bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical Simulation of Temperature Distribution in Robotic Arc welding by ARISTOTM Robot
Authors: Sharma Aman , Singh Pradeep Kumar , Sharma Rohit 
Published: May 2021

Abstract
The present analyses also studied a numerical simulation on the specimen of mild steel weld by robotic welding. A conical moving temperature source from Gaussian was applied to the current numerical simulation. ANSYS is also used for thermally mechanical weld tests by the ARISTO robot, with some variations. Taking into consideration the thermal and physical properties of mild steel that affect the welding thermal conductivity. The analysis of temperature distribution was defined according to robotic arc welding process parameters, such as welding temperature, welding current, and welding speed impact on the geometry of the weld bead was investigated. The temperature distribution based on numerical observations is associated with experiment results. This form is well in line with the results obtained by numerical simulation of the weld zone profile.
Bayesian K-Nearest Neighbour based Redundancy Removal and Hand Gesture Recognition in Isolated Indian Sign Language without Materials Support
Authors: Agarwal Rohit 
Published: May 2021

Abstract
Indian sign language is used by deaf and dumb persons for communication. Physical materials are not needed for ISL. During this anticipated paper we tend to propose a unique vision-based (VB) methodology for the Indian language (ISL) recognition of isolated signs. The methodology proposed consists of 3 modules: preprocessing, extraction and classification of features. One signer hand is segmented from sign video in segmentation or preprocessing phase. Feature vector is extracted from feature extraction module and show the manual sign parameters used as input for classification. To decrease the computational complexity of the system, a redundant frame algorithmic rule has been applied. The experiment results demonstrate that proposed system achieves 90.3% recognition accuracy based on a lexicon of twenty-one signs of ISL.
Prediction of students’ performance in education system based on artificial intelligence
Authors: Pathak Pooja , Farheen Nazia , Dubey Avinash 
Published: May 2021

Abstract
The main objective of any educational system is to provide the best knowledge to students. To achieve this goal this is important to identify the weak students who need more support and take correct decisions to improve their performance. In this research for predicting the students’ performance, four techniques of machine learning are used. For this technique, we take the data from computer science students of GLA University, Mathura, U.P. INDIA. These machine learning techniques include various processes such as Artificial Neural Networks (ANN), Naive Bayes (NB), Logistic Regression, and Decision Tree. In this model, we put more efforts to know the time attended by the students on the internet for learning and social media. Also, various measurements have been done such as precision, F measure, recall, and classification errors. We used the dataset for building a model depending upon the survey that given to the all-computer science students and grade copy of students. The decision tree identified four main attributes that influence the performance of students a lot. This helps us to achieve an accurate prediction of around 98%.
A Deep Learning Approach for Plant Material Disease Identification
Authors: Tripathi R K 
Published: May 2021

Abstract
Plant Material Disease Identification is essential for the food safety. To increase the crop production for the growing population of the world, the proper treatment is required on proper time to save the plant. Therefore, disease diagnosing on time is very important. This paper uses a deep learning convolutional neural network model to identify the plant disease. The pre-existing deep learning model Alexnet has been employed for plant disease identification in which an external feature of segmented plant material (leaves) is passed to the deepest fully connected layer. This combination of extracted feature by Alexnet and external feature of segmented plant material helps in plant disease identification. Experimental analysis has been done on a standard dataset Plant Village which has total 54,306 leaf images of 15 distinct plants having 38 diseases. The presented CNN approach worked well and outperformed to the existing approach.
Investigation of the impact of eco-friendly building materials on carbon footprints of an affordable housing in hilly region
Authors: Gupta Ankur , Kumar Shubham , Gupta Nakul , Pal Shilpa 
Published: May 2021

