bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unified treatment of recoil and Doppler broadening in molecular high-energy photoemission
Authors: Kukk E , Céolin D , Travnikova O , Püttner R , Piancastelli M N , Guillemin R , Journel L , Marchenko T , Ismail I , Martins J , Rueff J-P , Simon M 
Published: June 2021

Abstract
Doppler and recoil effects are an integral part of the photoemission process at the high kinetic energies reached in hard x-ray photo-electron spectroscopy (HAXPES) and have a major effect on the observed lineshape, resulting in broadening, energy losses and discrete excitations. These effects can be modeled with a high degree of detail for small systems like diatomic molecules, for larger systems such treatment is often superfluous as the fine spectral features are not observable. We present a united description of the Doppler and recoil effects for arbitrary polyatomic systems and offer an approximate description of the recoil- and Doppler-modified photoemission spectral lineshape as a practical tool in the analysis of HAXPES spectra of core-level photoemission. The approach is tested on the examples of carbon dioxide and pentane molecules. The C and O 1s photoelectron spectra of CO2 in gas phase were also measured at 2.3 and 7.0 keV photon energy at Synchrotron SOLEIL and the spectra were analyzed using the model description. The limitations and applicability of the approach to adsorbates, interfaces and solids is briefly discussed.
FSS: Fuzzy Supervised Learning for Optimal Path Selection in RPL
Authors: Gopika D. , Rukmani P. 
Published: June 2021

Abstract
IPV6 routing protocol for low power lossy network (RPL) is a standardized routing protocol developed by the IETF ROLL working group. RPL has attained a lot of attraction to the research community as it demands modification adding to its improvement. RPL constructs a Destination Oriented Directed Acyclic Graph (DODAG) considering the metrics and constraints through explicit Objective Functions (OFs). The OFs chooses the best parent for reliable data communication. The existing objective function due to a single metric lacks in satisfying the requirement of real-time IoT applications. Still, the mobility aspect of the node is not considered in the objective function for optimal path selection. In the proposed methodology a Fuzzy Supervised Learning algorithm for quality node prediction using the composite metric based OF from the candidate parent set. The testing phase shows 93% accuracy of prediction with Artificial Neural Network (ANN) classifier which outperforms Naïve Bayes and Decision Tree (DT).
Removal of Noise in an Image using Boundary Detection Technique
Authors: Sarvesh M. , Sivagami M. , Maheswari N. 
Published: June 2021

Abstract
Image data recorded by devices contain mistakes or noises due to geometry and brightness values of the pixels. These mistakes are rectified using proper mathematical models. Examples of models include contrast and edge enhancement, pseudo-colouring, shadow removal, noise filtering, sharpening, and magnifying. Applying filters to remove a noise may lead to loss of some important data like edges in the image. The proposed work removes the noise from the image using local neighbourhood processing and preserves the edges using boundary-based approach. The noise filtered image is tested against the parameter entropy to validate the result.
Intelligent Tourist System For The 21st Century
Authors: Brindha Devi V , Meenaloshini M , Sriram G , Subhashini R 
Published: June 2021

Abstract
Travel Industry is always at the forefront of technology adoption. Most of our researchers and town planners have preferred the method of machine learning approach for tour recommendation models. Some traditional methods have achieved certain levels of success in tourism research, but sometimes artificial neural network (ANN) and regression analysis techniques give better results. Our objective is to investigate the different ways in which the machine learning models can be applied in tourism prediction problems and to show the performance of machine learning methods. In this paper we have an intelligent tourist system using ML/AI that has been modeled based on various features using Sentiment analysis and can be performed over these reviews which will be helpful to find tourist place popularity. Based on sentiment analysis results, tourists can easily decide their own tour destination to be visited. We have categorized the places based on their preference like the most visited or least visited family trip or friend’s trip and so on. The dataset was collected from various tourism review websites. We performed a comparative study of feature extraction algorithms that is Count Vectorization, TFIDF Vectorization, along with classification algorithms like Naive Bayes, Support Vector Machine, and Random Forest algorithm. With these results, a recommendation system has been built which would map an individual user’s interests to the highest rated tourist places and generates a tour plan satisfying the user’s needs.
Edge Aware Turbidity Restoration of Single Shallow Coastal Water Image
Authors: Mary Cecilia S. , Sakthivel Murugan S. 
Published: June 2021

