bluuebunny/crossref_metadata_2025 huggingface dataset:
Derrick Bell on Living in Relation to Others
Authors: Bell Derrick
Published: August 2024

None
Khalifa
Authors: Diggs Richard Khalifa
Published: August 2024

[This is the partial transcript of a video recorded in 1996 by documentary filmmaker William Gentile for his brother Lou Gentile, then Director of the Bureau of Narcotics for the Office of the Attorney General. Lou showed the video nationally at conferences and mentorship events as well as making copies for anyone who asked so that the video could be more widely shared, and William has generously given permission for Kalfou to publish this transcript. Special thanks to Stephen Stept for his transcription services. See the full video at https://youtu.be/mO5T6hCOBMw.]
My name is Richard Khalifa Diggs, Khalifa being an attribute that I adopted in 1977 at the Allegheny County Jail. I’m in for a double homicide on a life sentence without parole. I’ve been down nineteen years, six months, and seven days as of this morning. 
I work at the operations building here at SCIP, the State Correctional Institution at Pittsburgh. About eight years ago I worked in this same building, and I was always somehow drawn to this particular spot at this window. It’s got pretty much a full view of the yard, pretty much a view of the institution overall, and from here, I see a lot of me and three or four generations of me. Just running around playing handball, basketball, tag, lifting iron, playing cards, planting heads [killing people]. It’s a senseless maze of confused people, of which I include myself. It’s almost horrible to the extent that you sit here and you realize that you’re very much a part of this.
A City Divided: Race, Fear, and the Law in Police Confrontations, by David A. Harris
Authors: Wozniak Jesse S. G.
Published: August 2024

To most any U.S. American who has paid even a modicum of attention to the news over the past several years, the central incident of police violence examined in David A. Harris’s A City Divided: Race, Fear, and the Law in Police Confrontations is familiar almost to the point of banality. Indeed, even if you have never heard of Jordan Miles, you can probably guess the exact sequence of events with little effort: an eighteen-year-old Black man, who is unarmed and has committed no crime, is brutally beaten by multiple police officers; the young man’s version of the events contrasts drastically with that of the three police officers; the police force immediately backs its officers before any investigation has taken place; the community cries out for justice; authorities are extremely reluctant to prosecute the officers involved; criminal charges against the officers are unsuccessful but a large civil settlement is paid out to the victim; and a series of milquetoast reforms are instituted that fail to address the problem. The sad reality is that by simply changing the names and few geographic details, this book could be discussing virtually any incident of police brutality in the United States. Yet it is very much the terrifying familiarity of the Jordan Miles case that makes Harris’s book so gripping and informative.
The Acousmatic Question and the Will to Datafy: Otter.ai, Low-Resource Languages, and the Politics of Machine Listening
Authors: Sterne Jonathan , Sawhney Mehak
Published: August 2024

What happens when Nina Eidsheim’s acousmatic question—“Who is this?”—is delegated to machines? Machine listening processes turn sound and voices into data. This article explores the political stakes that accompany the automated extraction, processing, and analysis of human voices in machine listening, specifically speech recognition. While machine listening is promoted to users in the name of utility, inclusiveness, and access, it also serves corporate purposes: the expropriation and ownership of massive collections of data. This extractive will to datafy subtends commercial and state-based machine listening operations. We outline this problematic process though two case studies: the datafication of “low-resource” languages for speech recognition in India and the widespread adoption of Otter.ai transcription services in Canada and the United States during the COVID-19 pandemic. In both cases, noble aims—inclusion and access—are simultaneously coopted to serve corporations’ extractive projects, which are built on denying speakers the right to their own voices.
Listening Practice and History: Sound, Erasure
Authors: Yunhwa Rao Nancy
Published: August 2024

In narrating the musical life of Chinese immigrants in the United States of the nineteenth century, one of the most difficult challenges is its sound. The sound did not exist. Presumably, one could trace the sound through a careful study of the performing history of Cantonese opera, the popular genre that enchanted Chinese immigrants, the majority of whom came from the Pearl River Delta of southern China. Chinese theaters performing Cantonese opera proliferated in cities and mining and railroad towns throughout the second half of the nineteenth century, with four concurrent Chinese theaters in San Francisco by the end of the 1870s. However, Cantonese opera went through significant changes in the nineteenth and twentieth centuries, leaving limited sources for scholars to fully grasp the performance practice and repertoire of the nineteenth century. Although books of lyrics of classic verses and scripts of traditional Cantonese opera exist, their relation to the performance practices of this period, which also relied heavily on improvisation, remains little known. Lacking historical sources of the opera genre is not, however, the primary problem. Erasure is.
Boxing Ring Entrances as Insubordinate Spaces: A Disruptive Oral Herstory
Authors: Mondragón Rudy
Published: August 2024

