Search results for: personalized medicine application

Authors: Qianjia Cheng, Hongquan Jiang

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Crowdsourcing solves the problems that computers can't handle by integrating computers and the Internet. Its extensive knowledge sources, high efficiency, and high quality have made crowdsourcing attract wide attention in industry and academia in recent years. The development of online crowdsourcing platforms such as Clickworker, Amazon Mechanical Turk(Mturk) tends to mature gradually. This paper sorts out the concept of crowdsourcing, sorts out the workflow of competitive crowdsourcing, summarizes the related technologies of crowdsourcing based on workflow, quality control, cost control, and delay control, and introduces the typical crowdsourcing platform. Finally, we highlight some open problems of the current crowdsourcing and present some future research directions in this area.

Keywords: application, crowdsourcing, crowdsourcing platform, system architecture

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Authors: Mustapha Abdulsalam, R. N. Ahmed

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Nauclea latifolia is one of the medicinal plants used in traditional Nigerian medicine in the treatment of various diseases such as fever, toothaches, malaria, diarrhea among several other conditions. Nauclea latifolia leaf extract acts as a capping and reducing agent in the formation of silver nanoparticles. Silver nanoparticles (AgNPs) were synthesized using a combination of aqueous extract of Nauclea latifolia and 1mM of silver nitrate (AgNO₃) solution to obtain concentrations of 100mg/ml-400mg/ml. Characterization of the particles was done by UV-Vis spectroscopy and Fourier transform infrared (FTIR). In this study, aqueous as well as ethanolic extract of leaf of Nauclea latifolia were investigated for antibacterial activity using the standard agar well diffusion technique against three clinical isolates (Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa). The Minimum Inhibitory Concentration (MIC) was achieved by microbroth dilution method and Minimum Bactericidal Concentration (MBC) was also determined by plate assay. Characterization by UV-visible spectrometry revealed peak absorbance of 0.463 at 450.0nm, while FTIR showed the presence of two functional groups. At 400mg/ml, the highest inhibitory activities were observed with S.aureus and E.coli with zones of inhibition measuring 20mm and 18mm respectively. The MIC was obtained at 400mg/ml while MBC was at a higher concentration. The data from this study indicate the potential of silver nanoparticle of Nauclea latifolia as a suitable alternative antibacterial agent for incorporation into orthodox medicine in health care delivery in Nigeria.

Keywords: agar well diffusion, antimicrobial activity, Nauclea latifolia, silver nanoparticles

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Nazmul Huda, Ashik Mosaddik, Abdul Awal, Shafiqur Rahman, Rukhsana Shaheen, Mustofa Nabi

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Polyherbal formulation Sharbat Deenar is a very popular unani medicine in Bangladesh. It is usually used for different kinds of liver disorders. In absence of reliable and inadequate hepatoprotective agents in conventional medicine, the herbal preparations are preferred for liver diseases. The present study was designed to evaluate the hepatoprotective activity of Sharbat Deenar on carbon tetrachloride (CCl₄) induced hepatotoxicity in male Long-Evans albino rats. Group I served as normal control and received neither formulation nor carbon tetrachloride. Group II received only CCl₄ 1mL/kg body weight of rat intraperitoneally for consecutive 14 days. Group III received CCl₄ 1mL/kg body weight of rat intraperitoneally and Silymarin, in dose 50mg/kg body weight of rat orally. Group IV received CCl₄ 1mL/kg body weight of rat intraperitoneally and Sharbat Deenar 1mL/kg body weight of rat for the same 14 consecutive days. At the end of the study, hepatoprotective activity was evaluated by the levels of total bilirubin, alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP). Histopathological study of rat liver was also carried out. The results showed that polyherbal formulation Sharbat Deenar exhibited a significant hepatoprotective effect. Such an outcome seems to be the synergistic effect of all ingredients of tested herbal formulation. Although this study suggests that Sharbat Deenar may be used to cure or minimize various liver diseases, it needs further study to attain the clarity of mechanism and safety.

