International Institute of
A Customer Service Chatbot Using Python, Machine Learning, and Artificial Intelligence
Ebsen, Ty; Segall, Richard S.; Aboudja, Hyacinthe; Berleant, Daniel (United States)
https://doi.org/10.54808/IMCIC2024.01.148
ABSTRACT:
This report shows that with the most recent advancements in Artificial
Intelligence (AI) and Natural Language Processing (NLP) using generative-pretrained
transformers, we can develop robust AI applications to assist customer
service departments with question answer systems. This paper addresses
the question answering task using an OpenAI Application Programming
Interface (API). This report examines how to create an AI question answering
application from documents that generated correct answers to questions
about those documents. We used two different approaches to create the
question answering system. One was to use just the OpenAI API. The other
was to use the LangChain framework and libraries. Both applications
did answer questions correctly. LangChain used less code with a higher
learning curve. The OpenAI API used more code and provided more detailed
answers.
A Passive Assessment of Homecare Need with a Rasch Model
Bouchet, Pierre; Toinard, Christian; Jacquot, Sophie (France)
https://doi.org/10.54808/IMCIC2024.01.40
ABSTRACT:
This article proposes a new way of passively assessing homecare need
for older people living at home. The main advantage is to provide a
precise measure with a limited effort for the caregivers. Research proposition
is based on a Rasch model that uses available daily activities of care,
which are performed by the professional caregivers. The proposed approach
follows the idea of a precision and personalized care where the collected
data provide a dedicated measure for the recipient’s homecare needs.
Then from the latter, the recipient’s autonomy can be approached. Data
from 531 recipients were used. They are collected by a French company
providing a Cloud service hosting different homecare services. The proposed
Rasch model aims at completing the available geriatric level of autonomy
(GIR) in order to have a precise and continuous evaluation of the autonomy.
No significant misfit appeared on the considered items of the Rasch
model. Thus, a satisfying Rasch model is proposed for the different
GIR levels showing a consistent relation with this widespread scale.
The proposed assessment enables a continuous evaluation of the evolution
of the loss of autonomy for each recipient through the assessment of
each recipient’s homecare need. Moreover, it provides a wide range of
uses and is a good starting point to bring forth new indicators towards
a precision care. Indeed, our assessment is more responsive but dependent
on the GIR scale. For example, a changepoint detection on a recipient’s
need curve can open discussions amongst the various stakeholders and
thus new means of care can be submitted regarding the evolution of autonomy.
This approach’s purpose is to help the stakeholders, especially the
professional caregivers, to adapt their action plan. It addresses the
complexity of having better indicators for the caregiving needs of older
persons living at home.
Advancements in Digital Twin Application in the Metalforming Industry: State of the Art and Challenges
Brandão Júnior, Paulo S.; Shigaki, Yukio (Brazil)
https://doi.org/10.54808/IMCIC2024.01.46
ABSTRACT:
The application of Digital Twin in the metalforming industry has proven
promising in enhancing procedural control and predictive maintenance.
A Digital Twin is a digital replica of a physical system used to predict
behaviors and optimize processes. Key challenges faced include the acquisition
and quality of production data, validation of the digital environment
and the reliability of results, as well as system automation, which
can be hindered by the dynamic nature of physical processes. Thus, the
main objective of this study is to develop an architecture that can
act in the automation of the DT. This article presents the state of
the art of Digital Twin (DT) technology in the metalforming industry,
highlighting its growth and diverse applications in intelligent manufacturing,
predictive maintenance, and structural analysis. Additionally, it proposes
a Digital Twin architecture for fault prediction and process control
in the forming industry, considering data acquisition and quality, digital
environment validation, and system automation as the main challenges
to be addressed. In the proposed architecture, the inferential base
distinguishes itself, contributing to the system operating autonomously
through four stages: perception, cognition, decision, and execution.
An Assessment of Voice Quality and QoS in Real VoIP Calls Using Multiple Voice Codecs
Ortega Ortega, Martín; Ortega Ortega, Josué (Ecuador)
https://doi.org/10.54808/IMCIC2024.01.79
ABSTRACT:
To get an excellent voice quality in Voice over Internet Protocol (VoIP)
calls you need to analyze and evaluate the perception that the user
has in these calls, in addition to their Quality of Service (QoS). Thus,
the analysis of the Mean Opinion Score (MOS) and the technical theoretical
values of QoS, such as latency, jitter, and packet loss, were carried
out in this research. For this we used different case scenarios based
on the Intra-Wireless Local Area Network (Intra-WLAN) belonging to the
institution of higher education in Ecuador, where the present research
work was carried out, using also an External WLAN or a plan of Internet
services and mobile data. In the case scenarios, real VoIP calls were
made, of which 64 were documented. These calls were made through three
softphone applications with Session Initiation Protocol (SIP) accounts
installed in two terminal equipment (smartphones). Within the three
applications, the following 8 voice codecs were configured: G.711u,
G.711a, G.722 (wideband), G.726-32 (between wideband and narrowband),
and GSM 06.10, G.729, Speex-8 and iLBC-13.33 (narrowband). In the tests
performed during VoIP calls regarding MOS and QoS, the best result was
obtained with the iLBC-13.33 codec.
Analyzing Spatiotemporal Congestion Value on Urban Road Networks Based on Taxi GPS Data
Alshikhe, Rania *; Jindal, Vinita **; Harland, James * (* Australia, ** India)
https://doi.org/10.54808/IMCIC2024.01.32
ABSTRACT:
Traffic congestion poses significant challenges, impacting travel times,
decreasing fuel efficiency, and intensifying air pollution. Consequently,
individuals face difficulties in punctually reaching work or school,
while the increased fuel consumption contributes to elevated gas prices.
Furthermore, air pollution arising from congestion leads to various
health complications. This paper provides a spatiotemporal congestion
analysis, the level of traffic congestion in a specific area is evaluated
and understood for a specific time. Furthermore, this paper proposed
the Road Congestion Matrix (RCM) which provides a novel definition of
traffic congestion as that vehicle traffic flow on road networks involves
the movement of vehicles on individual road segments. In the proposed
method, we consider the congestion value for each edge. As a result,
congested edges can be obtained within the given amount of time. Based
on the congestion value of the road segment itself, we expect the answer
to be able to identify the congested seed of traffic diffusion. In addition,
since most exits are two-way roads, the proposed algorithm also takes
into account the properties of the road segment facing in the opposite
direction with considering the local and global thresholds on the proposed
model. This study illustrates the effectiveness of our method by using
real GPS taxi data and providing detailed analysis of the results.
Application of Building Information Modeling (BIM) in the Planning and Construction of a Building
Baracho, Renata Maria Abrantes; Santiago, Luiz Gustavo da Silva; Silva, Antonio Tagore Assumpção Mendoza e; Porto, Marcelo Franco (Brazil)
https://doi.org/10.54808/IMCIC2024.01.216
ABSTRACT:
This paper aims to introduce Building Information Modeling (BIM) technology
into the process of construction to achieve more efficient buildings,
considering sustainability, economic improvements, reduced waste, and
time optimization. The study involves the design, 3D modeling, planning,
and monitoring of the work to assess the advantages and limitations
of BIM through a real simulation. The methodology comprises theoretical
foundations, 3D modeling, budgeting, and work monitoring. The project
commenced with a 2D blueprint using Autodesk AutoCAD, followed by 3D
modeling in Autodesk Revit. The resultant building, serving as an information
system with a database and 3D modeling, allows for automated budgeting.
