Search results for: eye tracking method

Authors: Marcella De Filippo, Delio Colangelo, Luca Farnia

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In recent decades, the hyper-competition of tourism scenario has implicated the maturity of many businesses, attributing a central role to innovative processes and their dissemination in the economy of company management. At the same time, it has defined the need for monitoring the application of innovations, in order to govern and improve the performance of companies and destinations. The study aims to analyze and define the innovation in the tourism sector. The research actions have concerned, on the one hand, some in-depth interviews with experts, identifying innovation in terms of process and product, digitalization, sustainability policies and, on the other hand, to evaluate the interaction between these factors, in terms of substitutability and complementarity in management scenarios, in order to identify which one is essential to be competitive in the global scenario. Fuzzy measures and Choquet integral were used to elicit Experts’ preferences. This method allows not only to evaluate the relative importance of each pillar, but also and more interestingly, the level of interaction, ranging from complementarity to substitutability, between pairs of factors. The results of the survey are the following: in terms of Shapley values, Experts assert that Innovation is the most important factor (32.32), followed by digitalization (31.86), Network (20.57) and Sustainability (15.25). In terms of Interaction indices, given the low degree of consensus among experts, the interaction between couples of criteria on average could be ignored; however, it is worth to note that the factors innovations and digitalization are those in which experts express the highest degree of interaction. However for some of them, these factors have a moderate level of complementarity (with a pick of 57.14), and others consider them moderately substitutes (with a pick of -39.58). Another example, although outlier is the interaction between network and digitalization, in which an expert consider them markedly substitutes (-77.08).

Keywords: innovation, business model, tourism, fuzzy

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Authors: Asamaporn Puetpaiboon, Sunisa Chatmongkolchart, Nalinee Kovitwanawong, Osaree Akaraborworn

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Traumatic patients with massive bleeding require intensive resuscitation. The actual cost of anesthesia per case has never been clarified, so our study aimed to quantify the direct cost, and cost-to-charge ratio of anesthetic care in traumatic patients with intraoperative massive bleeding. This study was a prospective, observational, cost analysis study, conducted in Prince of Songkla University hospital, Thailand, with traumatic patients, of any mechanisms being recruited. Massive bleeding was defined as estimated blood loss of at least one blood volume in 24 hours, or a half of blood volume in 3 hours. The cost components were identified by the micro-costing method, and valued by the bottom-up approach. The direct cost was divided into 4 categories: the labor cost, the capital cost, the material cost and the cost of drugs. From September 2017 to August 2018, 10 patients with multiple injuries were included. Seven patients had motorcycle accidents, two patients fell from a height and another one was in a minibus accident. Two patients died on the operating table, and another two died within 48 hours. The median Sequential Organ Failure Assessment (SOFA) score was 8. The median intraoperative blood loss was 3,500 ml. The median direct cost, per case, was 250 United States Dollars (2017 exchange rate), and the cost-to-charge ratio was 0.53. In summary, the direct cost was nearly half of the hospital charge, for these traumatic patients with massive bleeding. However, our study did not analyze the indirect cost.

Keywords: cost, cost-to-charge ratio, micro-costing, trauma

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Authors: Raja Ezman Raja Shariff

