bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning based Lung Cancer Diagnostic System using Optimized Feature Subset Selection
Authors: Perumal Ramya , Kumaran S Yogesh , Manimozhi I. , Kaladevi A.C. , Rohith Bhat C.
Published: October 2024

Lung is a vital organ that plays a major role in respiration. Without breathing, one may not survive in this world. Hence lung is an important organ that acts as filter to absorb oxygen and supply it to heart where pumping takes place through blood vessel in the circulatory system .The pumped blood takes oxygen and other nutrients to every other parts of the body. Hence one must take care of lung. There are various diseases associated with lungs. Lung Cancer is a deadly disease that spread across the countries all over the world. An early detection of lung cancer has been proved to improve the survival rate of human life. There are various resources are available to detect the lung cancer disease. They are low dose CT-scans, X-rays, blood-based screening, pathology slide reading, biopsy’s test, survey data(clinical dataset) etc. helps to predict the disease well in advance. Our proposed work uses two clinical datasets that has various features to detect how likely the persons get affected from the lung disease. Dataset1 includes features such as age, gender, smoking, yellow fingers, anxiety, peer-pressure, chronic disease, fatigue, allergy, wheezing, alcohol, coughing, shortness of breath, swallowing difficulty, and chest pain. Also, the work has experimented with another dataset2 that represents causes of lung cancer due to exposure of pesticide. Our proposed diagnostic system consider all these features in total and perform feature selection to extract optimal feature subsets using cuckoo search algorithm then perform classification using machine learning algorithms such as Linear Support Vector Machine, Logistic Regression and Random Forest algorithm. It is observed that with the cuckoo search algorithm, dataset 1 achieves an accuracy of 100%, precision of 100%, recall of 100%, and F1-score of 100% by LR Classifier. The Linear SVC classifier achieves an accuracy of 90%, a precision of 88%, a recall of 86%, and an F1-score of 87%.The Random forest Classifier achieves an accuracy of 91%, precision of 86%, recall of 93%, and F1-score of 90%. For dataset 2, both the LR classifier and Linear SVC classifier outperform with an accuracy of 100%, precision of 100%, recall of 100%, and F1-score of 100%. Whereas Random Forest provides accuracy of 97%, precision of 97%, recall of 96%, and F1-score of 97%.
MResGat: Multi-head Residual Dilated Convolution Assisted Gated Unit Framework for Crop Yield Prediction
Authors: Shetty Sahana , T R Mahesh
Published: October 2024

The importance of predicting crop yields has increased due to growing concerns of surrounding food security. Early forecasting of crop yields holds a pivotal role in avoiding starvations by estimating the food supply available for the expanding global population. Several Deep Learning (DL) and Machine Learning (ML) techniques are involved to develop effective and accurate crop yield prediction model. Nevertheless, existing models faces some limitations such as less accuracy, high error rate because of noisy data, high training time and extracted less effective features for prediction. To overcome these issues, the novel DL methodology is introduced for attaining high accurate crop yield prediction. Initially, the soil, weather and other resources big data are collected from the various agriculture field. In data collection phase, the input data of larger size are stored in the Hadoop platform for the purpose of storing as well as processing the entire data in a distributed manner. The data are pre-processed through the utilization of Missing value imputation and z-score based data normalization. From the pre-processed data, the optimal features are considered using Integrated Correlation Random recursive elimination (InCorRe) approach. Based on the previous soil and weather information, the suitable yield of crops can be predicted using Multi head Residual dilated convolution assisted gated unit (MResGat) model. Finally, the losses of the network model can be optimized using African vulture optimization algorithm (AVO). The proposed method is evaluated using the several performance metrics, which achieved 0.023% of MSE value and 0.036% of MAE values.
Sports Player Action Recognition based on Deep Learning
Authors: Li Feng
Published: October 2024

A sports auxiliary evaluation system suitable for China’s national conditions was established using big data and sports identification technology. First of all, this paper extends the data of normative behavior and constructs a normative library of scores and comparisons. The acquisition of 3D data is emphasized. The method based on Fourier descriptors is used to locate the motion accurately. In this way, better gait recognition results can be obtained. The Fourier characteristics before and after wavelet transform are compared with the actual object characteristics, and the results show that the proposed algorithm can extract the features with high precision. This scheme can obtain a more accurate identification effect. The system proposed in this paper provides a powerful means for judges to score.
Visual Communication Method of Multi frame Film and Television Special Effects Images Based on Deep Learning
Authors: Zhang Jinglei
Published: October 2024

