bluuebunny/crossref_metadata_2025 huggingface dataset:
Roman Holiday (1953)
Authors: Özsoy Bilge Ataç
Published: April 2024

This study examines the effects of the city and places on people in the
coexistence of the disciplines of cinema and architecture, through the movie “Roman
Holiday”. Cinema and architecture are similar in terms of constructing the space lived
and experienced. Architecture creates spaces based on lifestyles, human needs, and
expectations, whereas, in cinema, spaces are needed in order to tell stories. Cinema
spaces can be created and designed in different ways depending on the characteristics
of the movie. From time to time, the movies occur in actual places where life continues
in its ordinary course. In both cases, space becomes the most important part of human
life and the story told.

In this study, the movie “Roman Holiday” was evaluated in the context of human-space
and city relations. In different cultures and times, human life emerges and is shaped
through space, and in the meantime, space continues to be an important part of human
life. In the movie, while various sections from the life of a princess are shown, the
effect of the city and urban spaces on human behavior are analyzed through the city of
Rome and its places.

The city of Rome and its places can be evaluated by their functions, forms, and
physical features. With these evaluations, numerical results can be obtained. However,
in order to understand the intertwined connection between people and space and the
communication they establish, it is necessary to evaluate people and human life. The
main preoccupation of human-centered disciplines is to understand these connections.

While evaluating the spaces in the unity of architecture and cinema, the effects of urban
spaces on human life are observed through the story told in the movie. This study aims
to question the ways in which the relations between the city, society, and the individual
are constructed through space through the example of Roman Holiday movies.
Intellectual Criticism and Space in Cinema; Winter Sleep
Authors: Akarsu Hikmet Temel
Published: April 2024

Winter Sleep is a movie that won the Palme d'Or at the Cannes Film Festival
in 2014. It is directed by Nuri Bilge Ceylan who has a worldwide reputation and
prestige. Let us also add that this movie won the FIBRESCI award, and it has more
accomplishments at the box office than the director’s other movies, which have more
stable cinematic language.

In regard to the narrative of Winter Sleep, although the preference for space is made
effortlessly, through common sense and intuition, it is the right choice for sure. The
reason for that is that Cappadocia and the Turkish intellectuals have identical attributes.
Rough life climbing up a magnificent history, structures in which makeshift lives with
a profound past reside as well as a sophisticated spatial formation that undertakes the
duty of reflecting the silence that mocks its miserable people, and a generation that has
been brought up incorrectly, corruptly mediating the vulgarized use of a magnificent
architecture.

Winter Sleep is filled with these, and it is truly a film of melancholia. Because the
director went about his creation in a place where the psychopathology of the space and
the problems of our intellectual intersect, paradoxically, the work has found a strong
structural foundation. That is to say, the success of Winter Sleep comes from the fact
that it approached the architecture of Cappadocia, which had been used as a gallery of
cliches and antiquity until then, with a negative commentary. The significance of the
movie lies in the fact that it judges, or rather dissects, our intellect through the
mistreated, hurt, and pessimistic appearance of Cappadocia.

On the one hand, corrupted intellectuals, who are looking for a remedy for their
hopeless spiritual wounds in suffocating hazy, narrow rooms and in depressing spaces
that are engaged with mazes, make their games central to their lives.
The Truman Show: A Different American Dream
Authors: Erar Oya Tunçay
Published: April 2024

Truman Burbank, a child who was adopted before he was born by a film
company, had been brought up on Seahaven Island, a large and completely humandesigned plateau. On the island, Truman is the only ‘real’ person. Not only the
surrounding environment but his mother, father, wife, and best friend are all part of the
fiction as “actors.” The interplay between real and fiction is in fact being watched by
millions of different countries in the world. Everything used in the show, all products,
are objects of advertisement and for sale. We see in the movie that everything in the
real world has a price and how popular culture shapes society with visuals.

Today’s lifestyle leaning towards consumption bombards us with the ideology of use,
finish, throw it away, and continue for the new. We cannot deny that architects and
others from different disciplines working with architects are not complicit.
Environments constructed with the promise of creating ideal spaces for living do not
promote life experiences, city culture, or the well-being of the individual, but impose
capitalism’s demands.

The Truman Show, which leaves unanswered questions in our minds and brings about
questions to question ourselves and those around us, foreshadowed today’s spectacle
society. Social media and popular culture dominate our space of living day by day and
people choosing to become not only spectators but also those who are watched turned
to the directors of The Truman Show.

