Search results for: panel regression techniques

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Said Belaaouad

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This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site.

Keywords: QSAR, molecular docking, ADMET, 1, 2, 4-triazin-3(2H)-ones, breast cancer, anticancer, molecular dynamic simulations, MMPBSA calculation

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Authors: Festus Epetimehin

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Agriculture remains the dominant sector in the rural areas where over 70% of Nigerian reside and it’s still the backbone of our economy. The observed poor performance of farmers in agricultural productivity is due to the nature of risks and uncertainties in agriculture.Agricultural insurance is one of the mechanisms by which farmers can stabilize farm income and investment. The study examined the relationship between agricultural insurance scheme (AIS) and performance of agribusiness in Nigeria. The study adopted exploratory research design which is an ex-ante research approach. One hundred copies of structured questionnaire were administered for the purpose of the study. Correlation analysis and regression analysis were employed for the study. The correlation analysis of the finding revealed that the independent variable; agricultural insurance scheme (AIS) is positively and significantly correlated with the set of dependent variables; where turnover (ABT)=0.582**, profitability (ABP)=0.321**, solvency (ABS)=0.418**and cost of production (ABC)=0.23** respectively. The regression analysis result also revealed the degree of relationship between the independent variable (AIS) and set of dependent variables where one(1%) percent increase in independent variable will lead to 33.9% (ABT), 9.7% (ABP), 17.5%(ABS) and 1.5%(ABC).The study recommended that the Federal Government in collaboration with the participating Agricultural insurers embark on awareness campaign through to the length and breadth of Nigeria on government support and insurance scheme for farmers. Government should also ensure that the loan and insurance scheme should extend beyond the mechanized farmers and include the intensive subsistence farmers in view of the fact that they are the dominants in most of the farm produce markets.

Keywords: agribusiness, agricultural insurance, performance, turnover, solvency, agricultural risks

Procedia PDF Downloads 75

Authors: Akbar Rostamabadi, Adel Mazloumi, Abbas Rahimi Foroushani

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This study aimed to determine the Work Ability Index (WAI) and examine the influence of health dimensions and demographic variables on the work ability of Iranian farmers working in small farm enterprises. A cross-sectional study was conducted among 294 male farmers. The WAI and SF-36 questionnaires were used to determine work ability and health status. The effect of demographics variables on the work ability index was investigated with the independent samples t-test and one-way ANOVA. Also, multiple linear regression analysis was used to test the association between the mean WAI score and the SF-36 scales. The mean WAI score was 35.1 (SD=10.6). One-way ANOVA revealed a significant relationship between the mean WAI and age. Multiple linear regression analysis showed that work ability was more influenced by physical scales of the health dimensions, such as physical function, role-physical, and general health, whereas a lower association was found for mental scales such as mental health. The average WAI was at a moderate work ability level for the sample population of farmers in this study. Based on the WAI guidelines, improvement of work ability and identification of factors affecting it should be considered a priority in interventional programs. Given the influence of health dimensions on WAI, any intervention program for preservation and promotion work ability among the studied farmers should be based on balancing and optimizing the physical and psychosocial work environments, with a special focus on reducing physical work load.

Keywords: farmers, SF-36, Work Ability Index (WAI), Iran

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Authors: Muhammad Naveed Babur, Maria Liaqat

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Background & Objective: People with disabilities especially neurological disabilities have many unmet health and rehabilitation needs, face barriers in accessing mainstream health-care services, and consequently have poor health. There are not sufficient epidemiological studies from Pakistan which assess barriers to neurorehabilitation and ways to counter it. Objectives: The objective of the study was to determine the challenges and to evaluate the barriers for neuro-rehabilitation services in developing countries. Methods: This is Exploratory sequential qualitative study based on the Panel discussion forum in International rehabilitation sciences congress and national rehabilitation conference 2017. Panel group discussion has been conducted in February 2017 with a sample size of eight professionals including Rehabilitation medicine Physician, Physical Therapist, Speech Language therapist, Occupational Therapist, Clinical Psychologist and rehabilitation nurse working in multidisciplinary/Interdisciplinary team. A comprehensive audio-videography have been developed, recorded, transcripted and documented. Data was transcribed and thematic analysis along with characteristics was drawn manually. Data verification was done with the help of two separate coders. Results: After extraction of two separate coders following results are emerged. General category themes are disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. Barriers identified at the level are high cost, stigma, lengthy course of recovery. Hospital related barriers are lack of social support and individually tailored goal setting processes. Organizational barriers identified are lack of basic diagnostic facilities, lack of funding and human resources. Recommendations given by panelists were investment in education, capacity building, infrastructure, governance support, strategies to promote communication and realistic goals. Conclusion: It is concluded that neurorehabilitation in developing countries need attention in following categories i.e. disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. This study also revealed barriers at the level of patient, hospital, organization. Recommendations were also given by panelists.

