evaluation. The efficiency of packages was established at 79.50/81.35. 3. The results of using the packages were the posttest average scores of trainee’s achievement were higher than the pretest. 4. The trainee’s opinion on the package was at the highest level.

Keywords: distance training package, teacher, learner with special needs

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Authors: Abiola O. Temitayo-Oboh, Olugbenga L. Abodunrin, Wasiu O. Adebimpe, Micheal C. Asuzu

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Introduction: Many women who are sexually active would prefer to avoid becoming pregnant but are not using any method of contraception. These women are considered to have an unmet need for contraception. In an ideal situation, all women who want to space or limit their births and are exposed to the risk of conception would use some kind of conception; in practice, however, some women fail to use contraception which put them at risk of having mistimed or unwanted births, induced abortion, or maternal death. This study, therefore, aimed to assess the determinants of unmet need for contraception among currently married women in rural and urban communities of Osun State, South-West Nigeria. Methods: This was an analytical cross-sectional comparative study, which was carried out among currently married women. Three hundred and twenty respondents each were selected for the rural and urban groups from four Local Government Areas using multi-stage sampling technique. Data were collected using a pre-tested semi-structured interviewer-administered questionnaire and focus group discussion (FGD) guide; data analysis was done with Statistical Package for Social Sciences (SPSS) version 17.0 and detailed content analysis method respectively. Statistical analysis of the difference between proportions was done by the use of the Chi-square test and T-test was used to compare the means of the continuous variables. The study also utilized descriptive, bivariate and multivariate analytical techniques to examine the effect of some variables on unmet need. Level of statistical significance was set at p-value < 0.05 for all values. Results: Two hundred and ninety-six (92.5%) of the rural and 306 (95.6%) of the urban study population had heard of contraception, 365 (57.0 %) of the total respondents had good knowledge [162 (50.6 %) for rural respondents and 203 (63.4 %) for urban respondents]. This difference was statistically significant (p < 0.001). Five hundred and twenty-one (81.4%) respondents had a positive attitude towards contraception [243 (75.9%) in the rural and 278 (86.9%) in the urban area], and the difference was also statistically significant (p < 0.001). Only 47 (14.7%) and 59 (18.4%) of rural and urban women were current contraceptive users respectively. The total unmet need for contraception among rural women was 138 (43.1%) of which 82 (25.6%) was for spacing and 56 (17.5%), for limiting. While the total unmet need for contraception among urban women was 145 (45.3%) of which 96 (30.0%) was for spacing and 49 (15.3%) for limiting. Number of living children, knowledge of contraceptive methods, discussion with health workers about family planning, couples discussion about family planning and availability of family planning services were found to be predictors of women’s unmet need for contraception (p < 0.05). Conclusion: It is, therefore, recommended that there is need to intensify reproductive health education in bridging the knowledge gap, improving attitude and modifying practices regarding use of contraception in Nigeria. Hence, this will help to enhance the utilization of family planning services among Nigerian women.

Keywords: contraception, married women, Nigeria, rural, urban, unmet need

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Authors: Maksudur Rahman Khan, Kar Min Chan, Huei Ruey Ong, Chin Kui Cheng, Wasikur Rahman

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Microbial fuel cells (MFCs) represent a promising technology for simultaneous bioelectricity generation and wastewater treatment. Catalysts are significant portions of the cost of microbial fuel cell cathodes. Many materials have been tested as aqueous cathodes, but air-cathodes are needed to avoid energy demands for water aeration. The sluggish oxygen reduction reaction (ORR) rate at air cathode necessitates efficient electrocatalyst such as carbon supported platinum catalyst (Pt/C) which is very costly. Manganese oxide (MnO2) was a representative metal oxide which has been studied as a promising alternative electrocatalyst for ORR and has been tested in air-cathode MFCs. However, the single MnO2 has poor electric conductivity and low stability. In the present work, the MnO2 catalyst has been modified by doping Pt nanoparticle. The goal of the work was to improve the performance of the MFC with minimum Pt loading. MnO2 and Pt nanoparticles were prepared by hydrothermal and sol-gel methods, respectively. Wet impregnation method was used to synthesize Pt/MnO2 catalyst. The catalysts were further used as cathode catalysts in air-cathode cubic MFCs, in which anaerobic sludge was inoculated as biocatalysts and palm oil mill effluent (POME) was used as the substrate in the anode chamber. The as-prepared Pt/MnO2 was characterized comprehensively through field emission scanning electron microscope (FESEM), X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and cyclic voltammetry (CV) where its surface morphology, crystallinity, oxidation state and electrochemical activity were examined, respectively. XPS revealed Mn (IV) oxidation state and Pt (0) nanoparticle metal, indicating the presence of MnO2 and Pt. Morphology of Pt/MnO2 observed from FESEM shows that the doping of Pt did not cause change in needle-like shape of MnO2 which provides large contacting surface area. The electrochemical active area of the Pt/MnO2 catalysts has been increased from 276 to 617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The CV results in O2 saturated neutral Na2SO4 solution showed that MnO2 and Pt/MnO2 catalysts could catalyze ORR with different catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode catalyst generates a maximum power density of 165 mW/m3, which is higher than that of MFC with MnO2 catalyst (95 mW/m3). The open circuit voltage (OCV) of the MFC operated with MnO2 cathode gradually decreased during 14 days of operation, whereas the MFC with Pt/MnO2 cathode remained almost constant throughout the operation suggesting the higher stability of the Pt/MnO2 catalyst. Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced performance.

