Search results for: collaborative tasks

Authors: Matias Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, the most roads in rural areas are dirt road. They require frequent maintenance since are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the main-tenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like in Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision

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Authors: Lucie Cote, Isabelle Rodier

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The main objective of the research was to identify demonstrated mechanisms promoting psychological well-being and psychological health in the workplace, and to take a critical look at the 'National Standard of Canada for Psychological Health and Safety in the Workplace - Prevention, Promotion and Guidance to Staged Implementation (Standard)' as a mechanism to promote the psychological well-being and psychological health in the workplace. A review of the scientific literature was conducted, and a case study was done using data from a Canadian federal department. The following six mechanisms with an efficiency supported by most of the studies reviewed were identified: improving psychological well-being in the workplace literacy; strengthening the resilience of employees; creating an environmentally friendly and healthy workplace; promoting a healthy lifestyle; taking into account psychological characteristics in the drafting of job descriptions and tasks during the hiring process; and offering psychological self-care tools. The Standard offers several mechanisms beyond those previously identified and their implementation can be demanding. Research based on objective data and addressing the magnitude of the effect would be required.

Keywords: critical review, national standard of Canada, psychological health, workplace

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Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

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Authors: Kika Ioannou Kazamia

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This paper examines the action research cycle of the second phase of longitudinal research on sustainable interior design practices, between two groups of stakeholders, designers and clients. During this phase of the action research, the second step - the change stage - of Lewin’s change management model has been utilized to change values, approaches, and attitudes toward sustainable design practices among the participants. Affective domain learning theory is utilized to attach new values. Learning with the use of information technology, collaborative learning, and problem-based learning are the learning methods implemented toward the acquisition of the objectives. Learning methods, and aims, require the design of interventions with participants' involvement in activities that would lead to the acknowledgment of the benefits of sustainable practices. Interventions are steered to measure participants’ decisions for the worth and relevance of ideas, and experiences; accept or commit to a particular stance or action. The data collection methods used in this action research are observers’ reports, participants' questionnaires, and interviews. The data analyses use both quantitative and qualitative methods. The main beneficial aspect of the quantitative method was to provide the means to separate many factors that obscured the main qualitative findings. The qualitative method allowed data to be categorized, to adapt the deductive approach, and then examine for commonalities that could reflect relevant categories or themes. The results from the data indicate that during the second phase, designers and clients' participants altered their behaviours.

Keywords: design, change, sustainability, learning, practices

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Authors: Vaibhav Garg

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The concept of guest engagement lies in the rigor of operational excellence and the emotional engagement of associates who perform their tasks genuinely from their hearts and hence in word and indeed, in intent and through gestures, a great hospitality is always genuine, attentive, passionate, caring and warm where engaged associates deliver exceptional service experiences and creates memories to last forever for the guests. One out of every five guests says that their decision of coming back to the same hotel is influenced by the opportunity to “experience and be engaged” A key question is what does a guest mean by experience and be engaged? Most hotels are highly concerned about the guest satisfaction. Therefore they have the brand standards which are a guide to the associate to ensure consistent implementation of set service and product standards to satisfy a guest. However, satisfaction of basic guest needs does not necessarily lead to engagement. For example an absolutely clean room and an in room dining order delivered on time can satisfy a guest but may not engage him. Absence of these standards can certainly lead to guest dissatisfaction however; the presence of these standards does not necessarily lead to guest engagement or guest delight.

