bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonlinear convective motion of the asthenosphere and the lithosphere melting: a model for the birth of a volcano
Authors: Godano C. , De Nicola S. , Fedele R. , Carlino S. , Oliveri F.
Published: April 2022

The processes of heat transfer occurring between the Earth’s asthenosphere and lithosphere are responsible for partial melting of rocks, leading to the magma generation and its migration and segregation in the crust and, possibly, to volcanoes generation at the surface. Convection is the dominant mechanism regulating the heat transfer from the asthenosphere to the lithosphere, although many aspects of the whole process are not yet clear. Therefore, the knowledge of the physical processes leading to the melting of the lithospheric rocks has important consequences in understanding the interior Earth dynamics, the surface volcanic dynamics, and its related hazards. Rock melting occurs when the temperature gradient meets the rock solidus. Here, we propose a nonlinear convective 1D analytical model (representing an approximation of more 3D complex models). The steady-state solution of our equation is in good agreement with the estimated geotherms of the asthenosphere. A perturbative approach leads to a heat swelling at the boundary between asthenosphere and lithosphere able to determine its melting and the birth of a volcano.
On solution of ordinary differential equations by using HWCM, ADM and RK4
Authors: Bakir Yasemin , Mert Oya
Published: April 2022

The Haar wavelet collocation approach (HWCM) is an impressive numerical method for solving linear initial value problems when compared to the existing numerical methods (Adomian decomposition method (ADM) & Runge–Kutta method (RK4)). The objective of this study is to use the Haar-wavelet technique, Adomian decomposition technique (ADM) and Runge–Kutta (RK4) method to achieve the numerical solution of second-order ordinary differential equations. The proposed methods are applied to three different problems and the numerical results show that the HWCM has better agreement with analytic solutions than the other numerical methods.
WHICH FACTORS MATTER TO DEPOSIT INSURANCE COVERAGE LIMIT? EVIDENCE FROM EMERGING MARKETS
Authors: CHANG YIMING , YU XIANGYUAN , ZHAO SHANGMEI , YANG HAIJUN
Published: April 2022

This paper analyzes the effects of the household savings rate, interest rate spread and bank capital to total assets on the relationship between banks’ risk-taking and explicit deposit insurance coverage while controlling for certain macroeconomic factors, bank-level factors and political factors with data from 50 emerging markets. It is found that the U-shaped relationship between banks’ risk-taking and coverage is more apparent in countries with higher household savings rates, lower interest rate spreads or lower bank capital to total assets. The risk-minimizing coverage settings are analyzed and compared with the actual limits for emerging market economies in 2013. For emerging market countries, the effects of the household savings rate, deposit and loan spreads and banks’ capital to assets ratio should be fully considered when setting reasonable deposit insurance coverage, and their interaction with coverage should be emphasized.
Image Inpainting Based on Contextual Coherent Attention GAN
Authors: Li Hong-an , Hu Liuqing , Hua Qiaozhi , Yang Meng , Li Xinpeng
Published: April 2022

In order to address the problems of traditional inpainting algorithm models, such as the inability to automatically identify the specific location of the area to be restored, the cost of inpainting and the difficulty of inpainting, and the problems of structural and texture discontinuity and poor model stability in deep learning-based image inpainting, this paper proposes an image inpainting based on a contextual coherent attention. This paper designs a network model based on generative adversarial networks. First, to improve the global semantic continuity and local semantic continuity of images in image inpainting, a contextual coherent attention layer is added to the network; second, to solve the problems of slow convergence and insufficient training stability of the model, a cross-entropy loss function is used; finally, the trained generator is used to repair images. The experimental results are compared using PSNR and SSIM metrics, compared with the traditional GAN model, our model has a 3.782dB improvement in peak signal-to-noise ratio and a 0.025% improvement in structural similarity. The experimental results show that the image inpainting method in this paper has better performance in terms of image edge processing, pixel continuity and overall image structure.
Extracting Prerequisite Relations among Concepts From the Course Descriptions
Authors: Xiao Kui , Bai Youheng , Wang Zesong
Published: April 2022

Nowadays, online learning is becoming more and more popular. Various online learning platforms provide a huge amount of learning resources for learners around the world. When choosing or sorting learning resources, learners often need to know what important knowledge concepts are addressed in each learning resource. Exploring the prerequisite relations among concepts is of great significance to educational planning. In this paper, we extracted concepts from the content of course descriptions and proposed a new approach that uses both course-based features and Wikipedia-based features to discover the prerequisite relations between knowledge concepts. Experiments on both English and Chinese datasets show that the proposed method outperforms existing baselines.
Study of anisotropic stellar objects, a revisit to Buchdahl metric potential
Authors: Tamta Pramesh , Fuloria Pratibha
Published: April 2022

