Search results for: artificial vision
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3060

Search results for: artificial vision

1020 Investigation of Corrosion of Steel Buried in Unsaturated Soil in the Presence of Cathodic Protection: The Modified Voltammetry Technique

Authors: Mandlenkosi G. R. Mahlobo, Peter A. Olubambi, Philippe Refait

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The aim of this study was to use voltammetry as a method to understand the behaviour of steel in unsaturated soil in the presence of cathodic protection (CP). Three carbon steel coupons were buried in artificial soil wetted at 65-70% of saturation for 37 days. All three coupons were left at open circuit potential (OCP) for the first seven days in the unsaturated soil before CP, which was only applied on two of the three coupons at the protection potential -0.8 V vs Cu/CuSO₄ for the remaining 30 days of the experiment. Voltammetry was performed weekly on the coupon without CP, while electrochemical impedance spectroscopy (EIS) was performed daily to monitor and correct the applied CP potential from the ohmic drop. Voltammetry was finally performed on the last day on the coupons under CP. All the voltammograms were modeled with mathematical equations in order to compute the electrochemical parameters and subsequently deduced the corrosion rate of the steel coupons. For the coupon without CP, the corrosion rate was determined at 300 µm/y. For the coupons under CP, the residual corrosion rate under CP was estimated at 12 µm/y while the corrosion rate of the coupons, after interruption of CP, was estimated at 25 µm/y. This showed that CP was efficient due to two effects: a direct effect from the decreased potential and an induced effect associated with the increased interfacial pH that promoted the formation of a protective layer on the steel surface.

Keywords: carbon steel, cathodic protection, voltammetry, unsaturated soil, Raman spectroscopy

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1019 A Literature Review about Responsible Third Cycle Supervision

Authors: Johanna Lundqvist

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Third cycle supervision is a multifaceted and complex task for supervisors in higher education. It progresses over several years and is affected by several proximal and distal factors. It can result in positive learning outcomes for doctoral students and high-quality publications. However, not all doctoral students thrive during their doctoral studies; nor do they all complete their studies. This is problematic for both the individuals themselves as well as society at large: doctoral students are valuable and important in current research, future research and higher education. The aim of this literature review is to elucidate what responsible third cycle supervision can include and be in practice. The question posed is as follows: according to recent literature, what is it that characterises responsible third cycle supervision in which doctoral students can thrive and develop their research knowledge and skills? A literature review was conducted, and the data gathered from the literature regarding responsible third cycle supervision was analysed by means of a thematic analysis. The analysis was inspired by the notion of responsible inclusion outlined by David Mitchell. In this study, the term literature refers to research articles and regulations. The results (preliminary) show that responsible third cycle supervision is associated with a number of interplaying factors (themes). These are as follows: committed supervisors and doctoral students; a clear vision and research problem; an individual study plan; adequate resources; interaction processes and constructive feedback; creativity; cultural awareness; respect and research ethics; systematic quality work and improvement efforts; focus on overall third cycle learning goals; and focus on research presentations and publications. Thus, responsible third cycle supervision can occur if these factors are realized in practice. This literature review is of relevance to evaluators, researchers, and management in higher education, as well as third cycle supervisors.

Keywords: doctoral student, higher education, third cycle supervisors, third cycle programmes

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1018 A Reflection: Looking the Pattern of Political Party (Gerindra Party) Campaign by Social Media in Indonesia General Election 2014