The Truman Show movie, with all of its metaphorical descriptions, treats carefully the
change in the notion of space. It eventually is a remarkable movie, bringing a new
perceptive to architectural culture.
The Journey Of Love(Before Sunrise/Before Sunset/Before Midnight)
Authors: Kartal Semiha
Published: April 2024

In the Richard Linklater film series, one of the examples of independent
cinema, the journeys of two American and French young people who met on the train
during their European trips are described with architectural details. In the film series
featuring the same director and actors, the architectural identities of Vienna, Paris, and
Greece are presented with their natural and built environments. The intensity of
emotion that can be called “First Love” in this work was experienced in Vienna. It is
possible to see the relationship established by culture, art, and architecture with its
buildings, avenues, streets, palaces, squares, cemeteries, fountains, and sculptures in
this city. Various styles of the history of art and architecture, ranging from a Gothic
cathedral to Baroque buildings, have been visualized through this film. It is possible to
say that these styles differ from each other in terms of form and content, as well as the
aesthetic values they add to the city. In the city, traces of eclecticism can be seen,
reflecting the complexity of the intellectual environment, which is the subject of
criticism by architects. In this context, the story of two young people presenting the
history and texture of the city with a visual feast on the streets of Vienna also showed
the relationship established by architecture and cinema. While describing 'Love', the
frames in which the unique architectural beauties of the city are exhibited have
presented how the art of cinema uses the architectural elements that are the language of
the city in a visual dimension. In this context, it is possible to say that the art of cinema,
which visualizes the stories of cities as living organisms, effectively uses architecture
to contribute to its memory.
Dogville: Destruction is Architectural
Authors: Boyacıoğlu Can
Published: April 2024

This article is on the architectural discussion of a four-fold portrayal of Lars
von Trier’s film Dogville. The film is about a lonely woman’s refuge in a middle-ofnowhere American town and how the town community turns her into a slave. The film
was shot in a dark hangar and has a single stage that is only decorated with chalk lines.
The article contains an introduction, a conclusion, and four chapters: “the lone subject”,
“the philosopher/architect”, “(lack of) Nature” and “Waiting for Destruction”. The
introduction is about the grotesque character of the film with the stage’s unliving dark
atmosphere and the plot’s unearthly feelings. The first chapter is about the subjectoriented character of the film. All unhuman materialities are clarified only with the
clues of human perception through the film. The second chapter is about how the
intellectual idea becomes the slave of public opinion through the character Tom’s
transformation. It is used to understand the transformed role of an architect in a
capitalist society. The third one is the vacuum of materiality in the film; the only
natural elements are metaphors of the action and reaction in human-nature duality. The
fourth chapter is about the metaphorical destruction promise of the film that is actually
understood as an architectural element in the context of the text that is not normally
used to be handled as a part of the architecture. Destruction not only means the
possibility of new beginnings but also an ethical clearance for the regrowth of nature
physically and metaphorically
Examining the Spaces of (The Shining) through Human Psychology
Authors: Gündoğdu Nihan Sümeyye
Published: April 2024

Shining, a 1980 film directed by Stanley Kubrick and based on the novel of
the same name by Stephen King, is one of the crucial examples of the psychological
thriller genre. Stanley Kubrick is an American film director of Jewish origin. The
director, who prefers to create uniqueness in his films, has adapted many literary works
for the cinema. One of them, the movie Shining is about the experiences of the
protagonist of the film, Jack, working as an off-season caretaker and with his family in
that place. Jack resigns from his teaching job, agrees to work at the Overlook Hotel on
a deserted hill during winter, and settles into the hotel with his family. Since the hotel
is closed in the winter, Danny, the gifted son of this family residing in the hotel, sees
through his superpowers that there are evil spirits in the inn, that his father is possessed
by these spirits, and that he is slowly coming to the point of insanity and his
psychological breakdown.

The central theme of the film, which has an important screenplay in terms of space and
human relationships, is drama and horror. Within the scope of the study, the effects of
human psychology on space and, at the same time, the impact of space on human
psychology are discussed via space, through colors and sound, as well as light. From
the beginning of the movie, it is possible to see scenes that will affect Jack's insanity,
starting from the outside.

In addition to these architectural elements that have caused Jack to go insane, the
labyrinth theme and symmetry that we often see in places in the film also have an
important place in the story. As a result of all this, the phenomenon that affects human
psychology in the film, that is, the main character Jack's insanity, is uncanniness. In the
article, the phenomenon of uncanniness is conveyed within the flow of the film via the
characters and their spatial reflections. The psychological effect of space on people, as
well as the psychological effect of people on space, has been processed through the
phenomenon of the uncanny.
Koyaanisqatsi
Authors: Yalçın Esra Eres
Published: April 2024

