Search results for: predictive mining

Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Yuliya Kovalenko

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Given the social nature of people, it is interesting to explore strategies of responding to psycho-traumatic situations in individuals of different ethnic and religious identity. This would allow to substantially expand the idea of human behavior in general, and coping behavior, in particular. This paper investigated the weighted impact of ethnic and religious identities on the patterns of coping behavior. This cross-cultural research empirically revealed intergroup differences in coping strategies and behavior in the samples of young students and teachers of different ethnic identities (Egyptians N=216 and Ukrainians N=109) and different religious identities (Egyptian Muslims N=147 and Christians, including Egyptian Christians N=68 and Ukrainian Christians N = 109). The empirical data were obtained using the questionnaires SACS and COPE. Statistical analysis and interpretation of the results were performed with IBM SPSS-23.0. It was found that, compared to the religious identity, the ethnic identity of the subjects appeared more predictive of coping behavior. It was shown that the constant exchange of information and the unity of biological and social contributed to a more homogeneous picture in the society where Christians and Muslims were integrated into a single cultural space. It was concluded that depending on their ethnic identity, individuals would form a specific hierarchy of coping strategies resulting in a specific pattern of coping with certain stressors. The Egyptian subjects revealed the following pattern of coping with various kinds of academic stress: 'seeking social support', 'problem solving', 'adapting', 'seeking information'. The coping pattern demonstrated by the Ukrainian subjects could be presented as 'seeking information', 'adapting', 'seeking social support', 'problem solving'. There was a tendency in the group of Egyptians to engage in more collectivist coping strategies (with the predominant coping strategy 'religious coping'), in contrast to the Ukrainians who displayed more individualistic coping strategies (with 'planning' and 'active coping' as the mostly used coping strategies). At the same time, it was obvious that Ukrainians should not be unambiguously attributed to the individualistic coping behavior due to their reliance on 'seeking social support' and 'social contact'. The final conclusion was also drawn from the peculiarities of developing religious identity, including religiosity, in Egyptians (formal religious education of both Muslims and Christians) and Ukrainians (more spontaneous process): Egyptians seem to learn to resort to the religious coping, which could be an indication that, in principle, it is possible and necessary to train individuals in desirable coping behavior.

Keywords: coping behavior, cross-cultural research, ethnic and religious identity, hierarchical pattern of coping

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Authors: Calvin Stephen, Biswajit Basu, Aonghus McNabola

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Market liberalization in the power sector has led to the emergence of micro-hydropower schemes that are dependent on the use of pumps-as-turbines in applications that were not suitable as potential hydropower sites in earlier years. These applications include energy recovery in water supply networks, sewage systems, irrigation systems, alcohol breweries, underground mining and desalination plants. As a result, there has been an accelerated adoption of pumpsas-turbine technology due to the economic advantages it presents in comparison to the conventional turbines in the micro-hydropower space. The performance of this machines under cavitation conditions, however, is not well understood as there is a deficiency of knowledge in literature focused on their turbine mode of operation. In hydraulic machines, cavitation is a common occurrence which needs to be understood to safeguard them and prolong their operation life. The overall purpose of this study is to investigate the effects of cavitation on the performance of a pumps-as-turbine system over its entire operating range. At various operating speeds, the cavitating region is identified experimentally while monitoring the effects this has on the power produced by the machine. Initial results indicate occurrence of cavitation at higher flow rates for lower operating speeds and at lower flow rates at higher operating speeds. This implies that for cavitation free operation, low speed pumps-as-turbine must be used for low flow rate conditions whereas for sites with higher flow rate conditions high speed turbines should be adopted. Such a complete understanding of pumps-as-turbine suction performance can aid avoid cavitation induced failures hence improved reliability of the micro-hydropower plant.

Keywords: cavitation, micro-hydropower, pumps-as-turbine, system design

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Authors: Osama Moustafa Zayed

