bluuebunny/crossref_metadata_2025 huggingface dataset:
Concurrent Cerebral Thrombophlebitis and Nonfunctioning Pituitary Adenoma in a Postpartum Woman: A Rare Coexistence and Diagnostic Challenges
Authors:   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco, A Boubekri , H Bellamlih ,   Radiology Department, Moulay-Ismail Military Hospital, Meknes, Sidi Mohamed Ben Abdellah University, Fez, Morocco, M Ababou ,   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco, W Atmani ,   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco, M Meziane ,   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco, A Jaafari ,   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco, A Baite ,   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco, M Bensghir ,   Department of Anesthesiology and Intensive Care, Mohammed V University, Morocco
Published: April 2024

This case report presents a rare occurrence of concurrent cerebral thrombophlebitis and nonfunctioning pituitary adenoma in a postpartum woman. Cerebral thrombophlebitis is a rare condition that can manifest with diverse clinical presentations, posing diagnostic challenges. The patient, a 30-year-old primipara, presented with progressive vision loss, diplopia, and intense frontal headaches shortly after childbirth. Magnetic resonance angiography revealed thrombophlebitis in the right lateral sinus extending into the ipsilateral internal jugular vein, along with a large suprasellar lesion suggestive of a pituitary macroadenoma. Ophthalmological examination revealed papilledema and ptosis. Laboratory analyses ruled out hormonal abnormalities associated with pituitary adenomas. The patient received intravenous methylprednisolone and therapeutic anticoagulation, resulting in neurological and ophthalmological improvements. Subsequently, the patient underwent transsphenoidal resection. This case highlights the diagnostic and management challenges associated with rare postpartum conditions and emphasizes the importance of comprehensive evaluation and multidisciplinary care in such cases.
Pregnancy-Associated Cancer: A Case Report of a Gastric Cancer Diagnosis in the III Trimester of Pregnancy and Subsequent Management
Authors:   Department of Medical Sciences, Institute of Obstetrics and Gynecology, University of Ferrara, Italy, A Sabattini , D Morano ,   Department of Medical Sciences, Institute of Obstetrics and Gynecology, University of Ferrara, Italy, P Greco ,   Department of Medical Sciences, Institute of Obstetrics and Gynecology, University of Ferrara, Italy
Published: April 2024

The co-occurrence of gastric carcinoma and pregnancy is very rare event. Diagnosis is often delayed, frequently at an advanced stage due to the nonspecific symptomatology, which can be confused with the normal physiological symptoms of pregnancy. Therefore, a multidisciplinary approach is essential to initiate the treatment of maternal pathology as early as possible, with the goal of delivering at a moderately preterm gestation age to ensure favorable neonatal outcome. We present a case of gastric carcinoma diagnosed during the third trimester, where the earliest presentation included liver metastases, and the primary tumor’s location was unknown. Throughout our observation period, we conduced clinical-laboratory monitoring, a preliminary radiological staging of the illness (considering the limitations imposed by pregnancy), and a histological diagnosis with biopsy sampling. An elective cesarean section was performed in the moderately preterm period, following the completion of Respiratory Distress Syndrome (RDS) prophylaxis.
The Use of Forensic Musicology in Criminal Investigations
Authors:   CAMB, University of the Punjab, Lahore, Pakistan, Z Zaroon , Rashid Jumana ,   CAMB, University of the Punjab, Lahore, Pakistan, Iftikhar Anwaar ,   CAMB, University of the Punjab, Lahore, Pakistan, Bashir Hamid ,   CAMB, University of the Punjab, Lahore, Pakistan, Parveen Rukhsana ,   CAMB, University of the Punjab, Lahore, Pakistan
Published: April 2024

Forensic musicology is the scientific study of music in a legal context. It can be used to help identify the composer of a piece of music, to determine the ownership of a copyright, or to resolve disputes over the use of musical works. Forensic musicologists may also be called upon to give expert testimony in court cases involving questions of music. Forensic musicology is a relatively new field, and there are no formal educations or training requirements for becoming a forensic musicologist. However, most forensic musicologists have advanced degrees in music theory, musicology, or a related field, and many also have experience working as professional musicians. Forensic musicologists use their knowledge of musical composition, history, and performance to answer questions raised in legal cases. Forensic musicologists typically collaborate with attorneys, judges, and other legal professionals to provide expert testimony or analysis in court cases. In some cases, they may also be asked to testify in front of a grand jury or give depositions. Forensic musicologists may also be consulted by law enforcement agencies to help identify unknown pieces of music or to authenticate recordings. This review will focus on the application of forensic musicology in civil and criminal cases.
A Case Report on the Toxicological Evaluation of Pyridaben from a Human Cadaver
Authors:   Crime Scene Management Division, Forensic Science Laboratory, New Delhi, India, Gautam Ajay Kumar , Paul Subhra Kumar ,   Chemistry Division, Forensic Science Laboratory, New Delhi, India, Verma Deepa ,   Director, Forensic Science Laboratory, New Delhi, India
Published: April 2024