For the dynamic film and television special effects industry, creating visually stunning and valuable graphics requires the integration of excellent deep-learning algorithms. This paper presents an enhanced version of the 3-D Convolutional Neural Network (3-D CNN), specifically tailored to meet the demanding needs of multi-frame television and film special effects. The version’s key feature is its efficient data handling through coupled precision training, significantly increasing computational efficiency while reducing memory needs. This method, which combines floating-issue operations of 16 and 32 bits, is ideal for efficiently processing large amounts of high-resolution video data. The proposed 3-D CNN structure excels in extracting and analysing complex spatiotemporal capabilities from video sequences, capturing the spatial and temporal nuances crucial in film imagery. This capability is important for accomplishing excessive fidelity in visual results, ensuring seamless integration with live motion pics. Incorporating a cutting-edge attention mechanism inspired by the aid of transformer-based architectures, the model specialises inside the maximum pertinent components of video frames to enhance the quality and realism of outcomes. Furthermore, the model boasts an excessive-resolution processing characteristic, permitting simultaneous capture of first-rate records and broader scene context. This guarantees consistency and realism in outcomes, from complicated textures to the overarching visual narrative. Advanced regularisation strategies are hired to prevent overfitting, permitting the model to generalise efficiently through numerous film manufacturing conditions. The state-of-the-art 3-D information augmentation techniques make the model robust and prepare it to deal with an intensive variety of challenging situations involving computer special effects. Real-time processing competencies make the model a game-changer for on-set visible outcomes and adjustments. Designed for seamless integration with the famous CGI software program software utility, it allows a harmonious aggregate of AI and ingenious creativity. Acknowledging the environmental impact of high-powered computing, the model consists of power-efficient computational techniques that align with sustainable computing practices, lower operational costs, and are related to processing complex video statistics. model boasts an excessive-resolution processing characteristic, permitting simultaneous capture of first-rate records and broader scene context. This guarantees consistency and realism in outcomes, from complicated textures to the overarching visual narrative. Advanced regularisation strategies are hired to prevent overfitting, permitting the model to generalize efficiently through numerous film manufacturing conditions. The state-of-the-art 3-D information augmentation techniques, in addition, make the model robust, and prepare it to deal with an intensive variety of computer special effects challenging situations.
Research on Broadband Oscillation Suppression Strategy in Power System Based on Genetic Algorithm
Authors: Yang Yuanwei , Zhao Huashi , Li Jin , Zhou Huafeng , Gu Huijie , Xu Danli , Li Yang , Liu Kemeng
Published: October 2024

This examination presents an original Broadband Oscillation Concealment Procedure in Power Systems utilizing a Genetic Algorithm (GA). The philosophy’s suitability is deliberately assessed through comprehensive examinations, including affiliation investigation, strength appraisal, and near investigations with elective optimization algorithms. Results show that the GA-based approach displays predominant affiliation, appearing at a health worth of 0.05 after 100 ages, beating Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Simulated Annealing (SA). Strength examination features the versatility of the proposed procedure, with a standard wellbeing worth of 0.08 ± 0.02 under changing power framework conditions. Similar investigation against related work reveals the procedure’s advantage, showing its genuine breaking point with regards to helpful broadband oscillation concealment. The GA-based philosophy changes speedy mixing and computational capacity, with an ordinary execution season of 120 seconds. The examination contributes important pieces of information into power framework strength, offering a good answer for mitigating broadband oscillations in various working situations.
Hybridization of Machine Learning Model with Bee Colony based Feature Selection for Medical Data Classification
Authors: R Raja , B Ashok
Published: October 2024

Nowadays, an important count of biomedical data is created continuously in several biomedical equipment and experiments because of quick technical enhancements in biomedical science. The study of clinical and health data is vital to enhance the analysis precision, prevention, and treatment. Initial analysis and treatment are extremely important approaches for preventing deaths in many diseases. Accordingly, the data mining and machine learning (ML) approaches are helpful tools for utilizing minimization error and for providing helpful data for analysis. But the data obtained in digital machines takes higher dimensionality, and not every data attained in digital machines is significant to specific diseases. This article develops an artificial bee colony-based feature selection with optimal hybrid ML model for medical data classification (ABCFS-OHML) technique. The presented ABCFS-OHML technique mainly aims to identify and classify the presence of disease using medical data. To attain this, the presented ABCFS-OHML technique initially pre-processes the input data in two ways namely null value removal and data transformation. Furthermore, the presented ABCFS-OHML technique uses ABCFS model for the choice of effectual subset of features. At last, root means square propagation with convolutional neural network-Hop field neural network (CNN-HFNN) model for classification purposes. The usage of RMSProp optimizer assists in attaining optimal hyperparameter selection of the CNN-HFNN method. The performance validation of the ABCFS-OHML technique takes place using three medical datasets. The comparison study reported that the ABCFS-OHML technique has accurately classified the medical data over other recent approaches.
Decision-making Optimization of Cross-border E-commerce Supply Chain based on Genetic Simulated Annealing Algorithm
Authors: Qiu Renyi
Published: October 2024

This paper mainly studies the collaborative operation of a cross-border e-commerce supply chain composed of manufacturers, e-commerce platforms and foreign warehouses. Firstly, the decision models of transnational e-commerce enterprises based on decentralized, centralized, and hybrid modes are established. The sensitivity of the contract and each determining variable is analyzed using the simulation method. Through the joint contract of ”revenue sharing + volume discount,” the production efficiency of the enterprise and the logistics service of the international warehouse can be improved. The genetic algorithm combined with simulated annealing was adopted. Finally, a concrete example is given to verify the feasibility of the proposed method. The results show that the member departments can work together better under centralized decision-making compared to the decentralized management mode. Manufacturers to increase production capacity and improve the level of logistics services in overseas warehouses will help improve the profitability of cross-border e-commerce.
The Application of Artificial Intelligence Technology in Mechanical Manufacturing and Automation
Authors: Wu Mingming
Published: October 2024

