bluuebunny/crossref_metadata_2025_split huggingface dataset:
Observation of blackbody-like emission from laser-induced plasma at early times and implications for thermal equilibrium
Authors: Nedić Nikodin V , Bukvić Srdjan , Dojić Dejan , Rajačić Luka , Skočić Miloš 
Published: September 2022

Abstract
We present spectroscopic investigation of laser-induced plasma at an early stage of development when the Nd:Yag laser still illuminates the copper target. According to experiments during this phase the plasma nearly meets the three requirement characteristics for a black body: the spectrum is continuous and close in form to Planck’s distribution, the plasma is nontransparent, while reflectivity is close to zero. The surface temperature of the plasma is derived from continuous nearly black-body spectra, emitted by the plasma. The spectra are recorded with temporal resolution of 1 ns, and with spatial resolution of 50 μm in the axial direction. At a later stage, when the plasma becomes transparent, the absorption properties of the plasma are estimated by measuring attenuation of two low-power diagnostic CW lasers (a He–Ne 633 nm and a diode laser 400 nm) applied side-on. By assuming that inverse bremsstrahlung is the dominant absorption mechanism and by comparing absorption coefficients for 633 nm and 400 nm wavelength radiation we derived values for electron density and electron temperature inside the plasma.
Tevatron greatest hits
Authors: Denisov Dmitri , Vellidis Costas 
Published: September 2022

Abstract
The Tevatron collider led the World energy frontier program in particle physics during the late 20th and early 21st centuries. During this exciting period the standard model of particle physics was in its final stages of development and the search for physics beyond the standard model became one of the main research topics. In this review article we summarize the design and performance of the Tevatron collider and its two detectors, CDF and D0, as well as their evolution. Highlights of the Tevatron scientific results are provided, including the discovery of the top quark and measurements of its properties, studies and discoveries of the particles containing heavy quarks, precision studies of the strong and electroweak forces, searches for beyond the standard model particles and interactions, as well as the hunt for the Higgs boson.
Interacting particles in an activity landscape
Authors: Wysocki Adam , Dasanna Anil K , Rieger Heiko 
Published: September 2022

Abstract
We study interacting active Brownian particles (ABPs) with a space-dependent swim velocity via simulation and theory. We find that, although an equation of state exists, a mechanical equilibrium does not apply to ABPs in activity landscapes. The pressure imbalance originates in the flux of polar order and the gradient of swim velocity across the interface between regions of different activity. An active–passive patch system is mainly controlled by the smallest global density for which the passive patch can be close packed. Below this density a critical point does not exist and the system splits continuously into a dense passive and a dilute active phase with increasing activity. Above this density and for sufficiently high activity the active phase may start to phase separate into a gas and a liquid phase caused by the same mechanism as motility-induced phase separation of ABPs with a homogeneous swim velocity.
Robust orbital diamagnetism in correlated Dirac fermions
Authors: Tada Yasuhiro 
Published: September 2022

Abstract
We study orbital diamagnetism at zero temperature in (2 + 1)-dimensional Dirac fermions with a short-range interaction which exhibits a quantum phase transition to a charge density wave (CDW) phase. We introduce orbital magnetic fields into spinless Dirac fermions on the π-flux square lattice, and analyze them by using infinite density matrix renormalization group. It is found that the diamagnetism remains intact in the Dirac semimetal regime, while it is monotonically suppressed in the CDW regime. Around the quantum critical point of the CDW phase transition, we find a scaling behavior of the diamagnetism characteristic of the chiral Ising universality class. Besides, the scaling analysis implies that the robust orbital diamagnetism at weak magnetic fields in a Dirac semimetal regime would hold not only in our model but also in other interacting Dirac fermion systems as long as scaling regions are wide enough. The scaling behavior may also be regarded as a quantum, magnetic analogue of the critical Casimir effect which has been widely studied for classical phase transitions.
Classification of static spherically symmetric perfect fluid space-times via conformal vector fields in f(T) gravity
Authors: Hussain Fiaz , Ali Murtaza , Ramzan Muhammad , Qazi Sabiha 
Published: September 2022

