Search results for: feedback timing

Authors: Armin Eilaghi, Ahmad Sedaghat, Hayder Abdurazzak, Fadi Alkhatib, Shiva Sadeghi, Martin Jaeger

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A summary of experiences, recommendations, and lessons learnt in the application of PBL in the course of “Engineering Skills” in the School of Engineering at Australian College of Kuwait in Kuwait is presented. Four projects were introduced as part of the PBL course “Engineering Skills” to 24 students in School of Engineering. These students were grouped in 6 teams to develop their skills in 10 learning outcomes. The learning outcomes targeted skills such as drawing, design, modeling, manufacturing and analysis at a preliminary level; and also some life line learning and teamwork skills as these students were exposed for the first time to the PBL (project based learning). The students were assessed for 10 learning outcomes of the course and students’ feedback was collected using an anonymous survey at the end of the course. Analyzing the students’ feedbacks, it is observed that 67% of students preferred multiple smaller projects than a single big project because it provided them with more time and attention focus to improve their “soft skills” including project management, risk assessment, and failure analysis. Moreover, it is found that 63% of students preferred to work with different team members during the course to improve their professional communication skills. Among all, 62% of students believed that working with team members from other departments helped them to increase the innovative aspect of projects and improved their overall performance. However, 70% of students counted extra time needed to regenerate momentum with the new teams as the major challenge. Project based learning provided a suitable platform for introducing students to professional engineering practice and meeting the needs of students, employers and educators. It was found that students achieved their 10 learning outcomes and gained new skills developed in this PBL unit. This was reflected in their portfolios and assessment survey.

Keywords: project-based learning, engineering skills, undergraduate engineering, problem-based learning

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Authors: Farnoosh Faal

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The rapid growth of social media has brought significant changes to the field of urban e-planning. This study aims to review the existing literature on the impact of social media on urban e-planning processes. The study begins with a discussion of the evolution of social media and its role in urban e-planning. The review covers research on the use of social media for public engagement, citizen participation, stakeholder communication, decision-making, and monitoring and evaluation of urban e-planning initiatives. The findings suggest that social media has the potential to enhance public participation and improve decision-making in urban e-planning processes. Social media platforms such as Facebook, Twitter, and Instagram can provide a platform for citizens to engage with planners and policymakers, express their opinions, and provide feedback on planning proposals. Social media can also facilitate the collection and analysis of data, including real-time data, to inform urban e-planning decision-making. However, the literature also highlights some challenges associated with the use of social media in urban e-planning. These challenges include issues related to the representativeness of social media users, the quality of information obtained from social media, the potential for bias and manipulation of social media content, and the need for effective data management and analysis. The study concludes with recommendations for future research on the use of social media in urban e-planning. The recommendations include the need for further research on the impact of social media on equity and social justice in planning processes, the need for more research on effective strategies for engaging underrepresented groups, and the development of guidelines for the use of social media in urban e-planning processes. Overall, the study suggests that social media has the potential to transform urban e-planning processes but that careful consideration of the opportunities and challenges associated with its use is essential for effective and ethical planning practice.

Keywords: social media, Urban e-planning, public participation, citizen engagement

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Authors: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: rapid urbanization, traditional street space, space re-construction, bottom-up design

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Authors: Henrique Fernandes, Sofia Catalucci, Richard Leach, Kapil Sugand

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Background: Holograms are 3D images formed by the interference of light beams from a laser or other coherent light source. Pepper’s ghost is a form of hologram conceptualised in the 18th century. This Holographic visualisation with metrology measuring techniques by displaying measurements taken in real-time in holographic form can assist in research and education. New structural designs such as the Plexiglass Stand and the Hologram Box can optimise the holographic experience. Method: The equipment used included: (i) Zeiss’s ATOS Core 300 optical coordinate measuring instrument that scanned real-world objects; (ii) Cloud Compare, open-source software used for point cloud processing; and (iii) Hologram Box, designed and manufactured during this research to provide the blackout environment needed to display 3D point clouds in real-time measurements in holographic format, in addition to a portability aspect to holograms. The equipment was tailored to realise the goal of displaying measurements in an innovative technique and to improve on conventional methods. Three test scans were completed before doing a holographic conversion. Results: The outcome was a precise recreation of the original object in the holographic form presented with dense point clouds and surface density features in a colour map. Conclusion: This work establishes a way to visualise data in a point cloud system. To our understanding, this is a work that has never been attempted. This achievement provides an advancement in holographic visualisation. The Hologram Box could be used as a feedback tool for measurement quality control and verification in future smart factories.