Keywords: polyherbal formulation, sharbat deenar, carbon tetrachloride, silymarin, hepatoprotective

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Authors: Jin Woong Lee, Kyuman Cho, Taehoon Kim

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The application of constructability is increasingly required not only in the construction phase but also in the whole project stage. In particular, the proper application of construction experience and knowledge during the design phase enables the minimization of inefficiencies such as design changes and improvements in constructability during the construction phase. In order to apply knowledge effectively, engineering technology efforts should be implemented with design progress. Among many engineering technologies, engineering for temporary works, including facilities, equipment, and other related construction methods, is important to improve constructability. Therefore, as basic research, this study investigates the applicability of temporary work engineering during the design phase in the building construction industry. As a result, application of temporary work engineering has a greater impact on construction cost reduction and constructability improvement. In contrast to the existing design-bid-build method, the turn-key and CM (construct management) procurement methods currently being implemented in Korea are expected to have a significant impact on the direction of temporary work engineering. To introduce temporary work engineering, expert/professional organization training is first required, and a lack of client awareness should be preferentially improved. The results of this study are expected to be useful as reference material for the development of more effective temporary work engineering tasks and work processes in the future.

Keywords: Temporary Work Engineering, Design Phase, Constructability, Building Construction

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Authors: Rajeev Kumar, Harishankar Kumar

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Fragmented data silos within enterprises impede the extraction of meaningful insights and hinder efficiency in tasks such as product development, client understanding, and meeting preparation. To address this, we propose a system-agnostic framework that leverages large language models (LLMs) to unify diverse data sources into a cohesive, user-centered knowledge graph. By automating entity extraction, relationship inference, and semantic enrichment, the framework maps interactions, behaviors, and data around the user, enabling intelligent querying and reasoning across various data types, including emails, calendars, chats, documents, and logs. Its domain adaptability supports applications in contextual search, task prioritization, expertise identification, and personalized recommendations, all rooted in user-centric insights. Experimental results demonstrate its effectiveness in generating actionable insights, enhancing workflows such as trip planning, meeting preparation, and daily task management. This work advances the integration of knowledge graphs and LLMs, bridging the gap between fragmented data systems and intelligent, unified enterprise solutions focused on user interactions.

Keywords: knowledge graph, entity extraction, relation extraction, LLM, activity graph, enterprise intelligence

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Authors: C. C. Liang

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MSN used to be the most popular application for communicating among social networks, but Facebook chat is now the most popular. Facebook and MSN have similar characteristics, including usefulness, ease-of-use, and a similar function, which is the exchanging of information with friends. Facebook outperforms MSN in both of these areas. However, the adoption of Facebook and abandonment of MSN have occurred for other reasons. Functions can be improved, but users’ willingness to use does not just depend on functionality. Flow status has been established to be crucial to users’ adoption of cyber applications and to affects users’ adoption of software applications. If users experience flow in using software application, they will enjoy using it frequently, and even change their preferred application from an old to this new one. However, no investigation has examined choice behavior related to switching from Facebook to MSN based on a consideration of flow experiences and functions. This investigation discusses the flow experiences and functions of social-networking applications. Flow experience is found to affect perceived ease of use and perceived usefulness; perceived ease of use influences information ex-change with friends, and perceived usefulness; information exchange influences perceived usefulness, but information exchange has no effect on flow experience.

Keywords: consumer behavior, social media, technology acceptance model, flow experience

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Authors: Walaa Mohammed Metwally

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This case study used the action research concept as a tool to integrate the innovation in a learning experience on a design course. The action research was investigated at Prince Sultan University, College of Engineering in the Interior Design and Architecture Department in January 2015, through the Higher Education Academy program. The action research was presented first with the definition of the research, leading to how it was used and how solutions were found. It concluded by showing that once the action research application in interior design and architecture were studied it was an effective tool to improve student’s learning, develop their practice in design courses, and it discussed the negative and positive issues that were encountered.

