bluuebunny/crossref_metadata_2025 huggingface dataset:
Social perception of Embodied Digital Technologies interacting with
humans
Authors: Mandl Sarah , Brade Jennifer , Bretschneider Maximilian , Skripcak Anabel , Asbrock Frank , Meyer Bertolt , Jahn Georg , Klimant Philipp , Strobel Anja
Published: February 2023

Social perception of Embodied Digital Technologies (EDTs) governs their
successful adoption. However, prior findings on processes governing the
social perception of EDTs and corresponding attributions are inconclusive.
With the present study, we investigate social perception and trustworthiness
of robots and Telepresence Systems (TPS). 293 Participants rated five
different EDTs after watching a short video sequence of a space sharing
conflict between the EDT and a human in terms of anthropomorphism,
sociability/morality, activity/cooperation, competence, and trustworthiness.
We found differences between the robots for all four social dimensions. TPS
were perceived differently only in terms of anthropomorphism.
Trustworthiness was not attributed differently to the EDTs. We found
associations between social perception of EDTs and personality traits. With
our findings, we add to the growing body of research on social perception of
EDTs and show that EDTs are indeed perceived differently in dependence of
their design.
Ergonomics and worker well-being: contributions to sustainability in the
apparel manufacturing industry
Authors: Bezerra Gomes De Pinho Pessoa Juliana , Costa Nélson , Carvalho Miguel
Published: February 2023

The main research studies, involving the apparel manufacturing industry,
are more focused on the study and development of new fabrics (technological
and intelligent); new fibers and their combinations; updated anthropometric
tables; functional textile finishing; among others; not being valued the
productivity nor the welfare of the worker. The new demands for the clothing
manufacturing industry, in the context of Industry 4.0, reinforce the need
for new studies, involving the planning, organization, and control of
production, focusing on the worker, analyzing his well-being and the quality
of work. The main objective of this paper is to expand the discussion about
the contributions of ergonomics and well-being to the sustainability of the
worker, in the clothing manufacturing industry, via a bibliographic and
descriptive review of the literature. The PRISMA method was used, with the
research divided in four phases: identification, screening, eligibility, and
inclusion. National and international papers were screened in Scopus, Web of
Science, Google Scholar, and databases of Portuguese and Brazilian
universities, published between 2015 and 2022. Among the 78 articles found,
all were reviewed according to the scope of the research, in which 7 were
included for detailed analysis. The keywords that were used for this
research were: sustainability, apparel industry, industry 4.0, well-being,
ergonomics, productivity, and mental health. From the conducted research, it
was possible to identify two key ideas within industry 4.0: mental health
and well-being of the worker.
Artificial Cognitive Systems and Aviation training
Authors: Del Cid Flores Abner , Ziakkas Dimitrios , G Dillman Brian
Published: February 2023

The research objectives are to (1) provide a complete assessment of
extended reality technologies and (2) discuss the viability of these
technologies for use in US college aviation training programs.The field of
educational services is one of the many that can benefit from utilizing
extended reality technology due to its versatility. Learning and general
performance of student pilots and flight trainees can benefit from applying
extended reality technologies in flight training, which can be advantageous
when using these technologies. We examine the utilization of XR technologies
by looking at them from an educational theoretical framework and analyzing
their applicability across several industries and simulations in Purdue
Artificial Intelligence Laboratory. A comprehensive literature review
resulted in four subtopics, which are as follows: educational theoretical
foundation, XR technologies across industries; XR technologies in education;
and XR technologies in aviation.Results show that the use of XR technologies
has the potential for enhancing learning and performance in safe flight
instruction environments, a possible reduction in student pilot turnover
mainly due to the elimination of the fear factor involved during initial
training when compared to flying in the actual airplane, and an overall low
cost for both flight training organizations and trainees due to the high
levels of portability. These findings led us to propose using XR
technologies as having the potential to enhance learning and performance in
safe flight instruction environments.A comprehensive understanding of the
possibilities offered by XR technology is necessary for the continuation of
aeronautical psychology research offered in Purdue AI laboratory.
Sensor based ergonomic cushion for posture detection and correction
Authors: Shastri Anshuman , Arora Namrata , Sagar Kavita
Published: February 2023