Natural destruction caused by technology, globalization, and industrial movements has threatened the ecological balance. The risk of depletion of natural resources has led people to be more respectful of nature and to protect it. Achieving the goal of ecological studies and reducing environmental problems is possible by understanding environmental awareness at the social level. Documentary films shot in the ecological field are an effective tool in raising social awareness by showing the state of nature in the face of the production activities of humans. Koyaanisqatsi, which is among these productions, is 1982 American experimental and non-narrative documentary film produced and directed by Godfrey Reggio, with music by Philip Glass and director of cinematography, Ron Fricke. In this film, in which the turmoil of life is emphasized, the narration has further been strengthened thanks to representations of the built environment. In this study, the turmoil in life and the effect of this turmoil on the natural and built environment are covered, based on the strong representations of Koyaanisqatsi. This study aims to contribute to the ecological development of design approaches in built environment production and to increase environmental awareness. In the study, the change and transformation of human-nature relations until the present, and the urban and architectural reflections of the turmoil in life are discussed. In line with the search for solutions to ecological problems experienced on a global scale, the importance of design approaches that will not conflict with ecological interests in the production of the built environment has been revealed. The widespread use of architectural approaches that take into account the climatic data of the region, which is sensitive to nature in material selection and gives importance to the effective use of renewable energy sources, is of great importance in preventing the chaos emphasized in Koyaanisqatsi.
Edward Scissorhands and the Realities of Suburbia for an Extraordinary Body
Authors: Köseoğlu Emine
Published: April 2024

Spatial perception is the process of receiving information from stimuli and transforming it into meaningful experiences of the built environment. The interaction of the sensing body and the perceived thing plays an important role in this process. The body leads to the mechanisms of the mind as the subjective side of the process, whereas the physical and sensory objects of the outer world form the spatial part of the interaction. This study aims to express a rereading of the extraordinary perceptual realities of suburbia in Edward Scissorhands in which the protagonist is struggling with extraordinary built and social environmental clusters. The director Tim Burton successfully reflects the hidden perceptual realities of suburbia within its apparent characteristic physical features in an uneasy manner, which is raised by the survival of an extraordinary individual who fell into a suburbia seeming normal at first sight. During the study, first, the structure and story of the film are presented, then some conceptual perspectives such as body space perception are explained, and then some rereading of the film towards these perspectives is reflected. A subtle figuration of psycho-social conflicts is pictured successfully in the movie using the physical environment within its contrast and emphasis. It can be concluded that the dramatic loneliness of Edward is emphasized by the Gothic and dark house at the end of the street, whereas the superficial and apparent purity of the suburban society is represented by the basic forms and soft colors of the architectural and urban environment.
Unveiling Genetic Variation in Garlic Genotypes in Response to Rust Disease Using RAPD Markers
Authors: Askari Somayeh Alimoradi , Esfahani Mehdi Nasr , Shirazi Kowsar , Esfahani Arman Nasr , Zeinalzadeh-Tabrizi Hossein , Mohammadi Mojtaba
Published: April 2024

Garlic (Allium sativum), cultivated worldwide for its medicinal and nutritional value, faces challenges due to diseases caused by various pathogens. In this study, eleven garlic genotypes from Iran and one from China were selected and sown under natural infection rendered by the rust fungus (Puccinia alli) over two consecutive years. Subsequently, disease distribution and severity, percentage of infection and susceptibility of different garlic genotypes to rust disease were investigated. The results showed that genotype Solan was the most susceptible, with disease severity of 30.81%. In comparison, genotypes Aliabad and Bahar were resistant against rust disease with the lowest infection percentages of 13% and 16.37%, respectively. Further, genetic diversity was assessed using random-amplified polymorphic DNA (RAPD) markers. Out of 10 primers used, 95 scorable bands were generated, of which 66 (69.48%) were found to be polymorphic. A dendrogram was constructed based on RAPD polymorphism using the UPGMA method, and the genotypes were separated into six distinct clusters based on Jaccard's coefficient of similarity. Additionally, it was observed that there is no genetic differentiation among the genotypes based on their geographical origin. This study highlights the significant diversity in resistance and susceptibility among garlic genotypes, which can be harnessed in plant breeding programs.
Compassion-Focused Mentoring: An Antidote to Adverse Faculty-Student Mentoring Outcomes?
Authors: Kaye A. Maya
Published: April 2024

Fueled by decreased state support, economic pressures, and a growing emphasis on academic capitalism, higher education in the United States faces significant challenges. These shifts have fostered fast-paced, competitive environments, impacting the quality and equity of faculty-student mentoring in graduate programs, particularly for Black, Indigenous, People of Color (BIPOC), and first-generation students. This article proposes a novel framework, the compassion-focused mentoring conceptual model (CFM-CM), to address the complex challenges faced by under-represented students seeking meaningful faculty mentorship. The CFM-CM expands on Johnson's model for mentor competence by integrating principles from Gilbert’s compassion-focused therapy (CFT) approach. It emphasizes the cultivation of a compassionate Self-identity in mentors, grounded in compassion motivation and mindfulness, as a foundation for fostering ethical, equitable, and supportive mentoring relationships. By exploring the limitations of current mentoring practices and analyzing negative mentoring experiences through the lens of CFT, this article suggests that the CFM-CM can pave the way for improved faculty-student relationships, fostering well-being, inclusivity, and success for BIPOC and first-generation students in graduate education.
Low Mortality Associated with COVID-19 Infection in Lung Transplant Recipients at a Single Center
Authors: Gomez Rahul , Kafi Aarya , Yung Gordon , Aslam Saima , Lin Christine M. , Pollema Travis , Golts Eugene , Afshar Kamyar
Published: April 2024

