Search results for: testing techniques

Authors: Hamad Albadr

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Joint Commission International (JCI) accreditation process intent to improve the safety and quality of care in the international community through the provision of education, publications, consultation, and evaluation services. These standards apply to the entire organization as well as to each department, unit, or service within the organization. Medical Technology that contains both medical equipment and devices, is an essential part of health care. Appropriate management of equipment maintenance for ensuring medical technology safe, the equipment life is maximized, and the total costs are minimized. JCI medical technology evaluation and accreditation use standards, intents, and measurable elements. The paper focuses on evaluation of JCI standards for medical technology in Saudi Arabian hospitals: a Study Case of PSMMC that define the performance expectation, structures, or functions that must be in place for a hospital to be accredited by JCI through measurable elements that indicate a score during the survey process that identify the requirements for full compliance with the standard specially through Facility Management and Safety (FMS) section that require the hospital establishes and implements a program for inspecting, testing, and maintaining medical technology and documenting the results, to ensure that medical technology is available for use and functioning properly, the hospital performs and documents; an inventory of medical technology; regular inspections of medical technology; testing of medical technology according to its use and manufacturers’ requirements; and performance of preventive maintenance.

Keywords: joint commission international (JCI) accreditation, medical technology, Saudi Arabia, Saudi Arabian hospitals

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Syed Islam, Yiyun Huang, Sebastian Magierowski, Ebrahim Ghafar-Zadeh

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This paper presents system level CMOS solid-state nanopore techniques enhancement for speedup next generation molecular recording and high throughput channels. This discussion also considers optimum number of base-pair (bp) measurements through channel as an important role to enhance potential read accuracy. Effective power consumption estimation offered suitable rangeof multi-channel configuration. Nanopore bp extraction model in statistical method could contribute higher read accuracy with longer read-length (200 < read-length). Nanopore ionic current switching with Time Multiplexing (TM) based multichannel readout system contributed hardware savings.

Keywords: DNA, nanopore, amplifier, ADC, multichannel

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Authors: Noppadon Sintuboon, Benjamas Sawatdipong, Anchalee Kongsuk

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This study was conducted to investigate the engineering parameters: compressional wave: Vp, shear wave: Vs, and density: ρ related to the dynamically geotechnical properties of soils compaction in the core of earth-filled dam located in northern part of Thailand by using multichannel analysis of surface wave (MASW) techniques. The Vp, Vs, and ρ from MASW were 1,624 - 1,649 m/s, 301-323 m/s, and 1,829 kg/m3, respectively. Those parameters were calculated to Poison’s ratio: ν (0.48), shear modulus: G (1.66 x 108 - 1.92 x 108 kg/m2), Vp/Vs ratio (5.10 – 5.39) and Standard Penetration Test (SPT) showing the dynamic characteristics of soil deformation and stress resulting from dynamic loads. The results of this study will be useful in primary evaluating the current condition and foundation of the dam and can be compared to the data from the laboratory in the future.

Keywords: earth-filled dam, MASW, dynamic elastic constant, shear wave

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Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

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Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

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Authors: Ruth Muturi Wanjiku

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HIV/AIDS in Kenya for unborn and young kids. HIV/AIDS is a significant health concern in Kenya, with an estimated 1.5 million people living with the disease. Unfortunately, many of these individuals are unaware of their HIV status, and the disease continues to spread among the population or unborn kids. HIV/AIDS can be transmitted from an infected mother during pregnancy, childbirth, or breastfeeding. However, with early testing and treatment, the risk of mother-to-child transmission can be significantly reduced. Therefore, it is crucial for pregnant women to get tested and receive appropriate medical care. For young kids, HIV/AIDS education is critical to preventing the spread of the disease. It is essential to teach children about the importance of safe sex practices, avoiding risky behaviors such as sharing needles and getting tested regularly. Additionally, children should be taught about the stigma surrounding HIV/AIDS and encouraged to treat individuals living with the disease with compassion and respect. In conclusion, HIV/AIDS is a significant health concern in Kenya that affects individuals of all ages. For unborn kids, early testing and treatment are critical to reducing the risk of mother-to-child transmission. For young kids, education about HIV/AIDS and safe sex practices is essential to preventing the spread of the disease and reducing stigma. It is essential to promote awareness and encourage individuals to get tested and seek medical care if they believe they may be infected with HIV/AIDS.

