Search results for: school based support program

Authors: Beata Jackowska-Zduniak

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We formulate and analyze a mathematical model describing dynamics of cancer growth under the influence of radiation therapy. The effect of this type of therapy is considered as an additional equation of discussed model. Numerical simulations show that delay, which is added to ordinary differential equations and represent time needed for transformation from one type of cells to the other one, affects the behavior of the system. The validation and verification of proposed model is based on medical data. Analytical results are illustrated by numerical examples of the model dynamics. The model is able to reconstruct dynamics of treatment of cancer and may be used to determine the most effective treatment regimen based on the study of the behavior of individual treatment protocols.

Keywords: mathematical modeling, numerical simulation, ordinary differential equations, radiation therapy

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Authors: Hariz Halilovich

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Based on conventional and digital ethnography, this paper discusses the ways Bosnian refugees utilise digital technologies and new media to recreate, synchronise and sustain their identities and memories in the aftermath of ‘ethnic cleansing’ and genocide and in the contexts of their new emplacements and home-making practices in diaspora. In addition to discussing representations of displacement and emplacement in the ‘digital age’, the paper also aims to make a contribution to the understanding and application of digital ethnography as an emerging method of inquiry in anthropology and related social science disciplines. While some researchers see digital ethnography as an exclusively online–based research, the author of this paper argues that it is critical to understand the online world in the context of the real world—made of real people, places, and social relations.

Keywords: Bosnia, cyber villages, digital diaspora, refugees

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Authors: Ashfaque Hossain Khan, Brian Thomson, Ratan Debnath, Abhishek Motayed, Mulpuri V. Rao

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Though the efforts had been made, the problem of cross-sensitivity for a single metal oxide-based sensor can’t be fully eliminated. In this work, a sensor array has been designed and fabricated comprising of platinum (Pt), copper (Cu), and silver (Ag) decorated TiO2 and ZnO functionalized GaN nanowires using industry-standard top-down fabrication approach. The metal/metal-oxide combinations within the array have been determined from prior molecular simulation study using first principle calculations based on density functional theory (DFT). The gas responses were obtained for both single and mixture of NO2, SO2, ethanol, and H2 in the presence of H2O and O2 gases under UV light at room temperature. Each gas leaves a unique response footprint across the array sensors by which precise discrimination of cross-sensitive gases has been achieved. An unsupervised principal component analysis (PCA) technique has been implemented on the array response. Results indicate that each gas forms a distinct cluster in the score plot for all the target gases and their mixtures, indicating a clear separation among them. In addition, the developed array device consumes very low power because of ultra-violet (UV) assisted sensing as compared to commercially available metal-oxide sensors. The nanowire sensor array, in combination with PCA, is a potential approach for precise real-time gas monitoring applications.

Keywords: cross-sensitivity, gas sensor, principle component analysis (PCA), sensor array

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Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: Hassen Hamouda, Mohamed Ouwais Kabaou, Med Salim Bouhlel

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The growth of wireless technology made opportunistic scheduling a widespread theme in recent research. Providing high system throughput without reducing fairness allocation is becoming a very challenging task. A suitable policy for resource allocation among users is of crucial importance. This study focuses on scheduling multiple streaming flows on the downlink of a WiMAX system based on orthogonal frequency division multiple access (OFDMA). In this paper, we take the first step in formulating and analyzing this problem scrupulously. As a result, we proposed a new scheduling scheme based on Round Robin (RR) Algorithm. Because of its non-opportunistic process, RR does not take in account radio conditions and consequently it affect both system throughput and multi-users diversity. Our contribution called MORRA (Modified Round Robin Opportunistic Algorithm) consists to propose a solution to this issue. MORRA not only exploits the concept of opportunistic scheduler but also takes into account other parameters in the allocation process. The first parameter is called courtesy coefficient (CC) and the second is called Buffer Occupancy (BO). Performance evaluation shows that this well-balanced scheme outperforms both RR and MaxSNR schedulers and demonstrate that choosing between system throughput and fairness is not required.

