S. Ravi Teja^a , Chellapilla V. K. N. S. N. Moorthy^b,*, S. Jayakumar^c , Ayyagari Kiran Kumar^d , V. Srinivas^c,*

Frontiers in Heat and Mass Transfer, Vol.15, No.1, pp. 1-9, 2020, DOI:10.5098/hmt.15.7

Abstract This article is a summary of research involving the evaluation of the thermo-physical properties of Mono-ethylene - glycol-based solar thermic fluids oxidized multiwalled carbon nanotubes. Nanofluids were prepared with Mono-ethylene glycol and water as base fluids in 100:0, 90:10 and 80:20 ratios. These base fluids of three categories were dispersed with purified and oxidized multiwalled carbon nanotubes (MWCNTs) in the weight fractions of 0.125, 0.25 and 0.5 percentages. The variation in zeta potential is studied to examine the dispersion stability during 2 months. Thermal conductivity and dynamic viscosity were measured by hot disk method and Anton paar viscometer respectively. Significant… More >

S. Duroudier¹ , S. Chardonnel¹, B. Mericskay² , I. Andre-Poyaud¹ , O. Bedel³ , S. Depeau², T. Devogele⁴, L. Etienne⁴, A. Lepetit², C. Moreau⁴, N. Pelletier² , E. Ployon¹, K. Tabaka¹

Revue Internationale de Géomatique, Vol.30, No.1, pp. 127-148, 2020, DOI:10.3166/rig.2020.00105

Abstract This paper aims at proposing a data quality diagnosis and cleansing data methodology experimented on an individual mobility survey (Mobi’Kids program). The first section presents the theoretical approach to highlight the issue of a data quality diagnosis applied to heterogeneous data collected from mixed methods (GPS tracks, surveys, observations). Secondly, two typologies of major errors are discussed according to their origin (GPS, algorithm, survey) and their nature (completeness, accuracy, consistency). A processing chain is thirdly defined to improve both internal and external data quality in order to the perspective of a replicable methodology.

RÉSUMÉ
Cet article a pour objectif de… More >

Xi Wang¹, Shan Qing^1,*, Zhumei Luo^1,*, Yiqin Liu^1,2, Zichang Shi¹, Jiachen Li¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.9, pp. 2399-2416, 2023, DOI:10.32604/fdmp.2023.028024

Abstract Propylene glycol-based MWCNT (multi-walled carbon nanotubes) nanofluids were prepared in the framework of a two-step method and by using a suitable PVP (polyvinyl pyrrolidone) dispersant. The BBD (Box-Behnken design) model was exploited to analyze 17 sets of experiments and examine the sensitivity of the absorbance to three parameters, namely the concentration of MWCNT, the SN ratio (mass ratio of carbon nanotubes to surfactants) and the sonication time. The results have revealed that, while the SN ratio and concentration of MWCNT have a strong effect on the absorbance, the influence of the sonication time is less important. The statistical method of… More >

Yue Yu¹, Junhua Wu^1,*, Guangshun Li¹, Wangang Wang²

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 583-598, 2023, DOI:10.32604/iasc.2023.037875

Abstract As an emerging hot technology, smart grids (SGs) are being employed in many fields, such as smart homes and smart cities. Moreover, the application of artificial intelligence (AI) in SGs has promoted the development of the power industry. However, as users’ demands for electricity increase, traditional centralized power trading is unable to well meet the user demands and an increasing number of small distributed generators are being employed in trading activities. This not only leads to numerous security risks for the trading data but also has a negative impact on the cost of power generation, electrical security, and other aspects.… More >

Zainab Ali Abbood^1,2,*, Doğu Çağdaş Atilla^3,4, Çağatay Aydin⁵

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 269-281, 2023, DOI:10.32604/iasc.2023.035276

Abstract Deep learning (DL) is a subdivision of machine learning (ML) that employs numerous algorithms, each of which provides various explanations of the data it consumes; mobile ad-hoc networks (MANET) are growing in prominence. For reasons including node mobility, due to MANET’s potential to provide small-cost solutions for real-world contact challenges, decentralized management, and restricted bandwidth, MANETs are more vulnerable to security threats. When protecting MANETs from attack, encryption and authentication schemes have their limits. However, deep learning (DL) approaches in intrusion detection systems (IDS) can adapt to the changing environment of MANETs and allow a system to make intrusion decisions… More >

