Search results for: user guidance

Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: M. P. Sebastian

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Health for all is considered as a sign of well-being and inclusive growth. New healthcare technologies are contributing to the quality of human lives by promoting health education and awareness, leading to the prevention, early diagnosis and treatment of the symptoms of diseases. Healthcare technologies have now migrated from the medical and institutionalized settings to the home and everyday life. This paper explores these new technologies and investigates how they contribute to health education and awareness, promoting the objective of high-value health system for all. The methodology used for the research is literature review. The paper also discusses the opportunities and challenges with futuristic healthcare technologies. The combined advances in genomics medicine, wearables and the IoT with enhanced data collection in electronic health record (EHR) systems, environmental sensors, and mobile device applications can contribute in a big way to high-value health system for all. The promise by these technologies includes reduced total cost of healthcare, reduced incidence of medical diagnosis errors, and reduced treatment variability. The major barriers to adoption include concerns with security, privacy, and integrity of healthcare data, regulation and compliance issues, service reliability, interoperability and portability of data, and user friendliness and convenience of these technologies.

Keywords: big data, education, healthcare, information communication technologies (ICT), patients, technologies

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Authors: Aliasghar Mehdizadeh Dastjerdi, Francisco Camara Pereira

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The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. This paper describes a study of the intention to use a real-time multi-modal travel app aimed at motivating travel behavior change in the Greater Copenhagen Region (Denmark) toward promoting sustainable transport options. The proposed app is a multi-faceted smartphone app including both travel information and persuasive strategies such as health and environmental feedback, tailoring travel options, self-monitoring, tunneling users toward green behavior, social networking, nudging and gamification elements. The prospective for mobility management travel apps to stimulate sustainable mobility rests not only on the original and proper employment of the behavior change strategies, but also on explicitly anchoring it on established theoretical constructs from behavioral theories. The theoretical foundation is important because it positively and significantly influences the effectiveness of the system. However, there is a gap in current knowledge regarding the study of mobility-management travel app with support in behavioral theories, which should be explored further. This study addresses this gap by a social cognitive theory‐based examination. However, compare to conventional method in technology adoption research, this study adopts a reverse approach in which the associations between theoretical constructs are explored by Max-Min Hill-Climbing (MMHC) algorithm as a hybrid causal discovery method. A technology-use preference survey was designed to collect data. The survey elicited different groups of variables including (1) three groups of user’s motives for using the app including gain motives (e.g., saving travel time and cost), hedonic motives (e.g., enjoyment) and normative motives (e.g., less travel-related CO2 production), (2) technology-related self-concepts (i.e. technophile attitude) and (3) use Intention of the travel app. The questionnaire items led to the formulation of causal relationships discovery to learn the causal structure of the data. Causal relationships discovery from observational data is a critical challenge and it has applications in different research fields. The estimated causal structure shows that the two constructs of gain motives and technophilia have a causal effect on adoption intention. Likewise, there is a causal relationship from technophilia to both gain and hedonic motives. In line with the findings of the prior studies, it highlights the importance of functional value of the travel app as well as technology self-concept as two important variables for adoption intention. Furthermore, the results indicate the effect of technophile attitude on developing gain and hedonic motives. The causal structure shows hierarchical associations between the three groups of user’s motive. They can be explained by “frustration-regression” principle according to Alderfer's ERG (Existence, Relatedness and Growth) theory of needs meaning that a higher level need remains unfulfilled, a person may regress to lower level needs that appear easier to satisfy. To conclude, this study shows the capability of causal discovery methods to learn the causal structure of theoretical model, and accordingly interpret established associations.

Keywords: travel app, behavior change, persuasive technology, travel information, causality

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Authors: Jerry D. Johnson, Jason A. LaFrance, Matthew A. Ohlson, Shane C. Shope

