bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental study of the effect of alkali contamination on geo-mechanical properties of the soil
Authors: Soni Atul , Varshney Deepak 
Published: May 2021

Abstract

As a civil engineer, we all are quite aware that the soils expansive in nature are not at all suitable as a material for foundation engineering purposes. Due to this very nature, geotechnical failures in expansive soil have been observed at various sites. Seasonal variations are responsible for swelling and shrinking that causes large volume changes in the expansive soil. Similar effects are also shown by the interaction of non-expansive soil with industrial sewage or effluent. It is a fact that engineering behavior of soil can be changed with the interaction of alkali. Alkali base solutions are discharged into the soil mass from differs industries, for example, paint and dyeing, paper manufacturing ventures, cotton factories and aluminum factories, etc. In this paper, an attempt has been made to investigate the effect of alkali interaction on engineering behavior of soil. For this, the samples of normal soil and contaminated soil were collected from Hindalco Industries Ltd., Renukoot (U.P.). The contamination was due to caustic liquor. The mechanical properties of normal soil and contaminated soil samples were investigated in laboratory by performing various geo-mechanical tests like specific gravity, grain size distribution, Atterberg’s limit, compaction characteristic, permeability, free swelling index, swelling pressure, shear strength parameter and consolidation characteristic.
Investigation of 7T SRAM Cell for IoT based devices
Authors: Mittal Deepak , Tomar V.K. 
Published: May 2021

Abstract
Internet of Thing (IoT) based devices require the design of ultra-low power Static Random Access Memory (SRAM) to sustain the long battery life. In present work, for execution different types of SRAM cell methodologies Cadence Virtuoso tool is used and all considered methodologies read and write operations have been supervised out. These SRAM cell methodologies various parameters also have been calculated, there are read static noise margin (RSNM), write static noise margin (WSNM), read delay, write delay, read power and write power. For low read, write power dissemination and faster read and write working new 7T SRAM cell methodology is proposed. It has been recognized that new 7T SRAM cell methodology as collated to 6T to 9T SRAM cell methodologies read power consumption reduced by 1.60* to 4*. New 7T SRAM cell methodology as collated to traditional 6T, 8T and 9T SRAM cell write power consumption is decreased by 2.3* to 2.6*. It is also noticed that as collated to 6T, 8T and 9T SRAM cell methodology that new 7T SRAM read delay suppressed by 2.40* to 2.60* and its write delay is also suppressed by 3.80* to 99*. As collate to 6T to 9T SRAM cell methodologies write operation robustness of new 7T SRAM cell is 3.0* to 6.5* perform in better way. New 7T SRAM cell has the tradeoff that its read operation robustness is 6* to 14* lesser as collate to 6T, 8T and 9T SRAM cell methodologies. Due to low power consumption and less delay new 7T SRAM cell methodology is suitable for Internet of things (IOT) based devices.
Mapping customer delight by discriminating augmented communication technology for sustainable advantage
Authors: Dubey P , Bajpai N , Kulshreshtha K , Singh D 
Published: May 2021

Abstract
The paper proposes to map customer delight experience through the firm’s product augmentation efforts. The study act as a juncture of conceptual insight, empirical analysis, and perceptual visualisation, classifying low (Chill), moderate (Smiling) and high (Feat) delight affect by using the product augmentation model. The present research aims to create a framework to assess smartphone customers’ delight by extending Kano (1984) and Fuller and Matzler (2008) proposal through product augmentation. The first section of the paper deals with the development of the conceptual model containing ten predictor variables of product augmentation along with the categories of customer delight experiences. The second section validates the model by using discriminant analysis. The last section substantiates the impact of predictor variables as vector quantity for profiling of customer delight categories by using a perceptual mapping technique. The proposal demonstrates and endorses the consistency in the delineating nature of product augmentation by identifying each predictor variable’s discriminating power in the respective category. The salience of the study affirms the conceptual and practical implications through behavioural segmentation based on augmentation efforts for technology enhancement.
A Method for Human Burn Diagnosis Using Machine Learning and SLIC Superpixels Based Segmentation
Authors: Yadav D. P. 
Published: May 2021