Authors: Clara Stella Anugerah

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This study actually is a reflection of the general election in 2014. The researcher was interested in this case as the assessment of several phenomenons that happened recently. One of them is the use of social media for the campaign. By this modern era, social media becomes closer with society. It gains the communication process, and by the time being communicating others also becomes easier than before. Furthermore, social media can minimize the cost of communication with many people as a far distance that often comes to be an obstacle of communication does not become a big problem anymore. In Indonesia, the advantages of social media were used by a political party, Gerindra, to face the election that was held on 2014. Actually Gerindra is a newly formed political party that was established in 2008. In spite of Gerindra is the new comer in the election, according to the General Election Committee’s data in Indonesia, Gerindra has the biggest budget than others to cost campaign in social media. Because of that, this research wants to look “how is the pattern of Gerindra party’s campaign to face the general election in 2014? To ask that question, the theory used for this research is campaign method based on ICT (Information Communication Technology) by Rummele. According to the rummele, Gerindra was a party that used a product of social media massively, mainly facebook and twitter. According to that observation, this research focus on campaign that had been done by Gerindra in both of those social media by the time window given by KPU (General Election Committee) on Maret 16th until April 5th, 2014. The conclusion was derived by content analysis method that was used in the methodology. In this context, that method was used while interpreting the content uploaded by Gerindra to facebook or twitter, such as picture and writing. Finally, by that method and reflecting the rummele theory, this research inferred that the patern used for Gerindra’s campaign in social media tends to be top-down. It means: Gerindra showed uncommunicative tendency in social media and only want to catch much mass without mentioned a mission and vision clearly.

Keywords: Gerindra party, political party, social media, campaign, general election on 2014

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1017 Structural Strength Potentials of Nigerian Groundnut Husk Ash as Partial Cement Replacement in Mortar

Authors: F. A. Olutoge, O.R. Olulope, M. O. Odelola

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This study investigates the strength potentials of groundnut husk ash as partial cement replacement in mortar and also develops a predictive model using Artificial Neural Network. Groundnut husks sourced from Ogbomoso, Nigeria, was sun dried, calcined to ash in a furnace at a controlled temperature of 600⁰ C for a period of 6 hours, and sieved through the 75 microns. The ash was subjected to chemical analysis and setting time test. Fine aggregate (sand) for the mortar was sourced from Ado Ekiti, Nigeria. The cement: GHA constituents were blended in ratios 100:0, 95:5, 90:10, 85:15 and 80:20 %. The sum of SiO₂, Al₂O₃, and Fe₂O₃ content in GHA is 26.98%. The compressive strength for mortars PC, GHA5, GHA10, GHA15, and GHA20 ranged from 6.3-10.2 N/mm² at 7days, 7.5-12.3 N/mm² at 14 days, 9.31-13.7 N/mm² at 28 days, 10.4-16.7 N/mm² at 56days and 13.35- 22.3 N/mm² at 90 days respectively, PC, GHA5 and GHA10 had competitive values up to 28 days, but GHA10 gave the highest values at 56 and 90 days while GHA20 had the lowest values at all ages due to dilution effect. Flexural strengths values at 28 days ranged from 1.08 to 1.87 N/mm² and increased to a range of 1.53-4.10 N/mm² at 90 days. The ANN model gave good prediction for compressive strength of the mortars. This study has shown that groundnut husk ash as partial cement replacement improves the strength properties of mortar.

Keywords: compressive strength, groundnut husk ash, mortar, pozzolanic index

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1016 The Orthodontic Management of Multiple Tooth Agenesis with Macroglossia in Adult Patient: Case Report

Authors: Yanuarti Retnaningrum, Cendrawasih A. Farmasyanti, Kuswahyuning

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Orthodontists find challenges in treating patients who have cases of macroglossia and multiple tooth agenesis because difficulties in determining the causes, formulating a diagnosis and the potential for relapse after treatment. Definition of macroglossia is a tongue enlargement due to muscle hypertrophy, tumor or an endocrine disturbance. Macroglossia may cause many problems such as anterior proclination of upper and lower incisors, development of general diastema and anterior and/ or posterior open bite. Treatment for such patients with multiple tooth agenesis and macroglossia can be complex and must consider orthodontic and/or surgical interventions. This article discusses an orthodontic non surgical approach to a patient with a general diastema in both maxilla and mandible associated with multiple tooth agenesis and macroglossia. Fixed orthodontic therapy with straightwire appliance was used for space closure in anterior region of maxilla and mandible, also to create a space suitable for future prosthetic restoration. After 12 months treatment, stable and functional occlusal relationships was achieved, although still have edentulous area in both maxilla and mandible. At the end of the orthodontic treatment was obtained with correct overbite and overjet values. After removal of the brackets, a maxillary and mandibular removable retainer combine with artificial tooth were placed for retention.