Keywords: AIDS, HIV, children, pregnant

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Authors: Esther Ranero Carrazana, Maria Karla Ramirez Valdes

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First responders, including firefighters, police officers, and emergency medical personnel, are frequently exposed to high-stress scenarios that significantly increase their risk of mental health issues such as depression, anxiety, and post-traumatic stress disorder (PTSD). Their work involves life-threatening situations, witnessing suffering, and making critical decisions under pressure, all contributing to psychological strain. The objectives of this research on "Stress Reduction Techniques for First Responders: Scientifically Proven Methods" are as follows. One of them is to evaluate the effectiveness of stress reduction techniques. The primary objective is to assess the efficacy of various scientifically proven stress reduction techniques explicitly tailored for first responders. Heart Rate Variability (HRV) Training, Interoception and Exteroception, Sensory Integration, and Body Perception Awareness are scrutinized for their ability to mitigate stress-related symptoms. Furthermore, we evaluate and enhance the understanding of stress mechanisms in first responders by exploring how different techniques influence the physiological and psychological responses to stress. The study aims to deepen the understanding of stress mechanisms in high-risk professions. Additionally, the study promotes psychological resilience by seeking to identify and recommend methods that can significantly enhance the psychological resilience of first responders, thereby supporting their mental health and operational efficiency in high-stress environments. Guide training and policy development is an additional objective to provide evidence-based recommendations that can be used to guide training programs and policy development aimed at improving the mental health and well-being of first responders. Lastly, the study aims to contribute valuable insights to the existing body of knowledge in stress management, specifically tailored to the unique needs of first responders. This study involved a comprehensive literature review assessing the effectiveness of various stress reduction techniques tailored for first responders. Techniques evaluated include Heart Rate Variability (HRV) Training, Interoception and Exteroception, Sensory Integration, and Body Perception Awareness, focusing on their ability to alleviate stress-related symptoms. The review indicates promising results for several stress reduction methods. HRV Training demonstrates the potential to reflect stress vulnerability and enhance physiological and behavioral flexibility. Interoception and Exteroception help modulate the stress response by enhancing awareness of the body's internal state and its interaction with the environment. Sensory integration plays a crucial role in adaptive responses to stress by focusing on individual senses and their integration. Therefore, body perception awareness addresses stress and anxiety through enhanced body perception and mindfulness. The evaluated techniques show significant potential in reducing stress and improving the mental health of first responders. Implementing these scientifically supported methods into routine training could significantly enhance their psychological resilience and operational effectiveness in high-stress environments.

Keywords: first responders, HRV training, mental health, sensory integration, stress reduction

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Authors: K. Genise, S. Murthy

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Introductory Statement: The results of this retrospective chart review suggest the effects of bacterial colonization in critically ill children with viral bronchiolitis, currently unproven, are clinically insignificant. Background: Viral bronchiolitis is one of the most prevalent causes of illness requiring hospitalization among children worldwide and one of the most common reasons for admission to pediatric intensive care. It has been hypothesized that co-infection with bacteria results in more severe clinical outcomes. Conversely, the effects of bacterial colonization in critically ill patients with bronchiolitis are poorly defined. Current clinical management of colonized patients consists primarily of supportive therapies with the role of antibiotics remaining controversial. Methods: A retrospective review of all critically ill children admitted to the BC Children’s Hospital Pediatric Intensive Care Unit (PICU) from 2014-2017 with a diagnosis of bronchiolitis was performed. Routine testing in this time frame consisted of complete pathogen testing, including PCR for Streptococcus pneumoniae. Analyses were performed to determine the impact of bacterial colonization and antibiotic use on a primary outcome of PICU length-of-stay, with secondary outcomes of hospital length-of-stay and duration of ventilation. Results: There were 92 patients with complete pathogen testing performed during the assessed timeframe. A comparison between children with detected Streptococcus pneumoniae (n=22) and those without (n=70) revealed no significant (p=0.20) differences in severity of illness on presentation as per Pediatric Risk of Mortality III scores (mean=3.0). Patients colonized with S. pneumoniae had significantly shorter PICU stays (p=0.002), hospital stays (p=0.0001) and duration of non-invasive ventilation (p=0.002). Multivariate analyses revealed that these effects on length of PICU stay and duration of ventilation do not persist after controlling for antibiotic use, presence of radiographic consolidation, age, and severity of illness (p=0.15, p=0.32). The relationship between colonization and duration of hospital stay persists after controlling for these variables (p=0.008). Conclusions: Children with viral bronchiolitis colonized with S. pneumoniae do not appear to have significantly different PICU length-of-stays or duration of ventilation compared to children who are not colonized. Colonized children appear to have shorter hospital stays. The results of this study suggest bacterial colonization is not associated with increased severity of presenting illness or negative clinical outcomes.