Abstract
Increasing emission of carbon di-oxide in the atmosphere is becoming one of the greatest threats to the humans and the society. The combustion of fossil fuels and the manufacturing process of cement are responsible for around 75% increases in the CO2 emissions. It has become important to monitor and control the greenhouse gas emissions in the atmosphere. The carbon footprint is one such concept which is becoming popular over past few years. It helps in evaluation of mitigation measures and emissions management by identifying the important sources of greenhouse gas emissions and reducing their efficiency. In spite of development of various types of eco-friendly materials, the construction industry uses traditional materials that contribute largely to carbon emissions. This case study based research focuses to identify and quantify the carbon emissions of the most commonly used materials for construction in India. A physical model of low energy affordable house for hilly region has been constructed at CBRI Roorkee by replacing the traditionally used building materials with the eco-friendly greener materials. The carbon footprints of these eco-friendly materials were calculated using Process Analysis-LCA technique and then compared with the traditionally used building materials. The initial carbon footprint was estimated to be 4.17 tonnes of CO2 that was reduced to 3.95 tonnes, resulting in reduction of carbon footprint by 5.3%. Therefore eco-friendly greener materials can effectively help in reducing the carbon footprint of the traditionally used building materials in construction.
Experimental study of the effect of bacillus megaterium bacteria on cement concrete
Authors: Parashar Arun Kumar , Gupta Ankur 
Published: May 2021

Abstract
The presence of voids in cement concrete may lead to a reduction in its performance when exposed to high shrinkage and settlement. This study focused on utilization of bacteria for improving the performance by reducing the voids in the concrete. Bacillus family bacteria were found to be the great healers for the concrete. Bacillus megaterium bacteria of bacillus family with a concentration of 108 CFU have been utilized in the current study. A total of 48 specimens were cast and tested for their mechanical strength and water absorption after 7 and 28 days of curing. The test results indicate that the compressive, split tensile and flexural strengths increased to 12.91%, 10.28% and 9.02% respectively after 28 days of curing as compared to standard M30 grade concrete mix. The water absorption value of bacterial concrete was also found to be less as compared to the standard concrete mix. This is because of the filling of the cracks in concrete due to calcite precipitation produced by the Bacillus megaterium bacteria. Therefore, the Bacillus megaterium bacteria of bacillus family can be effectively utilized to improve the mechanical strength by reducing the voids.
Automatic Car License Plate Detection System: A Review
Authors: Singh Sweta 
Published: May 2021

Abstract
Automatic license detection system is an essential system in today’s busy traffic system. It helps in automatic monitoring of traffic rules and other law enforcement activities. In India there are many cases of rash driving where in cars violating many traffic rules. It becomes very difficult for traffic policeman to capture the details of the vehicle. Thus, automatic license detection system have been proposed and implemented over the years to help easy and fast monitoring of traffic rules by the vehicles. This paper provides a concise review of various approaches used for automatic license detection system. These approaches can be broadly categorized into two categories: Techniques for automatic car number plate recognition and Techniques for character recognition. This paper also provides advantages and disadvantages of various approaches coming under these categories. Finally, the paper concludes with the comparative result analysis of all approaches reviewed under both the categories.
Surfactant effect in the thermal performance of a two-phase thermosyphon using Al2O3 nanofluid
Authors: Cacua Karen , Buitrago-Sierra Robison , Herrera Bernardo , Gallego Anderson , Pabón Elizabeth 
Published: May 2021

Abstract
An experimental study was carried out to evaluate the effect on the thermal performance of a two-phase closed thermosyphon (TPCT) during operation cycles using nanofluids. Al2O3 (0.1 wt.%) based nanofluids with two concentrations of SDBS (0.032 wt.% and 0.064 wt.%) were prepared via two-step method. Stability after nanofluids preparation was evaluated using visual inspection, UV-spectroscopy and dynamic light scattering (DLS). Nanofluids with and without surfactant were used as working fluid in a glass TPCT. Results show that the TPCT thermal resistance was decreased up to 20% respect to water by the presence of nanoparticles and surfactant. A dried limit with water as working fluid was observed and fluid expansion was identified with surfactant presence. Differences in thermal efficiency and temperature profiles using nanofluids with and without surfactant and only surfactant-water as working fluids in TPCT were not significative. However, in evaporator zone, a slight increase of the thermal resistance was identified when surfactant was added. After TPCT operation with nanofluids, nanoparticles agglomeration and sedimentation were observed and a layer on the evaporator surface was observed.
Water desalination and power cogeneration utilizing heat pipe heat exchanger
Authors: Velardo J , Searle J , Nihill J , Date A , Akbarzadeh A 
Published: May 2021