Keywords: action research, innovation, intervention, learning experience, peer review

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Authors: Fariborz Shekari, Abdollah Javanmard, Amin Abbasi

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A pot experiment conducted to evaluate the response of two red bean cultivars, Sayad and Derakhshan, to water deficit stress during post-flowering growth stage and recovery potential of plants after stress. Treatments were included regular irrigation or control, water deficit during flowering stage, water deficit during pod formation and water deficit during pod filling period. Results showed that plant height had positive effects on yield of cultivars so that, the tall cultivar, ‘Sayad’, had higher yields. Stress application during flowering stage showed the highest negative impact on plant height and subsequently yield. The longest and the higher number of pods as well as the greatest number of seeds in pods were recorded in control treatment in ‘Sayad’. Stress application during pod formation resulted in the minimum amount of all studied traits in both cultivars. Stress encountered during seed filling period had the least effect on number and length of pods and seed/pod. However, 100 seeds weight significantly decreased. The highest amount for 100 seeds weight was record in control plants in ‘Derakhshan’. Under all treatments, ‘Sayad’ had higher biologic and seed yield compared to ‘Derakhshan’. The least amount of yield was recorded during stress application in pod formation and flowering period for ‘Sayad’ and ‘Derakhshan’ respectively. Harvest index of ‘Sayad’ was more affect by stress application. Data related to photosynthetic rate showed that during stress application, ‘Derakhshan’ owned rapid decline in photosynthesis. Beyond stress alleviation and onset of irrigation, recovery potential of ‘Sayad’ was higher than ‘Derakhshan’ and this cultivar was able to rapidly restore the photosynthesis rate of stress faced plants near control ones. In total, stress had lower impacts on photosynthetic rate of ‘Sayad’ cultivar.

Keywords: common bean, water stress, yield, yield components, photosynthetic rate

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Authors: Saiakhil Chilaka

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Juvenile recidivism presents a significant challenge to the criminal justice system, impacting both the individuals involved and broader societal safety. This study aims to identify the key factors influencing recidivism and successful rehabilitation outcomes by utilizing a dataset of over 25,000 individuals from the NIJ Recidivism Challenge. We employed machine learning techniques, particularly Random Forest Classification, combined with SHAP (SHapley Additive exPlanations) for model interpretability. Our findings indicate that supervision risk score, percent days employed, and education level are critical factors affecting recidivism, with higher levels of supervision, successful employment, and education contributing to lower recidivism rates. Conversely, Gang Affiliation emerged as a significant risk factor for reoffending. The model achieved an accuracy of 68.8%, highlighting its utility in identifying high-risk individuals and informing targeted interventions. These results suggest that a comprehensive approach involving personalized supervision, vocational training, educational support, and anti-gang initiatives can significantly reduce recidivism and enhance rehabilitation outcomes for juveniles, providing critical insights for policymakers and juvenile justice practitioners.

Keywords: juvenile, justice system, data analysis, SHAP

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Authors: Mohammad Hashemi, John Herbert

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Quantifying and measuring Quality of Experience (QoE) are important and difficult concerns in Human Computer Interaction (HCI). Quality of Service (QoS) and the actual User Interface (UI) of the application are both important contributors to the QoE of a user. This paper describes a framework that measures accurately the way a user uses the UI in order to model users' behaviours and profiles. It monitors the use of the mouse and use of UI elements with accurate time measurement. It does this in real-time and does so unobtrusively and efficiently allowing the user to work as normal with the application. This real-time accurate measurement of the user's interaction provides valuable data and insight into the use of the UI, and is also the basis for analysis of the user's QoE.