Abstract
The burn is a global health issue. The treatment of burn is performed by a burn surgeon. Burn region color is used to categorize burn types by a burn surgeon. Due to the lack of resources in many places burn patient dies. In such a situation a computer-based diagnosis system is very helpful. The severity of the burn is based on the depth and size of the burn region. The burn severity analysis can be accurately done by using the CIELab image as it contains all spectrums of colors. In the proposed work, the CIELab image is segmented using SLIC (Simple Linear Iterative Clustering) superpixel segmentation algorithm to form the same color pixels clusters. These clusters are used to diagnosis the severity of a burn, The severity of a burn is measured by the value of kurtosis. A high kurtosis value implies a larger depth and a small value implies a smaller depth. Based on the depth of burn, grafting or non-grafting is suggested by a burn surgeon. We observed depth of the burn is high in full-thickness burn compared to the deep dermal and the superficial dermal burn. The proposed method can correctly identify full-thickness burn and most of the deep dermal burn image. The open-access standard data set BURNS BIP-US DATABASE is used for training and testing of the proposed model on SVM (Support Vector Machine). The proposed model can classify with an accuracy of 89.16% and F1- score 90%. The achieved accuracy of the model is better than 79% of multidimensional scaling (MDS) in previous work.
A Novel Approach for Solving TSP Problem Using Genetic Algorithm Problem
Authors: Sharma Sachin , Jain Vinod 
Published: May 2021

Abstract
TSP is a well-known optimization problem. It comes in the category of NP-Hard problems. The solution of TSP problem is not possible using traditional algorithms. It is having many application areas in science and engineering. Genetic algorithm is a well-known AI technique which performs well to solve optimization problems. The performance of genetic algorithm depends upon its operators. In this paper a novel genetic cross over is proposed to solve TSP problem. The performance of proposed algorithm is better as compared to other techniques to solve TSP.
Use of Artificial Intelligence in Emotion Recognition by Ensemble based multilevel classification
Authors: Rathor Sandeep , Kansal Megha , Verma Mansi , Garg Madhav , Tiwari Rishabh 
Published: May 2021

Abstract
Emotion is a part of communication. By the communication we can recognize the emotions whether the communicator is happy, sad, surprise, etc. The objective of this research is to decrease the gap between humans and machines taking emotions into account. In this regard, an artificial intelligence with machine learning techniques is used. In this paper, 8 distinct emotions are used as happy, sad, surprised, angry, calm, neutral, disgust and fearful. For feature extraction, MFCC, chroma and mel is used. The proposed model is executed on the standard LibriSpeech dataset. For feature reduction principal component analysis is used before train the model. The classification is also done by using the basic machine learning classifiers like KNN, SVM and MLP and found the individual accuracy of the classifiers 29.83%, 68.69% and 61.50% respectively. To enhance the accuracy more, we propose an ensemble based classification model using the MLP Classifier with 300 hidden layers, SVM (rbf) and KNN (weight uniform, distance), AdaBoost and Gradient Boost classifier. The obtained accuracy of the proposed model is higher than any of the individual classifier i.e. 90%.
Cloud Computing, Exigency, Issues, Solutions: A survey
Authors: Bansal Saloni , Tomar V.K 
Published: May 2021