Keywords: bronchiolitis, colonization, critical care, pediatrics, pneumococcal, infection

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Authors: Prikhil Agrawal, N. Priyanka

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With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

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Authors: Anna Suvorova

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Classical motivation theories hold that there are two kinds of motivation, intrinsic and extrinsic. Leaders are looking for effective motivation techniques, but frequently external influences do not work or, even worse, reduce team productivity. We see only the tip of the iceberg -human behavior. However, beneath the surface of the water are factors that directly affect our behavior -desires. Believing that employees need to be motivated, companies design a motivation system based on the principle: do it and get a reward. As a matter of fact, we all have basic desires. Everybody is motivated but to different extents. Following the principle "intrinsic motivation over extrinsic rewards", we need to create an environment that will support intrinsic motivation and potential of employees, and team, rather than individual work.

Keywords: motivation profile, motivation techniques, agile HR, basic desires, agile people, human behavior, people management

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Authors: Özgür Tan

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In different fields of industry, there is a huge demand to acquire surface information in the dimension of micrometer up to centimeter in order to characterize functional behavior of products. Thanks to the latest developments, there are now different methods in surface metrology, but it is not possible to find a unique measurement technique which fulfils all the requirements. Depending on the interaction with the surface, regardless of optical or tactile, every method has its own advantages and disadvantages which are given by nature. However new concepts like ‘multi-sensor’, tools in surface metrology can be improved to solve most of the requirements simultaneously. In this paper, after having presented different optical techniques like confocal microscopy, focus variation and white light interferometry, a new approach is presented which combines white-light interferometry with chromatic confocal probing in a single product. Advantages of different techniques can be used for challenging applications.

Keywords: flatness, chromatic confocal, optical surface metrology, roughness, white-light interferometry

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Authors: Parastou Kharazmi

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Degradation of building materials particularly pipelines causes environmental damage during renovation or replacement and is a time consuming and costly process. Rehabilitation by polymer composites is a solution for renovation of degraded pipeline in heritage buildings and other structures which are less costly, faster and causes less damage to the environment; however, it is still not clear for how long these materials can perform as expected in the field and working condition. To study their service life, two types of composites based on Epoxy and Polyester resins have been evaluated by accelerated exposure and field exposure. The primary degradation agent used in accelerated exposure has been cycling temperature with half of the tests performed in presence of water. Thin films of materials used in accelerated testing were prepared in laboratory by using the same amount of material as well as technique of multi-layers application used in majority of the field installations. Extreme intensity levels of degradation agents have been used only to evaluate materials properties and as also mentioned in ISO 15686, are not directly correlated with degradation mechanisms that would be experienced in service. In the field exposure study, the focus has been to identify possible failure modes, causes, and effects. In field exposure, it has been observed that there are other degradation agents present which can be investigated further such as presence of contaminants and rust before application which prevents formation of a uniform layer of polymer or incompatibility between dissimilar materials. This part of the study also highlighted the importance of application’s quality of the materials in the field for providing the expected performance and service life. Results from extended accelerated exposure and field exposure can help in choosing inspection techniques, establishing the primary degradation agents and can be used for ageing exposure programs with clarifying relationship between different exposure periods and sites.