Abstract
The blur and low contrast of underwater images are indicative of the high noise, intense scattering and ultimately the low quality of such images. Image Enhancement and Restoration are imperative pre processing steps for single images from shallow coastal areas. Pre processing of underwater images is hence a prerequisite to processes like classification, object detection and computer vision. The paper presents an effective edge aware restoration models that goals turbid water images. The dark channel based restoration method with a rolling guidance filter gives a more edge aware restored and denoised version of the heavily blurred, low contrast shallow coastal image. This is evident from the subjective and objective projections. Moreover the edge preserving nature projects 13.05% and 5.53% more than UHP (which is in close) in terms of number of edges and UCIQE scores in comparisons with promising algorithms over the decade.
Unsupervised Neural Network approach for the Identification of Anomaly in Speech Signal from Spectrogram Images
Authors: Joshwin Darington M. , Sathiesh Kumar V. 
Published: June 2021

Abstract
In this paper, anomaly identification in speech signal is carried out using an unsupervised Neural Network approach. Input audio signal is divided into small segments of information. Initial segment of the samples are used in the training process. The later portion of the sample segments are used in the test process. The features (Spectral Roll-off, Spectral Centroid, Mel Frequency Cepstral Coefficient (MFFC), Pitch (PH) and Energy Density (ED)) are extracted from the input data. The extracted 1D features are converted into spectrogram images. Then, the images are fed as an input to Neural Network for the prediction of feature values. If three or more feature value does not exceed the threshold value of 75% then the input signal is considered to be free from anomaly. The proposed model results in an accuracy of 97.50% in the detection of anomaly in input speech signal.
Motion Deblurring Analysis for Underwater Image Restoration
Authors: Vimal Raj M. , Sakthivel Murugan S. 
Published: June 2021

Abstract
Exploration of Underwater Images will be a challenging task due to its degradations by haze, blur, colour cast and noise. In order to extract the latent information from the blurred portion, its parameters are estimated and various algorithms were analysed. Initially, length and angle of motion blurred image are estimated. Then, filters and restoration algorithms were implemented for controlling of ringing artifacts, removal of noise and latent information restoration. Some of the model based classical methods were implemented and analysed for underwater motion blurred image restoration.
Heavy-Vehicle Detection Based on YOLOv4 featuring Data Augmentation and Transfer-Learning Techniques
Authors: Sowmya V , Radha R 
Published: June 2021

Abstract
Real-time Vehicle detection is crucial in today’s era for our complex interconnected transportation ecosystem built on an advanced technological network of intelligent systems encompassing a wide range of applications such as autonomous vehicles, traffic Surveillance, advanced driver assistance systems, and etcetera. The significance of its application to digital transportation infrastructure embarks upon a distinct framework for heavy-vehicle detection integrated with the YOLOv4 algorithm for real-time detection. In this proposed work, two entities of heavy vehicles such as buses, trucks are considered. The crux of the model, an algorithmic computational mechanism incorporates Mosaic Data augmentation and Transfer-learning techniques that are applied to avoid over-fitting and to improve the optimal speed during training. Subsequently, a fine-tuning YOLOv4 algorithm is implemented for detecting the heavy vehicle. The algorithm is tested for real-time situations in various traffic densities through Computer Vision. Experimental results show that the proposed system achieves higher detection accuracy of 96.54% mAP. More specifically, the performance of the proposed algorithm with the COCO test set and PASCAL VOC 2007 test set demonstrates improvement when compared with other state-of-the-art approaches.
Built-in translation on Web Messenger
Authors: Karthikeyan U , Ajit Surya A , Bhargav S , Bhargav P 
Published: June 2021

