IRJET Journal
International Research Journal of Engineering and Technology (IRJET) is an peer reviewed, open access, Multidisciplinary journal in English for the enhancement of research in various discipline of Engineering, Science and Technology. Prime Focus of the Journal is to publish articles related to the current trends of research . IRJET brings together Scientists, Academician, Engineers, Scholars and Students of Engineering Science and Technology.Published by Fast Track Publications.
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consumed cereal grain in Asian countries, while also enjoying
global accessibility. Within the rice market, the overarching
determinant of milled rice lies in its quality, an attribute that
assumes heightened significance in the context of import and
export trade. Rice samples often harbor assorted extraneous
elements such as paddy, chaff, damaged grains, weed seeds,
and stones. The principal objective of the proposed approach is
to introduce an alternative avenue for quality control and
analysis, characterized by reduced expenditure in terms of
effort, cost, and time. Image processing emerges as a pivotal
and technologically advanced sphere marked by significant
advancements. Image processing maneuvers images to execute
targeted operations, thereby refining and enhancing the
desired outcome. Moreover, this technique enables the
extraction of valuable insights from input images. This study
strives to develop image processing algorithms with a specific
focus on segmenting and identifying rice grains. By harnessing
image processing algorithms, it becomes possible to efficiently
analyze the quality of grains based on their size. This paper
furnishes a solution for the classification and assessment of
rice grains, predicated on their dimensions and morphology,
through the application of image processing techniques. While
prior research has focused on the morphological attributes of
grains, encompassing parameters such as area and shape,
these endeavors often struggle to yield a generalized formula
capable of classifying diverse rice varieties due to the
considerable variance in shapes and sizes. In a distinctive
departure, this paper augments the analysis by incorporating
Fourier features extracted from grain images, thus
augmenting the accuracy of classification outcomes
devices and applications is on the rise, resulting in an increase
in both the quantity and complexity of malicious attacks. It is
imperative to establish robust security measures for IoT
networks to counteract malicious attacks, particularly with
the aim of preventing unauthorized control over these devices.
While numerous security solutions for IoT have been proposed
in recent years, a significant portion of them lacks
standardization and interoperability. As the IoT landscape
continues to expand, the diversity and intricacy of IoT
applications also grow, rendering such networks susceptible to
attacks aimed at data theft, device takeover, and service
disruption.
A multitude of protocols and networking frameworks have
been developed for IoT, with some achieving standardization
and facilitating interoperability among devices and internet
connectivity. These protocols have received endorsement from
prominent standardization bodies such as IETF, IEEE, and
industry consortia like the Rawan coalition and thread group.
This paper's objective is to present a model that establishes
secure communication channels among IoT devices as well as
between these devices and a server or router, accomplished
through the implementation of encryption algorithms. The
popularity of smart home IoT systems is increasing due to
their efficiency in simplifying various tasks. However, this
trend also introduces vulnerabilities in terms of user privacy.
Safeguarding the privacy of personal data remains a
paramount concern for electronic services. To address this
challenge, we employ well-established encryption algorithms
such as RSA to create and utilize secure communication
channels through Socket Programming for IoT devices.
of the intersection between Semiotics and Artificial
Intelligence (AI) within digital advertising. Three critical
objectives guide this research: 1) Analyzing the nuanced role
of visual and linguistic semiotics in advertising to discern how
personalized content is created through signs and symbols; 2)
Investigating real-world applications by dissecting existing
advertising campaigns where AI technologies have utilized
semiotics to enhance personalization and targeting, including
the provision of semiotics theories used wherever possible; 3)
Assessing the cutting-edge AI techniques that interpret and
employ semiotics, such as machine learning, computer vision,
and Large Language Models (LLMs), to accentuate their
contribution to mass personalization. The study also delves
into fascinating examples, highlighting innovative practices
employed by brands to connect with audiences. As digital
advertising stands at an intriguing crossroads, the
intertwining of semiotics and AI offers an unexplored path
with far-reaching implications. The insights and findings
presented in this paper serve as a beckoning call to scholars,
advertisers, and technologists to venture into this uncharted
territory. The full exploration holds the promise of unlocking
unseen potentials and transforming the very fabric of
advertising in the digital age. For those eager to understand
the future landscape of personalized advertising through the
lens of semiotics and AI, this paper offers a thrilling and
illuminating journey.
stability to the human body. These joints will be replaced by
the implants during hip replacement procedures due to
wear and strain brought on by ageing and other factors. Hip
joint prostheses are structural parts that still struggle with
complex issues including the interaction of the hip stem's
physical and biological characteristics with the human
femur bone. On the commercial market, there are numerous
varieties of artificial hip joints. The needs of the patients can
be accommodated by choosing from a variety of materials
and designs. One of them is the hip stem design with
fenestrations. Titanium and stainless steel are the materials
that are frequently utilised in hip joint replacement. The
design and analysis of complete joint replacements and
other orthopaedic devices have benefited from the use of the
finite element approach in orthopaedic biomechanics.