Abstract
In the era of digitalization all over the world, cloud computing is the ubiquitous supreme technology that provides many computer resources and data storage network to the consumers smoothly on-demand. Many researchers of both academics as well as industries are proactively indulge in providing the benefits of cloud computing to the society. As per ray of IT industries is increases drastically also leads in the need of network of dynamic nature. This dynamic and scalable nature of cloud computing creates hurdles in security of data appears in the network. Mainly, three services are the centre of study in cloud computing i.e. Saas, Paas, Iaas. Several security aspects namely multitancy, variability, trouble in data and hackers attacks also focused on priority basis. This paper demonstrate the conceve outlook of latest issues related with cloud computing and the solution of issues. Many authors also convey several methodologies for cloud computing.It is especially recommended to newcomer ensuing their study in field of cloud computing to find the solutions related the issues of cloud computing.
Potential Use of Artificial Neural Networks in Prediction of Dengue Abundance in Agra District
Authors: Sant Tatavarty Guru , Satsangi Neh 
Published: May 2021

Abstract
India being a sub-tropical country faces several diseases spread through mosquito vectors, one of which being Dengue. Dengue is classified as mosquito-borne viral infection causing severe illness and mortality in children and adults in Asian sub continent. There are an estimated 390 million infections annually and to reduce the impact of dengue among population in sub-tropical regions, a novel disease prediction model is required. The aim of this study is to estimate the dengue cases with clinical and environmental variables like rainfall, relative humidity and temperature from 2005-2018 using data available on the India meteorological department for the geographical location of Agra district, Uttar Pradesh, India. Datasets were represented as average minimum and maximum temperature, average annual rainfall in cm, relative humidity and number of reported dengue cases. In this paper, we examined the effectiveness of the artificial neural network (ANN) for dengue prediction for four major sites in Agra (Dayalbagh, Sikandra, Agra cantonment and Kamla Nagar) and prediction model was designed for the period of 2019 and compared with the observed values. The results show variation in the prediction model with respect to clinical and environmental variables corresponding to four different sites. The average error of the prediction model ranged between 27.3% and 84% respectively. Until now several approaches have been discovered for controlling mosquito vectors but their effectiveness is still questioned. Therefore developing prediction model for mosquito prevalent areas in India will help in better encounter with the disease, causing less mortality.
Analysis of modified time series prediction techniques: A case study with bakery industry
Authors: Sharma Rajkumar , Agrawal Manoj Kumar , Singhal Piyush , Agrawal Deepak 
Published: May 2021

Abstract
In the current scenario, it is a very difficult task to predict the demand for a particular product in the market. It is very challenging work for the industries to manufacture the product without being acquainted with the actual sale. To meet the demand of customers and to make the supply chain process optimize various strategies are being adopted at each node of the supply chain. Manufacturing the product by the market consumption significantly affects the revenue generation of small and medium scale enterprises especially of the FMCG industry.
In this paper, a case study of a medium-scale industry named “Gopal Ji Food Products.” Kosi Kalan (U.P.) has been performed, Highlights of this case study have been kept to know the demand for the number of boxes of biscuits which are to be distributed in the market. The primary work is done by collecting historical data of the requirement of boxes for the last 104 weeks (April 2017 to March 2018). With the help of this data, the demand pattern is known. After knowing the demand pattern, an attempt has been made to develop a prediction model using time series forecasting to acquaint with the number of boxes to be manufactured in advance. The result shows that the data obtained through Non-linear Autoregressive time series forecasting can be used for better planning and fulfilling market demand on time and making the whole supply chain more optimize, effective, and cost-efficient.
Thermal Stability and Light Transmission Capability of Nano TIO2 Enhanced Phase Change Material as Thermal Energy Storage
Authors: Fikri M. Arif , Pandey A. K. , Samykano Mahendran , Sharma Kamal , Selvaraj Jeyraj , Rahim Nasrudin Abd , Saidura R. 
Published: May 2021