The advantages of BIM encompass an interface between project and program,
an interface between software, realistic renderings, precise material
specifications, and family modeling. Limitations include the absence
of material families, reformatting of Autodesk Revit tables when transferred
to the Microsoft Excel program, generic family models with distorted
renderings of reality, and heavy files. Despite these limitations, the
implementation of BIM in buildings proves beneficial for projects. Collaborative
work among stakeholders, optimization of project stages, and the reduction
of expenses and rework can be achieved.
Applying Intelligent System to Sandplay Psychological Status Detection – Transdisciplinary Collaboration
Wu, Yung Gi; Chen, Jwu Jenq; Xie, Jia Ying (Taiwan)
https://doi.org/10.54808/IMCIC2024.01.95
ABSTRACT:
Sandplay psychotherapy, employing sand, water, and miniatures, facilitates
the non-verbal expression of clients' inner worlds. Challenges include
a lack of standardized tools and interpretation difficulties. Applying
intelligent systems addresses these, enhancing assessment accuracy,
providing feedback, and reducing training costs. Transdisciplinary collaboration
is essential, merging psychology, computer science, and art. Our project
integrates AI into sandplay diagnosis, aiming for improved therapeutic
outcomes.
Behind the Numbers: Decoding the Victimization Rate in Albania and Advocating for a Data Revolution
Rokaj, Iv; Leka, Adrian (Albania)
https://doi.org/10.54808/IMCIC2024.01.297
ABSTRACT:
This paper is an effort to explore three important dimensions of victimological
research in Albania. Firstly, it investigates the conceptualization
of the victim within the Albanian legal system and its evolution. Secondly,
the paper critically examines the availability and reliability of victimization
statistics in Albania, assessing current data completeness and areas
for improvement. Lastly, it conducts an in-depth analysis of relevant
statistics to detect victimization patterns and associated risks, providing
meaningful insights into the dynamics of victimization in the Albanian
context. The combined analysis of these aspects highlights the challenges
posed by the scarcity of victimization data. Territorial disparities,
demographic influences, and a detailed analysis of crime categories
contribute to unveiling what is known about victimhood in Albania, making
this the first research of this kind to be conducted in Albania. The
paper advocates for a data revolution, underscoring the importance of
improved data collection and reporting practices to inform effective
interventions and policies in Albania's dynamic landscape. Thus, the
paper offers a comprehensive perspective on victimological research
in Albania, laying the groundwork for informed policies in the evolving
landscape of crime and victimhood in the country.
Benefits of Effective Root Cause Analysis in Software Testing
Nenov, Hristo; Djambazoff, Phil (Bulgaria)
https://doi.org/10.54808/IMCIC2024.01.70
ABSTRACT:
This article describes the problematic reality of software error investigation,
and its short and long-term financial burden [1]. The short-term financial
aspect includes the cost involved in completing the software error [2]
investigation concerning a single issue. The long-term financial weight
pays attention on metrics, such as software stability in production
environment, user’s churn rate probability of increase, potential disapproval
of investment, etc.
The proposed solution is enclosed in a simple testing approach [3],
which is based on a multi-layer validation technic [4] within a single
runtime session.
Business Intelligence (BI) and Geographic Information Systems (GIS) Tools in a Coordinated Strategy for Handling and Controlling Outbreaks of African Swine Fever
Nalesso, Giacomo; Urbani, Rachele; Tassinato, Clara; Tregnaghi, Vittoria; Mazzucato, Matteo; Trolese, Matteo; Lorenzetto, Monica; Rizzo, Simone; Mulatti, Paolo; Di Martino, Guido; Manca, Grazia (Italy)
https://doi.org/10.54808/IMCIC2024.01.294
ABSTRACT:
African Swine Fever (ASF), a severe swine disease with potential zoonotic
implications, historically limited to Sardinia in Italy since 1978,
made its mainland debut in January 2022, raising concerns. The genotype
found in northwest Italy (genotype II) differs from the Sardinian strain
(genotype I). By January 2024, the epidemic had escalated, with 1435
wild boar cases and 21 domestic pig outbreaks reported [6]. The Epidemiology
department of the "Istituto Zooprofilattico Sperimentale delle Venezie"
(IZSVe) responded with innovative tools. These included a comprehensive
data warehouse, integrating farm, processing centre, and slaughterhouse
data with Laboratory Information Management Systems and geospatial information.
Additionally, an "African Swine Fever/Manager" (ASF-Manager) tracked
outbreak specifics, while "IZSVe GIS African Swine Fever" (IZSVeGIS-ASF)
provided real-time monitoring and support for control measures. IZSVeGIS-ASF
facilitates spatial analysis and filtering of data, offering insights
into animal demographics and premises characteristics. Currently exclusive
to IZSVe's Epidemiology department, efforts are underway to expand access
to local and regional veterinary services, fostering collaborative ASF
management. Ongoing enhancements aim to optimize functionality and broaden
utilization during ASF outbreaks.
Business Processes in the Artificial Transformation of Industry 5.0
Babica, Viktorija; Sceulovs, Deniss (Latvia)
https://doi.org/10.54808/IMCIC2024.01.170
ABSTRACT:
In the realm of industrial evolution, the emergence of the Fifth Industrial
Revolution (Industry 5.0) has sparked scholarly discourse since 2017,
merely six years after the widespread recognition of Industry 4.0. Industry
5.0 emerges as a response to the mechanistic tendencies of Industry
4.0, aiming to introduce a more humanistic approach to address global
challenges. However, this evolution is controversial, particularly concerning
its relationship with its predecessor, Industry 4.0. Authors have meticulously
charted a map highlighting the most pivotal elements of each industrial
revolution, spanning from the third to the sixth. This study endeavours
to scrutinise and differentiate the implications and significance of
technologies and methodologies advocated by the Industry 5.0 paradigm
on business processes while concurrently delineating synthetic transformation.
Cell Sorting Using Diagonal Bottom Grooves in Microchannel
Yamamoto, Kota; Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.27
ABSTRACT:
Cell shape and deformability are related to cell function. For the purpose
of cell sorting, a channel with diagonal grooves on the bottom was designed.
Cells suspension was poured into a channel created by micromachining,
and cell sorting according to size was confirmed. Based on the experimental
results, a microchannel for cell sorting using diagonal bottom grooves
in microchannel was proposed.
Control of Biological Cell Orientation on Scaffold
Saito, Keisuke; Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.14
ABSTRACT:
Individual cells have directionality. Cell orientation leads to tissue
orientation. The orientation of cells and tissues is related to their
functions. Cell orientation depends on neighboring cells and the surrounding
environment: mechanical fields (gravity, fluid force), electric fields,
magnetic fields, scaffolding, etc. Methods for controlling the direction
of cells include waves and light. This paper introduces the latest research
results on cell orientation control by type (micropattern, electric
field, ultrasound, magnetic field) and discusses future research directions.
A method that combines electrical stimulation and ultrasound stimulation
is advantageous from the viewpoint of non-contact and minimally invasive
methods. Application to multiple types of cells and tissue formation
is desired.