In this paper, we explore anisotropic compact stellar models in the framework of general theory of relativity with [Formula: see text] component governed by Buchdahl ansatz. We choose the anisotropic factor such as to render the solution physically compatible for stellar modeling. We have analyzed the solution for different values of [Formula: see text] to demonstrate the profiles of thermodynamical variables. The stability of the proposed models has been verified using different stability criteria. The hydrostatic equilibrium condition is well retained by the models studied in this work. The Buchdahl limit is well obeyed by the proposed models. The models of four compact stars viz., PSR J1614-2230, Vela X-1, Cen X-3 and SMC X-4 are extensively analyzed in close agreement with their observational details.
Seismic Performance Control of Tall Buildings Using a Novel Self-Centering Shear Wall System
Authors: Xiong Chen , Liu Yousen , Xie Linlin , Li Qiangsheng
Published: April 2022

The reinforced concrete (RC) shear wall system is widely used as a lateral force resisting system in high-rise buildings. Nevertheless, the shear wall components of the system are vulnerable to destructive earthquakes, and the damage of shear wall components is a major hindrance for the seismic resilience of high-rise buildings. Therefore, a novel self-centering repairable (SCR) shear wall system is introduced in this study. Compared with the conventional RC shear wall system, the proposed SCR shear wall system exhibits good self-centering capability, and the energy dissipation element can be replaced easily after an earthquake. First, the configuration of the SCR shear wall is presented. Next, the design criteria used to achieve good self-centering and energy dissipation are discussed, and the finite element model used to simulate the SCR shear wall is presented. Finally, case studies are performed, and the numerical results indicate that the proposed SCR shear wall system exhibits better self-centering performance than the RC shear wall benchmark model. The outcomes of this study are expected to provide a useful reference for future experimental studies and practical applications of the presented SCR shear wall systems.
Damping Performance Analysis of the Damped Outrigger System Based on H∞
Authors: Liu Liangkun , Li Xiangxiu , Tan Ping , Pan Zhaodong , Zhang Shangrong
Published: April 2022

A cantilever beam with multiple rotation spring-dampers was utilized to simulate the damped outrigger system. Two new methods, namely, the “Maxwell dampers type method” and the “virtual small mass method,” were proposed to present the simplified seismic response analysis of the damped outrigger system. Corresponding dynamic characteristic equations based on the proposed methods were also given. Subsequently, [Formula: see text] performance index was employed to obtain the optimal damper parameters. The numerical analysis shows that the proposed methods agree well with the finite-element method and have relatively accurate results. Stiffness ratios of the perimeter columns have a significant effect on the pseudo frequencies and system damping ratios. Lower stiffness ratios of the perimeter columns commonly lead to higher pseudo frequencies and system damping ratios. Furthermore, the damped outrigger system has excellent seismic mitigation performance when applied with appropriate damping parameters based on [Formula: see text].
Dynamic Response Analysis of Dual-Rotor System with Rubbing Fault by Dimension Reduction Incremental Harmonic Balance Method
Authors: Zhao Qian , Liu Jie , Yuan Jing , Jiang Huiming , Gao Linxing , Zhu Jun , Yao Hongliang , Wen Bangchun
Published: April 2022

The dimension reduction incremental harmonic balance (DRIHB) method is developed to study the dynamic behavior of dual-rotor system with multi-frequency excitations and nonlinear rubbing faults. On the basis of consideration of an aero-engine, a dynamic model of rotor system is built and the piecewise-nonlinear model of rubbing force is used to investigate the nonlinear behavior of system. Considering the features of multi-frequency excitation, high dimension and strong nonlinearity of dual-rotor system, the dimension reduction approach combined with the incremental harmonic balance (IHB) method is derived for theoretically studying the dynamic response of system with nonlinear rubbing fault. The accuracy and efficiency of the method are proved through comparison with the numerical simulation result solved by the Newmark-[Formula: see text] method and the IHB method. Then, the influences of rubbing stiffness, contact gap, rotational speed and speed ratio on dynamic response are studied and discussed. It is shown that the dual-rotor system with nonlinear rubbing fault will cause the system to generate rich combination frequency components in addition to excitation frequency. All the works indicate that the DRIHB method is an effective tool for studying the nonlinear behavior of dual-rotor systems with multi-frequency excitation, high dimensions and strong nonlinearities.
Shear Performance of Corrugated Steel Webs with Local Uniform Defects
Authors: Wen Zong-Yi , Wei Xing , Xiao Lin , Dai Li-Jun
Published: April 2022

Owing to the superior mechanical performance, corrugated steel webs are extensively applied and their shear performance is critical, because of the thin wall. After the steel is corroded and the web is weakened, the problem of shear resistance may become more prominent. The shear performance of corrugated steel webs with local uniform loss was studied to simulate a common corrosion state. Twenty-eight FE models with different defect characteristics, containing defect height and web thickness, are established to simulate corroded corrugated webs. Shear capacity, shear strength, out-of-plane stiffness and bending stiffness are studied. Based on previous studies, the prediction formula is proposed to predict the residual shear strength. Additional FE models are built to validate the reliability. Results indicate that web thickness is the key factor to decide the deformation shape and shear capacity, compared with defect height. Bending stiffness decreases as defect increases. With 62.5% of the initial thickness, the influence of the variation of defect height on the bending stiffness is within 10%. Variation in thickness also affects the sensitivity of shear capacity to corrosion parameters and failure modes. When the thickness exceeds 1.25 mm, about 62.5% of the initial thickness, shear capacity is more sensitive to corrosion height than when the thickness is less than 1.25 mm. The proposed formula is validated and has a good agreement with the FE results, which could help to design the durability of corrugated steel webs and evaluate the performance of existing corrugated steel webs.
Gen “Z” and Tourism Destination: A Tourism Perspective of Augmented Reality Gaming Technology
Authors: Mavragani Eleni , Dionysios Paliouras
Published: April 2022