Abstract
InPhase Change Material (PCM) already pick up some interests among recent researchers and engineers due to its unique characteristic of storage and releasing high quantity of heat energy during phase transition process. However, there’s some disadvantages for this material such as low absorption of irradiance and super cooling phenomena occurred. To overcome this problem high conductive nanoparticles are dispersed in to the PCM resulting a new composite called nano-enhanced PCM (NEPCM). In this present paper, the impact of adding Titanium (IV) oxide nanoparticles (TiO2) on pure paraffin wax also was investigated. Output reveal that NEPCM have greater thermal stability than pure PCM. When increasing the %wt, the thermal stability also increases, as shown clearly when using Sodium Dodecylbenzene Sulfonate (SDBS) as surfactant.
Flat Plate Pulsating Heat Pipes with and without separating grooves: experimental investigation on adiabatic length, coolant temperature and orientation
Authors: Pagnoni F , Ayel V , Romestant C , Bertin Y 
Published: May 2021

Abstract
Two Flat Plate Closed Loop Pulsating Heat Pipes have been tested under various operating conditions, working fluids and different evaporator-to-condenser distances. The devices have the same geometrical features; nevertheless, on one FPPHP plate external grooves between adjacent channels have been engraved to minimize the transversal thermal conductive spreading whilst the other is a simple smooth plate. The working fluids are ethanol and FC72. Both FPPHPs have shown better performances when tilted in favorable vertical position. It has been found that higher secondary fluid temperatures within the condenser provide better thermal performances. The fluids’ different thermophysical properties and critical diameters have remarkable effects on FPPHPs behavior. Moving the condenser towards evaporator increases the heat transfer capabilities, reducing the influence of gravity. Finally, the higher thermal insulation between adjacent channels, provided by the external grooves, seems to degrade the thermal performance, especially on horizontal position and on the edge.
Modelling of a screen mesh wick heat pipe using Al2O3 nanofluids
Authors: Herrera B , Chejne F , Mantelli M B H , Mejía J , Cacua K 
Published: May 2021

Abstract
In this work, a phenomenological model that considers the interaction of nanoparticles of a Al2O3/water nanofluid within a cylindrical mesh wick heat pipe has been developed. The model is based on Navier-Stokes equations and it uses population balance as a method to account for the interaction of nanoparticles. The model predicted values of capillary limit with nanofluids up to 32% higher than that of the heat pipe using DI water. Those values were in agreement with the values found experimentally. Although the better performance of the capillary limit in the model was a consequence of the reduction of the pore radius which increases the capillary pressure, that was not the main cause for better capillary limit in experimental conditions at lower nanofluid concentrations. On the other hand, it was found that exists an optimum concentration of nanoparticles which decreases the effective thermal resistance of the heat pipes. In this work, that concentration was 0.5% w/w.
Experimental investigation of a capillary-assisted high performance evaporator
Authors: Marie Alexandre , Lavieille Pascal , Miscevic Marc , Lachassagne Laurent , Dupont Vincent 
Published: May 2021

Abstract
A particular architecture for a miniaturized evaporator is proposed in which liquid is spread on the heat source using a thin capillary structure connected to two manifolds. The vapor produced by the heat source is extracted from the device using a separate outlet. A prototype has been designed, manufactured and integrated in a mechanically pumped loop in order to evaluate the evaporator efficiency in terms of heat transfer coefficient and induced pressure drop. In this paper, a capillary structure consisting in parallel rectangular micro-grooves is investigated with HFE7000 used as the working fluid. Results show that the evaporator is able to extract heat flux of the order of 10 W.cm-2 with heat transfer coefficients close to 104 W.m-2.K-1 while inducing pressure losses below a few hundred Pascal. Direct visualizations of the flow in the capillary structure allowed a precise characterization of the evaporator functioning mode, in particular the existence of two distinct two-phase flow regimes depending on the flooding of the capillary structure: nucleate boiling and liquid films evaporation. In order to predict the occurrence of these operating modes, a hydraulic model of the evaporator assembly has been developed and validated thanks to dedicated experimental campaigns. In particular, this model is able to predict the separation between the nucleate boiling and evaporation mode and highlights the fact that the capillary limit is not the main restricting factor in terms of the device maximum manageable heat flux.
Performance of a small diameter two-phase closed thermosyphon in geyser boiling condition
Authors: Pabón Nelson Yurako Londoño , Vieira Gabriel Serafin Couto , Milanez Kênia Warmling , Mantelli Marcia Barbosa Henriques 
Published: May 2021

