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The main aim of this paper is to investigate properties of certain class of logharmonic mappings. Initially, we establish the argument principle of sense-preserving mappings F = h g ¯ + H G ¯ , where h, g, H and G are analytic functions. As applications, we obtain a direct extension of Rouché’s theorem, open mapping theorem and minimal area image of sense-preserving logharmonic mappings. Furthermore, we present an estimate for the modulus of the partial derivative of K-quasiconformal logharmonic mappings, and by using it, we get a Schwarz type lemma of K-quasiconformal logharmonic mappings. Finally, we obtain estimates of h ′ ′ (0) 2 and g ′ ′ (0) 2 for univalent sense-preserving logharmonic mappings f = h g ¯ in the unit disk. [ABSTRACT FROM AUTHOR]

Speech digit recognition research is growing decisively, and a bulk of digit recognition algorithms are used in European and a few Asian languages. Kui is a low-resourced tribal language locally used in several states of India. Despite its significance, there is not much research on Kui's speech. This research aims to present an in-depth analysis of novel Kui digit recognition using predefined machine learning (ML) techniques. For this purpose, we first gathered spoken numbers i.e. from 0 to 9 of eight different speakers containing a total of 200 words. Secondly, we choose the numbers: ଶନୂ (zero), ଏକ (one), ଦୁଇ (two), ତିନି (three), ସାରି (four), ପାସ (five), ସଅ (six), ସାତ (seven), ଆଟ (eight), ନଅ (nine). Meanwhile, we build nine different ML models to recognize Kui digits that take the Mel-frequency cepstral coefficients (MFCCs) method to extract the relevant features for model predictions. Finally, we compared the performance of ML models for both augmented and non-augmented Kui data. The result shows that the SVM+Augmentation method for Kui digit recognition combined obtained the highest accuracy of 83% than other methods. Moreover, the difficulties and potential prospects for Kui digit recognition are also highlighted in this work. [ABSTRACT FROM AUTHOR]

In this paper, we define a new Ma-Minda type class based on binomial distribution series. Our investigation will be focused on the coefficients of the function f belonging to that class. [ABSTRACT FROM AUTHOR]

This article, published in Frontiers in Marine Science, provides a comprehensive analysis of biogeochemical processes in Chilika Lagoon, India. The study examines factors such as primary production, dissolved oxygen concentrations, ammonia and nitrification processes, and phosphorus dynamics. The results indicate that water quality fluctuations in the lagoon are closely linked to algal growth and nutrient regeneration from sediment. The article also discusses the complex relationship between phytoplankton carbon biomass and chlorophyll concentration, the role of zooplankton in the ecosystem, and the importance of measuring dissolved oxygen concentration. The study concludes that the lagoonal ecosystem shows resilience and further investigations are needed. This article is a valuable resource for researchers studying similar ecosystems. [Extracted from the article]

This paper is concerned with the experimental investigation and mechanistic prediction of cutting forces for flat-end milling with tool runout. The effects of the tool geometry, the workpiece material and cutting parameters such as spindle speed, tool engagement and cutting direction are investigated. The mechanistic force model uses the trochoidal flute path to calculate the undeformed chip thickness. Average cutting force and linear regression model are applied for identifying the coefficients of the force model, and tool runout parameters are established from the radii of all flutes at the free end of the cutting tool. A series of milling processes are conducted on AZ31 Magnesium (Mg) alloy and titanium alloy (Ti6Al4V) to analyze the instantaneous cutting force curves, amplitudes of cutting forces and peak forces over a wide range of conventional spindle speeds, namely 600, 1200 and 3000 rev/min. It is found that the values of the cutting force coefficients are higher at lower spindle speed and decrease with an increase in spindle speed, especially when machining Ti6Al4V alloy. For the edge force coefficients, it is observed a slight variation when using cutting tools with different helix angles. Besides, the cutting force amplitudes strongly depend upon the workpiece material. The helix angle has a significant influence on the transverse force amplitude at the spindle speed of 600 rev/min. The cutting forces obtained mechanistically are also substantiated by comparison with measurements. [ABSTRACT FROM AUTHOR]

The current trends or procedures followed in the customer relation management system (CRM) are based on reviews, mails, and other textual data, gathered in the form of feedback from the customers. Sentiment analysis algorithms are deployed in order to gain polarity results, which can be used to improve customer services. But with evolving technologies, lately reviews or feedbacks are being dominated by audio data. As per literature, the audio contents are being translated to text and sentiments are analyzed using natural processing language techniques. However, these approaches can be time consuming. The proposed work focuses on analyzing the sentiments on the audio data itself without any textual conversion. The basic sentiment analysis polarities are mostly termed as positive, negative, and natural. But the focus is to make use of basic emotions as the base of deciding the polarity. The proposed model uses deep neural network and features such as Mel frequency cepstral coefficients (MFCC), Chroma and Mel Spectrogram on audio-based reviews. [ABSTRACT FROM AUTHOR]