Awkward postures are associated with a number of musculoskeletal
disorders in almost all work sectors. Various studies have indicated the
prevalence of awkward postures in different work setups and have provided
ways to assess postural deviations and their unfavourable effects on general
well being of the workers. The need of the hour is to have an aid that
provides a means not only to assess the awkwardness of a posture, but also
to correct it as soon as it is identified. The study, here, is designed to
develop a solution for assessment and correction of the awkward posture as
soon as it is attained. An ergonomic cushion is presented which is fitted
with printed flex sensors to detect the awkward postures, considering lumbar
curve, thoracic curve and cervical curve. A mobile application is used to
configure the sensing range of the sensors. The application collects the
data for the flex pressure sensors positioned at different points and warn
the user to correct the posture. If not corrected within the stipulated
time, the cushion automatically corrects the posture with the help of a
microcontroller that expands or deflates the cushion as per postural
requirement.
A Data Driven Approach for Language Acquisition
Authors: Liu Ting , Small Sharon , Kubricht James , Tu Peter , Shen Harry , Cartwright Lydia , Orlioglu Samuil
Published: February 2023

Automatic Language Acquisition focuses on teaching an agent to acquire
knowledge to understand the surrounding environment and be adaptive to a new
environment. The traditional language understanding models fall into three
main categories, supervised, semi-supervised, and unsupervised. A supervised
approach is usually accurate but requires a large training dataset, which
building process is expensive and time consuming. In addition, the trained
model is difficult to shift to other domains. On the other hand, building an
unsupervised model is cheap and flexible, but its performance is usually
significantly lower than the performance of the supervised one. With a
relatively small set of guidance at the beginning, a semi-supervised
approach can teach itself through the unlabeled dataset to achieve a
comparable performance as a supervised modal. However, building the guidance
is not a trivial task since the learning process won’t be effective if the
relationship between labeled data and unlabeled data. Different from the
traditional modals, when children learn, they do not require large amounts
of training data. Instead, they can accurately generalize their knowledge
from one object to other objects. In addition, the communication between
them and their parents/teachers/peers helps to fix the wrong claims from the
generalization. In this paper, we present a multimodal system that simulates
the children’s learning process to acquire the knowledge of the entities by
studying three types of attributes, descriptive (the outlook of an entity),
defining (the components of an entity), and affordance (how an entity can be
used). We first utilize an unsupervised Emergent Language (EL) approach to
generate symbolic language (EL codes) to interpret the given images of the
entities (10 images per entity). The K-Mean clustering methods to group
entity images that share the similar EL code. Then we employ a data driven
approach to teach the agent the attributes of the entities in the clusters.
We first calculate the tf-idf scores of the words from the text pieces
(extracted from Corpus of Contemporary American English, a balanced corpus
for American English) containing an entity. From the top ranked words with a
few sample text pieces, the human expert tells which words are attributes
and the attribute type. The human expert also marked the text pieces having
the attributes. For example, red is the descriptive attribute of cup in “the
red cup’ but not in “a cup of red wine”. The learned knowledge is sent to a
bootstrapping modal to find not only new attributes but also new entities.
Our system results show that the data driven approach spent much less time
but learned more attributes compared with the baseline of our system,
teaching the agent the defining attributes of the entities using a carefully
designed curriculum.
The feasibility of fatigue state monitoring based on eye parameters in
virtual reality environment
Authors: Han Jichen , Zhou Xiaozhou , Zong Chenglong , Teng Fei
Published: February 2023

In human‒machine environments, real-time fatigue monitoring of operators
is particularly important. Excessive fatigue will threaten the operation
efficiency and even the safety of operators. At present, experimental
research methods include simulation experiments, half-physical simulations
and real environment tests. The simulation environment experiment has the
advantages of low cost, high security, high repeatability and
anti-interference from external factors. The virtual reality (VR)
environment is a virtual scene based on a 3D virtual model, which is an
important development trend of simulation experiment. However, the
reliability of various measurement methods in VR simulation environment
needs to be verified. In this study, the Varjo XR3 VR device with the best
display effect currently on the market is used together with headphones to
construct a closed simulation experiment scene and at the same time collect
subjective evaluation of monotonous fatigue and eye parameters. Then, the
mapping relationship between the two is explored through confirmatory
experiments. A total of 10 subjects were recruited in this experiment to
induce fatigue by cruising tasks with low load in flight missions. Subjects
needed to independently complete the route cruise task for approximately 50
minutes and report their own fatigue subjective evaluation parameters using
the Borg scale at the flight turning points every 3 minutes. The data of
percentage of eyelid closure over the pupil over time (PERCLOS) and blink
rate were obtained by using head display internal camera image and
projection vectors algorithm, and the validity of eye data was evaluated by
correlation validation with monotonic fatigue subjective evaluation
parameters. The results show that the quality of eye parameters collected by
VR meets the monitoring requirements, and parameters such as PERCLOS and
blink rate have a high correlation with subjective monotonic fatigue
evaluation. Eye monitoring has high availability to evaluate operator
monotonic fatigue in virtual simulation environment.
Multiphase pointing motion model based on hand-eye bimodal cooperative
behavior
Authors: Zong Chenglong , Zhou Xiaozhou , Han Jichen , Wang Haiyan
Published: February 2023