Keywords: building, renovation, service life, pipelines

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Authors: Thomas J. Bell III

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Pursuing a business degree is fraught with perplexing questions regarding the rising tuition cost and the immediate value of earning a degree. Any decision to pursue an undergraduate business degree is perceived to have value if it facilitates post-graduate job placement. Business programs have decreased value in the absence of innovation in business programs that close the skills gap between recent graduates and employment opportunities. Industry-based certifications are seemingly becoming a requirement differentiator among job applicants. Texas Wesleyan University offers a Computer Information System (CIS) program with an innovative curriculum that integrates industry-recognized certification training into its traditional curriculum with core subjects and electives. This paper explores a culture of innovation in the CIS business program curriculum that creates sustainable stakeholder value for students, employers, the community, and the university. A quantitative research methodology surveying over one-hundred students in the CIS program will be used to examine factors influencing the success or failure of students taking certification exams. Researchers will analyze control variables to identify specific correlations between practice exams, teaching pedagogy, study time, age, work experience, etc. This study compared various exam preparation techniques to corresponding exam results across several industry certification exams. The findings will aid in understanding control variables with correlations that positively and negatively impact exam results. Such discovery may provide useful insight into pedagogical impact indicators that positively contribute to certification exam success and curriculum enhancement.

Keywords: taking certification exams, exam training, testing skills, exam study aids, certification exam curriculum

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Authors: S. Bouhouche, R. Drai, J. Bast

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This paper is concerned with a method for uncertainty evaluation of steel sample content using X-Ray Fluorescence method. The considered method of analysis is a comparative technique based on the X-Ray Fluorescence; the calibration step assumes the adequate chemical composition of metallic analyzed sample. It is proposed in this work a new combined approach using the Kalman Filter and Markov Chain Monte Carlo (MCMC) for uncertainty estimation of steel content analysis. The Kalman filter algorithm is extended to the model identification of the chemical analysis process using the main factors affecting the analysis results; in this case, the estimated states are reduced to the model parameters. The MCMC is a stochastic method that computes the statistical properties of the considered states such as the probability distribution function (PDF) according to the initial state and the target distribution using Monte Carlo simulation algorithm. Conventional approach is based on the linear correlation, the uncertainty budget is established for steel Mn(wt%), Cr(wt%), Ni(wt%) and Mo(wt%) content respectively. A comparative study between the conventional procedure and the proposed method is given. This kind of approaches is applied for constructing an accurate computing procedure of uncertainty measurement.

Keywords: Kalman filter, Markov chain Monte Carlo, x-ray fluorescence calibration and testing, steel content measurement, uncertainty measurement

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Authors: Abdelkader Anouzla, Soukaina Bouaouda, Roukaya Bouyakhsass, Salah Souabi, Abdeslam Taleb

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During storage and under the combined action of rainwater and natural fermentation, these wastes produce over 800.000 m3 of landfill leachates. Due to population growth and changing global economic activities, the amount of waste constantly generated increases, making more significant volumes of leachate. Leachate, when leaching into the soil, can negatively impact soil, surface water, groundwater, and the overall environment and human life. The leachate must first be treated because of its high pollutant load before being released into the environment. This article reviews the different leachate treatments in September 2022 techniques. Different techniques can be used for this purpose, such as biological, physical-chemical, and membrane methods. Young leachate is biodegradable; in contrast, these biological processes lose their effectiveness with leachate aging. They are characterized by high ammonia nitrogen concentrations that inhibit their activity. Most physical-chemical treatments serve as pre-treatment or post-treatment to complement conventional treatment processes or remove specific contaminants. After the introduction, the different types of pollutants present in leachates and their impacts have been made, followed by a discussion highlighting the advantages and disadvantages of the various treatments, whether biological, physicochemical, or membrane. From this work, due to their simplicity and reasonable cost compared to other treatment procedures, biological treatments offer the most suitable alternative to limit the effects produced by the pollutants in landfill leachates.

Keywords: landfill leachate, landfill pollution, impact, wastewater

Procedia PDF Downloads 89

Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Sonia Zulfiqar, Daniele Mantione, Muhammad Ilyas Sarwar, Alexander Rothenberger, David Mecerreyes

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Climate change due to escalating carbon dioxide concentration in the atmosphere is an issue of paramount importance that needs immediate attention. CO2 capture and sequestration (CCS) is a promising route to mitigate climate change and adsorption is the most widely recognized technology owing to possible energy savings relative to the conventional absorption techniques. In this conference, the potential of a new family of solid sorbents for CO2 capture and separation will be presented. Novel pyridinium containing poly(ionic liquid)s (PILs) were synthesized with varying anions i.e bis(trifluoromethylsulfonyl)imide and hexafluorophosphate. The resulting polymers were characterized using NMR, XRD, TGA, BET surface area and microscopic techniques. Furthermore, CO2 adsorption measurements at two different temperatures were also carried out and revealed great potential of these PILs as CO2 scavengers.