In order to achieve intelligent production and quality control, improve production efficiency and accuracy, the author proposes an application method of artificial intelligence technology in mechanical manufacturing and automation. The author aims to explore the specific application of artificial intelligence technology in the mechanical manufacturing industry and summarize the main advantages of automation technology. By analyzing these advantages, the aim is to provide targeted recommendations for future technological development. Meanwhile, the author aims to provide theoretical support for promoting the application of modern artificial intelligence technology and automation technology in the field of mechanical manufacturing. In the manufacturing process, intelligent production and quality control can be achieved, improving production efficiency and accuracy; In the field of automation, artificial intelligence technology can achieve intelligent control systems and autonomous decision-making, improving the flexibility and adaptability of production lines. Overall, the application of artificial intelligence technology has brought revolutionary changes to mechanical manufacturing, promoting the upgrading and development of the industry.
A Method for Extracting Power Entity Relationships Based on Hybrid Neural Networks
Authors: Liu Xinran , Ruan Shidi , He Yini , Zhang Xiongbao , Chen Quanqi
Published: October 2024

In response to the challenges of entity relationship extraction in unstructured text, the author proposes a power entity relationship extraction method based on a hybrid neural network. This method aims to overcome the limitations of existing models in accurately representing contextual environment information, thereby improving the accuracy of the extraction model to meet practical application needs. Firstly, a Bidirectional Gated Recurrent Unit (BiGRU) was designed to better capture contextual information in text sequences. This helps the model to better understand the relationships between entities. Secondly, an attention mechanism was adopted to enable the model to automatically focus on sequence features that have a significant impact on relationships. This helps the model to extract entity relationships more accurately in complex text environments. Finally, a segmented convolutional neural network (PCNN) was introduced to further improve the accuracy of relationship extraction by learning the environmental feature information in the adjusted sequence. This enables the model to better understand the contextual relationships between entities. On the publicly available English dataset SemEval2010Task8, this method achieved satisfactory results, achieving an F1 value of 85.62%. These experiments have confirmed the effectiveness of our method, providing new ideas and support for automatic extraction of entity relationships, and are expected to play an important role in the field of information extraction.
Key Dimensions in Smart Cities' Rankings - Towards Enhancing the Quality of Life for Smart Cities’ Inhabitants
Authors: Pangsy-Kania Sylwia , Kania Katarzyna
Published: October 2024

Abstract
Motivation: Urbanization, demographic trends, globalization, and sustainable development contribute to the emergence of smart cities, which entail the intelligent integration of economy, governance, mobility, environment, daily life, and people. Smart city concept means a solution to support the growth of urban areas. One significant aspect discussed in the context of smart cities is the quality of life for their inhabitants. Smart cities are prevalent worldwide, but there is no universally accepted index for accurate and reliable global rankings. Essential criteria for evaluation include livability, health, technology, mobility and transport, economy, environment, governance, and sustainability. The primary objective of this paper is to address the following questions: How do smart cities enhance the quality of life for their inhabitants? What are the key dimensions and indicators used in smart cities rankings in the context of quality of life? Which cities are considered the smartest globally according to the most prominent rankings, and are there any European cities among them?
Aim: The aim of the article is to explore the main dimensions and indicators in smart cities indexes and to present the first three smartest countries based on 2022 rankings. The article answers the question which of the key dimensions of smart cities' rankings are most consistent with the areas of improvement in the quality of life of the inhabitants of these cities. This manuscript may prove valuable for researchers planning to assess the benefits and challenges associated with smart cities.
Evaluation of financial monitoring systems effectiveness in its relationship to the country's security indicators
Authors: Ksendzuk Valentyna , HRYTSYSHEN DYMYTRII , SERGIIENKO LARYSA , HRABCHUK IRYNA , ZAKHAROV DMYTRO
Published: October 2024

Motivation: The motivation for this research work is its potential to identify critical issues with far-reaching implications for economic security, governance and development, and to contribute to more informed decision-making in the area of countering the financing of terrorism.
Aim: The purpose of this research paper is to analyse the impact of the FATF (Financial Action Task Force) standards on crime and anti-corruption efforts and the effective implementation of the legal framework in countries.
Results: The article examines the relationship between crime, corruption, terrorism and FATF standards in 54 countries. Based on the regression analysis, the influence of crime, terrorism and perception of corruption on the effectiveness and compliance with FATF standards is investigated. The specific coefficients show that the perception of terrorism and corruption have a statistically significant negative and positive impact on the dependent variable, respectively, while the impact of the crime index is not statistically significant. By examining the impact of crime rates and anti-corruption efforts on FATF standards and the effective implementation of legal frameworks in countries, the study aims to provide information that can inform decision-making. Understanding how these factors interact can help to improve anti-money laundering and counter-terrorist financing strategies at both the national and international levels, including the improvement of financial monitoring systems. Understanding the relationship between crime, corruption and terrorism can have practical implications for various stakeholders, including law enforcement, government officials and international organisations. The findings are important for the implementation of effective measures to combat money laundering and terrorist financing, improve governance, security and overall socio-economic stability.
Elephant in the Room: How to Assess the Vote-weighting System in the Council of the EU
Authors: Kleinowski Marcin
Published: October 2024