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Aim of the work: To evaluate the effectiveness of venous glucose, levels of serum lactate and base deficit in polytraumatized patients as simple parameters to predict the mortality in these patients. Compared to the predictive value of Trauma and injury severity (TRISS) and Acute Physiology And Chronic Health Evaluation IV (APACHE IV). Introduction: Trauma is a serious global health problem, accounting for approximately one in 10 deaths worldwide. Trauma accounts for 5 million deaths per year. Prediction of mortality in trauma patients is an important part of trauma care. Several trauma scores have been devised to predict injury severity and risk of mortality. The trauma and injury severity score (TRISS) was most common used. Regardless of the accuracy of trauma scores, is based on an anatomical description of every injury and cannot be assigned to the patients until a full diagnostic procedure has been performed. So we hypothesized that alterations in admission glucose, lactate levels and base deficit would be an early and easy rapid predictor of mortality. Patient and Method: a comparative cross-sectional study. 282 Polytraumatized patients attended to the Emergency Department(ED) of the Suez Canal university Hospital constituted. The period from 1/1/2012 to 1/4/2013 was included. Results: We found that the best cut off value of TRISS probability of survival score for prediction of mortality among poly-traumatized patients is = 90, with 77% sensitivity and 89% specificity using area under the ROC curve (0.89) at (95%CI). APACHE IV demonstrated 67% sensitivity and 95% specificity at 95% CI at cut off point 99. The best cutoff value of Random Blood Sugar (RBS) for prediction of mortality was>140 mg/dl, with 89%, sensitivity, 49% specificity. The best cut off value of base deficit for prediction of mortality was less than -5.6 with 64% sensitivity, 93% specificity. The best cutoff point of lactate for prediction of mortality was > 2.6 mmol/L with 92%, sensitivity, 42% specificity. Conclusion: According to our results from all evaluated predictors of mortality (laboratory and scores) and mortality based on the estimated cutoff values using ROC curves analysis, the highest risk of mortality was found using a cutoff value of 90 in TRISS score while with laboratory parameters the highest risk of mortality was with serum lactate > 2.6 . Although that all of the three parameter are accurate in predicting mortality in poly-traumatized patients and near with each other, as in serum lactate the area under the curve 0.82, in BD 0.79 and 0.77 in RBS.

Keywords: APACHE IV, emergency department, polytraumatized patients, serum lactate

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Authors: L. Hoade, O. O. Onafowokan, K. Anderson, G. E. Bartlett, E. D. Fern, M. R. Norton, R. G. Middleton

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Aims: Femoroacetabular impingement (FAI) was first recognised as a potential driver for hip pain at the turn of the last millennium. While there is an increasing trend towards surgical management of FAI by arthroscopic means, open surgical hip dislocation and debridement (SHD) remains the Gold Standard of care in terms of reported outcome measures. (1) Long-term functional and survivorship outcomes of SHD as a treatment for FAI are yet to be sufficiently reported in the literature. This study sets out to help address this imbalance. Methods: We undertook a retrospective review of our institutional database for all patients who underwent SHD for FAI between January 2003 and December 2008. A total of 223 patients (241 hips) were identified and underwent a ten year review with a standardised radiograph and patient-reported outcome measures questionnaire. The primary outcome measure of interest was survivorship, defined as progression to total hip arthroplasty (THA). Negative predictive factors were analysed. Secondary outcome measures of interest were survivorship to further (non-arthroplasty) surgery, functional outcomes as reflected by patient reported outcome measure scores (PROMS) scores, and whether a learning curve could be identified. Results: The final cohort consisted of 131 females and 110 males, with a mean age of 34 years. There was an overall native hip joint survival rate of 85.4% at ten years. Those who underwent a THA were significantly older at initial surgery, had radiographic evidence of preoperative osteoarthritis and pre- and post-operative acetabular undercoverage. In those whom had not progressed to THA, the average Non-arthritic Hip Score and Oxford Hip Score at ten year follow-up were 72.3% and 36/48, respectively, and 84% still deemed their surgery worthwhile. A learning curve was found to exist that was predicated on case selection rather than surgical technique. Conclusion: This is only the second study to evaluate the long-term outcomes (beyond ten years) of SHD for FAI and the first outside the originating centre. Our results suggest that, with correct patient selection, this remains an operation with worthwhile outcomes at ten years. How the results of open surgery compared to those of arthroscopy remains to be answered. While these results precede the advent of collison software modelling tools, this data helps set a benchmark for future comparison of other techniques effectiveness at the ten year mark.

Keywords: femoroacetabular impingement, hip pain, surgical hip dislocation, hip debridement

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Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

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Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon

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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.

Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre

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Authors: Hicham Amar, Mustapha El Ghorfi, Yassine Taha, Abdellatif Elghali, Rachid Hakkou, Mostafa Benzaazoua

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Phosphate mine waste rock (PMWR) generated during ore extraction is continuously increasing, resulting in a significant environmental footprint. The main objectives of this study consist of i) elaboration of the sampling strategy of PMWR piles, ii) a mineralogical and chemical characterization of PMWR piles, and iii) 3D block model creation to evaluate the potential valorization of the existing PMWR. Destructive drilling using reverse circulation from 13 drills was used to collect samples for chemical (X-ray fluorescence analysis) and mineralogical assays. The 3D block model was created based on the data set, including chemical data of the realized drills using Datamine RM software. The optical microscopy observations showed that the sandy phosphate from drills in the PMWR piles is characterized by the abundance of carbonate fluorapatite with the presence of calcite, dolomite, and quartz. The mean grade of composite samples was around 19.5±2.7% for P₂O₅. The mean grade of P₂O₅ exhibited an increasing tendency by depth profile from bottom to top of PMWR piles. 3D block model generated with chemical data confirmed the tendency of the mean grades’ variation and may allow a potential selective extraction according to %P₂O₅. The 3D block model of P₂O₅ grade is an efficient sampling approach that confirmed the variation of P₂O₅ grade. This integrated approach for PMWR management will be a helpful tool for decision-making to recover the residual phosphate, adopting the circular economy and sustainability in the phosphate mining industry.

Keywords: 3D modelling, reverse circulation drilling, circular economy, phosphate mine waste rock, sampling

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Natalia Alonso-Alberca, Ana I. Vergara

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From the very first years of their life, children are confronted with situations in which they need to deal with emotions. The family provides the first emotional experiences, and it is in the family context that children usually take their first steps towards acquiring emotion knowledge. Parents play a key role in this important task, helping their children develop emotional skills that they will need in challenging situations throughout their lives. Specifically, mothers are models imitated by their children. They create specific spatial and temporal contexts in which children learn about emotions, their causes, consequences, and complexity. This occurs not only through what mothers say or do directly to the child. Rather, it occurs, to a large extent, through the example that they set using their own emotional skills. The aim of the current study was to analyze how maternal abilities to perceive and to manage emotions influence children’s emotion knowledge, specifically, their emotion situation knowledge, taking into account the role played by the mother’s personality, the time spent together, and controlling the effect of age, sex and the child’s verbal abilities. Participants were 153 children from 4 schools in Spain, and their mothers. Children (41.8% girls)age range was 35 - 72 months. Mothers (N = 140) age (M = 38.7; R = 27-49). Twelve mothers had more than one child participating in the study. Main variables were the child´s emotion situation knowledge (ESK), measured by the Emotion Matching Task (EMT), and receptive language, using the Picture Vocabulary Test. Also, their mothers´ Emotional Intelligence (EI), through the Mayer, Salovey, Caruso Emotional Intelligence Test (MSCEIT) and personality, with The Big Five Inventory were analyzed. The results showed that the predictive power of maternal emotional skills on ESK was moderated by the mother’s personality, affecting both the direction and size of the relationships detected: low neuroticism and low openness to experience lead to a positive influence of maternal EI on children’s ESK, while high levels in these personality dimensions resulted in a negative influence on child´s ESK. The time that the mother and the child spend together was revealed as a positive predictor of this EK, while it did not moderate the influence of the mother's EI on child’s ESK. In light of the results, we can infer that maternal EI is linked to children’s emotional skills, though high level of maternal EI does not necessarily predict a greater degree of emotionknowledge in children, which seems rather to depend on specific personality profiles. The results of the current study indicate that a good level of maternal EI does not guarantee that children will learn the emotional skills that foster prosocial adaptation. Rather, EI must be accompanied by certain psychological characteristics (personality traits in this case).

Keywords: emotional intelligence, emotion situation knowledge, mothers, personality, young children

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Authors: P. Thachitasing, N. Jansawang, W. Rakrai, T. Santiboon