Suicidal poisoning with pesticides in humans is common in India. Despite the interdiction or regulation of several pesticides, there are reported considerate poisoning cases in India. Pyridaben is a potentially fatal insecticide with extreme neurotoxicity in humans. Pyridaben toxicity reports in humans are uncommon. Here we describe a case of acute poisoning with Pyridaben in a minor girl who presented with severe nausea, vomiting, altered consciousness, body weakness, abdomen pain, and congestion of visceral organs. Soon after the poisoning, the patient was treated with life-saving mechanical ventilation. Forensic examination of the viscera of a minor victim enlightened that the death was assignable to Pyridaben intoxication. GC-MS analysis of viscera showed significant results in concern to the identification of Pyridaben. The present case study emphasized the misuse of readily accessible pesticides and identified a new pesticide that can exert a deleterious impact on human health deliberately (suicide) and unintentionally (accidental) exposure. The same needs to be communicated to the scientific community to explore this lethal pesticide for its all-possible detrimental impacts consequently gathering scientific evidence in this regard will abet to regulate it by legislative.
Quality Assurance in Digital Forensic Investigations: Optimal Strategies and Emerging Innovations
Authors:   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan, Iftikhar Anwaar , Farooq Rida ,   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan, Mumtaz Mehvish ,   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan, Hussain Sana ,   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan, Akhtar Mubeen ,   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan, Ali Muhammad ,   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan, Jahngir Ghulam Zahara ,   Centre for Applied Molecular Biology, University of Punjab, Lahore, Pakisthan
Published: April 2024

Digital forensic investigations are critical in modern law enforcement, cybersecurity, and legal proceedings. Ensuring digital evidence’s accuracy, integrity, and reliability is paramount in these contexts. This review article explores the challenges and best practices associated with quality control in digital forensic investigations and the emerging technologies that are reshaping the field. The article begins by discussing the foundational concepts of quality control in digital forensics, emphasizing the need for standardized procedures, documentation, and validation techniques. It delves into the potential sources of errors and bias that can arise during the acquisition, preservation, analysis, and presentation of digital evidence. It highlights the importance of continuous monitoring and review to mitigate these risks. The review article further examines the evolving landscape of digital forensic tools and technologies advancing quality control efforts. It covers advancements in data acquisition methods, including live forensics and memory analysis, and discusses the role of artificial intelligence and machine learning in automating quality control processes. The integration of Blockchain and cryptographic techniques for ensuring the integrity of digital evidence is also explored. In addition, the article addresses the challenges and opportunities presented by cloud computing, IoT devices, and the proliferation of digital data sources. It emphasizes adaptability and agility in quality control approaches to accommodate the changing digital landscape. Through a comprehensive analysis of established practices and emerging technologies, this review article offers practitioners, researchers, and policymakers’ insights into enhancing the reliability and trustworthiness of digital forensic investigations. By adopting robust quality control measures and embracing innovative technologies, the digital forensics community can ensure its findings hold up to scrutiny in the courtroom and beyond.
Flatfoot in Children: A Review of Literature (Point of View)
Authors:   Department of Orthopaedic and Trauma Surgery, ASL Bari, Italy, S Bernardino
Published: April 2024

Flatfoot (pes planus) is described as a reduction or absence of the Medial Longitudinal Arch (MLA) of the foot, with or without additional deformities of the foot and ankle. It is a very common orthopedic manifestation in infants and children and usually resolves by adolescence. Flatfoot is usually flexible and painless with no functional compromise so that described as physiologic. In some rare cases flatfoot can become painful or rigid and may be a sign of pathology such as vertical talus or tarsal coalition. Although it is very common, there is no standard definition and no universally accepted classification system for pediatric flatfoot. Furthermore there are no large, prospective studies comparing the natural history of flatfoot in response to various treatments during the developmental period. Current literature suggests that it is safe and appropriate to simply observe an asymptomatic child with flatfoot. Painful flexible flatfoot may benefit from orthopedic intervention such as physical therapy, orthosis or sometimes a surgical procedure.
Esophageal Stricture -Unusual Presentation of CMV
Authors:   Department of Gastroenterology, SVP Hospital, India, Shah Dhruv , Narang Sushil ,   Department of Gastroenterology, SVP Hospital, India, Vyas Kaushal ,   Department of Gastroenterology, SVP Hospital, India, Gupta Animesh ,   Department of Gastroenterology, SVP Hospital, India, Berriwala Vishal ,   Department of Gastroenterology, SVP Hospital, India
Published: April 2024

Esophageal stricture due to Cytomegalovirus (CMV) infection is an uncommon pathology, with most reported cases occurring in patients infected with human immunodeficiency virus. We report a case who presented with Odynophagia followed Dysphagia to solids gradually progressive from last 3 weeks with Total Dysphagia to solids and liquids on presentation. Endoscopic examination revealed a long esophageal stricture with a necrotic lesion but no typical CMV esophageal ulcers, with foreign body impaction in form of beans. Histology was positive for CMV. Dysphagia resolved after treatment with ganciclovir and serial esophageal dilations. We are presenting the first case of esophageal stricture due to CMV esophagitis in a young adult with chronic alcoholism and are reviewing current literature.
Benchmarking ML in ADMET predictions: the practical impact of feature representations in ligand-based models
Authors: Kamuntavičius Gintautas , Paquet Tanya , Bastas Orestis , Šalkauskas Dainius , Prat Alvaro , Aty Hisham Abdel , Norvaišas Povilas , Tal Roy
Published: April 2024