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Acute kidney injury (AKI) is commonly seen in inpatients, and places a great cost on the NHS and patients. Timely and appropriate management is both nephron sparing and potentially life-saving. Ultrasound scanning (USS) is a well-recognised method for stratifying patients. Subsequently, the NICE AKI guidance has defined groups in whom scanning is recommended within 6 hours of request (pyonephrosis), within 24 hours (obstruction/cause unknown), and in whom routine scanning isn't recommended (cause for AKI identified). The audit looks into whether Stockport NHS Trust USS practice was in line with such recommendations. The audit evaluated 92 patients with AKI who had USS, between 01/01/14 to 30/04/14. Data collection was divided into 2 parts. Firstly, radiology request cards and the online imaging software (PACS) were evaluated. Then, the electronic case notes (ADVANTIS) was evaluated further. Based on request cards, 10% of requests were for pyonephrosis. Only 33% were scanned within 6hours and a further 33% within 24hours. 75% were requested for possible obstructions and unknown cause collectively. Of those due to possible obstruction, 71% of patients were scanned within 24 hours. Of those with unknown cause, 50% were scanned within 24 hours. 15% of requests had a cause declared and so potentially did not require scanning. Evaluation of the patients’ notes suggested further interesting findings. Firstly, potentially 39% of patients had a known cause for AKI, therefore, did not need USS. Subsequently, the cohort of unknown cause and possible obstruction was collectively reduced to 45%. Alarmingly the patient cohort with possible pyonephrosis went up to 16%, suggesting an under-recognition of this life-threatening condition. We plan to highlight these findings within our institution and make changes to encourage more appropriate requesting and timely scanning. Time will tell if we manage to save or increase our costs in this cost-conscious NHS. Patient benefits, though, seem to be guaranteed.

Keywords: AKI, ARF, kidney, renal

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Authors: Hamed Nazeri, Pierre Mertiny, Yongsheng Ma, Kajsa Duke

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The background of the present study is the use of environment-friendly biopolymer and biocomposite materials. Among the recently introduced biopolymers, poly (propylene carbonate) (PPC) has been gaining attention. This study focuses on the size of representative volume elements (RVE) in order to simulate PPC composites reinforced by cellulose nanocrystals (CNCs) as a bio-nanocomposite. Before manufacturing nanocomposites, numerical modeling should be implemented to explore and predict mechanical properties, which may be accomplished by creating and studying a suitable RVE. In other studies, modeling of composites with rod shaped fillers has been reported assuming that fillers are unidirectionally aligned. But, modeling of non-aligned filler dispersions is considerably more difficult. This study investigates the minimum RVE size to enable subsequent FEA modeling. The matrix and nano-fillers were modeled using the finite element software ABAQUS, assuming randomly dispersed fillers with a filler mass fraction of 1.5%. To simulate filler dispersion, a Monte Carlo technique was employed. The numerical simulation was implemented to find composite elastic moduli. After commencing the simulation with a single filler particle, the number of particles was increased to assess the minimum number of filler particles that satisfies the requirements for an RVE, providing the composite elastic modulus in a reliable fashion.

Keywords: biocomposite, Monte Carlo method, nanocomposite, representative volume element

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Authors: Suppara Charoenpoom

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This study focuses on 1) a good-quality management procedures of buildings and environment in schools 2) designing the management procedures and 3) creating an operation manual for the procedures. This study is the combination of qualitative and quantitative research method. Populations in the research were 83 deans and directors of primary and secondary schools from the 10th educational district in Samut Songkram. Sample group was selected from the voluntary deans and directors. There were 14 participants in sample group. Research tools in this study were divided into 2 categories. The first one was data-collecting tools, which were in-depth interview and questionnaires. The second one was the designing tools to help creating management procedures: quality business, quality work procedure and key quality indicator of each activity in schools. All data were analyzed by mean and standard deviation. The result from this study has found out 1 effective process of building and environment management for basic education schools which is called Quality Business Process (QBP) and 7 Quality Work Procedures (QWP). In terms of academic feasibility checkup by experts, the research had shown that new design of building and environment management was approved unanimously. It means that new process of building and environment management in schools works very well and can be adapted. After examining the possibility of management process being used in schools by calculating the mean value among sample group (14 school deans and directors), the mean value was between 0.64-1.00. It means that the new design of building and environment management can be operated effectively in schools. For the satisfaction part, deans and school directors gave the satisfaction score in the highest level (Mean = 4.7372, S.D. = 0.4385).

