bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Film Festival Celebrates the Pacific Islands
Authors: Labbé Emilie , Zerouki Shania , Zhao Linlin 
Published: August 2021

Abstract
FIFO stands for Festival International du Film Documentaire Océanien (International Festival of Oceanic Documentary Films). Created in 2004, the festival features documentaries on the theme of ‘Oceania’, an important goal being to promote the southern Pacific region for its diversity and authenticity. FIFO has been influential in developing the audio-visual sector in this part of the world. It brings together most of the region’s industry professionals: producers, technicians, directors, television channels and foreign film festival representatives.

Information
For Skema: Written on the basis of interviews with Miriama Bono, President of FIFO.
© CAB International 2021
Improving resistance training prescription through the load‐velocity relationship in breast cancer survivors: The case of the leg‐press exercise
Authors: Díez‐Fernández David M. , Baena‐Raya Andrés , Alcaraz‐García Celia , Rodríguez‐Rosell David , Rodríguez‐Pérez Manuel A. , Soriano‐Maldonado Alberto 
Published: August 2021

ABSTRACTThe aims of this study were: (i) to analyse the load‐velocity relationship in the bilateral leg‐press exercise in female breast cancer survivors, (ii) to assess whether mean velocity (MV) or peak velocity (PV) show stronger relationship with the relative load, and (iii) to examine whether linear (LA) or polynomic (PA) adjustment predict the velocities associated with each %1RM with greater precision. Twenty‐two female breast cancer survivors (age: 50.2 ± 10.8 years, weight: 69.6 ± 15.2 kg, height: 160.51 ± 5.25 cm) completed an incremental load test until 1RM in the bilateral leg‐press exercise. The MV and the PV of the concentric phase were measured in each repetition using a linear velocity transducer, and were analysed by regression models using LA and PA. A very close relationship of MV (R 2 = 0.924; p < 0.0001; SEE = 0.08m.s−1 by LA, and R² = 0.952; p < 0.0001; SEE = 0.063 m.s−1 by PA) and PV (R² = 0.928; p < 0.0001; SEE = 0.119 m.s−1 by LA and R² = 0.941; p < 0.0001; SEE = 0.108 m.s−1 by PA) with %1RM were observed. The MV of 1RM was 0.24 ± 0.03 m·s−1, whereas the PV at 1RM was 0.60 ± 0.10 m.s−1. A comprehensive analysis of the bilateral leg‐press load‐velocity relationship in breast cancer survivors is presented. The results suggest that MV is the most recommendable velocity variable to prescribe the relative load during resistance training, and that the PA presents better accuracy to predict velocities associated with each %1RM, although LA is sufficiently valid to use this model as an alternative to the quadratic model. The implications for resistance training in breast cancer are discussed.Highlights
The load‐velocity relationship in the bilateral leg‐press exercise was described in female breast cancer survivors.
The mean velocity is the most recommendable velocity variable to prescribe the relative load during resistance training in this population.
The polynomial adjustment presents a better accuracy to predict velocities associated with each %1RM, although the linear adjustment is sufficiently valid as an alternative.
This study will likely contribute to improving exercise prescription and monitoring in breast cancer survivors.
Fredholm determinant representation of the homogeneous Painlevé II τ-function
Authors: Desiraju Harini 
Published: August 2021

Abstract
We formulate the generic τ-function of the homogeneous Painlevé II equation as a Fredholm determinant of an integrable (Its–Izergin–Korepin–Slavnov) operator. The τ-function depends on the isomonodromic time t and two Stokes parameters. The vanishing locus of the τ-function, called the Malgrange divisor is then determined by the zeros of the Fredholm determinant.
The statistics of the ordering of chiral ribbons on a honeycomb lattice
Authors: McCarthy Maxine M , Fall William S , Zeng Xiangbing , Ungar Goran , Gehring Gillian A 
Published: August 2021