Polynomial based secret sharing is the art of protecting information and a tool used in areas where a secret has to be distributed among multiple parties. In this method, secret is encrypted into noisy shares and transferred to participants in the group. Decoding of secret is possible only when sufficient number of authorized members in the group, stack their respective shares. In this article, polynomial based secret sharing for audio is proposed that computes a checksum to identify the dishonest participant and also the audio shares generated are of smaller dimension. To achieve this, a polynomial function is defined by considering amplitude values and random values as coefficients. Inclusion of random value as the coefficient of higher degree term in the polynomial makes the audio shares noisy and does not provide any information about the secret. This reduces the overhead of performing preprocessing on original audio before shares are generated. In addition, our proposed method can be used for multi secret sharing. Proposed scheme also facilitates identification of dishonest participant before reconstruction of secret through a trusted entity called combiner. [ABSTRACT FROM AUTHOR]

The efficacy of electronic government (E-Government) initiatives relies significantly on requirements engineering (RE). Every government wants sustainable solutions in the implementation of E-Government projects. The current research has adopted a mix of research methods. After conducting a comprehensive systematic literature review (SLR), the author conducted a case study to evaluate the proposed model. This research conducts an SLR of the contemporary literature on the success and failure factors of E-Government projects. Additionally, there is an association between the failure factors and the utilization of RE practices. A comprehensive search of electronic databases yielded a total of 71 pertinent articles. After meticulous screening and quality assessment, the data were extracted for analysis. A total of 62 papers were eventually selected. The SLR addressed the distinct hurdles encountered by government bodies. The findings indicated a positive relationship between the utilization of RE practices and the attainment of project success. Various aspects, such as project management practices, stakeholder engagement, and effective communication, were identified as factors that can reduce failures in E-Government projects. The deficiencies observed in E-Government initiatives were linked to inadequacies in implementing RE practices. The other issues identified were insufficient requirement elicitation, limited stakeholder involvement, and inadequate validation and verification of requirements. This study also presented a conceptual framework illustrating the difficulties in E-Government and the practices of RE. Statistical data analysis techniques were employed to examine this conceptual framework. This study suggests that managers examine and evaluate their E-Government project failure reasons and factors on a periodic basis to sustain and continuously enhance E-Government project success. [ABSTRACT FROM AUTHOR]

This paper presents a novel computational process used for determining matching coefficients for optical spectra either in real time or from a database. This simple algorithmic method is capable of outputting a set of coefficients relating to comparative matching datapoints and to a weighted similarity ratio between spectra whilst still maintaining high computational efficiency due to the minimization of floating-point calculations. The process works as effectively on signal data during real time processing or on images of spectra which may be stored in a database. A subset of the algorithm has already been used very effectively in an embedded mobile field device to determine the presence or absence of special security fluorescent emission peaks present in printing inks used in anti-counterfeiting labels. The process involves the division of test spectrum(s) signal/image into a grid of user definable blocks while applying the same grid to the test image or images. Each block is then checked to see if the signal/image passes through the block, if the signal/image passes through a block then the value of this grid block is set to 1 in a grid array. The same check is then applied to the reference signal/image(s).While it is possible to process a signal comparison without the need for data storage, useful for some embedded processes, it may be preferable to store the resultant data in simple data arrays. These arrays can then undergo simple arithmetical processing to quickly calculate a set of values representing the number of matching data points, the variation in non-matching data points and a divergence value. This check can be carried out between the test image or images and a larger number of reference images simultaneously by use of additional counters. In addition, when used with large databases of spectra this novel technique may be used to rapidly reduce a large test set to a more relevant subset which can be further analyzed using more conventional methods or by visual inspection. This grid square analysis method works as efficiently on images as it can for signal data and it is believed by the authors that the method will have applications in other image processing applications where fast and efficient comparative analysis between images is required.

