bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Technique For Enhancing Underwater Visibility Using Non-Local Stretch Directional Gradient
Authors: Chrispin Jiji A , Maik Vivek , Gowda Vijay Kumar 
Published: September 2022

Abstract
Owing to the many effects of the underwater medium, underwater images are often captured with a hazy quality. These effects are caused by suspended particles in the image forming phase, which cause light absorption and scattering. On account of these pictures with fluctuating levels of dimness and colour variation, traditional algorithms have several disadvantages. Underwater image enhancement’s main goal is to increase the clarity and contrast of underwater photographs in order to solve these issues. Our paper describes a novel technique by combining several algorithms characteristics for achieving the following goals: i) better scattering, (ii) grey world assumption, (iii) non-Local stretch Directional Gradient process. For example, a better scattering model would be better at modelling hazy scenes and overcoming the image illumination dimming effect. Second, for uniform visibility recovery on the captured picture, an appropriate gray world-assumption is used. Finally, the Non-Local stretch and Directional gradient filter work on the edge details and overall dual tone enhancement required for a high-quality picture. Simulation experiments indicate that the proposed methodology produces improved visual effects and has a greater impact on consistency metrics than other methods.
Skin Cancer Lesions Classification Using Probabilistic Neural Network
Authors: Prasad Kudumu Vara , Susmitha Bollamreddi , Chennu Tulasi , Bhanu Murthy Kambala Mithra Sai , Datta Meda Vishnu 
Published: September 2022

Abstract
One of the most frequent types of cancer is skin cancer. Skin cancer is one of a deadly disease caused due to the abnormal skin cell proliferation in the epidermis resulting in the formation of mass called as Tumor. The formed tumor can be cancerous known as Malignant, that is it can raise and can open out to the rest of the body and the other is non-cancerous tumor known as benign which can raise but it does not open out to the rest of the parts. Skin cancer is mainly caused because of exposure of skin to the harmful UV(Ultraviolet) radiation. If skin cancer is detected in early stage then there are high chances for successful skin cancer treatment. In this paper we are describing a model which uses deep learning technique and some Image processing techniques for distinguishing of skin cancer as benign tumor or malignant tumor. The proposed model gives results in less time and eliminates the cost compared to the formal strategy that is Biopsy which is used for skin cancer recognition. The proposed model uses image processing techniques like Pre-processing, different Segmentation techniques, Feature Extraction and deep learning technique PNN (Probabilistic Neural Network) is used for classification of the skin image.
Comparison of various CNN encoders for image captioning
Authors: Veena S , Ashwin K S , Gupta Prateek 
Published: September 2022

Abstract
Image captioning is the ability of machines to study the features of an image and then give a textual description of that image. It uses computer vision to extract the features from the image and natural language processing for generating the caption. Image captioning requires both Image analysis and natural language processing. It is a very important task for further research on visual intelligence in line with human perception. In this project we will compare the different CNN pretrained models that are available like VGG16, RESNET50, Xception and INCEPTION and find out which performs better for image captioning.
Analysis of various Pre-processing filtering methods for MRI brain tumour detection in a noisy environment
Authors: Jain Priyanka , Parmar Priyasha 
Published: September 2022

Abstract
Magnetic Resonance Imaging (MRI) is playing a very important role in the detection of various abnormalities in the human body. Biomedical image processing is helping us in the proper identification of various abnormalities such as a malignant tumour in various parts of the body. In this paper different types of filtering methods applied in the pre-processing stage have been compared. When MRI images have been corrupted by Gaussian noise then various filters are applied to obtain recovered MRI images. After performing filtering operation segmentation has been applied on MRI images to obtain tumour region. The processes have been implemented with the help of MatLab 2018.
Wave Active Low Pass Filter Employing Modern Active Block VDDIBA
Authors: Rana Prerna , Ranjan Ashish 
Published: September 2022