Abstract
In this paper, we classify static spherically symmetric (SS) perfect fluid space-times via conformal vector fields (CVFs) in f(T) gravity. For this analysis, we first explore static SS solutions by solving the Einstein field equations in f(T) gravity. Secondly, we implement a direct integration technique to classify the resulting solutions. During the classification, there arose 20 cases. Studying each case thoroughly, we came to know that in three cases the space-times under consideration admit proper CVFs in f(T) gravity. In one case, the space-time admits proper homothetic vector fields, whereas in the remaining 16 cases either the space-times become conformally flat or they admit Killing vector fields.
Advanced Foot step power generation system for mobile charging
Authors: Sai Bhargav K. , Guru Kiran Reddy L. , Patel Rushik P. B , Mounish Reddy T. , Shilpa Bagade 
Published: September 2022

Abstract
The major focus of this study is the generation of electric power from people’s footsteps and the pressure applied when walking. “Advanced Foot Step Power Generation System” refers to the mechanical power transformation into electrical power as a result of the pressure generated by the footstep and the use of transducers. The power-producing floor generates power, which is essentially the conversion of kinetic energy into electrical energy. Today’s electricity demand is growing, and existing power generation sources are unable to meet this worldwide challenge. The fundamental issue of the energy crisis is the demand and supply imbalance. Although it will not be enough to meet the world’s overwhelming need for electrical energy, it will be able to transform and reduce dependency on traditional methods of generating electricity. It can be implemented on roadside footpaths, parks and jogging tracks, as well as many other public places, such as airports, and will have a significant impact on electrical power generation.
Health monitoring smart glove using esp32 microcontroller
Authors: Jahnavi T S , Thumma Naveen , Reddy Kolla Abhishek , Teja Upadarsta V R S S H , Gunasree M , Kiran M 
Published: September 2022

Abstract
Even after voice assistants, virtual assistants, and other new technologies have come into existence, many are still facing problems to use them conveniently and effectively. Our project is mainly applicable to old people, physically challenged, and bedridden people. Our project application areas are hospitals and old age homes. During emergency situations where the user is not able to access his/her mobile phone, our prototype can handle such situations effectively by detecting the user’s hand gestures and sending alerts to caretakers and hospitals. Our model also has a medical alert system. According to the prior initialization of the time for the medicines to be taken, this prototype alerts the user at that exact time. The alert message is displayed on the OLED and also through a buzzer. This glove has a temperature sensor, flex sensors, and pulse-oxy sensors embedded which give the continuous readings of user-health parameters and are displayed on the OLED placed on the glove. The main feature of the glove is to communicate the needs of the user which can be accomplished by a flex sensor.
IOT Based Moisture Measurement and Conveyor Belt Monitoring in Yarn Mill
Authors: Kalavathi Devi T. , Madhan Mohan M. , Baluprithviraj K.N. , Poojashri V. , Swetha A. , Vasuki P. 
Published: September 2022

Abstract
Yarn manufacturing in spinning mills is done when the twisted length of fiber goes to cheese, doubling, and winding machines. The humidity and temperature must be maintained to ensure the yarn quality. The conveyor belts have to be monitored continuously to avoid the interruption of the belts. This paper provides a solution to maintain the precise range of humidity and temperature and also to surveil the conveyor belts. The system contains a DHT sensor and an IR sensor. If the DHT sensor detects the increase in the moisture level or temperature, the signal is sent to the controller, and using a relay, either the heater or the cooler is activated respectively. The humidity level and the temperature of the yarn are displayed on the LCD. Simultaneously, the values can also be viewed on the user’s mobile application Blynk using an IoT. Another feature of this application is the continuous monitoring of the conveyor belt. If the belt stops, the IR sensor detects it, and the user is alarmed by a buzzer indicating that action is required to restart. This method reduces yarn breakage and improves the quality of the yarn. It provides continuous monitoring; the IoT application provides real-time values.
Reduction of Electromagnetic Interference Using EMI Filter in a Buck Converter
Authors: Ruth Anita Shirley D , Sasipriya S , Sibi T , Ragul B , Praveen S 
Published: September 2022