Lung Transplant Recipients (LTR) are particularly vulnerable to severe infection, hospitalization, and death due to community acquired respiratory viruses. As a result, the global SARS-Cov-2 pandemic poses a higher risk to this population. We aim to study the lung function, severity of infection and mortality among LTR at a single center. A retrospective chart review was performed on all LTR at the University of San Diego, California Medical Center between June 2020 and September 2022. Spirometry was performed at 1-2 months and then again 3 months after infection. Patients were closely monitored for the development of acute cellular rejection (ACR). 72 LTR were infected with COVID-19. 37.5% required hospital admission, of which 25.9% required management in the intensive care unit (ICU). 73.6% LTR had received at least one vaccination dose prior to infection. Post-infection, the median drop in FEV1 was 140 mL and FVC was 25 mL within 1-2 months. At 3 months post-infection the median reduction in FVC was slightly larger at 75 ml, while median decline in FEV1 decreased to 55 ml. Overall, the rates of ACR and mortality in this population were both 4.2%. Additionally, monoclonal antibody (mAb) therapy reduced hospitalization (20.9% vs 62%) and mortality (0% vs 10.3%), Our study found low rates of ACR and mortality in LTR with confirmed COVID-19, despite the statistically significant decline in FEV1, and trends with FVC. The use of vaccinations and mAb therapy decreased rates of hospitalizations, with mAb therapy reducing mortality as well.
An Adaptive Robust Control Method for Chaotic State of Permanent Magnet Synchronous Motor
Authors: Zhang Wei , Chang Lingyan
Published: April 2024

In this paper, a chaotic control method based on adaptive robust controller is proposed to solve the chaos phenomenon of the permanent magnet synchronous motor system by mathematically analyzing the dynamic model of the permanent magnet synchronous motor system to eliminate or suppress chaos in the permanent magnet synchronous motors. This method also takes into account the parameter uncertainties (structural uncertainties) of the system and the external load torque interference (unstructured uncertainty).The former is compensated by adaptive control, and the latter by robust term. Feedforward elimination technology can integrate them together, and effectively reduce the influence of chaos on system performance and realize the high precision position tracking of the permanent magnet synchronous motor system. The Lyapunov method is used to prove the stability of the controller. The simulation results show that the method is better in robustness and control precision.
Construction and Image Communication of Urban Cultural Space under the Collision of Modern Art Elements and Chinese Traditional Culture: A Case Study of the Wuzhen Theatre Festival
Authors: Xu Zhenyi
Published: April 2024

Since its inception in 2013, the Wuzhen Theatre Festival has gradually grown into one of the most influential theatre festivals at home and abroad. As one of the brand characteristic events, it has helped Wuzhen transition from a traditional Jiangnan ancient town to a well-known cultural landmark through media communication. This paper aims to analyze the multiple cultural spaces presented in the Wuzhen Theatre Festival, explore how this medium combines modern art elements with Jiangnan culture, builds a bridge between high art and ordinary people, thereby endowing Wuzhen with a more diversified international image. It also attempts to summarize the enlightenment of the Wuzhen Theatre Festival on the construction of urban cultural space and image in China today.
Review of Research on Uncertain Repetitive Project Scheduling
Authors: Lin Zhou , Li Yifei , Hao Wang
Published: April 2024

With the continuous development of project management practice, the project often suffers from disturbance events in the actual execution activity, which leads to project delay and great economic losses.Uncertainty project scheduling studies have also received attention.Repetitive project is a type of project with its own characteristics in which the construction site can be divided into several independent units and all activities are repetitive on multiple units, such as high-rise buildings, highways, and pipeline works. The characteristics of repetitive project controlling paths and controlling activities have their own advantages in responding to uncertain events. This paper takes repetitive project scheduling as the object to sort out its uncertain scheduling research. Firstly, the uncertain research based on probability random theory, fuzzy set theory and robustness theory is summarized, and then the research on different scheduling strategies such as interruptions soft logic and multi-mode in repetitive project scheduling is further summarized. Finally, the current research status of uncertain reactive scheduling is summarized,and further research directions are pointed out.
Research on the Promotion Mechanism of Sports Participation in Children and Adolescents Based on Social Cognitive Theory
Authors: Zhao Jie
Published: April 2024