Keywords: disability, neurorehabilitation, telerehabilitation, disability

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

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The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development

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Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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Authors: Khandoker Akib Mohammad

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While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

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Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

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Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: manihot esculenta crantz, plant architecture, dartseq, snp markers, genome-wide association study

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Paul Campbell, Nicholas Biddle

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There is a complex, endogenous relationship between individual circumstances, attitudes, and behaviour. This study uses longitudinal panel data to assess changes in social and political attitudes over a 7-year period. Attitudes are captured with the question 'what is the most important issue facing Australia today', collected at multiple time points in a longitudinal survey of 2200 Australians. Consistency of attitudes, and factors predicting change over time, are assessed. The consistency of responses has methodological implications for data collection, specifically how often such questions ought to be asked of a population. When change in attitude is observed, this study assesses the extent to which individual demographic characteristics, personality traits, and broader societal events predict change.

Keywords: attitudes, longitudinal survey analysis, personality, social values

Procedia PDF Downloads 117

Authors: Juan Jose Filgueira, Daniela Londono-Serna, Liliana Maria Hoyos

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Carnation (Dianthus caryophyllus) is one of the most important products of exportation in the floriculture industry worldwide. Fusariosis is the disease that causes the highest losses on farms, in particular the one produced by Fusarium oxysporum f.sp. dianthi, called vascular wilt. Gene identification and metabolic routes of the genes that participate in the building of the plant response to Fusarium are some of the current targets in the carnation breeding industry. The techniques for the identifying of resistant genes in the plants, is the analysis of the transcriptome obtained during the host-pathogen interaction. In this work, we report the cell transcriptome of different varieties of carnation that present differential response from Fusarium oxysporum f.sp. dianthi attack. The cells of the different hybrids produced in the outbreeding program were cultured in vitro and elicited with the parasite in a dual culture. The isolation and purification of mRNA was achieved by using affinity chromatography Oligo dT columns and the transcriptomes were obtained by using Illumina NGS techniques. A total of 85,669 unigenes were detected in all the transcriptomes analyzed and 31,000 annotations were found in databases, which correspond to 36.2%. The library construction of genic expression techniques used, allowed to recognize the variation in the expression of genes such as Germin-like protein, Glycosyl hydrolase family and Cinnamate 4-hydroxylase. These have been reported in this study for the first time as part of the response mechanism to the presence of Fusarium oxysporum.

Keywords: Carnation, Fusarium, vascular wilt, transcriptome

Procedia PDF Downloads 130

Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

Procedia PDF Downloads 297

Authors: Mohammad Hossain Mohammadi, Saif Al Ameri, Sana Ziaei, Jinane Mounsef

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Automated enumeration of the number of hand fingers is widely used in several motion gaming and distance control applications, and is discussed in several published papers as a starting block for hand recognition systems. The automated finger enumeration technique should not only be accurate, but also must have a fast response for a moving-picture input. The high performance of video in motion games or distance control will inhibit the program’s overall speed, for image processing software such as Matlab need to produce results at high computation speeds. Since an automated finger enumeration with minimum error and processing time is desired, a comparative study between two finger enumeration techniques is presented and analyzed in this paper. In the pre-processing stage, various image processing functions were applied on a real-time video input to obtain the final cleaned auto-cropped image of the hand to be used for the two techniques. The first technique uses the known morphological tool of skeletonization to count the number of skeleton’s endpoints for fingers. The second technique uses a radial distance method to enumerate the number of fingers in order to obtain a one dimensional hand representation. For both discussed methods, the different steps of the algorithms are explained. Then, a comparative study analyzes the accuracy and speed of both techniques. Through experimental testing in different background conditions, it was observed that the radial distance method was more accurate and responsive to a real-time video input compared to the skeletonization method. All test results were generated in Matlab and were based on displaying a human hand for three different orientations on top of a plain color background. Finally, the limitations surrounding the enumeration techniques are presented.