Keywords: microbial fuel cell, oxygen reduction reaction, Pt/MnO2, palm oil mill effluent, polarization curve

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Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

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The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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Authors: Kehinde, Taye Adetutu

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The fact that Nigeria as a nation is faced by myriads of problems associated with religious crises and political insecurity is no news, the spoken statement and actions of most political giant were the major cause of this unrest. The 'unlearnt' youth within the regions has encompassed the situation. This scenario is further compounded by multilingual nature of the country as it is estimated that there exists amount 400 indigenous languages in Nigeria. It is an indisputable fact that english language which has assumed the status of an official language in Nigeria, given its status has a language of power and captivity by a few with no privilege to attend school. However, educating people in their indigenous language; crises can be averted through the proper orientation and mass literacy campaign, especially for the timid illiterate one, so as to live in unity, peace, tranquillity, and harmony as indivisible nation. In investigating the problem in this study with an emphasis on three major Nigerian language (Yoruba, Igbo and Hausa), participants observations and survey questionnaire were administered to about one hundred and twenty (120) respondents who were randomly selected throughout the three major ethnic groups in Nigeria. Findings from this study reveals that teaching and learning of cognitive words and information are more effective in ones mother tongue and helps in stimulating new ideas and changes. This paper was able to explore and critically examine the current state of affairs in Nigeria and proffer possible solutions to the prevailing situations by identifying how indigenous languages and linguistics can be used to ameliorate the present political and religious crisis for Nigeria, thus providing a proper recommendation to achieve meaningful stability and coexistence within a nation.

Keywords: multilingualism, political crisis, religious, Nigeria

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: B. D. Patni, Ashwani Jain, Arindom Chakraborty

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The world’s highest mountain range has been forming since the collision of Indian Plate with Asian Plate 40-50 million years ago. The Indian subcontinent has been deeper and deeper in to the rest of Asia resulting upliftment of Himalaya & Tibetan Plateau. The complex domain has become a major challenge for construction of hydro electric projects. The Himalayas are geologically complex & seismically active. Shifting of Indian Plate northwardly and increasing the amount of stresses in the fragile domain which leads to deformation in the form of several fold, faults and upliftment. It is difficult to undergo extensive geological investigation to ascertain the geological problems to be encountered during construction. Inaccessibility of the terrain, high rock cover, unpredictable ground water condition etc. are the main constraints. The hydroelectric projects located in Himalayas have faced many geological and geo-hydrological problems while construction of surface and subsurface works. Based on the experience, efforts have been made to identify the expected geological problems during and after construction of the projects. These have been classified into surface and subsurface problems which include existence of inhomogeneous deep overburden in the river bed or buried valley, abrupt change in bed rock profile, Occurrences of fault zones/shear zones/fractured rock in dam foundation and slope instability in the abutments. The tunneling difficulties are many such as squeezing ground condition, popping, rock bursting, high temperature gradient, heavy ingress of water, existence of shear seams/shear zones and emission of obnoxious gases. However, these problems were mitigated by adopting suitable remedial measures as per site requirement. The support system includes shotcrete, wire mesh, rock bolts, steel ribs, fore-poling, pre-grouting, pipe-roofing, MAI anchors, toe wall, retaining walls, reinforced concrete dowels, drainage drifts, anchorage cum drainage shafts, soil nails, concrete cladding and shear keys. Controlled drilling & blasting, heading & benching, proper drainage network and ventilation system are other remedial measures adopted to overcome such adverse situations. The paper highlights the geological uncertainties and its remedial measures in Himalaya, based on the analysis and evaluation of 20 hydroelectric projects during construction.