Keywords: buildings, environment, procedures, quality management

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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Authors: Esra Güney, Tuba Uçar

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Aim: This study has been conducted for the purpose of determining the effects of fetal movement counting on antenatal maternal attachment. Material and Method: This research was conducted on the basis of the real test model with the pre-test /post-test control groups. The study population consists of pregnant women registered in the six different Family Health Centers located in the central Malatya districts of Yeşilyurt and Battalgazi. When power analysis is done, the sample size was calculated for each group of at least 55 pregnant women (55 tests, 55 controls). The data were collected by using Personal Information Form and MAAS (Maternal Antenatal Attachment Scale) between July 2015-June 2016. Fetal movement counting training was given to pregnant women by researchers in the experimental group after the pre-test data collection. No intervention was applied to the control group. Post-test data for both groups were collected after four weeks. Data were evaluated with percentage, chi-square arithmetic average, chi-square test and as for the dependent and independent group’s t test. Result: In the MAAS, the pre-test average of total scores in the experimental group is 70.78±6.78, control group is also 71.58±7.54 and so there was no significant difference in mean scores between the two groups (p>0.05). MAAS post-test average of total scores in the experimental group is 78.41±6.65, control group is also is 72.25±7.16 and so the mean scores between groups were found to have statistically significant difference (p<0.05). Conclusion: It was determined that fetal movement counting increases the maternal antenatal attachments.

Keywords: antenatal maternal attachment, fetal movement counting, pregnancy, midwifery

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Authors: Shian Saroop, Dhiren Allopi

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In order to stay competitive and to meet upcoming stricter environmental regulations and customer requirements, designers have a key role in designing civil infrastructure so that it is environmentally sustainable. There is an urgent need for engineers to apply technologies and methods that deliver better and more sustainable performance of civil infrastructure as well as a need to establish a standard of measurement for greener infrastructure, rather than merely use tradition solutions. However, there are no systems in place at the design stage that assesses the environmental impact of design decisions on township infrastructure projects. This paper identifies alternative eco-efficient civil infrastructure design solutions and developed sustainability criteria and a toolkit to analyse the eco efficiency of infrastructure projects. The proposed toolkit is aimed at promoting high-performance, eco-efficient, economical and environmentally friendly design decisions on stormwater, roads, water and sanitation related to township infrastructure projects. These green solutions would bring a whole new class of eco-friendly solutions to current infrastructure problems, while at the same time adding a fresh perspective to the traditional infrastructure design process. A variety of projects were evaluated using the green infrastructure toolkit and their results are compared to each other, to assess the results of using greener infrastructure verses the traditional method of designing infrastructure. The application of ‘green technology’ would ensure a sustainable design of township infrastructure services assisting the design to consider alternative resources, the environmental impacts of design decisions, ecological sensitivity issues, innovation, maintenance and materials, at the design stage of a project.

Keywords: eco-efficiency, green infrastructure, infrastructure design, sustainable development

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Authors: Daudi S. Simbeye, Mbazingwa E. Mkiramweni

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Plant diseases have the potential to drastically diminish the quantity and quality of agricultural products. Guava (Psidium guajava), sometimes known as the apple of the tropics, is one of the most widely cultivated fruits in tropical regions. Monitoring plant health and diagnosing illnesses is an essential matter for sustainable agriculture, requiring the inspection of visually evident patterns on plant leaves and fruits. Due to minor variations in the symptoms of various guava illnesses, a professional opinion is required for disease diagnosis. Due to improper pesticide application by farmers, erroneous diagnoses may result in economic losses. This study proposes a method that uses artificial intelligence (AI) to detect and classify the most widespread guava plant by comparing images of its leaves and fruits to datasets. ESP32 CAM is responsible for data collection, which includes images of guava leaves and fruits. By comparing the datasets, these image formats are used as datasets to help in the diagnosis of plant diseases through the leaves and fruits, which is vital for the development of an effective automated agricultural system. The system test yielded the most accurate identification findings (99 percent accuracy in differentiating four guava fruit diseases (Canker, Mummification, Dot, and Rust) from healthy fruit). The proposed model has been interfaced with a mobile application to be used by smartphones to make a quick and responsible judgment, which can help the farmers instantly detect and prevent future production losses by enabling them to take precautions beforehand.