The article emphasises the complementarity of research based on voting power theory with the analysis of the structure of blocking. Combining both methods enables a more comprehensive assessment of the vote weighting system in the Council of the EU, in particular the impact of changes in the voting system on the position of individual Member States and the power balance in this institution. I make two contributions to the existing literature. Firstly, the study develops a non-random voting model, dedicated to QMV in the Council, which abandons the assumption that each coalition of players is equally likely and takes into account the role of the European Commission as an agenda-setter. This not only allows us to exclude many coalitions that are only theoretically possible, but also to analyse the blocking structure from the perspective of different states or coalitions in the Council. Secondly, it shows that the application of blocking structure analysis provides novel insights into the Council’s voting system. Unlike the a priori voting power approach, such analysis does not focus on distribution of winning power in the Council, but on the Member States’ ability to build minimal blocking coalitions. Hence, it complements the application of mathematical indices of voting power in the assessment of the voting system in this institution.
Civic Platform’s Views on the Security of Poland in the Context of the War in Ukraine
Authors: Sanecka-Tyczyńska Joanna
Published: October 2024

This study is concerned with one of Poland’s major political parties – Civic Platform (CP). Formed in 2001, it represents the liberal strain of Polish political thought. The Civic Platform was the ruling party between 2007 and 2015. For the ninth term of the Polish Parliament, it formed the Civic Coalition parliamentary group together with Modern, the Polish Initiative, and the Greens. This study explores the question of CP politicians’ perceptions of the security of Poland in the context of the war in Ukraine. It takes a closer look at Polish liberals’ assessment of the international situation and their diagnosis of the threats faced by Poland. Their outlook on political and military security is discussed as well, as is their attitude towards the steps taken by the Polish authorities after February 24, 2022. State security – defined as a condition obtained through effectively implemented defence and protection measures against a variety of military and non-military threats – was the main research category. State security may be considered a critical component of the raison d’état. It is also a key challenge for those in power.
Turkey’s Soft Power towards Serbia: Implications for the Security and Stability in the Region
Authors: Kujawa Karol , Polko Paulina , Öçalan Ceren
Published: October 2024

The purpose of this article is to analyze Turkish soft power towards Serbia in the 21st century. From a methodological point of view, this article is based on quantitative and qualitative research methods. In addition, the study uses content analysis, including newspaper articles, archival documents and other statements by individual politicians and intellectuals. The results of this research indicate that Turkey has established several public diplomacy institutions to influence Serbian public opinion, such as the Turkish Cooperation and Coordination Agency (TIKA), Diyanet, and the Yunus Emre Institute (YEI). Turkey has strengthened its influence in Serbia and other Balkan countries through their activities. It has significantly improved the image of Turkey and Turks in Serbia. It has also increased the popularity of the Turkish president in the region. On the other hand, such a policy strengthens stability in the Balkans and reduces conflicts between Serbs and Muslims in the Balkans, which is important for regional security.
Samorząd Studentów Uniwersytetu Warszawskiego w latach 1980-1982
Authors: Kunicki-Goldfinger Marek
Published: October 2024

THE UNIVERSITY OF WARSAW STUDENT LIAISON COMMITTEE IN THE YEARS 1980-1982 This book, which focuses on the activity of the Student Liaison Committee from September 1980 to September 1982, is divided into two parts. The first is a monographic study of the subject, while the second consists of a selection of the Committee’s documents, compiled and edited by the author of the monograph. The two parts are preceded by Professor Henryk Samsonowicz’s foreword entitled “Student Self-Governance”, in which he discusses the relationship between self-government and the traditions of Western civilisation, particularly emphasising the role of student unions in the development of universities. The first part of the book is organised into several chapters. The opening chapter explores differences between what self-government should ideally be and how much self-governance was tolerated under real socialism, from the post-Stalinist period up until 1980. The second chapter traces the grass roots efforts to establish various forms of student unionisation at Warsaw University between 1973 and 1977. Given the failure of these efforts, the chapter that follows discusses the significance of students’ illegal activities in support of self-governance, particularly as part of Student Solidarity Committees.
Um Estudo de Caso de Aplicação de um Método Ágil para Desenvolvimento de Requisitos de Software: O REACT
Authors: Santos Kleoson B. C. , Oliveira Sandro R. B.
Published: October 2024

Este estudo apresenta o relato de um estudo de caso sobre a aplicação do REACT (Requirements Evolution in Agile ContexT), um método ágil para o desenvolvimento de requisitos de software, em um ambiente real de desenvolvimento de software. Este estudo de caso avaliou as forças, as fraquezas, as oportunidades e as ameaças relacionadas aos ativos que compõem o REACT, a saber: artefatos, ciclo de vida, papéis e cerimônias. Dentre os resultados, observou-se que o REACT foi efetivo, simples de usar, fortemente colaborativo, suitable, centrado no usuário e orientado a metas. Assim, atendendo ao seu principal objetivo que é evoluir os requisitos de um produto de software de forma iterativa, eficiente e sob o guarda-chuva do mindset ágil. Os resultados contribuem à indústria de software fornecendo um relato de experiência sobre o uso de um método ágil para o desenvolvimento de requisitos de software, o qual pode servir de referência para organizações que buscam a adoção de métodos ágeis relacionados à área de requisitos, assim como, prover à comunidade científica um melhor entendimento empírico do relacionamento entre requisitos e métodos ágeis.
Aesthetic crown lengthening
Authors: Wadia Reena
Published: October 2024