Abstract
This paper presents a second and third-order wave active low pass filter (WALPF) using modern active block Voltage Differencing Differential Input Buffered Amplifier (VDDIBA) with a lower supply voltage of 1V. The wave-active approach is chosen for the filter designing to get a higher order, lower sensitivity, modular and stable filter structure. The design procedure of WALPF involves the implementation of wave-active equivalent for series inductor and shunt capacitor. And it needs to realize the subtractor block physically, and the lossy subtractor integrator block using VDDIBA gives a flavor of differencing voltage property. So, the physical implementation of the subtractor block and the lossy subtractor integrator block goes very smoothly using this block. It is considered a possible reason for reducing active blocks and passive components. Theoretical justification of the proposed WALPF is achieved by using the wave-equivalent concept of the wave-active approach. This method of WAF design consists of only one resistor and capacitor, making the filter structure less complex easy to use with a cut-off frequency of 10MHz. Finally, the workability test is examined with the PSPICE simulation that results in the WALPF frequency response using 180 nm TSMC CMOS technology parameter for VDDIBA.
High Gain CMOS Transimpedance Amplifier For Near Infrared Spectroscopy Applications
Authors: Muthukumaran B. , Ramachandran B. 
Published: September 2022

Abstract
In this paper, design and analysis of High Gain CMOS Transimpedance Amplifier (HGCTIA) is presented which is greatly necessitated for frequency domain functional Near Infrared Spectroscopy (FD-f NIRS). Generally, feedback resistor and drain resistor play a major role in deciding TIA gain and bandwidth. Most of the research work have utilized only feedback resistor and drain resistor. Here, the gain improvement is greatly achieved by replacing the drain resistor by an active inductor which is designed using CMOS transistor. The active inductor loaded based TIA exhibits only 0.01mW power dissipation which is comparatively lesser than previous research works. Also the proposed design achieves maximum value of transimpedance gain 140dB, bandwidth of 10 MHz, where average noise over the bandwidth is 4.6pA/√Hz with 0.68nArms. Input referred noise is 3.38pA/√Hz. These results are obtained by simulating the proposed approach using cadence 45nm technology. The simulated results shows that the proposed HGCTIA is superior in terms of power, gain and bandwidth.
Design and Performance Analysis of Partially Depleted and Fully Depleted Silicon on Insulator MOSFET
Authors: Shashwat  , Singh Adarsh Kumar , Misra Rishabh , Wadhwa Girish , Nirosha R , Agarwal Rajesh 
Published: September 2022

Abstract
In this paper, Partially Depleted Silicon on Insulator (PDSOI) MOSFET and Fully Depleted Silicon on Insulator (FDSOI) MOSFET are designed, and the impact of n-type doping concentration, work function variation, gate oxide, and silicon layer thickness on the performance of the device is studied and analyzed. The floating body and associated kink effects present in a PDSOI device are also investigated in detail. In addition to this, comparisons are made between PDSOI and FDSOI MOSFET to analyze their performance for various device parameters. The threshold voltage rises with increasing Si surface thickness and source doping, according to the data found. The drain current increases as the N-type doping concentration develops in both PD and FDSOI MOSFETs, and conduction begins after a concentration of 3x1017 cm−3 for PD and 2x1017 cm−3 for FDSOI, before which conduction is not effective. For the same n-type doping concentration and gate work function, FDSOI has a higher drain current than PDSOI. FDSOI is better than PDSOI since it eliminates PDSOI’s defects and enhances its performance. The Silvaco Atlas-2D TCAD simulator is used to simulate the device using conventional architecture and models.
Design and Analysis of Partial shading of the PV System Integrated with High-Frequency Inverter and Rectifier Operation for the Electric Vehicle
Authors: Geetha P , Usha S 
Published: September 2022