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The aim of this study is to investigate of the comparing the instructional design models between the Think-Pair-Share and Conventional Learning (5E Inquiry Model) Processes to enhance students’ learning achievements and their problem solving skills on stoichiometry issue for concerning the 2-instructional method with a sample consisted of 80 students in 2 classes at the 11th grade level in Chaturaphak Phiman Ratchadaphisek School. Students’ different learning outcomes in chemistry classes with the cluster random sampling technique were used. Instructional Methods designed with the 40-experimenl student group by Think-Pair-Share process and the 40-controlling student group by the conventional learning (5E Inquiry Model) method. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of Think-Pair-Share and STEM Education Method, students’ learning achievements and their problem solving skills were assessed with the pretest and posttest techniques, students’ outcomes of their instructional the Think-Pair-Share (TPSM) and the STEM Education Methods were compared. Statistically significant was differences with the paired t-test and F-test between posttest and pretest technique of the whole students in chemistry classes were found, significantly. Associations between student learning outcomes in chemistry and two methods of their learning to students’ learning achievements and their problem solving skills also were found. The use of two methods for this study is revealed that the students perceive their learning achievements to their problem solving skills to be differently learning achievements in different groups are guiding practical improvements in chemistry classrooms to assist teacher in implementing effective approaches for improving instructional methods. Students’ learning achievements of mean average scores to their controlling group with the Think-Pair-Share Model (TPSM) are lower than experimental student group for the STEM education method, evidence significantly. The E1/E2 process were revealed evidence of 82.56/80.44, and 83.02/81.65 which results based on criteria are higher than of 80/80 standard level with the IOC, consequently. The predictive efficiency (R2) values indicate that 61% and 67% and indicate that 63% and 67% of the variances in chemistry classes to their learning achievements on posttest in chemistry classes of the variances in students’ problem solving skills to their learning achievements to their chemistry classrooms on Stoichiometry issue with the posttest were attributable to their different learning outcomes for the TPSM and STEMe instructional methods.

Keywords: comparisons, students’ learning achievements, think-pare-share model (TPSM), stem education, problem solving skills, chemistry classes, stoichiometry issue

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Authors: Alexandre Chagnes

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Lithium-ion battery is the technology of choice in the development of electric vehicles. This technology is now mature, although there are still many challenges to increase their energy density while ensuring an irreproachable safety of use. For this goal, it is necessary to develop new cathodic materials that can be cycled at higher voltages and electrolytes compatible with these materials. But the challenge does not only concern the production of efficient batteries for the electrochemical storage of energy since lithium-ion battery technology relies on the use of critical and/or strategic value resources. It is, therefore, crucial to include Lithium-ion batteries development in a circular economy approach very early. In particular, optimized recycling and reuse of battery components must both minimize their impact on the environment and limit geopolitical issues related to tensions on the mineral resources necessary for lithium-ion battery production. Although recycling will never replace mining, it reduces resource dependence by ensuring the presence of exploitable resources in the territory, which is particularly important for countries like France, where exploited or exploitable resources are limited. This conference addresses the development of a new hydrometallurgical process combining leaching of cathodic material from spent lithium-ion battery in acidic chloride media and solvent extraction process. Most of recycling processes reported in the literature rely on the sulphate route, and a few studies investigate the potentialities of the chloride route despite many advantages and the possibility to develop new chemistry, which could get easier the metal separation. The leaching mechanisms and the solvent extraction equilibria will be presented in this conference. Based on the comprehension of the physicochemistry of leaching and solvent extraction, the present study will introduce a new hydrometallurgical process for the production of cobalt, nickel, manganese and lithium from spent cathodic materials.

Keywords: lithium-ion battery, recycling, hydrometallurgy, leaching, solvent extraction

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Authors: El-Said. I. Shabana, Mohammad S. Tayeb, Maher M. T. Qutub, Abdulraheem A. Kinsara

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Usually, phosphate deposits contain ²³⁸U and ²³²Th in addition to their decay products. Due to their different pathways in the environment, the ²³⁸U/²³²Th activity concentration ratio usually found to be greater than unity in phosphate sediments. The presence of these radionuclides creates a potential need to control exposure of workers in the mining and processing activities of the phosphate minerals in accordance with IAEA safety standards. The greatest dose to workers comes from exposure to radon, especially ²²²Rn from the uranium series, and has to be controlled. In this regard, radon (²²²Rn) was measured in the atmosphere (indoor and outdoor) of Al-Jalamid phosphate-mines working area using a portable radon-measurement instrument RAD7, in a purpose of radiation protection. Radon was measured in 61 sites inside the open phosphate mines, the phosphate upgrading facility (offices and rooms of the workers, and in some open-air sites) and in the dwellings of the workers residence-village that lies at about 3 km from the mines working area. The obtained results indicated that the average indoor radon concentration was about 48.4 Bq/m³. Inside the upgrading facility, the average outdoor concentrations were 10.8 and 9.7 Bq/m³ in the concentrate piles and crushing areas, respectively. It was 12.3 Bq/m³ in the atmosphere of the open mines. These values are comparable with the global average values. Based on the average values, the annual effective dose due to radon inhalation was calculated and risk estimates have been done. The average annual effective dose to workers due to the radon inhalation was estimated by 1.32 mSv. The potential excess risk of lung cancer mortality that could be attributed to radon, when considering the lifetime exposure, was estimated by 53.0x10^-4. The results have been discussed in detail.