This study, focusing on predicting Absorption, Distribution, Metabolism, Excretion, and Toxicology (ADMET) properties, addresses the key challenges of ML models trained using ligand-based representations. We propose a structured approach to data feature selection, taking a step beyond the conventional practice of combining different representations without systematic reasoning. Additionally, we enhance model evaluation methods by integrating cross-validation with statistical hypothesis testing, adding a layer of reliability to the model assessments. Our final evaluations include a practical scenario, where models trained on one source of data are evaluated on a different one. This approach aims to bolster the reliability of ADMET predictions, providing more dependable and informative model evaluations.
A New Reagent to Access Methyl Sulfones
Authors: Mykhailiuk Pavel K. , Poplavsky Yaroslav , Ripenko Vasyl , Bova Sergei , Biitseva Angelina , Dmitriv Yurii V. , Tolmachev Andrei A. , Sadkova Iryna V. , Phan Vo Quang Huy , Dias H. V. Rasika
Published: April 2024

A new chemical reagent to access methyl sulfones has been developed. Its reaction with various bis-nucleophiles leads to the rapid formation of previously unknown heteroaromatic methyl sulfones. Analogous strategy can also be used to construct alkyl-, CHF2-, CF3- and even bicyclo[1.1.1]pentane-containing derivatives. These compounds have been demonstrated to have a high potential for use in medicinal chemistry and coordination chemistry.
Methylthio-D-ribose-1-Phosphate Isomerase Uses a Novel Mechanism for Aldose–Ketose Isomerization
Authors: Murkin Andrew , Ubayawardhana Subashi
Published: April 2024

The enzyme-catalyzed interconversion of aldoses and ketoses historically involves one of two mechanisms, both of which require an aldehyde form of the substrate. Methylthio-D-ribose-1-phosphate (MTR1P) isomerase (MtnA), which functions in the methionine-salvage pathway, poses a challenge to this canon because its substrate cannot readily access such a form. In converting MTR1P to its ketose isomer, methylthio-D-ribulose 1-phosphate, MtnA must catalyze opening of the ribofuranose ring and hydrogen transfer between C-2 and C-1. Primary 2H and 13C kinetic isotope effects measured at these positions in MTR1P and ribose 1-phosphate indicate that these two events occur in a common and rate-limiting step with respect to kcat/KM. An inverse kinetic solvent viscosity effect and inverse solvent kinetic isotope effect were measured for this constant, implicating an open–closed protein conformational change after substrate binding and the participation of Cys160 as the catalytic base responsible for shuttling the proton between C-1 and C-2. An E2 elimination–tautomerization sequence is most consistent with these findings and represents a third mechanism for enzymatic aldose–ketose isomerization.
Synthesis, characterization and photophysical properties of a new family of rare-earth cluster-based metal–organic frameworks
Authors: Bicalho Hudson A. , Copeman Christopher , Barbosa Helliomar P. , Donnarumma P. Rafael , Davis Zoey , Quezada-Novoa Victor , Velazquez Garcia Jose de J. , Hemmer Eva , Howarth Ashlee J.
Published: April 2024

In this work, nine new rare-earth metal–organic frameworks (RE-MOFs, where RE = Lu(III), Yb(III), Tm(III), Er(III), Ho(III), Dy(III), Tb(III), Gd(III), and Eu(III)) isostructural to Zr-MOF-808 are synthesized, characterized, and studied regarding their photophysical properties. Materials with high crystallinity and surface area are obtained from a reproducible synthetic procedure that involves the use of two fluorinated modulators. At the same time, these new RE-MOFs display tunable photoluminescent properties due to efficient linker-to-metal energy transfer promoted by the antenna effect, resulting in a series of RE-MOFs displaying lanthanoid-based emissions spanning the visible and near-infrared regions of the electromagnetic spectrum.
Liquid Water Visualization in the Pt-Loading Catalyst Layers of Polymer Electrolyte Fuel Cells Using Operando Synchrotron X-ray Radiography
Authors: Yoshimune Wataru , Kato Akihiko , Hayakawa Tetsuichiro , Yamaguchi Satoshi , Kato Satoru
Published: April 2024

Water management is important for addressing the challenges posed by next-generation fuel cell electric vehicles. Although X-ray imaging techniques are useful for probing the mechanism of water transport in the gas diffusion layer of polymer electrolyte fuel cells, they cannot be easily applied to the Pt-loading catalyst layer because of its low X-ray transmittance due to the high absorption coefficient of Pt. Herein, we propose a method to realize the high-resolution X-ray imaging of the cathode catalyst layer in polymer electrolyte fuel cells using synchrotron X-ray radiography, thus bridging the above gap. The results of operando synchrotron X-ray radiography measurements reveal that water accumulation in the cathode catalyst layer depends on the cell temperature, feed gas humidity, and cell voltage, while time-slice analysis shows that the water accumulation rate in the cathode catalyst layer is approximately four times that in the cathode gas diffusion layer. The proposed imaging method can be used to evaluate the water uptake capability of the catalyst layer and thus deepen our understanding of flooding phenomena and cold-start behavior at subzero temperatures.
Unraveling O-Glycan Diversity of Mucins: Insights from SmE Mucinase and Ultraviolet Photodissociation Mass Spectrometry
Authors: Helms Amanda , Chang Vincent , Malaker Stacy , Brodbelt Jennifer
Published: April 2024