Pointing, as the most common interaction behavior in 3D interactions,
has become the basis and hotspot of natural human-computer interaction
research. In this paper, hand and eye movement data of multiple participants
in a typical pointing task were collected with a virtual reality experiment,
and we further clarified the movements of the hand and eye in spatial and
temporal properties and their cooperation during the whole task process. Our
results showed that the movements of both the hand and eye in a pointing
task can be divided into three stages according to their speed properties,
namely, the preparation stage, ballistic stage and correction stage. Based
on the verification of the phase division of hand and eye movements in the
pointing task, we further clarified the phase division standards and the
relationship between the duration of every pair of phases of hand and eye.
Our research has great significance for further mining human natural
pointing behavior and realizing more reliable and accurate human-computer
interaction intention recognition.
Protection and Transfer of Financial Digital Data Through Open Source
Software
Authors: Filchev Rusko , Dovramadjiev Tihomir , Dimova Rozalina , Parushev Plamen
Published: February 2023

Modern society is increasingly using ICT technologies to transfer
information quickly. In addition to the purely technological advantages of
IT tools, they enable the recipients of information data to be ultimately
facilitated in their operational activities. On the other hand, data
transfer, when it comes to transferring files with specific information, is
a serious issue that concerns both available technological resources and
security. This report aims to explore the current technological capabilities
for the transfer of digital information containing banking, financial and
other data, to be maximum protected from unauthorized or malicious users.
Also into question are conventional methods of transmitting digital data via
email or cloud. Open source software provides the possibility of reliable
encryption and protection: Money Manager Ex, Tor Browser and OnionShare. In
the present study, specific advantages of realizing the transfer of digital
data from the point of transmission to the final recipient are presented.
Fire Risk Assessment in Universities Based on Fault Tree Analysis and
Bayesian Network
Authors: Yang Ang , Sun Beibei
Published: February 2023

In order to scientifically and accurately analyze the fire hazards
existing in colleges and universities, and put forward feasible suggestions
for eliminating hidden dangers, a fire risk assessment method based on Fault
tree analysis and Bayesian network is proposed.Firstly, the Fault tree of
the large loss caused by the fire in the university premises is constructed,
and then the Fault tree is transformed into a Bayesian network model. In
this method, the failure risk of the fire protection system can be obtained
by forward reasoning according to the probability of the basic events in the
fire, and finally, the reliability of the fire protection system of the
whole university is analyzed.At the same time, combined with the reverse
diagnosis and reasoning technology of Bayesian network, according to the
known or assumed state of leaf nodes, the posterior probability and
probability importance degree of each root node can be reversed to check the
weak links in the fire protection system. In the conclusion, suggestions and
rectification strategies are put forward for the fire protection system in
colleges and universities.This paper proposes a method that combines fault
tree analysis with Bayesian network and applies it to fire risk assessment
in colleges and universities. Based on the fire protection big data, the
software Genie3.0 is used to construct a Bayesian network model of fire risk
in universities, and an example analysis of fire risk assessment is carried
out by taking a university in Nanjing as an example, which not only analyzes
the reliability of the entire system, but also It also uses the
bidirectional reasoning ability of Bayesian network to analyze the weak link
performance of the system, which improves the model's description ability
and inference computing ability. It is proved that the FTA-BN method has
application potential in the field of fire risk assessment.
Construction of Cooking Heat transfer Model and Prediction of Temperature
based on Machine Learning
Authors: Shi Huaizhi , Zhang Yan , Zheng Zhu
Published: February 2023

In order to simulate the cooking process heated by gas, considering the
characteristics of water and edible oil and combining with the existing heat
transfer research, a cooking heat transfer model with mass dissipation of
heating medium was constructed in this paper. The numerical simulation of
the heat-transfer model under different heating conditions was carried out
with MATLAB. The container and the medium temperature simulation results fit
well with the experimental data under the same conditions. Based on the
physical model, two deep learning models, MDTN (Multiple Time Difference
Network) and LSTM(Long Short-Term Memory), were used to learn the variation
law of the container temperature during heating. When using the MDTN model
to predict the temperature value over a long time horizon, the actual
temperature of the container was required to be added to the DataSet
intermittently to prevent temperature error from diverging gradually.
However, when using the LSTM model for prediction, since the temperature
change was relatively stable, this model could predict the temperature of a
longer time series using only the initial temperature sequence, and the
prediction result was close to the actual temperature. The prediction
results of both models conformed to the laws of physics.
An Intelligent Retrieval Method of Building Fire Safety Knowledge Based
on Knowledge Graph
Authors: Sun Fengyang , Sun Beibei
Published: February 2023