Keywords: dosimetry, environmental monitoring, phosphate deposits, radiation protection, radon

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Authors: Krzysztof J. Czarnocki, E. Czarnocka, K. Szaniawska

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Main goal of the research project is Scaffold Use Risk Assessment Model (SURAM) formulation, developed for the assessment of risk levels as a various construction process stages with various work trades. Finally, in 2016, the project received financing by the National Center for Research and development according to PBS3/A2/19/2015–Research Grant. The presented data, calculations and analyzes discussed in this paper were created as a result of the completion on the first and second phase of the PBS3/A2/19/2015 project. Method: One of the arms of the research project is the assessment of worker visual concentration on the sight zones as well as risky visual point inadequate observation. In this part of research, the mobile eye-tracker was used to monitor the worker observation zones. SMI Eye Tracking Glasses is a tool, which allows us to analyze in real time and place where our eyesight is concentrated on and consequently build the map of worker's eyesight concentration during a shift. While the project is still running, currently 64 construction sites have been examined, and more than 600 workers took part in the experiment including monitoring of typical parameters of the work regimen, workload, microclimate, sound vibration, etc. Full equipment can also be useful in more advanced analyses. Because of that technology we have verified not only main focus of workers eyes during work on or next to scaffolding, but we have also examined which changes in the surrounding environment during their shift influenced their concentration. In the result of this study it has been proven that only up to 45.75% of the shift time, workers’ eye concentration was on one of three work-related areas. Workers seem to be distracted by noisy vehicles or people nearby. In opposite to our initial assumptions and other authors’ findings, we observed that the reflective parts of the scaffoldings were not more recognized by workers in their direct workplaces. We have noticed that the red curbs were the only well recognized part on a very few scaffoldings. Surprisingly on numbers of samples, we have not recognized any significant number of concentrations on those curbs. Conclusion: We have found the eye-tracking method useful for the construction of the SURAM model in the risk perception and worker’s behavior sub-modules. We also have found that the initial worker's stress and work visual conditions seem to be more predictive for assessment of the risky developing situation or an accident than other parameters relating to a work environment.

Keywords: accident assessment model, eye tracking, occupational safety, scaffolding

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Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

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Authors: Abraham Addo-Bediako, Sophy Nukeri, Tebatso Mmako

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Many freshwater ecosystems have been subjected to prolonged and cumulative pollution as a result of human activities such as mining, agricultural, industrial and human settlements in their catchments. The objective of this study was to investigate spatial variability of heavy metal pollution of sediments and possible sources of pollutants in two streams of the Olifants River System, South Africa. Stream sediments were collected and analysed for Arsenic (As), Cadmium (Cd), Chromium (Cr), Copper (Cu), Lead (Pb), Nickel (Ni) and Zinc (Zn) concentrations using inductively coupled plasma-mass mass spectrometry (ICP-MS). In both rivers, As, Cd, Cu, Pb and Zn fell within the concentration ranges recommended by CCME and ANZECC, while the concentrations of Cr and Ni exceeded the standards; the results indicated that Cr and Ni in the sediments originated from human activities and not from natural geological background. The index of geo-accumulation (Igeo) was used to assess the degree of pollution. The results of the geo-accumulation index evaluation showed that Cr and Ni were present in the sediments of the rivers at moderately to extremely polluted levels, while As, Cd, Cu, Pb and Zn existed at unpolluted to moderately polluted levels. Generally, heavy metal concentrations increased along the gradient in the rivers. The high concentrations of Cr and Ni in both rivers are of great concern, as previously these two rivers were classified to be supplying the Olifants River with water of good quality. There is a critical need, therefore to monitor heavy metal concentrations and distributions, as well as a comprehensive plan to prevent health risks, especially those communities still reliant on untreated water from the rivers, as sediment pollution may pose a risk of secondary water pollution under sediment disturbance and/or changes in the geo-chemistry of sediments.