Keywords: geological problems, shear seams, slope, drilling & blasting, shear zones

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Mirim Kim, Won-Oak Oh

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Purpose: The purpose of this study was to identify hospitalized children's fall risk factors, fall prevention status and fall prevention strategies recognized by nurses and caregivers of hospitalized children and present an ecological model for fall preventive management in hospitalized children. Method: The participants of this study were 14 nurses working in medical institutions and having more than one year of child care experience and 14 adult caregivers of children under 6 years of age receiving inpatient treatment at a medical institution. One to one interview was attempted to identify their perception of fall preventive management. Transcribed data were analyzed through latent content analysis method. Results: Fall risk factors in hospitalized children were 'unpredictable behavior', 'instability', 'lack of awareness about danger', 'lack of awareness about falls', 'lack of child control ability', 'lack of awareness about the importance of fall prevention', 'lack of sensitivity to children', 'untidy environment around children', 'lack of personalized facilities for children', 'unsafe facility', 'lack of partnership between healthcare provider and caregiver', 'lack of human resources', 'inadequate fall prevention policy', 'lack of promotion about fall prevention', 'a performanceism oriented culture'. Fall preventive management status of hospitalized children were 'absence of fall prevention capability', 'efforts not to fall', 'blocking fall risk situation', 'limit the scope of children's activity when there is no caregiver', 'encourage caregivers' fall prevention activities', 'creating a safe environment surrounding hospitalized children', 'special management for fall high risk children', 'mutual cooperation between healthcare providers and caregivers', 'implementation of fall prevention policy', 'providing guide signs about fall risk'. Fall preventive management strategies of hospitalized children were 'restrain dangerous behavior', 'inspiring awareness about fall', 'providing fall preventive education considering the child's eye level', 'efforts to become an active subject of fall prevention activities', 'providing customed fall prevention education', 'open communication between healthcare providers and caregivers', 'infrastructure and personnel management to create safe hospital environment', 'expansion fall prevention campaign', 'development and application of a valid fall assessment instrument', 'conversion of awareness about safety'. Conclusion: In this study, the ecological model of fall preventive management for hospitalized children reflects various factors that directly or indirectly affect the fall prevention of hospitalized children. Therefore, these results can be considered as useful baseline data for developing systematic fall prevention programs and hospital policies to prevent fall accident in hospitalized children. Funding: This study was funded by the National Research Foundation of South Korea (grant number NRF-2016R1A2B1015455).

Keywords: fall down, safety culture, hospitalized children, risk factors

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity, a disease associated with a low-grade inflammation, is a risk factor for the development of metabolic syndrome (MetS). So far, MetS risk factors such as parameters related to glucose and lipid metabolisms as well as blood pressure were considered for the evaluation of this disease. There are still some ambiguities related to the characteristic features of MetS observed particularly in pediatric population. Hormonal imbalance is also important, and quite a lot information exists about the behaviour of some hormones in adults. However, the hormonal profiles in pediatric metabolism have not been cleared yet. The aim of this study is to investigate the profiles of cortisol, insulin, and thyroid hormones in children with MetS. The study population was composed of morbid obese (MO) children without (Group 1) and with (Group 2) MetS components. WHO BMI-for age and sex percentiles were used for the classification of obesity. The values above 99 percentile were defined as morbid obesity. Components of MetS (central obesity, glucose intolerance, high blood pressure, high triacylglycerol levels, low levels of high density lipoprotein cholesterol) were determined. Anthropometric measurements were performed. Ratios as well as obesity indices were calculated. Insulin, cortisol, thyroid stimulating hormone (TSH), free T₃ and free T₄ analyses were performed by electrochemiluminescence immunoassay. Data were evaluated by statistical package for social sciences program. p<0.05 was accepted as the degree for statistical significance. The mean ages±SD values of Group 1 and Group 2 were 9.9±3.1 years and 10.8±3.2 years, respectively. Body mass index (BMI) values were calculated as 27.4±5.9 kg/m² and 30.6±8.1 kg/m², successively. There were no statistically significant differences between the ages and BMI values of the groups. Insulin levels were statistically significantly increased in MetS in comparison with the levels measured in MO children. There was not any difference between MO children and those with MetS in terms of cortisol, T₃, T₄ and TSH. However, T₄ levels were positively correlated with cortisol and negatively correlated with insulin. None of these correlations were observed in MO children. Cortisol levels in both MO as well as MetS group were significantly correlated. Cortisol, insulin, and thyroid hormones are essential for life. Cortisol, called the control system for hormones, orchestrates the performance of other key hormones. It seems to establish a connection between hormone imbalance and inflammation. During an inflammatory state, more cortisol is produced to fight inflammation. High cortisol levels prevent the conversion of the inactive form of the thyroid hormone T₄ into active form T₃. Insulin is reduced due to low thyroid hormone. T₃, which is essential for blood sugar control- requires cortisol levels within the normal range. Positive association of T₄ with cortisol and negative association of it with insulin are the indicators of such a delicate balance among these hormones also in children with MetS.