Cyber Risks: Systematic Literature Analysis
Bahmanova, Alona; Lace, Natalja (Latvia)
https://doi.org/10.54808/IMCIC2024.01.177
ABSTRACT:
This systematic literature review focuses on the digitalization theme
and its associated risks, particularly cyber risks. Conducted through
a comprehensive exploration of the Scopus database over two decades,
employing keywords such as "digitalization," "digitization," and "digital
risks," this research aimed to understand the evolution of terminology
and scholarly discourse in this domain. The investigation initially
targeted "digital risks" but shifted towards keywords like "cyber risks,"
"cybersecurity," and "cyber resilience" to reflect the changing landscape.
The review traces the origins of the often-employed keyword "industry
4.0" and its impact on research interests, prompting a focus on more
recent publications due to the rapid pace of development in the field.
The study follows a structured process for systematic literature review,
providing insights into researchers' perceptions, challenges, and approaches
in addressing cyber risks and related concepts. Each section of the
study offers a concise overview based on the findings in published articles,
contributing to a deeper understanding of cyber risks across interdisciplinary
perspectives.
D-CIDE: An Interactive Code Learning Program
Grant, Lukas; Tennyson, Matthew F.; Owen, Jason (United States)
https://doi.org/10.54808/IMCIC2024.01.245
ABSTRACT:
This paper introduces D-CIDE (Distributed Classroom Integrated Development
Environment), a tool that is designed to improve student-teacher interactions
in programming classes. D-CIDE’s main objective is to provide more meaningful
interactions between teachers and students. Its goal is to create a
more seamless and interactive learning environment for everyone who
uses it. D-CIDE is a distributed integrated development environment
(IDE), where the teacher (host) can manage and interact with the IDEs
of all students (clients). It makes use of server-client interactions
to allow live sharing and editing of code, making it a useful tool for
demonstrating coding techniques and quickly addressing student questions.
The front-end was developed using HTML, CSS, and JavaScript, and provides
a way for the students and teachers to interact with each other. The
back-end is made with JavaScript and NodeJS and handles data processing
and transmission. The effectiveness of D-CIDE was analyzed through a
classroom case study involving a small group of students. The study
measured students' engagement, enjoyment, and learning outcomes using
D-CIDE compared to traditional teaching methods. Results indicated an
increase in student engagement and satisfaction when D-CIDE was used,
as well as an improvement in students' learning experiences.
Deep Learning for Predicting Cerebral Metabolism Changes Along the Alzheimer’s Disease Continuum
García-Gutiérrez, Fernando; Hernández-Lorenzo, Laura; Cabrera-Martín, María Nieves; Matias-Guiu, Jordi A.; Ayala, José L. (Spain)
https://doi.org/10.54808/IMCIC2024.01.115
ABSTRACT:
In recent years, there has been a significant increase in the application
of Artificial Intelligence (AI) techniques in Alzheimer’s disease (AD).
However, current research primarily focuses on differentiating clinical
phenotypes based on cross-sectional designs. In this study, we hypothesize
that modeling additional aspects of the disease, such as variations
in brain metabolism measured by [18F]- fluorodeoxyglucose positron emission
tomography (FDGPET), is possible, and can provide valuable insights
into AD progression. For this purpose, we first identified the brain
regions with the most pronounced brain hypometabolism in AD. Subsequently,
Deep Learning (DL) models, based on feed-forward networks (FFNs) and
convolutional neural networks (CNNs), were used to model variations
in brain metabolism. Our findings demonstrated the feasibility of predicting
trends in brain metabolism along the AD continuum. Overall, this study
introduces a novel dimension to predictive modeling in AD, highlighting
the relevance of predicting variations in brain metabolism.
Device for Sorting of Biological Cells
Haramura, Ten; Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.1
ABSTRACT:
Cells differ by type not only in shape but also in mechanical, electrical,
and magnetic properties. Cells can be sorted using these properties.
Based on each principle, devices for cell sorting have been designed.
This is a technology applied to cell diagnosis and tissue formation
promotion. In this research, the advantages and disadvantages of devices
have been compared and the direction of future research was discussed.
This technology is expected to be applied to the elucidation of cell
properties, disease diagnosis, and regenerative medicine.
Digital Humanities as a Transdisciplinary Communication Paradigm in the Age of AI
Makhachashvili, Rusudan; Semenist, Ivan (Ukraine)
https://doi.org/10.54808/IMCIC2024.01.286
ABSTRACT:
Transformative shifts in the knowledge economy of the XXI century, Industry
4.0 and Web 4.0 development and elaboration of networked society, emergency
digitization of all social communicative spheres due to pandemic measures
have imposed pressing revisions onto interdisciplinary and cross-sectorial
job market demands of university level education, curriculum design
and learning outcomes. As a product of modern civilization, digital
reality has become an independent format of being. Accordingly, electronic
media act not only as a means of transmitting information but also reveal
their own world-creating, meaning-making, and, as a consequence, communicative
potential. The global digital realm stands as an integral environment,
demanding new cognition and perception ways via complex philosophic,
cultural, social, and linguistic approaches, providing unlimited opportunities
for human intellect, communicative development, and research.
The consequent functional tasks to meet this challenge in the educational
sphere worldwide are estimated as 1) to adapt the existent educational
scenarios to digital, remote and hybrid formats; 2) to upgrade e-competence
and digital literacy of all stakeholders of the educational process
and industry; 3) to activate complex interdisciplinary skillsets, otherwise
latent or underutilized in the professional interaction; 4) to introduce
functional technical solutions for facilitation of formal and informal
educational workflow and communication.
The context of the erupted military
intervention in Ukraine and the ensuing information warfare in various
digital ambients (social media, news coverage, digital communications),
the specific value is allocated to the enhanced role of digital humanism
as a tool of the internationally broadcast strife for freedom and sovereignty.
Effect of Periodical Wall Shear Stress on Cultured Cell: Design of Couette Flow Device
Takabe, Yuuki; Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.20
ABSTRACT:
Endothelial cells are oriented in the direction of blood flow on the
inner wall of blood vessels. Endothelial cells are exposed to pulsatile
flow and are subjected to periodic wall shear stress. In this study,
a device was designed to apply periodically fluctuating shear stress
to cells. A Couette-type flow was generated in the culture medium sandwiched
between a rotating disk and a stationary culture plate. By periodically
varying the rotational speed of the disk in a rectangular wave pattern,
periodically varying shear stress was applied to the culture wall surface.
The device was placed in an incubator so that cells in culture could
be continuously observed under a microscope while being exposed to a
cyclic shear stress field. The flow of the culture medium was measured
by tracking the floating cells as tracers. It was confirmed that the
flow fluctuated in a rectangular wave pattern following the rotation
of the disk. This device allows observation of the behavior of cultured
cells under periodic wall shear stress. Research on cellular responses
to mechanical stimulation is expected to be applied to regenerative
medicine through tissue formation.
Examining the Social Determinants of Seeking Help for Postpartum Mental Health
Agustin, Antonni Mikela; Briones, Daryl John; Mallari, Miguel Alberto; Ong, Cristyanna Minda; Paboroquez, Annielov; Rufino, Neki Lora; Sanchez, Janna Mikaela; Adarlo, Genejane (Philippines)
https://doi.org/10.54808/IMCIC2024.01.100
ABSTRACT:
Postpartum is a vulnerable period for women's health, and postpartum
mental health issues, including postpartum depression, are growing concerns.