Abstract
Solar photovoltaic cells are in high demand for sustainable energy generation because of their capacity to provide direct power. As a result, DC-DC converters that can enhance the output voltage and do so reliably while eliminating changes in solar panel outputs are required. Inconsistencies in sun-light availability, ambient temperature, and shadows, among many other considerations, cause the fluctuations. Compared to the typical DC-DC Boost converter, the suggested converter architecture has a higher efficiency of over 95%. In a resonant inductive coupled power transmission system for an electric vehicle, this research demonstrates partial shading of a 250-W PV solar-powered interfaced with a high-frequency resonant full-bridge inverter. The suggested system’s DC input is provided by a PV panel. The ratio of DC Input sources supplied to the high-frequency inverter is 1:3. For a fixed modulation of 0.7, the step modulated for a high-frequency inverter uses a pre-calculated switching angle. Due to a very high-frequency AC connection, the suggested system is more efficient than a traditional system of 50 Hz inverter operation and multiple-output transformer architecture. Zero Voltage Switching (ZVS) is ensured in this study, which decreases switching losses. In the MATLAB/ SIMULINK environment, the suggested approach has been validated. The research aims to investigate and illustrate the effect of partial shading with and without a bypass diode on the I (V) and P (V) properties of solar panels. Hence, the suggested approach’s performance is compared to the present method in terms of parameters, and 95 percent efficiency may be attained. When compared to shaded and unshaded situations, this paper displays greater feature modifications.
Adaptive Central Control Scheme and Investigation of Fault Current Contribution for Protection of Microgrid
Authors: Balasubramanian Sujatha , Preetha Roselyn J. , Srividya K.S. 
Published: September 2022

Abstract
Microgrids suffer from issues namely protection blinding, sympathetic tripping. Microgrids operate in which differs from the conventional power system. Micro-grids operate in grid-connected mode or islanded mode of operation. In islanded mode microgrids utilize distributed energy resources that are renewable such as solar, wind, along with energy storage systems. In both, the modes of the system undergo various challenges such as protection blinding, sympathetic tripping, or short circuit current in power electronic interfaced generation. This work focuses on the analysis of fault in both modes of operation as well as the issues that are specific to a microgrid. Hence adaptive settings of the relay are required to switch over under the different modes of operation. This work utilizes an adaptive central controller for MG protection. Hence the sensed data from the system is fed to the controller and managing the relay operation which is the IDMT relay. This work focuses on the relay setting and plug set for the relays under modes of operation. The detailed analysis is carried out in IEEE 13 bus system and adaptive relay setting calculation for adaptive centralized MG protection is carried out.
Modelling of Vehicle Dynamics and Determination of Energy Demand for Electric Vehicle
Authors: Kubendran V , Mohamed Shuaib Y , Preetha Roselyn J 
Published: September 2022

AbstractThe WLTP Class 3 driving cycle is used in this article for the design of a battery and super-capacitor for electric vehicles. The energy demand for electric vehicle is calculated using WLTP drive cycle and the total power required for electric vehicle is calculated by calculating tractive force. A hybrid energy storage system (HESS) overcomes numerous shortcomings of a battery energy storage system (BESS), including reduced battery life, limited power density, etc. In a proposed system, a Li-Ion battery is coupled with a super-capacitor/Ultra-capacitor as a bidirectional converter, where the Li-Ion battery is the primary energy source, while the Super Capacitor/Ultra-capacitor is an auxiliary energy source. The range of battery and Super Capacitor/ultra-capacitor sizes for Tata Nixon 2020 are calculated and simulated using the MATLAB/SIMULINK environment to verify the efficiency and effectiveness of the proposed model.
Implementation of Quantum Key Distribution network simulation in Quantum Channel
Authors: Praveen Kumar S. , Jaya T. , Rajalingam Prithiviraj 
Published: September 2022

Abstract
The aim is to analyze the efficiency of a communication method, Quantum key distribution. This newly popularized method of communication uses the principles of quantum mechanics. The simulation environment allows researchers to create complex network topologies and a high degree of control and repeatable experiments, allowing them to conduct studies and verify their outcomes. It would be costly to implement QKD in reality, which would need optical and Internet connections between network nodes and the verification of a certain network method or protocol. Thus, the performance analysis here is done in open-source software called NS-3 or Network Simulator- 3, which has an in-built module called QKD netsim for creating the quantum channel.
Campus Routing Using QR Code
Authors: Padmaja M , Geethasri K , Sai Kousik J , Vaishnavi M , Kranthi Sai B , Lokesh Nayak D 
Published: September 2022