Keywords: climate change, CO2 capture, poly(ionic liquid)s, CO2/N2 selectivity

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Authors: Kedarnath Awati

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Some parallels between Indian Art Music and Western Art Music, such as the identity of the basic heptatonic scale structure, are quite obvious and need no further discussion. Other parallels are far less obvious, and it is one of them that the author is interested in. Specifically, the author would like to make a serious claim that in both types of music, there is an unspoken dependence on melody. Yes, it is true that the techniques that the two systems use for elaboration are very, very different: Western music uses the techniques of harmony, counterpoint, orchestration and motivic variation, while the Indian systems, both the Hindustani and the Carnatic traditions use the technique of raagdaari. The reason that this point is barely spoken about is that both in the West as well as in India, artists tend to think of melody as something elementary or as something 'given'. The Indian musicians would much rather dwell upon this or that meend or taan or other technical device, while the West thinks that melody is passé and would rather discuss the merits and demerits of spectralism and perhaps serialism. The author would like to explore this theme further in his paper.

Keywords: Indian art music, Western art music, melody, raagdaari, motivic variation.

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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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: Eriko Ochiai, Fumiko Satoh, Keiko Miyashita, Yu Kakimoto, Motoki Osawa

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Sudden and unexpected deaths from unknown causes occur in infants and youths. Recently, molecular links between a part of these deaths and several genetic diseases are examined in the postmortem. For instance, hereditary long QT syndrome and Burgada syndrome are occasionally fatal through critical ventricular tachyarrhythmia. There are a large number of target genes responsible for such diseases, the conventional analysis using the Sanger’s method has been laborious. In this report, we attempted to analyze sudden deaths comprehensively using the next generation sequencing (NGS) technique. Multiplex PCR to subject’s DNA was performed using Ion AmpliSeq Library Kits 2.0 and Ion AmpliSeq Inherited Disease Panel (Life Technologies). After the library was constructed by emulsion PCR, the amplicons were sequenced 500 flows on Ion Personal Genome Machine System (Life Technologies) according to the manufacture instruction. SNPs and indels were analyzed to the sequence reads that were mapped on hg19 of reference sequences. This project has been approved by the ethical committee of Tokai University School of Medicine. As a representative case, the molecular analysis to a 40 years old male who received a diagnosis of Brugada syndrome demonstrated a total of 584 SNPs or indels. Non-synonymous and frameshift nucleotide substitutions were selected in the coding region of heart disease related genes of ANK2, AKAP9, CACNA1C, DSC2, KCNQ1, MYLK, SCN1B, and STARD3. In particular, c.629T-C transition in exon 3 of the SCN1B gene, resulting in a leu210-to-pro (L210P) substitution is predicted “damaging” by the SIFT program. Because the mutation has not been reported, it was unclear if the substitution was pathogenic. Sudden death that failed in determining the cause of death constitutes one of the most important unsolved subjects in forensic pathology. The Ion AmpliSeq Inherited Disease Panel can amplify the exons of 328 genes at one time. We realized the difficulty in selection of the true source from a number of candidates, but postmortem genetic testing using NGS analysis deserves of a diagnostic to date. We now extend this analysis to SIDS suspected subjects and young sudden death victims.

Keywords: postmortem genetic testing, sudden death, SIDS, next generation sequencing

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Authors: Gebreegziabher Hailu

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This paper presents the development of residual power series methods aimed at efficiently solving stiff differential equations, which pose significant challenges in numerical analysis due to their rapid changes in solution behavior. The RPSM is a numerical approach that generates polynomial-based approximate solutions without the need for linearization, discretization, or perturbation techniques, making it straightforward to implement and less prone to computational errors. We introduce an approach that utilizes power series expansions combined with residual minimization techniques to enhance convergence and stability. By analyzing the theoretical foundations of stiffness, we delve into the formulation of the residual power series method, detailing how it effectively captures the dynamics of stiff systems while maintaining computational efficiency. Numerical experiments demonstrate the method's superiority in terms of accuracy and computational cost when compared to traditional methods like implicit Runge-Kutta or multistep techniques. We also explore adaptive strategies within our framework to automatically adjust parameters based on the stiffness characteristics of the problem at hand. Ultimately, our findings contribute to the broader toolkit for tackling stiff differential equations, offering a robust alternative that promises to streamline computational workflows in various applied mathematics and engineering contexts.