Abstract
The paper aims at providing the users with a web messenger application that translates messages sent by sender to the receiver. The translation is provided by Google Translate API. This helps in having a seamless conversation experience. Any language that is supported by Google Translate can be sent and received by the users. It is planned to provide transfer of graphic files as well as other file types. Interestingly, this method of communication is the most popular form. Encryption and Decryption is provided by employing AES Algorithm function set. The encryption and decryption make it safe for communication by protecting the conversation from outside threats. In order to have a conversation between two people normally in their own preferred language, they have to rely on using Google Translate solely by copying the message text and finding the translation. This web application we have proposed combats that problem by providing simultaneous translation of text messages to the user’s preferred language. Languages that can be translated are the same as what Google Translate provides. ISO 639-1 language codes are used as language code by the sending entity to send the data to the receiving entity. Accuracy have been identified as same as what Google Translate provides, above 60%.
An Approach to Skin Cancer Detection using Keras and Tensorflow
Authors: Panja Abilash , Christy Jackson J , Abdul Quadir Md 
Published: June 2021

Abstract
For humankind, skin cancer is a troubling illness. Given the rapid growth rate of skin cancer, its high treatment cost and death rate, the need for early detection of skin cancer has been increased. Now, the world has evolved in a way where skin cancer detection is possible by image pre-processing and machine learning methods. One well known and well worked method is Convolutional Neural Network (CNN). After segmentation of dermoscopic images, the features of the affected skin cells are extracted using feature extraction technique. We propose a convolutional neural network model to detect cancerous state of a person’s skin and classify them as malignant (melanoma) and benign (non-malignant). The above model’s architecture contains various layers which helps in reading the dataset by computer. Accurate results are always expected in these cases. We are using manual approach instead of automatic approach to overcome possible errors.
Effect of Curing Period and Binder Quantity on The Characteristics of Bagasse Ash-Calcium Carbide Residue Stabilized Organic Clay
Authors: Hatmoko J T , Handoko L 
Published: June 2021

AbstractOrganic clay has low bearing capacity, low shear strength, sensitive to water content, and high compressibility. Therefore, the study about engineering properties improvement of organic clay is continuously in progress. In this research, bagasse ash (BA) and calcium carbide residue (CCR) were used as stabilizing agents to improve engineering properties of organic clay. Preliminary investigation was done to get the physical parameters, especially Atterberg limit of soil samples. To get the optimum water content (OMC), the original soil was compacted according to standard compaction test. The oven dried soil was mixed with 5, 10, 15, 20, 25 and 30% of binder and cured with 7,21,36 and 56 days curing period. Then, Atterberg limits, unconfined compression strength, and modulus of elasticity of treated soil were investigated. The plasticity index (PI) of stabilized soil decreases proportional to the binder quantity. However, after 10% binder, there was no significant improvement of PI of treated soil. With respect to curing period, PI of stabilized soil decreased, but the decrease of PI was almost constant from 36 to 56 days curing time. Unconfined compression strength (UCS) and modulus of elasticity of stabilized organic clay improve proportionally to both binder proportion and curing period. However, the improvement is not significant enough due to organic content in the organic clay.
Borate Glasses for Low Loss Optical Fibre
Authors: Saraswati A , Marzuki A , Fausta D E , Suryanti V , Singgih G A 
Published: June 2021

Abstract
Borate glasses with composition 50B2O3 – (25-x) Bi2O3 – 25ZnO – xTiO2 where x = 0, 1, 2, 3, 4 (mol%) were succesfully fabricated using a convensional melt-quenching technique aimed at tailoring glass suitable for a low loss optical fiber fundament. For this purpose, glasses were characterized for their density, refractive index, reflectance, UV-Vis absorption and FTIR spectra. Density measurement was carried out by applying Archimedes principle. Refractive index was measured using Brewster’s angle method. UV-Vis spectrum was recorded within the range of 200-1100 nm and FTIR measurement was measured at IR range. Combining the spectra data recorded both from UV-Vis–NIR and FTIR, the theoretical minimum loss of the glass was obtained. In addition, the band gap energy of the present glasses was also calculated. From these data, it can be derived many other glass properties such as Oxygen Packing Density (OPD), ionic radius, and polaron radius.
Time dependence of the concentration of dissolved ozone in water generated by dielectric barrier discharge (DBD) plasma using atmospheric air
Authors: Cahyani M R , Zuhaela I A , Saraswati T E , Kusumandari  , Anwar M. , Suselo Y H , Ismayenti L 
Published: June 2021