Abstract
Energy production in Australia is predominantly achieved with non-renewable sources such as coal and natural gas, with up to 86% of national energy being produced by these processes. Further, access to fresh water is fast becoming an issue in the harsh Australian climate. This paper proposes a novel design capable of producing electrical energy and desalinating water using only waste heat from industrial processes. A finned heat pipe heat exchanger plays an integral role in this process, extracting heat from a low-medium temperature waste heat stream and passing it through a thermoelectric generator and evaporative water desalination unit. Preliminary experimentation on this system showed that different desalination loop configurations played a large role in the desalination ability of the system, however had negligible effect on the thermal to electrical conversion efficiency of the system. When a closed loop system was used, the recovery ratio of the desalination unit reached 4% at the highest waste heat temperature. In the open loop configuration, the recovery ratio was below 1% for all tested inputs. The thermal to electrical conversion efficiency of this system was also measured and a value of about 1.2% was determined for most cases. Thus the ability of this novel system to both produce useful electrical energy and desalinate water was proven.
Unconventional and Irregular Clustered Arrays
Authors: Abdulqader Ahmed Jameel , Ramadhan Mohammed Jafar , Thaher Raad H. 
Published: May 2021

Abstract
In this paper, two different structures based on fully and partially irregular clustered elements are presented to optimize the radiation patterns of the large arrays. In the Fully Irregular Clustered Elements (FICE) structure, all the elements of an ordinarily large linear array are divided into multiple irregular and unequal-size clusters, while in the Partially Irregular Clustered Elements (PICE) structure, only the elements those located at the edges of the ordinarily linear array are grouped into unequal-size clusters. In this structure, the central elements are left without clustering (i.e., excited individually). The PICE structure has several advantages over the FICE structure. Since the quantized amplitudes (i.e., discrete distribution) are used with the proposed clustered structures, the corresponding clustered array patterns are usually associated with the undesirable high periodic sidelobes. In order to overcome this problem, the elements in the clusters are distributed a periodically. Simulation results demonstrate the ability of the proposed two structures, FICE and PICE, to significantly reduce the high periodic sidelobe level to -35dB and -40dB respectively for an array with a number of elements N=100 and unequal-size clusters.
Performance Investigations of the Uniformly and Non-Uniformly Excited Linear Arrays
Authors: Younis Roua Moafaq , Mohammed Jafar R. 
Published: May 2021

Abstract
Uniform linear arrays include the arrangement of all array elements in one dimension with equal amplitude excitations. Such types of arrays usually have good directivity, narrow beam-width, and they suffer from high sidelobe levels that may cause interference and degrade the overall system performance. The problem of high side lobe levels may overcome by using non-uniformly excited arrays instead of its uniform counterpart. In this paper, the Dolph and Taylor excited arrays are adopted as a non-uniformly excited array. The performance in terms of half power beam width (HPBW), Peak sidelobe level (SLL), directivity (D), and first null-to-null beam width of the uniformly and the two non-uniformly excited arrays are investigated and compared. Simulation results show that the non-uniformly excited arrays can significantly reduce the peak SLL at the cost of lower directivity and wider HPBW. Thus, it is advised to use the non-uniformly excited arrays in the environments that borne high interference pollution.
Side Lobe Reduction Using Non-Uniform Linear Phased Arrays
Authors: Mohammed Rasha Bashar , Mohammed Jafar R. 
Published: May 2021

Abstract
Non-uniform amplitude excitation arrays are nowadays very desirable in the modern wireless communication systems. They have ability to provide required radiation characteristics such as low side lobes and good directivity. The uniform amplitude excitation arrays are good in providing good directivity and narrow beam width. However, these desired radiation features are come at the cost of relatively high side lobes. Thus, these types of arrays are not widely used in the wireless communication systems especially when these arrays are operated in a noisy and crowded environment that contains many interfering signals. Non-uniform amplitude excitations such as Dolph and Taylor are considered in this paper and their performances are investigated under various array parameters. Simulation results show that as the amplitude excitations of the array elements decaying at the edge elements more reduction in the sidelobe patterns can be obtained.
Distributed Generation Embedding to Enhancing the Iraqi Grids Based on Optimization Technique
Authors: Jawad Ihsan Mousa , Wafaa Said Majeed 
Published: May 2021