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The public school system is the largest employer and most impactful factor in the local economy for many rural communities in the United States. The relationship between the school system and the community is symbiotic—they thrive together or decline together. Understanding the perceptions of rural school superintendents (the titular head of the local school district) with regard to rural development is foundational to understanding how the school and community interact and collaborate in key areas like economic development, community development, and workforce development. To investigate those perceptions as they manifest among superintendents in thriving rural communities, a collective case study was designed and conducted to disclose and characterize superintendent perceptions about rural development in three diverse rural settings in the U.S.: Florida, Kansas, and Ohio. Appreciative Inquiry (AI) served as the conceptual framework and supported a focus on identifying and describing assets and strategies/activities that helped explain the positive results in the communities of interest. Implementation of a criterion-based purposive sampling process (using extant data and a nomination process to identify rural superintendents in communities with vibrant economies and recognized the contribution by the schools in rural development) resulted in two superintendents from each of these state settings who participated in semi-structured interviews. Interview transcripts and relevant extant documents were coded and analyzed to produce individual cases with representative themes, after which a cross-case analysis was conducted to generate overarching themes. The overarching themes were then scrutinized and tested through the application of appropriate credibility techniques to promote the trustworthiness of the results. Findings include the importance of building and maintaining relationships that extend beyond the immediate collaboration activity, the importance of collaboration skills, intentionality of practice, and organizational systems/structures as facilitators/affordances. The results offer potential guidance for leveraging the potential for public schools to contribute to their rural development in the communities they serve.

Keywords: collaboration, leadership, rural development, rural schools

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Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

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Authors: Kazuo Kiguchi, Kouta Ikegami

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In the case of physically weak persons, not only motor abilities, but also sensory abilities are sometimes deteriorated. The concept of perception-assist has been proposed to assist the sensory ability of the physically weak persons with a power-assist robot. Since upper-limb motion is very important in daily living, perception-assist for upper-limb motion has been proposed to assist upper-limb motion in daily living. A virtual tunnel was applied to modify the user’s upper-limb motion if it was necessary. In this paper, effective shape of the virtual tunnel which is applied in the perception-assist for upper-limb motion is proposed. Not only the position of the grasped tool but also the angle of the grasped tool are modified if it is necessary. Therefore, the upper-limb motion in daily living can be effectively modified to realize certain proper daily motion. The effectiveness of the proposed virtual tunnel was evaluated by performing the experiments.

Keywords: motion modification, power-assist robots, perception-assist, upper-limb motion

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Authors: Ofoegbu Ositadinma Edward

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This research paper discusses a web based monitoring system that enables effective monitoring of fuel pump output and sales volume from distributed fuel stations under the domain of a single company/organization. The traditional method of operation by these organizations in Nigeria is non-automated and accounting for dispensed product is usually approximated and manual as there is little or no technology implemented to presently provide information relating to the state of affairs in the station both to on-ground staff and to supervisory staff that are not physically present in the station. This results in unaccountable losses in product and revenue as well as slow decision making. Remote monitoring technology as a vast research field with numerous application areas incorporating various data collation techniques and sensor networks can be applied to provide information relating to fuel pump status in distributed fuel stations reliably. Thus, the proposed system relies upon a microcontroller, keypad and pump to demonstrate the traditional fuel dispenser. A web-enabled PC with an accompanying graphic user interface (GUI) was designed using virtual basic which is connected to the microcontroller via the serial port which is to provide the web implementation.

Keywords: fuel pump, microcontroller, GUI, web

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Authors: Ting Gao, Mingyue He

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Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain

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Intelligent Transportation System is an integrated application of communication, control and monitoring and display process technologies for developing a user–friendly transportation system for urban areas in developing countries. In fact, the development of a country and the progress of its transportation system are complementary to each other. Urban traffic has been growing vigorously due to population growth as well as escalation of vehicle ownership causing congestion, delays, pollution, accidents, high-energy consumption and low productivity of resources. The development and management of urban transport in developing countries like India however, is at tryout stage with very few accumulations. Under the umbrella of ITS, urban corridor management strategy have proven to be one of the most successful system in accomplishing these objectives. The present study interprets and figures out the performance of the 27.4 km long Urban Bus route having six intersections, five flyovers and 29 bus stops that covers significant area of the city by causality analysis. Performance interpretations incorporate Passenger Boarding and Alighting, Dwell time, Distance between Bus Stops and Total trip time taken by bus on selected urban route.