Keywords: children, cortisol, insulin, metabolic syndrome, thyroid hormones

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Authors: Olena Kavats, Dmitry Khramov, Kateryna Sergieieva, Vladimir Vasyliev, Iurii Kavats

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Geoinformation technologies of space agromonitoring are a means of operative decision making support in the tasks of managing the agricultural sector of the economy. Existing technologies use satellite images in the optical range of electromagnetic spectrum. Time series of optical images often contain gaps due to the presence of clouds and haze. A geoinformation technology is created. It allows to fill gaps in time series of optical images (Sentinel-2, Landsat-8, PROBA-V, MODIS) with radar survey data (Sentinel-1) and use information about agrometeorological conditions of the growing season for individual monitoring years. The technology allows to perform crop classification and mapping for spring-summer (winter and spring crops) and autumn-winter (winter crops) periods of vegetation, monitoring the dynamics of crop state seasonal changes, crop yield forecasting. Crop classification is based on supervised classification algorithms, takes into account the peculiarities of crop growth at different vegetation stages (dates of sowing, emergence, active vegetation, and harvesting) and agriculture land state characteristics (row spacing, seedling density, etc.). A catalog of samples of the main agricultural crops (Ukraine) is created and crop spectral signatures are calculated with the preliminary removal of row spacing, cloud cover, and cloud shadows in order to construct time series of crop growth characteristics. The obtained data is used in grain crop growth tracking and in timely detection of growth trends deviations from reference samples of a given crop for a selected date. Statistical models of crop yield forecast are created in the forms of linear and nonlinear interconnections between crop yield indicators and crop state characteristics (temperature, precipitation, vegetation indices, etc.). Predicted values of grain crop yield are evaluated with an accuracy up to 95%. The developed technology was used for agricultural areas monitoring in a number of Great Britain and Ukraine regions using EOS Crop Monitoring Platform (https://crop-monitoring.eos.com). The obtained results allow to conclude that joint use of Sentinel-1 and Sentinel-2 images improve separation of winter crops (rapeseed, wheat, barley) in the early stages of vegetation (October-December). It allows to separate successfully the soybean, corn, and sunflower sowing areas that are quite similar in their spectral characteristics.

Keywords: geoinformation technology, crop classification, crop yield prediction, agricultural monitoring, EOS Crop Monitoring Platform

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Authors: Emilie Zimet

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During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

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Authors: Ebrahim Panah, Muhammad Yasir Babar

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Thanks to the development of online technology and social networks, people are able to communicate as well as learn. WhatsApp is a popular social network which is growingly gaining popularity. This app can be used for communication as well as education. It can be used for instructor-learner, learner-learner, and learner-content interactions; however, very little knowledge is available on these potentials of WhatsApp. The current study was undertaken to investigate university students’ perceptions of WhatsApp used as a tool for instructor-learner dialogue, learner-content dialogue, and learner-learner dialogue. The study adopted a survey approach and distributed the questionnaire developed by Google Forms to 54 (11 males and 43 females) university students. The obtained data were analyzed using SPSS version 20. The result of data analysis indicates that students have positive attitudes towards WhatsApp as a tool for Instructor-Learner Dialogue: it easy to reach the lecturer (4.07), the instructor gives me valuable feedback on my assignment (4.02), the instructor is supportive during course discussion and offers continuous support with the class (4.00). Learner-Content Dialogue: WhatsApp allows me to academically engage with lecturers anytime, anywhere (4.00), it helps to send graphics such as pictures or charts directly to the students (3.98), it also provides out of class, extra learning materials and homework (3.96), and Learner-Learner Dialogue: WhatsApp is a good tool for sharing knowledge with others (4.09), WhatsApp allows me to academically engage with peers anytime, anywhere (4.07), and we can interact with others through the use of group discussion (4.02). It was also found that there are significant positive correlations between students’ perceptions of Instructor-Learner Dialogue (ILD), Learner-Content Dialogue (LCD), Learner-Learner Dialogue (LLD) and WhatsApp Application in classroom. The findings of the study have implications for lectures, policy makers and curriculum developers.