In this work, three different types of hip stems were
considered viz., hip stem with out fenestration, hip stem with
bigloop fenestration and hip stem with slot fenestration
were modeled using SOLIDWORKS 2018 by Dassault
Systems and these hip stems were analyzed for the stress–
strain distribution and deformation over the hip stem
prosthesis under different loading conditions like, standing,
walking, jumping and running for this we used two different
materials Polyether-ether-ketone (PEEK) and Ti-6Al-4V
using renowned tool ANSYS Workbench 2022 R2 version to
produce the hip stem with the best design and material
available.
efforts by providing insights into population dynamics,
habitat utilization and species behavior. This research
paper aims to explore the application of the YOLO (You
Only Look Once) algorithm a cutting-edge object
detection framework, in wildlife monitoring and
conservation. The primary focus of this study is to
evaluate the effectiveness of the YOLO algorithm in
identifying and tracking wildlife species, analyzing their
behavior, and supporting conservation efforts. By
utilizing CCTV cameras placed in wildlife habitats the
YOLO algorithm enables real-time detection, tracking, and
classification of wildlife objects thereby providing
researchers and conservationists with data. To conduct
this research we employed a methodology that involved
training the YOLO model using wildlife datasets[7]. This
training enabled the model to recognize and classify
species accurately. Furthermore, we optimized the
model’s performance before deploying it on CCTV camera
feeds allowing for the monitoring of wildlife populations.
The YOLO algorithms' efficient video frame processing
capabilities ensure real-time object detection enabling
access to insights about species presence, behavior
patterns, and potential threats. The utilization of the
YOLO algorithm has proven beneficial as it enables real-
time identification of elusive species. This technological
advancement plays a role, in providing information, for
conservation efforts surrounding these species.
consumed cereal grain in Asian countries, while also enjoying
global accessibility. Within the rice market, the overarching
determinant of milled rice lies in its quality, an attribute that
assumes heightened significance in the context of import and
export trade. Rice samples often harbor assorted extraneous
elements such as paddy, chaff, damaged grains, weed seeds,
and stones. The principal objective of the proposed approach is
to introduce an alternative avenue for quality control and
analysis, characterized by reduced expenditure in terms of
effort, cost, and time. Image processing emerges as a pivotal
and technologically advanced sphere marked by significant
advancements. Image processing maneuvers images to execute
targeted operations, thereby refining and enhancing the
desired outcome. Moreover, this technique enables the
extraction of valuable insights from input images. This study
strives to develop image processing algorithms with a specific
focus on segmenting and identifying rice grains. By harnessing
image processing algorithms, it becomes possible to efficiently
analyze the quality of grains based on their size. This paper
furnishes a solution for the classification and assessment of
rice grains, predicated on their dimensions and morphology,
through the application of image processing techniques. While
prior research has focused on the morphological attributes of
grains, encompassing parameters such as area and shape,
these endeavors often struggle to yield a generalized formula
capable of classifying diverse rice varieties due to the
considerable variance in shapes and sizes. In a distinctive
departure, this paper augments the analysis by incorporating
Fourier features extracted from grain images, thus
augmenting the accuracy of classification outcomes
devices and applications is on the rise, resulting in an increase
in both the quantity and complexity of malicious attacks. It is
imperative to establish robust security measures for IoT
networks to counteract malicious attacks, particularly with
the aim of preventing unauthorized control over these devices.
While numerous security solutions for IoT have been proposed
in recent years, a significant portion of them lacks
standardization and interoperability. As the IoT landscape
continues to expand, the diversity and intricacy of IoT
applications also grow, rendering such networks susceptible to
attacks aimed at data theft, device takeover, and service
disruption.