Keywords: congestion, dwell time, passengers boarding alighting, travel time

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Authors: Anish Bhargava

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By 2050, there will be more plastic than fish in our oceans. 51 trillion micro-plastics pollute our waters and contaminate the food on our plates, increasing the risk of tumours and diseases such as cancer. Our product is a solution to the ever-growing problem of plastic pollution. We call it the SmartBin. The SmartBin is a cylindrical device which will float just below the surface of the water, able to move with the aid of 4 water thrusters situated on the sides. As it floats, our SmartBin will suck water into itself and pump it out through the bottom. All waste is collected into a reusable filter including microplastics measuring down to 1.5mm. A speaker emitting sound at a frequency of 9 hertz ensures marine life stays away from the SmartBin. Featured along with our product is a smartphone app which will enable the user to designate an area for the SmartBin to cover on a satellite image. The SmartBin will then return to its start position near the shore, configured through the app. As global pressure to tackle water pollution continues to increase, environmental spending increases too. As our product provides an effective solution to this issue, we can seize the opportunity and scale our company. Our product is unparalleled. It can move at a high speed, covering a wide area rather than being restricted to one position. We target not only oceans and sea-shores, but also rivers, lakes, reservoirs and canals, as they are much easier to access and control.

Keywords: water, plastic, pollution, solution, hydroclean, smartbin, cleanup

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Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

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Authors: Fátima Farinha, Miguel J. Oliveira, Gina Matias, Armando Inverno, Jânio Monteiro, Cristiano Cabrita

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In the last decades, the construction of swimming pools for recreational activities has grown exponentially in southern Europe. Swimming pools are used both for private use in villas and for collective use in hotels or condominiums. However, they have a high environmental impact, mainly in terms of water and energy consumption, being used for a short period of time, depending significantly on favorable atmospheric conditions. Contrary to what would be expected, not enough research has been conducted to reduce the negative impact of this equipment. In this context, this work proposes and analyses technological measures to reduce the environmental impacts of swimming pools, such as thermal insulation of the tank, water balance in order to detect leaks and optimize the backwash process, integration of renewable energy generation, and a smart control system that meets the requirements of the user. The work was developed within the scope of the Ecopool+++ project, which aims to create innovative heated pools with reduced thermal losses and integration of SMART energy plus water management systems. The project is in the final phase of its development, with very encouraging results.

Keywords: swimming pools, sustainability, thermal losses, water management system

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Authors: Nazura Abdul Manap, Siti Nur Farah Atiqah Salleh

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For decades, the misuse of personal data has been a critical issue. Malaysia has accepted responsibility by implementing the Malaysian Personal Data Protection Act 2010 to secure personal data (PDPA 2010). After more than a decade, this legislation is set to be revised by the current PDPA 2023 Amendment Bill to align with the world's key personal data protection regulations, such as the European Union General Data Protection Regulations (GDPR). Among the other suggested adjustments is the Data User's appointment of a Data Protection Officer (DPO) to ensure the commercial entity's compliance with the PDPA 2010 criteria. The change is expected to be enacted in parliament fairly soon; nevertheless, based on the experience of the Personal Data Protection Department (PDPD) in implementing the Act, it is projected that there will be a slew of additional concerns associated with the DPO mandate. Consequently, the goal of this article is to highlight the issues that the DPO will encounter and how the Personal Data Protection Department should respond to this subject. The study result was produced using a qualitative technique based on an examination of the current literature. This research reveals that there are probable obstacles experienced by the DPO, and thus, there should be a definite, clear guideline in place to aid DPO in executing their tasks. It is argued that appointing a DPO is a wise measure in ensuring that the legal data security requirements are met.

Keywords: guideline, law, data protection officer, personal data

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Authors: Poh Im. Lim, Hillary Yee Qin. Tan

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Nowadays, going green has become a trend, and being emphasized in the construction industry. In Malaysia, there are several green rating tools available in the industry and among these, GBI and GreenRE are considered as the most common tools adopted for residential buildings. However, being green is not equal to or making something sustainable. Being sustainable is to take economic, environmental and social aspects into consideration. This is particularly essential in the affordable housing sector as the end-users belong to lower-income and places importance on many socio-economic needs beyond the environmental criteria. This paper discusses the arguments in proposing a sustainability framework that is tailor-made for high-rise affordable housing. In-depth interviews and observation mapping methods were used in gathering inputs from the end-users, non-governmental organisations (NGOs) as well as the professionals. ‘Bottom-up’ approach was applied in this research to show the significance of participation from the local community in the decision-making process. The proposed sustainability framework illustrates the discrepancies between user priorities and what the industry is providing. The outcome of this research suggests that integrating sustainability into high-rise affordable housing is achievable and beneficial to the industry, society, and the environment.