Abstract
A novel model, devised to describe spontaneous chirality synchronization in complex liquids and liquid crystals, is proposed and studied. Segments of ribbon-like molecular columns with left- or right-handed 180° twist lie on the bonds of a honeycomb lattice so that three ribbons meet in a vertex of the hexagonal honeycomb. The energy of each vertex is a minimum if the three ribbons have the same chirality, −ɛ, and is +ɛ otherwise, and the ground state is homochiral, i.e. all ribbons have the same handedness. The energy levels for two vertices linked by a single ribbon are either −2ɛ, 0 and +2ɛ in this vertex model. Monte Carlo simulations demonstrate that this model is identical to an Ising spin model on a Kagome lattice, for which the site energy structure is quite different. The equivalence of the ordering of the vertex and Ising spin models is also shown analytically. The energy difference between the disordered and ground states, 4J in the spin model, is related to the transition temperature for the Kagome lattice using the exact result, T
c = 2.14 J. The ordering energy difference for a single site is 50% higher for the vertex model. The thermodynamic energy for the vertex model is corrected by a factor of 1/3 due to double counting and this makes the specific heat of the vertex model also equal to that of the spin model as expected. Other similar models where there is an unusual relation between the site and thermodynamic energies are discussed briefly.
Internet of things enabled smart baggage follower with theft prevention
Authors: Paidimarry Sai Nidhi , Kishor Kumar Reddy C , Lolla Lalitha Gayatri 
Published: August 2021

Abstract
Innovations are advanced to reduce human endeavors and to ensure security. Mechanical innovations decline manual exertion and make human-machine communication. This paper discusses one such space where enablements result in decreasing endeavour and augmentation in security. A baggage that follows the human is planned, using one of the brilliant advancements in gadgets. It helps auto trailing, lost stuff recuperation through GSM and GPS, void battery gadgets resuscitating, hindrance discovery, alarming and keen opening.
Performance evaluation of IPv4-IPv6 tunneling procedure using IoT
Authors: Jain Amit , Singh Manpreet , Bhambri Pankaj 
Published: August 2021

Abstract
It has become a high need for specialist co-ops, endeavors, IP apparatuses producers, application designers, and governments to start their organizations of IPv6. Consistent movement from IPv4 to IPv6 is difficult to accomplish. Along these lines, a few instruments are required which guarantees smooth, stepwise, and free change to IPv6. Not exclusively is the change, yet the reconciliation of IPv6 is likewise required into the current systems. The arrangements are to be partitioned into three classes: Tunneling, Dual-Stack, and Translation. Numerous individuals believe that NAT is a superior methodology yet Tunneling is a liked and most adaptable approach to convey IPv6 in existing IPv4 situations. IPv6 can be empowered any place IPv4 is empowered alongside the related highlights needed to make IPv6 routable, exceptionally accessible, and secure. These current places of business the difficulties as far as availability, security, portability, and unwavering quality. The paper centers around the future works and vision expected to execute the Internet of Everything to arrive at an interoperable, trustable, versatile, conveyed, significant, and ground-breaking empowering agent for rising applications. The overall accuracy of the methods is calculated for transmitted packets during transmission and delay of the packets at different data rates. So there is a huge improvement at a higher data rate. Hence, the examination of IPv4, 4to6 passage, and IPv6 systems present us with their exhibition qualities through measurable investigation. The insights acquired from reproduction give us that the throughput execution of IPv6 is far superior to IPv4 and 4to6 passage. IPv6 performs better under explicit occasions. By considering the exhibition gauges the IPv6 convention has better transmission proficiency and high throughput. Quantitatively, the proposed method has outperformed 51.19% for different data rates and 18.90% for the same data rate in the case of IPv4. 64.34% for different data rates and 35.53% for the same data rate in the case of IPv6. 61.43% for different data rates and 29.27% for the same data rate in the case of Tunnelling.
Synchronizing asynchronous mobile robots with limited visibility using lights
Authors: Das D , Mukhopadhyaya S , Ghosh Mrityunjay 
Published: August 2021