Keywords: OFDMA, opportunistic scheduling, fairness hierarchy, courtesy coefficient, buffer occupancy

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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Authors: Keven A. Prusak, William F. Christensen, Zack Beddoes

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Background: For more than a decade, the Sport Motivation Scale (SMS) has been used to measure contextual motivation across a variety of sporting and physical education (PE) settings but not without criticism as to its tenability. Consequently, a new version of the sport motivation scale (SMS-II) was created to address certain weakness of the original SMS. Purpose: The purpose of this study is to assess the suitability of the SMS-II in the secondary PE setting. Methods: Three hundred and twenty (204 females, and 116 males; grades 7-9) completed the 18-item, six-subscale SMS-II at the end of a required PE class. Factor means, standard deviations, and correlations were calculated and further examined via confirmatory factor analysis (CFA). Model parameters were estimated maximum likelihood function. Results: Results indicate that participants held generally positive perceptions toward PE as a context (more so for males than females). Reliability analysis yielded adequate alphas (rα = 0.71 to 0.87, Mα = 0.78) with the exception of the AM subscale (αAM = .64). Correlation analysis indicated some support for the SIMPLEX pattern, but distal ends of the motivation continuum displayed no relationship. CFA yielded robust fit indices to the proposed structure of the SMS-II for PE. A small but significant variance across genders was noted and discussed. Conclusions: In all, the SMS-II suitably accesses PE context-specific motivational indices within Jr. High PE.

Keywords: motivation, self-determination theory, physical education, confirmatory factor analysis

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Authors: Ka Yan Chan

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Cohabitation among couples has been increasingly common in recent decades. Nonetheless, insufficient attention was given to the impact of attachment on cohabitation. This study discussed the experience of cohabitation among women with insecure attachments by collecting qualitative data through semi-structured interviews. Through thematic analysis, the study explored the characteristics of the women, the formation of cohabitation, struggles, coping mechanisms, and the impacts of cohabitation on the women. Moreover, the influences of the family-of-origin on cohabitation and the needs of the women were explored. The findings indicated that insecure attachment and the family-of-origin had significant effects on cohabitation and the interaction among the cohabitating couples. Women with insecure attachments were more likely to enter cohabitation unconsciously and without discussing what cohabitation means for their relationship with their partners. The findings also suggested that committing to marriage was not the only method for the women to feel secure in the relationship. Instead, long-lasting love and care, as well as reliability from their partners, could satisfy their emotional needs. More importantly, the findings revealed that repairing attachment problems and dealing with challenges in life stage transition is associated with positive impacts on the cohabitation experience. Additionally, to meet the needs of diverse family structures and to provide all-rounded support for enhancing the wellbeing of individuals, cohabitants, and couples, a comprehensive intervention model of relationship enrichment was discussed.

Keywords: cohabitation, family-of-origin, insecure attachment, relationship enrichment

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Authors: Abdulaziz Almustafa

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Considering the critical role permanence has on predictions related to the contextual interference effect on laboratory and field research, this study sought to determine whether the paradigm of the effect depends on the complexity of the skill during the acquisition and transfer phases. The purpose of the present study was to investigate the effects of contextual interference CI by extending previous laboratory and field research with adult athletes through the acquisition and transfer phases. Male (n=60) athletes age 18-22 years-old, were chosen randomly from Eastern Province Clubs. They were assigned to complete blocked, random, or serial practices. Analysis of variance with repeated measures MANOVA indicated that, the results did not support the notion of CI. There were no significant differences in acquisition phase between blocked, serial and random practice groups. During the transfer phase, there were no major differences between the practice groups. Apparently, due to the task complexity, participants were probably confused and not able to use the advantages of contextual interference. This is another contradictory result to contextual interference effects in acquisition and transfer phases in sport settings. One major factor that can influence the effect of contextual interference is task characteristics as the nature of level of difficulty in sport-related skill.

Keywords: contextual interference, acquisition, transfer, task difficulty

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Authors: Efthimios Kokkotos, Kostakis Marios, Beis Alexandros, Angelos Patakas, Antonios Avgeris, Vassilios Triantafyllidis