Keywords: guest engagement, guest satisfaction, hospitality, hotel operations, operational excellence

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Authors: Desmond Chinedu Oparaku, Emmanuel Uwazie Anyanwu, Oyemike Victor Benson, Ogbonna Isaac-Nnadimele

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The purpose of this paper is to provide a theoretical discourse that highlights the challenges associated with management of indigenous knowledge with reference to developing countries. Literature review and brainstorming were used to collect relevant data and draw inferences. The findings indicate that non-existence of indigenous knowledge management policy (IKMP), low level of partnership drive among library and information services providers, non-uniformity of format and content of indigenous knowledge, inadequate funding, and lack of access to ICTs, lack of indigenous people with indigenous expertise and hoarding of knowledge as challenges to indigenous knowledge management. The study is based on literature review and information gathered through brain storming with professional colleagues the geographic scope as developing countries. The study has birth several implication based on the findings made. Professionally, it has necessitated the need for formulating a viable indigenous knowledge management policy (IKMP), creating of collaborative network through partnership, and integration of ICTs to indigenous knowledge management practices by libraries in developing countries etc. The originality of this paper is revealed in its capability as serving as an eye opener to librarians on the need for preserving and managing indigenous knowledge in developing countries. It further unlocks the possibilities of exploring empirical based researches to substantiate the theoretical issues raised in this paper. The findings may be used by library managers to improve indigenous knowledge management (IKM).

Keywords: developing countries, ICTs, indigenous knowledge, knowledge management

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Authors: Minghui Zou

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This study investigates whether and how cognate status influences switching costs in bilingual language production. Two picture naming tasks will be conducted in this proposed study by manipulating the conditions of how cognates and non-cognates are presented, i.e., separately in two testing blocks vs intermixed in one single testing block. Participants of each experiment will be 24 L1-European Portuguese L2-English unbalanced speakers. Stimuli will include 12 pictures of cognate nouns and 12 of non-cognate nouns. It is hypothesized that there will be cognate switch facilitation effects among unbalanced bilinguals in both of their languages when stimuli are presented either in two single testing blocks or one mixed testing block. Shorter reaction times and higher naming accuracy are expected to be found in cognate switch trials than in non-cognate switch trials.

Keywords: cognates, language switching costs, picture naming, European Portuguese, cognate facilitation effect

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Authors: Yanyue Yuan

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In this paper, the author shares the findings of a pilot study that examines students’ creative expressions and their perceptions of creativity when engaged in project-based learning. The study is based on an elective course that the author co-designed and co-taught with a colleague to sixteen grade six and seven students over the spring semester in 2019. Using the Little Prince story as the main prompt, they facilitated students’ original creation of a storytelling concert that integrated script writing, music production, lyrics, songs, and visual design as a result of both individual and collaborative work. The author will share the specific challenges we met during the project, including learning cultures of the school, class management, teachers' and parents’ attitude, process-oriented versus product-oriented mindset, and facilities and logistical resources. The findings of this pilot study will inform the ongoing research initiative of exploring how we can foster creative learning in public schools in the Chinese context. While K-12 schools of China’s public education system are still dominated by exam-oriented and teacher-centered approaches, the author proposes that expression-based learning can be a starting point for promoting students’ creativity and can serve as experimental efforts to initiate incremental changes within the current education framework. The paper will also touch upon insights gained from collaborations between university and K-12 schools.

Keywords: creativity, expression-based learning, K-12, incremental changes

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Authors: Abdulrahman Nami Almutairi

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In the face of escalating climate change concerns, the concept of smart cities emerges as a promising approach to mitigate carbon emissions and move towards carbon neutrality. This paper provides a comprehensive review of the role of Natural Gas in achieving carbon neutrality. Natural gas has often been seen as a transitional fuel in the context of reducing carbon emissions. Its main role stems from being cleaner than coal and oil when burned for electricity generation and industrial processes. The urgent need to address this global issue has prompted a global shift towards cleaner energy sources and sustainable practices. In this endeavor, natural gas has emerged as a pivotal player, hailed for its potential to mitigate carbon emissions, and facilitate the transition to a low-carbon economy. With its lower carbon intensity compared to conventional fossil fuels, natural gas presents itself as a promising alternative for meeting energy demands while reducing environmental impact. As the world stands at a critical juncture in the fight against climate change, exploring the potential of natural gas as a transitional fuel offers insights into pathways towards a more sustainable and resilient future. By critically evaluating its opportunities and challenges, we can harness the potential of natural gas as a transitional fuel while advancing towards a cleaner, more resilient energy system. Through collaborative efforts and informed decision-making, we can pave the way for a future where energy is not only abundant but also environmentally sustainable and socially equitable.