Keywords: general diastema, macroglossia, space closure, tooth agenesis

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1015 AI as a Tool Hindering Digital Education

Authors: Justyna Żywiołek, Marek Matulewski

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The article presents the results of a survey conducted among students from various European countries. The aim of the study was to understand how artificial intelligence (AI) affects educational processes in a digital environment. The survey covered a wide range of topics, including students' understanding and use of AI, its impact on motivation and engagement, interaction and support issues, accessibility and equity, and data security and privacy concerns. Most respondents admitted having difficulties comprehending the advanced functions of AI in educational tools. Many students believe that excessive use of AI in education can decrease their motivation for self-study and active participation in classes. Additionally, students reported that interaction with AI-based tools is often less satisfying compared to direct contact with teachers. Furthermore, the survey highlighted inequalities in access to advanced AI tools, which can widen the educational gap between students from different economic backgrounds. Students also expressed concerns about the security and privacy of their personal data collected and processed by AI systems. The findings suggest that while AI has the potential to support digital education, significant challenges need to be addressed to make these tools more effective and acceptable for students. Recommendations include increasing training for students and teachers on using AI, providing more interactive and engaging forms of education, and implementing stricter regulations on data protection.

Keywords: AI, digital education, education tools, motivation and engagement

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1014 Malignant Idiopathic Intracranial Hypertension Revealed a Hidden Primary Spinal Leptomeningeal Medulloblastoma

Authors: Naim Izet Kajtazi

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Context: Frequently, the cause of raised intracranial pressure remains unresolved and rarely is related to spinal tumors, moreover less to spinal medulloblastoma without primary brain focus. Process: An 18-year-old woman had a 3-month history of headaches and impaired vision. Neurological examination revealed bilateral sixth cranial nerve palsies with bilateral papilloedema of grade III. No focal brain or spine lesion was found on imaging. Consecutive lumbar punctures showed high opening pressure and subsequent increasing protein level. The meningeal biopsy was negative. At one point, she developed an increasing headache, vomiting and back pain. Spine MRI showed diffuse nodular leptomeningeal enhancement with the largest nodule at T6–T7. Malignant cells were detected in cerebrospinal fluid. She underwent laminectomy with excisional biopsy, and pathology showed medulloblastoma WHO grade IV. Outcome: She was treated with chemotherapy and craniospinal irradiation and made a good recovery. Relevance: Primary spinal leptomeningeal medulloblastoma is extremely rare, especially without primary brain focus, but may cause increased intracranial pressure, even in the early microscopic phases, and it should be considered in the differential diagnosis if conventional and aggressive treatment of idiopathic intracranial hypertension fails. We assume that arachnoiditis from tumor seeding caused increased intracranial pressure. Appropriate neurosurgical intervention and surgical biopsy are mandated if a suspicious lesion is detected. Consider proper rescreening of the whole neuroaxis in refractory cases of intracranial hypertension.

Keywords: CNS infection, IIH, headache, primary spinal leptomeningeal medulloblastoma

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1013 Reproductive Health of Women After Taking Chemotherapy for Gestational Trophoblastic Disease