Cyclotomic polynomials play an imporant role in discrete mathematics. Recently, inverse cyclotomic polynomials have been defined and investigated. In this paper, we present some recent advances related to the coefficients of inverse cyclotomic polynomials, including a practical recursive formula for their calculation and numerical simulations. [ABSTRACT FROM AUTHOR]

This research investigated an alternate method for establishing the complex coefficients used in an electric vehicle's mathematical energy consumption model. While other methods for creating electric vehicle energy models exist, it would be beneficial to have a rapid and inexpensive technique that remains accurate. Producing a mathematical energy model for such a vehicle has the challenge of determining its aerodynamic drag and rolling resistance coefficients. Currently and most often, expensive and tedious (time-consuming) methods are used to find these coefficients. Computational fluid dynamics (CFD), wind tunnel testing, and extensive mathematics make this objective challenging. For this work, a solar-powered electric vehicle provided the source data to derive its coefficients cost-effectively and efficiently. Data were collected during a road test of the solar electric vehicle from South Africa to Namibia stretching over 2000 km, in which all required energy variables were recorded. The collected data were used in an optimisation routine to establish the two coefficients by minimising the actual and modelled energy consumption error and controlling the driving speed. The outcome of the optimisation routine produced accurate coefficients with a final error value of less than 5% when applied to a validation data set not used during optimisation. With minor modifications, this method may be integrated into any electric vehicle computer system to autonomously identify its two hard-to-find coefficients while driving, which can be used to provide an accurate and realistic driving range estimation to the driver. [ABSTRACT FROM AUTHOR]

Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanoparticles in the base fluid of ethylene glycol and water (60:40). Using response surface methodology (RSM) based on central composite design (CCD) and mini tab 20 standard statistical software, the impact of temperature, volume concentration, and type of nanofluid is used to construct an empirical mathematical formula. Analysis of variance (ANOVA) is applied to determine that the developed empirical mathematical analysis is relevant. For the purpose of developing the equations, 32 experiments are conducted for second-order polynomial to the specified outputs such as thermal conductivity and viscosity. Predicted estimates and the experimental data are found to be in reasonable arrangement. In additional words, the models could expect more than 85% of thermal conductivity and viscosity fluctuations of the nanofluid, indicating that the model is accurate. Optimal thermal conductivity and viscosity values are 0.4962 W/m-K and 2.6191 cP, respectively, from the results of the optimization plot. The critical parameters are 50 °C, 0.0254%, and the category factorial is GNP/CNC, and the relevant parameters are volume concentration, temperature, and kind of nanofluid. From the results plot, the composite is 0.8371. The validation results of the model during testing indicate the capability of predicting the optimal experimental conditions. [ABSTRACT FROM AUTHOR]

The modeling of tilting-pad journal and thrust bearings presents a level of complexity beyond that of bearings with a fixed-arc geometry, particularly with regard to their dynamic influences. With tilting-pad bearings, the theory surrounding their fluid film must be complemented with the representative modeling of the pad dynamics. What has been recognized in recent decades is the significance of the pad support, in particular the flexibility of the pivot region of the pad. The typical model for including the stiffness of the pivot is based on the Hertzian contact theory. Some researchers have noted that the Hertzian theory does not permit sufficient flexibility in the pivot region. It has been suggested that the contact mechanics at the pivot would be better represented as a pairing of rough surfaces. The modeling used here is based on a statistical asperity micro-contact theory for rough surface line contact that has been extended to include contact stiffness. This model has been applied to the determination of the effective dynamic properties of tilting-pad bearings. The results show that pivot stiffness can be as low as one third of the stiffness determined by the Hertzian theory. A comparison to published experimental results confirms the significance of the rough surface modeling, particularly for the line contacts associated with rocker-back tilting pads. [ABSTRACT FROM AUTHOR]

In this papers, we investigate the Hankel determinant and Toeplitz determinant for the class Bazilevič Function B1(a, d) related to the Bernoulli Lemniscate function on the unit disk D = {z: |z| < 1} and obtain the upper bounds of the determinant H2(1), H2(2), T2(1), and investigate H2(1) using coefficients invers function. We used lemma from Charateodory-Toeplitz and Libera about sharp inequalities for functions with positive real part. [ABSTRACT FROM AUTHOR]

Consider the random walk G n : = g n ... g 1 , n ⩾ 1 , where (g n) n ⩾ 1 is a sequence of independent and identically distributed random elements with law μ on the general linear group GL (V) with V = R d . Under suitable conditions on μ , we establish Cramér type moderate deviation expansions and local limit theorems with moderate deviations for the coefficients 〈 f , G n v 〉 , where v ∈ V and f ∈ V ∗ . Our approach is based on the Hölder regularity of the invariant measure of the Markov chain G n ⋅ x = R G n v on the projective space of V with the starting point x = R v , under the changed measure. [ABSTRACT FROM AUTHOR]