Keywords: natural gas, clean fuel, carbon emissions, global warming, environmental protection

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Authors: Roman Klas, František Pochylý, Pavel Rudolf

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This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.

Keywords: CFD, radiaxial pump, spiral case, stability

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Authors: M. Zaitoun, S. Cumming, A. Purcell

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This study aims to determine if audiologists' experience characteristics in ABR (Auditory Brainstem Response) reading is associated with their performance in interpreting ABR results. Fifteen ABR traces with varying degrees of hearing level were presented twice, making a total of 30. Audiologists were asked to determine the hearing threshold for each of the cases after completing a brief survey regarding their experience and training in ABR administration. Sixty-one audiologists completed all tasks. Correlations between audiologists’ performance measures and experience variables suggested significant associations (p < 0.05) between training period in ABR testing and audiologists’ performance in terms of both sensitivity and accuracy. In addition, the number of years conducting ABR testing correlated with specificity. No other correlations approached significance. While there are relatively few significant correlations between ABR performance and experience, accuracy in ABR reading is associated with audiologists’ length of experience and period of training. To improve audiologists’ performance in reading ABR results, an emphasis on the importance of training should be raised and standardized levels and period for audiologists training in ABR testing should also be set.

Keywords: ABR, audiology, performance, training, experience

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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Minimizing the response time to asynchronous events in a real-time system is an important factor in increasing the speed of response and an interesting concept in designing equipment fast enough for the most demanding applications. The present article will present the results regarding the validation of the nMPRA (Multi Pipeline Register Architecture) architecture using the FPGA Virtex-7 circuit. The nMPRA concept is a hardware processor with the scheduler implemented at the processor level; this is done without affecting a possible bus communication, as is the case with the other CPU solutions. The implementation of static or dynamic scheduling operations in hardware and the improvement of handling interrupts and events by the real-time executive described in the present article represent a key solution for eliminating the overhead of the operating system functions. The nMPRA processor is capable of executing a preemptive scheduling, using various algorithms without a software scheduler. Therefore, we have also presented various scheduling methods and algorithms used in scheduling the real-time tasks.

Keywords: nMPRA architecture, pipeline processor, preemptive scheduling, real-time system

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: Hakan Bozdoğan

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The goal of this paper is to evaluate the species richness, diversity and structure of in different habitats in the Kahramanmaraş Province in Turkey by using a mathematical program called as Geo-Gebra Software. The Ascalaphidae family comprises the most visually remarkable members of the order Neuroptera due to large dimensions, aerial predatory behaviour and dragonfly-like (or even butterfly-like) habits, allowing an immediate recognition also for occasional observers. Otherwise, they are one of the more poorly known families of the order in respect to biology, ecology and especially larval morphology. This discrepancy appears particularly noteworthy considering that it is a fairly large family (ca. 430 species) widely distributed in tropical and temperate areas of the World. The use of Dynamic Geometry, Analytical Softwares provides researchers a great way of visualising mathematical objects and encourage them to carry out tasks to interact with such objects and add to support of their researching. In this study we implemented; Circle with Center Through Point, Perpendicular Line, Vectors and Rays, Segments and Locus to elucidate the ecological and habitat behaviours of Butterfly-like lacewings in an analytical plane by using Geo-Gebra.

