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Bundan tashqari Multisim simulyatori – bu ishlab chiqaruvchilar tomonidan
tekshirilgan 55 000 dan ortiq bo‘lgan qurilmalarni modellashtirish uchun mo‘ljallangan
kompleks muhit bo‘lib, pechatli platalarni kompanovka qilish imkonini yaratadi.
Multisim dasturi dastlab Electronics Workbench firmasi tomonidan ishlab
chiqilgan bo‘lib, dastur juda oddiy grafik interfeysdan iborat edi.
Hozirgi kunda Electronics Workbench National Instruments Corporation firmasi
tarkibiga kiradi va bu firma ushbu dasturni mukammalashtirilgan variantlarini taklif
etadi.
Multisim dasturining asosiy xususiyati shundaki, o‘lchash asboblarining
analogini immitatsiya qiluvchi virtual o‘lchash asboblarini mavjudligidadir.
Multisim 14.0, Ultiboard 14.0 hozirgi kunda keng foydalaniladigan va SPICE-
modellashtirishda elektr sxemalarini tahlil etish, pechat platalarini loyihalash testlash
imkonini beradigan dasturlash versiyalari hisoblanadi.
Hulosa qilib shuni aytish mumkinki, axborot muhiti sharoitida amaliy
mashg‘ulotlarni bajarishda elektron dasturlarni keng qo‘llanilishi kursantlarda
AKTdan foydalanish kompetentligini shakllantirishga, pedagog va kursant o‘rtasidagi
hamkorlik tamoyili o‘qitishning didaktik maqsadlari (axborot ta’limiy– kompyuter
savodxonligi, elektron dasturlarni o‘rganish; rivojlantiruvchi - elektron dasturlardan
foydalana olish, natijalarni olish va ularni qayta ishlash) ni samarali amalga oshishida
hizmat qiladi.
Foydalanilgan adabiyotlar ro‘yxati:
1. Sh. Mirziyoyevning O‘zbekiston Respublikasi Qurolli Kuchlari tashkil
etilganligining 30 yilligi munosabati bilan yo‘llagan bayram tabrigi.
2. Пазилова Ш.А. Методы преподавания электротехники и электроники в
академии вооруженных сил республики Узбекистан// Вестник науки и
образования.– Москва , 2019. - № 15(69).– С.75-77.
3. A.A.Tulyaganov., S.S.Parsiev., V.A.Tulyaganova., U.M.Abdullayev. Elektr
zanjirlar nazariyasi. O‘quv qo‘llanma. –T.: Aloqachi, 2018. –144 bet.
DEFINITION OF TECHNIQUES FOR EMOTIONAL STATE ASSESSMENT
Kurbanov Abdurahmon Alishboyevich
Jizzakh branch of National University of Uzbekistan
Annotation:
This article aims to provide algorithmic insights into the evaluation
of human emotions, highlighting the progress that has been made and the challenges
that still exist. By utilizing machine learning algorithms and sentiment analysis,
researchers have been able to uncover valuable information about the emotions that
robots can express and how they impact consumers. This cross-disciplinary study paves
the way for next-level social, design, and creative experiences in artificial intelligence
research, particularly in the realms of consumer service and experience contexts.
Key words:
Emotional Contagion, Machine Learning Algorithms, Sentiment
Analysis, Facial Recognition, computer science, design.
11
In recent years, there have been significant advancements in technology that
have allowed robots to display emotions. This has opened up new possibilities for
human-robot interaction, particularly in the field of service. However, understanding
and evaluating emotions in this context remains relatively underexplored. Emotions
play a crucial role in shaping human experiences, and their impact on consumer
behavior cannot be underestimated. Therefore, it is important to delve deeper into how
emotional robots influence potential consumers' affective feelings.
The Power of Emotional Contagion in Human-Robot Interaction
Emotional contagion is a phenomenon wherein emotions can be transmitted
from one individual to another. It is a powerful mechanism that influences human
behavior and interactions. In the context of human-robot interaction, emotional
contagion plays a crucial role in shaping the affective experiences of potential
consumers. To understand this phenomenon, researchers turned to Instagram data,
utilizing machine learning algorithms and sentiment analysis techniques.
The findings of this study revealed that certain emotions expressed by robots,
such as surprise and happiness, have a significant impact on potential consumers. These
emotions create positive affective feelings and can influence consumer decision-
making processes. By understanding the power of emotional contagion in human-robot
interaction, researchers can design robots that elicit positive emotions and enhance the
overall consumer experience.
Machine Learning Algorithms and Sentiment Analysis in Evaluating
Emotions
Machine learning algorithms have played a vital role in evaluating and analyzing
emotions in human-robot interaction. These algorithms, when combined with
sentiment analysis techniques, can uncover valuable insights into the emotional impact
of robots on potential consumers. By training these algorithms on large datasets,
researchers can develop models that accurately classify and evaluate emotions
expressed by robots.