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H, C, and O stable isotope ratios were measured in different olive oils and table olives originating from different regions of Greece. In particular, the stable isotope ratios of different olive oils produced in the Lakonia region (Peloponesse – South Greece) from different varieties, i.e., cvs ‘Athinolia’ and ‘koroneiki’, were determined. Additionally, stable isotope ratios were also measured in different table olives (cvs ‘koroneiki’ and ‘kalamon’) produced in the same region (Messinia). The aim of this study was to provide sufficient isotope ratio data regarding each variety and region of origin that could be used in discriminative studies of oil olives and table olives produced by different varieties in other regions. In total, 97 samples of olive oil (cv ‘Athinolia’ and ‘koroneiki’) and 67 samples of table olives (cvs ‘kalmon’ and ‘koroneiki’) collected during two consecutive sampling periods (2021-2022 and 2022-2023) were measured. The C, H, and O isotope ratios were measured using Isotope Ratio Mass Spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques. The measurements of the isotope ratio analyses were expressed in permille (‰) using the delta δ notation (δ=Rsample/Rstandard-1, where Rsample and Rstandardis represent the isotope ratio of sample and standard). Results indicate that stable isotope ratios of C, H, and O ranged between -28,5+0,45‰, -142,83+2,82‰, 25,86+0,56‰ and -29,78+0,71‰, -143,62+1,4‰, 26,32+0,55‰ in olive oils produced in Lakonia region from ‘Athinolia’ and ‘koroneiki ‘varieties, respectively. The C, H, and O values from table olives originated from Messinia region were -28,58+0,63‰, -138,09+3,27‰, 25,45+0,62‰ and -29,41+0,59‰,-137,67+1,15‰, 24,37+0,6‰ for ‘Kalamon’ and ‘koroneiki’ olives respectively. Acknowledgments: This research has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH—CREATE—INNOVATE (Project code: T2EDK-02637; MIS 5075094, Title: ‘Innovative Methodological Tools for Traceability, Certification and Authenticity Assessment of Olive Oil and Olives’).

Keywords: olive oil, table olives, Isotope ratio, IRMS, geographical origin

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: N. Al Khashan, H. Al Shammari, W. Al Bahli

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Patients who are eligible to receive treatment at the National Guard Health Affairs (NGHA), Saudi Arabia will typically have four medical record numbers (MRN), one in each of the geographical areas. More hospitals and primary healthcare facilities in other geographical areas will launch soon which means more MRNs. When patients own four MRNs, this will cause major drawbacks in patients’ quality of care such as creating new medical files in different regions for relocated patients and using referral system among regions. Consequently, the access to a patient’s medical record from other regions and the interoperability of health information between the four hospitals’ information system would be challenging. Thus, there is a need to unify medical records among these five facilities. As part of the effort to increase the quality of care, a new Hospital Information Systems (HIS) was implemented in all NGHA facilities by the end of 2016. NGHA’s plan is put to be aligned with the Saudi Arabian national transformation program 2020; whereby 70% citizens and residents of Saudi Arabia would have a unified medical record number that enables transactions between multiple Electronic Medical Records (EMRs) vendors. The aim of the study is to explore the plan, the challenges and barriers of unifying the 4 MRNs into one Enterprise Patient Identifier (EPI) in NGHA hospitals by December 2018. A descriptive study methodology was used. A journey map and a project plan are created to be followed by the project team to ensure a smooth implementation of the EPI. It includes the following: 1) Approved project charter, 2) Project management plan, 3) Change management plan, 4) Project milestone dates. Currently, the HIS is using the regional MRN. Therefore, the HIS and all integrated health care systems in all regions will need modification to move from MRN to EPI without interfering with patient care. For now, the NGHA have successfully implemented an EPI connected with the 4 MRNs that work in the back end in the systems’ database.

Keywords: consumer health, health informatics, hospital information system, universal medical record number

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Authors: Yassir AbdelRazig, Eren Ozguven, Ren Moses

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While there exists a greater understanding of the differences between the driving behaviors of older and younger drivers, there is still a need to further understand how the two groups perform when attempting to perform complex intersection maneuvers. This paper looks to determine if, and to what extent, these differences exist when drivers encounter permissive left-hand turns, pedestrian traffic, two and four-lane intersections, heavy fog, and night conditions. The study will utilize a driving simulator to develop custom drivable scenarios containing one or more of the previously mentioned conditions. 32 younger and 32 older (+65 years) participants perform driving simulation scenarios and have their velocity, time to the nearest oncoming vehicle, accepted and rejected gaps, etc., recorded. The data collected from the simulator is analyzed via Raff’s method and logistic regression in order to determine and compare the critical gaps values of the two cohorts. Out of the parameters considered for this study, only the age of the driver, their experience (if they are a younger driver), the size of a gap, and the presence of pedestrians on the crosswalk proved significant. The results did not support the hypothesis that older drivers would be significantly more conservative in their critical gaps judgment and acceptance.

Keywords: older drivers, simulation, left-turn, human factors

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Expedito J. S. Parente Jr., Italo C. Rios, Joao Paulo C. Marques, Rosana M. A. Saboya, F. Murilo T. Luna, Célio L. Cavalcante Jr.