Keywords: holography, 3D scans, hologram box, metrology, point cloud

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Authors: Filip Franciszek Karuga, Szymon Turkiewicz, Marta Ditmer, Marcin Sochal, Piotr Białasiewicz, Agata Gabryelska

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Circadian rhythm, an internal coordinator of physiological processes is composed of a set of semi-autonomous clocks. Clocks are regulated through the expression of circadian clock genes which form feedback loops, creating an oscillator. The primary loop consists of activators: CLOCK, BMAL1 and repressors: CRY, PER. CLOCK can be substituted by the Neuronal PAS Domain Protein 2 (NPAS2). Orphan nuclear receptor (REV-ERB-α) is a component of the secondary major loop, modulating the expression of BMAL1. Circadian clocks might be disrupted by the obstructive sleep apnea (OSA), which has also been associated with type II diabetes mellitus (DM2). Interestingly, studies suggest that dysregulation of NPAS2 and REV-ERB-α might contribute to the pathophysiology of DM2 as well. The goal of our study was to examine the role of NPAS2 and REV-ERB-α in DM2 in OSA patients. After examination of the clinical data, all participants underwent polysomnography (PSG) to assess their apnea-hypopnea index (AHI). Based on the acquired data participants were assigned to one of 3 groups: OSA (AHI>30, no DM2; n=17 for NPAS2 and 34 for REV-ERB-α), DM2 (AHI>30 + DM2; n=7 for NPAS2 and 15 for REV-ERB-α) and control group (AHI<5, no DM2; n=16 for NPAS2 and 31 for REV-ERB-α). ELISA immunoassay was performed to assess the serum protein level of REV-ERB-α and NPAS2. The only statistically significant difference between groups was observed in NPAS2 protein level (p=0.037). Post-hoc analysis showed significant differences between the OSA and the control group (p=0.017). AHI and NPAS2 level was significantly correlated (r=-0.478, p=0.002) in all groups. A significant correlation was observed between the REV-ERB-α level and sleep efficiency (r=0.617, p=0.005) as well as sleep maintenance efficiency (r=0.645, p=0.003) in the OSA group. We conclude, that NPAS2 is associated with OSA severity and might contribute to metabolic sequelae of this disease. REV-ERB-α on the other hand can influence sleep continuity and efficiency.

Keywords: OSA, diabetes mellitus, endocrinology, chronobiology

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Authors: Yen-Mei Lee

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Mobile learning (m-learning) has been applied in the education field not only because it is an alternative to web-based learning but also it possesses the ‘anytime, anywhere’ learning features. However, most studies focus on the technology-related issue, such as usability and functionality instead of addressing m-learning from the motivational perspective. Accordingly, the main purpose of the current paper is to integrate critical factors from different motivational theories and related findings to have a better understand the catalysts of an individual’s learning motivation toward m-learning. The main research question for this study is stated as follows: based on different motivational perspectives, what factors of applying mobile devices as medium can facilitate people’s learning motivations? Self-Determination Theory (SDT), Uses and Gratification Theory (UGT), Malone and Lepper’s taxonomy of intrinsic motivation theory, and different types of motivation concepts were discussed in the current paper. In line with the review of relevant studies, three motivating factors with five essential elements are proposed. The first key factor is autonomy. Learning on one’s own path and applying personalized format are two critical elements involved in the factor of autonomy. The second key factor is to apply a build-in instant feedback system during m-learning. The third factor is creating an interaction system, including communication and collaboration spaces. These three factors can enhance people’s learning motivations when applying mobile devices as medium toward learning. To sum up, in the currently proposed paper, with different motivational perspectives to discuss the m-learning is different from previous studies which are simply focused on the technical or functional design. Supported by different motivation theories, researchers can clearly understand how the mobile devices influence people’s leaning motivation. Moreover, instructional designers and educators can base on the proposed factors to build up their unique and efficient m-learning environments.