This article examines the May 5, 2018, boxing ring entrance of world champion prizefighter Kali “KO Mequinonoag” Reis. Boxing ring entrances provide a source of entertainment, setting up the spectacle of the fight. They are also spaces where professional boxers can radically and creatively express themselves through their deployment of expressive culture. This article is based on a six-hour oral history with Reis and content analysis of the media coverage of her fights. It reveals that this boxer intentionally centers her gender, self-identification as a multiracial “Black Indian,” and two-spirit subjectivities as well as her “Fight 4 All Nations” motto in her ring entrance. Building on Barbara Tomlinson and George Lipsitz’s concept of insubordinate spaces, this article argues that Reis’s deployment of expressive culture in her insubordinate ring entrance serves as a disruption to neoliberal individualism, ideas of racial authenticity, Indigenous erasure, and gender politics in boxing. The oral herstory and examination of the ring entrance space constitute an important archive that challenges scholars to think about critical sports, ethnic, and cultural studies in new ways, all within a sporting space that has long remained underexamined.
“Did He Ever Hear of Egypt or Carthage?” Moses Roper’s Literary and Oratorical Activism in the British Isles
Authors: Murray Hannah-Rose
Published: August 2024

Moses Roper was one of the first African Americans to conduct an extensive lecturing tour of Britain and Ireland, and he published an autobiographical narrative there in 1837. He was a groundbreaking force in his use of literary, oratorical, and visual forms to expose slavery’s brutalities, and throughout his speeches, he resolved to tell the truth about his experiences no matter the cost to his personal and financial circumstances. Despite his radicalism on the transatlantic stage, Roper has been cast to the sidelines of abolitionist history and is overshadowed by figures such as Frederick Douglass, whose antislavery lecturing tour in Britain and Ireland between 1845 and 1847 electrified audiences. Throughout his life, Roper used the mediums of oratory and print to simultaneously expose slavery’s brutalities and ensure his voice and life-story were not rendered invisible by dominant white power structures. At the heart of his speeches, countless editions of his slave narrative, newspaper advertisements, and letters to the press was a pioneering emphasis on authorship and literary resistance against slavery. In this article, I shed new light on the relationship Roper established between performance and print culture and for the first time explore previously unpublished stories related to his life in Britain and the United States. In doing so, I provide a fresh examination of Roper’s transatlantic activism: in context with other Black international visitors, his visit has received scant attention, and the radicalism of his speeches, together with his relationship with print culture, has been overlooked.
Unsettling Complicities: An Autoethnographic Mapping
Authors: Sahiba
Published: August 2024

In my article “Mapping Complicities in Brahmin Supremacy to White Supremacy: An Unsettling of South Asia and South Asian America” (earlier in this issue of Kalfou) I mapped the pillars of brahmin and white supremacy. Please read that article first, as it provides the context for the writing of this article. In this rumination, I use autoethnographic accounting to un/map and un/settle complicities by tracing investments and continuities in the ideological pillars upholding brahmin and white supremacy.
Toward the Right to Housing in Canada: Lived Experience, Research, and Promising Practices for Deep Engagement
Authors: Malenfant Jayne , Annan Jes , Pin Laura , Levac Leah , Buchnea Amanda
Published: August 2024

Canada’s 2019 Housing Strategy Act (NHSA) lays the groundwork for important advances in ensuring the right to housing for all. Two key approaches outlined in the NHSA for communities in greatest need are conducting research and providing participatory ways for those communities to shape housing rights responses. This article presents insights from a project that explored how people with lived experience of housing need and homelessness engage in research on housing precarity in Canada. We review the literature on housing precarity that features people with lived experience as research participants, applying an intersectional framework and acknowledging the settler colonial context of Canada. And, as a research team who has members with lived experiences of housing precarity, we emphasize the importance of meaningfully incorporating people’s lived experiences, seeing deep engagement as a way to advance housing rights by harnessing lived knowledges.
Evaluating the role of pirnas and piwi-like proteins as biomarkers and therapeutic targets in leukemia and lymphoma: a comprehensive systematic review
Authors: Reyes Jheremy S , Reyes Jheremy E , Picón Laura T , Rodríguez María A
Published: August 2024

Introduction: This systematic review synthesizes current evidence on the role of PIWI-interacting RNAs (piRNAs) in leukemia and lymphoma, emphasizing their potential as diagnostic markers and therapeutic targets. Leukemia and lymphoma represent significant challenges in oncology, warranting exploration of novel biomarkers beyond conventional methods. piRNAs, a class of small non-coding RNAs, exhibit dysregulated expression in tumor tissues and biological fluids, suggesting their utility in disease diagnosis and targeted therapy. Methods: A systematic search was conducted in PubMed and ScienceDirect databases following PRISMA guidelines. Eligible studies explored piRNA expression, diagnostic efficacy in leukemia and lymphoma tissues, and therapeutic implications. Included studies spanned from 2000 to 2024 and underwent rigorous quality assessment. Results: Initially identifying 26 papers, the review included 5 studies meeting inclusion criteria. These studies identified specific piRNAs, such as piR-32877 and piR-30473, with significant diagnostic potential in leukemia and lymphoma (AUC = 0.78). Insights from extracellular vesicle-derived piRNAs, like piR-36225, suggested promising applications for disease monitoring (AUC = 0.69). Conclusions: piRNAs emerge as promising biomarkers for non-invasive diagnosis and therapeutic targets in leukemia and lymphoma. Future research should validate these findings across diverse populations and elucidate underlying mechanisms to advance clinical utility.
Засоби для передпосівного оброблення насіння на основі кремнезему і барвника метиленового синього
Authors: Крупська Т.В. , Головань А.П. , Сіора І.В. , Туров В.В.
Published: August 2024