Keywords: green building rating tools, high-rise affordable housing, sustainability framework, sustainable development

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: Ang Ling Weay, Mona Masood

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This paper discusses the potential benefits of an interactive multimedia information representation in enhancing students’ critical thinking aligned with history reasoning in learning history between Secondary School students in Malaysia. Two modes of multimedia information representation implemented which are chronological and thematic information representation. A qualitative study of an unstructured interview was conducted among two history teachers, one history education lecturer, two i-think expert and program trainers and five form 4 secondary school students. The interview was to elicit their opinions on the implementation of thinking maps and interactive multimedia information representation in history learning. The key elements of interactive multimedia (e.g. multiple media, user control, interactivity, and use of timelines and concept maps) were then considered to improve the learning process. Findings of the preliminary investigation reveal that the interactive multimedia information representations have the potential benefits to be implemented as instructional resource in enhancing students’ higher order thinking skills (HOTs). This paper concludes by giving suggestions for future work.

Keywords: multimedia information representation, critical thinking, history reasoning, chronological and thematic information representation

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Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz

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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.

Keywords: robotic, automated, production, offline programming, CAD

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Authors: T. Rocha, P. Carvalho, S. Paredes, J. Henriques, A. Bianchi, V. Traver, A. Martinez

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The main goal of LINK project is to join competences in intelligent processing in order to create a research ecosystem to address two central scientific and technical challenges for personal health care (PHC) deployment: i) how to merge clinical evidence knowledge in computational decision support systems for PHC management and ii) how to provide achieve personalized services, i.e., solutions adapted to the specific user needs and characteristics. The final goal of one of the work packages (WP2), designated Sustainable Linking and Synergies for Excellence, is the definition, implementation and coordination of the necessary activities to create and to strengthen durable links between the LiNK partners. This work focuses on the strategy that has been followed to achieve the definition of the Research Tracks (RT), which will support a set of actions to be pursued along the LiNK project. These include common research activities, knowledge transfer among the researchers of the consortium, and PhD student and post-doc co-advisement. Moreover, the RTs will establish the basis for the definition of concepts and their evolution to project proposals.

Keywords: LiNK Twin European Project, personal health care, cardiovascular diseases, research tracks

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Authors: Vano Tsertsvadze, Marina Chavchanidze, Lali Khurtsia

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Problem of drug use is often seen as a combination of psychological and social problems, but this problem can be considered as economically rational decision in the process of buying pleasure (looking after children, reading, harvesting fruits in the fall, sex, eating, etc.). Before the adoption of the decisions people face to a trade-off - when someone chooses a delicious meal, she takes a completely rational decision, that the pleasure of eating has a lot more value than the pleasure which she will experience after two months diet on the summer beach showing off her beautiful body. This argument is also true for alcohol, drugs and cigarettes. Smoking has a negative effect on health, but smokers are not afraid of the threat of a lung cancer after 40 years, more valuable moment is a pleasure from smoking. Our hypothesis - unsatisfied pleasure and frustration, probably determines the risk of dependence on drug abuse. The purpose of research: 1- to determine the relative measure unit of pleasure, which will be used to measure and assess the intensity of various human pleasures. 2- to compare the intensity of the pleasure from different kinds of activity, with pleasures received from drug use. 3- Based on the analysis of data, to identify factors affecting the rational decision making. Research method: Respondents will be asked to recall the greatest pleasure of their life, which will be used as a measure of the other pleasures. The study will use focus groups and structured interviews.

Keywords: drug, drug-user, measurement, satisfaction

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Carlos Gonzalez

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This paper describes a system to optimize the use of the internet by clients requiring downloading of videos at peak hours. The system consists of a web server belonging to a provider of video contents, a provider of internet communications and a software application running on a client’s computer. The client using the application software will communicate to the video provider a list of the client’s future video demands. The video provider calculates which videos are going to be more in demand for download in the immediate future, and proceeds to request the internet provider the most optimal hours to do the downloading. The times of the downloading will be sent to the application software, which will use the information of pre-established hours negotiated between the video provider and the internet provider to download those videos. The videos will be saved in a special protected section of the user’s hard disk, which will only be accessed by the application software in the client’s computer. When the client is ready to see a video, the application will search the list of current existent videos in the area of the hard disk; if it does exist, it will use this video directly without the need for internet access. We found that the best way to optimize the download traffic of videos is by negotiation between the internet communication provider and the video content provider.