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Increasing constraints of environmental regulation around the world have led to higher demand for biodegradable products. Vegetable oils present some properties that may favor their use as biolubricants; however, there are others, such as resistance to oxidation and pour point, which affect possible commercial applications. In this study, the physicochemical properties of biolubricants synthesized from different vegetable oils were evaluated and compared with petroleum-based lubricant and pure vegetable oil. Chemical modifications applied to the original vegetable oil improved their oxidative stability and pour point significantly. The addition of commercial antioxidants to the bio-based lubricants was evaluated, yielding values of oxidative stability close to those of mineral basestock oil.

Keywords: biolubricant, vegetable oil, oxidative stability, pour point, antioxidants

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Authors: Norah Almubairik, Wadha Almattar, Amani Alqarni

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Social media applications are increasingly being used in our everyday communications. These applications utilise end-to-end encryption mechanisms, which make them suitable tools for criminals to exchange messages. These messages are preserved in the volatile memory until the device is restarted. Therefore, volatile forensics has become an important branch of digital forensics. In this study, the WormHex tool was developed to inspect the memory dump files of Windows and Mac-based workstations. The tool supports digital investigators to extract valuable data written in Arabic and English through web-based WhatsApp and Twitter applications. The results verify that social media applications write their data into the memory regardless of the operating system running the application, with there being no major differences between Windows and Mac.

Keywords: volatile memory, REGEX, digital forensics, memory acquisition

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Authors: Ma. Eliza Jijeth V. dela Cruz

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Technology is a recent prodigy in people’s everyday life that has taken off. It infiltrated almost every aspect of one’s lives, changing how people work, how people learn and how people perceive things. Academic Institutions, just like other organizations, have deeply modified its strategies to integrate technology into the institutional vision and corporate strategy that has never been greater. Information and Communications Technology (ICT) continues to be recognized as a major factor in organizations realizing its aims and objectives. Consequently, ICT has an important role in the mobilization of an academic institution’s strategy to support the delivery of operational, strategic or transformational objectives. This ICT strategy should align the institution with the radical changes of the ICT world through the use of Enterprise Architecture (EA). Hence, EA’s objective is to optimize the islands of legacy processes to be integrated that is receptive to change and supportive of the delivery of the strategy. In this paper, the focus is to explore the motivational antecedents during the adoption of EA in a Higher Education Institution in the Philippines for its ICT strategic plan. The seven antecedents (viewpoint, stakeholders, human traits, vision, revolutionary innovation, techniques and change components) provide understanding into EA adoption and the antecedents that influences the process of EA adoption.

Keywords: Enterprise Architecture, Adoption, Antecedents, Higher Educational Institutions

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Authors: I Putu Indra Kusuma

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The rapid development of Information and Communication Technology (ICT) tools has improved the implementation of flipped classrooms in English Language Teaching (ELT), especially in speaking course. Flipped classrooms have therefore evolved from the oldest version, which uses recorded videos to the newest one (3.0 version), which combines various materials and enables out-of-class interaction and learning engagement. However, how the latest version of flipped classrooms affects students’ speaking performance and influences students’ learning engagement remains unclear. This study therefore sought (1) to examine the effect of flipped classrooms 3.0 towards students’ speaking performance and (2) to explore the students’ learning engagement during the implementation of flipped classrooms in the speaking course. This study then employed explanatory sequential mixed-method design. This study conducted a quasi-experimental study by recruiting 164 twelfth grade students of a public senior high school in Indonesia as the sample. They were distributed into experimental (80 students) and control (84 students) groups. The experimental group was treated by implementing flipped classrooms with various use of ICT tools such as Schoology, Youtube, websites, and Flipgrid for eight weeks. Meanwhile, the control group implemented a conventional method. Furthermore, there were two variables examined in this study, such as the implementation of flipped classrooms 3.0 as the independent variable and students’ speaking performance as the dependent variable. The data of these two variables were then collected through administering a speaking test to both groups. The data from this experimental study were analyzed by using independent t-test analysis. Also, five students were invited to participate in semi-structured interviews to explore their learning engagement during the implementation of flipped classrooms. The findings revealed that there was a significant difference in students’ speaking performance between experimental where t (df = 162) = 5.810, p < 0.001, d = 0.91 in which experimental group performed better in speaking than the control group. Also, the results of interviews showed that the students had positive learning engagement during the implementation of flipped classrooms 3.0, especially on out-of-class interactions and face-to-face meetings. Some relevant implications to ELT, especially in speaking courses, are also drawn from the data findings. From the findings, it can be concluded that flipped classrooms 3.0 has a significant effect on students’ speaking performance and it promotes students’ learning engagement. Therefore, flipped classrooms 3.0 should be embraced as the newest version of flipped classrooms that promotes interaction outside the classrooms and learning engagement.