Abstract
In today’s modernized world, proficiency is at a step forward expecting the man kind to be in advance. This elevation can be seen in various aspects of diversification which majorly include raising number of Smart cities around us. A smart city explains itself as the one, which consists of complex infrastructures, that takes help of communication technologies to increase operational efficiency. Increasing complexity in the infrastructure of institutions, organizations and even malls, make user more reliant on the navigation services. But these navigational services that are in use today are constrained to open areas. So, this Campus Routing using QR code is proposed, to provide better indoor navigation. It describes development of a web-based application that is designed for providing both outdoor and indoor routing to meet the user’s requirement and the same is extended to implement in exam halls for providing route pictures to students of different rooms. There are various solutions exist in the market for indoor navigation using NFC, Bluetooth, Wi-Fi, GPS, but their reliability at every situation is not ideal. Unlike previously proposed solutions this paper chose a different implementation technique by developing a full stack web application that helps in both indoor and outdoor navigation i.e., it involves creating a client interface at frontend and a server at backend. Maps used here are predefined using Auto-Cad tool, stored in database and are retrieved upon user’s request. These route pictures (Maps) can be accessed by the user through the mobile phone using QR code.
Smart Trolley Application with an Approximate Multiplier Approach Using Embedded Platform
Authors: Maria Dominic Savio M. , Deepa T. 
Published: September 2022

Abstract
Shopping malls, these days, are crowded and many people find it time-consuming and hard to shop. Locating a commodity coupled with standing in long queues for billing looks cumbersome. To overcome these difficulties, the authors of this paper, present the design of the product, smart trolley. When the customer enters the market, he has to log-in to the product and the map of the supermarket is displayed on the LCD screen. Later, once he starts shopping, upon entering each aisle, the details of the products in the aisle are displayed. For billing, the user has to scan the bar code for packed goods and based on the scanned code corresponding to the product, the price is displayed. For unpacked items such as fruits, vegetables etc, a picture of the commodity is taken which is classified with neural networks, the weight of the commodity is measured and the price is calculated with this information. Later, the customer has to click the finish button upon finishing shopping and pay via online transactions. This system design is validated with a prototype that has a camera, transducers, LCD screens RFID readers and raspberry Pi embedded in it. RFID technology is used for location tracking, cameras are used for scanning bar codes (packed goods) and taking snaps of commodities (unpacked) and a force transducer is used for measuring weight. Finally, the database images are multiplied with different level of approximate multipliers and various error level database has been created. The accuracy of all databases is tested with the VGG-16 network.
Using natural language processing to find research topics in Living Machines conferences and their intersections with Bioinspiration & Biomimetics publications
Authors: Carniel Théophile , Cazenille Leo , Dalle Jean-Michel , Halloy José 
Published: September 2022

Abstract
The number of published scientific articles is increasing dramatically and makes it difficult to keep track of research topics. This is particularly difficult in interdisciplinary research areas where different communities from different disciplines are working together. It would be useful to develop methods to automate the detection of research topics in a research domain. Here we propose a natural language processing (NLP) based method to automatically detect topics in defined corpora. We start by automatically generating a global state of the art of Living Machines conferences. Our NLP-based method classifies all published papers into different clusters corresponding to the research topic published in these conferences. We perform the same study on all papers published in the journals Bioinspiration & Biomimetics and Soft Robotics. In total this analysis concerns 2099 articles. Next, we analyze the intersection between the research themes published in the conferences and the corpora of these two journals. We also examine the evolution of the number of papers per research theme which determines the research trends. Together, these analyses provide a snapshot of the current state of the field, help to highlight open questions, and provide insights into the future.
Development of cannabidiol nanoemulsion for direct nose to brain delivery: statistical optimization, in vitro and in vivo evaluation
Authors: Ahmed Bakr , Rizwanullah Md , Mir Showkat Rasool , Akhtar M Shaheer , Amin Saima 
Published: September 2022