Keywords: internet optimization, video download, future demands, secure storage

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Mikiale Gebreslase Gebremariam, Chai Huaqi, Tesfay Gebretsdkan Gebremichael, Dawit Nega Bekele

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In recent years, brownfield redevelopment projects (BRPs) have contributed to the overarching paradigm of the United Nations 2030 agendas. In the present circumstance, most developed nations adopted BRPs, an efficacious urban policy tool. However, in developing and some advanced countries, BRPs are lacking due to limitations of awareness, policy tools, and financial capability for cleaning up brownfield sites. For example, the growth and development of Ethiopian cities were achieved at the cost of poor urban planning, including no community consultations and excessive urbanization for future growth. The demand for land resources is more and more urgent as the result of an intermigration to major cities and towns for socio-economic reasons and population growth. In the past, the development mode of spreading major cities has made horizontal urbanizations stretching outwards. Expansion in search of more land resources, while the outer cities are growing, the inner cities are polluted by environmental pollution. It is noteworthy that the rapid development of cities has not brought about an increase in people's happiness index. Thus, the proposed management framework for managing brownfields in Ethiopia as a lesson to the developing nation facing similar challenges and growth will add immense value in solving the problems and give insights into brownfield land utilization. Under the umbrella of the grey incidence decision-making model and with the consideration of multiple stakeholders and tight environmental and economic constraints, the proposed management framework integrates different criteria from economic, social, environmental, technical, and risk aspects into the grey incidence decision-making model and gives useful guidance to manage brownfields in Ethiopia. Furthermore, it will contribute to the future development of the social economy and the missions of the 2030 UN sustainable development goals.

Keywords: Brownfields, environmental sustainability, Ethiopia, grey-incidence decision-making, sustainable urban development

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

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Authors: Caroline Bradbury-Jones, Maria Clark, Eleanor Molloy, Nicki Ward

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Background: Significant developments in the protection of Lesbian, Gay, Bisexual, Transgender and Queer (LGBTQ) rights culminated in their inclusion in the Equality Act 2010. This provides legal protection against discrimination including the Public Sector Equality Duty requiring public bodies to consider all individuals when carrying out their day-to-day work. In the UK, whilst the Higher Education sector has made some commitment to eliminating discrimination and addressing LGBTQ inclusivity, there are two particular problems specifically affecting students on professional programmes: -All students will come into contact with LGBTQ patients/clients/students and need to be equipped to respond appropriately to their diverse needs but evidence suggests that this is not always the case. -Many LGBTQ students have specific concerns on professional placements; often ‘going back in the closet’ or feeling uncertain how to respond to questions about their personal lives and being reticent to challenge discrimination against LGBTQ patients/clients/students for fear of reprisal. Study aim: To investigate how best to prepare all students to deal with the issue of gender and sexual diversity and to support LGBTQ students in negotiating (non) disclosure in practice placements. Methods: This multi-method study was conducted in 2017 in the UK. It comprised a student survey, focus group interview with students and a national benchmarking exercise. Findings: Preliminary findings are that there is considerable variation across professional programmes regarding the preparation of students to respond to LGBTQ issues. Similarly, there is considerable difference between the level of preparedness experienced by students irrespective of whether they identify as LGBTQ. Discussion: Nationally there are a number of ‘best practice’ examples that we share in this presentation. These contain important details and guidance about how to better prepare university students for professional practice, and to contribute to eliminating discrimination and addressing LGBTQ inclusivity. Conclusions: The presentation will appeal to delegates who are interested in the equality agenda regarding LGBTQ people. The study findings will be discussed and debated to explore their impact on higher education and learning and to identify ways to integrate best practice into professional curricula across the UK and beyond.

Keywords: diversity, equality, practice, sexuality, students, university

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Authors: Mohamed Z. M. Duwahir, Shian Gao

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The main objective of this project was to introduce and test a new scheme for parameterization of subsonic aerofoil, using a function called Shape Function. Python programming was used to create a user interactive environment for geometry generation of aerofoil using NACA and Shape Function methodologies. Two aerofoils, NACA 0012 and NACA 1412, were generated using this function. Testing the accuracy of the Shape Function scheme was done by Linear Square Fitting using Python and CFD modelling the aerofoil in Fluent. NACA 0012 (symmetrical aerofoil) was better approximated using Shape Function than NACA 1412 (cambered aerofoil). The second part of the project involved comparing two turbulent models, k-ε and Spalart-Allmaras (SA), in Fluent by modelling the aerofoils NACA 0012 and NACA 1412 in conditions of Reynolds number of 3 × 106. It was shown that SA modelling is better for aerodynamic purpose. The experimental coefficient of lift (Cl) and coefficient of drag (Cd) were compared with empirical wind tunnel data for a range of angle of attack (AOA). As a further step, this project involved drawing and meshing 3D wings in Gambit. The 3D wing flow was solved and compared with 2D aerofoil section experimental results and wind tunnel data.