Створено зразки композитних матеріалів на основі кремнеземів — гідрофільного і гідрофобного, їх суміші та барвника метиленового синього (1, 2, 4, 8 мас. %,) як фунгіциду, які наносили безпосередньо на поверхню насіння пшениці шляхом опудрювання перед висіванням. Досліджено енергетичні та фунгіцидні властивості композитів. Встановлено, що методом механічного оброблення кремнеземів з метиленовим синім можна створити ефективні фунгіцидні композити для передпосівного оброблення насіння злакових культур, які водночас істотно підвищують його схожість. Композити на основі гідрофобного кремнезему характеризуються пролонгованою десорбцією метиленового синього, що, можливо, і підвищує їхні фунгіцидні властивості.
Вміст брадикініну у крові хворих на COVID-19 та цукровий діабет
Authors: Тронько М.Д. , Пушкарьов В.В. , Ковзун О.І. , Соколова Л.К. , Левчук Н.І. , Пушкарьов В.М.
Published: August 2024

Для пояснення причин гострого респіраторного синдрому, який виникає внаслідок інфікування коронавірусом-2 (SARS—CoV-2), висунуто дві гіпотези: теорія цитокінового і теорія брадикінінового шторму. Згідно з першою гіпотезою, підвищення рівня цитокінів, насамперед інтерлейкіну-6, спричиняє багатосистемні патологічні прояви COVID-19, зокрема гостре ураження легенів і респіраторний дистрес-синдром у тяжко хворих пацієнтів. Теорія брадикінінового шторму підкреслює важливість зниження кількості ангіотензин-перетворювальних ферментів у епітеліальних клітинах легенів, що призводить до нездатності розщеплювати брадикінін та аналог брадикініну des-Arg9-BK. Мета роботи — порівняльне дослідження рівня брадикініну в крові хворих на цукровий діабет і пацієнтів, що перехворіли легкою та важкою формами COVID-19. Показано, що рівень брадикініну вірогідно зростав у хворих на діабет. У хворих на цукровий діабет і COVID-19 спостерігалося незначне зростання кількості брадикініну, що вірогідно не відрізнялося від показників у пацієнтів із цукровим діабетом. Водночас кількість інтерлейкіну-6 вірогідно зростала у хворих на цукровий діабет і найістотніше у пацієнтів із гострою формою COVID-19.
OPTIMALISASI PERAN PETUGAS KLOTER HAJI PADA KANTOR KEMENTERIAN AGAMA KOTA TANGERANG TAHUN 2019
Authors: Jawab Ahmadih Rojalih
Published: August 2024

Penelitian ini bertujuan (1) untuk mengetahui optimalisasi peran petugas kloter haji pada kantor kementerian agama kota tangerang tahun 2019 (2) untuk mengetahui tugas dan fungsi petugas kloter pada kantor kementerian agama kota Tangerang (3) untuk mengetahui kendala yang dihadapi petugas kloter haji pada kantor kementerian agama kota tangerang tahun 2019. Penelitian ini menggunakan metode kualitatif dengan menggunakan teknik analisis deskriptif. Hasil penelitian menunjukkan bahwa optimalisasi peran petugas kloter pada kantor kementerian agama kota tangerang tahun 2019 mempunyai tugas yang penting dalam memandu perjalanan jamaah haji sehingga menjadi perjalanan ibadah haji yang lancar dan bermanfaat. Mengenai tugas dan fungsi petugas kloter pada kantor kementerian agama kota tangerang ini sudah efektif untuk mendukung kesuksesan penyelenggaraan ibadah haji. Kendala-kendala yang dihadapi petugas kloter dalam perjalanan ibadah haji antara lain: penempatan jamaah di 2 hotel madinah yang berbeda, jamaah yang hanya bisa berbicara bahasa daerah dan jamaah yang sudah tua.Kata Kunci : Peran, Petugas Kloter, Ibadah Haji  ABSTRACTThis study aims (1) to determine the optimization of the role of the hajj crew at the office of the ministry of religion in the city of Tangerang in 2019 (2) to find out the duties and functions of the crew officers at the ministry of religion in the city of Tangerang (3) to find out the obstacles faced by the hajj crew officers at the office. Ministry of Religion, Tangerang City in 2019. This study uses a qualitative method using descriptive analysis techniques. Theresults of the study indicate that optimizing the role of crew officers at the Ministry of Religion office in Tangerang City in 2019 has an important task in guiding the journey of pilgrims so that it becomes a smooth and useful pilgrimage. Regarding the duties and functions of the crew members at the Tangerang City Ministry of Religion, it has been effective in supporting the success of the Hajj pilgrimage. The obstacles faced by the crew during the pilgrimage included: the placement of pilgrims in 2 different Medina hotels, pilgrims who could only speak the local language and older pilgrims.Keywords : Role, Cluster Officer, Hajj
OPTIMALISASI ZAKAT PERUSAHAAN DALAM PENGEMBANGAN KOPERASI SYARIAH PONDOK PESANTREN
Authors: Mono Derys
Published: August 2024