Abstract
The presence of non-isolated DC-DC buck converter plays a crucial role in electrification of aircraft, bio-medical and automotive devices. To obtain output devoid of interference from external sources, maximizing specific power or power density of the EMI filter is necessary. This requires a filter that is capable of eliminating or filtering these unwanted surges or spikes in the power converters. In this paper an EMI filter is placed in the buck converter operating with common mode/differential mode. An EMI filter is first designed taking into account the impact of interference in the power rails and the ground rails. The model is implemented and the output of the buck converter in the presence and absence of the proposed EMI filter is analysed.
RETRACTED: Early Detection of Seizure Using Electrical Brain Activity
Authors: Sangeetha V , Shanthini E , Aravindhan T , Dineshkumar S , Ashwin Shivaa D 
Published: September 2022

Abstract
Epilepsy is a chronic brain condition characterized by an uncontrollable electric blast in the brain, manifested as Epilepsy seizures. More than one percent of the world population is affected by Epilepsy seizures. This framework employs a few corporal boundaries, such as temperature, pulse, and movement limits. The device measures the electrical activity of the brain by using an EEG sensor and alerts the patient according to the electrical brain activity. This paper focuses on the development of early detection of seizures by EEG to alert the patient to changes in his/her body.
Simulation Study of Hetero-Junction Single Gate Extended Source TFET
Authors: Singh Suryavansh , Roy Saurav Guha , Kumari Anjali , Chander Sweta , Sinha Sanjeet Kumar , Chaudhary Rekha 
Published: September 2022

Abstract
The paper provides the information regarding the examination of Uni-Gate-Extended Source TFET w.r.t the doping concentration of source, drain and channel and device’s dimensions. The moto of extending the source into channel is to enhance the point to point tunneling. 2D simulations in TCAD tool are carried out to analyse and investigate the performance of proposed device. Because of the transposed SS down the thermionic limit of 60 mV/decade, TFETs can be considered as the most trustworthy devices that have lower power consumption and that’s why they are among the deserving devices for upcoming future CMOS logic applications. Although the TFET marks have been examined in fewer material systems, they are burdened by low ON-currents. We discussed the impact of sound on Tunnel FET devices and circuits. The dialogue is designed for the sound of a random noise effects. The paper also deals with configuration of gm and gd and their obtained significant values are rise up in the graph till 1x10-4 V-1 and 2x10-4V-1.
Design of Montgomery Multiplier – RSA Algorithm
Authors: Venkatalakshmi K , Gayathri Pamuru , Likhitha Tadakaluru Sai , Shinde Sushmitha , Pavan Kumar MOV. 
Published: September 2022

Abstract
In cryptography, during the process of encryption, we use multiplication modulo architectures (2^n- 1) and (2^n+ 1) are proposed that enable the implementation of very efficient combinational and pipelined circuits for modular arithmetic. This project is an improvisation of existing modulo multiplier architectures for higher speed and regularity. We use the Montgomery multiplier in this project for the RSA algorithm. Hence, the IDEA block cipher is represented as a high-performance modulo multiplier adder. The circuits that arise are compared qualitatively and quantitatively for the RSA algorithm.
Hybrid Precoder Design Using Alternating Minimization Algorithm in MultiCell Multi-User Millimeter-Wave Communications for Massive MIMO
Authors: Al Imran Md. Ibrahim , Hossain Md. Farhad , Shabab Rashid 
Published: September 2022