Keywords: geo-accumulation index, heavy metals, sediment pollution, water quality

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

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Authors: Louise Bunce, Jill Childs, Adam J. Lonsdale, Naomi King

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A major concern for the Social Work profession concerns the frequency of burn-out and high turnover of staff. The characteristic of resilience has been identified as playing a crucial role in social workers’ ability to have a satisfying and successful career. Thus a critical role for social work education is to develop resilience in social work students. We currently need to know more about how to train resilient social workers who will also increase the academic standing of the profession. The specific aim of this research was to quantify characteristics that may contribute towards resilience and academic success among student social workers in order to mitigate against the problems of burn-out and low academic standing. These three characteristics were competence (effectiveness at mastering the environment), autonomy (sense of control and free will), and relatedness (interacting and connecting with others), as specified in Self-Determination Theory (SDT). When these three needs are satisfied, we experience higher degrees of motivation to succeed and wellbeing. Thus when these three needs are met in social work students, they have the potential to raise academic standards and promote wellbeing characteristics that contribute to the development of resilience. The current study tested the hypothesis that higher levels of autonomy, competence, and relatedness, as defined by SDT, will predict levels of academic success and resilience in social work students. Two hundred and ten social work students studying at a number of universities completed well-established questionnaires to assess autonomy, competence, and relatedness, level of academic performance and resilience (The Brief Resilience Scale). In this scale, students rated their agreement with items e.g., ‘I bounce back quickly after hard times’ and ‘I usually come through difficult times with little struggle’. After controlling for various factors, including age, gender, ethnicity, and course (undergraduate or postgraduate) preliminary analysis revealed that the components of SDT provided useful predictive value for academic success and resilience. In particular, autonomy and competence provided a useful predictor of academic success while relatedness was a particularly useful predictor of resilience. This study demonstrated that SDT provides a valuable framework for helping to understand what predicts academic success and resilience among social work students. This is relevant because the psychological needs for autonomy, competence and relatedness can be affected by external social and cultural pressures, thus they can be improved by the right type of supportive teaching practices and educational environments. These findings contribute to the growing evidence-base to help build an academic and resilient social worker student body and workforce.

Keywords: education, resilience, self-determination theory, student social workers

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Authors: Gwendolyn Royal-Smith

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Cocaine ranks as one of the world’s most addictive and commonly abused stimulant drugs. Recent evidence indicates that the abuse of cocaine has risen so quickly among females that this group now accounts for about 40 percent of all users in the United States. Neuropsychological studies have demonstrated that specific neural activation patterns carry higher risks for neurocognitive and executive function in cocaine addicted females thereby increasing their vulnerability for poorer treatment outcomes and more frequent post-treatment relapse when compared to males. This study examined secondary data with a convenience sample of 164 cocaine addicted male and females to assess neurocognitive and executive function. The principal objective of this study was to assess whether individual performance on the Stroop Word Color Task is predictive of treatment success by gender. A second objective of the study evaluated whether individual performance employing neurocognitive measures including the Stroop Word-Color task, the Rey Auditory Verbal Learning Test (RALVT), the Iowa Gambling Task, the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale (FrSBE) test demonstrated differences in neurocognitive and executive function performance by gender. Logistic regression models were employed utilizing a covariate adjusted model application. Initial analyses of the Stroop Word color tasks indicated significant differences in the performance of males and females, with females experiencing more challenges in derived interference reaction time and associate recall ability. In early testing including the Rey Auditory Verbal Learning Test (RALVT), the number of advantageous vs disadvantageous cards from the Iowa Gambling Task, the number of perseverance errors from the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale, results were mixed with women scoring lower in multiple indicators in both neurocognitive and executive function.

Keywords: cocaine addiction, gender, neuropsychology, neurocognitive, executive function

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Authors: Mir Md Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soils contaminated with metals, e.g., copper (Cu), zinc (Zn) and nickel (Ni) are one of the main global environmental problems. Zn is an important element for plant growth, but excess levels may become a threat to plant survival. Soils polluted with metals may also pose risks and hazards to human health. Afforestation based on short rotation Salix crops may be a good solution for the reduction of metals toxicity levels in the soil and in ecosystem restoration of severely polluted sites. In a greenhouse experiment, plant growth and zinc (Zn) uptake by four Salix cultivars grown in Zn contaminated soils collected from a mining area in Finland were tested to assess their suitability for phytoextraction. The sequential extraction technique and inductively coupled plasma‒mass spectrometry (ICP–MS) were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The cultivars displayed resistance to heavily polluted soils throughout the whole experiment. After uptake, the total mean Zn concentrations ranged from 776 to 1823 mg kg⁻¹. The average uptake percentage of Zn across all cultivars and treatments ranged from 97 to 223%. Lime and wood ash addition showed a significant effect on plant dry biomass growth and metal uptake percentage of Zn in most of the cultivars. The results revealed that Salix cultivars have the potential to accumulate and take up significant amounts of Zn. Ecological restoration of polluted soils could be environmentally favorable in conjunction with economically profitable practices, such as forestry and bioenergy production. As such, the utilization of Salix for phytoextraction and bioenergy purposes is of considerable interest.