Keywords: CFD simulation, shape function, turbulent modelling, aerofoil

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Authors: Merih Welay Welesilassie

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Understanding educators' readiness to incorporate AI tools into their teaching methods requires comprehensively examining the influencing factors. This understanding is crucial, given the potential of these technologies to personalise learning experiences, improve instructional effectiveness, and foster innovative pedagogical approaches. This study evaluated factors affecting teachers' adoption of AI tools in their English language instruction by extending the Technology Acceptance Model (TAM) to encompass digital readiness support, perceived risk, and trust. A cross-sectional quantitative survey was conducted with 128 English language teachers, supplemented by qualitative data collection from 15 English teachers. The structural mode analysis indicated that implementing AI tools in Ethiopian higher education was notably influenced by digital readiness support, perceived ease of use, perceived usefulness, perceived risk, and trust. Digital readiness support positively impacted perceived ease of use, usefulness, and trust while reducing safety and privacy risks. Perceived ease of use positively correlated with perceived usefulness but negatively influenced trust. Furthermore, perceived usefulness strengthened trust in AI tools, while perceived safety and privacy risks significantly undermined trust. Trust was crucial in increasing educators' willingness to adopt AI technologies. The qualitative analysis revealed that the teachers exhibited strong content and pedagogical knowledge but needed more technology-related knowledge. Moreover, It was found that the teachers did not utilise digital tools to teach English. The study identified several obstacles to incorporating digital tools into English lessons, such as insufficient digital infrastructure, a shortage of educational resources, inadequate professional development opportunities, and challenging policies and governance. The findings provide valuable guidance for educators, inform policymakers about creating supportive digital environments, and offer a foundation for further investigation into technology adoption in educational settings in Ethiopia and similar contexts.

Keywords: digital readiness support, AI acceptance, perceived risc, AI trust

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Authors: Marthinus Conradie

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The conversational dynamics of democratically orientated deliberation continue to stimulate critical scholarship for its potential to bolster robust engagement between different sections of pluralist societies. Several axes of deliberation that have attracted academic attention include face-to-face vs. online interaction, and citizen-to-citizen communication vs. engagement between citizens and political elites. In all these areas, numerous researchers have explored deliberative procedures aimed at achieving instrumental goals such a securing consensus on policy issues, against procedures that prioritise expressive outcomes such as broadening the range of argumentative repertoires that discursively construct and mediate specific political issues. The study that informs this paper, works in the latter stream. Drawing its data from the reader-comments section of a South African broadsheet newspaper, the study investigates online, citizen-to-citizen deliberation by analysing the discursive practices through which competing understandings of social problems are articulated and contested. To advance this agenda, the paper deals specifically with user-generated comments posted in response to news stories on questions of race and racism in South Africa. The analysis works to discern and interpret the various sets of discourse practices that shape how citizens deliberate contentious political issues, especially racism. Since the website in question is designed to encourage the critical comparison of divergent interpretations of news events, without feeding directly into national policymaking, the study adopts an analytic framework that traces how citizens articulate arguments, rather than the instrumental effects that citizen deliberations might exert on policy. The paper starts from the argument that such expressive interactions are particularly crucial to current trends in South African politics, given that the precise nature of race and racism remain contested and uncertain. Centred on a sample of 2358 conversational moves in 814 posts to 18 news stories emanating from issues of race and racism, the analysis proceeds in a two-step fashion. The first stage conducts a qualitative content analysis that offers insights into the levels of reciprocity among commenters (do readers engage with each other or simply post isolated opinions?), as well as the structures of argumentation (do readers support opinions by citing evidence?). The second stage involves a more fine-grained discourse analysis, based on a theorisation of argumentation that delineates it into three components: opinions/conclusions, evidence/data to support opinions/conclusions and warrants that explicate precisely how evidence/data buttress opinions/conclusions. By tracing the manifestation and frequency of specific argumentative practices, this study contributes to the archive of research currently aggregating around the practices that characterise South Africans’ engagement with provocative political questions, especially racism and racial inequity. Additionally, the study also contributes to recent scholarship on the affordances of Web 2.0 software by eschewing a simplistic bifurcation between cyber-optimist vs. pessimism, in favour of a more nuanced and context-specific analysis of the patterns that structure online deliberation.