Abstract
In the field of upcoming generation in wireless communication technology there is an extreme demand for higher bandwidth which is expected to be fulfilled by the frequency spectrum ranging from 30GHz to 300GHz which in other words can be defined as millimeter wave (mmWave). But it is a fact that, the mmWave technology lacks the simplicity in the design of precoder. There is higher power loss and higher cost in the baseband precoding in the case of fully digital baseband precoder. As the supported number of analog-to-digital (ADC) converters is very few, the mmWave technology requires ‘Hybrid Precoder’ which may reduce the loss of extensive power and lessen cost. The cost-effective hybrid precoder transceiver formulation has not been standardized yet. In this paper, we proposed the design of an optimal hybrid precoder in fully connected structure which has a higher complexity but lower cost and lower power consumption in the case of multi-cell multi-user massive MIMO. We have used Alternating Minimization Algorithm for getting the optimal Reimannian manifold solution. Here the comparison between the Digital Baseband precoder performance and the Hybrid Precoder performance has been done using simulation tools.
Partial Power Processing Based Bidirectional Converter for Electric Vehicle Fast Charging Stations
Authors: Geetha V M , Saravanan S , Swathisriranjani M , Satheesh C S , Saranraj S 
Published: September 2022

Abstract
This paper focuses on the design of a charging unit for an electric vehicle fast-charging station. Electric Vehicle is turning into a real alternative to conventional combustion-based vehicles due to their reduced greenhouse emissions. The conventional system experiences harmonic distortions, losses and takes more time to charge. To overcome these problems, new methods and techniques are established here.
With the help of a bidirectional-based converter, electric vehicle charging stations offer quick charging. When using a three-phase supply, phase voltage is given to the suggested converter. In conventional type converters, harmonic distortions are inherent; however, we can lessen voltage distortions by employing bidirectional converters. When tested with a prototype model featuring the suggested converter, the voltage ripple factor is quite low. Phase-shifting pulse width modulation is the topology employed in this procedure. The output voltages are controlled by a precise and simple algorithm. We can also use artificial intelligence gadgets to improve the circuit in the future. By comparing the input and output voltages in the feedback system, we can eliminate both steady-state and transient errors. The charging stations implemented in various areas are used effectively for efficiently charging Electric vehicles. The number of components is reduced compared to traditional converters and thus increasing the efficiency of bi-directional converters with less cost. This charger is also verified for fluctuations in power supply and supply voltages with higher magnitudes. The proposed charger gives us improved power factor and efficiency.
Friend Recommendation System using Image Encryption and Deep learning
Authors: Mohammed Yaseen M. , Akilan M. , Ranjith A.G. , Soundariya S. , Manisekaran S.V. , Ramakrishnan S. 
Published: September 2022

Abstract
The recommendation system functions similarly to a content filtering system, providing information depending on the preferences and behavior of the user. People use image sharing platforms such as Facebook, LinkedIn, and Instagram to share photographs of various elements to convey their sentiments with linked peers. As image sharing has been increasingly popular among individuals in recent years, it plays an important part in our daily lives. However, because of photo leaks and misuse, people are becoming increasingly concerned about their privacy. Encrypting photographs before publishing to social media is a better approach but decrypting the images and then searching for comparable images is computationally costly. The prior model advocated encrypting pictures using AES encryption and classifying them with deep autoencoders which is only a 2-step compression technique and takes quite more time for classifying. We provide a feasible privacy-protected friend recommendation system in proposed model by encrypting images using the Gaussian blur technique and a deep learning strategy for feature extraction and image classification for user recommendation. For training the dataset, the deep learning system utilizes the Keras model with CNN method, and a new model is generated from the features extracted from the blurred images. After that, the test dataset is compared to the model developed for similar image prediction. The accuracy measurements used to plot the graph are val acc and val loss. The accuracy result for the original image is 91.8%, while the accuracy result for the blurred image is 86.2% percent, demonstrating that our model is highly efficient and results in lower data loss.
Brain Tumor Segmentation and survival prediction using 3D U-net
Authors: Srinidhi Kotha , Ashwini Musthyala , Sree Banala Sowjanya , Apoorva Pinumalla , Akshitha Vadla , Khasim K.N.V. 
Published: September 2022