In contemporary Tourism industry, DMOs are necessary to adopt and offer innovative experience in order to attract contemporary tourists. Gamification, combined with Augmented Reality and all the relevant to this technology innovations are examined in this paper. Efforts should rely on the demands and needs of generation Z tourists as up and coming generation. However, there are specific implications such as the use of augmented reality smart glasses, incentives and personal data protection that occur. This paper contributes in understanding the new Generation called “Z”, under the light of tourism and the effective use of augmented reality for tourism purposes, combined in one travel-product experience.
Geometric phases for three cases of the electric field with new type Bishop frame in ℝ13
Authors: Yoon Dae Won , Gürbüz Nevin Ertuğ
Published: April 2022

In this paper, we study geometric phases for an electric field in Minkowski 3-space. In particular, we consider Bishop 2-type frames of a spacelike and a timelike curve in Minkowski 3-space and investigate three geometric phases for three cases of electric fields with respect to the Bishop 2-type frames along a spacelike and a timelike curve. Also, we compute spatial and time evolutions of the complex frame connected with electric fields for Bishop 2-type in terms of modified Hasimoto transformations. As a result, we give a modified Fermi–Walker parallel derivative and a Rytov parallel transportation of electric fields. Finally, we discuss Lorentz force of a magnetic field as a Killing vector field along a spacelike and timelike curve in Minkowski 3-space.
On the multiplicative independence of the roots of generalized Fibonacci and Pell polynomials
Authors: Alahmadi Adel , Luca Florian
Published: April 2022

The [Formula: see text]-generalized Fibonacci and Pell polynomials are the polynomials [Formula: see text] and [Formula: see text], respectively. Here, [Formula: see text] is any integer. In this paper, we show that any two roots of some generalized Fibonacci and Pell polynomials are multiplicatively independent confirming a conjecture from [Bravo, Herrera and Luca, Common values of generalized Fibonacci and Pell sequences, J. Number Theory  226 (2021) 51–71].
On the weighted average number of subgroups of ℤm × ℤn with mn ≤ x
Authors: Kiuchi Isao , Saad Eddin Sumaia
Published: April 2022

Let [Formula: see text] be the additive group of residue classes modulo [Formula: see text]. For any positive integers [Formula: see text] and [Formula: see text], let [Formula: see text] and [Formula: see text] denote the total number of subgroups and cyclic subgroups of the group [Formula: see text], respectively. Define [Formula: see text] In this paper, we study the asymptotic behavior of the functions [Formula: see text] and [Formula: see text].
Design of a Flat Panel Detector for the PET-Laparoscope System Using Simulations
Authors: Yue Xiaodong , Liyanaarachchi Madhushanka Rukshani , Shimazoe Kenji , Ogane Kenichiro , Takahashi Hiroyuki , Takahashi Miwako , Hara Kazuaki , Kobayashi Etsuko , Sakuma Ichiro
Published: April 2022

To improve spatial resolution in the PET-laparoscope system for intraoperative metastatic lymph nodes detection, design of a flat panel detector was optimized using Monte Carlo simulation tools. The performance of the new fixed detector was evaluated in point radio-source and phantom experiments. The experiment result shows that the system with the new fixed detector design has a spatial resolution better than 10[Formula: see text]mm in three dimensions, and the system can distinguish two radio-sources clearly in a 2-minute scan.
Responsible Computing: A Longitudinal Study of a Peer-led Ethics Learning Framework
Authors: McDonald Nora , Akinsiku Adegboyega , Hunter-Cevera Jonathan , Sanchez Maria , Kephart Kerrie , Berczynski Mark , Mentis Helena M.
Published: April 2022

We studied the impact of introducing first-year computer science (CS) students to ethical thinking about the social justice impacts of data collection, tracking, bias, internet privacy, and competitive “real world” system design and critique activities. While basic content was consistent for all, one group was involved throughout the course in peer discussions designed to foster greater engagement, with the anticipation that this would enable students to reach new levels of sensitivity through peer-to-peer interaction. This article reports on our observation of this design, interview, and project data collected throughout the course as well interviews conducted eight months later to learn about how students were retaining and applying what they learned. We found that students are sensitive to the technology-related risks and vulnerabilities encountered by individuals based on race, gender, and, to some extent, age, but they struggle to assess who is responsible for these risks, what to do about bias in technology design, and how to mitigate harms for individuals whom they perceive to be vulnerable, furthering the argument for an integrated ethics curriculum. We explore the value of formal peer-led discussion to evolve social justice thinking with a focus on identity, though note that opportunities for any group discussion are meaningful to students’ thinking about social justice. Over the longer term, students tend to recall and apply ethics that is closely related to their identity, suggesting that empathy has limits.
Identifying Museum Visitors via Social Network Analysis of Instagram
Authors: Chang Mi , Yi Taeha , Hong Sukjoo , Yan Lai Po , Jun Ji Young , Lee Ji-Hyun
Published: April 2022