Ideal smile aesthetics includes ‘pink’ aesthetics and aesthetic crown lengthening surgery is an integral surgical procedure that is commonly used to achieve optimal overall aesthetics. Understanding the reasons for a ‘gummy’ smile, or gingival excess, is key. A thorough assessment and careful treatment planning are required for successful results. Crown lengthening can be carried out as a stand-alone procedure or as part of a wider restorative treatment plan.

CPD/Clinical Relevance: This article discusses the ideal ‘pink’ aesthetics, indications for crown lengthening as well as the treatment sequence.
A minimally invasive approach to smile enhancement
Authors: Khan Shiraz , Mackenzie Louis
Published: October 2024

An 18-year-old male patient presented with generalised hypoplasia affecting the appearance of his maxillary anterior teeth. Aiming to keep any restorative intervention as minimally invasive as possible, a combination of tooth whitening, particle abrasion, resin infiltration and direct composite masking were used in this case to deliver significant aesthetic improvement.

CPD/Clinical Relevance: This article explores minimally invasive approaches to restorative dental procedures and provides an understanding of the motivations for these approaches, the considerations for treatment planning and the impacts on treatment outcomes for patients.
Barriers to health visitors identifying child neglect
Authors: Boyle Nicola , Taylor James
Published: October 2024

Child neglect poses a significant issue in the UK with enduring repercussions for the health and wellbeing of children. Health visitors are responsible for safeguarding and promoting child welfare and play a pivotal role in identifying and addressing neglect, but a multitude of barriers can hinder this. This article explores the complex landscape of health visitors identifying child neglect, outlining the significance of early intervention, with a particular focus on health visiting in Scotland. Challenges faced by health visitors are examined, including organisational barriers, family/carer disguised compliance, and varying professional thresholds for when to intervene. The importance of leadership support, enhanced training and clear thresholds in safeguarding work are highlighted. The concept of ‘respectful uncertainty’ is advocated as an approach for health visitors to navigate the challenges they encounter when protecting and promoting the wellbeing and safety of children in the UK.
Near Field Scatter from a Body of Revolution
Authors: Michaelchuck Jr Edward C. , Lambrakos Samuel G. , Coburn William O.
Published: October 2024

Better understanding of electromagnetic wave propagation through vegetation and forest environments can be achieved with the aid of modeling and simulation. Specifically, modeling the coherent summation of electromagnetic waves due to both single scatter and multi-scatter effects. To accurately perform simulations in lower frequency bands, S-band and below, the Body of Revolution (BOR) Method of Moments (MoM) must be extended to calculate the scattered electric and magnetic near-fields from BOR in the presence of a plane wave. The near field interactions specifically occur during the various higher order scattering harmonics, i.e. 2nd order and greater harmonics. Additionally, the method must accurately capture scattered fields in the presence of a non-plane wave incident upon BOR. The focus of this study is modeling lossy dielectric BOR that are characteristic of vegetation and forest environments, e.g., cylinders representing tree branches. Although the formal electric and magnetic field scattering definitions are known, this report presents analytical formulations of near field scattering from BOR for this implementation of BOR-MoM. The scattered-field extensions are validated using the commercial software FEKO©, which simulates electromagnetic-wave scattering in 3D using MoM formulation of scattered fields.
Approach to the Implementation of Laplace and a Broadband Helmholtz Fast Multipole Method as an Application Independent Library
Authors: Velamparambil Sanjay
Published: October 2024

In this paper, we propose an approach to develop an application independent library of Laplace and Helmholtz fast multipole method (FMM) that can be used in different applications. For this purpose, we consider a generalized problem and a corresponding canonical problem (defined below). In the first main contribution, we show that it is possible to capture the essential characteristics of the canonical summation from sampling the values of certain potentials or signature functions. In the second main contribution, we show that partial derivatives of arbitrary orders acting on the far field can be represented as product of sparse matrices within the library, transparent to the user. Combining the two ideas, we show that once the FMM is configured to compute the canonical summation, the same setup can be used to work with a much wider, general class of problems.
Design an RF Up-Down Convertor using Software Defined Radio and GNU Radio
Authors: Thavai Aniket , Subhedar Mansi , Thakur Yash , Patil Mrunal
Published: October 2024