Authors: Ezeh Chukwunonso Peter Excel, Akruti Vg

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Aim/Background: To show that even after undergoing 1-5 courses of chemotherapy for Gestational Trophoblastic Disease (GTD) reproductive health of women is intact and they conceive successfully after it. Method: Retrospective cohort analysis using data from the Lugansk regional maternity hospital database of years 1993-2013, which shows n=18 females had GTD and underwent 1-5 courses of chemotherapy. Results and Discussion: Frequency of GTD was rare. All 18 patients (pts) belong to age group of 17-39 years, covering wide range of reproductive age. Out of 18 pts, 15 had hydatidiform mole (HM) while other 3 had choriocarcinoma (CC). In anamnesis, among CC pts, 1 had early pre-eclampsia at 24 weeks and 1 had 4th week of late postpartum (PP) bleeding, while all HM pts had genital inflammatory diseases, 1 pt of HM during follow-up had High hCG and 3 times curettage in 5 months. 18 women became pregnant for 25 times after chemotherapy. Chemotherapy was given under indication of either high level of HCG, luteal cyst >6cm or path-morphological results of curettage. CC 3 pts had (2 spontaneous abortions (SA), 2 term cesarean section (CS), 1 preterm CS). HM 15 pts had (3 artificial abortion, 2 SA, 7CS (5 term and 2 preterm), 8 vaginal deliveries (7 term and 1 preterm)). Conclusion: During our research we got 22.2% preterm deliveries and 55.6% CS which is higher than the normal cases, but still all the 18 women were able to have kids successfully after chemotherapy. So we can conclude that chemotherapy for GTD was successful in keeping the reproductive health of women intact.

Keywords: reproductive health, chemotherapy, gestational trophoblastic disease, women

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1012 The Effect of Mist Cooling on Sexual Behavior and Semen Quality of Sahiwal Bulls

Authors: Khalid Ahmed Elrabie Abdelrasoul

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The present study was carried out on Sahiwal cattle bulls maintained at the Artificial Breeding Complex, NDRI, Karnal, Hayana, India, to assess the effect of cooling using mist cooling and fanning on Sahiwal bulls in the dry hot summer season. Fourteen Sahiwal bulls were divided into two groups of seven each. Sexual behavior and semen quality traits considered were: Reaction time (RT), Dismounting time (DMT), Total time taken in mounts (TTTM), Flehmen response (FR), Erection Score (ES), Protrusion Score (PS), Intensity of thrust (ITS), Temperament Score (TS), Libido Score (LS), Semen volume, Physical appearance, Mass activity, Initial progressive motility, Non-eosinophilic spermatozoa count (NESC) and post thaw motility percent. Data were analyzed by least squares technique. Group-1 was the control, whereas group-2 (treatment group) bulls were exposed to mist cooling and fanning (thrice a day 15 min each) in the dry hot summer season. Group-2 showed significantly (p < 0.01) higher value in DMT (sec), ES, PS, ITS, LS, semen volume (ml), semen color density, mass activity, initial motility, progressive motility and live sperm.

Keywords: mist cooling, Sahiwal bulls, semen quality, sexual behavior

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1011 Influence of Infinite Elements in Vibration Analysis of High-Speed Railway Track

Authors: Janaki Rama Raju Patchamatla, Emani Pavan Kumar

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The idea of increasing the existing train speeds and introduction of the high-speed trains in India as a part of Vision-2020 is really challenging from both economic viability and technical feasibility. More than economic viability, technical feasibility has to be thoroughly checked for safe operation and execution. Trains moving at high speeds need a well-established firm and safe track thoroughly tested against vibration effects. With increased speeds of trains, the track structure and layered soil-structure interaction have to be critically assessed for vibration and displacements. Physical establishment of track, testing and experimentation is a costly and time taking process. Software-based modelling and simulation give relatively reliable, cost-effective means of testing effects of critical parameters like sleeper design and density, properties of track and sub-grade, etc. The present paper reports the applicability of infinite elements in reducing the unrealistic stress-wave reflections from so-called soil-structure interface. The influence of the infinite elements is quantified in terms of the displacement time histories of adjoining soil and the deformation pattern in general. In addition, the railhead response histories at various locations show that the numerical model is realistic without any aberrations at the boundaries. The numerical model is quite promising in its ability to simulate the critical parameters of track design.