Keywords: autonomy, learning motivation, mobile learning (m-learning), motivational perspective

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Authors: H. Haryati, A. Nor Azura

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Over the turn of the century, the advertising landscape has evolved significantly, from print media to digital media. In line with the shift to the advanced science and technology dramatically shake the framework of societies Fifth Industrial Revolution (IR5.0), technological endeavors have increased exponentially, which influenced user interaction more inspiring through online advertising that intentionally leads to buying behavior. Users are more accustomed to interactive content that responds to their actions. Thus, immersive experience has transformed into a new engagement experience To centennials. The purpose of this paper is to investigate pleasure and arousal as the fundamental elements of consumer emotions and affective responses to marketing stimuli. A quasi-experiment procedure will be adopted in the research involving 40 undergraduate students in Nilai, Malaysia. This study employed a 2 (celebrity endorser vs. Social media influencer) X 2 (high and low visual complexity) factorial between-subjects design. Participants will be exposed to a printed version depicting a fashion product endorsed by a celebrity and social media influencers, presented in high and low levels of visual complexity. While the questionnaire will be Distributing during the lab test session is used to control their honesty, real feedback, and responses through the latest Instagram design and engagement. Therefore, the research aims to define the immersive experience on Instagram and the interaction between pleasure and arousal. An advertisement that evokes pleasure and arousal will be likely getting more attention from the target audience. This is one of the few studies comparing the endorses in Instagram advertising. Also, this research extends the existing knowledge about the immersive visual complexity in the context of social media advertising.

Keywords: immersive visual experience, instagram, pleasure, arousal

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Authors: Cath Grimley, Debra Bick, Sarah Hillman, Louise Clarke, Helen Atherton, Jo Parsons

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The problem: Women in the UK are offered influenza (flu), pertussis (whooping cough) and COVID-19 vaccinations during their pregnancy but uptake of all three vaccines is below the desired rate. These vaccines are offered during pregnancy as pregnant women are at an increased risk of hospitalisation, morbidity, and mortality from these illnesses. Exposure to these diseases during pregnancy can also have a negative impact on the unborn baby with an increased risk of serious complications both while in utero and following birth. The research aims to explore perceptions about the vaccinations offered in pregnancy both from the perspectives of pregnant women and midwives. To determine factors that influence pregnant women’s decisions about whether or not to accept the vaccines following the Covid-19 pandemic and to explore midwives’ experiences of recommending and delivering vaccines. The approach: This research follows a qualitative design involving semi-structured interviews with pregnant women and midwives in the UK. Interviews with midwives explored vaccination discussions they routinely have with pregnant women and identified some of the barriers to vaccination that pregnant women discuss with them. Interviews with pregnant women explored their views since the COVID-19 pandemic about vaccinations offered during pregnancy, and whether the pandemic has influenced perceptions of vulnerability to illness in pregnant women. Midwives were recruited via participating hospitals and midwife specific social media groups. Pregnant women were recruited via participating hospitals and community groups. All interviews were conducted remotely (using telephone or Microsoft Teams) and analysed using thematic analysis. Findings: 43 pregnant women and 16 midwives were recruited and interviewed. The findings presented here will focus on data from midwives. Topics identified included three key themes for midwives. These were 1) Delivery of vaccinations which includes the convenience of offering vaccinations while attending standard antenatal appointments and practical barriers faced in delivering these vaccinations at hospital. 2) Messages and guidance included the importance of up-to-date informational needs for midwives to deliver vaccines and that uncertainty and conflicting messages about the COVID-19 vaccine during pregnancy were a barrier to delivery. 3) Recommendations to have vaccines look at all aspects of recommendations such as how recommendations are communicated, the contents of the recommendation, the importance of the vaccine and the impact of those recommendations on whether women accept the vaccine. Implications: Findings highlight the importance for midwives to receive clear and consistent information so they can feel confident in relaying this information while recommending and delivering vaccines to pregnant women. Emphasising why vaccines are important when recommending vaccinations to pregnant women in addition to standard information on the availability and timing will add to the strength and impact of that recommendation in helping women to make informed decisions about accepting vaccines. The findings of this study will inform the development of an intervention to increase vaccination uptake amongst pregnant women.