Keywords: comparative study, hand recognition, fingertip detection, skeletonization, radial distance, Matlab

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Authors: Chayaporn Kaensar

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Recently, Job Recommender Systems have gained much attention in industries since they solve the problem of information overload on the recruiting website. Therefore, we proposed Extended Personalized Job System that has the capability of providing the appropriate jobs for job seeker and recommending some suitable information for them using Data Mining Techniques and Dynamic User Profile. On the other hands, company can also interact to the system for publishing and updating job information. This system have emerged and supported various platforms such as web application and android mobile application. In this paper, User profiles, Implicit User Action, User Feedback, and Clustering Techniques in WEKA libraries have gained attention and implemented for this application. In additions, open source tools like Yii Web Application Framework, Bootstrap Front End Framework and Android Mobile Technology were also applied.

Keywords: recommendation, user profile, data mining, web and mobile technology

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Authors: Ilias Katsanis, Paraskevas Papanikos, Nikolas Zacharopoulos, Vassilis C. Moulianitis, Evgenios Scourboutis, Diamantis T. Panagiotarakos

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This paper presents aspects of the detailed design of an automated biomethane potential measurement system using CAD techniques. First, the design specifications grouped in eight sets that are used to design the design alternatives are briefly presented. Then, the major components of the final concept, as well as the design of the test, are presented. The material selection process is made using ANSYS EduPack database software. The mechanical behavior of one component developed in Creo v.5 is evaluated using finite element analysis. Finally, aspects of software development that integrate the BMP test is finally presented. This paper shows the advantages of CAD techniques in product design applied in the design of a mechatronic product.

Keywords: automated biomethane test, detail mechatronics design, materials selection, mechanical analysis

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Authors: Viriyavudh Sim, WooYoung Jung

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Damage due to high wind is not limited to load resistance components such as beam and column. The majority of damage is due to breach in the building envelope such as broken roof, window, and door. In this paper, wind fragility of window glass in residential apartment was determined to compare the difference between two window configuration models. Monte Carlo Simulation method had been used to derive damage data and analytical fragilities were constructed. Fragility of window system showed that window located in leeward wall had higher probability of failure, especially those close to the edge of structure. Between the two window models, Model 2 had higher probability of failure, this was due to the number of panel in this configuration.

Keywords: wind fragility, glass window, high rise building, wind disaster

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Authors: Jaden Lu, Olivia Lu

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Despite the remarkable advancement of solar cell technology, the challenge of optimizing total solar energy harvest efficiency persists, primarily due to significant heat loss. This excess heat not only diminishes solar panel output efficiency but also curtails its operational lifespan. A promising approach to address this issue is the conversion of surplus heat into electricity. In recent years, there is growing interest in the use of thermoelectric generators (TEG) as a potential solution. The integration of efficient TEG devices holds the promise of augmenting overall energy harvest efficiency while prolonging the longevity of solar panels. While certain research groups have proposed the integration of solar cells and TEG devices, a substantial gap between conceptualization and practical implementation remains, largely attributed to low thermal energy conversion efficiency of TEG devices. To bridge this gap and meet the requisites of practical application, a feasible strategy involves the incorporation of a substantial number of p-n junctions within a confined unit volume. However, the manufacturing of high-density TEG p-n junctions presents a formidable challenge. The prevalent solution often leads to large device sizes to accommodate enough p-n junctions, consequently complicating integration with solar cells. Recently, the adoption of 3D printing technology has emerged as a promising solution to address this challenge by fabricating high-density p-n arrays. Despite this, further developmental efforts are necessary. Presently, the primary focus is on the 3D printing of vertically layered TEG devices, wherein p-n junction density remains constrained by spatial limitations and the constraints of 3D printing techniques. This study proposes a novel device configuration featuring horizontally arrayed p-n junctions of Bi2Te3. The structural design of the device is subjected to simulation through the Finite Element Method (FEM) within COMSOL Multiphysics software. Various device configurations are simulated to identify optimal device structure. Based on the simulation results, a new TEG device is fabricated utilizing 3D Selective laser melting (SLM) printing technology. Fusion 360 facilitates the translation of the COMSOL device structure into a 3D print file. The horizontal design offers a unique advantage, enabling the fabrication of densely packed, three-dimensional p-n junction arrays. The fabrication process entails printing a singular row of horizontal p-n junctions using the 3D SLM printing technique in a single layer. Subsequently, successive rows of p-n junction arrays are printed within the same layer, interconnected by thermally conductive copper. This sequence is replicated across multiple layers, separated by thermal insulating glass. This integration created in a highly compact three-dimensional TEG device with high density p-n junctions. The fabricated TEG device is then attached to the bottom of the solar cell using thermal glue. The whole device is characterized, with output data closely matching with COMSOL simulation results. Future research endeavors will encompass the refinement of thermoelectric materials. This includes the advancement of high-resolution 3D printing techniques tailored to diverse thermoelectric materials, along with the optimization of material microstructures such as porosity and doping. The objective is to achieve an optimal and highly integrated PV-TEG device that can substantially increase the solar energy harvest efficiency.