Deciphering the pattern and abundance of O-glycosylation of mucin domain proteins, glycoproteins heavily implicated in cancer and other diseases, remains an ongoing challenge. Both the macro- and micro-heterogeneity of glycosylation complicates the analysis, motivating the development of new strategies for structural characterization of this diverse class of glycoproteins. Here we combine digestion of mucin domain proteins using a targeted protease, Enhancin from Serratia marcescens (SmE), with ultraviolet photodissociation (UVPD) mass spectrometry to advance glycan mapping and elucidation of O-glycosylation trends of densely glycosylated mucin proteins. UVPD facilitates identification of O-glycoforms of mucin domain proteins TIM-1, MUC-1 and MUC-16. Additionally, UVPD elucidates several glycoforms of MUC-16 and unravels O-glycosylation across tandem repeats of MUC-1.
Proposal of a learning tool for introduction to petroleum engineering subject and recommendations for modification of petroleum engineering curricula in Colombian universities
Authors: Plazas Niño Fernando Antonio , Galvis Silva Henry Mauricio
Published: April 2024

A learning tool is proposed from the matrix of competences for graduating engineers presented by SPE Talent Council in order to provide a consistent instrument for teaching the subject of Introduction to Petroleum Engineering. In addition, this learning tool is used to analyze current curricula of petroleum engineering in the main colombian universities and recommend some adjustments to improve the programs and enhance the professional skills and the expectations alignment of future engineers.

A more condensed and visual perspective of the SPE Graduate Matrix is presented. The most important features of the learning tool based on the prime competences required by oil and gas industry are shown, as well as its potential use for standardizing the teaching of the subject of introduction to petroleum engineering. In addition, new trends of knowledge sets such as soft skills, unconventional reservoirs, and data science are discussed.

Based on the previous analyses, a comparative chart is built to assess the current content of petroleum engineering curricula in Colombian universities and several recommendations are proposed in order to achieve the required level in the professional profiles of future petroleum engineers and to guarantee the expectations alignment of these new professionals. In general terms, there is a prominent need for including courses on offshore technologies, field operations, data science and applied statistics and economics to strength the current curricula in Colombia.
Experiencia del uso de software de simulación en la resolución de problemas no estructurados para la formación en competencias de estudiantes de Fisicoquímica de la Universidad Nacional del Chaco Austral
Authors: Fernandez Carina , Riernersman Carola Noelia , Aguado María Inés
Published: April 2024

El objetivo de este trabajo es presentar los resultados de una experiencia con alumnos de Fisicoquímica de carreras de ingeniería referida a la conveniencia del uso de simuladores en combinación con la resolución de problemas no estructurados, buscando contribuir al desarrollo del pensamiento crítico y la toma de decisiones. Los resultados sugieren que, si bien el uso de simuladores tiene alto potencial como apoyo para el objetivo buscado, el tiempo necesario para la adaptación a la nueva metodología resulta un factor limitante, sumado a que la falta de solidez en los saberes previos de los alumnos retarda aún más este proceso. Por lo tanto, se considera prudente evaluar los pros y contras de cada una de las metodologías, eligiendo sólo una de ellas para los cursos posteriores, ya que el esfuerzo docente pierde sentido si los alumnos no manifiestan un aprendizaje significativo.
Experiencia de formación docente de Ingeniería empleando el modelo dinámico de aprendizaje activo para estándares 8, 9 y 10 - CDIO
Authors: Castillo Rosas Adriana , Vázquez García Raquel , Pérez Calva Stepani Josseth , Franco Clemente Lizeth
Published: April 2024

La iniciativa CDIO propone doce estándares competenciales para la formación profesional de la Ingeniería, específicamente los estándares 8, 9 y 10 se enfocan a al desarrollo de competencias profesionales y docentes de los educadores.  Bajo ese referente se diseñó un programa de formación para docentes de ingeniería, centrado en la promoción del conocimiento, aplicación y evaluación de tres estrategias de aprendizaje activo: método de casos de aprendizaje, aprendizaje basado en problemas y aprendizaje operado por proyectos. En el diseño se consideraron las siguientes dimensiones: socio-cultural, disciplinar, psico-pedagógica y tecnológica, así como la modalidad a distancia virtual. De la experiencia se obtuvo, como aportación didáctica para la pedagogía de la ingeniería, el Modelo Dinámico de Aprendizaje Activo (MoDAA) que es funcional para el diseño de estrategias de aprendizaje activo enfocadas al CDIO.
Home Lending Trends from Select Counties in Kentucky, Ohio, and Pennsylvania: 2018–2022
Authors: Klesta Matthew
Published: April 2024