Keywords: early identification, guava plants, fruit diseases, deep learning

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Authors: Ghazala Kausar

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This study investigates Pakistani first year university students’ perception of the role of pragmatics in their general approach to learning English. The research is triggered by National Curriculum’s initiative to provide holistic opportunities to the students for language development and to equip them with competencies to use English language in academic and social contexts (New English National Curriculum for I-XII). The traditional grammar translation and examination oriented method is believed to reduce learners to silent listener (Zhang, 2008: Zhao 2009). This lead to the inability of the students to interpret discourse by relating utterances to their meaning, understanding the intentions of the users and how language is used in specific setting (Bachman & Palmer, 1996, 2010). Pragmatic competence is a neglected area as far as teaching and learning English in Pakistan is concerned. This study focuses on the different types of pragmatic knowledge, learners perception of such knowledge and learning strategies employed by different learners to process the learning in general and pragmatic in particular. This study employed three data collecting tools; a questionnaire, discourse completion task and interviews to elicit data from first year university students regarding their perception of pragmatic competence. Results showed that Pakistani first year university learners have limited pragmatic knowledge. Although they acknowledged the importance of linguistic knowledge for linguistic competence in the students but argued that insufficient English proficiency, limited knowledge of pragmatics, insufficient language material and tasks were major reasons of pragmatic failure.

Keywords: pragmatic competence, Pakistani college learners, linguistic competence

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Hani Baek, Gwang Min Sun, Chansun Shin, Sung Ho Ahn

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Fast neutron irradiation using nuclear reactors is an effective method to improve switching loss and short circuit durability of power semiconductor (insulated gate bipolar transistors (IGBT) and insulated gate transistors (IGT), etc.). However, not only fast neutrons but also thermal neutrons, epithermal neutrons and gamma exist in the nuclear reactor. And the electrical properties of the IGBT may be deteriorated by the irradiation of gamma. Gamma irradiation damages are known to be caused by Total Ionizing Dose (TID) effect and Single Event Effect (SEE), Displacement Damage. Especially, the TID effect deteriorated the electrical properties such as leakage current and threshold voltage of a power semiconductor. This work can confirm the effect of the gamma irradiation on the electrical properties of 600 V NPT-IGBT. Irradiation of gamma forms lattice defects in the gate oxide and Si-SiO₂ interface of the IGBT. It was confirmed that this lattice defect acts on the center of the trap and affects the threshold voltage, thereby negatively shifted the threshold voltage according to TID. In addition to the change in the carrier mobility, the conductivity modulation decreases in the n-drift region, indicating a negative influence that the forward voltage drop decreases. The turn-off delay time of the device before irradiation was 212 ns. Those of 2.5, 10, 30, 70 and 100 kRad(Si) were 225, 258, 311, 328, and 350 ns, respectively. The gamma irradiation increased the turn-off delay time of the IGBT by approximately 65%, and the switching characteristics deteriorated.

Keywords: NPT-IGBT, gamma irradiation, switching, turn-off delay time, recombination, trap center

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Authors: M. Panidou, F. Kilipiris, E. Christou, K. Alexandris