Keywords: thermoelectric, finite element method, 3d print, energy conversion

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Authors: Alban Igwe, Ijeoma Kalu, Alloy Ezirim

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Food insecurity is a global problem, and the search for food security has assumed a central stage in the global development agenda as the United Nations currently placed zero hunger as a goal number in its sustainable development goals. Nigeria currently ranks 107th out of 113 countries in the global food security index (GFSI), a metric that defines a country's ability to furnish its citizens with food and nutrients for healthy living. Paradoxically, Nigeria is a global leader in food production, ranking 1st in yam (over 70% of global output), beans (over 41% of global output), cassava (20% of global output) and shea nuts, where it commands 53% of global output. Furthermore, it ranks 2nd in millet, sweet potatoes, and cashew nuts. It is Africa's largest producer of rice. So, it is apparent that Nigeria's food insecurity woes must relate to a factor other than food production. We investigated the nexus between food security and downstream supply chain losses in the yam industry with secondary data from the Food and Agricultural Organization (FAOSTAT) and the National Bureau of Statics for the decade 2012-2021. In analyzing the data, multiple regression techniques were used, and findings reveal that downstream losses have a strong positive correlation with food security (r = .763*) and a 58.3% variation in food security is explainable by post-downstream supply chain food losses. The study discovered that yam supply chain losses within the period under review averaged 50.6%, suggestive of the fact that downstream supply chain losses are the drainpipe and the major source of food insecurity in Nigeria. Therefore, the study concluded that there is a significant relationship between downstream supply chain losses and food insecurity and recommended the establishment of food supply chain structures and policies to enhance food security in Nigeria.

Keywords: food security, downstream supply chain losses, yam, nigeria, supply chain

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Authors: Ahmed Amin Mousa, M. Abd El Salam

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The current study presents a proposed program for acquisition the skills and techniques needed to produce concept cartoon. The proposed program has been prepared for non-specialist students who have never used neither graphics nor animating software. It was presented to postgraduates in Faculty of Education for Early Childhood, Cairo University, during the spring term of the 2014-2015 academic year. The program works in three different aspects: Drawing and images editing, sound manipulation, and creating animation. In addition, the researchers have prepared a questionnaire for measuring the quality of the concept cartoons produced by the students. The questionnaire was used as a pre-test and post-test, and at the end of the study, a significant difference was determined in favour of post-test results.

Keywords: cartoon, concept cartoon, kindergarten, animation

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Authors: Javier E. García-Gallo, Nelson J. Fonseca-Ruiz, John F. Duitama-Munoz