Aiming at the difficulty of searching standards and specifications due
to the huge and fragmented data in the field of fire safety in China, an
intelligent retrieval method of building fire safety knowledge based on
knowledge graph is proposed. First, ontology is used to construct conceptual
schemas from top down, and knowledge is extracted using rule templates and
stored in the Neo4j graph database to complete the construction of knowledge
graph. Then, on the basis of the knowledge graph, BERT-BiLSTM-CRF model and
BERT classifier are used to process complex questions with multiple
constraints, so as to extract key entities in the question and identify
query intention. Finally, according to the key entities and query intention,
an algorithm is used to generate a Cypher query statement, which is used to
obtain the answer in Neo4j. The intelligent retrieval method based on
knowledge graph standardizes the building fire safety knowledge, solves the
problem of scattered distribution and greatly improves the efficiency of
knowledge retrieval.
A Framework for Hybrid Risk Analysis
Authors: Zharikova Maryna , Pickl Stefan
Published: February 2023

Changes within the worldwide security environment proceed to challenge
our ability to comprehend and react to the constantly changing hybrid
threats that are becoming more diverse, emanating from a wide range of
actors who are enabled by technology. Actors can wield an array of means and
ways to further their security interests at the expense of a target and are
able to do so without being identified.Developing proper situational
awareness is a first and crucial step on the road to achieving better
protection against hybrid threats. Here we propose a novel framework for
hybrid risk analysis that enables the better understanding of operations of
the adversary before their taking place.The idea of the framework is based
on the model of hybrid operations, which combine the elements of space,
time, objects at risk, goals, and actors into a single structure - a
hyper-forest of multi-trees.Taking into account that hybrid operations are
carried out according to certain scenarios characterized by repeatability of
tools in relation to certain goals, we propose using case-based reasoning
approach based on calculating the dynamic similarity of the information
structure of ongoing attack to retrospective sequences of hybrid attacks for
which the goals, tools, and methods are known. Retrospective data is stored
in the case base.The proposed framework combines several models and methods,
the main of which are the multi-tree model of hybrid attack representation,
spatially distributed model of hybrid attack distribution, and the method
for hybrid risk analysis. The method for hybrid risk analysis is based on
two additional models such as vulnerability model and consequences
assessment model that are developed for each type of object at risk.The
suggested framework for hybrid risk analysis offers a better comprehension
of adversary operations prior to them occurring and aids in formulating an
appropriate reaction to the changing scenario.
Privacy Preserving Stress Detection System Using Physiological Data from
Wearable Device
Authors: Lee Yongho , Lee Nahyun , Pham Vinh , Lee Jiwoo , Chung Tai-myoung
Published: February 2023

Stress is considered to be an emotional state deserving of special
attention, as it brings about harmful effects on human health when exposed
to in the long term. Stress may also induce general health risks, including
headaches, sleep disorders, and cardiovascular diseases. Continuous
monitoring of emotion can help patients suffering from psychiatric disorders
better understand themselves and promote the emotional well-being of the
public in general. Recent advancements in wearable technologies and
biosensors enable a decent level of emotion and stress detection through
multimodal machine learning analysis and measurement outside of lab
conditions. As machine learning solutions demand a large amount of training
data, collecting and combining personal data is a prerequisite for accurate
analysis. However, due to the highly sensitive nature of medical data, the
additional implementation of measures for the preservation of user privacy
is a non-trivial task when developing an AI-based stress detection solution.
We propose a novel machine learning stress detection system that facilitates
privacy-preserving data exploitation based on FedAvg, a renowned federated
learning algorithm. We evaluated our system design on a standard multimodal
dataset for the detection of stress. Experiment results demonstrate that our
system may achieve a detection accuracy of 75% without jeopardizing the
privacy of user data.
Different approaches of conducting ergonomic assessment utilizing digital
human models and motion capture in industrial site assembly
Authors: Fischer Clara , Rupprecht Patrick , Schlund Sebastian
Published: February 2023