Abstract
There are three models of automated robots based on their activation schedules and time notions. They are FSYNC, SSYNC and ASYNC Model. The FSYNC-fully synchronous robots have the common notion of time and follow a global round of time. In every turn, all the robots are active and perform their job in synchronization. All the robots have the same notion of time in the SSYNC-semi-synchronous model, whereas in this model, all robots may not be active in each round. The activation time of ASYNC-asynchronous is independent and unpredictable. Research is ongoing to vanish the difference between asynchrony, semi-synchrony and synchrony by equipping the robots with various combination of lights and snapshots. Most of the research has been done on robots with unlimited visibility capabilities. In these works, a robot can view the colors of all other robots and based on that the decision is taken to change its own color thus achieves synchronization. Decision taking becomes challenging if the robots have limited view of the other robots. This paper proposed a technique of synchronizing the robots which are asynchronous by nature, using observable colored lights, where the robots have limited range of visibility.
Investigating weld strength of AA8011-6062 alloys joined via friction-stir welding using the RSM approach
Authors: Akhai Shalom , Srivastava Prateek , Sharma Venktesh , Bhatia Amit 
Published: August 2021

Abstract
In this study, an effort has been made for analyzing the results of the weld strength of aluminum composites AA6061 and 8011 which were developed by friction stir welding (FSW), via response surface methodology (RSM). The RSM approach was adopted considering rotational speed (RS) of 1200, 1300 and 1400 rpm, welding speed (WS) of 75,100 and 125 mm/min and axial force (AF) 5, 6 and 7 KN as the process parameters and output weld characteristic was obtained in terms of the weld strength. Design-Expert software version 11 was used in this paper to plan the survey and generate response surface plots. This investigation revealed that the best welding strength of AA6061 and 8011 aluminum amalgams obtained was 127 MPA, in run no. eight which had parameters RS 1400 RPM, WS 100 mm/min, and AF 7 KN. The obtained values of results were further analyzed through ANNOVA statistical analysis for obtaining the percentage contribution of selected variable parameters towards strength enhancement. The AF contributed significantly around 90%, RS contributed 10 % and contribution of WS was minimal for selected ranges to enhance the strength quality of the weld joint.
IoT Based Smart and Portable System for Remote Patient Monitoring and Drug Delivery
Authors: Kumar Naveen , Kaushal Rajesh Kumar , Panda Surya Narayan 
Published: August 2021

AbstractIn recent, there has been significant development in the healthcare technology particularly due to Internet of Things (IoT). The ubiquitous computing has brought a progressive change in the field of healthcare. In this way, the wellbeing experts are serving the society in a superior manner by utilizing such IoT based gadgets. This paper presents an IoT based model “Smart Portable Intensive Care Unit” for real-time patient monitoring with an additional feature of drug delivery from the remote location. The proposed model assisting the healthcare professionals and the relatives of the patient to monitor the physiological data of the patient from the remote location. The patient’s physiological data is transmitted to the cloud. An android based mobile application is developed to fetch the patient’s data from the cloud database in real-time. The authenticity of the user is maintained throughout the data communication process. The patient’s data is transmitted on the mobile application of the doctor both in analog and digital form. The doctor can also set the flow of drug infusion from a remote location. The proposed model can be effectively used for the patients admitted in the hospital or inside the ambulance.
Educational Data Mining: A Review
Authors: Bachhal P. , Ahuja S. , Gargrish S. 
Published: August 2021

Abstract
Data mining in the field of education plays a vital role. The main objective of this analysis is to understand how researchers have done data mining in the past and the current data mining developments in educational research. It describes how academic data and learning analytics applied to academic data. EDM uses computational methods to evaluate data concerning education to research questions related to education. This paper discusses the most important studies conducted to date in this area. EDM is implemented and the various user groups, various educational environments/data are defined. The problem solved by data mining techniques in different areas to improve the success of students is addressed.
Experimental Analysis of the co-efficient of static friction between different pairs of surfaces using Horizontal Plane Apparatus
Authors: Hasan Ali 
Published: August 2021

Abstract
This study is based on a quick, simple and reliable Engineering Mechanics laboratory experiment for determining the coefficient of static friction between common as well as different materials. First of all, author determines the performance of the Horizontal plane Apparatus to understand facts and concepts of development of frictional force with respect to applied external force causing motion or tends to cause the motion. The average value of coefficient of friction between wood-wood surface, wood-glass surface and wood-leather surface, using simple plane horizontal apparatus obtained by the author are 0.79, 0.49 and 0.61 respectively. Author compares the same with the available values of coefficient of friction in the literature. The work is extremely useful for B.Tech./M.Tech. Students and research scholars for their project/thesis work.
Impact of applying super resolution to low resolution face images on the performance of deep neural networks
Authors: Moghekar Rajeshwar , Ahuja Sachin 
Published: August 2021