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This study intends to investigate the travel preferences of Generation Z (born between 1996 and 2012), focusing on their inclination towards unique and unconventional travel experiences, prioritization of authentic cultural immersion and local experiences over traditional tourist attractions, and their value for flexibility and spontaneity in travel plans. By examining these aspects, the research aims to provide insights into the preferences and behaviors of Generation Z travelers, contributing to a better understanding of their travel choices and informing the tourism industry in catering to their needs and desires. Secondary data was gathered from academic literature and industry reports to offer a thorough study of the topic. A quantitative method was used, and primary data was collected through an online questionnaire. One hundred Greek people between the ages of eighteen and twenty-seven were the study's sample. SPSS software was used to assist in the analysis of the data. The findings of the research showed that Gen Z is attracted to unusual and distinctive travel experiences, prioritizing genuine cultural immersion over typical tourist attractions, and they highly value flexibility in their travel decision-making. This research contributes to a deeper understanding of how Gen Z travelers are reshaping the travel industry. Travel companies, marketers, and destination management organizations will find the findings useful in adjusting their products to suit this influential demographic's changing demands and preferences. Considering the limitations of the sample size, future studies could expand the sample size to include individuals from different cultural backgrounds for a more comprehensive understanding.

Keywords: cultural immersion, flexibility, generation Z, travel preferences, unique experiences

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Authors: Marsha R. Lawrence

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Introduction: In February and March of 2020, many Black Americans in Albany, Georgia, were impacted by COVID-19 compared to the rest of the country. Due to misinformation and distrust in the community, citizens were not able to make good health decisions regarding COVID-19. The city of Albany applied for a grant with the Department of Health and Human Services, specifically the Office of Minority Health and it was approved. The city of Albany partnered with Albany State University to administer the grant and implementation ensued. Method: An eleven-page electronic and paper cross-sectional survey was given to participants. Albany State University recruited community partners like health care organizations and faith-based organizations to reach the citizens of Albany, Georgia. These partners reached participants through creative community activities to educate participants about COVID-19 and provide incentives to receive a vaccine. Data collection is still in progress because activities are ongoing. Anticipated Results: By December 2023, we anticipate results of the number of participants who accepted vaccines based on participants who stated providers checked their understanding, participants who were satisfied with communication regarding COVID-19 health information about the vaccine, and participants who were involved in decisions regarding the COVID-19 vaccine. Conclusion: Health communication is a subsection of health literacy. At this point, approximately 4000 individuals have received information and education about COVID-19 in the Albany area. We expect building trusting relationships played an important part in the increase in knowledge and vaccination in Albany, Georgia.

Keywords: health literacy, health communication, vaccination, COVID-19

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Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

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This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

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Authors: Sze Shin Low, Michelle T. T. Tan, Poi Sim Khiew, Hwei-San Loh

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An efficient graphene/zinc oxide (PSE-G/ZnO) platform based on pi-pi stacking, non-covalent interactions for the development of aptamer-based biosensor was presented in this study. As a proof of concept, the DNA recognition capability of the as-developed PSE-G/ZnO enhanced aptamer-based biosensor was evaluated using Coconut Cadang-cadang viroid disease (CCCVd). The G/ZnO nanocomposite was synthesised via a simple, green and efficient approach. The pristine graphene was produced through a single step exfoliation of graphite in sonochemical alcohol-water treatment while the zinc nitrate hexahydrate was mixed with the graphene and subjected to low temperature hydrothermal growth. The developed facile, environmental friendly method provided safer synthesis procedure by eliminating the need of harsh reducing chemicals and high temperature. The as-prepared nanocomposite was characterised by X-ray diffractometry (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) to evaluate its crystallinity, morphology and purity. Electrochemical impedance spectroscopy (EIS) was employed for the detection of CCCVd sequence with the use of potassium ferricyanide (K3[Fe(CN)6]). Recognition of the RNA analytes was achieved via the significant increase in resistivity for the double stranded DNA, as compared to single-stranded DNA. The PSE-G/ZnO enhanced aptamer-based biosensor exhibited higher sensitivity than the bare biosensor, attributing to the synergistic effect of high electrical conductivity of graphene and good electroactive property of ZnO.