A radiator is used to remove a portion of the heat generated by a vehicle engine. It is challenging to efficiently maintain the heat transfer in an automotive cooling system even though both internal and external systems need enough time to keep pace with catching up with evolving engine technology advancements. The effectiveness of a unique hybrid's heat transfer nanofluid was investigated in this study. The hybrid nanofluid was mainly composed of graphene nanoplatelets (GnP), and cellulose nanocrystals (CNC) nanoparticles suspended in a 40:60 ratio of distilled water and ethylene glycol. A counterflow radiator equipped with a test rig setup was used to evaluate the hybrid nano fluid's thermal performance. According to the findings, the proposed GNP/CNC hybrid nanofluid performs better in relation to improving the efficiency of heat transfer of a vehicle radiator. The suggested hybrid nanofluid enhanced convective heat transfer coefficient by 51.91%, overall heat transfer coefficient by 46.72%, and pressure drop by 34.06% with respect to distilled water base fluid. Additionally, the radiator could reach a better CHTC with 0.01% hybrid nanofluid in the optimized radiator tube by the size reduction assessment using computational fluid analysis. In addition to downsizing the radiator tube and increasing cooling capacity over typical coolants, the radiator takes up less space and helps to lower the weight of a vehicle engine. As a result, the suggested unique hybrid graphene nanoplatelets/cellulose nanocrystal-based nanofluids perform better in heat transfer enhancement in automobiles. [ABSTRACT FROM AUTHOR]

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We prove the sharp inequality |H3,1(f)| ≤ 1/16 for the third Hankel determinant H3,1(f) for convex functions of order -1/2 i.e., functions f analytic in z ∈ D:= {z ∈ C: |z| < 1} with an:= f (n)(0)/n!, n ∈ N, a1:= 1, such that Re {1+ zf"(z)/f'(z)} > -1/2, z ∈ D, thus proving a recent conjecture. [ABSTRACT FROM AUTHOR]

Continuous attractor refers to a kind of low-dimensional manifold, which is embedded in high-dimensional state space. The line attractor is one-dimensional continuous attractor, while the two-dimensional continuous attractor is called plane attractor. The weight matrix and the external input play the key role for the expression of the continuous attractor. In this paper, some conditions for the parameter selection to achieve line attractor and plane attractor are given. we see that even a pretty small perturbation of the parameter may heavily affect the type and shape of the continuous attractor. The parameter selection scheme is crucial for designing the neural network model. [ABSTRACT FROM AUTHOR]

Automatic speech recognition system is one of the essential ways of interaction with machines. Interests in speech based intelligent systems have grown in the past few decades. Therefore, there is a need to develop more efficient methods for human speech recognition to ensure the reliability of communication between individuals and machines. This paper is concerned with Arabic phoneme recognition of electrolarynx device. Electrolarynx is a device used by cancer patients having vocal laryngeal cords removed. Speech recognition here is considered to find the preferred machine learning model that can classify phonemes produced by electrolarynx device. The phonemes recognition employs different machine learning schemes, including convolutional neural network, recurrent neural network, artificial neural network (ANN), random forest, extreme gradient boosting (XGBoost), and long short-term memory. Modern standard Arabic is utilized for testing and training phases of the recognition system. The dataset covers both an ordinary speech and electrolarynx device speech recorded by the same person. Mel frequency cepstral coefficients are considered as speech features. The results show that the ANN machine learning method outperformed other methods with an accuracy rate of 75%, a precision value of 77%, and a phoneme error rate (PER) of 21.85%. [ABSTRACT FROM AUTHOR]

Drag crisis has been described as a drop in the drag coefficient (Cd). This procedure was lately assessed in able-bodied cyclists in time trial position by computational fluid dynamics (CFD). Therefore, the aim of this study was to assess the phenomenon of the drag crisis by computer fluid dynamics in transradial and transtibial amputee cyclists in the upright position. A male elite-level cyclist was recruited for this research. The subject was scanned (3D geometry with a 3D Scan) with his competition bicycle, helmet, suit, and shoes. Consequently, transradial and transtibial 3D models were created editing the able-bodied 3D model. To perform the CFD analyses, a domain measuring 7 x 2.5 x 2.5 m (length, width and height, respectively) was created around each bicycle-cyclist model. The domains were meshed with more than 42 million elements. Numerical simulations by CFD were performed in fluent numerical for speeds between 1 m/s and 13 m/s, with increments of 1 m/s. The total Cd decreased with speed. It ranged from 0.84 to 0.55 in the able-bodied, 0.86 to 0.64 in the transradial and 0.90 to 0.61 in the transtibial. The drag crisis phenomenon was observed between 1m/s and 4m/s in all models. [ABSTRACT FROM AUTHOR]