Keywords: Flipped Classrooms 3.0, learning engagement, teaching speaking with technology, technology-enhanced language learning

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Authors: Joao Fialho

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The mathematical modelling of idiopathic scoliosis has been studied throughout the years. The models presented on those papers are based on the orthotic stabilization of the idiopathic scoliosis, which are based on a transversal force being applied to the human spine on a continuous form. When considering the ATT (Antalgic-Trak Technology) device, the existent models cannot be used, as the type of forces applied are no longer transversal nor applied in a continuous manner. In this device, vertical traction is applied. In this study we propose to model the idiopathic scoliosis, using the ATT (Antalgic-Trak Technology) device, and with the parameters obtained from the mathematical modeling, set up a case-by-case individualized therapy plan, for each patient.

Keywords: idiopathic scoliosis, mathematical modelling, human spine, Antalgic-Trak technology

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Authors: Abdullah Işıktaş, Kevser Dincer

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The use of HEPA filters for air conditioning systems in clean rooms tends to increase progressively in pharmaceutical, food stuff industries and in hospitals. There are two standards widely used for HEPA filters; the EN 1822 standards published by the European Union, CEN (European Committee for Standardization) and the US based IEST standard (Institute of Environmental Sciences and Technology. Both standards exhibit some differences in the definitions of efficiency and its measurement methods. While IEST standard defines efficiency at the grit diameter of 0.3 µm, the EN 1822 standard takes MPPS (Most Penetrating Particle Size) as the basis of its definition. That is, the most difficult grit size to catch up. On the other hand, while IEST suggests that photometer and grit counters be used for filter testing, in EN 1822 standard, only the grit (grain) counters are recommended for that purpose. In this study, powder holding capacities of H13 and H14 grade materials under the EN 779 standard are investigated experimentally by using activated carbon. Measurements were taken on an experimental set up based on the TS 932 standard. Filter efficiency was measured by injecting test powder at amounts predetermined in the standards into the filters at certain intervals. The data obtained showed that the powder holding capacities of the activated carbon filter are high enough to yield efficiency of around 90% and that the H13 and H14 filters exhibit high efficiency suitable for the standard used.

Keywords: activated carbon filters, HEPA filters, powder holding capacities, air conditioning systems

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Authors: Sophia Cyril Vincent

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Background: As per the Indian Census 2011, there is nearly 104 million elderly population aged above 60 years (53 million females and 51 males), and the count is expected to be 173 million by the end of 2026. Nearly 5.5% of women and 1.5% of men are living alone.1 In India, even though it is the moral duty of the children to take care of aged parents, many elders are landing in old age homes due to the social transformation factors like mushrooming of nuclear families, migration of children, cultural echoes, differences in mindset and values. Nearly 728 old age homes are seen across the country, out of which 78 old age homes with approximately 3000 inmates are seen only in Bangalore2. The existing literature shows that elderly women residing in old age homes experience the challenges like- loneliness, health issues, rejection from children, grief, death anxiety, etc, which leads to mental and physical wellbeing in numerous and tangible ways3. Hence the best and cost-effective way to improve the meaning and quality of life among elderly females is logotherapy, a type of psychotherapeutic analysis and treatment, motivating and driving force4 within the human experience to lead a decent life. Aim: The current research is aimed at studying the effectiveness of a logotherapy intervention on meaning and quality of life among elderly women of old age homes. Samples:200 women aged < 60 years and staying in the old age home for more than 1 year were randomly allocated to the control group and experimental group. Methodology: Using the Meaning in life questionnaire (MLQ)and the World health organization quality of life (WHOQOL) questionnaire, meaning and quality of life were assessed among both groups' women. Intensive Logotherapy and meaning in life program for five days were provided for the experimental group and the control group, with no treatment. Result: Under analysis. Conclusion: It is the right of the elderly woman to lead a happy and peaceful life till her death irrespective of the residing place. Hence, continuous monitoring and effective management are necessary for elderly women.