Keywords: high speed railway track, finite element method, Infinite elements, vibration analysis, soil-structure interface

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1010 Perceptions of College Students on Whether an Intelligent Tutoring System Is a Tutor

Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate the benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. Developments improving the ease of ITS creation have recently increased their proliferation, leading many K-12 schools and institutions of higher education in the United States to regularly use ITS within classrooms. We investigated how students perceive their experience using an ITS. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course and were subsequently asked for feedback on their experience. Results show that their perceptions were generally favorable of the ITS, and most would seek to use an ITS both for STEM and non-STEM courses in the future. Along with detailed transaction-level data, this feedback also provides insights on the design of user-friendly interfaces, guidance on accessibility for students with impairments, the sequencing of exercises, students’ expectation of achievement, and comparisons to other tutoring experiences. We discuss how these findings are important for the creation, implementation, and evaluation of ITS as a mode and method of teaching and learning.

Keywords: college statistics course, intelligent tutoring systems, in vivo study, student perceptions of tutoring

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1009 Mnemotopic Perspectives: Communication Design as Stabilizer for the Memory of Places

Authors: C. Galasso

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The ancestral relationship between humans and geographical environment has long been at the center of an interdisciplinary dialogue, which sees one of its main research nodes in the relationship between memory and places. Given its deep complexity, this symbiotic connection continues to look for a proper definition that appears increasingly negotiated by different disciplines. Numerous fields of knowledge are involved, from anthropology to semiotics of space, from photography to architecture, up to subjects traditionally far from these reasonings. This is the case of Design of Communication, a young discipline, now confident in itself and its objectives, aimed at finding and investigating original forms of visualization and representation, between sedimented knowledge and new technologies. In particular, Design of Communication for the Territory offers an alternative perspective to the debate, encouraging the reactivation and reconstruction of the memory of places. Recognizing mnemotopes as a cultural object of vertical interpretation of the memory-place relationship, design can become a real mediator of the territorial fixation of memories, making them increasingly accessible and perceptible, contributing to build a topography of memory. According to a mnemotopic vision, Communication Design can support the passage from a memory in which the observer participates only as an individual to a collective form of memory. A mnemotopic form of Communication Design can, through geolocation and content map-based systems, make chronology a topography rooted in the territory and practicable; it can be useful to understand how the perception of the memory of places changes over time, considering how to insert them in the contemporary world. Mnemotopes can be materialized in different format of translation, editing and narration and then involved in complex systems of communication. The memory of places, therefore, if stabilized by the tools offered by Communication Design, can make visible ruins and territorial stratifications, illuminating them with new communicative interests that can be shared and participated.

Keywords: memory of places, design of communication, territory, mnemotope, topography of memory

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1008 Time Driven Activity Based Costing Capability to Improve Logistics Performance: Application in Manufacturing Context

Authors: Siham Rahoui, Amr Mahfouz, Amr Arisha

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In a highly competitive environment characterised by uncertainty and disruptions, such as the recent COVID-19 outbreak, supply chains (SC) face the challenge of maintaining their cost at minimum levels while continuing to provide customers with high-quality products and services. More importantly, businesses in such an economic context strive to maintain survival by keeping the cost of undertaken activities (such as logistics) low and in-house. To do so, managers need to understand the costs associated with different products and services in order to have a clear vision of the SC performance, maintain profitability levels, and make strategic decisions. In this context, SC literature explored different costing models that sought to determine the costs of undertaking supply chain-related activities. While some cost accounting techniques have been extensively explored in the SC context, more contributions are needed to explore the potential of time driven activity-based costing (TDABC). More specifically, more applications are needed in the manufacturing context of the SC, where the debate is ongoing. The aim of the study is to assess the capability of the technique to assess the operational performance of the logistics function. Through a case study methodology applied to a manufacturing company operating in the automotive industry, TDABC evaluates the efficiency of the current configuration and its logistics processes. The study shows that monitoring the process efficiency and cost efficiency leads to strategic decisions that contributed to improve the overall efficiency of the logistics processes.