Keywords: vaccination, pregnancy, qualitative, interviews, Covid-19, midwives

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Authors: Revalin Herdianto

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Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

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Authors: Uranus Saadat

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ChatGPT, as one of the well-known artificial intelligence (AI) tools, has recently been integrated into English language education and has had several impacts on learners. Accordingly, concerns regarding the overuse of this tool among EFL/ESL learners are rising, which could lead to several disadvantages in their writing skills development. The use of ChatGPT in facilitating writing skills is a novel concept that demands further studies in different contexts and learners. In this study, a qualitative case study is applied to investigate the impact of ChatGPT on the writing skills of a group of EFL bachelor’s students from Uzbekistan studying Teaching English as the Second Language (TESL) at a private university in Malaysia. The data was collected through the triangulation of document analysis, semi-structured interviews, classroom observations, and focus group discussions. Subsequently, the data was analyzed by using thematic analysis. Some of the emerging themes indicated that ChatGPT is helpful in engaging students by reducing their anxiety in class and providing them with constructive feedback and support. Conversely, certain emerging themes revealed excessive reliance on ChatGPT, resulting in a decrease in students’ creativity and critical thinking skills, memory span, and tolerance for ambiguity. The study suggests a number of strategies to alleviate its negative impacts, such as peer review activities, workshops for familiarizing students with AI, and gradual withdrawal of AI support activities. This study emphasizes the need for cautious AI integration into English language education to cultivate independent learners with higher-order thinking skills.

Keywords: ChatGPT, EFL/ESL learners, English writing skills, artificial intelligence tools, critical thinking skills

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Authors: Meva Apaydin, Fatih Apaydin

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Role of education in the development of society is great. Teaching and training started with the beginning of the history and different methods and techniques which have been applied as the time passed and changed everything with the aim of raising the level of learning. In addition to the traditional teaching methods, technology has been used in recent years. With the beginning of the use of internet in education, some problems which could not be soluted till that time has been dealt and it is inferred that it is possible to educate the learners by using contemporary methods as well as traditional methods. As an advantage of technological developments, distance education is a system which paves the way for the students to be educated individually wherever and whenever they like without the needs of physical school environment. Distance education has become prevalent because of the physical inadequacies in education institutions, as a result; disadvantageous circumstances such as social complexities, individual differences and especially geographical distance disappear. What’s more, the high-speed of the feedbacks between teachers and learners, improvement in student motivation because there is no limitation of time, low-cost, the objective measuring and evaluation are on foreground. In spite of the fact that there is teaching beneficences in distance education, there are also limitations. Some of the most important problems are that : Some problems which are highly possible to come across may not be solved in time, lack of eye-contact between the teacher and the learner, so trust-worthy feedback cannot be got or the problems stemming from the inadequate technological background are merely some of them. Courses are conducted via distance education in many departments of the universities in our country. In recent years, giving lectures such as Turkish Language, English, and History in the first grades of the academic departments in the universities is an application which is constantly becoming prevalent. In this study, the application of Turkish Language course via distance education system by analyzing advantages and disadvantages of the distance education system which is based on internet.

Keywords: distance education, Turkish language, motivation, benefits

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Authors: Kayla Renteria

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This study explored the role animal-assisted psychotherapy (AAP) can play in treating Post-Traumatic Stress Disorder (PTSD) when incorporated into Trauma-informed cognitive behavioral therapy (TF-CBT). A review of the literature was performed to show how incorporating AAP could benefit TF-CBT since this treatment model often presents difficulties, such as client motivation and avoidance of the exposure element of the intervention. In addition, the fluidity of treatment goals during complex trauma cases was explored, as this issue arose in the case study. This study follows the course of treatment of a 12-year-old female presenting with symptoms of PTSD. Treatment consisted of traditional components of the TF-CBT model, with the added elements of AAP to address typical treatment obstacles in TF-CBT. A registered therapy dog worked with the subject in all sessions throughout her treatment. The therapy dog was incorporated into components such as relaxation and coping techniques, narrative therapy techniques, and psychoeducation on the cognitive triangle. Throughout the study, the client’s situation and clinical needs required the therapist to switch goals to focus on current safety and stability. The therapy dog provided support and neurophysiological benefits to the client through AAP during this shift in treatment. The client was assessed quantitatively using the Child PTSD Symptom Scale Self Report for DSM-5 (CPSS-SR-5) before and after therapy and qualitatively through a feedback form given after treatment. The participant showed improvement in CPSS-SR-V scores, and she reported that the incorporation of the therapy animal improved her therapy. The results of this study show how the use of AAP provided the client a solid, consistent relationship with the therapy dog that supported her through processing various types of traumas. Implications of the results of treatment and for future research are discussed.