This series of reports examines home mortgages and refinances from 2018 through 2022, a period of great change. The reports look at seven large counties in Kentucky, Ohio, and Pennsylvania: Allegheny County, Pennsylvania (Pittsburgh); Cuyahoga County, Ohio (Cleveland); Fayette County, Kentucky (Lexington); Franklin County, Ohio (Columbus); Hamilton County, Ohio (Cincinnati); Lucas County, Ohio (Toledo); and Montgomery County, Ohio (Dayton).
Land Registration System Using Blockchain
Authors:   UG Scholar, Department of Information Technology Sengunthar College of Engineering, Tiruchengode, India, S Kabilan , S Sanjaykumar ,   UG Scholar, Department of Information Technology Sengunthar College of Engineering, Tiruchengode, India, S SachinKumar ,   UG Scholar, Department of Information Technology Sengunthar College of Engineering, Tiruchengode, India, S Sasidhar ,   UG Scholar, Department of Information Technology Sengunthar College of Engineering, Tiruchengode, India
Published: April 2024

The current land registration system relies on paper-based methods, prone to fraud, errors, and security vulnerabilities. These shortcomings contribute to prolonged registration processes and an increase in fraudulent activities. To overcome these challenges, this paper proposes a blockchain-based land registration system. Blockchain technology provides an immutable and decentralized ledger, ensuring the security and reliability of land records. By eliminating intermediaries, the blockchain-based registry streamlines land ownership validation, reduces costs, and accelerates registration timelines. This paper explores the potential of blockchain in land registration, focusing on fraud prevention, secure ownership record storage, and facilitation of transfer through cryptographic algorithms and smart contracts. The paper discusses the limitations of traditional land registration systems, including security, transparency, and efficiency issues. It then outlines how blockchain technology addresses these challenges by offering a transparent and secure registration mechanism. Utilizing cryptographic algorithms and smart contracts, blockchain ensures tamper-proof record-keeping and enables swift and transparent ownership transfers.
Energy-Efficient Framework for Green Cloud Computing in Dynamic Resource Allocation
Authors:   PG Scholar, Dept of CSE Sengunthar Engineering College (Autonomous), Tamil Nadu, India,, Vigram Prasanna , kumar K.Ashok ,   Associate Professor, Dept of CSE Sengunthar Engineering College (Autonomous), Tamil Nadu, India,
Published: April 2024

Cloud Computing has been a trending technology for a few years supporting computational services over internet. But ever since its adoption, cloud’s consistent challenge is in its dynamic resource allocation. The existing cloud model details the online and offline algorithms used to decide the dynamic resource allocation. The goal is to have a dynamic resource allocation framework that aligns to cloud data management’s objective of maximizing revenue with minimum cost. This encourages both consumers and cloud providers not only with energy-efficient power usage but also high CPU utilization. This article discusses the impediments of migrating to Public Cloud, what is dynamic resource allocation, HPC workloads with complex communication path on cloud platform, and the benefits of bare metal platform for latency-sensitive applications. We shed light on trade- offs (compute balance) between Private and Public Cloud, how existing resources can be leveraged, Random forest (RF) solutions including a study on hybrid cloud computing capacity optimization framework. Understanding RL architecture, problem solving approach, learning structure and Hybrid Cloud Management Architecture framework are also explored. Also given are a few RL implemented gaming examples on how it makes an impact. Lastly, we shall do the comparisons of RL with other Machine Learning (ML) approaches.
A Block Chain-Based Access Control Framework with Privacy Protection in Cloud
Authors:   PG Scholar, Department of CSE, Sengunthar Engineering College (Autonomous) Tiruchencode, Tamil Nadu, India, P. Shobika , G. Dr.Jayamurugan ,   Associate Professor, Department of CSE  Sengunthar Engineering College (Autonomous) Tiruchencode, Tamil Nadu, India
Published: April 2024

Access control is a pivotal aspect of modern computing systems, ensuring that only authorized entities can interact with sensitive data and resources. Traditional access control methods, while effective, face challenges in terms of security, transparency, and scalability. Blockchain technology has emerged as a promising solution to enhance access control in cloud computing environments. Blockchain's inherent features, such as decentralization, immutability, and cryptographic security, offer a unique framework for addressing the limitations of traditional access control systems. In this paper, we explore the integration of blockchain technology with cloud computing to establish a more secure and transparent access control mechanism. By utilizing blockchain, access control policies and permissions can be stored in a tamper-proof and transparent ledger. Scalability is an issue since processing many access control transactions on the blockchain might cause network congestion and sluggish processing. Transactions take time to upload to the blockchain, which can delay real-time access choices. It takes skill to integrate and manage blockchain and cloud technologies together. Choosing the correct consensus mechanism affects system efficiency and security. Consider the costs of establishing and maintaining such a system and the difficulty of fixing faults owing to blockchain immutability. In conclusion, this paper underscores the significance of access control in cloud computing and the limitations of traditional approaches. By harnessing the power of blockchain technology, a more secure, transparent, and scalable access control framework can be established, revolutionizing the way we manage access to sensitive data and resources in complex digital ecosystems.
DIGI Attendance
Authors:   UG Student, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchencode, India, Kumar Naveen , Kumar Prince ,   UG Student, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchencode, India, Kumar Vikash ,   UG Student, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchencode, India, B. Dr.Sujatha ,   Dean Academics,  Sengunthar Engineering College (Autonomous) Tiruchencode, India
Published: April 2024