Keywords: user modelling, user interface experience, quality of experience, user experience, human and computer interaction

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Authors: Vanessa G. P. Severino, JOÃO Gabriel M. Junqueira, Michelle N. G. do Nascimento, Francisco W. B. Aquino, João B. Fernandes, Ana P. Terezan

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The scientific interest in analyzing VOCs represents a significant modern research field as a result of importance in most branches of the present life and industry. Therefore it is extremely important to investigate, identify and isolate volatile substances, since they can be used in different areas, such as food, medicine, cosmetics, perfumery, aromatherapy, pesticides, repellents and other household products through methods for extracting volatile constituents, such as solid phase microextraction (SPME), hydrodistillation (HD), solvent extraction (SE), Soxhlet extraction, supercritical fluid extraction (SFE), stream distillation (SD) and vacuum distillation (VD). The Chemometrics is an area of chemistry that uses statistical and mathematical tools for the planning and optimization of the experimental conditions, and to extract relevant chemical information multivariate chemical data. In this context, the focus of this work was the study of the chemical VOCs by SPME of the specie X. aromatica, in search of constituents that can be used in the industrial sector as well as in food, cosmetics and perfumery, since these areas industrial has a considerable role. In addition, by chemometric analysis, we sought to maximize the answers of this research, in order to search for the largest number of compounds. The investigation of flowers from X. aromatica in vitro and in alive mode proved consistent, but certain factors supposed influence the composition of metabolites, and the chemometric analysis strengthened the analysis. Thus, the study of the chemical composition of X. aromatica contributed to the VOCs knowledge of the species and a possible application.

Keywords: chemometrics, flowers, HS-SPME, Xylopia aromatica

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Authors: Yutong An

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Premature babies in the Neonatal Intensive Care Unit (NICU) are usually protected in individual incubators to ensure a constant temperature and humidity. Accompanied by 24-hour monitoring by medical equipment, this provides a considerable degree of protection for the growth of preterm babies. However, preterm babies are still continuously exposed to noise at excessively high decibels (>45dB). Such noise has a highly damaging effect on the growth and development of preterm babies. For example, in the short term, it can lead to sleep deprivation, stress reactions, and difficulty calming emotions, while in the long term, it can trigger endocrine disorders, metabolic disorders, and hearing impairment. Fortunately, musical interventions in the NICU have been shown to provide calmness to newborns. This article integrates existing research on three types of music that are beneficial for preterm infants and their respective advantages and disadvantages. This paper aims to present a possibility, based on existing NICU equipment and experimental data related to musical interventions, to reduce the impact of noise on preterm babies in the NICU through a system design approach that incorporates a personalized adjustable music system in the incubator and an overall music enhancement in the open bay of the NICU.

Keywords: music interventions, neonatal intensive care unit (NICU), premature babies, neonatal nursing

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Authors: V. Nigam, V. Nambiar

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Aegle Marmelos leaf has been used as a remedy for various gastrointestinal infections and lowering blood sugar level in traditional system of medicine in India due to the presence of various constituents such as flavonoids, tannins and alkaloids (eg. Aegelin, Marmelosin, Luvangetin).The objective of the present study was to evaluate the total antioxidant activity, total and individual phenol content of the wild and cultivated variety of Aegle marmelos leaves to assess the role of this plant in ethanomedicine in India. The methanolic extracts of the leaves were screened for total antioxidant capacity through Ferric Reducing Antioxidant Potential (FRAP) and 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay; Total Phenol content (TPC) through spectrophotometric technique based on Folin Ciocalteau assay and for qualitative estimation of phenols, High performance Liquid Chromatography was used. The TPC of wild and cultivated variety was 7.6% and 6.5% respectively whereas HPLC analysis for quantification of individual polyphenol revealed the presence of gallic acid, chlorogenic acid and Ferullic acid in wild variety whereas gallic acid, Ferullic acid and pyrocatechol in cultivated variety. FRAP values and IC 50 value (DPPH) for wild and cultivated variety was 14.65 μmol/l and 11.80μmol/l; 437 μg/ml and 620μg/ml respectively and thus it can be used as potential inhibitor of free radicals. The wild variety was having more antioxidant capacity than the cultivated one it can be exploited further for its therapeutic application. As Aegle marmelos is rich in antioxidant, it can be used as food additives to delay the oxidative deterioration of foods and as nutraceutical in medicinal formulation against degenerative diseases like diabetes.