Keywords: neuroptera, Ascalaphidae, geo-gebra software, habitat selectivity

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su

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Deep reinforcement learning has been applied to address various problems in robotics, such as autonomous driving and unmanned aerial vehicle. However, because of the sparse reward penalty for a collision with obstacles during the navigation mission, the agent fails to learn the optimal policy or requires a long time for convergence. Therefore, using obstacles and enemy agents, in this paper, we present a curriculum-based boost learning method to effectively train compound skills during multi-agent reinforcement learning. First, to enable the agents to solve challenging tasks, we gradually increased learning difficulties by adjusting reward shaping instead of constructing different learning environments. Then, in a benchmark environment with static obstacles and moving enemy agents, the experimental results showed that the proposed curriculum learning strategy enhanced cooperative navigation and compound collision avoidance skills in uncertain environments while improving learning efficiency.

Keywords: curriculum learning, hard exploration, multi-agent reinforcement learning, robotic navigation, sparse reward

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Authors: Adamu Mudi, Ibrahim Wahab Fawole, Abubakar Abba Kolo

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In this research paper, we present a microcontroller-based liquid level controller that identifies the various levels of a liquid, carries out certain actions, and is capable of communicating with the human being and other devices through the GSM network. This project is useful in ensuring that a liquid is not wasted. It also contributes to the internet of things paradigm, which is the future of the internet. The method used in this work includes designing the circuit and simulating it. The circuit is then implemented on a solderless breadboard, after which it is implemented on a strip board. A C++ computer program is developed and uploaded into the microcontroller. This program instructs the microcontroller on how to carry out its actions. In other to determine levels of the liquid, an ultrasonic wave is sent to the surface of the liquid similar to radar or the method for detecting the level of sea bed. Message is sent to the phone of the user similar to the way computers send messages to phones of GSM users. It is concluded that the routine of observing the levels of a liquid in a tank, refilling the tank when the liquid level is too low can be entirely handled by a programmable device without wastage of the liquid or bothering a human being with such tasks.

Keywords: Arduino Uno, HC-SR04 ultrasonic sensor, internet of things, IoT, SIM900 GSM module

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Authors: Khenfer Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

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This paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a human-machine interface with a voice recognition system that allows the operator to teleoperate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands pronounced in two languages: French and Arabic. The obtained recognition rate is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equals 30 dB, in this case; the Arabic speech recognition rate is 69%, and the French speech recognition rate is 80%. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: Arabic speech recognition, Hidden Markov Model (HMM), HTK, noise, TIMIT, voice command

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Authors: Shubham V. Kamdi

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This paper aims to serve as an introduction to image resource caching techniques for iOS mobile applications. It will explain how developers can break down multiple image-downloading tasks concurrently using state-of-the-art iOS frameworks, namely Swift Concurrency and Combine. The paper will explain how developers can leverage SwiftUI to develop reactive view components and use declarative coding patterns. Developers will learn to bypass built-in image caching systems by curating the procedure to implement a swift-based LRU cache system. The paper will provide a full architectural overview of a system, helping readers understand how mobile applications are designed professionally. It will cover technical discussion, helping readers understand the low-level details of threads and how they can switch between them, as well as the significance of the main and background threads for requesting HTTP services via mobile applications.

Keywords: main thread, background thread, reactive view components, declarative coding

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Authors: Brogan Guest, Amy Donaldson-Perrott