The Digi Attendance project is a comprehensive and innovative system designed to transform attendance management in various settings, including educational institutions, workplaces, and events. This project report presents the development, implementation, and evaluation of the Digi Attendance system, highlighting its key features, benefits, and future potential. Digi Attendance system deal with the maintenance of the student's attendance details. It generates the attendance of the student on basis of presence in class. It is maintaining daily basis of attendance, only if the student presents the particular date, the attendance will be calculated.
Video Forgery Detection with Deep Learning Using RESNET and CNN Algorithm
Authors:   Final Year CSE, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchengode,Tamil Nadu,INDIA, E Arun , S Deepak ,   Final Year CSE, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchengode,Tamil Nadu,INDIA, T Prakash ,   Final Year CSE, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchengode,Tamil Nadu,INDIA, kumar K.Ashok ,   Associate Professor, Dept. of CSE Sengunthar Engineering College (Autonomous) Tiruchengode,Tamil Nadu,INDIA
Published: April 2024

Video forgery is continuously increasing in the digital world due to breaches of information security, consequently establishing a scenario for image and video content monitoring for forgery identification. The spread of fake videos raises security risks and anarchy in society. The reason for video forgery is to the augmentation in the malware, which has facilitated user (anyone) to upload, download, or share objects online comprising audio, images, or video. With the development of technology and ease of creation of fake content, the manipulation of media is carried out on a large scale in recent times. Video forgery detection has applications in media science, forensic analysis, digital investigations, and authenticity verification of a video. The purpose of video forensic technology is to extract features to distinguish fake content frames from original videos.
Intrusion Detection using Deep Learning
Authors:   Final year, CSE / Dept. of CSE Sengunthar Engineering College (Autonomous), Tiruchengode, Tamil Nadu, INDIA, C Gokul , M Kavinraj ,   Final year, CSE / Dept. of CSE Sengunthar Engineering College (Autonomous), Tiruchengode, Tamil Nadu, INDIA, P Rohith ,   Final year, CSE / Dept. of CSE Sengunthar Engineering College (Autonomous), Tiruchengode, Tamil Nadu, INDIA, P Sangeetha ,   Assistant Professor/CSE Sengunthar Engineering College (Autonomous), Tiruchengode, Tamil Nadu, INDIA
Published: April 2024

The focus of cloud computing nowadays has been reshaping the digital epoch, in which clients now face serious concerns about the security and privacy of their data hosted in the cloud, as well as increasingly sophisticated and frequent cyber attacks. Therefore, it has become imperative for both individuals and organizations to implement a robust intrusion detection system (IDS) capable of monitoring packets in the network, distinguishing between benign and malicious behaviour, and detecting the type of attacks. IDS based on ML are efficient and precise in spotting network threats. Yet, for large dimensional data sizes, the performance of these systems decreases. Thus, it is critical to build a suitable feature selection approach that selects necessary features without having an impact on the classification process or causing information loss. Furthermore, training ML models on unbalanced datasets show a rising false positive rate (FPR) and a lowering detection rate (DR). In this paper, we present an improved cloud IDS designed by incorporating the synthetic minority over-sampling technique (SMOTE) to address the imbalanced data issue, and for feature selection, we propose to use a hybrid approach that includes three techniques: information gain (IG), chi-square (CS), and particle swarm optimization (PSO). Finally, the random forest (RF) model is utilized for detecting and classifying various types of attacks. The suggested system has been verified by the UNSW-NB15 and Kyoto datasets, achieving accuracies of over 98% and 99% in the multi-class classification scenario, respectively. It was noticed that an intrusion detection system with fewer informative features would operate more effectively. The simulation results significantly outperform other methodologies proposed in the related work in terms of different evaluation metrics.
Identification of Fake Currency Using Convolution Neural Network
Authors:   Final Year CSE, Dept of CSE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, INDIA, S Sowmiya , S Anitha ,   Final Year CSE, Dept of CSE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, INDIA, . Ilavarasi ,   Final Year CSE, Dept of CSE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, INDIA
Published: April 2024

The progression of shading printing innovation has expanded the rate of Fake currency copying notes on a large scale. Albeit electronic monetary exchanges a returning out to be more popular and the utilization of paper cash has been diminishing as of late, banknotes still remain in distribution attributable to their dependability and straight forwardness in use. Few years ago, the printing should be possible in a printing-house, yet presently anybody can print a money paper with most extreme exactness utilizing a straightforward laser printer. As an outcome, the issue of duplicate currency rather than the authentic ones has been increases generally. India had reviled the problems like defilement and dark cash and fake of money notes is likewise a big issue to it. To handle this problem, a deep learning- based framework is proposed to identify the fake Indian currency. The MATLAB tool has been used to identify the fake currency. The outcome will classify whether the Indian currency note is Real or Fake.
Machine Learning Approaches Predicting the Best Features of Child Birth Using Support Vector Machine (SVM) Algorithm
Authors:   UG Scholar, Dept of Information Technology, Sengunthar College of Engineering, Tiruchengode, Tamil Nadu,India, N Adhithyan , D Dheerendra ,   UG Scholar, Dept of Information Technology,  Sengunthar College of Engineering, Tiruchengode, Tamil Nadu,India, K Dineshkumar ,   UG Scholar, Dept of Information Technology, Sengunthar College of Engineering, Tiruchengode, Tamil Nadu,India, S.V Sanjay ,   UG Scholar, Dept of Information Technology, Sengunthar College of Engineering, Tiruchengode, Tamil Nadu,India
Published: April 2024