Keywords: antioxidant activity, aegle marmelos, antidiabetic, nutraceutical

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Authors: Golnaz Shahtahmassebi, Jose Maria Sarabia

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In this talk, we introduce a new class of conjugate prior distributions obtained from conditional specification methodology. We illustrate the application of such distribution in Bayesian change point detection in Poisson processes. We obtain the posterior distribution of model parameters using a general bivariate distribution with gamma conditionals. Simulation from the posterior is readily implemented using a Gibbs sampling algorithm. The Gibbs sampling is implemented even when using conditional densities that are incompatible or only compatible with an improper joint density. The application of such methods will be demonstrated using examples of simulated and real data.

Keywords: change point, bayesian inference, Gibbs sampler, conditional specification, gamma conditional distributions

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Authors: Liu Ziyu, Gao Yongfeng, Li Muhua, Zhao Jiahao, Meng Song

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The effect of thermal shock on the operation of micro electromechanical systems (MEMS) were examined. All MEMS device were tested before and after three different conditions of thermal shock (from -55℃ to 85℃, from -65℃ to 125℃, from -65℃ to 200℃). The micro lens showed no changes after thermal shock, which shows that the design of the micro lens can be well adapted to the application environment in the space. The design of the micro mirror can be well adapted to the space application environment. The micro-magnetometer, RF MEMS switch and the micro accelerometer exhibited degradation and parameter drift after thermal shock, potential mechanical was proposed.

Keywords: MEMS, thermal shock test, reliability, space environment

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Paulina Ojeda, Damaris Estrella, Hector Rubio

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Insomnia is a disorder characterized by difficulty falling asleep, staying asleep or both. It negatively affects the life quality of people, it hinders the concentration, attention, memory, motor skills, among other abilities that complicate work or learning. Some studies show that women are more susceptible to insomnia. Medicine curricula usually involve a great deal of theoretical and memory content, especially in the early years of the course. The way to accredit a university course is to demonstrate the level of competence or acquired knowledge. In Mexico the most widely used form of measurement is written exams, with numerical scales results. The prevalence of sleep disorders in university students is usually high, so it is important to know if insomnia has an effect on school performance in men and women. A cross-sectional study was designed that included a probabilistic sample of 118 regular students from the School of Medicine of the Autonomous University of Yucatan, Mexico. All on legally age. The project was authorized by the School of Medicine and all the ethical implications of the case were monitored. Participants completed anonymously the following questionnaires: Pittsburgh Sleep Quality Index, Insomnia Severity Index, AUDIT test, epidemiological and clinical data. Academic performance was assessed by the average number of official grades earned on written exams, as well as the number of approved or non-approved courses. These data were obtained officially through the corresponding school authorities. Students with at least one unapproved course or average less than 70 were considered to be poor performers. With all courses approved and average between 70-79 as regular performance and with an average of 80 or higher as a good performance. Statistical analysis: t-Student, difference of proportions and ANOVA. 65 men with a mean age of 19.15 ± 1.60 years and 53 women of 18.98 ± 1.23 years, were included. 96% of the women and 78.46% of the men sleep in the family home. 16.98% of women and 18.46% of men consume tobacco. Most students consume caffeinated beverages. 3.7% of the women and 10.76% of the men complete criteria of harmful consumption of alcohol. 98.11% of the women and 90.76% of the men are perceived with poor sleep quality. Insomnia was present in 73% of women and 66% of men. Women had higher levels of moderate insomnia (p=0.02) compared to men and only one woman had severe insomnia. 50.94% of the women and 44.61% of the men had poor academic performance. 18.86% of women and 27% of men performed well. Only in the group of women we found a significant association between poor performance with mild (p= 0.0035) and moderate (p=0.031) insomnia. The medical students reported poor sleep quality and insomnia. In women, levels of insomnia were associated with poor academic performance.