There is a need to design of RF Up/Down- converter for (from C/Ku to/from L band) signals required for several applications. The proposed work presents a design of an RF Up/Down Converter that makes use of GNU Radio and Software-Defined Radios (SDRs). The converter helps in frequency translation between the C/Ku and L bands, leading to a cost-effective and versatile solution for RF signal processing. By using open-source GNU Radio software, the proposed system enhances accessibility, enabling its deployment in diverse applications, from satellite communication to radar systems. The converter’s unique features include real-time processing capabilities, customization through an intuitive graphical interface, and Python scripting. This idea presents the design considerations, signal processing techniques, and performance evaluation of the RF Up/Down Converter. The advantages of an open-source solution over other available alternatives are in terms of cost, flexibility, and rapid prototyping. Simulation and hardware results demonstrate the efficacy of the proposed work.
Cloud Replica Management-Based Hybrid Optimization
Authors: Djebbara Mohamed Redha
Published: October 2024

This research addresses the challenges in cloud-based replica management by proposing a novel strategy employing a Genetically Implied Greywolf with Oppositional Learning (GIGOL) hybrid optimization technique. This approach optimizes multi-objectives such as response time, load balancing, availability, replication cost, and energy consumption, ensuring cost-effectiveness and energy efficiency. The GIGOL model integrates Genetic Algorithm, opposition learning, and Grey Wolf Optimization, aiming to achieve optimal replica placement. The study emphasizes resolving overhead issues through machine learning techniques for efficient cloud-based replica management. Performance evaluation showcases improvements in response time, load balancing, availability, replication cost, and energy consumption, highlighting the effectiveness of the proposed approach within budget constraints and management policies.
Enhanced light-matter interactions in Spherical Bragg Resonators
Authors: García-Puente Yalina , Kashyap Raman
Published: October 2024

Our research optimized Spherical Bragg Resonators to engineering emissions from Er3+ and Eu3+ emitters, enhancing light-matter interaction. The study achieved significant electromagnetic field and radiative decay rate enhancements, demonstrating the potential for efficient lasing and all-dielectric nanoantenna.
High order fiber Bragg gratings using point-by-point femtosecond laser technique
Authors: Cotillard Romain , Roussel Nicolas
Published: October 2024

Here we describe the inscription of high-order Bragg gratings. These optical components feature the combined properties of Bragg gratings and Fabry-Perot cavities, open new possibilities both for sensor applications and as optical components, such as wavelength references or fiber-optic verniers.
Survival of nanogratings in high melting oxide glasses upon thermal annealing
Authors: Ktafi Imane , Xie Qiong , Torun Gözden , Bellouard Y. , Yembele Maureen , Allix Mathieu , Hawkins T. W. , Ballato John , Cavillon Maxime , Lancry Matthieu
Published: October 2024

Nanogratings were fabricated using a fs-laser inside more than 20 oxide glasses. Glass viscosity mostly dictates their thermal stability but deviation from this trend was observed in glasses containing large amount of Al2O3 or ZrO2.
Effect of Group Delay Ripples of Chirped Fiber Bragg Gratings Used in CPA lasers
Authors: Ouellette François , Wang Hui
Published: October 2024

The effect of group delay ripples (GDR) in chirped fiber Bragg gratings used in chirped pulse amplification lasers is a nalyzed. The polarization rotation method is shown to measure the most deleterious GDR with a resolution better than 50 fs.
Interferometric inscription of sapphire fiber Bragg gratings and temperature diagnosis using these gratings in applications above 1400°C
Authors: Habisreuther Tobias , Schröder Kerstin , Eisermann Rene , Lorenz Adrian , Krenek Stephan
Published: October 2024

The paper reports the inscription of fiber Bragg gratings by 400nm femtosecond laser pulses using an interferometer setup. High temperatures probes were assembled, calibrated using temperature fixed-points and applied in industrial processes at T>1400°C.
Femtosecond laser writing of Fiber Bragg Grating within a PM active fiber for 1535 nm all-fiber laser demonstration
Authors: Khalil Alain Abou , Freysz Valerian , Armengaud Kevin , Pierre Christophe , Castaing Marc
Published: October 2024

Using femtosecond laser pulses, a highly reflective Fiber Bragg Grating was inscribed inside the core of an active PM fiber, integrated into a 1535 nm all-fiber PM laser system.
All-optical Switch and Logic Gates Using Phase Asymmetries in High-Q Resonators
Authors: Pal Arghadeep , Ghosh Alekhya , Zhang Shuangyou , Hill Lewis , Bi Toby , Del’Haye Pascal
Published: October 2024

We demonstrate an optical switch and propose designs of photonic logic gates exploiting the Kerr-effect induced enhancement of phase asymmetries. This will be of immense importance in integrated all-optical computing.
Numerical Estimation of a Propagation Loss Evaluation using an Asymmetric Mach-Zehnder Interferometer
Authors: Sato Kodai , Fukuda Hiroshi
Published: October 2024

This study numerically estimated the effectiveness of an evaluation method using an asymmetric Mach-Zehnder interferometer and an embedded photodiode and revealed that this technique is applicable for propagation loss characterization in a practical range.
Analysis of the Optical Behavior of Diffuse Reflectance in Polycrystalline Yttrium–Iron Garnet Synthesized by Different Methods and its Effect to Estimate Eg by Tauc Plot
Authors: Tamayo-Rivera L. , López-Sierra A. , Salvador-García D. , Valdivieso-Villegas J. E. , Gutiérrez-Amador M. P. , Sánchez-Castillo A.
Published: October 2024