Abstract
This research aims to analyze the impact of Distributed Generation (DG) on congestion line mitigation, power loss reduction, and voltage profile enhancement for Iraq’s 400kV national grid system. The suggested Particle Swarm Optimization (PSO) and Exchange Market Algorithm (EMA) are implemented to specify the optimum size and location based on an analytic approach depended on voltage, active losses, and congestion lines as fitness. Then it is added to the super 400kV Iraqi grid. The results demonstrate the efficiency of the proposed approach in determining the optimum size and location, decreasing the congestion line, reducing power losses, reducing line flow, and improving the bus voltage profile. The results are obtained with proposed algorithms implementation by using programming language within MATLAB/R2018a environment.
Integrated Artificial Intelligent with RS and GIS for Long-Term Drought Prediction
Authors: Yahya Bashar Muneer , Seker Dursun Zafer , Hameed Basman Younus 
Published: May 2021

Abstract
The accurate evaluation of drought plays an urgent role in the optimal solution for future development. The present research aimed to predict and assess drought in Nineveh governorate northwestern Iraq by integrated a fuzzy logic procedure with Geographical Information System (GIS) environment. Primary meteorological data for six stations were used in this study. Vegetation cover changes were detected using remote sensing analysis in which there was a decrease in the vegetation cover’s area by 17.7% from 592.3 km 2 in the year 1992 to 487.46 km 2 in the year 2016. Standardized Precipitation Index (SPI) as a proxy for drought conditions was simulated by developing the model of Adaptive Neuro-Fuzzy Inference System (ANFIS) as an artificial intelligent approach where its performance reached to 82% when evaluating the Nash-Sutcliffe coefficient and Root Mean Square Error (RMSE)as performance criteria. However, the long-term meteorological drought was an assessment where the results show that the drought level will intensify in a future by 10.1% with more successive droughts levels. Those results were clarified through developing spatial distribution map for long-term drought simulation by employing the (GIS) as a database to develop future plans for the study area.
Influence of Dam to Rainfall-Runoff Response in a Tropical Climate – A Case Study of Selangor River Basin, Malaysia
Authors: Bahar A F , Yusop Z , Alias N E , Ramli M W A 
Published: May 2021

Abstract
This paper discusses the rainfall-runoff response by comparing the runoff coefficient, c between two catchments of different characteristics within the Selangor River Basin, namely Catchment A (CA) and Catchment B (CB). Catchment B is a sub-catchment of Catchment A, whereby CA is about 6.8 times larger than to CB. The landscape of CB is largely covered by forest, has higher river slope and a dam completed in year 2004 at upstream of the basin. Annual mean-areal-rainfall (MAR) and total runoff from 1990 until 2018 was used for the rainfall-runoff coefficient, c calculations. The rainfall-runoff response was assessed by separating the analysis into 2-time frames; 1990 to 2000 (before dam construction) and 2007 to 2018 (after dam construction). The analysis before dam construction showed that CB has higher runoff response compared to CA. This was due to the difference in land use, catchment slope and lesser water abstractions compared to CA. The runoff coefficient, c for CA was in the range of 0.19-0.48, while CB was in the range of 0.59-0.79. This means that 19% to 48% of the rainfall was converted into runoff for CA, and 59% to 79% of the precipitation turned into runoff for CB. As suspected, after the dam construction the c coefficient for CB changed to 0.28-0.89, indicating a higher variability in the catchment response due to dam operations and control at the upstream.
Effect of Biocementation via Enzymatic Induced Calcium Carbonate Precipitation (EICP) on the Shear Strength of Compacted Clay Liner
Authors: Zango M U , Kassim K A , Muhammed A S , Ahmad K , Makinda J 
Published: May 2021