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Sepsis is a syndrome that occurs with physiological and biochemical abnormalities induced by severe infection and carries a high mortality and morbidity, therefore the severity of its condition must be interpreted quickly. After patient admission in an intensive care unit (ICU), it is necessary to synthesize the large volume of information that is collected from patients in a value that represents the severity of their condition. Traditional severity of illness scores seeks to be applicable to all patient populations, and usually assess in-hospital mortality. However, the use of machine learning techniques and the data of a population that shares a common characteristic could lead to the development of customized mortality prediction scores with better performance. This study presents the development of a score for the one-year mortality prediction of the patients that are admitted to an ICU with a sepsis diagnosis. 5650 ICU admissions extracted from the MIMICIII database were evaluated, divided into two groups: 70% to develop the score and 30% to validate it. Comorbidities, demographics and clinical information of the first 24 hours after the ICU admission were used to develop a mortality prediction score. LASSO (least absolute shrinkage and selection operator) and SGB (Stochastic Gradient Boosting) variable importance methodologies were used to select the set of variables that make up the developed score; each of this variables was dichotomized and a cut-off point that divides the population into two groups with different mean mortalities was found; if the patient is in the group that presents a higher mortality a one is assigned to the particular variable, otherwise a zero is assigned. These binary variables are used in a logistic regression (LR) model, and its coefficients were rounded to the nearest integer. The resulting integers are the point values that make up the score when multiplied with each binary variables and summed. The one-year mortality probability was estimated using the score as the only variable in a LR model. Predictive power of the score, was evaluated using the 1695 admissions of the validation subset obtaining an area under the receiver operating characteristic curve of 0.7528, which outperforms the results obtained with Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS) and Simplified Acute Physiology Score II (SAPSII) scores on the same validation subset. Observed and predicted mortality rates within estimated probabilities deciles were compared graphically and found to be similar, indicating that the risk estimate obtained with the score is close to the observed mortality, it is also observed that the number of events (deaths) is indeed increasing as the outcome go from the decile with the lowest probabilities to the decile with the highest probabilities. Sepsis is a syndrome that carries a high mortality, 43.3% for the patients included in this study; therefore, tools that help clinicians to quickly and accurately predict a worse prognosis are needed. This work demonstrates the importance of customization of mortality prediction scores since the developed score provides better performance than traditional scoring systems.

Keywords: intensive care, logistic regression model, mortality prediction, sepsis, severity of illness, stochastic gradient boosting

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Authors: Shin Ku Kim, Yun Ah Oh, Eun Hee Seo, Chang Min Dae, Yun Jung Bae

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Objectives: The commonly used PRESS technique in magnetic resonance spectroscopy (MRS) has a limitation of incomplete water suppression. The recently developed sLASER technique is known for its improved effectiveness in suppressing water signal. However, no prior study has compared both sequences in a normal human brain. In this study, we firstly aimed to compare the performances of both techniques in brain MRS. Materials and methods: From January 2023 to July 2023, thirty healthy participants (mean age 38 years, 17 male, 13 female) without underlying neurological diseases were enrolled in this study. All participants underwent single-voxel MRS using both PRESS and sLASER techniques on 3T MRI. Two regions-of-interest were allocated in the left medial thalamus and left parietal white matter (WM) by a single reader. The SpectroView Analysis (SW5, Philips, Netherlands) provided automatic measurements, including signal-to-noise ratio (SNR) and peak_height of water, N-acetylaspartate (NAA)-water/Choline (Cho)-water/Creatine (Cr)-water ratios, and NAA-Cr/Cho-Cr ratios. The measurements from PRESS and sLASER techniques were compared using paired T-tests and Bland-Altman methods, and the variability was assessed using coefficients of variation (CV). Results: SNR and peak_heights of the water were significantly lower with sLASER compared to PRESS (left medial thalamus, sLASER SNR/peak_height 2092±475/328±85 vs. PRESS 2811±549/440±105); left parietal WM, 5422±1016/872±196 vs. 7152±1305/1150±278; all, P<0.001, respectively). Accordingly, NAA-water/Cho-water/Cr-water ratios and NAA-Cr/Cho-Cr ratios were significantly higher with sLASER than with PRESS (all, P< 0.001, respectively). The variabilities of NAA-water/Cho-water/Cr-water ratios and Cho-Cr ratio in the left medial thalamus were lower with sLASER than with PRESS (CV, sLASER vs. PRESS, 19.9 vs. 58.1/19.8 vs. 54.7/20.5 vs. 43.9 and 11.5 vs. 16.2) Conclusion: The sLASER technique demonstrated enhanced background water suppression, resulting in increased signals and reduced variability in brain metabolite measurements of MRS. Therefore, sLASER could offer a more precise and stable method for identifying brain metabolites.

Keywords: Magnetic resonance spectroscopy, Brain, sLASER, PRESS

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Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu

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This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.

Keywords: distributed model, flexible manipulator, observer, robot control

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Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid

Abstract:

Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.