A multitude of protocols and networking frameworks have
been developed for IoT, with some achieving standardization
and facilitating interoperability among devices and internet
connectivity. These protocols have received endorsement from
prominent standardization bodies such as IETF, IEEE, and
industry consortia like the Rawan coalition and thread group.
This paper's objective is to present a model that establishes
secure communication channels among IoT devices as well as
between these devices and a server or router, accomplished
through the implementation of encryption algorithms. The
popularity of smart home IoT systems is increasing due to
their efficiency in simplifying various tasks. However, this
trend also introduces vulnerabilities in terms of user privacy.
Safeguarding the privacy of personal data remains a
paramount concern for electronic services. To address this
challenge, we employ well-established encryption algorithms
such as RSA to create and utilize secure communication
channels through Socket Programming for IoT devices.
of the intersection between Semiotics and Artificial
Intelligence (AI) within digital advertising. Three critical
objectives guide this research: 1) Analyzing the nuanced role
of visual and linguistic semiotics in advertising to discern how
personalized content is created through signs and symbols; 2)
Investigating real-world applications by dissecting existing
advertising campaigns where AI technologies have utilized
semiotics to enhance personalization and targeting, including
the provision of semiotics theories used wherever possible; 3)
Assessing the cutting-edge AI techniques that interpret and
employ semiotics, such as machine learning, computer vision,
and Large Language Models (LLMs), to accentuate their
contribution to mass personalization. The study also delves
into fascinating examples, highlighting innovative practices
employed by brands to connect with audiences. As digital
advertising stands at an intriguing crossroads, the
intertwining of semiotics and AI offers an unexplored path
with far-reaching implications. The insights and findings
presented in this paper serve as a beckoning call to scholars,
advertisers, and technologists to venture into this uncharted
territory. The full exploration holds the promise of unlocking
unseen potentials and transforming the very fabric of
advertising in the digital age. For those eager to understand
the future landscape of personalized advertising through the
lens of semiotics and AI, this paper offers a thrilling and
illuminating journey.
stability to the human body. These joints will be replaced by
the implants during hip replacement procedures due to
wear and strain brought on by ageing and other factors. Hip
joint prostheses are structural parts that still struggle with
complex issues including the interaction of the hip stem's
physical and biological characteristics with the human
femur bone. On the commercial market, there are numerous
varieties of artificial hip joints. The needs of the patients can
be accommodated by choosing from a variety of materials
and designs. One of them is the hip stem design with
fenestrations. Titanium and stainless steel are the materials
that are frequently utilised in hip joint replacement. The
design and analysis of complete joint replacements and
other orthopaedic devices have benefited from the use of the
finite element approach in orthopaedic biomechanics.
In this work, three different types of hip stems were
considered viz., hip stem with out fenestration, hip stem with
bigloop fenestration and hip stem with slot fenestration
were modeled using SOLIDWORKS 2018 by Dassault
Systems and these hip stems were analyzed for the stress–
strain distribution and deformation over the hip stem
prosthesis under different loading conditions like, standing,
walking, jumping and running for this we used two different
materials Polyether-ether-ketone (PEEK) and Ti-6Al-4V
using renowned tool ANSYS Workbench 2022 R2 version to
produce the hip stem with the best design and material
available.
efforts by providing insights into population dynamics,
habitat utilization and species behavior. This research
paper aims to explore the application of the YOLO (You
Only Look Once) algorithm a cutting-edge object
detection framework, in wildlife monitoring and
conservation. The primary focus of this study is to
evaluate the effectiveness of the YOLO algorithm in
identifying and tracking wildlife species, analyzing their
behavior, and supporting conservation efforts. By
utilizing CCTV cameras placed in wildlife habitats the
YOLO algorithm enables real-time detection, tracking, and
classification of wildlife objects thereby providing
researchers and conservationists with data. To conduct
this research we employed a methodology that involved
training the YOLO model using wildlife datasets[7]. This
training enabled the model to recognize and classify
species accurately. Furthermore, we optimized the
model’s performance before deploying it on CCTV camera
feeds allowing for the monitoring of wildlife populations.
The YOLO algorithms' efficient video frame processing
capabilities ensure real-time object detection enabling
access to insights about species presence, behavior
patterns, and potential threats. The utilization of the
YOLO algorithm has proven beneficial as it enables real-
time identification of elusive species. This technological
advancement plays a role, in providing information, for
conservation efforts surrounding these species.