Despite the increased awareness of mental health, several factors hinder
women from seeking help for mental health concerns during the postpartum
period. Hence, this qualitative study used the World Health Organization’s
Social Determinants of Health Framework to examine the structural and
intermediary determinants that shape women’s help-seeking behaviors
regarding mental health during the postpartum period. A thematic analysis
of interviews with 12 new mothers revealed that the structural determinants
of help-seeking behaviors for postpartum mental health include employment
status and working conditions as enablers and social perceptions of
mental health, societal expectations of motherhood, and financial capabilities
as barriers. This study also showed that intermediary determinants that
enable help-seeking for postpartum mental health include effective communication,
familiarity, informational support, perceptions of formal sources of
help, and the severity of the situation. Conversely, hindrances include
gaps in communication, inadequate emotional support, fear of being misunderstood,
being gossiped about, and being a burden, belief in the responsibilities
associated with motherhood, and belief in self-reliance. These findings
can be used to develop initiatives to promote postpartum mental health.
Exploring Programmatic Thinking: Efficient Code Generation in Programming Languages with Generative Artificial Intelligence for System Simulation
More Valencia, Rubén A.; Tume Ruíz, Juan M.; Rangel Vega, Antia; Puicon Zapata, Hoower A.; Saavedra Arango, Moises D. (Peru)
https://doi.org/10.54808/IMCIC2024.01.139
ABSTRACT:
The study on the application of artificial intelligence (AI) in education,
specifically in computational programming languages and system simulation,
proposes a procedure as part of a structured process to develop libraries
in the R language. In the coding phase, students seek assistance from
Generative AI, which generates code while students create instructions
to assess its quality.
This iterative approach allows continuous improvements in the code.
The evaluation phase involves students working on programming and simulation
tasks validated by the instructor, establishing a structured evaluation
framework.
During the simulation phase, students analyse the results, collaborating
with the instructor to validate their findings. The final stage, reporting
and presentation, emphasizes creating additional scenarios to compare
and validate models, with students presenting reports to the instructor
and showcasing results to the class.
Regarding results, the effectiveness of Generative AI in rapidly and
efficiently generating code is highlighted, showing robust adaptability
to different programming languages. Instructor evaluations suggest some
diversity in the quality of students' work, particularly in code clarity
and readability. Students demonstrate strengths in optimizing code efficiency
and handling exceptions and errors, showcasing their ability to interact
and scale algorithmic knowledge.
The study suggests areas for future research, such as exploring approaches
to enhance the clarity and readability of code generated by Generative
AI, as well as further optimizing efficiency in the practical application
of programming and system simulation through artificial intelligence.
Face Authentication by Constructing a 3D Face Image from 2D Face Images, and Encoding a Unique Identification
Domb, Menachem; Zadok, Ayelet (Israel)
https://doi.org/10.54808/IMCIC2024.01.65
ABSTRACT:
With the vast spread of automation, the significant demand for communication
services, the addition of IoT to the Internet, and the corresponding
increase and sophistication in malicious attacks utilizing system vulnerabilities
to penetrate systems. Identification and Authentication are heavily
used in every access trial towards any electronic resource and communication
networks. The traditional approach to coping with such challenges is
using passwords, encryption, Secure ID, Firewall, Etc. More safety methods
use Biometrics, which suffer from spoofing. The access control market
is a fast-growing and highly volatile market that poses significant
challenges for investors seeking to make secured decisions. As the market
continues to evolve and become more mainstream, there is a growing demand
for new identification and authentication technologies. This paper proposes
expanding the number of features extracted from a 3D image, with unique
features evolved during the generation of the 3D image of the prospect
at the access control stage. Experiments support the proposed approach.
Factors Influencing Positive Financial Performance: The Assessment Given by Latvian Companies
Kasperovica, Ludmila; Lace, Natalja; Ciemleja, Guna (Latvia)
https://doi.org/10.54808/IMCIC2024.01.192
ABSTRACT:
The paper summarises the factors influencing positive financial performance
(profit) in the digital age and the dynamic business environment. Based
on the qualitative and quantitative literature analysis, 33 dominating
financial and non-financial factors were selected, which the authors
emphasize as important for sustainable and profitable business development.
Web of Science-indexed research papers and a bibliometric analysis were
used to assess them. The selected factors were approved and extended.
A survey among Latvian businessmen was carried out to assess the practical
influence of the specified factors on small and medium-sized companies.
The survey involved 77 companies of various sectors and sizes. Turnover
is taken as a unit to measure a company's size. In general, the businessmen
evaluated the essential influence of the selected factors on the positive
financial performance of small and medium-sized companies (profit).
However, in additional comments, they specified risks or deeper views
of the influence of the factors.
Financially Effective Intellectual Property Defense Through Secured Remote Testing
Nenov, Hristo; Djambazoff, Phil (Bulgaria)
https://doi.org/10.54808/IMCIC2024.01.75
ABSTRACT:
For a startup, remotely testing their new launching UI (User Interface)
feature on a real device might be a concern when it comes to intellectual
property rights (IPR) and its safe possession. Today’s approach using
a testing farm [1] is not only quite an expensive service, but also
the intellectual property defense of the testable content is under a
great question mark.
We propose a testing approach with the usage of a reverse proxy mechanism
set up against an exposed local port, which will allow us to run tests
from any location while keeping the new design and functionality of
the launching feature within the physical borders of the startup entity
itself.
From Expert Computational Knowledge to Interdisciplinary Communication
Dokladalova, Eva; Hamouche, Rédha; Kocik, Rémy (France)
https://doi.org/10.54808/IMCIC2024.01.235
ABSTRACT:
In the contemporary landscape, the fields of cybernetics, artificial
intelligence, and digital technology significantly impact society, reshaping
production processes, decision-making frameworks, and human behaviors.
Training engineers with transversal skills becomes imperative to navigate
workflow complexities and communicate across these disciplines. We propose
a new learning approach structured around expert prerequisites, integrating
AI principles dedicated to Embedded Systems engineering track. Our module
focuses on creating an autonomous driving vehicle using an autonomous
robot kit, fostering interdisciplinary learning. Real-time demonstrations
assess learning outcomes, emphasizing problem-solving skills. Inspired
from recent evaluation concept of interdisciplinary assessment. Our
evaluation criteria emphasize functionality, integrated idea defense,
and written reports. The defense organization scheme fosters positive
perceptions of interdisciplinary links.
Geodata Processing Methodology on GIS Platforms When Creating Spatial Development Plans of Territorial Communities: Case of Ukraine
Kopishynska, Olena; Utkin, Yurii; Sliusar, Ihor; Flehantov, Leonid; Somych, Mykola; Yakovlieva, Oksana; Scryl, Olena (Ukraine)
https://doi.org/10.54808/IMCIC2024.01.251
ABSTRACT:
The article offers a detailed expert analysis on handling spatial information
of territorial communities amid administrative and land reforms. The
authors have developed multiple methodological recommendations and justified
the selection of efficient tools for contemporary GIS systems. It also
delves into the essence of GIS technologies, the nuances of working
with geodata, and provides a concise overview of the world's most prevalent
GIS platforms. The paper outlines an algorithm for developing a land
resource management strategy for communities in preparation for land
reform. Through the analysis and visualization of spatial data, the
paper highlights enhancements in economic valuation and the ability
to pinpoint risks and infringements of property rights.