Kesimpulan tulisan ini adalah bahwa dalam upaya mengoptimalisasi zakat perusahaan dalam pengembangan koperasi syariah pondok pesantren melalui beberapa pendekatan. Pertama; optimal dalam pengumpulan zakat perusahaan. Kedua: optimal dalam pendistribusian dan penyaluran zakat perusahaan yaitu dengan pendekatan zakat produktif, 1) zakat produktif tradisional, 2) zakat produktif kreatif, 3) zakat produktif beasiswa pelatihan seputar koperasi syariah 4) zakat produktif berupa sarana-pra sarana
PENGELOLAAN DAN PENGEMBANGAN WAKAF BERBASIS MASJID (STUDI KASUS MASJID RAYA MUHAMMADIYAH USWATUN HASANAH)
Authors: Yumna Laila , Bariyah Oneng Nurul , Riani Dede , Fadilah Hilal Ainun , Sabita Najmah
Published: August 2024

Paper ini menjelaskan model pengelolaan dan pengembangan yang dilakukan oleh nadzir dalam mengelola aset wakaf berupa masjid. Metode penelitian yang digunakan yaitu deskriptif analisis dengan pengumpulan data melalui observasi dan wawancara yang dilaksanakan di Masjid Raya Muhammadiyah Uswatun Hasanah. Hasil yang diperoleh dari penelitian ini bahwa model pengelolaan dan pengembangan aset wakaf di Masjid Raya Muhammadiyah Uswatun Hasanah dilakukan dengan berbagai aktifitas dalam beberapa sektor diantaranya pendidikan, kesehatan dan ekonomi yang meliputi kajian keislaman, pemenuhan kebutuhan pangan, pelaksanaan nikah, khitan dan bekam gratis, pembagian ifhtar untuk musafir dan fasilitas warung umat.
IMPLEMENTASI BAURAN PROMOSI DALAM MENINGKATKAN JUMLAH JAMAAH UMRAH PT ARMINAREKA PERDANA JAKARTA PUSAT
Authors: Kusumaningsih Navira
Published: August 2024

The purpose of this study is to find out how the Implementation of The Promotion Mix in Increasing the Number of Umrah Pilgrims of PT Arminareka Perdana and to know the supporting factors and inhibitions of promotional mix activities at PT Arminareka Perdana. The research method used is a qualitative method with a descriptive approach and uses data collection techniques through interviews, observations, and documentation.From the results of the research it can be concluded that the promotional mix used by PT Arminareka Perdana is in accordance with kotler and Armstrong's theory which states that the variables contained in the promotional mix there are five, namely advertising in the form of brochures and company profiles printed. Sales promotion through incentives, ease of installment of Umrah costs and follow travel fair activities. Public relations through publicity, lobbying, building trust and good relationships, as well as being responsible. Personal sales through a process of approaching, presenting, and overcoming objections. Direct marketing by phone, WhatsApp, television, website, e-mail, blog. Keywords : Implementation and Promotional Mix
Clinical Indications for and Outcomes of Reoperation in Adult Tetralogy of Fallot Patients in Japan: A Nationwide Retrospective Study
Authors: Mizuno Atsushi , Ueno Takayoshi , Tateno Shigeru , Inai Kei , Adachi Osamu , Yamamura Kenichiro , Yamazawa Hirokuni , Koide Masaaki , Waki Kenji , Ichikawa Hajime , Matsuo Kozo , Shiraishi Isao , Niwa Koichiro ,   Research Committee, Japanese Society for Adult Congenital Heart Disease
Published: August 2024

Background: Reoperation significantly improves outcomes in tetralogy of Fallot (TOF) patients. However, it is challenging to determine the timing for surgery, especially with complex indications, such as pulmonary regurgitation (PR) with right ventricular outflow tract stenosis or tricuspid regurgitation. Methods: This retrospective study analysed adult TOF patients who underwent reoperation at specialised centres between 2000 and 2015. Exclusions included pulmonary atresia with ventricular septal defect repaired by an extracardiac conduit, double-outlet right ventricle with subaortic ventricular septal defect and pulmonary stenosis and pulmonary atresia. Surgeons determined the primary reoperation indication. Results: Of 154 patients (59.1% male, mean age 35.2 ± 12.0 years), from 10 hospitals, eight deaths (5.2%) occurred over 5.7 years (range 2.5–8.0 years) post-reoperation. The main indications for reoperation were PR, right ventricular outflow tract stenosis, and tricuspid regurgitation (62.3%, 24.0% and 18.2%, respectively). Patients with PR showed more variability in preoperative right ventricular end-diastolic volume index values, particularly without concurrent indications. Conclusion: This study sheds light on reoperation outcomes in Japanese TOF patients before percutaneous treatment availability. Surgical decisions, especially with concurrent indications, need adaptable approaches. Despite the absence of a consensus on preoperative evaluation and thresholds for reoperation, our findings may support current surgical decision-making.
Metadata of environmental and abiotic variables of wells in Benin (West Africa)
Authors:   Université d'Abomey-Calavi, Bénin, Hotèkpo Sourou Joseph , Namiotko Tadeusz , Lagnika Moïssou , Ibikounlé Moudachirou , Martin Patrick , Schön Isa , Martens Koen
Published: August 2024

The database comprises georeferenced data on Benin's wells, their attributes, and a series of physical and chemical variables for the water samples.
Considerations for Precast Concrete Girder End Regions with Large-Diameter Strands
Authors: Harries Kent A. , Liu TianQiao , Shahrooz Bahram M. , Miller Richard A. , Castrodale Reid W.
Published: August 2024