As social networking services (SNSs) have become increasingly influential, they are now a vital element in art museums because communication with visitors is crucial. However, conventional methods of visitor studies do not consider the characteristics of SNSs. Even when a museum uses a SNS as a marketing tool, it cannot sufficiently analyze the data to understand the visitor. Additionally, linking the SNS analysis content with the actual visitor in the museum requires an application to identify visitor types. Therefore, we extracted communities through a social network analysis of museum followers, analyzed the characteristics for specific groups, and designed a web-based, visitor-type analysis application for art museums based on text-similarity measurements. The experimental results demonstrated that followers of each art museum on a SNS form a community with similar characteristics or interests. Furthermore, our developed application provides a new way to analyze the type of visitors in an art museum. Consequently, because it can automatically identify visitor types, it improves the exhibition experience of visitors by linking them with the exhibition contents or guide services and is a new attempt to connect a SNS with the museum visitor.
Heterogeneous Network Access and Fusion in Smart Factory: A Survey
Authors: Xia Dan , Jiang Chun , Wan Jiafu , Jin Jiong , Leung Victor C. M. , Martínez-García Miguel
Published: April 2022

With the continuous expansion of the Industrial Internet of Things (IIoT) and the increasing connectivity among the various intelligent devices or systems, the control of access and fusion in smart factory networks has significantly gained importance. However, the contradiction between the high Quality of Service (QoS) requirements of massive data and the limited network bandwidth and the heterogeneous network is becoming deeper and deeper. The heterogeneity of smart factory networks brings many challenges to unified access and fusion, real-time transmission, and centralized control and management. This article provides a survey on heterogeneous networks in smart factories. We first study and discuss the heterogeneity of smart factory networks, and then discuss the existing mainstream wired and wireless network technologies, as well as promising future technologies, including 5G, OLE for Process Control Unified Architecture (OPC UA), and Time-Sensitive Networking (TSN). In addition, we also analyze current heterogeneous network fusion architecture and discuss the enabling technologies of heterogeneous network fusion in view of the shortcoming of the current solutions. Finally, we conclude with a discussion of open challenges and future research directions towards the effective realization of the smart factory.
PEACE: A Model of Key Social and Emotional Qualities of Conversational Chatbots
Authors: Svikhnushina Ekaterina , Pu Pearl
Published: April 2022

Open-domain chatbots engage with users in natural conversations to socialize and establish bonds. However, designing and developing an effective open-domain chatbot is challenging. It is unclear what qualities of a chatbot most correspond to users’ expectations and preferences. Even though existing work has considered a wide range of aspects, some key components are still missing. For example, the role of chatbots’ ability to communicate with humans at the emotional level remains an open subject of study. Furthermore, these trait qualities are likely to cover several dimensions. It is crucial to understand how the different qualities relate and interact with each other and what the core aspects would be. For this purpose, we first designed an exploratory user study aimed at gaining a basic understanding of the desired qualities of chatbots with a special focus on their emotional intelligence. Using the findings from the first study, we constructed a model of the desired traits by carefully selecting a set of features. With the help of a large-scale survey and structural equation modeling, we further validated the model using data collected from the survey. The final outcome is called the
PEACE model (Politeness, Entertainment, Attentive Curiosity, and Empathy)
. By analyzing the dependencies between the different PEACE constructs, we shed light on the importance of and interplay between the chatbots’ qualities and the effect of users’ attitudes and concerns on their expectations of the technology. Not only PEACE defines the key ingredients of the social qualities of a chatbot, it also helped us derive a set of design implications useful for the development of socially adequate and emotionally aware open-domain chatbots.
Ineffectual Transference of SDGs as Local Level Indicators: Tracing India’s Path to Agenda 2030
Authors: Kushwaha Neeharika , Nangia Charu , Adhvaryu Bhargav
Published: April 2022

Since the conception of the Agenda 2030, indicator based systems formulated as sustainability assessment tools on different scopes and geographical scales of urban development strive for ubiquitous application of the 17 SDGs globally. The execution of these goals in India as well are focused through formal assessment tools with standardized indicators of sustainability at various levels. However, semantic literature perusal and analysis of these tools show us a substantial lag towards their enactment as subordinates to one another and in promoting the effective translation of SDG targets as local level indicators among the pillars of sustainability. The study thus intends to abate the gap in existing literature focusing on sustainability issues of India and direct a discussion towards sculpturing the SDG indicators as core dimensions of city development plans than just as performance assessors of the cities.
Substrate Dependent Study of Mim Capacitors for Resistive Random-Access Memory Applications
Authors: Kaushik Shikha , Pandey Sujata , Singhal Rahul
Published: April 2022