Abstract
Detecting Brain Tumor is a critical problem in the medical field and analyzing its location and size has been a challenging task for doctors. Designing automated brain tumor systems for MRI is one of the important factor in this decade, to avoid high expenses, low accuracy due to parallax errors and time consumption. Automated systems assist in diagnosis and early detection of tumors, which allows physicians to focus more on treating a patient. A method based on Convolutional Neural Network (encoder decoder architecture) captures 3D Flair (MRI) for glioblastomas as an input, which could be anywhere, any shape or size of the brain. These factors made us to investigate for an artificial intelligence system that utilizes the flexibility of a highly efficient neural network with an astonishing efficiency. The U-Net model is essential for achieving optimal performance in segmenting brain tumor and patient stage. The current approach uses 3d image instead of 2d image for proper diagnosis.
An Analysis of Machine Learning-Based Android Malware Detection Approaches
Authors: Srinivasan R. , Karpagam S , Kavitha M. , Kavitha R. 
Published: September 2022

Abstract
Despite the fact that Android apps are rapidly expanding throughout the mobile ecosystem, Android malware continues to emerge. Malware operations are on the rise, particularly on Android phones, it make up 72.2 percent of all smartphone sales. Credential theft, eavesdropping, and malicious advertising are just some of the ways used by hackers to attack cell phones. Many researchers have looked into Android malware detection from various perspectives and presented hypothesis and methodologies. Machine learning (ML)-based techniques have demonstrated to be effective in identifying these attacks because they can build a classifier from a set of training cases, eliminating the need for explicit signature definition in malware detection.
This paper provided a detailed examination of machine-learning-based Android malware detection approaches. According to present research, machine learning and genetic algorithms are in identifying Android malware, this is a powerful and promising solution. In this quick study of Android apps, we go through the Android system architecture, security mechanisms, and malware categorization.
Radiomics software comparison using digital phantom and patient data: IBSI-compliance does not guarantee concordance of feature values
Authors: Paquier Zelda , Chao Shih-Li , Acquisto Anaïs , Fenton Chifra , Guiot Thomas , Dhont Jennifer , Levillain Hugo , Gulyban Akos , Bali Maria Antonietta , Reynaert Nick 
Published: September 2022

Abstract
Introduction. Radiomics is a promising imaging-based tool which could enhance clinical observation and identify representative features. To avoid different interpretations, the Image Biomarker Standardisation Initiative (IBSI) imposed conditions for harmonisation. This study evaluates IBSI-compliant radiomics applications against a known benchmark and clinical datasets for agreements. Materials and methods. The three radiomics platforms compared were RadiomiX Research Toolbox, LIFEx v7.0.0, and syngo.via Frontier Radiomics v1.2.5 (based on PyRadiomics v2.1). Basic assessment included comparing feature names and their formulas. The IBSI digital phantom was used for evaluation against reference values. For agreement evaluation (including same software but different versions), two clinical datasets were used: 27 contrast-enhanced computed tomography (CECT) of colorectal liver metastases and 39 magnetic resonance imaging (MRI) of breast cancer, including intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) MRI. The intraclass correlation coefficient (ICC, lower 95% confidence interval) was used, with 0.9 as the threshold for excellent agreement. Results. The three radiomics applications share 41 (3 shape, 8 intensity, 30 texture) out of 172, 84 and 110 features for RadiomiX, LIFEx and syngo.via, respectively, as well as wavelet filtering. The naming convention is, however, different between them. Syngo.via had excellent agreement with the IBSI benchmark, while LIFEx and RadiomiX showed slightly worse agreement. Excellent reproducibility was achieved for shape features only, while intensity and texture features varied considerably with the imaging type. For intensity, excellent agreement ranged from 46% for the DCE maps to 100% for CECT, while this lowered to 44% and 73% for texture features, respectively. Wavelet features produced the greatest variation between applications, with an excellent agreement for only 3% to 11% features. Conclusion. Even with IBSI-compliance, the reproducibility of features between radiomics applications is not guaranteed. To evaluate variation, quality assurance of radiomics applications should be performed and repeated when updating to a new version or adding a new modality.