Keywords: instructor-learner dialogue, learners-contents dialogue, learner-learner dialogue, whatsapp application

Procedia PDF Downloads 153

Authors: Matt Fullmer, Carol Wilkinson, Keven Prusak, Dennis Eggett, Todd Pennington

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Obesity and chronic health issues are linked to physical inactivity. Physical education (PE) programs in school can play a major role in combating these health-related issues. This study focused on supporting competence through keeping a leisure-time physical activity (LTPA) record as part of PE. Keeping a daily LTPA record may be an effective intervention helping students feel more competent toward exercise, and thus, self-determined (within the context of self-determination theory) to exercise. Little is known about the relationship between daily LTPA records and perceived competence, motivational profiles, and LTPA levels of students enrolled in PE. This study examined the relationship between keeping a daily, online LTPA record and adolescent (a) motivational profiles toward LTPA, (b) perceived competence toward LTPA, and (c) LTPA behaviors. Secondary students (N = 124) in physical education classes completed a baseline questionnaire which consisted of the Behavioural Regulation in Exercise Questionnaire–2, the Perceived Competence Scale, and the Godin Leisure-Time Exercise Questionnaire. For three weeks, the students were assigned to keep the Presidential Active Lifestyle Award Challenge (PALAC) as their online LTPA record. They completed the questionnaire after each week. A 2 (gender) x 4 (trials) repeated measures ANCOVA examined the relationships between recording compliance and motivation, perceived competence, and physical activity. Results showed that recording compliance was not a significant predictor of perceived competence to participate in LTPA. Examining motivational factors, a significant interaction between recording compliance and introjected regulation was found. The more students recorded the less motivated they were by guilt or obligation to exercise in their leisure-time. Also, a significant interaction was found between recording compliance and intrinsic regulation, indicating that the more students recorded the more intrinsically motivated they were to exercise in their leisure-time. Lastly, there was a significant interaction between recording compliance and LTPA. As students kept the LTPA record, girls’ LTPA levels significantly decreased and boys’ LTPA levels significantly increased. The key findings are that, as implemented in this study: a) the lack of PALAC compliance suggests that daily LTPA records may NOT be the most effective intervention for this population, b) keeping a daily LTPA record did NOT help students feel more competent to exercise in their leisure-time, c) a daily LTPA record may help students move towards being more self-determined in their feelings towards LTPA, and d) the outcome of keeping a LTPA record on LTPA behavior is statistically significant, although actual differences may not be practically important.

Keywords: behavioural regulation in exercise questionnaire–2, Godin leisure–time exercise questionnaire, online physical activity log, perceived competence scale, self-determination theory

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Authors: Abdul Rahmat

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Community-based education in the economic empowerment of the family is an attempt to accelerate human development index (HDI) Dumbo Kingdom District of Gorontalo economics (purchasing power) program developed in this activity is the manufacture of functional skills shredded fish, fish balls, fish nuggets, chips anchovies, and corn sticks fish. The target audience of this activity is fishing se mothers subdistrict Dumbo Kingdom include Talumolo Village, Village Botu, Kampung Bugis Village, Village North and Sub Leato South Leato that each village is represented by 20 participants so totaling 100 participants. Time activities beginning in October s/d November 2014 held once a week on every Saturday at 9.00 s/d 13:00/14:00. From the results of the learning process of testing the skills of functional skills of making shredded fish, fish balls, fish nuggets, chips anchovies, fish and corn sticks residents have additional knowledge and experience are: 1) Order the concept include: nutrient content, processing food with fish raw materials , variations in taste, packaging, pricing and marketing sales. 2) Products made: in accordance with the wishes of the residents learned that estimated Eligible selling, product packaging logo creation, preparation and realization of the establishment of Business Study Group (KBU) and pioneered the marketing network with restaurant, store / shop staple food vendors that are around CLC.