The further development of Industry 4.0 to 5.0 focuses even more on
human-centred and sustainable production. The ergonomic factor plays a major
role, as it is crucial for the well-being and productivity of workers and
should already be considered in production planning. One of the most common
ergonomic analysis methods is the “Ergonomic As-sessment Worksheet (EAWS)”,
which is based on a paper & paper method for assessing human working
posture. Currently, there are various approaches to automate this
evalua-tion process with the help of digital human models or motion capture
systems. All of these methods have their pros and cons; however, companies
are faced with the problem of finding the best suited method for their
processes. This paper compares three different methods to conduct an EAWS
study for industrial site assembly in terms of methodology, effort, and
efficiency. For this purpose, an evaluation of the physical movement with
the original manual paper and pencil method was created and a generic
movement with a digital human model was implemented and automatically
evaluated. Furthermore, using motion capture, the automatic recording of
physical movement data was carried out, which was computer-assisted
evaluated using digital human models. To exclude software-specific
inconsistencies, we used two different process simulation tools. As a final
result, this paper shows a comparison of different implementation
possibilities of the EAWS anal-yses and indicates the effort and efficiency
for their use in industry. Furthermore, this initial analysis provides an
opportunity for further research on digital human models and motion capture.
Conceptual Exploration of Contextual Information for Situational
Understanding
Authors: Aloimonos Stratis , Raglin Adrienne
Published: February 2023

The Army is often required to deploy soldiers into dangerous situations
to offer assistance and relief. When deployed, these soldiers need to be
aware of the potential dangers, properly assess the level of possible
threats, and make the best choices to respond. One solution for this problem
space is to have an intelligent system that recognizes scenes which may
contain danger, regardless of the type or timeframe associated with that
danger. This type of system would help make decisions about what to do in
situations where danger may be prevalent. Thus, creating an intelligent
system that could identify the scene and contextual information, for
example, potential dangers, would provide greater situational understanding
and support autonomous systems and solider interactions. As a proxy for
representing scenes that may be similar to those encountered by soldiers, a
set of images of natural or manmade disasters were selected and used to
identify strengths and weaknesses in existing models for this type of
intelligent system. In this work, images from CRISISMMD, a dataset of
natural disasters tweets, as well as other images of disasters in the public
domain which do not belong to any particular dataset, are used. For the
initial phase of the work this dataset was used to determine and showcase
the strengths and weaknesses of existing object recognition and visual
question answering systems that when combined would create a prototype
intelligent system. Specifically, YOLO (You Only Look Once), augmented with
Word2Vec (a natural language processing (NLP) system which finds the
similarities of different words in a very large corpus) was selected for
performing the object recognition (Bochkovskiy et al. 2020). This system was
selected to identify objects further based on the presence of other, similar
objects using the similarities between their names. Also, CLIP (Contrastive
Language Image Pretraining), which identifies the probabilities of scenes
based on a certain number of possibilities and BLIP (Bootstrapping Language
Image Pretraining) (Li et al. 2022), an advanced visual question answering
system which is also capable of generating captions for images were
explored. In addition, a concept of an intelligent system where contextual
information is identified and utilized can be used to support situational
understanding.
Creating Virtual Worlds with the Virtual Human Toolkit and the Rapid
Integration & Development Environment
Authors: Hartholt Arno , Mozgai Sharon
Published: February 2023

The research and development of virtual humans, and the virtual worlds
they inhabit, is inherently complex, requiring interdisciplinary approaches
that combine social sciences, computer science, design, art, production, and
domain expertise. Our previous work in managing this complexity has resulted
in the release of the Virtual Human Toolkit (VHToolkit), aimed at lowering
the burden of creating embodied conversational agents. In our current
efforts, we are integrating the VHToolkit with the Rapid Integration &
Development Environment (RIDE), a rapid prototyping modeling and simulation
middleware platform that leverages real-time game engines. This integration
results in the ability to mix and match commercial AI services from AWS,
Azure, and Google, as well as leverage novel 3D geospatial terrain creation
pipelines. Combined with dedicated authoring tools that have been developed
through human-centered design processes, the platform enables researchers,
developers, and domain experts to rapidly create digital worlds with virtual
humans for both military and civilian contexts. Our approach is highly
interdisciplinary, including academia, government, and industry
collaborators. The demonstration shows a user interacting with an embodied
conversational agent embedded within real-world captured and virtualized
terrain. Further research and development features of the platform are
shown, including scripted agent behaviors, networked team play, and machine
learning interfaces.
Sustainable Human Performance In Large People-oriented Corporations:
Integration Of Human Systems For Next-generation Metaverse
Authors: heilala Janne , Singh Khushboo
Published: February 2023