Keywords: lime, phytoextraction, Salix, wood ash, zinc

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Authors: Adeola Ibukunoluwa Samuel, Afsoon Kazerouni

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Industrial mineral kaolin has many favourable properties such as colour, shape, softness, non-abrasiveness, natural whiteness, as well as chemical stability. It occurs extensively in North of Bedford road Grahamstown, South Africa. The relationship between both the physical and chemical properties as lead to its application in the production of certain industrial products which are used by the public; this includes the prospect of production of paper, ceramics, rubber, paint, and plastics. Despite its interesting economic potentials, kaolinite clay mineral remains undermined, and this is threatening its sustainability in the mineral industry. This research study focuses on a detailed evaluation of the kaolinite mineral and possible ways to increase its lifespan in the industry. The methods employed for this study includes petrographic microscopy analysis, X-ray powder diffraction analysis (XRD), and proper field reconnaissance survey. Results emanating from this research include updated geological information on Grahamstown. Also, mineral transformation phases such as quartz, kaolinite, calcite and muscovite were identified in the clay samples. Petrographic analysis of the samples showed that the study area has been subjected to intense tectonic deformation and cement replacement. Also, different dissolution patterns were identified on the Grahamstown kaolinitic clay deposits. Hence incorporating analytical studies and data interpretations, possible ways such as the establishment of processing refinery near mining plants, which will, in turn, provide employment for the locals and land reclamation is suggested. In addition, possible future sustainable industrial applications of the clay minerals seem to be possible if additives, cellulosic wastes are used to alter the clay mineral.

Keywords: kaolinite, industrial use, sustainability, Grahamstown, clay minerals

Procedia PDF Downloads 181

Authors: Bahaa Eldin A. Fouda, Khaled N. Yossef, Mohamed Elhosseny, Ahmed Lotfy, Mohamed Salama, Mohamed Sobh

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Developmental neurotoxicity (DNT) entails the toxic effects imparted by various chemicals on the brain during the early childhood period. As human brains are vulnerable during this period, various chemicals would have their maximum effects on brains during early childhood. Some toxicants have been confirmed to induce developmental toxic effects on CNS e.g. lead, however; most of the agents cannot be identified with certainty due the defective nature of predictive toxicology models used. A novel alternative method that can overcome most of the limitations of conventional techniques is the use of 3D neurospheres system. This in-vitro system can recapitulate most of the changes during the period of brain development making it an ideal model for predicting neurotoxic effects. In the present study, we verified the possible DNT of epoxomicin which is a naturally occurring selective proteasome inhibitor with anti-inflammatory activity. Rat neural progenitor cells were isolated from rat embryos (E14) extracted from placental tissue. The cortices were aseptically dissected out from the brains of the fetuses and the tissues were triturated by repeated passage through a fire-polished constricted Pasteur pipette. The dispersed tissues were allowed to settle for 3 min. The supernatant was, then, transferred to a fresh tube and centrifuged at 1,000 g for 5 min. The pellet was placed in Hank’s balanced salt solution cultured as free-floating neurospheres in proliferation medium. Two doses of epoxomicin (1µM and 10µM) were used in cultured neuropsheres for a period of 14 days. For proliferation analysis, spheres were cultured in proliferation medium. After 0, 4, 5, 11, and 14 days, sphere size was determined by software analyses. The diameter of each neurosphere was measured and exported to excel file further to statistical analysis. For viability analysis, trypsin-EDTA solution were added to neurospheres for 3 min to dissociate them into single cells suspension, then viability evaluated by the Trypan Blue exclusion test. Epoxomicin was found to affect proliferation and viability of neuropsheres, these effects were positively correlated to doses and progress of time. This study confirms the DNT effects of epoxomicin on 3D neurospheres model. The effects on proliferation suggest possible gross morphologic changes while the decrease in viability propose possible focal lesion on exposure to epoxomicin during early childhood.