Keywords: aptamer-based biosensor, graphene/zinc oxide nanocomposite, green synthesis, screen printed carbon electrode

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Authors: Ikechi Gilbert

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Oral communication is the transmission of ideas or messages through the speech process. Acquiring competence in this area which, by its volatile nature, is prone to errors and inaccuracies would require the adoption of a well-suited teaching methodology. Efficient oral communication facilitates exchange of ideas and easy accomplishment of day-to-day tasks, by means of a demonstrated mastery of oral expression and the making of fine presentations to audiences or individuals while recognizing verbal signals and body language of others and interpreting them correctly. In Anglophone states such as Nigeria, Ghana, etc., the French language, for instance, is studied as a foreign language, being used majorly in teaching learners who have their own mother tongue different from French. The same applies to Francophone states where English is studied as a foreign language by people whose official language or mother tongue is different from English. The ideal approach would be to teach these languages in these environments through a pedagogical approach that properly takes care of the oral perspective for effective understanding and application by the learners. In this article, we are examining the communicative approach as a methodology for teaching oral communication in a foreign language. This method is a direct response to the communicative needs of the learner involving the use of appropriate materials and teaching techniques that meet those needs. It is also a vivid improvement to the traditional grammatical and audio-visual adaptations. Our contribution will focus on the pedagogical component of oral communication improvement, highlighting its merits and also proposing diverse techniques including aspects of information and communication technology that would assist the second language learner communicate better orally.

Keywords: communication, competence, methodology, pedagogical component

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Authors: Deepak Ganjiwale, Karthik Vishwanathan

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Objective: Splinting is a great domain of occupational therapy profession.Making a splint for the patient would depend upon the need or requirement of the problems and deformities. Swan neck deformity is not very common in finger it may occur after any disease. Conservative treatment of the swan neck deformity is available by using different static splints only. There are very few reports of surgical correction of swan-neck deformity in benign hypermobility syndrome. Method: This case report describes the result of surgical intervention and hand splint in a twenty year old lady with past history of cardiovascular stroke with no residual neurological deficit. She presented with correctable swan neck deformity and failed to improve with static ring splints to correct the deformity. She was noted to have hyperlaxity (EhlerDanlos type) as per modified Beighton’s score of 5/9. She underwent volar plate plication of the proximal interphalangeal joint of the left ring finger along with hemitenodesis of ulnar slip of flexor digitorum superficialis (FDS) tendon whereby, the ulnar slip of FDS was passed through a small surgically created rent in A2 pulley and sutured back to itself. Result: Postoperatively, the patient was referred to occupational therapy for splinting with the instruction that the splint would work some time for as static and some time as dynamic for positional and correction of the finger. Conclusion: After occupational therapy intervention and splinting, the patient had a full correction of the swan-neck deformity with near full flexion of the operated finger and is able to work independently.

Keywords: swan neck, finger, deformity, splint, hypermobility

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Authors: Milena Lakicevic

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The paper deals with the problem of optimizing management options for urban parks within different scenarios of nature protection and tourism importance. The procedure is demonstrated on a case study example of urban parks in Novi Sad (Serbia). Six management strategies for the selected area have been processed by the decision support method PROMETHEE. Two criteria used for the evaluation were nature protection and tourism and each of them has been divided into a set of indicators: for nature protection those were biodiversity and preservation of original landscape, while for tourism those were recreation potential, aesthetic values, accessibility and culture features. It was pre-assumed that each indicator in a set is equally important to a corresponding criterion. This way, the research was focused on a sensitivity analysis of criteria weights. In other words, weights of indicators were fixed and weights of criteria altered along the entire scale (from the value of 0 to the value of 1), and the assessment has been performed in two-dimensional surrounding. As a result, one could conclude which management strategy would be the most appropriate along with changing of criteria importance. The final ranking of management alternatives was followed up by investigating the mean PROMETHEE Φ values for all options considered and when altering the importance of nature protection/tourism. This type of analysis enabled detecting an alternative with a solid performance along the entire scale, i.e., regardlessly of criteria importance. That management strategy can be seen as a compromise solution when the weight of criteria is not defined. As a conclusion, it can be said that, in some cases, instead of having criteria importance fixed it is important to test the outputs depending on the different schemes of criteria weighting. The research demonstrates the state of the final decision when the decision maker can estimate criteria importance, but also in cases when the importance of criteria is not established or known.