Abstract
In the present article, the geyser boiling phenomenon is experimentally investigated in a small diameter two-phase closed thermosyphon. The studied thermosyphon has an inner diameter of 4.8 mm and total length of 918 mm. Three specific filling ratios and four temperatures for the thermal bath used to provide cooling water to the condenser were tested. Power was inputted in steps of 20 W, up to 100 W. Variation of the temperatures on the walls of the evaporator, adiabatic and condenser sections as well as variations on pressure, obtained from a pressure transducer installed on the thermosyphon, indicated the presence of Geyser boiling. The results show that the studied variables affect directly the intensity and periodicity of the geyser boiling phenomenon.
Path Loss and Channel Modeling at 3.5GHz for 5G Cellular System
Authors: Al-Khero S Kh , Abbosh Y M 
Published: May 2021

Abstract
Wireless channel characterization is the basis of the architecture of the wireless communication system. The detailed propagation models are indeed the requirement for fifth generation communication network design. This paper presents the characteristics of channel propagation for a fifth-generation system in Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) scenarios with co-polarization (V-V) and cross polarization (V-H) in a second floor/Communication Engineering Department/Electronics college building at 3.5GHz frequency. The comparison between two path loss models shows that the Close-In (CI) of free space reference distance path loss model is more suitable than Floating-Intercept (FI) path loss model. The results of both models show that the path loss exponent value (n) is ranged between 1.7 and 2.9 for the LOS scenario, while it was between 2.1 and 3.1 for NLOS scenario for both co-polarization and cross polarization.
MIMO to Enhance the Performance of VLC Systems
Authors: Ali Ahmed Taher , Younus Safwan Hafeedh , Ozbay Serkan 
Published: May 2021

Abstract
In general, visible light communication (VLC) systems run at low data rates. By introducing multiple input and multiple output (MIMO) techniques, service at enhanced data rates can be viable for VLC systems. This work proposes MIMO technique to attain VLC system with high data rates. To attain MIMO method this system includes a number of photodiodes with a narrow field of view (FOV), which highlights the benefit of using MIMO technology in improving the data rate. The results show that using MIMO technique leads to enhance the VLC system when it is compared with the traditional system (without using MIMO). The results show that an improvement in the signal-to-noise ratio (SNR) level, which is the most attempt to determine communication quality, increasing the channel bandwidth and reducing the delay spread are achieved when MIMO technique is used.
A Method for Designing Unequal Power Divider for Implementing Antenna Array Excitations
Authors: Ali Yaser Ahmed , Abdulqader Ahmed Jameel , Mohammed Jafar Ramadhan 
Published: May 2021

Abstract
In this paper, a method for designing a feeding network to obtain a low peak sidelobe pattern of an 8*1 linear antenna array is proposed. The optimized element weights were first obtained using genetic algorithm. Then two different networks based on equal and unequal power dividers are designed for the linear antenna arrays. In an equal power divider structure, the power is divided equally into all branches of the network to reach the final ports, while in the unequal structure; the division is only made equal in some branches and unequal in other branches to build an unequal power divider. In the two methods, the design process is based on two stages, the first stage uses a T-junction power divider, and the second stage a Wilkinson power divider is used. In an equal power divider, T-junction and Wilkinson divide the power equally, while in the case of an unequal power divider the T-junction divider is only unequal. In the two designs, the feeding network is designed according to the following specifications: the substrate (FR-4 with ϵr =4.3) and ground dimensions are 440.4mm × 103.8mm ×1.6 mm and 440.4mm × 103.8mm × 0.035mm respectively, and at a resonant frequency of 2.36 GHz. The simulation results showed the effectiveness of the designed power dividers that to be used as a feeding network in the linear antenna arrays.