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The Master’s of Physician Associate Studies (MPAS) programme at St George’s, University of London (SGUL), is an intensive two-year course that trains students to become physician associates (PAs). PAs are generalized healthcare providers who work in primary and secondary care across the UK. PA programmes face the difficult task of preparing students to become safe medical providers in two short years. Our goal is to teach students to develop clinical reasoning early on in their studies and historically, this has been done predominantly though problem-based learning (PBL). We have had an increase concern about student engagement in PBL and difficulty recruiting facilitators to maintain the low student to facilitator ratio required in PBL. To address this issue, we created ‘Clinical Application of Anatomy and Physiology (CAAP)’. These peer-led, interactive, problem-based, small group sessions were designed to facilitate students’ clinical reasoning skills. The sessions were designed using the concept of Team-Based Learning (TBL). Students were divided into small groups and each completed a pre-session quiz consisting of difficult questions devised to assess students’ application of medical knowledge. The quiz was completed in small groups and they were not permitted access of external resources. After the quiz, students worked through a series of openended, clinical tasks using all available resources. They worked at their own pace and the session was peer-led, rather than facilitator-driven. For a group of 35 students, there were two facilitators who observed the sessions. The sessions utilised an infinite space whiteboard software. Each group member was encouraged to actively participate and work together to complete the 15-20 tasks. The session ran for 2 hours and concluded with a post-session quiz, identical to the pre-session quiz. We obtained subjective feedback from students on their experience with CAAP and evaluated the objective benefit of the sessions through the quiz results. Qualitative feedback from students was generally positive with students feeling the sessions increased engagement, clinical understanding, and confidence. They found the small group aspect beneficial and the technology easy to use and intuitive. They also liked the benefit of building a resource for their future revision, something unique to CAAP compared to PBL, which out students participate in weekly. Preliminary quiz results showed improvement from pre- and post- session; however, further statistical analysis will occur once all sessions are complete (final session to run December 2022) to determine significance. As a post-graduate healthcare professional programme, we have a strong focus on self-directed learning. Whilst PBL has been a mainstay in our curriculum since its inception, there are limitations and concerns about its future in view of student engagement and facilitator availability. Whilst CAAP is not TBL, it draws on the benefits of peer-led, small group work with pre- and post- team-based quizzes. The pilot of these sessions has shown that students are engaged by CAAP, and they can make significant progress in clinical reasoning in a short amount of time. This can be achieved with a high student to facilitator ratio.

Keywords: problem based learning, team based learning, active learning, peer-to-peer teaching, engagement

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Authors: Qianxi Lv, Junying Liang

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Among the various modes of interpreting, simultaneous interpreting (SI) is regarded as a ‘complex’ and ‘extreme condition’ of cognitive tasks while consecutive interpreters (CI) do not have to share processing capacity between tasks. Given that SI exerts great cognitive demand, it makes sense to posit that the output of SI may be more compromised than that of CI in the linguistic features. The bulk of the research has stressed the varying cognitive demand and processes involved in different modes of interpreting; however, related empirical research is sparse. In keeping with our interest in investigating the quantitative linguistic factors discriminating between SI and CI, the current study seeks to examine the potential lexical simplification, syntactic complexity and sequential organization mechanism with a self-made inter-model corpus of transcribed simultaneous and consecutive interpretation, translated speech and original speech texts with a total running word of 321960. The lexical features are extracted in terms of the lexical density, list head coverage, hapax legomena, and type-token ratio, as well as core vocabulary percentage. Dependency distance, an index for syntactic complexity and reflective of processing demand is employed. Frequency motif is a non-grammatically-bound sequential unit and is also used to visualize the local function distribution of interpreting the output. While SI is generally regarded as multitasking with high cognitive load, our findings evidently show that CI may impose heavier or taxing cognitive resource differently and hence yields more lexically and syntactically simplified output. In addition, the sequential features manifest that SI and CI organize the sequences from the source text in different ways into the output, to minimize the cognitive load respectively. We reasoned the results in the framework that cognitive demand is exerted both on maintaining and coordinating component of Working Memory. On the one hand, the information maintained in CI is inherently larger in volume compared to SI. On the other hand, time constraints directly influence the sentence reformulation process. The temporal pressure from the input in SI makes the interpreters only keep a small chunk of information in the focus of attention. Thus, SI interpreters usually produce the output by largely retaining the source structure so as to relieve the information from the working memory immediately after formulated in the target language. Conversely, CI interpreters receive at least a few sentences before reformulation, when they are more self-paced. CI interpreters may thus tend to retain and generate the information in a way to lessen the demand. In other words, interpreters cope with the high demand in the reformulation phase of CI by generating output with densely distributed function words, more content words of higher frequency values and fewer variations, simpler structures and more frequently used language sequences. We consequently propose a revised effort model based on the result for a better illustration of cognitive demand during both interpreting types.