Keywords: residual power series methods, stiff differential equoations, numerical approach, Runge Kutta methods

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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: 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: 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: Jorge Duarte de Sá

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The project presented in this investigation is part of the multidisciplinary field of Architecture and explores an experience in media architecture, integrated in Arts, Science and Technology. The objective of this work is to create a visual experience comprehending Architecture, Media and Art. It is intended to specifically explore the sacred spaces that are losing social, cultural or religious dynamics and insert new Media technologies to create a new generate momentum, testing tools, techniques and methods of implementation. Given an architectural project methodology, it seems essential that 'the location' should be the starting point for the development of this technological apparatus: the church of Santa Clara in Santarém, Portugal emerged as an experimental space for apparatus, presenting itself as both temple and museum. We also aim to address the concept of rehabilitation through media technologies, directed at interventions that may have an impact on energizing spaces. The idea is emphasized on the rehabilitation of spaces that, one way or another, may gain new dynamics after a media intervention. Thus, we intend to affect the play with a sensitive and spiritual character which endemically, sacred spaces have, by exploring a sensitive aspect of the subject and drawing up new ideas for meditation and spiritual reflection. The work is designed primarily as a visual experience that encompasses the space, the object and the subject. It is a media project supported by a dual structure with two transparent screens operating in a holographic screen which will be projecting two images that complement the translucent overlay film, thus making the merger of two projections. The digitally created content reacts to the presence of observers through infrared cameras, placed strategically. The object revives the memory of the altarpiece as an architectural surface, promoting the expansion of messages through the media technologies.

Keywords: architecture, media, sacred, technology

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Authors: Karolina Mazur, Stanislaw Kuciel

Abstract:

Polylactides (PLA) and polyhydroxyalkanoates (PHA) are the two groups of biodegradable and biocompatible thermoplastic polymers most commonly utilised in medicine and rehabilitation. The aim of this work is to determine the changes in the strength properties and the microstructures taking place in biodegradable polymer composites during their long-term storage in a highly cooled environment (i.e. a freezer at -24ºC) and to initially assess the durability of such biocomposites when used as single-use elements of rehabilitation or medical equipment. It is difficult to find any information relating to the feasibility of long-term storage of technical products made of PLA or PHA, but nonetheless, when using these materials to make products such as casings of hair dryers, laptops or mobile phones, it is safe to assume that without storing in optimal conditions their degradation time might last even several years. SEM images and the assessment of the strength properties (tensile, bending and impact testing) were carried out and the density and water sorption of two polymers, PLA and PHA (NaturePlast PLE 001 and PHE 001), filled with cellulose fibres (corncob grain – Rehofix MK100, Rettenmaier&Sohne) up to 10 and 20% mass were determined. The biocomposites had been stored at a temperature of -24ºC for 4 years. In order to find out the changes in the strength properties and the microstructure taking place after such a long time of storage, the results of the assessment have been compared with the results of the same research carried out 4 years before. Results shows a significant change in the manner of fractures – from ductile with developed surface for the PHA composite with corncob grain when the tensile testing was performed directly after the injection into a more brittle state after 4 years of storage, which is confirmed by the strength tests, where a decrease of deformation is observed at point of fracture. The research showed that there is a way of storing medical devices made out of PLA or PHA for a reasonably long time, as long as the required temperature of storage is met. The decrease of mechanical properties found during tensile testing and bending for PLA was less than 10% of the tensile strength, while the modulus of elasticity and deformation at fracturing slightly rose, which may implicate the beginning of degradation processes. The strength properties of PHA are even higher after 4 years of storage, although in that case the decrease of deformation at fracturing is significant, reaching even 40%, which suggests its degradation rate is higher than that of PLA. The addition of natural particles in both cases only slightly increases the biodegradation.

Keywords: biocomposites, PLA, PHA, storage

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

Abstract:

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

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