Keywords: scholar-average, sex, sleep, university

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Authors: Diogo Ribeiro, Teresa Neto, Ricardo Santos, Maria Portela, Alexandra Trincão

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This article describes a set of innovating student recruitment strategies in a 1st cycle course of Civil Engineering, in particular the Civil Engineering Degree from the School of Engineering - Polytechnic of Porto (ISEP-PP). The strategies described were two-fold, targeting, for one, the increment on the number of admissions for the degree’s first year and two, promoting the re-entry of students who, for whatever reason, interrupted their studies. For the first objective, teacher-student binomials were set, whilst for the second, personalized contacts and assistance were provided. The main initiatives were promoted by the team of degree directors and were upheld with the participation and in consonance with the School’s external relations office. These initiatives were put forward as an attempt to minimize the impact of a national and international crisis on the AEC industry when the sustainability of the course was at risk. The implementation of these strategies was assessed on basis of a statistical analysis of the data collected from official sources and by surveys promoted. The results showed that the re-entry boost of former students, attending classes scattered on the three curricular years, secured registrations on some Curricular Units (UC’s) which more than doubled their numbers. Accompanied by a still incipient but regained interest on Civil Engineering it was possible in the short span of three years to reset the number of new students from less than 10 to the currently maximum allowed of 75, and so invert the tendency of an abrupt decline on the total number of students enrolled on the degree.

Keywords: civil engineering, monitoring, performance indicators, strategies, student recruitment

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Authors: Natalia Marulanda, Henry González, Gonzalo León, Alejandro Hincapié

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Continuous improvement tools are the result of a set of studies that developed theories and methodologies. These methodologies enable organizations to increase their levels of efficiency, effectiveness, and productivity. Based on these methodologies, lean manufacturing philosophy, which is based on the optimization of resources, waste disposal, and generation of value to products and services, was developed. Lean application has been massive globally, but Colombian companies have been made it incipiently. Therefore, the purpose of this article is to identify the impacts generated by the implementation of lean manufacturing tools in five companies located in Colombia and Medellín metropolitan area. It also seeks to make a comparison of the results obtained from the implementation of lean philosophy and Theory of Constraints. The methodology is qualitative and quantitative, is based on the case study interview from dialogue with the leaders of the processes that used lean tools. The most used tools by research companies are 5's with 100% and TPM with 80%. The less used tool is the synchronous production with 20%. The main reason for the implementation of lean was supply chain management with 83.3%. For the application of lean and TOC, we did not find significant differences between the impact, in terms of methodology, areas of application, staff initiatives, supply chain management, planning, and training.

Keywords: business strategy, lean manufacturing, theory of constraints, supply chain

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Authors: A. C. Khor, M. R. Mohamed, M. H. Sulaiman, M. R. Daud

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Packaging for vanadium redox flow battery is one of the key elements for successful implementation of flow battery in the electrical energy storage system. Usually the bulky battery size and low energy densities make this technology not available for mobility application. Therefore RFB with improved packaging size and energy capacity are highly desirable. This paper focuses on the study of packaging improvement for unit cell V-RFB to the application on Series Hybrid Electric Vehicle. Two different designs of 25 cm2 and 100 cm2 unit cell V-RFB at same current density are used for the sample in this investigation. Further suggestions on packaging improvement are highlighted.

Keywords: electric vehicle, redox flow battery, packaging, vanadium

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Authors: Ebru Esen, Omer Akkaya, Nattanan Pankrobkaew

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Though the experience concept found its place in the field of marketing in 1982, it is today in front of us as an important phenomenon in understanding the consumer behaviours. In parallel with the globalization and intensification of the competition, the enterprises have been in an effort to provide unique experiences for their consumers by going beyond providing services with the products. In this context, experience-oriented marketing enables the enterprises to use the marketing strategies of providing experiences for their customers and to have advantages in terms of competition. Based on it, this article discusses the concepts of experience, experience-oriented marketing and buying behaviour of consumers as a whole, and details about the application conducted in Konya Selcuklu University.