Keywords: cognitive demand, corpus-based, dependency distance, frequency motif, interpreting types, lexical simplification, sequential units distribution, syntactic complexity

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Authors: Yu Liang, Wei Wei

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Spatial representation of numbers and numerical magnitude are important for preschoolers’ mathematical ability. Mental number line, a typical index to measure numbers spatial representation, and numerical comparison are both related to arithmetic obviously. However, they seem to rely on different mechanisms and probably influence arithmetic through different mechanisms. In line with this idea, preschool children were trained with two tasks to investigate which one is more important for approximate arithmetic. The training of numerical processing and number line estimation were proved to be effective. They both improved the ability of approximate arithmetic. When the difficulty of approximate arithmetic was taken into account, the performance in number line training group was not significantly different among three levels. However, two harder levels achieved significance in numerical comparison training group. Thus, comparing spatial representation ability, symbolic approximation arithmetic relies more on numerical magnitude. Educational implications of the study were discussed.

Keywords: approximate arithmetic, mental number line, numerical magnitude, preschooler

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Authors: Yihao Kuang, Bowen Ding

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With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graphs and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improved strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain a better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference

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Authors: K. Power, M. White, B. Dunleavey, E. Comerford, C. Doherty, N. Delanty, R. Corbridge, M. Fitzsimons

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Introduction: Providing people with access to their own healthcare information and engaging them as co-authors of their health record can promote better transparency, trust, and inclusivity in the healthcare system. With the advent of electronic health records, there is a move towards involving patients as partners in their healthcare by providing them with access to their own health data via electronic patient portals (ePortal). For example, a recently developed ePortal to the Irish National Epilepsy Electronic Patient Record (EPR) provides access to summary medical records, tools for Patient Reported Outcomes (PROM), health goal-setting and preparation for clinical appointments. Aim: To determine what people with epilepsy (their families/carers) value about the Irish epilepsy ePortal. Methods: A socio-technical process was employed recruiting 30 families of people with epilepsy who also have an intellectual disability (ID). Family members who are a care partner of the person with epilepsy (PWE) were invited to co-design, develop and implement the ePortal. Family members engaged in usability and utility testing which involved a face to face meeting to learn about the ePortal, register for a user account and evaluate its structure and content. Family members were instructed to login to the portal on at least two separate occasions following the meeting and to complete a self-report evaluation tool during this time. The evaluation tool, based on a Usability Questionnaire (Lewis, 1993), consists of a short assessment of comfort using technology, instructions for using the ePortal and some tasks to complete. Tasks included validating summary record details, assessing ePortal ease of use, evaluation of information presented. Participants were asked for suggestions on how to improve the portal and make it more applicable to PWE who also have an ID. Results: Family members responded positively to the ePortal and valued the ability to share information between clinicians and care partners; use the ePortal as a passport between different healthcare settings (e.g., primary care to hospital). In the context of elderly parents of PWE, the ePortal is valued as a tool for supporting shared care between family members. Participants welcomed the facility to log lists of questions and goals to discuss with the clinician at the next clinical appointment as a means of improving quality of care. Participants also suggested further enhancements to the ePortal such as access to clinic letters which can provide an aide memoir in terms of the careplan agreed with the clinical team. For example, through the ePortal, people could see what investigations or therapies are scheduled. Conclusion: The Epilepsy Patient Portal is accessible via a range of devices such as smartphones and tablets. ePortals have the potential to help personalise care, improve patient involvement in clinical decision making, engage them as quality and safety partners, and help clinicians be more responsive to patient needs. Acknowledgement: The epilepsy ePortal project is part of PISCES, a Lighthouse Project funded by eHealth Ireland and HSE to help build an understanding of the benefits of eHealth technologies in the Irish Healthcare System.