Keywords: criteria weights, PROMETHEE, sensitivity analysis, urban parks

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Romeo A. Botes, Imelda Smit

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The demands of an ever changing and complex higher education environment, along with the profile of modern learners challenge current approaches to assessment and feedback. More learners enter the education system every year. The younger generation expects immediate feedback. At the same time, feedback should be meaningful. The assessment of practical activities in programming poses a particular problem, since both lecturers and learners in the information and computer science discipline acknowledge that paper-based assessment for programming subjects lacks meaningful real-life testing. At the same time, feedback lacks promptness, consistency, comprehensiveness and individualisation. Most of these aspects may be addressed by modern, technology-assisted assessment. The focus of this paper is the continuous development of an artefact that is used to assist the lecturer in the assessment and feedback of practical programming activities in a senior database programming class. The artefact was developed using three Design Science Research cycles. The first implementation allowed one programming activity submission per assessment intervention. This pilot provided valuable insight into the obstacles regarding the implementation of this type of assessment tool. A second implementation improved the initial version to allow multiple programming activity submissions per assessment. The focus of this version is on providing scaffold feedback to the learner – allowing improvement with each subsequent submission. It also has a built-in capability to provide the lecturer with information regarding the key problem areas of each assessment intervention.

Keywords: programming, computer-aided assessment, technology-assisted assessment, programming assessment software, design science research, mixed-method

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Wilma Coetzee

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Statistics lecturers experience that many students who are taking a service course in statistics do not like statistics. Students in these courses tend to struggle and do not perform well. This research takes a look at the student’s perspective, with the aim to determine how to change the teaching of statistics so that students will enjoy it more and perform better. Questionnaires were used to determine the perspectives of first year service statistics students at a South African university. Factors addressed included motivation to study, attitude toward statistics, statistical anxiety, mathematical abilities and tendency to procrastinate. Logistic regression was used to determine what contributes to students performing badly in statistics. The results show that the factors that contribute the most to students performing badly are: statistical anxiety, not being motivated and having had mathematical literacy instead of mathematics in secondary school. Two open ended questions were included in the questionnaire: 'I will enjoy statistics more if…' and 'I will perform better in statistics if…'. The answers to these questions were analyzed using qualitative methods. Frequent themes were identified for each of the questions. A simulation study incorporating bootstrapping was done to determine the saturation of the themes. The majority of the students indicated that they would perform better in statistics if they studied more, managed their time better, had a flare for mathematics and if the lecturer was able to explain difficult concepts better. They also want more active learning. To ensure that students enjoy statistics more, they want an active learning experience. They want fun activities, more interaction with the lecturer and with one another, more computer based problems, and more challenges. They want a better understanding of the subject, want to understand the relevance of statistics to their future career and want excellent lecturers. These findings can be used to direct the improvement of the tuition of statistics.

Keywords: active learning, performance in statistics, statistical anxiety, statistics education

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Authors: Goudjil kamel, Boukhatem Ghania, Jlailia Djihene

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This paper delves into the development of a sophisticated desktop application designed to calculate soil bearing capacity and predict limit pressure. Drawing from an extensive review of existing methodologies, the study meticulously examines various approaches employed in soil bearing capacity calculations, elucidating their theoretical foundations and practical applications. Furthermore, the study explores the burgeoning intersection of artificial intelligence (AI) and geotechnical engineering, underscoring the transformative potential of AI- driven solutions in enhancing predictive accuracy and efficiency.Central to the research is the utilization of cutting-edge machine learning techniques, including Artificial Neural Networks (ANN), XGBoost, and Random Forest, for predictive modeling. Through comprehensive experimentation and rigorous analysis, the efficacy and performance of each method are rigorously evaluated, with XGBoost emerging as the preeminent algorithm, showcasing superior predictive capabilities compared to its counterparts. The study culminates in a nuanced understanding of the intricate dynamics at play in geotechnical analysis, offering valuable insights into optimizing soil bearing capacity calculations and limit pressure predictions. By harnessing the power of advanced computational techniques and AI-driven algorithms, the paper presents a paradigm shift in the realm of geotechnical engineering, promising enhanced precision and reliability in civil engineering projects.