Keywords: consumer behavior, experience, experience marketing, marketing

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Authors: Layan Kateb, Jawaher Ragban, Rawia Alamri, Rewaa Alhazmi

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This paper evaluates user satisfaction with the AI functionality of Coconote, an innovative app designed to transform raw input -documents, voice recordings, and video recordings- into structured study materials such as flashcards, study guides, and transcripts. Leveraging AI-driven natural language processing and summarization algorithms, Coconote aims to streamline the study process by providing personalized, accessible, and accurate learning tools. To measure user satisfaction, we conducted a survey among 20 participants, including students, educators, and professionals, who tested the app’s core features over a two-week period. The survey assessed criteria such as ease of use, accuracy of generated materials, and perceived value in enhancing productivity. Results indicate high satisfaction levels with the app’s ability to produce coherent and concise outputs, with 83% of respondents reporting improved study efficiency. However, feedback highlighted areas for improvement, including occasional inaccuracies in transcription and customization limitations in flashcard formatting. This study demonstrates the potential of AI to transform learning methods and identifies key areas for refinement in user-centric design. Coconote represents a step forward in leveraging AI to enhance educational technology

Keywords: tools for students, artificial intelligence in education, AI study tool, ethical AI tools

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Authors: Andrew White, Abigail Lowe, Kory Watkins, Hamed Akhlaghi, Nicole Winter

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The timing and appropriateness of diagnostic imaging are critical to the evaluation and management of traumatic injuries. Within the subclass of trauma patients, the prevalence of c-spine injury is less than 4%. However, the incidence of delayed diagnosis within this cohort has been documented as up to 20%, with inadequate radiological examination most cited issue. In order to assess those in which c-spine injury cannot be fully excluded based on clinical examination alone and, therefore, should undergo diagnostic imaging, a set of criteria is used to provide clinical guidance. The NEXUS (National Emergency X-Radiography Utilisation Study) criteria is a validated clinical decision-making tool used to facilitate selective c-spine radiography. The criteria allow clinicians to determine whether cervical spine imaging can be safely avoided in appropriate patients. The NEXUS criteria are widely used within the Emergency Department setting given their ease of use and relatively straightforward application and are used in the Victorian State Trauma System’s guidelines. This audit utilized retrospective data collection to examine the concordance of c-spine imaging in trauma patients to that of the NEXUS criteria and assess compliance with state guidance on diagnostic imaging in trauma. Of the 183 patients that presented with trauma to the head, neck, or face (244 excluded due to incorrect triage), 98 did not undergo imaging of the c-spine. Out of those 98, 44% fulfilled at least one of the NEXUS criteria, meaning the c-spine could not be clinically cleared as per the current guidelines. The criterion most met was intoxication, comprising 42% (18 of 43), with midline spinal tenderness (or absence of documentation of this) the second most common with 23% (10 of 43). Intoxication being the most met criteria is significant but not unexpected given the cohort of patients seen at St Vincent’s and within many emergency departments in general. Given these patients will always meet NEXUS criteria, an element of clinical judgment is likely needed, or concurrent use of the Canadian C-Spine Rules to exclude the need for imaging. Midline tenderness as a met criterion was often in the context of poor or absent documentation relating to this, emphasizing the importance of clear and accurate assessments. The distracting injury was identified in 7 out of the 43 patients; however, only one of these patients exhibited a thoracic injury (T11 compression fracture), with the remainder comprising injuries to the extremities – some studies suggest that C-spine imaging may not be required in the evaluable blunt trauma patient despite distracting injuries in any body regions that do not involve the upper chest. This emphasises the need for standardised definitions for distracting injury, at least at a departmental/regional level. The data highlights the currently poor application of the NEXUS guidelines, with likely common themes throughout emergency departments, highlighting the need for further education regarding implementation and potential refinement/clarification of criteria. Of note, there appeared to be no significant differences between levels of experience with respect to inappropriately clearing the c-spine clinically with respect to the guidelines.