Keywords: quality of life, meaning of life, logo therapy, old age home

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

Procedia PDF Downloads 65

Authors: Michael Bach

Abstract:

Extensive weld repair was carried out in 2009 after a leak was detected in the aluminum 5052 vessel of the National Research Universal (NRU) reactor. This was the second vessel installed since 1974. In support of the NRU vessel leak repair and fitness for service assessments, an estimate of property changes due to irradiation exposure is required to extend the service of the reactor until 2018. In order to fully evaluate the property changes in the vessel wall, an Iodine-125 rod (I rod) made from the same material and irradiated in the NRU reactor from 1974 1991, was retrieved and sectioned for microstructure characterization and mechanical testing. The different sections of the I rod were exposed to various levels of thermal neutron fluences from 0 to a maximum of 11.9 x 1022 n/cm2. The end of life thermal neutron fluence of the NRU vessel is estimated to be 2.2 x 1022 n/cm2 at 35 years of service. Tensile test and fracture toughness test was performed on the I-rod material at various axial locations. The changes in tensile properties were attributed primarily to the creation of finely dispersed Mg-Si precipitates that harden the material and reduced the ductility. Despite having a reduction in fracture toughness, the NRU vessel is still operation at the current fluence levels.

Keywords: aluminum alloy, fitness-for-service assessment , fracutre toughness, nuclear reactor, precipitate strengthening, radiation damage, tensile strength

Procedia PDF Downloads 182

Authors: Musa M. Umar, S. G. Ado

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The paper examines the activities of the National Programme for food security (NPFS) for averting food insecurity in Nigeria and beyond. The components of the NPFS include site development, outreach, community development and management support. On each site, core activities comprise crop productivity, production diversification and agro-processing. The outreach activities consist of inputs and commodity marketing, rural finance, strengthening research-extension-farmers-inputs linkages, health and nutrition and expansion of site activities. The community development activities include small-scale rural infrastructure, micro-earth dams and community forestry. The overall benefits include food security, improved productivity, marketing and processing, enhanced land and water use, increased animal production and fish catches, improved nutrition, reduction in post-harvest losses and value addition, improved rural infrastructure and diversification of production leading to improved livelihood. The NPFS would poster sustained development of small-holder agricultural and income generation.

Keywords: food-security, community development, post-harvest, production

Procedia PDF Downloads 350

Authors: Zuzana Chaloupková, Zdeňka Marková, Václav Ranc, Radek Zbořil

Abstract:

Prostate cancer is now one of the most serious oncological diseases in men with an incidence higher than that of all other solid tumors combined. Diagnosis of prostate cancer usually involves detection of related genes or detection of marker proteins, such as PSA. One of the new potential markers is PSMA (prostate specific membrane antigen). PSMA is a unique membrane bound glycoprotein, which is considerably overexpressed on prostate cancer as well as neovasculature of most of the solid tumors. Commonly applied methods for a detection of proteins include techniques based on immunochemical approaches, including ELISA and RIA. Magnetically assisted surface enhanced Raman spectroscopy (MA-SERS) can be considered as an interesting alternative to generally accepted approaches. This work describes a utilization of MA-SERS in a detection of PSMA in human blood. This analytical platform is based on magnetic nanocomposites Fe3O4@Ag, functionalized by a low-molecular selector labeled as JB303. The system allows isolating the marker from the complex sample using application of magnetic force. Detection of PSMA is than performed by SERS effect given by a presence of silver nanoparticles. This system allowed us to analyze PSMA in clinical samples with limits of detection lower than 1 ng/mL.

Keywords: diagnosis, cancer, PSMA, MA-SERS, Ag nanoparticles

Procedia PDF Downloads 224

Authors: Ahmad Awajan, Sadam Al Wadi

Abstract:

In this study, a hybrid method based on Empirical Mode Decomposition and Holt-Winter (EMD-HW) is used to forecast Amman stock market data. First, the data are decomposed by EMD method into Intrinsic Mode Functions (IMFs) and residual components. Then, all components are forecasted by HW technique. Finally, forecasting values are aggregated together to get the forecasting value of stock market data. Empirical results showed that the EMD- HW outperform individual forecasting models. The strength of this EMD-HW lies in its ability to forecast non-stationary and non- linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy comparing with eight existing forecasting methods based on the five forecast error measures.

Keywords: Holt-Winter method, empirical mode decomposition, forecasting, time series

Procedia PDF Downloads 122

Authors: Toktam Khatibi

Abstract:

Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.

Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers

Procedia PDF Downloads 75

Authors: David P. Tantua, Abdulkader Helwan

Abstract:

Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

Procedia PDF Downloads 366