The present study focusses on the fabrication of Metal/MOx/Metal for ReRAM application. We evaluated I-V characteristics using pressure contact with both substrates and found that the silicon substrate has a relatively low switching rate (nearly linear curve), whereas the ITO substrate has a resistance ratio of 10, which gives the optimum switching performance. The identical model was developed in COMSOL software and used for validation, and the metal rich characteristics enhancement is studied. The stoichiometry of metal oxide film has been measured by Resonant Rutherford back Scattering (RRBS) of ZnO coated Au deposited Silicon. X-ray diffraction (XRD) analysis was used to characterize the crystalline structures of Au-deposited ZnO on ITO samples. It was observed that the desired (002)-oriented ZnO wurtzite phase exists. Raman parameters like force constant and bond length is calculated corresponding to the wave number.
Ethical Tenets of Stock Price Prediction Using Machine Learning Techniques: A Sustainable Approach
Authors: Vellaiparambill Alan , Natchimuthu Natchimuthu
Published: April 2022

When Machine Learning (ML) algorithms take over decision-making from human conscience and cognition, the essence of ethics gets saturated. The visible decline of ethics generally gets reflected in financial markets, as it portrays human actions and sentiments in numerical terms than any sector. Accuracy in stock market prediction remains inefficient due to many known and unknown variables. Academia and industry recently relied on ML at large to track the market and monetize the movements. The norms of fairness, accuracy, dependability, and transparency in financing is left unattended in ML prediction models with assumptions far from reality. The integration of the tenets proposed in this study can emphasize and reconfigure the sustainable side of investing with concepts already in place but not connected to the network of prediction models. This study focuses on the ethical dimension of Machine Learning models and generates a sustainable framework for investors. Specifically, the Sustainable Development Goals (SDG) can enhance the prediction models in ML with improved efficiency. Along with SDG, this research broadens the variables' horizon of prediction in ML of computer science domain with concepts of Socially Responsible Investing (SRI), Environmental Social and Corporate Governance (ESG), and carbon footprints. With 115 articles reviewed, the proposed framework ensures sustainability in investments at the grassroots level. When adding the sustainability quotient backed by recognized norms, the research can be a breakthrough in rational investing based on ethical judgments aided by initiatives like the United Nation's SDG goals.
Zinc Aluminate (ZnAl2O4) Supported and Catalyzed Highly Effective Sonogashira Cross-Coupling and Cyclization Reaction Under Microwave Irradiation Used in One-Pot Tandem Synthesis of Furo[3,2-H]Quinolines
Authors: SAHA Pritam , Taran Subhrangsu , Mukherjee Koushik
Published: April 2022

The Sonogashira reaction (SR) which forms a C–C bond by cross-coupling a vinyl/aryl halide with a terminal alkyne, uses a palladium species as a catalyst, with a copper species as co-catalysts and a phosphine/amine as ligand/base in its actual form. This efficient reaction is beneficial in synthesizing heterocycles, nanomaterials, medicines and other complex molecules with biological functions. However, in this study, we were able to successfully execute the SR under microwave irradiation, using zinc aluminate (ZnAl2O4) as the catalyst, without using palladium, phosphines/amine as a ligand/base. This method, therefore, particularly useful for adhering to green chemistry principles and achieving atom-friendly reaction. In order to do this, we adopted a straightforward and concise method involving the development of a convergent protocol for sequential coupling and cyclization from Acetylenic 8-quinolinols generated in situ by the microwave-assistance SR to synthesize furo[3,2-h]quinolines, using ZnAl2O4 as a catalyst.
A Survey on Hadoop Security and Comparative Analysis on Authentication Frameworks in Hadoop Clusters
Authors: M Hena , Jeyanthi N
Published: April 2022

This paper presents a survey on various security frameworks which aim to secure Hadoop clusters and the files stored there. Most of the Hadoop platforms rely on Kerberos Authentication Protocol for user authentication. It is known that Kerberos itself has some vulnerabilities like Password Guessing Attacks, Single Point of Failure, Insider Attacks, and Time Synchronization problems. A new authentication framework that can address most of the identified issues and is computationally feasible than other schemes is introduced in this paper. The proposed framework is based on Secure Remote Password Protocol (SRP), Threshold Cryptography, and Blockchain Technology. The system focus on eradicating Password Guessing Attacks and Single Point of Failure in Kerberos Enabled Hadoop Clusters. The analysis results strengthen the claim that the proposed scheme beats the others in terms of computational efficiency and feasibility while offering the same security features. The paper is concluded with directions for future work.
Synthesis and Characterization of Rgo Doped Nb2O5 Nano Composite for Chemical Sensor Studies
Authors: M Mylarappa , S Chandruvasan , S Kantharaju , S Rekha
Published: April 2022