The study selects the Cadastr.UA system on the Soft.Farm platform, developed
by Ukrainian company Quart Soft, as a notably user-friendly and promising
GIS for land accounting and auditing. Research based on the experimental
practical application of most functions of GIS Cadastr.UA indicates
that this system aligns well with the needs for land plot accounting
and auditing within the framework of Ukraine's Public cadastral map.
The paper details the practical implementation of GIS technologies,
using Cadastr.UA as a case study, and illustrates how to employ selected
GIS tools in various scenarios and tasks.
How to Link Educational Purposes and Immersive Video Games Development? An Ontological Approach Proposal
Aky, Nathan (France)
https://doi.org/10.54808/IMCIC2024.01.208
ABSTRACT:
Video games offer a interesting approach for enhancing educational experiences
across various domains. Whether repurposing existing games, such as
Sim City for teaching budget management, or developing dedicated serious
games, they enrich the spectrum of educational resources available.
Nevertheless, creating immersive gaming and learning environments presents
challenges. The absence of consensus on comprehensive tools or models
poses an initial hurdle. Furthermore, designing such experiences entails
intricate considerations, including multidisciplinary collaboration
and the inherent complexity of open nature of learning experiences.
Our proposed ontology addresses these challenges by integrating concepts
from education, immersive game design, and virtual environments. This
integration facilitates the alignment of learning objectives with game-design
elements, leveraging the multi-agent systems paradigm for coherence.
Serving as a semantic hub, our ontology enhances communication among
interdisciplinary teams by employing clearly defined terms. Additionally,
it provides a robust conceptual framework to navigate the complexity
inherent in educational game development.
We assess the efficacy of our ontology by instantiating it with several
existing games or game engine. This instantiation validates its expressiveness
and completeness, while logical consistency is confirmed through inference
engine verification. Through these efforts, our ontology emerges as
a valuable tool for advancing the design and development of educational
video games.
How to Overcome the Challenges Faced to Enhance the Efficiency of Islamic Banking in the Asian Region
Mehmood, Khalid; Oganisjana, Karine; Lace, Natalja (Latvia)
https://doi.org/10.54808/IMCIC2024.01.200
ABSTRACT:
Islamic banking (IB) has emerged as an essential part of the global
banking network. Despite the rapid rise of Asian Islamic banking, previous
research has largely focused on Islamic banks in specific countries.
This study aims to fill the gap in the literature by proposing ways
to solve the issues faced by Islamic banks in the Asian region. In this
study, the methodology employed was qualitative content analysis. Researchers
collected qualitative data from scientific literature written by Muslim
and non-Muslim authors. This approach systematically analyses textual
content, integrating qualitative and quantitative aspects. The paper
covered various potential solutions for the betterment of Islamic banks,
introducing innovative products, standardizing Sharia governance, modernizing
financial policies and marketing strategies, and developing a strong
alliance with Conventional banks (CB) and other organizations, which
will enhance the effectiveness and growth of Islamic banks. In addition
to these solutions, the study acknowledges that other solutions also
develop the establishment and expansion of Islamic banking in the region.
Identifying and onboarding these solutions will help stakeholders and
policymakers in Islamic banking implement effective strategies and policies
to address today’s most pressing challenges and prepare for and prevent
the challenges of tomorrow.
Identifying the Features of Graduated Students of the Computer Science Degree of the National University of Asuncion
Roman Mancuello, Jesus Gabriel; Rios Alvarez, Luis Fernando; Paciello Coronel, Julio Manuel; Mendez Xavier, Ellen Lujan; Von Lucken Martinez, Christian Daniel (Paraguay)
https://doi.org/10.54808/IMCIC2024.01.89
ABSTRACT:
This study addresses identifying characteristics of graduated Computer
Science students in Paraguay. Using Data Mining (DM) and Educational
Data Mining (EDM) techniques, data from 1751 students was analyzed,
uncovering patterns and crucial factors that influence student success.
Attribute selection techniques, including ANOVA and Chi-Square Test
of Independence, were implemented, significantly reducing the dataset
and increasing the precision of the analysis. Machine learning algorithms
were employed within the H20 framework, focusing on supervised models.
The experiments showed that appropriate attribute selection notably
improves performance, achieving an F1 metric of up to 80% for predicting
student graduation. This work highlights the importance of analyzing
academic data to better understand the factors contributing to the success
of computer science students, proposing a model that can be a valuable
tool for decision-making in the educational field.
Information Literacy, Information Transparency and Information Accessibility – Distinctive Features of Cyber Security
Denchev, Stoyan; Peteva, Irena; Yordanova, Steliana (Bulgaria)
https://doi.org/10.54808/IMCIC2024.01.145
ABSTRACT:
The study analyzes the concept of security, and the distinctive characteristics
of this concept in particular, related to information literacy and to
the opportunities to access various information intended for public
use. Based on existing theories on security, perceived as a building
block and a logical state of society, a natural pattern is analyzed,
associated with the level of information literacy of specialists who
study security issues. This pattern occurs primarily in the depths of
the conclusions in the process of the category definition and redefinition
of the topics, related to the regulatory function of cyber security
in the process of building and developing a culture of information transparency.
Background and problem oriented conclusions.
The category of "security" has been researched as a universal category,
reflecting the essential aspects of existence of natural and social
systems, mainly related to the measure and the transition from one situation
to another of the respective tangible and intangible systems [5]. The
study is based on the main thesis that without the acquiring, availability,
development and practical use of respective levels of information literacy,
the so-called security professionals demean the category "security"
itself and turn it into a label and declarative concept, which gradually
passes on to the "dead zone" of scientific knowledge. The study pays
special attention to the regulating function of security. From this
position fusion between the desires and the possibilities for total
transparency is made, a transparency accomplished on the basis of high
level of information literacy, unrestricted access to public information
and the necessary regulatory activities of the state, ensuring the appropriate
degree of general and cyber security on a national, regional or international
level.
Results.
Analyzed problems give reason to sum up that acquiring knowledge and
skills in the field of security necessarily requires reaching maximum
levels of information literacy, which permanently transform into information
competency. As a result, basic and upgraded knowledge is synthesized.
Every specialist on security issues, depending on their professional
orientation, must possess this knowledge in order to be functionally
literate. Of course, this basic and upgraded knowledge, as conceptualization
of the functional literacy, should be differentiated depending on the
narrow experience and professional qualifications of specialists involved
in the process.
Integrating Generative AI in Active Learning Environments: Enhancing Metacognition and Technological Skills
ElSayary, Areej (United Arab Emirates)
https://doi.org/10.54808/IMCIC2024.01.135
ABSTRACT:
This paper explores the innovative integration of Generative AI (GenAI)
in active learning environments to augment metacognitive knowledge and
technological skill development among students. While active learning
has been pivotal in promoting student engagement and learning, the incorporation
of GenAI presents a novel approach to further enhance these outcomes.