This study aims to explore the promotion mechanism of children and adolescents' sports participation, based on social cognitive theory. By analyzing the theoretical framework of social cognitive theory, this study aims to gain a deeper understanding of the internal mechanisms of children and adolescents' participation in sports, and provide theoretical support for promoting their physical and mental health development. The study adopted various research methods, including literature review, expert interviews, observation, and teaching experiments, to systematically analyze the elements and promotion mechanisms of children and adolescents' participation in sports. The research results show that social cognitive theory plays a crucial role in interpreting children and adolescents' sports participation behavior, cognitive processes, and emotional experiences. In terms of practice, research has proposed multiple strategies, including innovating the teaching mode of physical education for children and adolescents, integrating sports training camps with social cognitive theory, and designing intervention programs for children and adolescents in sports participation based on social cognitive theory. Future research directions include providing diverse role models, encouraging diverse ways of social participation, and establishing a positive sense of social identity to further promote the practice and development of sports participation among children and adolescents.
Comparative Study of G+6 Irregular Multistoryed Building of L Shape of Diaphragm Discontinuity
Authors: Saxena Ritik , Golghate Kavita
Published: April 2024

Abstract: This study investigates the effectiveness of incorporating roof openings in re-entrant corner plan irregular buildings at various locations under earthquake loads. Three models L-shaped diaphragm discontinuity were analyzed using STAAD Pro software. Node displacement and storey shear in both the X and Z directions were evaluated to assess structural performance. The results indicate that models with square diaphragm discontinuity exhibit increased node displacements and storey shear compared to those with L-shaped diaphragm discontinuity. The model with L-shaped diaphragm discontinuity consistently demonstrates superior performance in terms of lower displacements and shear stress values. However, the final model selection should take into account specific project requirements and design considerations.
An Analysis of Convolutional Neutral Network for Image Classification
Authors: Hanchinal Tainiyat K
Published: April 2024

Abstract: Convolutional Neural Networks (CNNs) have emerged as a powerful tool for image classification tasks, owing to their ability to automatically learn hierarchical representations from raw pixel data. This paper presents a comprehensive analysis of CNNs for image classification, focusing on their architecture, training process, and performance evaluation metrics. The study investigates various CNN architectures, including AlexNet, GoogLeNet, and ResNet, highlighting their respective strengths and weaknesses in different scenarios. Moreover, the paper explores the impact of hyperparameters such as network depth, filter size, and pooling strategies on classification accuracy and computational efficiency. Furthermore, the training process of CNNs, encompassing data preprocessing, augmentation techniques, and optimization algorithms, is scrutinized to elucidate best practices for achieving optimal performance. Additionally, the paper discusses commonly used evaluation metrics such as accuracy, precision, recall, and F1-score, elucidating their interpretation and significance in assessing model performance. Through a systematic review of existing literature and experimental validation, this analysis aims to provide insights into the underlying mechanisms of CNNs for image classification tasks. Finally, the paper outlines future research directions, emphasizing the need for exploring novel architectures, optimizing hyperparameters, and enhancing interpretability and robustness of CNN models. Overall, this study contributes to a deeper understanding of CNNs for image classification and provides valuable guidance for practitioners and researchers in the field.
Development of Dynamic Image Recognition System for Hand Sign Language into Audio and Visual Output using Artificial Neural Networks
Authors: Chavan Prof. M. C. , Chaudhari Prof. D. N. , J Pratham , M Vinay , C Lalit , T Ashish
Published: April 2024

Abstract: This system provides a simple solution to a complex problem faced by deaf and dumb community. This paper visualizes the development web application of a real-time image recognition system whose main aim is to convert or translate the hand signs used in sign language in textual or visual and audio form output by using artificial neural networks. This system used computer vision to see signs as an input for processing and makes accurate predictions by using deep learning methods in realtime. By using artificial neural networks (ANN), the system achieves better performance in predicting or recognizing hand signs. The system makes communication between people using sign language and people who don’t know sign language effective by providing output as an audio and texted / visual, which even helps people in both ways. The project aims only to provide the society a solution by helping people who use sign language to express themselves to make it more effective and give them an ability to speak by using the technologies.
HealthTech Companion: Promoting Access to Personalized Medical Advice
Authors: Garg Dr. Rishabh , Prasad Shashi Shekhar , Verma Mohita , Singh Abhishek , Singh Abhinav
Published: April 2024