Keywords: animal-assisted therapy, trauma-focused cognitive behavioral therapy, PTSD in children, trauma treatment

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

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

Keywords: imaging, guidelines, emergency medicine, audit

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Francesco Ceresia

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Workplace aggression is broadly recognized as a main work-related risk for healthcare organizations the world over. Scholars underlined that nonfatal workplace aggressions can be also produced by Type II workplace aggression, that occur when the aggressor has a legitimate relationship with the organization and commits an act of hostility while being served or cared for by members of the organization. Several reviews and meta-analysis highlighted the main antecedents and consequences of Type II verbal and physical workplace aggression in the healthcare sector, also focusing on its economic and psychosocial costs. However, some scholars emphasized the need for a systemic and multi-factorial approach to deeply understand and effectively respond to such kind of aggression. The main aim of the study is to propose a qualitative model of Type II workplace aggression in a health care organization in accordance with the system thinking and multi-factorial perspective. A case study research approach, conducted in an Italian non-hospital healthcare organization, is presented. Two main data collection methods have been adopted: individual and group interviews with a sample (N = 24) of physicians, nurses and clericals. A causal loop diagram (CLD) that describes the main causal relationships among the key-variables of the proposed model has been outlined. The main feedback loops and the causal link polarities have been also defined to fully describe the structure underlining the Type II workplace aggression phenomenon. The proposed qualitative model shows how the Type II workplace aggression is related with burnout, work performance, job satisfaction, turnover intentions, work motivation and emotional dissonance. Finally, strategies and policies to reduce the strength of workplace aggression’s drivers are suggested.

Keywords: healthcare, system thinking, work motivation, workplace aggression

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Authors: Preeti Gacche

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A considerable part of undergraduate level English Examination papers is devoted to grammar. Hence the grammar questions in the question papers are evaluated and the opinions of both students and teachers about them are obtained and analyzed. A grammar test of 100 marks is administered to 43 students to check their performance. The question papers have been evaluated by 10 different teachers and their scores compared. The analysis of 38 University question papers reveals that on an average 20 percent marks are allotted to grammar. Almost all the grammar topics are tested. Abundant use of grammatical terminology is observed in the questions. Decontextualization, repetition, possibility of multiple correct answers and grammatical errors in framing the questions have been observed. Opinions of teachers and students about grammar questions vary in many respects. The students responses are analyzed medium-wise and sex-wise. The Medium at the School level and the sex of the students are found to play no role as far as interest in the study of grammar is concerned. English medium students solve grammar questions intuitively whereas non-English medium students are required to recollect the rules of grammar. Prepositions, Verbs, Articles and Model auxiliaries are found to be easy topics for most students whereas the use of conjunctions is the most difficult topic. Out of context items of grammar are difficult to answer in comparison with contextualized items of grammar. Hence contextualized texts to test grammar items are desirable. No formal training in setting questions is imparted to teachers by the competent authorities like the University. They need to be trained in testing. Statistically there is no significant change of score with the change in the rater in testing of grammar items. There is scope of future improvement. The question papers need to be evaluated and feedback needs to be obtained from students and teachers for future improvement.

Keywords: context, evaluation, grammar, tests

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Authors: Sara D. Garduno-Diaz, Lorena Loriato

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Food selection is one of the main modifiable risk factors for the avoidance of several detrimental health conditions. Excessive and regular sugar intake has been identified as highly unfavorable, yet a highly occurring practice. A proposed approach to modify this eating practice is the online program developed here. The program targets a modification of mindset and lifestyle habits around food, through a four week raw-vegan guided eating program. While the focus of the program is to set up sustainable changes in sugar intake reduction, it also aims to promote a plant-based eating style. Three pilot sessions have been run with participants from seven different countries. Participants are guided through the program via a combination of daily e-mails, a 24-hour support platform, and by-weekly remote live sessions. Meal preparation techniques, as well as cooking instructions, are provided, following set menus developed by a team of professional chefs and nutritionists. Goal setting, as well as alternatives to specific food-related challenges, is addressed. While the program is intended for both women and men, the majority of participants to date have been female. Feedback has been positive, with changes in eating habits have included an elimination of added sugars, an increase in home cooking and vegetable intake, and a reduction in foods of animal origin. Difficulties in following the program have been reported as unavailability of certain ingredients depending on the country of residence of the participants, social and cultural hurdles, and time restrictions. Nevertheless, the results obtained to date indicate this to be a highly interactive program with the potential to be scaled up and applied to various populations as a public health measure on the way to better health.