The study investigates how GenAI tools can be utilized within a reflective
practice model to bolster metacognitive regulation and technological
proficiency. By discussing the synergistic relationship between GenAI,
active learning, and metacognitive strategies, this paper provides insights
into the evolving landscape of educational technology and its impact
on student learning processes. The paper offers a theoretical framework
based on established concepts in metacognition, active learning, reflective
practice, and technological skills, contextualized within the realm
of GenAI. This paper contributes to the understanding of how GenAI can
be harnessed as an educational tool, facilitating deeper and more effective
learning experiences.
Interdisciplinarity in Smart Systems Applied to Rural School Transport in Brazil
Baracho, Renata Maria Abrantes; Vidigal, Mozart Joaquim Magalhães; Porto, Marcelo Franco; Couto, Beatriz (Brazil)
https://doi.org/10.54808/IMCIC2024.01.222
ABSTRACT:
Interdisciplinarity applied to rural transport in Brazil through expert
systems is the focus of this paper. Rural school transport is a challenge,
considering the size of Brazil, the great diversity of biomes and insufficient
infrastructure. Collaboration between areas by interdisciplinarity articulates
individual knowledge through the object and by transdisciplinarity requires
developing new knowledge, based on an individual area, going beyond
and extrapolating with different criteria. The “Transcolar Rural” intelligent
transport system has been developed at the UFMG School of Engineering
to plan and manage rural school transport by optimizing routes and costs.
The system is used in 13 states in Brazil, 500 municipalities and manages
the daily transport of more than 400 thousand students in rural areas.
Reducing transportation costs allows resources to be reallocated to
other educational activities. The project highlights Brazil's limited
resources, recognized by the government, to meet the population's health,
education and transport priorities. Transparent information helps managers
make decisions and supervise citizens, allowing both parties to determine
priorities for resource allocation. The Project demonstrates how interdisciplinarity
is effective for complex problems. The project comprehensively addresses
the challenges of transporting children in Brazil by integrating technology,
exact sciences and applied social sciences.
Interdisciplinary Digital Skills Development for Educational Communication: Emergency and Ai-Enhanced Digitization
Makhachashvili, Rusudan; Semenist, Ivan; Prihodko, Ganna; Kolegaeva, Irina; Prykhodchenko, Olexandra; Tupakhina, Olena (Ukraine)
https://doi.org/10.54808/IMCIC2024.01.281
ABSTRACT:
The wartime emergency induced amplified digitalization measures in the
higher education sphere, informed by the need to take quick comprehensive
action in order to achieve the overarching result to transform educational
scenarios into interdisciplinary digital, blended, and hybrid frameworks.
Taking into account the context of the erupted military intervention
on Ukraine in February 2022, and the ensuing information warfare in
various digital environments (social media, news coverage, digital communications),
the specific value of the learning outcomes and outputs is allocated
to the digitally enhanced foreign languages education as a tool of the
internationally broadcast strife of Ukraine for freedom and sovereignty.
The study results disclose the comprehensive review of dynamics of the
metadigital skills development and application to construe interdisciplinary
competencies of students of European (English, Spanish, French, Italian,
German) and Asian (Mandarin Chinese, Japanese) Languages major programs
in Ukraine through the span of educational activities in the time-frame
of wartime emergency digitization measures of 2022-2023.
Iron Deficiency Anemia and Supplementation Practices with Polymaltosed Iron in Mothers with 4 - 5 Months Infants in a Rural Andean Health Center
Soto Carrión, Carolina; Cervantes Carrión, Justina; Ccasani Contreras, Mariluz Roxana; De La Cruz Quispe, Fidel; Bravo Mendoza, Guido; Jimenez Mendoza, Wilber (Peru)
https://doi.org/10.54808/IMCIC2024.01.123
ABSTRACT:
The Childhood anemia is a latent problem and according to the WHO more
than half of Children who suffer from anemia in the world suffer from
iron deficiency. Aim: Determine the relationship between the level of
knowledge of iron deficiency anemia and practices with polymaltose iron
supplementation in mothers with 4 – 5-month-old infants in an Andean
rural health center. Materials and Methods: Quantitative approach, type
cross-sectional correlational prospective, the hypothetical-deductive
method was applied Prospective, the population corresponds to 52 mothers
with their respective infants of 4 and 5 months. The survey technique
was applied and the questionnaire was used as an instrument for collection.
of data, validated through expert judgment, taking as a contrast the
hypothesis the Spearman's Rho statistical test. Results: More than 50%
of mothers present ages between 26-35 years and have completed secondary
school. 26.9% of mothers have a high level of knowledge and presented
risky practices; while 17.3% have a medium level of knowledge and presented
good practices; and 13.5% have a level low knowledge and presented risky
practices. Conclusion: The level of Knowledge of iron deficiency anemia
is not directly related to health care practices, supplementation with
polymaltose iron and whether it is related to the educational level
of nursing mothers of 4 and 5 months of the Andean Rural Health Center
the p-value (sig) for all tests was greater than 0.05.
Measurement of Biological Cell Deformability
Iinuma, Sota; Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.5
ABSTRACT:
Cell shape changes depending on the surrounding environment: mechanical
fields (gravitational and fluid forces), electric fields, magnetic fields,
electrochemical interactions at interfaces, etc. Deformation responses
to environmental stimuli represent cell properties and activities. Stimuli
that cause deformation include mechanical fields, electric fields, and
magnetic fields. By restricting cell movement in the flow path, cell
deformation can be observed: the shape of the channel wall, gaps, etc.
The deformability of a cell is related to its function. For example,
red blood cells that are insufficiently deformable cannot pass through
capillaries and continue to circulate in the blood circulation system.
Cancer cells are thought to have different deformability from normal
cells. Measuring the deformability of cells can be applied to disease
diagnosis and cell selection. This paper reviews research on measuring
the deformability of cells and provides an outlook for future research
developments.
Microchannel Design for Cell Sorting by Dielectrophoresis
Ono, Ryuya; Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.9
ABSTRACT:
Cell sorting is a useful technique that can be applied to disease diagnosis
and tissue formation technology. Dielectrophoresis has been attempted
to be applied to cell sorting as a label-free, microinvasive sorting
technique. This study aimed to create a device suitable for myoblast
cell sorting based on previous research results. Using photolithography
technology, microchannels with surface electrodes were designed and
fabricated.
Mobile Augmented Reality Application for Digital Storytelling in High School Education
Bustos, Henrry; Camogliano, Josealdo; Subauste, Daniel (Peru)
https://doi.org/10.54808/IMCIC2024.01.54
ABSTRACT:
Since the beginning of the pandemic, high education has been significantly
affected, due to the sudden change from in-person to remote mode, which
has led to not all teaching methods adapting to this new modality. In
this context, the storytelling technique, which in face-to-face mode
is effective, in the remote mode presents significant deficiencies since
it cannot be interacted with in a shared space and with objects between
students and the teacher. In this situation, some applications are poorly
adapted for high education to solve this lack, which leads us in this
work to present the development of a mobile application as a complement
to the teaching of high education with storytelling using augmented
reality, which leads to improving how to tell stories between students
and teachers in remote teaching using digital storytelling, supported
with augmented reality, a more participatory and interactive way of
telling stories.