Abstract: Science has come a long way in the last several years, thanks in large part to machine learning tools. This improvement is most noticeable in the field of medical diagnostics, where it is now much easier to diagnose disorders based only on symptoms. Although there are frequently similarities between the symptoms, each disease presents with its own distinct set of signs. It is therefore essential for a diagnosis to be made correctly to identify patterns within these symptoms. However, the sheer number of illnesses and the symptoms that go along with them provide a formidable obstacle to anybody trying to identify their own health issues. Picture yourself feeling sick, but not knowing why you are feeling so bad. This is where a useful chatbot may be quite beneficial, letting users enter their symptoms and acting as an informed guide in making educated guesses about possible illnesses. The Apriori algorithm, which is well-known for its capacity to find patterns in big datasets by linking objects together, is one potent tool used in this situation. Within the healthcare industry, the Apriori algorithm is particularly good at identifying patterns of disease by associating it with related symptoms. This allows the chatbot to provide well-informed information in response to user inputs. Apart from the Apriori method, Recurrent Neural Networks (RNNs) are also utilized due to their ability to handle sequential input and produce replies to user queries that are relevant for the context. The chatbot gives people the ability to evaluate health issues even in the lack of expert medical knowledge by integrating these algorithms. This gives people the ability to take charge of their health by quickly requesting help and according to the chatbot's instructions. Furthermore, the use of Quantum Machine Learning methods enhances the chatbot's skills even further. A viable path to improving illness prediction accuracy and honing the chatbot's recommendations is through the use of quantum algorithms, which can handle complicated data structures and carry out calculations that are beyond the capabilities of conventional algorithms Because these sophisticated algorithms enable early diagnosis, diseases may be treated and lifestyle changes can be made earlier, improving prognoses and boosting survival rates. Additionally, early identification shortens the time it takes for illnesses to worsen
The Impact of Artificial Intelligence on Personalized Marketing
Authors: S Gautham , Rao Dr. Shalini
Published: April 2024

Abstract: Artificial intelligence (AI) has become increasingly prevalent in various industries, revolutionizing traditional practices and introducing novel approaches. One such domain significantly influenced by AI is marketing, particularly in the realm of personalized marketing. Personalized marketing aims to tailor promotional efforts to individual consumers based on their preferences, behaviours, and demographics. The integration of AI technologies in personalized marketing strategies has promised to enhance targeting accuracy, improve customer engagement, and ultimately drive higher conversion rates Consequently, investigating the impact of AI on personalized marketing holds substantial significance in understanding the evolving dynamics of consumer-brand interactions in the digital age.
Iris Unleashed: Revolutionizing Mouse Control through OpenCV
Authors: Mahammad Farooq Sunar
Published: April 2024

Abstract: Background: In today's modern world, personal computers have become an essential part of our daily routines, serving various purposes like work, education, and entertainment. However, for individuals with limited mobility, using traditional input devices such as keyboards and mouse can be quite challenging. In such cases, alternative input methods that utilize different abilities, such as eye movements, are preferred. Objectives: The proposed system begins by capturing an image with a camera and using OpenCV code to detect the pupil's position in the eye. This information serves as a reference point for the user to control the cursor by moving their eyes left and right.
Enhancing Techniques for Adaptable Decision Feedback Balancer for 5G Communication
Authors: G Venkatesha , N Vijaya Kumar C , C Hema
Published: April 2024

Abstract: This complete review examines two basic parts of cutting edge correspondence frameworks. First and foremost, it investigates novel plan procedures and models for Adaptable Decision Feedback Balancer (ADFB) in rapid correspondence frameworks. Strategies like look-into tables, disseminated math, and prescient equal branch slicers are utilized to upgrade union rates, throughput, and mistake execution while limiting equipment intricacy. The proposed plans exhibit significant advancement in region, power proficiency, and rationale usage across different regulation plans, channel models, and portability situations. Furthermore, the examination digs into Super Dependable Low Idleness Correspondence (SDLIC) headways inside the 5G New Radio (NR) downlink, tending to actual layer difficulties determined in 3GPP Delivery 15. The review presents a clever correspondence framework utilizing super codes to moderate between image impedance in remote conditions. Also, inventive equal plans for high velocity Choice Input Adjusters (CIAs) and equipment proficient models for versatile balancers utilizing disseminated number-crunching are introduced. The joined discoveries contribute significant bits of knowledge into streamlining versatile balancers for group of people yet to come correspondence frameworks and progressing SDLIC in 5G NR.
Campus Connect - Bridging the Academic Community with Blockchain-Powered Decentralization
Authors: Tyagi Shreya , Srivastava Shikhar , Raj Geetanjali
Published: April 2024

Abstract: In response to the evolving landscape of education in the digital era, CampusConnect emerges as a transformative blockchain-based decentralized application. This platform seeks to redefine the college experience by establishing a secure and collaborative environment for students, faculty, and campus communities. Leveraging blockchain technology, CampusConnect ensures data integrity, transparency, and decentralization, addressing the limitations of traditional social media platforms in meeting the unique needs of educational institutions. The objectives of this innovative initiative include enhancing communication, promoting resource sharing, improving campus event management, and offering a specialized academic network.
Applied Machine Learning Predictive Analytics to SQL Injection Attack Detection and Prevention
Authors: P Bhaskar , K Shashikala , V Susma Swaraj , A Gayathri , G Madhavi , C Venkata Juhitha
Published: April 2024