Human systems integration (HSI) involves Human Factors and Ergonomics
(HFE), Human-Machine Interaction (HMI), engineering, and domain experience,
which are the initial components of systems engineering (SE) in all
industries' economies: wellbeing, transportation, energy, IT, retail,
finance, manufacturing, and production. HSI can be achieved by combining
virtual prototyping with Human-In-the-Loop (HIL) simulations. HMI is
typically a model-based and patented innovation; it uses HIL and requires a
homogenized systemic reflection with feedback. Virtual Reality (VR)
Human-Centered Design (HCD) is sustainable. VR-controlled HCD acts as a
definitive Key Enabling Technology (KET) concept in considering the full
range of system Life Cycle Assessments (LCAs) and whether the process is
sustainable. To this end, on the planet earth, human organizational elements
are not only assessed during the design process but the whole LC of a
system. Against intuitive education, it has been stated that conservative
and narrow LCA should not be implemented in a sustainable world but instead
Cradle-to-Cradle (C2C) design from social, economic, or environmental terms;
the objective is to increase positive impacts, not reduce negative ones as
in LCA. By enabling virtual environments, digital tools enable these new
capabilities, which should be realized as sustainable by Digital Twin (DT)
formable as a Sustainable Model Based HSI (SMBHSI) concept with high-level
Artificial Intelligence (AI) and C2C consideration forming the level of the
metaverse, straining from VR. DT-based Internet of Things (IoT) solutions
enable investigators to test scenarios for future foresight, give
corporations abilities to benefit from performance metrics based on domain
experience, and are a crucial concept in SMBHSI. A case on this proceeding
instance will display an example for SMBHSI when the method is scoping
review to the strategic objective to form an up-to-date linear outlook.
Integrating HSI on AI and C2C thinking methodologies helps to save resources
and move towards the globalized green level of circular economies,
representing the economic integration of the economy of the human system by
indirect resources utilization suggestion as indicative as inference and
adaptation to blockchains.
Recognition Model for Activity Classification in Everyday Movements in
the Context of Dementia Diagnostics – Cooking
Authors: Staab Sergio , Martin Ludger , Luderschmidt Johannes , Bröning Lukas
Published: February 2023

By monitoring movements and activities, the progression of neurological
diseases can be detected. The documentation required for this is associated
with a high level of effort, which is hardly possible in view of the
increasing shortage of nursing staff. In order to gradually relieve the
nursing staff, we are developing an approach to automate documentation in
cooperation with two dementia residential communities. The aim of this work
is to facilitate everyday life of caregivers. Previous research results from
this working group show that everyday activities of dementia patients can be
recognized well by combining smartwatch sensor technology and machine
learning. However, the state of research has gaps when it comes to recognize
activities consisting of a variety of movement patterns. In this paper, we
present an approach to classify the activity of cooking. We divide this
activity into several sub-activities each consisting of a distinct motion
pattern that a recurrent network recognizes. This is followed by a model for
calculating the probability that cooking actually occurred based on the
different sub-activities recognized. We show the advantages of different
smartwatch sensor combinations and compare the different approaches of our
model with the prediction accuracy of the classification. This model can
later be integrated into the care documentation of the residential
communities in addition to the activities that are easier to recognize.
Human Factors in Aviation and Artificial Systems: The Purdue Aviation
Virtual Reality case study
Authors: Ziakkas Dimitrios , Del Cid Flores Abner , W Suckow Michael
Published: February 2023