Navigating the Missteps: An In-Depth Critique of Albania's Sex Offender Registry
Leka, Adrian; Haxhiu, Brunilda (Albania)
https://doi.org/10.54808/IMCIC2024.01.267
ABSTRACT:
This article critically examines the legislative journey and implications
of Albania's Sex Offender Registry Law 62/2023, shedding light on the
disconnection between scientific research and public policy formulation.
Tracing the historical origins of sex offender registries and contrasting
various international models, the study underscores the lack of alignment
between the approved law and established research findings. The article
highlights the overestimation and misrepresentation of statistical data,
the shortcomings in the legislative process, and the absence of a transparent,
evidence-based approach. The law's failure to materialize the intended
registry within the stipulated timeframe and the inherent limitations
of the approved model further emphasize the challenges in creating effective
legislation. The findings not only critique the flaws in Law 62/2023
but also reflect broader concerns about utilizing scientific research
in shaping legal frameworks, underscoring the need for a more informed
and evidence-driven approach to policymaking.
New Online Tools for the Data Visualization of Bivalve Molluscs' Production Areas of Veneto Region
Franzago, Eleonora; Casarotto, Claudia; Trolese, Matteo; Toson, Marica; Ruzza, Mirko; Dalla Pozza, Manuela; Manca, Grazia; Arcangeli, Giuseppe; Ferrè, Nicola; Bille, Laura (Italy)
https://doi.org/10.54808/IMCIC2024.01.240
ABSTRACT:
The current European Food Hygiene Legislation makes the control and
monitoring of all bivalve molluscs (BM) classified production areas
mandatory in order to ensure the compliance of the product. Whenever
the results of the controls highlight non-compliance, the Local Veterinary
Competent Authority (LVCA) issues a measure to limit or suspend harvesting
activities in the involved production area. Therefore, it is essential
for LVCA accessing to updated information in near real time on sanitary
status, laboratory test results and spatial distribution of production
areas. In the framework of a project financed by the European Maritime
and Fisheries Fund (n. 04/INP/20/VE), three Information Technology (IT)
tools have been developed to aid the LVCA in their daily control activities.
The developed IT tools also indirectly help to ensure a safe product
for the end consumer, because they support food safety control activities.
Moreover, the open access to information regarding these systematic
controls will enhance the consumers’ trust in the local product increasing
its value on the market.
Paraguayan Sign Language Translation Using Machine Learning
Gutierrez, Bethania; Alfonzo, Ever; Paciello, Julio; von Lucken, Christian (Paraguay)
https://doi.org/10.54808/IMCIC2024.01.157
ABSTRACT:
The Paraguayan deaf community often faces daily challenges in interacting
with teachers and people who do not understand the Paraguayan Sign language,
obstructing their access to standard communication. Paraguay requires
more resources to promote the learning and teaching of Paraguayan Sign
Language.
By applying machine learning techniques to preprocess Paraguayan Sign
Language signs videos, we can create a dataset that serves as a foundation
for various applications. These tools can help disseminate knowledge,
bridge communication gaps, and enable deaf individuals to communicate
effectively, even with those who do not understand Sign Language. Additionally,
they can assist in educating the public about this language.
Peculiarities of the Realization of IT Projects for the Implementation of ERP Systems on the Path of Digitalization of Territorial Communities Activities
Kopishynska, Olena; Utkin, Yurii; Sliusar, Ihor; Makhmudov, Khanlar; Kalashnyk, Olena; Moroz, Svitlana; Kyrychenko, Olena (Ukraine)
https://doi.org/10.54808/IMCIC2024.01.259
ABSTRACT:
This study presents a detailed case analysis focusing on the intricacies
involved in preparing a project for implementing an Enterprise Resource
Planning (ERP) system, aimed at the comprehensive, phased digitalization
of resource management and the operations of territorial communities.
The urgency of transitioning to a more effective audit and management
system for all types of resources in territorial communities is underscored
by the current absence of specialized information systems designed for
these specific tasks. The authors demonstrate that deploying ERP systems
to manage the diverse activities of territorial communities represents
a complex, yet innovative solution. Specifically, a Four-Phase Model
for implementing each segment of the project have been adopted. Drawing
from the extensive experience of university researchers involved in
consulting for numerous territorial communities across Ukraine, this
work develops principles for constructing main elements for the project.
Special emphasis is placed on the careful selection of software to facilitate
project activities.
Quantifying the Risk of Complaints in Public Procurement Tenders in Paraguay Using Machine Learning
López San Martín, Matías; Núñez Benitez, David Ramon; Paciello Coronel, Julio Manuel; Pane Fernandez, Juan Ignacio (Paraguay)
https://doi.org/10.54808/IMCIC2024.01.164
ABSTRACT:
Public procurement processes are critical for effective governance,
and they are susceptible to protests, causing delays and possibly added
costs. This study aims to assess the risk of protests in paraguayan
public procurement tenders using artificial intelligence. The research
leveraged machine learning techniques, including a classifier, to analyze
historical data from the Public Procurements Office of Paraguay (DNCP
for its initials in Spanish) available in the open format of the Open
Contracting Data Standard (OCDS). Pre-calculated red flags were incorporated
into the model as an indicator of potential irregularities. A structured
and unified dataset was generated, laying the foundation for future
investigations. The model exhibited promising predictive capabilities
identifying the procurement tenders at high risk of protests. This work
represents a significant step towards proactive protest risk management
in public procurement. The combination of complaint-derived data, machine
learning, and the structured dataset enhances the potential for technology-driven
transparency and efficiency in public procurement processes.
Serverless Approach in Continued Integration Testing
Djambazoff, Phil (Bulgaria)
https://doi.org/10.54808/IMCIC2024.01.61
ABSTRACT:
This article describes an efficient approach of continuous integration
(CI) [1] automated testing in both, labor-intensive, and financial aspects.
The current methodology of running integration tests in the cloud is
by keeping at least several servers running all the time, and probably
another few for backup purposes. That commonly used approach creates
a financial burden in the short and long term, and it is also quite
labor involved when it comes to setup and maintainability. Our proposal
is based on a serverless runtime setup [2], which on one hand eliminates
the need to have 24/7 servers running, and a heavy backup plan preparation,
and on the other gets the labor contribution decreased in times - due
to the usage of preconfigured docker [3] images or other similar container-based
image software components.
Start-up Support Efficiency Assessment
Bistrova, Julija; Lace, Natalja; Kasperovica, Ludmila (Latvia)
https://doi.org/10.54808/IMCIC2024.01.185
ABSTRACT:
Globally, start-up companies receive state support, which is considered
to be an investment in future economic growth and regional development.
Extensive research consistently demonstrates the efficiency of state
aid for newly-established firms. This study adds to the empirical evidence,
highlighting the significance and effectiveness of start-up support.
An analysis of 112 Latvian supported companies reveals that over half
experienced notable improvements in profitability and productivity,
often outperforming industry peers at an accelerated rate. The study's
findings indicate the importance of the monetary grant’s size: the higher
it is, the better productivity and asset profitability results the company
achieves after three years of receiving support. These findings emphasize
the importance of tailored financial assistance, linking larger grants
to enhanced performance metrics. Based on evaluation results and a thorough
analysis of scientific literature, the authors present practical recommendations
for optimizing the performance indicators of business incubators, providing
valuable guidance for policymakers and stakeholders committed to fostering
sustainable economic development.