Abstract: The back-end database is pivotal to the storage of the massive size of big data Internet exchanges stemming from cloud-hosted web applications to Internet of Things (IoT) smart devices. Structured Query Language (SQL) Injection Attack (SQLIA) remains an intruder’s exploit of choice on vulnerable web applications to pilfer confidential data from the database with potentially damaging consequences. The existing solutions of mostly signature approaches were all before the recent challenges of big data mining and at such lacks the functionality and ability to cope with new signatures concealed in web requests. An alternative Machine Learning (ML) predictive analytics provides a functional and scalable mining to big data in detection and prevention of SQLIA. Unfortunately, lack of availability of readymade robust corpus or data set with patterns and historical data items to train a classifier are issues well known in SQLIA research. In this project, we explore the generation of data set containing extraction from known attack patterns including SQL tokens and symbols present at injection points. Also, as a test case, we build a web application that expects dictionary word list as vector variables to demonstrate massive quantities of learning data. The data set is pre-processed, labelled and feature hashing for supervised learning. The trained classifier to be deployed as a web service that is consumed in a custom dot NET application implementing a web proxy Application Programming Interface (API) to intercept and accurately predict SQLIA in web requests thereby preventing malicious web requests from reaching the protected back-end database. This project demonstrates a full proof of concept implementation of an ML predictive analytics and deployment of resultant web service that accurately predicts and prevents SQLIA with empirical evaluations presented in Confusion Matrix (CM) and Receiver Operating Curve (ROC).
Smart Automated Liquid Sprinkler Robot Integrating IoT and Deep Learning for Precision Crop Management
Authors: Maneesha L. L. S. , Manasa N. Chinni , Manoja K , Chowdary M A Raghava
Published: April 2024

Abstract: The Smart Automated Liquid Sprinkler (SALS) is a groundbreaking solution aimed at revolutionizing traditional watering systems through the integration of IoT technology. Its development addresses pressing challenges such as water scarcity and labor-intensive maintenance in outdoor environments. SALS combines advanced sensors to monitor humidity and weather conditions in real-time, ensuring precise watering tailored to the specific needs of plants while minimizing manual intervention. Furthermore, it incorporates obstacle detection and avoidance features, enhancing its efficiency and durability by mitigating the risk of accidents. By integrating deep learning models for rainfall prediction, SALS optimizes water usage preemptively, adjusting watering schedules to environmental conditions. Offering independent operation and a modular design, SALS provides flexibility to users, catering to gardens of all sizes and promoting greener and healthier environments. The longterm savings from reduced water consumption and labor costs make SALS a wise investment for homeowners, businesses, and municipalities, heralding a new era of efficiency and sustainability in outdoor maintenance
AI Based Multilingual College Enquiry Voice Bot Using Python
Authors: H M Prof. Kotresh
Published: April 2024

Abstract: This paper addresses the growing need for seamless cross-language communication in our global society. Leveraging AI, it offers a versatile conversational agent capable of understanding and responding to inquiries in multiple languages. Through speech recognition and advanced NLP, the system interprets user intent and retrieves relevant information from a college database. Integrated language translation services enable communication in various languages namely-Kannada, English, Tamil and Telugu enhancing accessibility. Responses are dynamically translated into the user's preferred language using text-to-speech conversion. This project demonstrates AI's potential in bridging linguistic barriers and improving access to educational resources. Future enhancements could include personalized responses and expanded language support in five South Indian languages, further enriching the user experience and solidifying the bot's role as a valuable educational tool.
Solar Tracking Methods: A Comprehensive Survey
Authors: Rajkumar Dr. Newlin , Govindhavasan  , Jeyasri  , Kumar Abishek , Mahilarasi Andro
Published: April 2024

Abstract: In the pursuit of maximizing solar energy utilization, solar tracking systems have emerged as indispensable tools for enhancing the efficiency of photovoltaic (PV) systems. This comprehensive survey delves into the multifaceted landscape of solar tracking methods, elucidating the diverse techniques and strategies employed in optimizing solar panel orientation relative to the sun's position Solar tracking systems are classified into two primary categories: single-axis and dual-axis tracking. Single-axis tracking systems adjust solar panels along one axis, typically the azimuth axis, while dual-axis tracking systems dynamically alter both azimuth and elevation angles to accurately follow the sun's apparent motion across the sky.Within the realm of solar tracking, passive and active tracking methods are explored. Passive tracking mechanisms rely on natural phenomena such as gravity or thermal expansion to adjust panel orientation, whereas active tracking systems employ mechanical, electrical, or hydraulic actuators driven by motors or other means to actively adjust panel angles based on real-time tracking algorithms.A pivotal aspect of solar tracking systems is the selection and implementation of tracking algorithms. Various algorithms, including sun position algorithms, maximum power point tracking (MPPT) algorithms, and predictive algorithms, are analyzed for their effectiveness in accurately predicting and optimizing solar panel orientation.Furthermore, this survey scrutinizes the role of sensor technologies in solar tracking, encompassing GPS-based tracking, light-intensity-based tracking, weather-based tracking utilizing meteorological sensors, and horizon tracking techniques. These sensor-based methodologies offer different advantages and trade-offs in terms of accuracy, cost, and reliability. To provide a comprehensive understanding, comparative analyses are conducted, evaluating the efficiency, cost-effectiveness, and energy yield of different tracking methods. These comparative assessments offer valuable insights into the performance characteristics and suitability of various tracking methodologies across diverse applications and environmental conditions.In conclusion, this survey serves as an invaluable resource for researchers, engineers, and policymakers involved in the design, development, and optimization of solar tracking systems for renewable energy applications. By synthesizing the latest advancements and comparative analyses, this survey facilitates informed decision-making and fosters the advancement of sustainable solar energy technologies.
Driver Drowsiness Detection System
Authors: Khangar Dhawal Nilesh , Khandave Prathamesh Jagannath , Meshram Prakashit Dadarao , Kullarkar Harshal Kishore , Nakawal Mital Vikas
Published: April 2024