Abstract
Cannabidiol (CBD) is a prescribed drug for epilepsy but has low oral bioavailability and gastric instability. Because of the direct link between the nasal cavity and the central nervous system, intranasal administration of CBD as nanoemulsions which are the small sized lipid carriers seem to improve the bioavailability. CBD-nanoemulsions (NEs) were made using Capryol 90, Tween 80, and Transcutol P as oil, surfactant, and co-surfactant, respectively, following aqueous titration approach. Then, using the Box–Behnken design, CBD-NE was statistically optimised for the selection of desirable excipient concentrations in order to create the optimal CBD-NE formulation. As independent variables in the statistical design, Capryol 90 (oil; coded as A), Tween 80 (surfactant; coded as B), and Transcutol P (co-surfactant; coded as C) were used. The dependent variables were droplet size (DS; coded as R
1) and polydispersity index (PDI; coded as R
2). The average DS, PDI, and the zeta potential of the optimized CBD-NEs were observed to be 88.73 ± 2.67 nm, 0.311 ± 0.015, and −2.71 ± 0.52 mV respectively. Pure CBD and lyophilized CBD-NE Fourier-transform infrared spectra demonstrated no physicochemical interaction between excipients and the drug. Furthermore, differential scanning calorimetry and x-ray diffraction measurements revealed the amorphous CBD in the NE. As compared to pure CBD, the optimised CBD-NE showed considerably better in vitro drug release as well as ex vivo nasal permeability. The drug targeting efficiency and direct transport percentage of the optimised CBD-NEs were found to be 419.64% and 76.17%, respectively, in this research. Additionally, pharmacokinetic investigations after intranasal administration of CBD-NE revealed considerably higher drug concentrations in the brain with better brain targeting efficiency. As a result, the development of CBD-NE may be an excellent alternative for better intranasal delivery.
Design, synthesis, and characterization of a novel dual cross-linked gelatin-based bioadhesive for hard and soft tissues adhesion capability
Authors: Pirmoradian Maryam , Hooshmand Tabassom , Najafi Farhood , Haghbin Nazarpak Masoumeh , Davaie Sotoudeh 
Published: September 2022

Abstract
Many surgical treatments require a suitable tissue adhesive that maintains its performance in wet conditions and can be applied simultaneously for hard and soft tissues. In the present study, a dual cross-linked tissue adhesive was synthesized by mixing the gelatin methacryloyl (Gel-MA) and gelatin-dopamine conjugate (Gel-Dopa). The setting reaction was based on a photopolymerization process in the presence of a combination of riboflavin and triethanolamine and a chemical cross-linking process attributed to the genipin as a natural cross-linker. Modified gelatin macromolecules were characterized and the best wavelength for free radical generation in the presence of riboflavin was obtained. Tissue adhesives were prepared with 30% hydrogels of Gel-MA and Gel-Dopa with different ratios in distilled water. The gelation occurred in a short time after light irradiation. The chemical, mechanical, physical, and cytotoxicity properties of the tissue adhesives were evaluated. The results showed that despite photopolymerization, chemical crosslinking with genipin played a more critical role in the setting process. Water uptake, degradation behavior, cytotoxicity, and adhesion properties of the adhesives were correlated with the ratio of the components. The SEM images showed a porous structure that could ensure the entry of cells and nutrients into the surgical area. While acceptable properties in most experiments were observed, all features were improved as the Gel-Dopa ratio increased. Also, the obtained hydrogels revealed excellent adhesive properties, particularly with bone even after wet incubation, and it was attributed to the amount of gelatin-dopamine conjugate. From the obtained results, it was concluded that a dual adhesive hydrogel based on gelatin macromolecules could be a good candidate as a tissue adhesive in wet condition.