It has been reported that an effective synthesis of rGO-Nb2O5 composite for electrochemical sensor studies has been reported. The modified Hummer's method was used to produce reduced graphene oxide (rGO). The metal oxide (Nb2O5) was introduced to the rGO via the hydrothermal method to form the composite. X-ray diffraction (XRD), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR), and were used to examine the sample. The CV measurements show a significant improvement in electrochemical reversibility, with the specific capacitances of rGO and Nb2O5/rGO being 45 and 110 Fg-1, respectively. These results indicate that the capacitive behavior and electron transfer of the Nb2O5/rGO nano composite was significantly higher than that of rGO. The charge-discharge curves show good symmetry and linear deviations with time change, indicating superior capacitance. This is primarily due to the electrode reversible reaction, and it has also been revealed as a type of super capacitor electrode material. The electrode materials obtained have the highest specific capacitance and excellent rate capability.
Memristor-Based Deep Learning Classification Model for Object Detection
Authors: K I Ravikumar
Published: April 2022

The memristor-based neural network takes full use of the benefits of memristive devices, such as their low power consumption, high integration density, and great network recognition capacity, and therefore can be efficiently used for binary image classification in AI based applications. Before implementing the memristor-based memory at circuit level, the performance need to be analyzed. In this work, a nine-layer neuromorphic network is designed and is used to classify binary images. Using the MNIST dataset, the performance of architecture is validated and the impact of device yield and resistance fluctuations under various neuron configurations on network performance are studied. The implementation of restive random access memory (memristor based memory) is carried out using the memtorch in python 3.7 scripting language and the simulation was carried out using MemTorch, an open-source framework for customized large-scale memristive DL applications. The findings indicate that the nine-layer network has an accuracy of about 98 percent in digit recognition.
Optimal Location and Sizing of Reactive Power Compensation Devices for Voltage Stability Improvement of Radial Power Systems
Authors: Bhargavi R Naveena , Bhargavi R Anurup
Published: April 2022

With the advancement in technology, the electricity demand is increasing day by day. Power supply utilities are facing the problem to expand their network owing to the problems like availability of land in urban areas and Right of Way (ROW). Due to these problems, many of the existing lines are operating nearer to their thermal stability limit. Maintaining the voltage within the limits will be a challenging task for the utilities. Increased loading of the lines is making the power system to the verge of voltage stability. Many indices are proposed in the literature for predicting the voltage stability of the system. In this paper, L-Index is used for voltage stability analysis of the radial distribution system. L-Index sensitivity method is used to the locate and size the reactive power compensation devices. The effectiveness of L-Index sensitivity method on the larger power system like IEEE-33 bus system is presented in this paper and simulation studies are performed using MATLAB/SIMULINK.
Nanomaterial Reinforced Portland Pozzolana Cement Composite with Improved Strength for Reduced Carbon Emission
Authors: Laad Meena
Published: April 2022

The worldwide increase in greenhouse gas emissions is resulting in global warming and harming the land and aquatic species. One of the major components of greenhouse gases is carbon dioxide (55%) which is released into the atmosphere by different sources. Cement is the key ingredient of construction materials. Its production contributes about 3.2% of CO2 emissions. The present work elaborates the constituents, major sectors responsible for greenhouse emission, various techniques to reduce CO2 emission, and synthesis of graphene and fly ash reinforced Portland Pozzolana cement (PPC) composite. The study also reports the effect on the compressive strength of synthesized composites and its dependence on the curation time. The graphene and fly ash induced cement was found to be more robust, durable, efficient, and help significantly in reducing CO2 emission.
A Case Study on Human Health Risk Assessment Attributable to Particulate Matter at Kota Metropolis, Rajasthan (India)
Authors: Kuldeep Kuldeep , Sisodiya Sohil , Mathur Anil
Published: April 2022

Kota, an Indian metropolis, has been experiencing high particulate matter pollution for the last few years. The primary aim of this study is to perform a human health risk assessment caused by particulate matter concentrations for Kota Metropolis. The annual PM2.5 and PM10 concentrations for Kota Metropolis were 52.63 and 106.86 µg/m3, respectively, indicating the violation of Indian NAAQS. The PM2.5 induced long-term ENACs for mortality due to all-natural causes in adults, LC, ALRI, COPD, IHD, and Stroke were 4624, 819, 258, 440, 1976, and 1791, respectively, while short-term ENACs for hospital admission due to respiratory disease, cardiovascular disease, and all-cause mortality in adults were 1288, 50, and 679, respectively. The PM10 induced long-term ENACs for postneonatal infant mortality, chronic bronchitis incidences (adults), and pervasiveness of bronchitis in kids were 317131, 13448, and 700, respectively. The study presents important conclusions to stakeholders and policymakers to implement suitable mitigation measures.
Nature, Prevalence, and Impact of Undernutrition on Intelligence Among School Children: A Cross-Sectional Study from South India
Authors: R Anitha
Published: April 2022