Optical characterization of colored samples allowed us to observe clear differences in amplitude and position of reflectivity bands around the fundamental absorption energy edge; so, different criteria to estimate Eg by Tauc Plot are discussed
Exploring Bistable Properties in AgCl-Ag Multilayer Nonlinear Structures for Blood Serum Analysis
Authors: Riabenko Iuliia , Beloshenko Konstantin
Published: October 2024

Silver transfer to interference minima in AgCl-Ag films creates periodic structures through interaction with the waveguide TE0-mode. This phenomenon enables the recording of Raman spectra of biological samples, potentially enhancing low-intensity signal registration.
Specificity of NY-ESO-1 Antibody Detection Using TFBG Plasmonic Sensor
Authors: Tan Linyao , Qu Hang , Chen Xiaoyong , Xu Yi-Wei , Mégret Patrice , Caucheteur Christophe , Hu Xuehao
Published: October 2024

Autoantibodies against New York esophageal squamous cell cancer 1 (NY-ESO-1) are essential for diagnosing esophageal cancer. This study introduces a surface plasmonic tilted fiber Bragg grating (TFBG) biosensor designed to detect NY-ESO-1 antibody and investigate its specificity.
Demonstration of Graphene Waveguide Photodetector Based on Photothermoelectric Effect
Authors: Huang Yishu , Reep Tom , Tsai Hung-Chieh , De Coster Jeroen , Brems Steven , Asselberghs Inge , Tielrooij Klaas-Jan , Van Thourhout Dries , Haffner Christian
Published: October 2024

We demonstrate a graphene waveguide photodetector featuring a responsivity of ~1.2 V/W. The photovoltage map measured under zero bias confirms that photothermoelectric effect is dominating.
BER measurement in data transmission with a double-pass SOA
Authors: Sakumoto Hiroya , Wang Yi , Feyisa Desalegn Wolde , Reniers Sander , Stabile Ripalta , Williams Kevin , Jiao Yuqing
Published: October 2024

We demonstrate transmitting NRZ-OOK PRBS31 signal at 25 Gb/s with a double-pass SOA, showing a 61% gain boosted with the same electrical power consumption while keeping almost the same BER as a conventional single-pass SOA.
Proposal for a 500 GHz Silicon Photonic Modulator
Authors: Sun Conglin , Kim Minkyu , Van Dorpe Pol , Catthoor Francky , Mazur Mikael , Van Campenhout Joris , Haffner Christian
Published: October 2024

We propose a silicon modulator concept utilizing organic electro-optical Pockels materials in a vertical gap configuration to reach 500 GHz bandwidth. Simulations show that optical losses can be ~0.5 dB/~0.2 dB for a 500 GHz/200 GHz design with a Vπ of <7 V/<3 V respectively.
Silicon Nitride Microring Resonator for Optical Frequency Comb Generation in Normal Dispersion
Authors: Nazneen Rifat , -Ladouceur Odile Liboiron
Published: October 2024

We measure a SiN microring resonator with a Q-factor of 7.78 × 104. Simulation shows that the resonator can generate six comb lines with 60 mW sources using four-wave mixing in normal dispersion.
Mastering Silicon Photonics Device Design for Scalable and Robust Optical Neural Networks
Authors: Ghanaatian Zahra , Shafiee Amin , Nikdast Mahdi
Published: October 2024

We demonstrate a design optimization approach for Mach–Zehnder Interferometers (MZIs) in optical neural networks under fabrication-process variations (FPVs). Our results show increased inferencing accuracy in the network under realistic FPVs by using optimized MZIs.
Direct Laser Writing of a Compact 1x4 Splitter for Multi-Core Optical Fibers
Authors: Baghdasaryan Tigran , Vanmol Koen , Thienpont Hugo , Berghmans Francis , Van Erps Jürgen
Published: October 2024

We used triangular cross-section multimode interference coupler, S-bends, and adiabatic tapers as building blocks to design and fabricate ultracompact 3D splitters for multi-core optical fiber with an insertion loss below -3 dB per channel.
Image-to-Image Computer Vision for Advanced Nanophotonic Fabrication and Design
Authors: Gostimirovic Dusan , Liboiron-Ladouceur Odile
Published: October 2024

We present PreFab, an image-to-image computer vision system that predicts and corrects nanofabrication variations in complex integrated photonic circuits with fine features, enabling higher precision, improved yields, and accelerated development of next-generation photonic technologies.
Supporting 100 Gb/s and 200Gb/s Optical Access for PON using Coherent Technologies
Authors: Laubach Mark
Published: October 2024

Demand for higher speed subscriber networks coupled with developing ecosystems for coherent point-to-point technologies suggest cost-effective re-use for 100 Gb/s and 200 Gb/s for the standardization of Coherent PON.
Holotomography and artificial intelligence: label-free 3D imaging, classification, and inference of live cells, tissues, and organoids
Authors: Park YongKeun
Published: October 2024