Abstract
Ozone is one of the reactive oxygen species that can be produced from plasma. In this study, the ozone was generated by using a dielectric barrier discharge (DBD) plasma technology. DBD plasma was generated using two electrodes separated by a glass dielectric isolator and an alternating current (AC) voltage source of 5 kV with an airflow rate of 1 L/min at room temperature and atmospheric pressure. In this study, the ozone concentration was determined using the titration method. The ozone concentration was measured by varying the titration time between 0-10 minutes. The time dependence of ozone concentration in water tends to follow the polynomial trendline. The longer plasma treatment was performed, the higher ozone concentration was measured. The ozone significantly increased when the treatment was conducted for more than 6 min.
Cassava waste pulp – poly(acrylamide-acrylic acid) based hydrogels using gamma irradiation
Authors: Puspita I , Kurniati M , Winarti C , Maddu A 
Published: June 2021

Abstract
Cassava waste pulp (onggok) based hydrogels were synthesis with added of acrylic acid (AA) and acrylamide (AAm). The used of onggok promises superior properties such as eco-friendly, lower prices because the raw materials are available naturally in abundant quantities compared to synthetic polymers, and biodegradable. Gamma irradiation method at doses of 0, 10, 20, and 30 kGy was carried out to produced cross-linked structures. Swelling, gel fraction, physical strength, and morphology were parameters of the hydrogels. The most optimum result was obtained from the addition of 25% acrylic acid and irradiation dose of 10 kGy, with swelling of 9423%, diffusion coefficient of 0.2393, gel fraction of 75.98%, the hardness of 8.53 mJ, and elasticity modulus of 7.01 kPa.
Preparation of Poliblend Suweg Starch-Chitosan with Addition of Essential Oil from Sweet Orange Peel as Edible Coating on Malang’s Apples
Authors: Susilowati E , Mahardiani L , Sulistyowati D 
Published: June 2021

Abstract
Poliblend edible coating of suweg starch-chitosan (SSC) was prepared as a package with the addition of essential oil from sweet orange peel as antibacterial because of the high limonene content (95%) to increase the shelf life of malang’s apples. There are 6 variations formulation of the suweg starch: chitosan, namely 10: 0, 9: 1, 8: 2, 7: 3, 6: 4 and 5: 5 in total volume 60 mL. Essential oil of sweet orange peel was added with variations in the concentration of essential oil is 0%; 2%; 4%, and 6%.). Furthermore, characterization was carried out by mechanical testing, Water Vapor Transmission Rate (WVTR), solubility, and swelling of the SSC polyblend edible film and the antibacterial activity test of the SSCO polyblend edible coating on Staphylococcus Aureus bacteria before it was applied on malang’s apples. Organoleptic tests and physical observations of malang’s apples were carried out after the application of edible coating SSCO. The result characterization of the functional groups of polyblend edible film SSCO showed the absorption of the wave number 3373.64 cm−1; 1646.32 cm−1; 1570.12 cm−1; 1416.78 cm−1 and 1337.69 cm−1; and 1040.64 cm−1 with functional groups-OH, N-H, C=C, CH3, and C-O. The variation composition affects on the physical properties of edible film SSC in the mechanical test, WVTR, and WVP with the optimum concentration edible film SSC 7: 3, while the solubility and swelling reach the optimum concentration edible film SSC of 5: 5. The addition of sweet orange peel as essential oil had an effect on the antibacterial activity of polyblend edible film SSCO with a maximum inhibition zone 16.55 mm on concentration 6% for S. aureus bacteria. Based on organoleptic test, consumers prefer edible coating SSC with the lowest essential oil content and malang’s apples can last 22 days on physical performance observations.
Modified Activated Carbon on Electric Double Layer Capacitor Applications
Authors: Ramelan A H , Fuady M I A 
Published: June 2021