Good nutrition is a basic criterion for optimum health, productivity, and overall functional efficiency. The children who had malnutrition in their early years secured poor cognitive test scores in school years compared to children with optimal nutrition. The present study aimed to associate the degrees of undernutrition and intelligence among school children. This is a cross-sectional study that included 600 children aged 6 and 12 years, and assessed the anthropometry and intelligence quotient levels through appropriate scales. The results revealed that the higher percentage of stunted, underweight, and thinness were highly associated with below-average intelligence, which was more than two times greater risk compared to the percentage with the degrees of undernutrition to the above-average intelligence. The children’s age, gender, birth weight, and socioeconomic status were also strongly associated with the intelligence quotient level. This study offers new insight for formulating the policies and intervention programs in the future.
Survey of Sentiment Analysis and Its Impact on Data Extraction
Authors: Ajmeera Narahari , P Kamakshi , B Vishnu Vardhan
Published: April 2022

With the advent of information exploration over the years, the most important thing to make the business decision is to consider the opinion of the people. Sometimes the opinions which are transformed to sentiments plays a vital role in the aforementioned areas. The opinion of the people is shared by the e-commerce, and social media networks like Twitter, Facebook, blogs, forums, etc. The opinion is categorized into positive, negative, and neutral opinion. To extract the sentiments, opinion there are different approaches available in the literature such as Support Vector Machine, Naïve Bayes, Neural Networks, lexicon based approaches, etc. In this paper, it is aimed at comparing different types of machine learning approaches, such as supervised, unsupervised, and semi-supervised learning algorithms, which are useful to extract the various opinions over the Net. It is further surveyed to understand various performance measures when the extracted opinions were transformed to sentiments.
Synthesis and Characterization of ZnO and MgO Nanoparticles through Green Approach and Their Antioxidant Properties
Authors: M Mylarappa , S Rekha , S Kantharaju , S Chandruvasan , K N Shravana
Published: April 2022

The present work focus on the synthesis and structural characterization of ZnO and MgO Nanoparticles using geranium leaves extract as reducing agent through green approach. The prepared ZnO and MgO Nanoparticles were characterized using X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM).The elemental composition of ZnO and MgO Nanoparticles were investigated using Energy Dispersive X-ray analysis (EDAX). Based on the XRD data, the ZnO and MgO particles were measured to be 64 and 42 nanometers in size, respectively. The DPPH method was used to further test the antioxidant property of the synthesized Nanoparticles. MgO and ZnO were both found to be excellent free radical scavengers, as measured by their DPPH scavenging activities. The antioxidant property of MgO is enhanced when compared to ZnO nanoparticles.
Studies on Bending Properties of AA 6061-T6 Aluminium Alloy Joined By Friction Stir Welding
Authors: Channabasavachar Yogeesha
Published: April 2022

Presently for various engineering applications AA6061-T6 aluminum-magnesium alloys are widely preferred, which is due to its light weight and superior properties as compared to other aluminum alloys. The metal joining process is most complex in various industrial applications like automobile, aerospace, railway and marine. The Friction Stir Welding (FSW) of AA6061-T6 alloy has influenced substantial scientific and industrial importance, because it has a potential to transform the welded product with a good quality joint. In the present work AA6061-T6 alloy joined using FSW process. Observation has been made about material flow behavior and effect of process parameters on various mechanical properties and associated defects during FSW. From experimental results it can be concluded that FSW can be used to produce defect free welds, with better bending properties as compared to the welds produced by other conventional welding process.
Unobtrusive Accelerometer-Based Longitudinal ADL Monitoring Among Different Populations
Authors: Soangra Rahul , Rajagopal Sivakumar , Shiraishi Michael , Daerendinger Johanna , Kohl Bridgette
Published: April 2022

Approximately 15 million people worldwide suffer from stroke each year and more than 10 million people live with Parkinson’s disease. Although wearable technology can monitor and collect data needed to make predictions about one’s health status, new methods for interpreting longitudinal datasets are lacking. Therefore, long-duration data cannot be translated into usable results that state a person’s health status. ADL is an essential factor in these populations since it results from health status and is influenced due to illnesses on the individuals. The amount of movement performed, the number of transitions occurring during sleep and when awake, variations in transitions of ADL, how much time in between each movement transition, and how often these movement transitions occur were considered aspects of daily living activities. We investigated using accelerometer sensors compared among healthy young, older, and individuals who had stroke and Parkinson’s disease.
Experimental Study of Bearing Capacity Bridge Foundation Determination
Authors: Nagappa Vijaykumar
Published: April 2022

Ethiopia is almost mountainous and hilly in topography, with many rivers flowing from the cities' centers. To facilitate transportation, a bridge across the Berbere Wonze River must be built. The bearing capacity of foundation soil is important for foundation design because it can carry heavy loads from the superstructure. The primary goal of this experimental geotechnical investigation is to determine the bearing capacity of foundation soil for the design of bridge foundation at Berbere Wonze River in Amahara Region South Wollo, Kombolcha, Ethiopia. The foundation investigation work includes a Dynamic Cone Penetration (DCP) test, a Standard Penetration Test (SPT), visual identification, groundwater monitoring, soil sampling, and subsequent laboratory tests on representative samples to determine the physical and engineering properties of the subsurface formations and soil underlying the proposed bridge sites. These are to provide safe and cost-effective foundations based on a combination of field data and laboratory test results.
Mass Residential Housing Projects and Sustainable Construction Practices
Authors: Aderogba Aderemi Muhammed , Faremi Olajide Olajide , Ajayi Oluranti Olupolola
Published: April 2022