Keywords: efficiency, operational performance, supply chain costing, time driven activity based costing

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1007 Competition between Regression Technique and Statistical Learning Models for Predicting Credit Risk Management

Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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1006 Exploring the Spatial Relationship between Built Environment and Ride-hailing Demand: Applying Street-Level Images

Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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1005 Experiences of Trainee Teachers: A Survey on Expectations and Realities in Special Secondary Schools in Kenya

Authors: Mary Cheptanui Sambu

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Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

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1004 The Trajectory of the Ball in Football Game

Authors: Mahdi Motahari, Mojtaba Farzaneh, Ebrahim Sepidbar

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Tracking of moving and flying targets is one of the most important issues in image processing topic. Estimating of trajectory of desired object in short-term and long-term scale is more important than tracking of moving and flying targets. In this paper, a new way of identifying and estimating of future trajectory of a moving ball in long-term scale is estimated by using synthesis and interaction of image processing algorithms including noise removal and image segmentation, Kalman filter algorithm in order to estimating of trajectory of ball in football game in short-term scale and intelligent adaptive neuro-fuzzy algorithm based on time series of traverse distance. The proposed system attain more than 96% identify accuracy by using aforesaid methods and relaying on aforesaid algorithms and data base video in format of synthesis and interaction. Although the present method has high precision, it is time consuming. By comparing this method with other methods we realize the accuracy and efficiency of that.

Keywords: tracking, signal processing, moving targets and flying, artificial intelligent systems, estimating of trajectory, Kalman filter

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1003 Genetic Structure of Four Bovine Populations in the Philippines Using Microsatellites

Authors: Peter James C. Icalia, Agapita J. Salces, Loida Valenzuela, Kangseok Seo, Geronima Ludan

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This study evaluated polymorphism of 11 microsatellite markers in four local genetic groups of cattle. Batanes cattle which has never been studied using microsatellites is evaluated for its genetic distance from the Ilocos cattle while Brahman and Holstein-Sahiwal are also included as there were insemination programs by the government using these two breeds. PCR products that were genotyped for each marker were analyzed using POPGENEv32. Results showed that 55% (Fst=0.5501) of the genetic variation is due to the differences between populations while the remaining 45% is due to individual variation. The Fst value also indicates that there were very great differences from population to population using the range proposed by Sewall and Wright. The constructed phylogenetic tree based on Nei’s genetic distance using the modified neighboor joining procedure of PHYLIPv3.5 showed the admixture of Brahman and Holstein-Sahiwal having them grouped in the same clade. Batanes and Ilocos cattle were grouped in a different cluster showing that they have descended from a single parental population. This would presumably address the claim that Batanes and Ilocos cattle are genetically distant from other groups and still exist despite the artificial insemination program of the government using Brahman and other imported breeds. The knowledge about the genetic structure of this population supports the development of conservation programs for the smallholder farmers.

Keywords: microsatellites, cattle, Philippines, populations, genetic structure

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1002 An Entropy Stable Three Dimensional Ideal MHD Solver with Guaranteed Positive Pressure

Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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1001 Necrotising Anterior Scleritis and Scleroderma: A Rare Association

Authors: Angeliki Vassila, Dimitrios Kalogeropoulos, Rania Rawashdeh, Nigel Hall, Najiha Rahman, Mark Fabian, Suresh Thulasidharan, Hossain Parwez

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Introduction: Necrotising scleritis is a severe form of scleritis and poses a significant threat to vision. It can manifest in various systemic autoimmune disorders, systemic vasculitis, or as a consequence of microbial infections. The objective of this study is to present a case of necrotizing scleritis associated with scleroderma, which was further complicated by a secondary Staphylococcus epidermidis infection. Methods: This is a retrospective analysis that examines the medical records of a patient who was hospitalised in the Eye Unit at University Hospital Southampton. Results: A 78-year-old woman presented at the eye casualty department of our unit with a two-week history of progressively worsening pain in her left eye. She received a diagnosis of necrotising scleritis and was admitted to the hospital for further treatment. It was decided to commence a three-day course of intravenous methylprednisolone followed by a tapering regimen of oral steroids. Additionally, a conjunctival swab was taken, and two days later, it revealed the presence of S. epidermidis, indicating a potential secondary infection. Given this finding, she was also prescribed topical (Ofloxacin 0.3% - four times daily) and oral (Ciprofloxacin 750mg – twice daily) antibiotics. The inflammation and symptoms gradually improved, leading to the patient being scheduled for a scleral graft and applying an amniotic membrane to cover the area of scleral thinning. Conclusions: Rheumatoid arthritis and granulomatosis with polyangiitis are the most commonly identifiable systemic diseases associated with necrotising scleritis. Although association with scleroderma is extremely rare, early identification and treatment are necessary to prevent scleritis-related complications.