Because of the COVID-19 pandemic, video conferencing has dramatically
expanded as an alternative to traditional face-to-face classroom
instruction. It is particularly challenging to replace practical classes
with video education since they require theoretical and empirical
competence. This research presents a method that uses virtual reality and
metaverse techniques in the classroom as well as simulators to solve the
limitations present in the current models of practical education delivered
at a distance. There is a chance to use emerging hardware and software and
integrate them to establish a new paradigm of training platforms and
pedagogical methods. This can be accomplished through the utilization of
existing resources and the creation of new ones. Traditional flight
simulators are very different in their operational aspects from virtual
reality (VR) due to VR's more reasonable cost, more accessibility, fewer
space requirements, and sustainability. In addition, training with VR can
improve a learner's cognition as well as their ability to acquire new
skills, as well as their technical and psychomotor abilities, and their
willingness to study (Fussel & Hight, 2021). The use of virtual reality
(VR) in training could potentially improve the soft skills of aviation
workers, according to empirical evidence (Haritos & Fussel, 2018;
Oberhauser & Dreyer, 2017). For instance, the findings of Thomas et al.
(2021) suggested that real-world aviation illusion VR scenarios might
increase pilots' ability to prevent accidents originating from visual
illusions when flight operations were being carried out. In undergraduate
aviation education programs, innovative teaching methods that leverage VR
technologies can increase student engagement and reduce the cost of
traditional simulator training for each student. Although VR will not
replace the use of traditional simulators in the near future, this does not
mean that VR will never replace traditional simulators.We developed a
simulated aircraft flight and maintenance environment at the Purdue
Artificial Intelligence Lab (Purdue University - SATT) to verify the
suggested strategy's efficacy. We then compared this environment to the
video-based training system that was already in place. Assessments of the
student's ability to acquire and retain information and attendance were
carried out to determine whether or not the educational efforts were
successful. The experiment findings show that the group that followed the
advised technique fared significantly better on both knowledge tests than
the group that watched the video training. The results of the presence
questionnaire, which validated the participants' perception of physical
presence, were used to establish how user-friendly the proposed system would
be.
Towards a territorial marketing based on citizen involvement
Authors: Alaoui Yasmine
Published: February 2023

The aim of this research is to examine how local authorities, and more
particularly municipalities, should focus on the local population in order
to develop their territorial strategies. The study of governance falls
within the scope of research on the transformation of local public action
and on new forms of multi-level and multi-associates coordination: what
roles do the devices and tools, in this case marketing in the fabric of
local governance, play for a successful attractiveness, and how can
governance be promoted on the basis of an endogenous strategy? The main
purpose of this document is to provide a tool enabling deep reflections on
better ways to strengthen territorial governance. It sets out the issues
involved and proposes to contribute to the engineering of territorial
governance defined as "the set of methods and tools enabling the
coordination, participation and learning of actors and the piloting of
territorial projects".Keywords: Territorial governance, endogenous strategy,
territorial attractiveness, citizen
Sketches versus Artificial Intelligence Systems in Design Creative
Process
Authors: Moreira da Silva Ana
Published: February 2023

Artificial Intelligence Systems are part of our daily life and play an
important role in so many human activities. As most professions, design
practice also relies on artificial intelligence tools. Creativity is an
essential element for design as designer’s task is searching to solve
problems by creating solutions through new ideas, new designs. Sketching has
been traditionally used by designers over the centuries, so it is often seen
as an outdated method for design, as tradition can be thought as a strong
and unalterable link to the past. In this sense, some consider sketching
obsolete, but nowadays its use has evolved and expanded, being widely used
by various areas of knowledge and professional practice, surpassing the
previous and restricted use only by areas linked to the project such as
architecture, engineering and design. Sketches emerge from the need to fix
those first ideas that occur and that are manifested through the first
signs, coming from the brain. A sketch can be like the ‘thought of the
hand’, the hand as an extension of each thought fixed at the moment by the
hand gesture that registers it. This paper investigates the nowadays use of
sketches by designers despite the Artificial Intelligence Systems growing
importance. We intend to rise questions and search for answers and, also,
open a debate about several related issues. What is the nowadays role of
sketches in Design? Sketches can be a necessary step of a design: its first
spark? The process of thinking through sketching helps designers getting
their creativity flowing? Can freehand drawings/sketches in Design practice
take advantages of the Artificial Intelligence Systems?
A Task-Technology Fit Model for Digital Audio Workstations Evaluation
Authors: Etinger Darko
Published: February 2023

Music industry changes in the last decade largely shifted the music
production tasks from big established studios to music artists. With the
addition of online music streaming platforms, an end-to-end process of music
creation, publishing, delivery, and consummation is achieved. This
phenomenon emphasizes music artists as content creators to handle music
production. Digital audio workstation systems enabled end users to compose,
record, mix and master music. This research focuses on identifying the fit
between various tasks music artists must perform during music creation and
the technical characteristic of the tools used, particularly modern digital
audio workstations. Ultimately, it is tested whether the task- technology
fit (TTF), a well-established information systems theory model is a good
predictor of the intention to use digital audio workstation systems by music
artists. By applying the PLS-SEM method, results show that TTF positively
influences music artists' intention to use DAWs.
Design of an economic house with polyurethane wall technology applying
the Lego removable system for the Monte Sinaí Sector, Guayaquil
Authors: Rendon Ivonne , Espinoza Felipe , Ching Johnson , Colorado Bryan , Torres Rommy
Published: February 2023