Abstract
Face images captured in unconstrained environment differ in various aspects such as expression, illumination, resolution, occlusion, pose etc. which makes face recognition task difficult. The face images captured by the camera from a distance will have low resolution and lack many finer details that makes face recognition a challenging task. Super resolution (SR) is a process of generating high resolution (HR) images from one or more images. In this work, we apply super resolution to low resolution (LR) images of faces to find the impact on the deep models performance. To achieve this, we create dataset with face images captured in unconstrained environment. Later we designed a CNN model with eight layers and trained on the dataset created. Our deep model with low memory requirement and less parameters achieves an accuracy of 99.75% on test dataset and outperforms fine-tuned VGGFace by a small margin. The performance of our deep neural network and fine-tuned VGGFace was observed on low resolution images pre and post-super resolution. The deep neural network-based model available in OpenCV, SRGAN super resolution model and INTER_CUBIC interpolation are used to generate HR images. The HR images generated by OpenCV, SRGAN are better than INTER_CUBIC interpolation. The results show that HR images generated by applying SR to low resolution face images improve the image quality in terms of Mean squared error (MSE), Structural similarity index measure (SSIM) and Peak to signal noise ratio (PSNR). However, the results indicate that improvement in the image quality does not significantly improve performance of deep model.
Energy Efficient Scheduling in Cloud Computing using Black Widow Optimization
Authors: Kumar Manoj , Suman  
Published: August 2021

Abstract
The delivery of services at IaaS, SaaS, and PaaS levels in Cloud Computing through internet proves to a promising technology. The increase in demand of services of cloud computing increased the creation of cloud datacenters in the world. This leads to increase in demand of energy consumption by datacenter. The integration of green computing with cloud tries to minimize the consumption of power, to minimize their energy costs, and increases their profit. Minimizing the energy consumption with promise of better Quality of Service (QoS) seems to be mutually explosive task for cloud service providers (CSP). To deal with these, a meta-heuristic technique called Energy Efficient Black Widow Optimization based Scheduling algorithm (EEBWOSA) is developed and analyzed in this paper. The special stage of cannibalism which excludes bad solutions will not be used for generating new solution which leads to early convergence. The performance of EEBWOSA is tested on workload taken from HPC2N dataset in CloudSim tool. It exhibits reduction in energy consumption by 25.69% and 13.52% as compared to GA and PSO.
Machine Learning Based Security Solutions in MANETs: State of the art approaches
Authors: Popli Renu , Sethi Monika , Kansal Isha , Garg Atul , Goyal Nitin 
Published: August 2021

Abstract
Machine learning (ML) techniques provide the learning capability to a system and encourage adaptation into the environment, based upon many logical and statistical operations. The prime goal of ML is to recognize the complex patterns and make decisions based on the results. There are various ML algorithms which are implemented to secure the mobile ad-hoc networks. The infrastructure-less environment of MANETs poses a great challenge in implementation of the security systems. The security approaches in MANETs mainly focus on intrusion detection, malicious attacks mitigation, elimination of outlier/misbehavior/selfish nodes and securing routing paths. The researchers have been using cutting edge technologies for providing efficient security solutions by taking into the consideration of dynamic environment of MANETs. These technologies include machine learning, Artificial Intelligence (AI), Genetic Algorithms based methods, biological-inspired algorithms and so on. This paper presents a comprehensive and systematic study of various modern approaches for intensifying security in MANETs.
An Empirical Study for the Deep Learning Models
Authors: Sethi Monika , Ahuja Sachin , Kukreja Vinay 
Published: August 2021