Keywords: scleritis, necrotizing scleritis, scleroderma, autoimmune disease

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1000 The Impact of Artificial Intelligence on Rural Life

Authors: Triza Edwar Fawzi Deif

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In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

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999 The Post Thawing Quality of Boer Goat Semen after Freezing by Mr. Frosty System Using Commercial Diluter

Authors: Gatot Ciptadi, Mudawamah, R. P. Putra, S. Wahjuningsih, A. M. Munazaroh

Abstract:

The success rate of Artificial Insemination (AI) application, particularly in the field at the farmer level is highly dependent on the quality of the sperms one post thawing. The objective of this research was to determine the effect of freezing method (-1oC/ minute) using Mr. Frosty system with commercial diluents on the post-thawing quality of Boer goat semen. Method use is experimental design with the completely randomized design (CRD) with 4 treatments of commercial diluter percentage (v/v). Freezing semen was cryopreserved in 2 main final temperatures of –45 oC (Freezer) and –196 oC (liquid nitrogen). Result showed that different commercial diluter is influenced on viability motility and abnormalities of Boer semen. Pre-freezing qualities of viability, motilities and abnormalities was 88.67+4.16 %, 66.33 +1.53 % and 4.67+ 0.57 % respectively. Meanwhile, post-thawing qualities is considered as good as standard qualities at least more than 40 % (51.0+6.5%). The percentage of commercial diluents were influenced highly significant (P<0.01).The best diluents ration is 1:4 (v/v) for both final sperms stocked. However freezing sperm conserved in -196 oC is better than –45 oC (i.e. motility 39.3.94 % vs. 51.0 + 6.5 %). It was concluded that Mr. frosty system was considered as the feasible method for freezing semen in the reason for practical purposes.

Keywords: sperm quality, goat, viability, diluteR

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998 The Effect of Artificial Intelligence on International Law, Legal Security and Privacy Issues

Authors: Akram Waheb Nasef Alzordoky

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The wars and armed conflicts have frequently ended in violations of global humanitarian law and regularly devote the maximum severe global crimes, which include war crimes, crimes towards humanity, aggression and genocide. But, simplest inside the XX century, the guideline changed into an articulated idea of establishing a frame of worldwide criminal justice so that you can prosecute those crimes and their perpetrators. The first steps on this subject were made with the aid of setting up the worldwide army tribunals for warfare crimes at Nuremberg and Tokyo, and the formation of ad hoc tribunals for the former Yugoslavia and Rwanda. Ultimately, the global criminal courtroom was established in Rome in 1998 with the aim of justice and that allows you to give satisfaction to the sufferers of crimes and their families. The aim of the paper was to provide an ancient and comparative analysis of the establishments of worldwide criminal justice primarily based on which those establishments de lege lata fulfilled the goals of individual criminal responsibility and justice. Moreover, the authors endorse de lege ferenda that the everlasting global crook Tribunal, in addition to the potential case, additionally takes over the current ICTY and ICTR cases.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

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997 3D Human Face Reconstruction in Unstable Conditions