Cesarean childbirth, though often necessary for medical reasons, carries inherent risks and impacts maternal and neonatal health. Predicting the likelihood of cesarean delivery can assist healthcare providers in making informed decisions and optimizing maternal care. In this study, we propose an ensemble machine learning approach to predict cesarean childbirth based on maternal and fetal health data. First, we collect comprehensive data including maternal age, BMI, gestational age, fetal weight, previous cesarean history, and other relevant factors. After preprocessing the data to handle missing values and encode categorical variables, we select informative features using correlation analysis and domain expertise. Next, we employ various ensemble machine learning methods, including Voting Classifiers, Bagging, Random Forest, Boosting, and Stacking. These methods combine predictions from multiple base learners, leveraging their diverse strengths to enhance predictive accuracy.
Diabetic Retinopathy Detection Using Image Processing
Authors:   Assistant Professor/ ECE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, India, B Priyanka , R Abishri ,   UG Scholar/ Dept. of ECE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, India, K. Ramyaasree ,   UG Scholar/ Dept. of ECE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, India, s Gayathri ,   UG Scholar/ Dept. of ECE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, India, P Gokilavani ,   UG Scholar/ Dept. of ECE Sengunthar Engineering College (Autonomous) Tiruchengode, Tamil Nadu, India
Published: April 2024

In today’s world, Diabetes is a very common disease that affects a lot of people’s health. As the number of diabetic patients is increasing significantly in India, there is a rise in numerous associated diseases that have disturbed society.Diabetic Retinopathy (DR) is considered to be one of such silent diseases that occur as a result of either Type 1 or Type 2 diabetes. Late diagnosis of this disease may lead to permanent eye blindness. Thus, for early diagnosis of Diabetic Retinopathy, a software-based algorithm is designed here. This technique can be promising for the pre-detection of DR without any involvement of an expert doctor and hence will save both time and money. Here, MATLAB-based image processing is used which exploits the knowledge of Computer Science and Biomedical Engineering to identify whitish lesions, cotton wool spots and hard exudates associated with DR. Based on the value of pixel counts, the image of the patient’s eye under examination is classified. Diabetic retinopathy (DR), a complication of diabetes, poses a significant threat to global vision health. Early detection and timely intervention are crucial to prevent irreversible vision loss.
Generation of Power from Footpath Using IOT
Authors:   Assistant Professor, Department of ECE, Sengunthar Engineering College (Autonomous), Tiruchengode, Tamil Nadu, INDIA, P Sivasankaran , R Akash ,   UG Student, Department of ECE, Sengunthar Engineering College (Autonomous),  Tiruchengode, Tamil Nadu, INDIA, R Harish ,   UG Student, Department of ECE, Sengunthar Engineering College (Autonomous),  Tiruchengode, Tamil Nadu, INDIA, S Suresh ,   UG Student, Department of ECE, Sengunthar Engineering College (Autonomous),  Tiruchengode, Tamil Nadu, INDIA
Published: April 2024

The present scenario, the requirement for energy has been increasing in a distressing rate and the availability of the energy resources are not abundant for sustainable development and the need of the hour is to establish an economical pollution free inexhaustible energy resource to compensate the increasing demands. Since, walking is the most common activity in human day to day life, whenever a person walks, he exhausts energy to the ground which goes as a waste. In order to preserve and make use of this energy we are converting it into electrical energy using piezoelectric effect. Piezoelectric effect is utilized by piezoelectric sensor producing output energy in the form of AC voltage. To produce energy in a large extent, in this model implementation of the piezoelectric sensor network along the footpath is carried out which is given to the lane of streetlights along with it the smart shoe is implemented for a small production that consists GPS tracking. In this proposed work model, GPS tracking has been added and also streetlights switching technique comparing with existing model
Integrated Poultry Care System (IPCS)
Authors:   Professor, Department of ECE Sengunthar Engineering College (Autonomous) Tiruchencode, Tamil Nadu, INDIA, C. Dr.Aarthi , V.B. Kavipreetha ,   UG Student, Department of ECE Sengunthar Engineering College (Autonomous) Tiruchencode, Tamil Nadu, INDIA, S. Kivisha ,   UG Student, Department of ECE Sengunthar Engineering College (Autonomous) Tiruchencode, Tamil Nadu, INDIA, V Nounitha ,   UG Student, Department of ECE Sengunthar Engineering College (Autonomous) Tiruchencode, Tamil Nadu, INDIA
Published: April 2024