Abstract
Deep Learning (DL) models have tested to be very powerful in solving many hard problems. Especially, those are related to computer vision, text, speech, and classification. However, the blueprint of such models requires large space and elaboration that needs to be examined. Convolutional Neural Network (CNN) is the most popular neural network that can extract the features automatically as compared to conventional machine learning algorithms (CMLA). Our aim in this paper is to lessen the human attempt required to layout architectures by the use of a gadget architecture development process that allows the exploration of huge design space by automating sure version construction, alternative generation, and assessment. The main operations in CNN are Convolution, Pooling, Flattening, Full Connection between the input and output layer. The dataset taken as CIFAR 10 having 60,000 color images of 10 different classes is considered for the study where, various classes represent the images of cars, trucks, frogs, horses, trucks, cats, cars, airplanes, ships, and deer. It is expected that the performance of the CNN model can be further improved by using the deeper network architecture, or by an increasing number of epochs or data augmentation. In this paper, an attempt has been made to explain simple and deeper CNN models on the CIFAR 10 dataset and the comparison has been carried out to check the accuracy achieved from both the models.
RPL Based Routing Protocols for Load Balancing in IoT Network
Authors: Rani Sangeeta , Kumar Ajay , Bagchi Arko , Yadav Snehlata , Kumar Sachin 
Published: August 2021

Abstract
RPL is a directing convention for remote organizations with low force utilization and large defenseless to parcel misfortune. It is a proactive convention dependent on distance vectors and works on IEEE 802.15.4. RPL can uphold a wide assortment of connection layers, including IoT, which is a technology that taking hold of research and industries with a fast tramp. It is a collection of actuators and sensors that collect data which can be processed to produce actual information. Important parameters allied to human body and physical environment data such that humidity, temperature, pressure, pollution etc. have immense significance for computerization, failure recognition, well timed, and appropriate cure. In this manner, IoT network offered ascend to keen urban communities, home mechanization, savvy wellbeing, present day travel strategic and some more. There is a distance vector normalization Routing Protocol for Low force and Lossy organization (RPL) for IoT sending, which relies upon different course improvement Objective functions (OF). These capacities rely upon different networks in the vein of energy like Received Sign Strength Indicator (RSSI) and Expected Transmission tally (ETX) for course streamlining. Course enhancement is influenced by issue of burden adjusting. In this paper, an inclusive survey of existing load balancing schemes, matrices, Objective Functions and different RPL based Routing protocols with reference to load imbalance is represented and highlighted when load balancing merged with the RPL, how it had a great impact.
Analysis of Temperature Effect on the Mass Sensing Capabilities of Boron Nitride Nanotubes
Authors: Deshwal Dinesh , Deshwal Monika , Gaur Nitin 
Published: August 2021

Abstract
In the periodic table, it is mentioned that the closer atoms or just intermediate atoms to Carbon are Boron & Nitrogen. Now Scientists also confirmed that Boron & Nitrogen can form a perfect nanotube structure. Boron Nitride Nanotube (BNNT), possesses a similar tubular nanostructure as carbon nanotube (CNT) but it is composed of the B-N atoms hexagonally. BNNT possesses various properties & its properties can show different-different behavior according to the conditions & environment. Here we are discussing the temperature & its effects on the mass sensing capabilities. Along with this, the various configurations of the BNNT’s are also discussed simultaneously. Due to their superior properties & high effectiveness, these are widely used all over the world.
Study of process conditions on surface roughness in Incremental Forming Process
Authors: Kumar Ajay , Chauhan Mohit , Sandhu Jasminder Kaur , Kumar Amit 
Published: August 2021

Abstract
The employment of a green manufacturing process can directly save energy and materials in industrial sectors. Single Point Incremental Forming (SPIF) is an agile and flexible method of fabricating sheet material components and exempts the use of dedicated die-sets which further makes it a choice of green manufacturing. Furthermore, the customized components can be easily fabricated by SPIF economically. The surface quality of fabricated parts can greatly decide the suitability and sustainability of the process in various applications. This work investigates the impact of significant process factors on the roughness of the parts during the SPIF process. The average roughness has been considered to determine the surface quality. The increment in the value of wall angle and step size resulted in the increment in Ra value of formed components drastically. It was also observed that as the forming angle was raised from a lower level (60°) to a higher level (68°), the Ra value was found to increase significantly.