Keywords: electronic patient portal, electronic patient record, epilepsy, intellectual disability, usability testing

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Authors: Sara Tusian, Zahra Salehi Motaahed, Narges Sajjadie, Nikoo Dialame

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One of the methods which have frequently been used in Quran is the “question”. In the Quran, in addition to the content, methods are also important. Using analysis-interpretation method, the present study has investigated Quranic questions, and extracted its functions from educational perspective. In so doing, it has first investigated all the questions in Quran and then taking the three-stage classification of education into account, it has offered question functions. The results obtained from this study suggest that question functions in Quran are presented in three categories: the preparation stage (including preparation of the audience, revising the insights, and internal Evolution); main body (including the granting the insight, and elimination of intellectual negligence and the question of innate and logical axioms, the introducting of the realm of thinking, creating emotional arousal and alleged in the claim) and the third stage as modification and revision (including invitation to move in the framework of tasks using the individual beliefs to reveal the contradictions and, Error detection and contribution to change the function) that each of which has a special role in the education process.

Keywords: education, question, Quranic questions, Quran

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Authors: Matich Lyubov

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Today roadmaps are becoming commonly used tools for detecting and designing a desired future for companies, states and the international community. The growing popularity of this method puts tasks such as identifying basic roadmapping principles, creation of concepts and determination of the characteristics of the use of roadmaps depending on the objectives as well as restrictions and opportunities specific to the study area on the agenda. However, the system approach, e.g. the elements which are recognized to be major for high-quality roadmapping, remains one of the main fields for improving the methodology and practice of their development as limited research was devoted to the detailed analysis of the roadmaps from the view of system approach. Therefore, this article is an attempt to examine roadmaps from the view of the system analysis, to compare areas, where, as a rule, roadmaps and systems analysis are considered the most effective tools. To compare the structure and composition of roadmaps and systems models the identification of common points between construction stages of roadmaps and system modeling and the determination of future directions for research roadmaps from a systems perspective are of special importance.

Keywords: technology roadmap, roadmapping, systems analysis, system modeling, innovation management

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Authors: Claire Griffin

Abstract:

Recent years have witnessed a surge in the use of innovative teaching approaches to support student engagement and higher-order learning within higher education. This paper seeks to explore the use of collaborative, interactive teaching and learning strategies to support student engagement in a final year undergraduate Developmental Psychology module. In particular, the use of the jigsaw method, in-class presentations and online discussion fora were adopted in a ‘lectorial’ style teaching approach, aimed at scaffolding learning, fostering social interdependence and supporting various levels of student engagement in higher education. Using the ‘Student Course Engagement Questionnaire’, the impact of such teaching strategies on students’ college classroom experience was measured, with additional qualitative student feedback gathered. Results illustrate the positive impact of the teaching methodologies on students’ levels of engagement, with positive implications emerging across the four engagement factors: skills engagement, emotional engagement, participation/interaction engagement and performance engagement. Thematic analysis on students’ qualitative comments also provided greater insight into the positive impact of the ‘lectorial’ teaching approach on students’ classroom experience within higher level education. Implications of the findings are presented in terms of informing effective teaching practices within higher education. Additional avenues for future research and strategy usage will also be discussed, in light of evolving practice and cutting edge literature within the field.

Keywords: learning, higher education, scaffolding, student engagement

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Authors: Mozadded Hossen

Abstract:

This study investigates the varied effects of internet addiction on college students, specifically examining the behavioral and academic outcomes. The widespread use of the Internet in academic settings has substantially impacted students' mental well-being and academic achievements. The study investigates the correlation between excessive internet usage and addiction, which manifests through symptoms including social isolation, anxiety, despair, and sleep disruptions. Additionally, the study examines the relationship between internet addiction and academic results, finding that kids with more severe addiction levels generally have lower academic performance, experience diminished focus, and show reduced involvement in academic tasks. The study intends to analyze the many consequences of internet addiction to gain insights into its ramifications. It also urges educational institutions to develop techniques that can reduce the negative impact of internet addiction and encourage healthier internet use among students. The results emphasize the necessity of implementing comprehensive measures to tackle the behavioral and academic difficulties caused by internet addiction among college students.