Keywords: eating habits, food addiction, nutrition education, plant-based, remote practice

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Authors: Amine M. Benmehaia, Amine Oulmane

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The supply response of agricultural commodities to changes in price incentives is an important issue for the success of any policy reform in the agricultural sector. This study aims to quantify the responsiveness of producers of some livestock commodities to price incentives in Algerian context. Time series analysis is used on annual data for a period of 52 years (1966-2018). Both co-integration and vector error correction model (VECM) are used through the Nerlove model of partial adjustment. The study attempts to determine the long-run and short-run relationships along with the magnitudes of disequilibria in the selected commodities. Results show that the short-run price elasticities are low in cow and sheep meat sectors (8.7 and 8% respectively), while their respective long-run elasticities are 16.5 and 10.5, whereas eggs and milk have very high short-run price elasticities (82 and 90% respectively) with long-run elasticities of 40 and 46 respectively. The error correction coefficient, reflecting the speed of adjustment towards the long-run equilibrium, is statistically significant and have the expected negative sign. Its estimates are 12.7 for cow meat, 33.5 for sheep meat, 46.7 for eggs and 8.4 for milk. It seems that cow meat and milk producers have a weak feedback of about 12.7% and 8.4% respectively of the previous year's disequilibrium from the long-run price elasticity, whereas sheep meat and eggs producers adjust to correct long run disequilibrium with a high speed of adjustment (33.5% and 46.7 % respectively). The implication of this is that much more in-depth research is needed to identify those factors that affect agricultural supply and to describe the effect of factors that shift supply in response to price incentives. This could provide valuable information for government in the use of appropriate policy measures.

Keywords: Algeria, cointegration, livestock, supply response, vector error correction model

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Authors: Bulcha Belay Etana, Benny Malengier, Janarthanan Krishnamoorthy, Timothy Kwa, Lieva Vanlangenhove

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Electromyography measures the electrical activity of muscles using surface electrodes or needle electrodes to monitor various disease conditions. Recent developments in the signal acquisition of electromyograms using textile electrodes facilitate wearable devices, enabling patients to monitor and control their health status outside of healthcare facilities. Here, we have developed and tested wearable textile electrodes to acquire electromyography signals from patients suffering from Parkinson’s disease and incorporated a feedback-control system to relieve muscle cramping through thermal stimulus. In brief, the textile electrodes made of stainless steel was knitted into a textile fabric as a sleeve, and their electrical characteristic, such as signal-to-noise ratio, was compared with traditional electrodes. To relieve muscle cramping, a heating element made of stainless-steel conductive yarn sewn onto a cotton fabric, coupled with a vibration system, was developed. The system integrated a microcontroller and a Myoware muscle sensor to activate the heating element as well as the vibration motor when cramping occurred. At the same time, the element gets deactivated when the muscle cramping subsides. An optimum therapeutic temperature of 35.5°C is regulated and maintained continuously by a heating device. The textile electrode exhibited a signal-to-noise ratio of 6.38dB, comparable to that of the traditional electrode’s value of 7.05 dB. For a given 9 V power supply, the rise time for the developed heating element was about 6 minutes to reach an optimum temperature.

Keywords: smart textile system, wearable electronic textile, electromyography, heating textile, vibration therapy, Parkinson’s disease

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Jacob Livingston Slosser, Naja Holten Moller, Thomas Troels Hildebrandt, Henrik Palmer Olsen

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In this paper, we propose a model for human-AI interaction in public administration that involves legal decision-making. Inspired by Alan Turing’s test for machine intelligence, we propose a way of institutionalizing a continuous working relationship between man and machine that aims at ensuring both good legal quality and higher efficiency in decision-making processes in public administration. We also suggest that our model enhances the legitimacy of using AI in public legal decision-making. We suggest that case loads in public administration could be divided between a manual and an automated decision track. The automated decision track will be an algorithmic recommender system trained on former cases. To avoid unwanted feedback loops and biases, part of the case load will be dealt with by both a human case worker and the automated recommender system. In those cases an experienced human case worker will have the role of an evaluator, choosing between the two decisions. This model will ensure that the algorithmic recommender system is not compromising the quality of the legal decision making in the institution. It also enhances the legitimacy of using algorithmic decision support because it provides justification for its use by being seen as superior to human decisions when the algorithmic recommendations are preferred by experienced case workers. The paper outlines in some detail the process through which such a model could be implemented. It also addresses the important issue that legal decision making is subject to legislative and judicial changes and that legal interpretation is context sensitive. Both of these issues requires continuous supervision and adjustments to algorithmic recommender systems when used for legal decision making purposes.