The construction industry significantly consumes enormous energy and emits greenhouse gases due to its effort in bridging housing deficit arising from increased population both in developed and developing countries. The study assesses the extent to which sustainable building construction practices are incorporated in the construction of buildings in Lagos State, Nigeria. A survey of 100 construction professionals and mass housing unit owners was conducted on frequently implemented sustainable practices on buildings projects and the perceived satisfaction of users of buildings on sustainability features. A total of 80 questionnaires were successfully retrieved and processed for analysis using frequency tables and relative implementation index. The result shows that sustainable practices that are often incorporated into mass housing projects during construction include downsizing the dominant use of incandescent bulbs and replacing them with energy saving bulbs. The study concludes that there is a significant relationship between sustainable practices and the building users’ satisfaction.
Design and Development of a Low-Cost, Less Weight, and Lead-Free Composite Materials for Radiation Shielding
Authors: Rajagopal Sivakumar , Anand Suya Prem
Published: April 2022

The paper analyzes the performance of various composite materials in the lead-free apron for radiation shielding in biomedical applications. The challenging task is to extend the duration of wearing an apron, reduce the weight, and increase the comfort level for physicians. The lead-free composite materials used an alternative to lead in an apron due to their excellent properties, such as mass attenuation coefficients, effectiveness against gamma radiation, flexibility and light weight, and absorption. The present study discusses different simulation software used to assess the properties of the shielding material against the radiation effects. At the end of the paper, the promising directions are presented for future research.
Eyeball Movement Cursor Control Using OpenCV
Authors: B Chandra , Raja S Kanaga Suba , M Rohit , Vignesh R Sriram
Published: April 2022

The upcoming generation is going to be evolved with an interaction that will be nonverbal, which is called the eye gaze and it also develops a new mode of communication for disabled people. The basic need for this kind of a system is that it can provide the assistance that a third person gives for the physically disabled people and hence by the means of tracking the eyeball movement this is made possible. The right, left, top, and bottom movements are incorporated concerning the movement of the eyeball. The advanced version of this system comes with a chai that has wheels on the ends, hence this can also be mounted with the chair and hence it makes the user take the system wherever and everywhere he moves around. The tracking is generally done by taking the trace of the center of the pupil and hence with the traces it generates the center, top, right, left, and bottom.
Implementation of an Intelligent Neonatal Monitoring System Using Raspberry Pi
Authors: T M Inba Malar , Rajagopal Sivakumar , M Amala Justus Selvam , V Kannagi , G Bharatha Sreeja , Vivekanad Chettiyar Vani , A Jasmine Vijithra , N Sanjeev Kumar
Published: April 2022

An incubator is a biomedical apparatus used to keep neonates if they are ill and in need of further investigations. This is also useful for observation and care of newborn babies who were premature or of low birth weight. There will be loss of lives of neonates if the incubator is not appropriately monitored and this may even lead to accidents. In view of these, it has been proposed to implement an Intelligent Monitoring System for Neonatal Intensive Care Unit (NICU). For monitoring the premature infants continuously it requires sensors. It has been learnt that the temperature, breathing rate, body movements, loudness, or cry are some of the features to be monitored in incubator. Hence, in this paper, a wireless communication and body area network based system that constantly examine the vital physiological parameters of the baby kept in the NICU has been discussed. The analog signals from the sensors are processed using a Raspberry Pi. The system has been developed with Raspberry Pi B+ module as the controller. Sensors are used to monitor the physiological parameters and Pi camera is used to detect the baby movements. Global System for Mobile Communications (GSM) module is incorporated in the proposed system to transmit the parameters via a short message service (SMS). Hence, this system offers a suitable method for parents and nurses to monitor premature infants.
Contemporary Study on Citrus Disease Classification System
Authors: Dhiman Poonam
Published: April 2022

Machine vision systems enable many applications in all important fields of life like medical healthcare, agriculture, fruit and vegetable industry, etc. One of the application fields is disease detection of fruit. The disease identification of fruits is a critical issue and advanced automatic detection systems need to be developed. In the recent years, image processing techniques have been employed for the quality evaluation of the fruits. This paper presents the current advancement in image processing techniques used by the disease recognition system of the citrus fruits. In past few years, different approaches are applied for grading the citrus fruits using machine vision system. The paper presents the overview of different techniques like pre-processing, segmentation, and classification that is used by the disease detection system of citrus fruits. This paper also presents the detailed description of the different state of art disease detection system proposed by the researcher for attending identifying the disease present in citrus fruit. The detailed survey of the disease detection technique present in citrus fruit has been presented to investigate the usage of recent approaches employed in machine vision systems.