Sentiment analysis, in particular, allows researchers to analyze the sentiment and
emotional tone of text data. By applying sentiment analysis to Instagram data,
researchers have been able to identify the emotions that are most influential in human-
robot interaction. The combination of machine learning algorithms and sentiment
analysis has proven to be a powerful tool in understanding and evaluating emotions in
this context.
The Role of Facial Recognition in Emotion Evaluation
Facial recognition technology has been instrumental in evaluating emotions in
human-robot interaction. By analyzing facial expressions, researchers can gain
valuable insights into the emotions expressed by both humans and robots. Facial
recognition algorithms can accurately detect and classify emotions, allowing for a more
comprehensive understanding of emotional responses.
In the context of human-robot interaction, facial recognition technology can be
used to evaluate the emotional impact of robots on potential consumers. By analyzing
the facial expressions of consumers during interaction with robots, researchers can
assess the effectiveness of emotional expression in creating positive affective
12
experiences. This information can then be used to optimize the design and functionality
of robots to elicit desired emotional responses.
Challenges and Limitations in Evaluating Human Emotions
While significant progress has been made in evaluating human emotions in the
context of human-robot interaction, there are still challenges and limitations that need
to be addressed. One of the primary challenges is the complex and multifaceted nature
of human emotions. Emotions are subjective experiences influenced by various factors,
making it difficult to develop a comprehensive evaluation framework.
Another challenge is the lack of standardized methodologies for evaluating
emotions in human-robot interaction. There is a need for standardized protocols and
measures that can be used across different studies to ensure consistency and
comparability of results. Additionally, the ethical implications of emotional
manipulation by robots need to be carefully considered and addressed.
Future Directions in Evaluating Human Emotions
The field of evaluating human emotions in human-robot interaction is still
evolving, and there are exciting opportunities for future research. One direction is the
development of more sophisticated machine learning algorithms that can accurately
classify and evaluate complex emotional responses. This would enable researchers to
gain a deeper understanding of the nuances and subtleties of human emotions.
Another direction is the integration of multimodal data sources in emotion
evaluation. By combining facial expressions, physiological responses, and textual data,
researchers can obtain a more comprehensive picture of emotional experiences. This
would allow for a more holistic evaluation of emotions in human-robot interaction.
Additionally, there is a need for interdisciplinary collaboration in this field. The
integration of expertise from psychology, computer science, design, and other
disciplines can lead to a more comprehensive understanding of emotions and their
evaluation in human-robot interaction. Collaborative efforts can also help address the
challenges and limitations mentioned earlier.
Conclusion
The evaluation of human emotions in the context of human-robot interaction is
a complex and challenging task. However, through the use of machine learning
algorithms, sentiment analysis, and facial recognition technology, researchers have
made significant progress in understanding the impact of emotional expression by
robots on potential consumers. By uncovering the emotions that have the most
significant influence and developing a deeper understanding of emotional contagion,
researchers can design robots that create positive affective experiences.
While there are challenges and limitations that need to be addressed, the future
of evaluating human emotions in human-robot interaction is promising. With
advancements in machine learning algorithms, the integration of multimodal data
sources, and interdisciplinary collaboration, researchers can continue to make strides
in this field. Ultimately, this research has the potential to enhance consumer service
and experience contexts and shape the future of human-robot interaction.
13
References:
1.
KURBANOV A.A. Multimodal emotion recognition: a comprehensive
survey with deep learning. Journal of Research and Innovation, pp. 43-47. 2023
2.
Kurbanov Abdurahmon Alishboyevich. A Methodological Approach to
Understanding Emotional States Using Textual Data. Journal of Universal Science
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Kurbanov Abdurahmon. AI MODELS OF AFFECTIVE COMPUTING.
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Abdurahmon
Alishboyevich.
USING
AFFECTIVE
COMPUTING SYSTEMS IN MODERN EDUCATION. Journal Science and
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Atzeni, Recupero, 2020 M. Atzeni, D.R. Recupero Multi-domain sentiment
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“KOMPYUTER ARXITEKTURASI” FANIDAN MOBIL ILOVA
AXBOROT TIZIMINI ISHLAB CHIQISH
Xusanov K.X., Axrorov M.A., Toshboyev J.S.
Toshkent axborot texnologiyalari universiteti Samarqand filiali
Annotatsiya:
Keyingi yillarda muayyan fanni mustaqil o’zlashtirish uchun
tayyorlangan elektron darslik yoki elektron qo’llanmalar tarkibida mustaqil
o’rganuvchilarning shu fanga oid bilimlarini sinab ko’rishga oid interfaol uslubda
ishlaydigan test dasturlarini yaratish zaruriy ehtiyojga aylandi. Bu borada faoliyat
ko’rsatuvchilar mazkur ishda qisman foydalanishlari mumkin. Bundan tashqari,
o’quvchilar mustaqil ravishda o’z ustida ishlari uchun ham ularga tayanch bo’la
oladigan, ular uchun metodik adabiyotlar xoh qog’ozda bo’lsin, xoh elektron
ko’rinishda bo’lsin, imkon qadar ko’proq bo’lgani maqsadga muvofiqdir.