Keywords: administrative law, algorithmic decision-making, decision support, public law

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Gülay Dalgıç, Gildis Tachir

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Architectural design studios are ambiencein where architecture design is realized as a palpable product in architectural education. In the design studios that the architect candidate will use in the design processthe information, the methods of approaching the design problem, the solution proposals, etc., are set uptogetherwith the studio coordinators. The architectural design process, on the other hand, is complex and uncertain.Candidate architects work in a process that starts with abstre and ill-defined problems. This process starts with the generation of alternative solutions with the help of representation tools, continues with the selection of the appropriate/satisfactory solution from these alternatives, and then ends with the creation of an acceptable design/result product. In the studio ambience, many designs and thought relationships are evaluated, the most important step is the early design phase. In the early design phase, the first steps of converting the information are taken, and converted information is used in the constitution of the first design decisions. This phase, which positively affects the progress of the design process and constitution of the final product, is complex and fuzzy than the other phases of the design process. In this context, the aim of the study is to investigate the effects of face-to-face learning model and e-learning model on the early design phase. In the study, the early design phase was defined by literature research. The data of the defined early design phase criteria were obtained with the feedback graphics created for the architect candidates who performed e-learning in the first year of architectural education and continued their education with the face-to-face learning model. The findings of the data were analyzed with the common graphics program. It is thought that this research will contribute to the establishment of a contemporary architectural design education model by reflecting the evaluation of the data and results on architectural education.

Keywords: education modeling, architecture education, design education, design process

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Authors: Tom Ryan

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This paper investigates the rural mobility and accessibility challenges of a specific target group - Seniors. The target group is those over 66 years of age who are entitled to use the Public Transport (PT) Free Travel Scheme in rural Ireland. The paper explores at a high level some of the projected rural PT challenges and requirements over the next 10-15 years, noting that statistical predictions show that there will be a significant population demographic shift within the Senior's age profile. Using the PESTEL framework, the literature review explored existing research concerning mobility, accessibility challenges, and the opportunities Seniors face. Twenty-seven qualitative in-depth interviews with stakeholders within the ecosystem were undertaken. The stakeholders included: rural PT customers, Local-Link managers, NTA senior management, a Minister of State, and a European parliament policymaker. Tier 1 interviewee feedback spotlights that the PT network system does not exist for rural patients to access hospital facilities. There was no evidence from the Tier 2 research findings to show that health policymakers and transport planners are working to deliver a national solution to support patients getting access to hospital appointments. Several research interviewees discussed the theme of isolation and the perceived stigma of senior males utilising PT. The findings indicated that MaaS is potentially revolutionary in the PT arena. Finally, this paper suggests several short-, medium- and long-term recommendations based on the research findings. These recommendations are a potential springboard to ensure that rural PT is suitable for future Irish generations.

Keywords: accessibility, active ageing, car dependence, isolation, seniors health issues, behavioural changes, environmental challenges, internet of things, demand responsive, mobility as a service

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Authors: Pavel Prochazka

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The study deals with transducers for measuring vibration displacements of rotating blade tips in turbomachines. In order to prevent major accidents with extensive economic consequences, it shows an urgent need for every low-pressure steam turbine stage being equipped with modern non-contact measuring system providing information on blade loading, damage and residual lifetime under operation. The requirement of measuring vibration and static characteristics of steam turbine blades, therefore, calls for the development and operational verification of both new types of sensors and measuring principles and methods. The task is really demanding: to measure displacements of blade tips with a resolution of the order of 10 μm by speeds up to 750 m/s, humidity 100% and temperatures up to 200 °C. While in gas turbines are used primarily capacitive and optical transducers, these transducers cannot be used in steam turbines. The reason is moisture vapor, droplets of condensing water and dirt, which disable the function of sensors. Therefore, the most feasible approach was to focus on research of electromagnetic sensors featuring promising characteristics for given blade materials in a steam environment. Following types of sensors have been developed and both experimentally and theoretically studied in the Institute of Thermodynamics, Academy of Sciences of the Czech Republic: eddy-current, Hall effect, inductive and magnetoresistive. Eddy-current transducers demand a small distance of 1 to 2 mm and change properties in the harsh environment of steam turbines. Hall effect sensors have relatively low sensitivity, high values of offset, drift, and especially noise. Induction sensors do not require any supply current and have a simple construction. The magnitude of the sensors output voltage is dependent on the velocity of the measured body and concurrently on the varying magnetic induction, and they cannot be used statically. Magnetoresistive sensors are formed by magnetoresistors arranged into a Wheatstone bridge. Supplying the sensor from a current source provides better linearity. The MR sensors can be used permanently for temperatures up to 200 °C at lower values of the supply current of about 1 mA. The frequency range of 0 to 300 kHz is by an order higher comparing to the Hall effect and induction sensors. The frequency band starts at zero frequency, which is very important because the sensors can be calibrated statically. The MR sensors feature high sensitivity and low noise. The symmetry of the bridge arrangement leads to a high common mode rejection ratio and suppressing disturbances, which is important, especially in industrial applications. The MR sensors feature high sensitivity, high common mode rejection ratio, and low noise, which is important, especially in industrial applications. Magnetoresistive transducers provide a range of excellent properties indicating their priority for displacement measurements of rotating blades in turbomachines.