Kunda Suresh Babu, Yamarthi Narasimha Rao^*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5887-5909, 2023, DOI:10.32604/cmc.2023.037486

Abstract The demand for cybersecurity is rising recently due to the rapid improvement of network technologies. As a primary defense mechanism, an intrusion detection system (IDS) was anticipated to adapt and secure computing infrastructures from the constantly evolving, sophisticated threat landscape. Recently, various deep learning methods have been put forth; however, these methods struggle to recognize all forms of assaults, especially infrequent attacks, because of network traffic imbalances and a shortage of aberrant traffic samples for model training. This work introduces deep learning (DL) based Attention based Nested U-Net (ANU-Net) for intrusion detection to address these issues and enhance detection performance.… More >

Ki-Yeol Eom¹, Byungseok Min^2,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6337-6350, 2023, DOI:10.32604/cmc.2023.035336

Abstract Automated X-ray defect inspection of occluded objects has been an essential topic in semiconductors, autonomous vehicles, and artificial intelligence devices. However, there are few solutions to segment occluded objects in the X-ray inspection efficiently. In particular, in the Ball Grid Array inspection of X-ray images, it is difficult to accurately segment the regions of occluded solder balls and detect defects inside solder balls. In this paper, we present a novel automatic inspection algorithm that segments solder balls, and detects defects fast and efficiently when solder balls are occluded. The proposed algorithm consists of two stages. In the first stage, the… More >

Afrah Al-Bossly^*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6395-6408, 2023, DOI:10.32604/cmc.2023.028433

Abstract Due to the drastic increase in global population as well as economy, electricity demand becomes considerably high. The recently developed smart grid (SG) technology has the ability to minimize power loss at the time of power distribution. Machine learning (ML) and deep learning (DL) models can be effectually developed for the design of SG stability techniques. This article introduces a new Social Spider Optimization with Deep Learning Enabled Statistical Analysis for Smart Grid Stability (SSODLSA-SGS) prediction model. Primarily, class imbalance data handling process is performed using Synthetic minority oversampling technique (SMOTE) technique. The SSODLSA-SGS model involves two stages of pre-processing… More >

Kaprawi Sahim^*, Dewi Puspitasari, Nukman

Frontiers in Heat and Mass Transfer, Vol.16, No.1, pp. 1-6, 2021, DOI:10.5098/hmt.16.22

Abstract The recent trend application of the nanofluids is used in some industrial equipment such as tube heat exchanger, double pipe exchanger and shell-tube type heat exchanger. The Triangle tubes may be used in the heat exchanger. Thus, this experimental study reports the convective heat transfer performance of the aluminum oxide-water nanofluids flowing in the triangle channel. In this study, the amount of the volume fraction of the Al₂O₃ used was 0.1 %, 0.2 %, and 0.3 respectively in base-water as the nanofluids and the Reynolds numbers were varied from about 1000 to 7000. The channel was heated by the electric… More >

Kafel Azeez Mohammed^a,*, Ahmed Mustaffa Saleem^b , Zain alabdeen H. Obaid^a

Frontiers in Heat and Mass Transfer, Vol.16, No.1, pp. 1-8, 2021, DOI:10.5098/hmt.16.20

Abstract Numerical investigation is performed for the determination of Nusselt number of ZnO, TiO₂ and SiO₂ nanoparticles dispersed in 60% ethylene glycol and 40% water inside inclined cylinder for adiabatic and isothermal process. The present study was conducted for both the constant heat flux (10,000 W/m²) and constant wall temperature (313.15 K) boundary conditions. At the inlet, the uniform axial velocity and initial temperature (293 K) were assumed. The results show the change of average Nusselt number at Reynolds number (400), Rayleigh number (10⁶) and volume fraction percentage (2%). From results for adiabatic process when increasing the slop up to (45o),… More >