Abstract
The increase of populatioin in the world will be accompanied by the increase of energy need. The energy is not available in all time, sometime we lack of energy and also sometime the energy is available in abundant and in turn the energy wasted to nature. Therefore efforts have to be conducted to solve the problem. One of those is to make a cell which can store the excessive energy so called a supercapacitor. The supercapacitor in this research was fabricated using an activated carbon from the palm kernel shell (PKS). The performace of biomass-based activated carbon as an electrode for Electric Double Layer Capacitor (EDLC) was investigated using the cyclic voltammetry method. The test of EDLC was conducted using three electrode system, with carbon as the working electrode, Ag/AgCl as the reference electrode, Pt as the auxiliary electrode and 0.5 M H2SO4 solution as the electrolyte. The carbon tested was activated carbon pyrolysis at temperature 700°C, 800°C, and 900°C. Testing was carried out by varying the scanning rate in 5 and 100 mV s−1. The test was carried out using a potentiostat by settling the potential value between −0.2 V to 0.7 V. The results showed that activated carbon at 5 mV s−1 has the highest capacitance value of 49.76 F/g. It is also noted that the specific capacitance decreased by increasing scanning rates.
Crystallite structure of Palm shell Activated Carbon/MgO and Its Influence on Carbon Monoxide and Carbon Dioxide Adsorption
Authors: Yuliusman  , Nafisah A R 
Published: June 2021

Abstract
Gas emission of the motor vehicle is a major contributor to climate change, with a total of 14% emission annually, and the best potential option for reducing pollution is using the adsorption method. Magnesium oxide (MgO) has been proven as an effective adsorbent for liquid and gases. The impregnation of MgO on porous structure increases the affinity toward nonpolar gases, which is one of the purposes of this study. The crystallite structure is also a key factor that determines the adsorption capacity of activated carbon (AC). However, deeper analysis is needed in the activated carbon crystallite structure represented by d002 (aromatic layer), Lc (crystallite height), and La (crystallite diameter) on the adsorption of motor vehicle gas emissions. Three types of palm shell-based activated carbon were tested in this experiment. The results showed that activated carbon made using the two-step method and the AC/MgO produced surface structure with a d002 value of 0.33 nm and 0.32 nm, respectively. The impregnation of MgO on AC showed changes in surface structure and affected its crystallinity. The ability to adsorb CO2 and CO by AC/MgO increase up to 80% and 88%, respectively.
Synthesis and Metal Phases Characterization of Mordenite Supported Copper Catalysts
Authors: Sabiilagusti A I , Nugrahaningtyas K D , Hidayat Y 
Published: June 2021

Abstract
Three catalysts were synthesized by the impregnation method using copper as an active metal and mordenite as a support material. The metal loading was set at 0, 4 and 8 %wt, respectively. The used copper salt solutions were collected as filtrate and analyzed by atomic absorption spectroscopy (AAS) to predict the metal content was successfully loaded onto mordenite. For a further step, catalysts are activated through the calcination and reduction process. The metal content was further confirmed by X-Ray Fluorescence (XRF) and the results were not much different compared to AAS analysis. It was obtained that copper metals were successfully impregnated on the catalyst as 3.74 %wt for Cu/MOR 4 and 5.52 %wt for Cu/MOR 8. Meanwhile, the catalysts were also characterized using X-ray diffraction (XRD) and then followed by match with a mordenite standard diffractogram. Further diffractogram analysis was carried out by the Le Bail method to get semi-quantitative data of metal phases on catalysts. Mordenite phase was consistently obtained as the main content of all catalysts, over 99%. The copper phase at Cu/MOR 4 catalyst was consisted of Cu, Cu(OH)2 and Cu2O. In contrast, Cu/MOR 8 catalysts showed no Cu(OH)2 phase on it, but Cu and Cu2O still found.