Strand debonding patterns and release (prestress trans¬fer) practices can result in significant local stresses at prestressed girder ends, which are not accounted for in design. This article presents a numerical and analytic study of various single-webbed prestressed concrete girder shapes for which large amounts of prestressing are necessitated by the use of 0.7 in. (17.8 mm) diame¬ter strands. Shapes with wide bottom flanges are shown to potentially exhibit large stresses that effectively pry, or peel, the portions of the flanges extending from the web away from the web. Such peeling stresses can be mostly mitigated by partially debonding strands in the recommended pattern from the outside in. Simi¬larly, releasing or cutting strands in a uniform manner mitigates peeling stresses. While releasing all strands simultaneously is optimal, it is unlikely to be practical for large prestressed components. For conventional release operations, the results presented in this article indicate that a symmetrical top-down method would not result in significant peeling stress. Moreover, pre¬stressed girder end region detailing requirements aimed at providing adequate flange confinement and strand anchorage at the ultimate limit would be adequate to control peeling stresses, including those resulting from the inadvertent use of a poor release sequence.
Modeling of the results of laser correction of hyperopia by the methods of cluster and discriminant analysis
Authors:   National Medical Research Center ", Kulikova Irina ,   Eye Microsurgery", Pikusova Svetlana , Kornikov Vladimir ,   Saint Petersburg State University, Davydenko Bogdan , Bauer Svetlana
Published: August 2024

Statistical methods are used to solve the problem of evaluating refractive results in patients The issue of optimizing refractive laser surgeries for hyperopia correction remains relevant, as current keratorefractive surgery methods for hyperopia are less predictable, effective, and stable compared to myopia correction. This non-randomized retrospective study includes the results of 161 patients who underwent FemtoLASIK laser correction at the Cheboksary branch of National Medical Research Center "Eye Microsurgery". The average age of the patients was 41.9 years. Evaluations were conducted before sur-gery and on the third day postoperatively using standard examination methods, including uncorrected and best-corrected visual acuity, refractometry, non-contact tonometry, biomicroscopy, keratotopography, anterior segment analyzer examination, and fundus examination, among other parameters. Through cluster and discriminant analyses, a "risk group" was identified, showing the least accuracy in postoperative spherical equivalent and the lowest visual acuity indicators. A rule was developed to categorize eyes into one of the groups. The best refractive outcomes were observed in the low-degree hyperopia group, while the "risk group" included patients with high-degree hy-peropia, either alone or in combination with astigmatism. Pairwise comparisons indicat-ed that cases from the "risk group" more frequently fell into groups with the highest (by absolute value) cylindrical component of refraction and the lowest spherical equivalent postoperatively, explaining the low uncorrected and best-corrected visual acuity indica-tors. High-degree hyperopia requires longer laser ablation time, which can lead to corneal dehydration and uneven ablation, as well as the induction of higher-order aberra-tions and astigmatism formation. Accommodative disorders in hyperopic patients may lead to prolonged myopic refraction postoperatively. Correction of low and moderate hyperopia using FemtoLASIK shows more accurate results compared to high-degree hyperopia correction. To improve outcomes, it is necessary to consider the degree of hyperopia, age, accommodative apparatus tone, presence of optical correction, binocu-lar interaction characteristics, and Kappa angle during surgery planning and postoper-ative management. These measures can lead to more predictable and stable results, reduce the risk of complications, and enhance patient satisfaction with the treatment.
Ser Buddha, Ficar Woke : Formação Racial na Escrita Budista Negra
Authors: Santos Atila Augusto , Coyle Joe
Published: August 2024

Este artigo desafia as explorações acadêmicas do orientalismo como interação entre um Ocidente branco e um Oriente asiático no contexto das comunidades budistas americanas. Tomando como foco escritos semiautobiográficos dos séculos XX e XXI de budistas ne
Mianowanie proboszcza na czas określony (kan. 522 KPK)
Authors: Adamczyk Jerzy
Published: August 2024

Celem artykułu jest ukazanie zagadnienia mianowania proboszcza na czas określony zgodnie z kan. 522 KPK. W jego pierwszej części przedstawiono następujące zagadnienie: proboszcz własnym pasterzem zleconej sobie parafii. W drugiej części ukazano kwestię możliwości mianowania proboszcza na określoną kadencję według kan. 522 KPK, natomiast część trzecia została poświęcona normom komplementarnym konferencji episkopatów dotyczącym mianowania proboszczów na określony czas. Całość artykułu zamyka podsumowanie i bibliografia.
IoT-based Image Encryption: Analysis and Implementation Strategies
Authors: Mishra Prateek .
Published: August 2024

With the proliferation of Internet of Things (IoT) devices, securing image data transmitted across diverse and often vulnerable networks has become a critical concern. This paper explores IoT-based image encryption methods, focusing on the analysis and implementation strategies to enhance data security in IoT environments. We begin by surveying existing encryption techniques and their suitability for IoT applications, highlighting the unique challenges posed by constrained devices, limited computational resources, and varying network conditions. Our analysis includes a comparison of traditional encryption algorithms with advanced cryptographic methods specifically adapted for IoT contexts. We then propose a novel image encryption framework tailored for IoT devices, emphasizing efficiency and scalability. This framework integrates lightweight encryption algorithms and adaptive key management strategies to balance security and performance. Experimental results demonstrate the effectiveness of our approach in terms of encryption strength, computational overhead, and energy consumption. The findings offer valuable insights into optimizing image encryption for IoT systems, contributing to the development of more secure and efficient IoTbased image transmission solutions.
A Comparative Study of Plant-Based Coagulants for Water Purification: Performance and Sustainability
Authors: Hoonka Vaibhav , Tiwari Manish , Khare Arun Kumar , Tiwari Preeti , Jain Pranshul
Published: August 2024