Abstract
The strength of residual soil treated via biocementation means by employing enzymatic induced calcium carbonate precipitation (EICP) was assessed based on the standard recommended for compacted clay liner. EICP treated samples were prepared at four different concentrations of cementation solution (urea-CaCl 2) (0.25, 0.50, 0.75 and 1.00 M) and at various moulding water content (-2, 0, +2 and +4% OMC) using reduced British standard light compaction effort (RBSL). The result obtained has shown UCS values of untreated natural soil at the four molding water contents were less 200 kPa, the minimum standard recommended for compacted clay liner. Upon EICP treatment, it was determined that the UCS values increase with the increase in the concentration of cementation solution. The treated soils at all the cementation solutions and molding water contents have UCS values greater than 200 kPa. The lowest strength of the treated soils was 468.5 kPa determined at 0.25 M cementation solution and +2% OMC molding water content. The maximum UCS (643.5 kPa) value was determined at 1.00 M urea-CaCl 2 and -2% OMC. The results also reveal that calcium carbonate content in the treated soil increases with the increase in the concentration of cementation solution. Microstructural analysis on the treated soil indicated the presence of white precipitation within the pore space of the soil, and the mineral was confirmed to be calcite through XRD analysis.
Effects of Cement on the Compaction Properties of Lateritic Soil
Authors: Wahab N A , Rashid A S A , Roshan M J , Rizal N H A , Yunus N Z M , Hezmi M A , Tadza M Y M 
Published: May 2021

Abstract
Lateritic soils at Universiti Teknologi Malaysia (UTM) Skudai, Malaysia was investigated subjected to their geotechnical properties and their suitability to be used as construction materials. The soil samples were collected and tested for various basic soil properties tests such as Atterberg Limit, Specific Gravity (SG), Sieve Analysis, and Compaction test. Atterberg’s consistency limit test shows that the liquid limit (LL) is 70.3%, the plastic limit (PL) is 42.0%, and the plasticity index (PI) is 28.3%. The specific gravity (SG) value for laterite is 2.74. For the compaction test, the optimum moisture content (OMC) and maximum dry density (MDD) obtained are 28% and 1.39 g/cm 3. A laboratory study was performed to compare and evaluate the stabilization efficiency of different percentages (3%, 6%, 9%, 12%) of Ordinary Portland Cement (OPC) when applied to the available laterite soil; a major soil group in the tropical areas. Analysis of laboratory data is assessed from a soil compaction test through the standard proctor method by using the automatic compactor. The soil mixtures were compacted at optimum moisture content in accordance with the British Standard (BS) of BS 1377-4:1990. From the preceding results, it was found that the OMC increase from 28% to 34% while the MDD increase from 1.39 g/cm³ to 1.47 g/cm³ with the rise in the percentage of cement.
Microstructure and wear resistance of bimodal cemented carbide coating prepared by direct laser powder deposition
Authors: Ye Nan , Ma Yunzhu , Tang Jiancheng 
Published: May 2021

Abstract
Compact spherical WC-12Co composite powder was deposited on 304 stainless steel substrate by multi-layer laser powder deposition (LPD) to fabricate cemented carbide coating. The phase constitution and microstructure of the coating as well as the feedstock powder were characterized. Microhardness and dry sliding wear tests were also performed to assess the mechanical properties of the coating. The results showed that the coating exhibited distinct microstructures and phase constitutions at different depths due to the various thermal cycles and the resulting heat damages of feedstock powders. The upper region of the coating (i.e. the wear resistant layer) exhibited bimodal microstructure in which the incompletely dissolved WC-Co composite particles preserved the original submicron sintered structure and secondary carbides were precipitated around them. Owing to the fine-grained strengthening of submicron WC grains in the undissolved areas, the microhardness of wear resistant layer was enhanced to 8 times that of the substrate. The wear rate of the cemented carbide coating was about three orders of magnitude lower than that of the substrate when dry sliding against Al2O3 ball under 10 N normal load. The bimodal structure of the wear resistant layer and the synergistic enhancement of differently sized carbides are the key factors for the excellent wear resistance of the coating.