Authors: Xiaoyuan Suo

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3D object reconstruction is a broad research area within the computer vision field involving many stages and still open problems. One of the existing challenges in this field lies with micromotion, such as the facial expressions on the appearance of the human or animal face. Similar literatures in this field focuses on 3D reconstruction in stable conditions such as an existing image or photos taken in a rather static environment, while the purpose of this work is to discuss a flexible scan system using multiple cameras that can correctly reconstruct 3D stable and moving objects -- human face with expression in particular. Further, a mathematical model is proposed at the end of this literature to automate the 3D object reconstruction process. The reconstruction process takes several stages. Firstly, a set of simple 2D lines would be projected onto the object and hence a set of uneven curvy lines can be obtained, which represents the 3D numerical data of the surface. The lines and their shapes will help to identify object’s 3D construction in pixels. With the two-recorded angles and their distance from the camera, a simple mathematical calculation would give the resulting coordinate of each projected line in an absolute 3D space. This proposed research will benefit many practical areas, including but not limited to biometric identification, authentications, cybersecurity, preservation of cultural heritage, drama acting especially those with rapid and complex facial gestures, and many others. Specifically, this will (I) provide a brief survey of comparable techniques existing in this field. (II) discuss a set of specialized methodologies or algorithms for effective reconstruction of 3D objects. (III)implement, and testing the developed methodologies. (IV) verify findings with data collected from experiments. (V) conclude with lessons learned and final thoughts.

Keywords: 3D photogrammetry, 3D object reconstruction, facial expression recognition, facial recognition

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996 Predicting Supply Delivery Delays Using Advanced Analytical Approaches

Authors: Mohammad Alshehri, Fahd Alfarsi

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Efficient supply chains play an essential role in delivering humanitarian supplies and directly impact the success of public aid initiatives globally. Predicting the delivery status of these essential supplies in a timely manner is crucial. Therefore, this study investigates the application of various machine learning (ML) approaches to predict whether humanitarian deliveries will be made on time, using a comprehensive case-study dataset provided by one of the largest international supplying organizations. We employed several ML methods, namely Logistics Regression, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Navie Bays, to assess the proposed predictive model. The outcome of the analysis showed promising results, with weighted Recall (WRec.) / Accuracy (Acc.) scores ranging from 0.77 to 0.86 using the 4 algorithms mentioned earlier. These high-performance levels indicate the robustness of Machine Learning (ML) techniques in forecasting delivery status, potentially enabling more proactive and efficient supply chain management in global aid initiatives. The implications of this study suggest that integrating advanced predictive analytics in supply chain management can significantly enhance the delivery performance of critical commodities to those in need.

Keywords: humanitarian aids, supply chains, artificial intelligence, delivery status

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995 Application of a Universal Distortion Correction Method in Stereo-Based Digital Image Correlation Measurement

Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

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994 Breast Cancer Diagnosing Based on Online Sequential Extreme Learning Machine Approach

Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

Abstract:

Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

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993 Artificial Intelligence Impact on the Australian Government Public Sector

Authors: Jessica Ho

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AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

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992 Contactless Heart Rate Measurement System based on FMCW Radar and LSTM for Automotive Applications

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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991 The Impact of Artificial Intelligence on Food Nutrition

Authors: Antonyous Fawzy Boshra Girgis

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Nutrition labels are diet-related health policies. They help individuals improve food-choice decisions and reduce intake of calories and unhealthy food elements, like cholesterol. However, many individuals do not pay attention to nutrition labels or fail to appropriately understand them. According to the literature, thinking and cognitive styles can have significant effects on attention to nutrition labels. According to the author's knowledge, the effect of global/local processing on attention to nutrition labels has not been previously studied. Global/local processing encourages individuals to attend to the whole/specific parts of an object and can have a significant impact on people's visual attention. In this study, this effect was examined with an experimental design using the eye-tracking technique. The research hypothesis was that individuals with local processing would pay more attention to nutrition labels, including nutrition tables and traffic lights. An experiment was designed with two conditions: global and local information processing. Forty participants were randomly assigned to either global or local conditions, and their processing style was manipulated accordingly. Results supported the hypothesis for nutrition tables but not for traffic lights.

Keywords: nutrition, public health, SA Harvest, foodeye-tracking, nutrition labelling, global/local information processing, individual differencesmobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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