Access to housing in Ecuador is limited and specifically in the
outskirts of Guayaquil it does not accommodate strata with resources of less
than $100 per month, which is a constant in the Monte Sinaí study sector.
Sustainable development focused on living has allowed new designs to serve
as utilities for society, satisfying emerging housing needs for low-income
populations. The objective of this study is to propose an alternative
architectural design for housing with the use of polyurethane-based
biomaterials using the Lego removable wall construction system to obtain
economic, environmental and social benefits. For the aesthetic development
of the house, the use of scalar modulations is contemplated. The methodology
applied is of a qualitative nature, through the analysis of case studies
that operate as analogous models. The results focused on the development of
types of removable Lego walls and the study of polyurethane additives to the
structural mixture. In conclusion, it is obtained that the development of
housing within the sustainable approach contributes to the economic,
environmental and social well-being of the users of the Monte Sinaí Sector,
who can access decent housing with this design alternative.
Simulation of analytical calculations when optimizing integrative
properties and composite metal coatings
Authors: Rusanov Vyacheslav , Gubanov Ilya , Agafonov Sergey , Daneev Alexey
Published: February 2023

In this work, a nonlinear multidimensional regression-tensor (valence 3)
model is constructed and investigated for the analytical substantiation of
the necessary / sufficient conditions for optimizing the technological
calculation of the multifactor physicochemical process of hardening complex
composite media of metal coatings. An adaptive-a posteriori procedure for
the parametric formation of the target functional of the quality of the
integrative physical and mechanical properties of the designed metal coating
is proposed. The results of the study can serve as the basic elements of the
mathematical language in the creation of automated design of precision
nanotechnologies for hardening the surfaces of complex composite metal
coatings on the basis of group accounting of multifactorial tribological, as
well as anti-corrosion, tests. In this case, the main goal is not so much
the formal accuracy of inferences, but rather the clarity of concepts in the
development of general problems of tribology associated with precision
modeling of nanostructures of complex composite metal coatings. The
multivariate regression-tensor model for tribological / anti-corrosion tests
is substantiated by means of the least squares identification of
multivariate nonlinear regression equations with the minimum tensor norm.
This approach, due to the abundance of available computational problems, as
well as due to the possibilities that it opens up for applications of
nonlinear multivariate regression tensor analysis, can acquire great
(extended) significance in the problems of precision multifactorial
nonlinear optimization of physicochemical processes. strengthening of
complex composite metal coatings and metamaterials.
Informed Materials: Design with Designed Materials as a Method
Authors: Holzbach Markus , Brück Valentin , Zhou Ziyu
Published: February 2023

Materials link countless design issues we are concerned about the most
nowadays: smart technology, digital/analog, user experiences, ecological
environment, etc. Thanks to technological evolutions, designers are
exploring new hybrid materials, which expands the contemporary design
territories. The generation of new materials is due to the transdisciplinary
dialogues among design, art, engineering, human-computer interaction,
biotechnology, etc., but also thanks to designers' understanding, exploring,
and manipulating the properties and attributes of materials in
unconventional ways. The new attributes of these material innovations have
the potential to subvert the conventional material selection in design, and
provide inspiration for new design concepts, functions, and formal
potentials. This approach, known as ‘Design with Designed Materials’,
emphasises the triggering role of materials, especially for experimental
design processes which link with various (artistic) research and creative
methods. This paper will describe how the ‘design with designed materials’
approach contributes to new material explorations and innovations, where
material can be informed by various aspects： digital, material intrinsic, or
a combination of both. By action research, the paper will elaborate on which
way ‘design with designed materials’ acts as a methodical approach in design
research and design education. This is a transdisciplinary approach that
combines the areas of drafting, known from disciplines such as architecture
and design, with those of analysis, research and development of materials,
which are known from engineering and materials technology. On the basis of
an experimental and transdisciplinary approach, new material-based and
material-induced design concepts are developed and researched, putting
material at the beginning of the design process. This approach was validated
in a series of teaching and designing activities, resulting in diverse
design works that brought new logic to the use, exploration and
transformation of materials, and the generation of design concepts. Four
example projects are selected as representatives for describing four
characteristics of materials design: properties, structures, interfaces and
systems. This paper will share those results, bringing the insight that the
new logic of materials is often beyond their original ‘inherent’ properties,
which can trigger the new way of concept generations. Materials become
carriers of a wide variety of information that enter into a dialogue with
their environment, increasingly take on the role of the actual object and
become informative and intuitive.