The Influence of Needs Satisfaction and Support on the Well-Being of Physicians Deployed in Underserved Communities
Bautista, Karl Hendrick; Capillo, Jianna; Lopez, Mari Jazmin Ezekielle; Santos, Edgardo Javier; Severino, Ivan Matthew; Sio, Chloe Angela Mae; Tanchanco, Samantha Marie; Adarlo, Genejane; Eustaquio, Michelle Pia (Philippines)
https://doi.org/10.54808/IMCIC2024.01.108
ABSTRACT:
This study investigated the influence of needs satisfaction and support
on the well-being of physicians deployed in underserved communities.
Basic Psychological Needs Theory is used as the theoretical framework,
positing that fulfilling the three basic psychological needs of autonomy,
competence, and relatedness can foster well-being and optimal functioning.
The results revealed that meeting basic psychological needs alongside
workplace conditions and individual characteristics can play distinct
roles in promoting emotional, psychological, and social well-being as
well as reducing the likelihood of anxiety and depression. This study
suggests that promoting the well-being of human resources for health,
particularly among physicians deployed in underserved communities, is
crucial for achieving the Sustainable Development Goal for good health
and well-being. By recognizing and addressing the diverse factors that
contribute to the well-being of these physicians, healthcare organizations
and policymakers can create environments that support their optimal
functioning and, consequently, contribute to the overall improvement
of health outcomes in underserved communities.
The Model on Patent Investment Strategy of Technology Portfolio and Industrial Research
Lee, Yen-Feng; Wang, Wei-Tsong (Taiwan)
https://doi.org/10.54808/IMCIC2024.01.159
ABSTRACT:
The concept of portfolio theory is widely applied in financial investment,
which would like to search the most valuable result or the lowest risk.
In the recent years, some scholars suggest the portfolio theory within
technology investment into Technology Portfolio. This article examines
the impact of different portfolio strategies with Modified Sharpe Index
to examine the values of internal/external technologies investment of
companies. Moreover, we surveyed and arranged those research models
from journal papers involved technology portfolio to illustrate the
paths that technology portfolio theories developed.
Innovative approach of valuing intellectual property is proposed to
estimate how technology portfolios may influence product values. Accordingly,
technology portfolio strategies of companies can be utilized to identify
the standards of product pricing, as well as to improve its sales volume
or numbers with appropriate promotion. In this study, the technology
portfolio is evaluated by suggested Modified-Sharpe-Index (MSI) function.
Portfolio theory in financial is adopted with the concepts of technology
development, which also combines the value of tangible and intangible
assets along with risk and strategic factors, to evaluate the performance
of a technology portfolio. The simulated experimental results may explain
technology adoption and diffusion of management and strategies of companies
in different industries.
Transfer Learning for Facial Emotion Recognition on Small Datasets
Barile, Paolo; Bassano, Clara; Piciocchi, Paolo (Italy)
https://doi.org/10.54808/IMCIC2024.01.230
ABSTRACT:
In the context of human interactions, complexity science (CS) provides
a way to understand the dynamics that arise from the interplay of different
individuals. Recently, the possibility of applying the theory of CS
to computer science, has shifted the focus to the research of machine
learning methods for studying human behaviors and relational dynamics.
Among the various existing AI techniques, facial emotion recognition
(FER) has proven to be the best-performing and easiest to use human-
computer interaction (HCI) tool for emotion detection. Despite the numerous
existing approaches, the task of FER is not trivial, mainly due to the
absence of large enough datasets to train deep learning (DL) models.
A widely used solution is transfer learning (TL), which allows a model,
pre-trained on enough data, to be used for a specific task where there
is much less data available. The aim of our work is to test the effectiveness
of TL for FER on an extremely small dataset, to understand which parameters
need to be optimised to obtain the best outcomes. The results showed
an overall accuracy of 85.54% for our model and revealed the concrete
possibility of applying computer science to complex systems typical
of the human psyche.
Transformative, Transdisciplinary, Transcendent Digital Education: Synergy, Sustainability and Calamity
Makhachashvili, Rusudan; Semenist, Ivan (Ukraine)
https://doi.org/10.54808/IMCIC2024.01.273
ABSTRACT:
Dynamic transformation of the knowledge economy, enhanced by Industry
4.0/5.0 development and rise of the networked society in the Digital
Age, emergency digitization of all social communicative spheres due
to pandemic measures have imposed dramatic changes onto transdisciplinary
overlap in different areas of human knowledge and experience, induced
by the cross-sectorial job market demands of university level education,
curriculum design and learning outcomes.
The global pandemic and subsequent warfare in Ukraine induced amplified
digitalization measures in the higher education sphere. This end-to
end digital shift in the educational processes (communication, content,
outcomes and outputs, skills) heralded the introduction of meta-disciplinary
dimensions of learning – digital, hybrid and, blended. These meta-disciplinary
dimensions can be considered conduits of vertical (endocentric) and
horizontal (exocentric) transdisciplinary of digital education as a
sustainable dynamic system.
Applied trans-disciplinary lens contributes to the solution of holistic
modeling of processes and results of updating models and mechanisms
of the highly dynamic communication system of education in the digital
environment as a whole and its individual formats in the emergency digitization
measures of different types.
Use of Xception Architecture for the Classification of Skin Lesions
Tejada, Cledmir; Espinoza, Gustavo; Subauste, Daniel (Peru)
https://doi.org/10.54808/IMCIC2024.01.129
ABSTRACT:
This study investigates the application of the Xception architecture
for accurate classification of skin lesions, focusing on the early detection
of melanoma and other malignant skin conditions. Utilizing deep learning
techniques, the research aims to enhance the precision and efficiency
of skin lesions diagnosis. The study utilizes the TensorFlow framework
and the HAM10000 dataset, comprising a vast collection of benign and
malignant skin lesion images, for training and evaluating the Xception
model. Preprocessing steps, including data splitting, augmentation,
and image resizing, are applied to the dataset. The Xception architecture,
a deep convolutional neural network, serves as the foundational model,
supplemented with customized classification layers for specialized features
and predictions. The model’s performance is evaluated using diverse
metrics. The experimental outcomes reveal the Xception architecture’s
potential in accurately classifying skin lesions. Moreover, the study
underscores the significance of extensive and diverse datasets, as well
as rigorous clinical validation, in the development of deep learning
models for skin cancer detection. The findings contribute to the advancement
of early melanoma detection, thereby improving patient outcomes and
alleviating the burden of the disease.
Utilization of Artificial Intelligence by Students in Interdisciplinary Field of Biomedical Engineering (Invited Paper)
Hashimoto, Shigehiro (Japan)
https://doi.org/10.54808/IMCIC2024.01.302
ABSTRACT:
Students were encouraged to actively use artificial intelligence (AI) in learning and research in the field of biomedical engineering. In this study, student reports in class and the results of student research projects were analyzed. An issue with AI that was often discussed among students was the handling of copyright. In students' graduation research, AI was often used to search for technical terms and references. AI was used to list related technologies and check the feasibility of their ideas. AI was effective for self-learning. Particularly in interdisciplinary fields that require extensive basic knowledge, AI has demonstrated its power in self-learning specialized terminology. It was found that AI can be helpful for students in developing research topics and writing papers.
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