Keywords: internet addiction, behavioral consequences, college students, social isolation

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Authors: Fabrice Setephin Atedjio, Jean-Pierre Lienou, Frederica F. Nelson, Sachin S. Shetty

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Malicious users exploit vulnerabilities in computer systems, significantly disrupting their performance and revealing the inadequacies of existing protective solutions. Even machine learning-based approaches, designed to ensure reliability, can be compromised by adversarial attacks that undermine their robustness. This paper addresses two critical aspects of enhancing model reliability. First, we focus on improving model performance and robustness against adversarial threats. To achieve this, we propose a strategy by harnessing deep reinforcement learning. Second, we introduce an approach leveraging generative adversarial networks to counter adversarial attacks effectively. Our results demonstrate substantial improvements over previous works in the literature, with classifiers exhibiting enhanced accuracy in classification tasks, even in the presence of adversarial perturbations. These findings underscore the efficacy of the proposed model in mitigating intrusions and adversarial attacks within the machine learning landscape.

Keywords: machine learning, reliability, adversarial attacks, deep-reinforcement learning, robustness

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Authors: M. Isabel Santos, Ana Breda, Ana Margarida Almeida

Abstract:

Research on academic abilities of individuals with autism spectrum disorder (ASD) underlines the importance of mathematics interventions. Yet the proposal of digital applications for children and youth with ASD continues to attract little attention, namely, regarding the development of mathematical reasoning, being the use of the digital technologies an area of great interest for individuals with this disorder and its use is certainly a facilitative strategy in the development of their mathematical abilities. The use of digital technologies can be an effective way to create innovative learning opportunities to these students and to develop creative, personalized and constructive environments, where they can develop differentiated abilities. The children with ASD often respond well to learning activities involving information presented visually. In this context, we present the digital Learning Environment on Mathematics for Autistic children (LEMA) that was a research project conducive to a PhD in Multimedia in Education and was developed by the Thematic Line Geometrix, located in the Department of Mathematics, in a collaboration effort with DigiMedia Research Center, of the Department of Communication and Art (University of Aveiro, Portugal). LEMA is a digital mathematical learning environment which activities are dynamically adapted to the user’s profile, towards the development of mathematical abilities of children aged 6–12 years diagnosed with ASD. LEMA has already been evaluated with end-users (both students and teacher’s experts) and based on the analysis of the collected data readjustments were made, enabling the continuous improvement of the prototype, namely considering the integration of universal design for learning (UDL) approaches, which are of most importance in ASD, due to its heterogeneity. The learning strategies incorporated in LEMA are: (i) provide options to custom choice of math activities, according to user’s profile; (ii) integrates simple interfaces with few elements, presenting only the features and content needed for the ongoing task; (iii) uses a simple visual and textual language; (iv) uses of different types of feedbacks (auditory, visual, positive/negative reinforcement, hints with helpful instructions including math concept definitions, solved math activities using split and easier tasks and, finally, the use of videos/animations that show a solution to the proposed activity); (v) provides information in multiple representation, such as text, video, audio and image for better content and vocabulary understanding in order to stimulate, motivate and engage users to mathematical learning, also helping users to focus on content; (vi) avoids using elements that distract or interfere with focus and attention; (vii) provides clear instructions and orientation about tasks to ease the user understanding of the content and the content language, in order to stimulate, motivate and engage the user; and (viii) uses buttons, familiarly icons and contrast between font and background. Since these children may experience little sensory tolerance and may have an impaired motor skill, besides the user to have the possibility to interact with LEMA through the mouse (point and click with a single button), the user has the possibility to interact with LEMA through Kinect device (using simple gesture moves).

Keywords: autism spectrum disorder, digital technologies, inclusion, mathematical abilities, mathematical learning activities

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