The Integrated Poultry Care System (IPCS) is an innovative IoT-based real-time monitoring and control system designed specifically for poultry farms. Leveraging the power of Internet of Things (IoT) technology, IPCS offers comprehensive monitoring capabilities, allowing farmers to remotely track with using individual tags for identifying the temperature, humidity in their poultry houses in real-time. Raspberry Pi 4 serves as the central processing unit and data hub, collection, processing, and transmission of sensor data from the poultry houses. The ESP8266 module is specifically utilized for its capability to connect to Wi-Fi networks, allowing seamless communication between sensors. These modules then transmit the collected data wirelessly to the central control unit, typically powered by a Raspberry Pi or a similar computing device, for processing, analysis, and monitoring. It also serves as the interface through which farmers can remotely access and monitor the conditions within their poultry houses via a user-friendly dashboard or mobile application.
Text Recognition for the Speed Control of the Vehicle
Authors:   Assistant Professors, Department of ECE, Sengunthar Engineering College (Autonomous) Tiruchencode, TamilNadu, India, G Suresh , S. Deepan ,   UG Students, Department of ECE, Sengunthar Engineering College (Autonomous) Tiruchencode, TamilNadu, India, E Elumalai ,   UG Students, Department of ECE, Sengunthar Engineering College (Autonomous) Tiruchencode, TamilNadu, India, R Sathish ,   UG Student, Department of ECE, Sengunthar Engineering College (Autonomous) Tiruchencode, TamilNadu, India
Published: April 2024

An automatic vehicle human-voice-based safety control is proposed to decrease the happening of vehicle accidents due to an eye or hand activities while driving. The design is implemented using an Arduino microcontroller. One of the most important safety control features is the automotive speed control (ASC). In this safety control function, which prevents a vehicle sudden hit, the necessary action is issued based on the vehicle-to- vehicle distance measure. To prevent the driver from attention withdraw and maintain a proper road and situation focus (as especially is the case at night), several other automated safety control operations are provided (i.e., radio, flasher, left flasher, right flasher, wipers, drive, and stop). These features are controlled according to human voice commands using an EasyVR module. The proposed model has been designed, built, and tested providing suitable results as desired.
Breast Cancer Detection Using Deep Learning
Authors:   Student, Dept. of Medical Electronics Engineering, Sengunthar Engineering College (Autonomous), Thiruchengode Thiruchengode, Tamil Nadu, INDIA, R. Suguna , Sathik Raja Prof.Muhammadu ,   Professor, Dept. of Medical Electronics Engineering, Sengunthar Engineering College (Autonomous), Thiruchengode Thiruchengode, Tamil Nadu, INDIA, S Priya ,   Professor, Dept. of Medical Electronics Engineering, Sengunthar Engineering College (Autonomous), Thiruchengode Thiruchengode, Tamil Nadu, INDIA
Published: April 2024

The most frequently occurring cancer among Indian women is breast cancer. The second major cause of women's death is breast cancer (after lung cancer). 246,660 of women's new cases of invasive breast cancer are expected to be diagnosed in the US during 2016 and 40,450 of women’s death is estimated. The number of breast cancer cases is steadily growing especially with increasing number of ageing population. Breast cancer is a type of cancer that starts in the breast. Cancer starts when cells begin to grow out of control. Breast cancer cells usually form a tumour that can often be seen on an x-ray or felt as a lump. The screening practice using mammography needs to be better and potentially efficient. There is always room for advancement when it comes to medical imaging. Early detection of cancer can reduce the risk of death for cancer patients. Breast cancer can spread when the cancer cells get into the blood or lymph system and are carried to other parts of the body. This overview looks at the results of a proposed system for automatically diagnosing breast cancer using several convolutional neural network (CNN) designs and compares them to those achieved using machine learning (ML) techniques. All buildings were built from a large database. Validation tests were conducted in order to provide quantifiable results using the performance parameters of each approach. Functions like VGG16 and ResNet50 are used in this model to improve the accuracy of the model. The cause of Breast Cancer includes changes and mutations in DNA. Women are seriously threatened by breast cancer with high morbidity and mortality. The breast cancer dataset is publicly available on the UCI Machine Learning Repository and therefore the implementation phase dataset is going to be partitioned as 80% for the training phase and 20% for the testing phase then apply a significant performance in respect of all parameters.
Casson Fluid Flow Past a Shrinking Surface with Heat and Mass Transfers
Authors: Das Rajesh Kumar , Dey Debasish
Published: April 2024

In this study, we have numerically investigated the heat and mass transfers behaviour of Casson fluid flow past a porous shrinking sheet in existence of a magnetic field, thermal radiation, and suction or blowing at the surface. Applying suitable similarity transformations, the leading partial nonlinear differential equations of mass, flow, and heat transfer are converted into solvable ordinary differential equations, which can then be solved numerically with the help of the MATLAB bvp4c scheme. We have analyzed and shown graphically the implications of several non-dimensional controlling factors on the profiles of temperature, concentration, and velocity. Additionally, the Sherwood, Nusselt, and Skin friction for Casson fluids are examined and tabulated. The current study's findings for Casson fluid exhibit great consistency with previous research under specific circumstances.