Keywords: neural progentor cells, epoxomicin, neurosphere, medical and health sciences

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Authors: Teguh Nurhidayat, Nurhamid, Dicky Muslim, Zufialdi Zakaria, Irvan Sophian

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This paper presents the role of climate change as the factor that induces landslide. Case study is located at Lahat Regency, South Sumatera Province, Indonesia. Study area has high economic value of coal reserves (mostly subbituminous – bituminous), which is developable for open pit coal mining in the future. Seams are found in Muara Enim Formation. This formation is at south Sumatera basin which is formed at Tertiary as a result of collision between the indian plate and eurasian plate. South Sumatera basin which is a basin located in back arc basin. This study aims to unravel the relationship between slope stability with different season condition in tropical climate. Undisturbed soil samples were obtained in the field along with other geological data. Laboratory works were carried out to obtain physical and mechanical properties of soils. Methodology to analyze slope stability is bishop method. Bishop methods are used to identify safety factor of slope. Result shows that slopes in rainy season conditions are more prone to landslides than in dry season. In the dry seasons with moisture content is 22.65%, safety factor is 1.28 the slope in stable condition. If rain is approaching with moisture content increasing to 97.8%, the slope began to be critical. On wet condition groundwater levels is increased, followed by γ (unit weight), c (cohesion), and φ (angle of friction) at 18.04, 5,88 kN/m2, and 28,04°, respectively, which ultimately determines the security factor FS to be 1.01 (slope in unstable conditions).

Keywords: rainfall, moisture content, slope analysis, landslide prone

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Authors: Gor Muradyan

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The paper is about friction and wear, including mechanisms, modeling, characterization, measurement and testing case in Bangladesh. Bangladesh is a country under development, A lot of people live here, approximately 145 million. The territory of this country is very small. Therefore buildings are very close to each other. As the pipe lines are very old, and people get almost dirty water, there are a lot of ongoing projects under ADB. In those projects the contractors using HDD machines (Horizontal Directional Drilling ) and grundoburst. These machines are working underground. As ground in Bangladesh is very sludge, machine can't work relevant because of big friction in the soil. When drilling works are finished machine is pulling the pipe underground. Very often the pulling of the pipes becomes very complicated because of the friction. Therefore long section of the pipe laying can’t be done because of a big friction. In that case, additional problems rise, as well as additional work must be done. As we mentioned above it is not possible to do big section of the pipe laying because of big friction in the soil, Because of this it is coming out that contractors must do more joints, more pressure test. It is always connected with additional expenditure and losing time. This machine can pull in 75 mm to 500 mm pipes connected with the soil condition. Length is possible till 500m related how much friction it will had on the puller. As less as much it can pull. Another machine grundoburst is not working at this soil condition at all. The machine is working with air compressor. This machine are using for the smaller diameter pipes, 20 mm to 63 mm. Most of the cases these machines are being used for the installing of the house connection pipes, for making service connection. To make a friction less contractors using bigger pulling had then the pipe. It is taking down the friction, But the problem of this machine is that it can't work at sludge. Because of mentioned reasons the friction has a big mining during this kind of works. There are a lot of ways to reduce the friction. In this paper we'll introduce the ways that we have researched during our practice in Bangladesh.

Keywords: Bangladesh, friction and wear, HDD machines, reducing friction

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Authors: Sandra H. Fukurozaki, Andre L. N. Silva, Joao B. F. Neto, Fernando J. G. Landgraf

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Nowadays, the rare earth (RE) metals play an important role in emerging technologies that are crucial for the decarbonisation of the energy sector. Their unique properties have led to increasing clean energy applications, such as wind turbine generators, and hybrid and electric vehicles. Despite the substantial media coverage that has recently surrounded the mining and processing of rare earth metals, very little quantitative information is available concerning their subsequent life stages, especially related to the metallic production of didymium (Nd-Pr) in fluoride molten salt system. Here we investigate a gate to gate scale life cycle assessment (LCA) of the didymium electrolysis based on three different scenarios of operational conditions. The product system is modeled with SimaPro Analyst 8.0.2 software, and IMPACT 2002+ was applied as an impact assessment tool. In order to develop a life cycle inventories built in software databases, patents, and other published sources together with energy/mass balance were utilized. Analysis indicates that from the 14 midpoint impact categories evaluated, the global warming potential (GWP) is the main contributors to the total environmental burden, ranging from 2.7E2 to 3.2E2 kg CO2eq/kg Nd-Pr. At the damage step assessment, the results suggest that slight changes in materials flows associated with enhancement of current efficiency (between 2.5% and 5%), could lead a reduction up to 12% and 15% of human health and climate change damage, respectively. Additionally, this paper highlights the knowledge gaps and future research efforts needing to understand the environmental impacts of Nd-Pr electrolysis process from the life cycle perspective.

Keywords: didymium electrolysis, environmental impacts, life cycle assessment, rare earth metals

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

Procedia PDF Downloads 55