Holotomography (HT) is a powerful label-free imaging technique that enables high-resolution, three-dimensional quantitative phase imaging (QPI) of live cells and organoids through the use of refractive index (RI) distributions as intrinsic imaging contrast1-3. Similar to X-ray computed tomography, HT acquires multiple two-dimensional holograms of a sample at various illumination angles, from which a 3D RI distribution of the sample is reconstructed by inversely solving the wave equation.
Tunable Nanophotonic Materials for Multispectral Reconfigurability
Authors: Luo Yujie , Christensen Thomas , Ilic Ognjen
Published: October 2024

We show that active metasurface networks can accurately emulate and switch between complex spectral profiles, such as those of gases. This multispectral reconfigurability applies to coupled networks in active materials, including 2D or phase-change materials.
Transparent Conductive Oxides for Epsilon-Near-Zero and Integrated Photonics
Authors: Wang Alan X.
Published: October 2024

Transparent conductive oxides offer unique optical properties for epsilon-near-zero photonics and photonic integrated circuits. The research progress in energy-efficient optical modulators, tunable filters, and metasurfaces will be reviewed. We also discuss perspectives toward scalable manufacturing through integration with silicon photonics.
Harnessing Ultrafast Optical Pulses for 3D Microfabrication by Selective Tweezing and Immobilization of Colloids
Authors: Krishna Krishangi , Sun Jieliyue , Toussaint Kimani C.
Published: October 2024

We employ femtosecond-laser pulses for a two-step microfabrication process: optical tweezing of microparticles to target positions, followed by immediate particle immobilization by two-photon polymerization. The challenges and opportunities of this platform are discussed.
Advances in quantitative label-free imaging for micro/nano-scale object analysis
Authors: Rodrigo Jose A. , Alieva Tatiana
Published: October 2024

Quantitative label-free imaging provides information about the 3D shape of micro/nano-scale objects and their electric permittivity. Advantages and drawbacks of refractive index tomography and a technique based on nanoparticle manipulation by structured light are discussed.
Hollow Plasmonic 3D Metamaterials for LDOS Enhancement and Control of Light-Matter Interaction
Authors: Córdova-Castro R. M. , Jonker D. , Cabriel C. , Mamchur Yaryna , Izzedin I. , Susarrey-Arce A. , Krachmalnicoff V. , Boyd R. W.
Published: October 2024

We proposed to explore room-temperature quantum devices operating at the single-photon level, with functionalities that can be tailored changing different parameters of a plasmonic metamaterial composed of hollow truncated nanocones that greatly enhance the photonic density of states. We study numerically and experimentally the photonic properties of this material supporting very high field enhancement with dipolar and quadrupolar plasmonic modes as functions of angle and polarization of illumination. We measure the dependence of their resonance wavelengths on different device parameters and surrounding media of this new nanomaterial platform. Depending on the desired resonant wavelengths, this new material platform can be designed for applications in SERS, nonlinear, sensing, and single-photon emission control.
Laser-Assisted Deposition of Oxide Layers for Transparency in Different Wavelength Ranges
Authors: Bougdid Yahya , Kulkarni Gunjan , Chenard Francois , Sugrim Chandraika (John) , Kumar Ranganathan , Kar Aravinda
Published: October 2024

CO2 laser-assisted deposition of transparent chalcogenide As2S3glass and TiO2 films is reported. A theoretical model is developed to select the laser sintering parameters. The optical properties of transparent As2S3and TiO2 coatings are investigated.
Novel Porous-Cladding Polydimethylsiloxane Optical Waveguide for Biomedical Pressure Sensing Applications
Authors: Amouzou Koffi Novignon , Zimmermann Camila Aparecida , Romero Alberto Alonso , Sengupta Dipankar , Gravel Normand , Lina Jean-Marc , Ung Bora
Published: October 2024

We report a new concept of pressure sensor made from polydimethylsiloxane solid core and porous cladding that operates through frustrated total internal reflection. A high sensitivity to transverse compression of 0.22%/dB optical losses is demonstrated.
Spontaneous symmetry breaking in a coupled photonic crystal dimer with periodic driving
Authors: Bitha Rodrigues Dikandé , Stitely Kevin , Krauskopf Bernd , Broderick Neil G. R.
Published: October 2024

This study examines the interactions between two optical modes in a periodically driven photonic crystal dimer. We find that the system features spontaneous symmetry breaking of different types of solutions.
Exploiting time reversal symmetry for beam shaping in multimode nonlinear fiber optics
Authors: Poisson Arnaud , Tonello Alessandro , Couderc Vincent , Restoin Christine
Published: October 2024

We numerically study the nonlinear propagation in multimode GRIN fibers. By exploiting the time-reversal symmetry, we identify the conditions for robust on-demand modal distributions. We extend our study to the reversal of spatial beam self-cleaning.
Four Coherent Dispersive Waves Emission for OAM3,1 Mode in a Ring-Core Fiber
Authors: Geng Wenpu , Fang Yuxi , Zeng Zhi , Bao Changjing , Pan Zhongqi , Yue Yang
Published: October 2024

A ring-core fiber is designed to generate four DWs for OAM3,1 mode. Pumping under normal dispersion, the simulated coherent output spectrum spans 1100 nm with four distinct peaks at 760, 1130, 1430 and 1685 nm.