Keywords: turbines, blade vibration, blade tip timing, non-contact sensors, magnetoresistive sensors

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Authors: David Cobham

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In higher education, a great degree of importance is placed on the internationalization of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks and connections, and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment through learning approaches, assessment methods, and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country, either to study, to work, to volunteer or to gain cultural and social enhancement, has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience, and adopting collaborative online projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learned and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways and that they will persist beyond the present to become part of the 'new normal' for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.

Keywords: higher education management, internationalization, transnational education, virtual mobility

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: N. Liu, N. Tuah, D. Ying

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This research aims to identify and test whether serious games can help children learn and pick up healthy eating habits. The practical component takes the form of digitalizing an already existing educational board game called “All you can eat” (AYCE), designed with the nutritious subject matter in mind. This time with the added features of online playability, which will widen its availability and accessibility to reach more players compared to the physical iteration. The game will be deployed alongside the conducting of theoretical research, which also involves teachers leading children to play said digital version. The research methodology utilizes two experiments, such as handing out surveys to gather feedback from both the partners and students. The research was carried out in several countries, namely Brunei, Malaysia, and Taiwan. The results are to be used for validating the concept of “serious games,” particularly when tied to the health aspect of the players, which in this case were children. As for the research outcomes, they can be applied to a variety of serious games that are related to health topics more broadly and not simply limited to healthy eating habits alone, adopting a balanced combination of practical and theoretical considerations. The study will also help other researchers in the correlated fields of serious game development and pediatrics to better comprehend the needs of children. On the theoretical side, these findings can enable further technological advancements to be made possible, a case in point being more serious games, to provide the appropriate social support precisely on the matter of health-related issues. Not just individuals but rather communities could benefit from improved health and well-being as a result of the project, which, when done right, will potentially improve their quality of life and have fun while doing it. AYCE will be demonstrated to support a wide range of health issues as a result of this research case.

Keywords: culture heritage, digital games, digitalization, traditional religious culture

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Authors: Tae Bo Jeon

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Korean air force is undertaking a big project to replace prevailing hundreds of old air fighters such as F-4, F-5, KF-16 etc. The task is to develop and produce domestic fighters equipped with 2 complete-type engines each. A large number of engines, however, will be purchased as products from a foreign engine maker. In addition to the fighters themselves, secure the proper number of spare engines serves a significant role in maintaining combat readiness and effectively managing the national defense budget due to high cost. In this paper, we presented a model dynamically updating spare engine requirements. Currently, the military administration purchases all the fighters, engines, and spare engines at acquisition stage and does not have additional procurement processes during the life cycle, 30-40 years. With the assumption that procurement procedure during the operational stage is established, our model starts from the initial estimate of spare engine requirements based on limited information. The model then performs military missions and repair/maintenance works when necessary. During operation, detailed field information - aircraft repair and test, engine repair, planned maintenance, administration time, transportation pipeline between base, field, and depot etc., - should be considered for actual engine requirements. At the end of each year, the performance measure is recorded and proceeds to next year when it shows higher the threshold set. Otherwise, additional engine(s) will be bought and added to the current system. We repeat the process for the life cycle period and compare the results. The proposed model is seen to generate far better results appropriately adding spare engines thus avoiding possible undesirable situations. Our model may well be applied to future air force military operations.

Keywords: DMSMS, operational availability, METRIC, PRS

Procedia PDF Downloads 172