Keywords: optimization, harmony search algorithm, MATLAB, electronic

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Authors: Hyun-Woo Cho

Abstract:

Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Faisal Alsaaq

Abstract:

Hydrographic surveys have traditionally relied on the availability of tide information for the reduction of sounding observations to a common datum. In most cases, tide information is obtained from tide gauge observations and/or tide predictions over space and time using local, regional or global tide models. While the latter often provides a rather crude approximation, the former relies on tide gauge stations that are spatially restricted, and often have sparse and limited distribution. A more recent method that is increasingly being used is Global Navigation Satellite System (GNSS) positioning which can be utilised to monitor height variations of a vessel or buoy, thus providing information on sea level variations during the time of a hydrographic survey. However, GNSS heights obtained under the dynamic environment of a survey vessel are affected by “non-tidal” processes such as wave activity and the attitude of the vessel (roll, pitch, heave and dynamic draft). This research seeks to examine techniques that separate the tide signal from other non-tidal signals that may be contained in GNSS heights. This requires an investigation of the processes involved and their temporal, spectral and stochastic properties in order to apply suitable recovery techniques of tide information. In addition, different post-mission and near real-time GNSS positioning techniques will be investigated with focus on estimation of height at ocean. Furthermore, the study will investigate the possibility to transfer the chart datums at the location of tide gauges.

Keywords: hydrography, GNSS, datum, tide gauge

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Authors: Varsha Pandurang Nagargoje, K. S. James

Abstract:

Background: Social participation is considered as one of the central components of successful and healthy aging. This study aimed to examine the moderating role of marital status and living arrangement in the relationship between social participation and life satisfaction and other potential factors associated with life satisfaction of Indian older adults. Method: For analyses, the nationally representative study sample of 31,464 adults aged ≥60 years old was extracted from the Longitudinal Ageing Study in India (LASI) wave 1, 2017-18. Descriptive statistics and bivariate analysis have been performed to determine the proportion of life satisfaction. The first set of multivariable linear regression analyses examined Diener’s Satisfaction with Life Scale and its association with various predictor variables, including social participation, marital status, living arrangements, socio-demographic, economic, and health-related variables. Further, the second and third sets of regression investigated the moderating role of marital status and living arrangements respectively in the association of social participation and level of life satisfaction among Indian older adults. Results: Overall, the proportion of life satisfaction among older men was relatively higher than women counterparts in most background characteristics. Regression results stressed the importance of older adults’ involvement in social participation [β = 0.39, p < 0.05], being in marital union [β = 0.68, p < 0.001] and co-residential living arrangements either only with spouse [β = 1.73, p < 0.001] or with other family members [β = 2.18, p < 0.001] for the improvement of life satisfaction. Results also showed that some factors were significant for life satisfaction: in particular, increased age, having a higher level of educational status, MPCE quintile, and caste category. Higher risk of life dissatisfaction found among Indian older adults who were exposed to vulnerabilities like consuming tobacco, poor self-rated health, having difficulty in performing ADL and IADL were of major concern. The interaction effect of social participation with marital status or with living arrangements explained that currently married older individuals, and those older adults who were either co-residing with their spouse only or with other family members irrespective of their involvement in social participation remained an important modifiable factor for life satisfaction. Conclusion: It would be crucial for policymakers and practitioners to advocate social policy programs and service delivery oriented towards meaningful social connections, especially for those Indian older adults who were staying alone or currently not in the marital union to enhance their overall life satisfaction.

Keywords: Indian, older adults, social participation, life satisfaction, marital status, living arrangement

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Authors: Jim J. Catina, Jackee M. Gwynn, Jin S. Kang

Abstract:

Additive manufacturing (AM) for hybrid rocket engines is becoming increasingly attractive due to its ability to create complex grain configurations with improved regression rates when compared to cast grains. However, the presence of microvoids in parts produced through the additive manufacturing method of Fused Deposition Modeling (FDM) results in a lower fuel density and is believed to cause a decrease in regression rate compared to ideal performance. In this experiment, FDM was used to create hybrid rocket fuel grains with a star configuration composed of acrylonitrile butadiene styrene (ABS). Testing was completed to determine the effect of heat treatment as a post-processing method to improve the combustion performance of hybrid rocket fuel grains manufactured by FDM. For control, three ABS star configuration grains were printed using FDM and hot fired using gaseous oxygen (GOX) as the oxidizer. Parameters such as thrust and mass flow rate were measured. Three identical grains were then heat treated to varying degrees and hot fired under the same conditions as the control grains. This paper will quantitatively describe the amount of improvement in engine performance as a result of heat treatment of the AM hybrid fuel grain. Engine performance is measured in this paper by specific impulse, which is determined from the thrust measurements collected in testing.

Keywords: acrylonitrile butadiene styrene, additive manufacturing, fused deposition modeling, heat treatment

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Authors: Rodrigo Aguiar, Adelino Ferreira

Abstract:

Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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