Water purification remains a critical global challenge, particularly in developing regions where access to clean water is limited. Traditional chemical coagulants, while effective, pose environmental and health risks. This research paper compares the performance and sustainability of various plant-based coagulants in water purification. The study evaluates the efficacy of Moringa oleifera, Opuntia spp., and Cicer arietinum in reducing turbidity and improving water quality. Additionally, it examines the environmental impact, cost-effectiveness, and potential health benefits of using plant-based coagulants. The findings highlight the promising potential of plant-based coagulants as sustainable alternatives to chemical coagulants in water treatment.
An Approach for Hairstyle Recommendation using Machine Learning
Authors: Paranjape Vishal , Sharma Saurabh , Singh Abhishek , Zohaib Hasan Zohaib Hasan
Published: August 2024

Aesthetic assessments indicate that hair is a distinctive feature that can significantly enhance facial appearance. According to beauty experts, approximately 70% of a person's overall facial look is influenced by their haircut or hairstyle. Haircuts play a crucial role in shaping women's self-perception, making the choice of a suitable hairstyle a challenging decision. This paper introduces an innovative framework for selecting the ideal hairstyle or haircut by first classifying the face shape. The model integrates facial shape analysis, expertise in hairstyles, and hair length to recommend the most fitting options. Focused primarily on women's hairstyles, this framework addresses a specific segment within the broader field. Recognizing face shape is considered a vital preliminary step for choosing the appropriate hairstyle. The proposed model classifies face shapes from user-uploaded portraits using machine learning techniques to identify facial landmarks. A Naïve Bayes classifier then recommends suitable hairstyles based on the detected face shape, hair length, and input from hair experts. Users can share their recommended styles with beauticians through "The Beauty Quest" Salon network platform. The system was trained with 5,000 images using Python, achieving a 91% accuracy rate in face shape classification and an 83% accuracy rate in hairstyle recommendations.
Exploring Naive Bayes for Movie Review
Sentiment Classification
Authors: Hasan Zohaib , Singh Abhishek , Paranjape Vishal , Sharma Saurabh
Published: August 2024

This study investigates the performance of Naive Bayes and Logistic Regression classifiers in sentiment
analysis of movie reviews using two feature extraction methods: Bag of Words (BoW) and Term Frequency-Inverse
Document Frequency (TF-IDF). We utilized a dataset of 50,000 IMDB reviews, preprocessed through denoising, stop
word removal, and stemming. The reviews were then vectorized using BoW and TF-IDF techniques. Our analysis
reveals that Logistic Regression outperforms Naive Bayes in terms of accuracy, with Logistic Regression achieving
89.52% accuracy for BoW and 89.23% for TF-IDF, while Naive Bayes obtained 85.01% and 85.74%, respectively.
Despite its slightly lower accuracy, Naive Bayes demonstrates a consistent performance with a minimal gap between
training and testing accuracies, suggesting robust generalization capabilities. The findings indicate that while Logistic
Regression is superior in accuracy, Naive Bayes remains a competitive choice due to its simplicity and consistent
performance across different feature extraction methods. This comparison provides valuable insights for selecting
appropriate classifiers and feature extraction methods for text classification tasks in sentiment analysis.
Integrating Smart Technologies for Enhanced Indoor Environmental Quality: A Review of Recent Innovations
Authors: Sahu Ranu , Verma Saurabh , Maravi Indu , Kumar Umesh
Published: August 2024

The rising need for enhanced indoor environmental quality (IEQ) is driven by the changing urban landscape and increased awareness of the influence of indoor environments on health and well-being. With ongoing urban expansion and technological advancements, it is vital to integrate smart technologies that improve IEQ while optimizing energy efficiency. This paper explores the development and deployment of sophisticated smart building systems that address these needs through the use of sensors, data analytics, and automation. Recent innovations have revolutionized indoor environment management by utilizing real-time data and adaptive technologies. For instance, occupancy-based energy management systems, as outlined by Agarwal et al. (2010) and Balaji et al. (2013), enhance energy efficiency by adjusting HVAC operations according to actual occupancy levels [2][4]. Furthermore, wearable sensors for tracking physiological data, investigated by Adib et al. (2015) and Choi et al. (2009), present new opportunities for improving individual comfort and health through real-time environmental adjustments [1][7]. Moreover, recent research underscores the significance of managing thermal comfort and indoor air quality, where smart technologies have made considerable progress. Systems examined by Clear et al. (2013) and Gottscho et al. (2017) demonstrate how adaptive technologies can effectively balance thermal comfort and energy usage [8][16]. These systems use data from environmental sensors and user feedback to continuously optimize indoor conditions. The proposed method achieved an accuracy of 97.6%, with a mean absolute error (MAE) of 0.406 and a root mean square error (RMSE) of 0.208, highlighting its effectiveness in practical applications. This paper presents a thorough review of recent advancements in smart technologies for enhancing IEQ, analyzing various smart building systems, and detailing improvements in sensor technology, data-driven control mechanisms, and their impact on energy efficiency and occupant satisfaction. The aim is to provide an overview of current innovations, evaluate their impact, and identify future research directions in smart building automation.
Challenges and Opportunities in AI Applications: A Sector-Wise Analysis
Authors: Choubey Khushboo , Anjum Gulafsha , Anjum Kaynat
Published: August 2024