Keywords: community development, functional skills, gender, HDI

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Authors: Abel Olusegun Egunjobi, Olusegun Oyeleye Adesanya

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Teaching effectiveness of lecturers in a tertiary institution in Nigeria is one of the determinants of the lecturer’s productivity. In this study, therefore, lecturers’ teaching effectiveness was examined vis-à-vis their multimedia technologies utilisation in Colleges of Education (CoE) in South-West, Nigeria. This is for the purpose of ascertaining the relationship and contribution of multimedia technologies utilisation to lecturers’ teaching effectiveness in Nigerian colleges of education. The descriptive survey research design was adopted in the study, while a multi-stage sampling procedure was used in the study. A stratified sampling technique was used to select colleges of education, and a simple random sampling method was employed to select lecturers from the selected colleges of education. A total of 862 lecturers (627 males and 235 females) were selected from the colleges of education used for the study. The instrument used was lecturers’ questionnaire on multimedia technologies utilisation and teaching effectiveness with a reliability coefficient of 0.85 at 0.05 level of significance. The data collected were analysed using descriptive statistics, multiple regression, and t-test. The findings showed that the level of multimedia technologies utilisation in colleges of education was low, whereas lecturers’ teaching effectiveness was high. Findings also revealed that the lecturers used multimedia technologies purposely for personal and professional developments, so also for up to date news on economic and political matters. Also, findings indicated that laptop, Ipad, CD-ROMs, and computer instructional software were the multimedia technologies frequently utilised by the lecturers. There was also a significant difference in the teaching effectiveness between lecturers in the Federal and State COE. The government should, therefore, make adequate provision for multimedia technologies in the COE in Nigeria for lecturers’ utilisation in their instructions so as to boost their students’ learning outcomes.

Keywords: colleges of education, lecturers’ teaching effectiveness, multimedia technologies utilisation, Southwest Nigeria

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: Olga Gomez De Miranda, Jose R. Ochoa-Gomez, Stefaan De Wildeman, Luciano Monsegue, Soraya Prieto, Leire Lorenzo, Cristina Dineiro

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The chemical industry is facing a new revolution. As long as processes based on the exploitation of fossil resources emerged with force in the XIX century, Society currently demands a new radical change that will lead to the complete and irreversible implementation of a circular sustainable economic model. The implementation of biorefineries will be essential for this. There, renewable raw materials as sugars and other biomass resources are exploited for the development of new materials that will partially replace their petroleum-derived homologs in a safer, and environmentally more benign approach. Isosorbide, (1,4:3,6-dianhydro-d-glucidol) is a primary bio-based derivative obtained from the plant (poly) saccharides and a very interesting example of a useful chemical produced in biorefineries. It can, in turn, be converted to other secondary monomers as isosorbide bis-methyl carbonate (IBMC), whose main field of application can be as a key biodegradable intermediary substitute of bisphenol-A in the manufacture of polycarbonates, or as an alternative to the toxic isocyanates in the synthesis of new polyurethanes (non-isocyanate polyurethanes) both with a huge application market. New products will present advantageous mechanical or optical properties, as well as improved behavior in non-toxicity and biodegradability aspects in comparison to their petro-derived alternatives. A robust production process of IBMC, a biomass-derived chemical, is here presented. It can be used with different raw material qualities using dimethyl carbonate (DMC) as both co-reactant and solvent. It consists of the transesterification of isosorbide with DMC under soft operational conditions, using different basic catalysts, always active with the isosorbide characteristics and purity. Appropriate isolation processes have been also developed to obtain crude IBMC yields higher than 90%, with oligomers production lower than 10%, independently of the quality of the isosorbide considered. All of them are suitable to be used in polycondensation reactions for polymers obtaining. If higher qualities of IBMC are needed, a purification treatment based on nanofiltration membranes has been also developed. The IBMC reaction-isolation conditions established in the laboratory have been successfully modeled using appropriate software programs and moved to a pilot-scale (production of 100 kg of IBMC). It has been demonstrated that a highly efficient IBMC production process able to be up-scaled under suitable market conditions has been obtained. Operational conditions involved the production of IBMC involve soft temperature and energy needs, no additional solvents, and high operational efficiency. All of them are according to green manufacturing rules.

Keywords: biomass, catalyst, isosorbide bis-methyl carbonate, polycarbonate, polyurethane, transesterification

Procedia PDF Downloads 129