Abstract: Drowsy driving poses a significant threat to road safety, necessitating the development of effective drowsiness detection systems. This research paper provides a thorough review of current technologies employed in drowsiness detection, encompassing image-based, physiological, and behavioural approaches. Evaluating the strengths and limitations of existing systems, the study identifies key challenges, including false positives and negatives, adaptability to diverse conditions, and integration complexities. Recent advancements, such as deep learning, sensor fusion, and real-time processing, are explored, offering insights into their impact on system accuracy and usability. The paper proposes hybrid approaches, personalized algorithms, and integration with smart infrastructure as potential enhancements. Through case studies, the effectiveness of drowsiness detection in real-world scenarios is highlighted, emphasizing the positive influence on road safety. The research concludes with a discussion on future directions, outlining emerging technologies and identifying research gaps. This paper aims to contribute to the ongoing evolution of drowsiness detection systems, fostering innovation for improved safety on the roads
Facial Recognition Attendance System Using AI
Authors: Kunjir Yash , Nikalje Vaishali , Thakur Priya , Yelimeli Shraddha , Shinde Sakshi , Kure Sushama , Thakur Bisweswar
Published: April 2024

bstract: This paper presents a concise overview of a facial attendance system implemented using Python. Leveraging deep learning techniques and popular libraries such as OpenCV and Tensor Flow, the system offers accurate and efficient attendance tracking based on facial recognition. The paper discusses the system architecture, dataset used for training, performance evaluation, and potential implications for real-world deployment. Overall, this research contributes to the advancement of attendance management systems through the integration of facial recognition technology. Index Terms- Facial Recognition,Attendance Management Systems, Python Programming, Deep Learning, Convolutional Neural Networks (CNNs),Learning, Convolutional Processing, Privacy Concerns, Ethical Considerations
Smart Fault Detector Robo to Detect Gas and Fire
Authors: Ghode Shivam S , Gedam Samiksha K. , Mahajan Tejas S. , Nikalje Piyush R. , Parate Ankit M. , Pathan Ameenkhan F.
Published: April 2024

Abstract: The Smart Fault Detector Robo revolutionizes safety protocols with its cutting-edge design, employing a synergy of state-of-the-art sensors, AI, and robotics. Its primary goal is the early identification of gas leaks and fire incidents across diverse settings. Utilizing advanced gas sensors, it can detect a broad spectrum of harmful gases, including methane and carbon monoxide, with remarkable precision. Powered by sophisticated AI algorithms, it swiftly analyzes data in real-time, distinguishing between normal fluctuations and potential hazards, ensuring unparalleled accuracy and reliability.
Comprehensive Overview of GAN Technology: Architecture, Training, and Applications
Authors: Bhavani Vaishali
Published: April 2024

Abstract: Generative Adversarial Networks (GANs) is a groundbreaking artificial intelligence technology that transforms generative modeling through the implementation of a novel adversarial training framework. GANs are made up of two neural networks, the generator and the discriminator, which compete in a minimax game in order to generate counterfeit samples of data and distinguish between real and fake data. This adversarial training method results in the creation of highly proficient generative models capable of producing data that is identical to real-world samples. GANs have been shown to have significant outcomes in a variety of programs, consisting of synthesizing images, style transfer, medical visualization, and natural language processing. However, GANs encounter difficulties with problems like mode collapse and operational irregularities. Presently, research is aimed at tackling these problems and strengthening GAN frameworks and training approaches. GANs’ adaptability and perspective contribute to an intriguing technology for a wide range of sectors and artistic activities, with consequences for artificial intelligence growth and generative modeling breakthroughs. GANs incorporate the potential of competitive training with their capacity to generate extremely realistic data in a variety of domains. We will begin by looking at the fundamental concepts, and underlying principles that reinforce GANs, and their general architecture, investigate their different possible uses, and discuss the obstacles and potential developments in this instantly transforming field.