Artificial intelligence (AI) has transitioned from the realm of science fiction to a cornerstone of modern technology, permeating various aspects of daily life and industries. AI, defined as the capability of a machine to imitate intelligent human behavior, has experienced rapid advancements in both theoretical and practical domains. The transformative power of AI lies in its ability to analyze vast amounts of data, recognize patterns, and make decisions with minimal human intervention. This research paper explores the diverse applications of artificial intelligence across different sectors, including healthcare, finance, transportation, and entertainment, highlighting both the benefits and the challenges posed by this revolutionary technology. Significant improvements in diagnostic accuracy and treatment personalization have been observed in the healthcare industry through AI-driven tools. In finance, AI algorithms optimize trading strategies, detect fraudulent activities, and enhance customer service through chatbots and personalized financial advice. The transportation sector benefits from AI in the development of autonomous vehicles, improving safety and efficiency on the roads. In entertainment, AI is reshaping content creation, recommendation systems, and interactive experiences. Despite the remarkable progress, the integration of AI into various fields raises critical ethical and societal concerns. Issues such as data privacy, algorithmic bias, and the displacement of jobs due to automation necessitate ongoing dialogue and regulation. The proposed method demonstrates an accuracy of 96.6%, with a mean absolute error (MAE) of 0.406 and a root mean square error (RMSE) of 0.207. This paper provides a comprehensive overview of the current state of AI applications, shedding light on both its potential to drive innovation and the imperative to address the accompanying challenges.
Advanced Threat Detection Systems for Protecting Critical Infrastructure
Authors: Verma Saurabh , Pali Pankaj , Kori Pavani , Tiwari Muskan
Published: August 2024

As critical infrastructure increasingly relies on digital technologies and interconnected systems, the security landscape becomes more complex, necessitating advanced threat detection systems to protect these essential assets. This paper reviews contemporary approaches and technologies for threat detection in critical infrastructure, including machine learning algorithms, anomaly detection techniques, and hybrid security models. It investigates the effectiveness of these systems in real-time monitoring, integration of advanced analytics, and the use of predictive models to anticipate and mitigate potential threats. The paper also addresses key challenges such as managing false positives, ensuring scalability, and integrating new systems with existing security frameworks. Through case studies and recent advancements, the impact of innovative solutions on enhancing infrastructure resilience is evaluated. The study concludes that while progress is notable, ongoing research is essential to address evolving threats and improve the effectiveness of threat detection systems in a dynamic security environment.
"Advancements in Natural Language
Processing: Integrating Machine Learning for
Enhanced Accuracy and Precision"
Authors: Vishwakarma Abhishek , Paranjape Vishal , Singh Abhishek
Published: August 2024

Natural Language Processing (NLP) has emerged as a transformative technology within the domain of
artificial intelligence, significantly advancing the ability of machines to comprehend and interact with human language.
Recent advancements in machine learning algorithms have led to substantial improvements in a variety of NLP
applications, including sentiment analysis, machine translation, automated summarization, and question answering.
This study presents a novel approach to NLP, which integrates advanced machine learning techniques to enhance
performance in these areas. The proposed method achieves a high level of accuracy, with an overall accuracy rate of
97.6%. Additionally, it demonstrates strong performance in error metrics, including a Mean Absolute Error (MAE) of
0.403 and a Root Mean Square Error (RMSE) of 0.203. These results indicate a significant advancement in the
precision and effectiveness of language-based tasks. Despite these achievements, challenges such as the management of
ambiguous language, the need for extensive annotated datasets, and the demand for real-time processing capabilities
remain. This paper aims to explore the current state of NLP driven by machine learning, examining key techniques and
methodologies that have propelled its development. The analysis will cover various machine learning approaches
applied to NLP, evaluate their impact on different applications, and identify ongoing challenges and future research
directions. By providing a comprehensive overview of the interplay between NLP and machine learning, this research
seeks to enhance understanding of how these technologies can be leveraged to improve language processing and
communication
High-Throughput Sequencing and Advanced Computational Methods: Revolutionizing Genomic Data Analysis
Authors: Pateriya Nidhi
Published: August 2024

: The advent of high-throughput sequencing technologies has revolutionized the field of genomics,
generating vast amounts of genetic data at an unprecedented scale and resolution. This explosion of data presents both
extraordinary opportunities and significant challenges. The sheer volume and complexity of genomic data necessitate
advanced computational methods for efficient analysis and interpretation. Genomic data analysis encompasses a range
of techniques and tools designed to process, manage, and derive meaningful insights from genetic sequences. Central to
genomic research is the imperative to understand the genetic basis of health and disease. Computational methods
facilitate the identification of genetic variations, elucidate their implications, and predict phenotypic outcomes. These
methods include sequence alignment, variant calling, functional annotation, and integrative analyses that merge genetic
data with other biological information. The application of machine learning and artificial intelligence in genomic data
analysis further enhances the capacity to detect patterns and make predictive inferences. As the field evolves, the
integration of computational approaches with biological research continues to deepen the understanding of complex
genetic architectures and the molecular underpinnings of various traits and diseases. This paper explores the current
computational strategies employed in genomic data analysis, highlighting their applications, advantages, and
limitations. The proposed computational method for genomic data analysis demonstrates high accuracy and reliable
performance metrics. The method achieves an accuracy of 95.8%, indicating a high level of precision in the analysis
and interpretation of genetic data. The performance is further validated by a Root Mean Squared Error (RMSE) of
0.206 and a Mean Absolute Error (MAE) of 0.405. These metrics reflect the method's capability to provide consistent
and precise results, making it a robust tool for genomic data analysis. Advancing these methodologies has the potential
to unlock the full potential of genomic data, driving innovations in personalized medicine, evolutionary biology, and
beyond.
Predictive Analytics for Student Performance: A Machine Learning Model for Higher Education
Authors: Pali Pankaj , Verma Sourabh
Published: August 2024