Keywords: online deliberation, discourse analysis, qualitative content analysis, racism

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Authors: Tanja Ecken, Laura Fricke, Anika Wehling, Maren M. Michaelsen, Tobias Esch

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Studies and applied experiences evidence severe and traumatic accidents not only require physical rehabilitation and recovery but also necessitate a psychological adaption and reorganization to the changed living conditions. Neurobiological models underpinning the experience of happiness and satisfaction postulate life shocks to potentially enhance the experience of happiness and life satisfaction, i.e., posttraumatic growth (PTG). This present study aims to provide an in-depth understanding of the underlying psychological processes of PTG and to outline its consequences on subjective happiness and life satisfaction. To explore the aforementioned, Esch’s ABC Model was used as guidance for the development of a questionnaire assessing changes in happiness and life satisfaction and for a schematic model postulating the development of PTG in the context of paraplegia. Two-stage qualitative interview procedures explored participants’ experiences of paraplegia. Specifically, narrative, semi-structured interviews (N=28) focused on the time before and after the accident, the availability of supportive resources, and potential changes in the perception of happiness and life satisfaction. Qualitative analysis (Grounded Theory) indicated an initial phase of reorganization was followed by a gradual psychological adaption to novel, albeit reduced, opportunities in life. Participants reportedly experienced a ‘compelled’ slowing down and elements of mindfulness, subsequently instilling a sense of gratitude and joy in relation to life’s presumed trivialities. Despite physical limitations and difficulties, participants reported an enhanced ability to relate to oneself and others and a reduction of perceived everyday nuisances. Concluding, PTG can be experienced in response to severe, traumatic life events and has the potential to enrich the lives of affected persons in numerous, unexpected and yet challenging ways. PTG appears to be a spectrum comprised of an interplay of internal and external resources underpinned by neurobiological processes. Participants experienced PTG irrelevant of age, gender, marital status, income or level of education.

Keywords: post traumatic growth, happiness, life satisfaction, traumatic life events, paraplegia, ABC model, trauma

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Authors: Allyson Dale, Max Hlywa

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The Canadian public expects the highest moral standards from Canadian Armed Forces (CAF) members and Department of National Defence (DND) employees. The Chief, Professional Conduct and Culture (CPCC) stood up in April 2021 with the mission of ensuring that the defence culture and members’ conduct are aligned with the ethical principles and values that the organization aspires towards. The Defence Ethics Program (DEP), which stood up in 1997, is a values-based ethics program for individuals and organizations within the DND/CAF and now falls under CPCC. The DEP is divided into five key functional areas, including policy, communications, collaboration, training and education, and advice and guidance. The main focus of the DEP is to foster an ethical culture within defence so that members and organizations perform to the highest ethical standards. The measurement of organizational ethics is often complex and challenging. In order to monitor whether the DEP is achieving its intended outcomes, a performance measurement framework (PMF) was developed using the Director General Military Personnel Research and Analysis (DGMPRA) PMF development process. This evidence-based process is based on subject-matter expertise from the defence team. The goal of this presentation is to describe each stage of the DGMPRA PMF development process and to present and discuss the products of the DEP PMF (e.g., logic model). Specifically, first, a strategic framework was developed to provide a high-level overview of the strategic objectives, mission, and vision of the DEP. Next, Key Performance Questions were created based on the objectives in the strategic framework. A logic model detailing the activities, outputs (what is produced by the program activities), and intended outcomes of the program were developed to demonstrate how the program works. Finally, Key Performance Indicators were developed based on both the intended outcomes in the logic model and the Key Performance Questions in order to monitor program effectiveness. The Key Performance Indicators measure aspects of organizational ethics such as ethical conduct and decision-making, DEP collaborations, and knowledge and awareness of the Defence Ethics Code while leveraging ethics-related items from multiple DGMPRA surveys where appropriate.

Keywords: defence ethics, ethical culture, organizational performance, performance measurement framework

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