Keywords: imaging, guidelines, emergency medicine, audit

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

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Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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Authors: Sirine Sayed, Mostapha Tarfaoui, Abdelmalek Toumi, Youssef Qarssis, Mohamed Daly, Chokri Bouraoui

Abstract:

This paper delves into the combination of additive manufacturing (AM) and artificial intelligence (AI) to solve challenges related to the mechanical behavior of AM-produced parts. The article highlights the fundamentals and benefits of additive manufacturing, including creating complex geometries, optimizing material use, and streamlining manufacturing processes. The paper also addresses the challenges associated with additive manufacturing, such as ensuring stable mechanical performance and material properties. The role of AI in improving the static behavior of AM-produced parts, including machine learning, especially the neural network, is to make regression models to analyze the large amounts of data generated during experimental tests. It investigates the potential synergies between AM and AI to achieve enhanced functions and personalized mechanical properties. The mechanical behavior of parts produced using additive manufacturing methods can be further improved using design optimization, structural analysis, and AI-based adaptive manufacturing. The article concludes by emphasizing the importance of integrating AM and AI to enhance mechanical operations, increase reliability, and perform advanced functions, paving the way for innovative applications in different fields.

Keywords: additive manufacturing, mechanical behavior, artificial intelligence, machine learning, neural networks, reliability, advanced functionalities

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Authors: Akinbuluma Ayodeji Theophilus, Adewale Olutaiwo

Abstract:

When building roads and paved surfaces, a strong foundation is always essential. A durable material that can withstand years of traffic while staying trustworthy must be used to build the foundation. A frequent problem in the construction of roads and pavements is the lack of high-quality, long-lasting materials for the pavement structure (base, subbase, and subgrade). Hence, this study examined the stabilization of lateritic soil samples from Ijoko with cement kiln dust and lime. The study adopted the experimental design. Laboratory tests were conducted on classification, swelling potential, compaction, California bearing ratio (CBR), and unconfined compressive tests, among others, were conducted on the laterite sample treated with cement kiln dust (CKD) and lime in incremental order of 2% up to 10% of dry weight soft soil sample. The results of the test showed that the studied soil could be classified as an A-7-6 and CL soil using the American Association of State Highway and transport officials (AASHTO) and the unified soil classification system (USCS), respectively. The plasticity (PI) of the studied soil reduced from 30.5% to 29.9% at the application of CKD. The maximum dry density on the application of CKD reduced from 1.9.7 mg/m3 to 1.86mg/m3, and lime application yielded a reduction from 1.97mg/m3 to 1.88.mg/m3. The swell potential on CKD application was reduced from 0.05 to 0.039%. The study concluded that soil stabilizations are effective and economic way of improving road pavement for engineering benefit. The degree of effectiveness of stabilization in pavement construction was found to depend on the type of soil to be stabilized. The study therefore recommended that stabilized soil mixtures should be used to subbase material for flexible pavement since is a suitable.

Keywords: lateritic soils, sand, cement, stabilization, road pavement

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Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

Abstract:

Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: ecosystem, business model, personal data, preventive healthcare

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Authors: Mohammad Reza Haj Seyed Hadi, Fereshteh Ghanepasand, Mohammad Taghi Darzi

Abstract:

The main objective of this study was to determine the effects of Nitrogen fixing bacteria and manure application on the seed yield and yield components in black cumin (Nigella sativa L.). The experiment was carried out at the RAN Research Station in Firouzkouh in 2012. A 4×4 factorial experiment, arranged in a randomized complete blocks designed with three replications. The treatments consisted of 4 level of nitrogen fixing bacteria (control, Azotobacter, Azospirillum and Azotobacter + Azospirillum) and 4 level of manure (0, 2.5, 5 and 7.5 ton ha-1). The present results have shown that the highest height, 1000 seeds weight, seed number per follicle, follicle yield, seed yield and harvest index were obtained after using Azotobacter and Azospirillum, simultaneously. Manure application only affects on follicle yield and by 5ton manure ha-1 the highest follicle yield obtained. Results of this investigation showed that the maximum seed yield obtained when Aotobacter+Azospirillum inoculated with black cumin seeds and 5 ton manure ha-1 applied. Combined application of nitrogen fixing bacteria and manure can be helpful in developing of production and yield in Black cumin.

Keywords: azotobacter, azospirillum, black cumin, yield, yield components

Procedia PDF Downloads 470