The dynamic landscape of higher education necessitates innovative approaches to enhance academic success and student performance. Traditional methods of evaluating and supporting student achievement frequently fall short in addressing the diverse and evolving needs of modern learners. This research explores the application of machine learning (ML) to predict student performance in higher education, aiming to develop a predictive model that can identify at-risk students early and enable targeted interventions. The study analyzes various factors influencing student performance, including demographic information, academic history, behavioral data, and socio-economic status. The proposed model demonstrates a high degree of accuracy, with an accuracy rate of 98.8%, a mean absolute error (MAE) of 0.402, and a root mean square error (RMSE) of 0.202. These metrics underscore the model's precision and reliability in predicting student outcomes. The significance of this research lies in its potential to transform educational practices by providing a data-driven framework for decision-making. Accurate predictions of student performance enable educational institutions to allocate resources more effectively, enhance student engagement, and ultimately improve graduation rates. Furthermore, this study contributes to the growing body of knowledge in educational data mining and learning analytics, offering insights that can be generalized across different educational contexts. This research aims to demonstrate the efficacy of machine learning in enhancing academic success and to provide a roadmap for future studies in this domain.
AI in Social Media: Navigating the Balance
between User Engagement and Misinformation
Authors: Niveditha Kalukuri Princy
Published: August 2024

In the current digital age, social media has emerged as a formidable entity influencing public discourse,
shaping behaviors, and redefining communication norms. Central to this evolution is Artificial Intelligence (AI), a
technology that has rapidly advanced and now exerts a significant impact across various societal domains. The
integration of AI into social media platforms manifests in numerous ways, including personalized content
recommendations, advanced chat bots, and automated content moderation systems. The intersection of AI and social
media introduces both opportunities and challenges. AI algorithms enhance user experiences by customizing content to
individual preferences, thus fostering increased engagement and satisfaction. Conversely, these algorithms may also
contribute to the formation of echo chambers, the proliferation of misinformation, and heightened concerns regarding
privacy and data security. A comprehensive understanding of AI's impact on social media necessitates a detailed
analysis of how these technologies affect content dissemination, user interaction, and the broader socio-political
environment. This study employs a rigorous methodological framework to assess the effectiveness of AI-driven
systems in social media. The proposed method achieves an accuracy of 96.6%, with a Mean Absolute Error (MAE) of
0.403 and a Root Mean Square Error (RMSE) of 0.203. By examining recent advancements and pertinent case studies,
this research provides a thorough overview of how AI-driven technologies are transforming the social media landscape,
highlighting both the advantages and the challenges associated with this transformation.
Enhancing Urban Mobility Management: A Machine Learning Approach to Real-Time Traffic Congestion Prediction
Authors: Pali Prof. Pankaj , Verma Prof. Saurabh
Published: August 2024

Traffic congestion continues to pose a significant challenge in urban environments, affecting economic efficiency, environmental sustainability, and overall quality of life. Traditional traffic management methods often fail to address the complexities of contemporary traffic systems. However, recent advancements in machine learning (ML) and data analytics present new opportunities for real-time traffic congestion detection and prediction. This study examines the application of various ML algorithms to enhance traffic management by analyzing extensive real-time data. The proposed approach achieved an accuracy of 93.4%, with a mean absolute error (MAE) of 0.509 and a root mean square error (RMSE) of 0.405. Utilizing advanced techniques such as neural networks, ensemble learning, and reinforcement learning, the study aims to improve traffic flow management and contribute to the development of more responsive urban transportation systems. The findings underscore the potential of ML algorithms to offer significant improvements over traditional methods, providing a framework for the effective implementation of these technologies in urban mobility solutions.
Adaptive and Resilient Watermarking Techniques for Real-Time Data Streams in Cloud Computing
Authors: Verma Prof. Saurabh , Pali Prof. Pankaj , Tiwari Ayush , Patel Srajal
Published: August 2024

Ensuring the security of real-time data streams in cloud computing environments is critical for data integrity and privacy. This paper presents an innovative approach that combines adaptive watermarking techniques with artificial intelligence (AI) to enhance the protection of real-time data streams. The proposed method utilizes dynamic, resilient watermarking schemes optimized by AI algorithms, ensuring robust protection against unauthorized access and tampering while maintaining the quality of data. Experimental results demonstrate significant improvements in security and resilience compared to traditional watermarking methods, highlighting the effectiveness of this approach for safeguarding real-time data streams in cloud environments.