Keywords: limit pressure of soil, xgboost, random forest, bearing capacity

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Authors: Abdelkader Hachemi & Boualem Remini

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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.

Keywords: seawater, intrusion, sharp interface, Algeria

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Authors: Nordin Mamat, Abdul Rahim Razalli, Loy Chee Luen, Abdul Talib Hashim

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This study was designed to investigate preschool environment in multi-ethnic preschool in Malaysia. The objectives are to identify the quality of work environment in multi-ethnic preschools; to investigate the practices of teachers’ role and responsibility; and to identify the quality of human resources. The study involved 2004 respondents who are the staff of multi-ethnic preschool from the government agency who provide preschool service. This study was conducted using a mixed method in which questionnaires and interviews were used to obtain data from respondents. The findings were analysed using mean and used Likert scale to determine the three-stage level such as the high, moderate and low. Findings indicated that the work environment at a moderate level, but the facilities provided insufficient to carry out educational activities with children. The result based on ranking of duties and responsibilities of teachers in multi-ethnic preschool shows the teachers practice daily record of children's development is very little, that only 65 persons are recording the child's development. The poor ratio of teachers and child in multi-ethnic preschool is between 25 to 35 children per class which means the children need a lot of attention. Meanwhile, the work environment is moderate with a mean score of 3.65 and overall mean score for level of staff career development 3.66 also moderate. The findings indicate the facilities provided in their workplace and staff career development requires improvements. Overall, the level of work environment is moderate, and it needs an improvement in term of facilities.

Keywords: environment, human resources, multi-ethnic preschool, quality teacher

Procedia PDF Downloads 323

Authors: Garima, S. Pushpavanam

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In this work, analysis of an Aqueous two-phase (polymer-salt) system for extraction of sunset yellow dye is carried out. A polymer-salt ATPS i.e.; Polyethylene glycol-600 and anhydrous sodium sulfate is used for the extraction. Conditions are chosen to ensure that the extraction results in a concentration of the dye in one of the phases. The dye has a propensity to come to the Polyethylene glycol-600 phase. This extracted sunset yellow dye is degraded photo catalytically into less harmful components. The cloud point method was used to obtain the binodal curve of ATPS. From the binodal curve, the composition of salt and Polyethylene glycol -600 was chosen such that the volume of Polyethylene glycol-600 rich phase is low. This was selected to concentrate the dye from a dilute solution in a large volume of contaminated solution into a small volume. This pre-concentration step provides a high reaction rate for photo catalytic degradation reaction. Experimentally the dye is extracted from the salt phase to Polyethylene glycol -600 phase in batch extraction. This was found to be very fast and all dye was extracted. The concentration of sunset yellow dye in salt and polymer phase is measured at 482nm by ultraviolet-visible spectrophotometry. The extraction experiment in micro channels under stratified flow is analyzed to determine factors which affect the dye extraction. Focus will be on obtaining slug flow by adding nanoparticles in micro channel. The primary aim is to exploit the fact that slug flow will help improve mass transfer rate from one phase to another through internal circulation in dispersed phase induced by shear.

Keywords: aqueous two phase system, binodal curve, extraction, sunset yellow dye

Procedia PDF Downloads 358

Authors: Chen Zhang, Nan Chen

Abstract:

High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

Procedia PDF Downloads 49