Numerous studies consider combinatorial optimization problems and their solution methods, since a large number of practical problems are described by means of combinatorial optimization models. Among these problems, the most prominent ones are function optimization problems on combinatorial configurations. Many of the studies mentioned above propose approaches and describe methods to solve combinatorial optimization problems for linear and fractionally linear functions on combinatorial sets such as permutations and arrangements. This work describes new approaches and methods to solve some maximization problems for linear, fractionally linear and quadratic functions on permutation set. Algorithms for solving these problems are given. For linear function, we provide a considerably easy method to find the permutation on which the function attains its maximum value. We describe the general algorithm to find fractionally linear function maximum. We consider the cases in which variables of numerator and denominator do not intersect, and when the numerator function and the denominator function have one common variable. We also describe the case in which the numerator function and the denominator function in total have incomplete variable list, i.e. when the total quantity of variables is less than the quantity of numbers in the permutation set. As for solving the problem of finding quadratic function maximum on permutation set, it turned out that there is no universal algorithm to solve this problem for any quadratic function. In this paper, we describe a method of finding maximum on permutation set for quadratic function consisting of two items. We provide examples of solving the considered optimization problems.

Drag crisis has been described as a drop in the drag coefficient (Cd). This procedure was lately assessed in able-bodied cyclists in time trial position by computational fluid dynamics (CFD). Therefore, the aim of this study was to assess the phenomenon of the drag crisis by computer fluid dynamics in transradial and transtibial amputee cyclists in the upright position. A male elite-level cyclist was recruited for this research. The subject was scanned (3D geometry with a 3D Scan) with his competition bicycle, helmet, suit, and shoes. Consequently, transradial and transtibial 3D models were created editing the able-bodied 3D model. To perform the CFD analyses, a domain measuring 7 x 2.5 x 2.5 m (length, width and height, respectively) was created around each bicycle-cyclist model. The domains were meshed with more than 42 million elements. Numerical simulations by CFD were performed in fluent numerical for speeds between 1 m/s and 13 m/s, with increments of 1 m/s. The total Cd decreased with speed. It ranged from 0.84 to 0.55 in the able-bodied, 0.86 to 0.64 in the transradial and 0.90 to 0.61 in the transtibial. The drag crisis phenomenon was observed between 1m/s and 4m/s in all models.

Nonuniform ionospheric delay is a well-known cause of degradations in radio wave propagations such as in satellite communication and positioning. In general, the ionospheric delay can be estimated using the Global Navigation Satellite System (GNSS) data from dual or multiple-frequency receivers; however, satellite differential code biases (DCBs) must be downloaded via network connection. For positioning based on standalone single-frequency receivers, the Klobuchar model, a well-known model in the GPS positioning system, is used to estimate the ionospheric delay based on solar activity, season, or region by using the eight coefficients in the broadcast navigation message. Although this model can reduce positioning errors by about 50 percent, the low-latitude disturbances such as the equatorial plasma bubble (EPB) phenomenon, significantly diminishes the accuracy of modeled delay estimation. In this work, we propose an ionospheric delay estimation technique based on observed single-frequency GPS data without requiring network-based corrections for DCB. The ionospheric delays estimated by the proposed method are compared with those from the GPS dual-frequency observation, the broadcast/network models in 2014 (high solar activity) and 2020 (low solar activity). According to the results, the proposed ionospheric delay estimation can correct the ionosphere errors better than the well-known Klobuchar model, by about 9.98 percent and 6.77 percent in 2014 and 2020, respectively. The proposed model increases the ionospheric error correction efficiency in vertical positioning by up to 81 percent in 2014 and 79 percent in 2020.

Cyclotomic polynomials play an imporant role in discrete mathematics. Recently, inverse cyclotomic polynomials have been defined and investigated. In this paper, we present some recent advances related to the coefficients of inverse cyclotomic polynomials, including a practical recursive formula for their calculation and numerical simulations.

In this paper, we prove the sharp inequality | H 3 , 1 ⁢ (f) | ≤ 4 / 9 for starlike functions 푓, where H 3 , 1 ⁢ (f) is the third Hankel determinant, thus solving a long-standing problem. [ABSTRACT FROM AUTHOR]

Fault diagnosis has a great significance in preventing serious failures of rotating machinery and avoiding huge economic losses. The performance of the existing fault diagnosis approaches might be affected by two factors, i.e., the quality of fault features extracted from monitoring signals and the capability of fault diagnosis model. This paper proposes a new fault diagnosis method combined mel-frequency cepstral coefficients (MFCC) with a designed parallel multi-fusion convolutional neural network (MFCNN) Specifically, a MFCC-based feature extraction method is defined to reduce the noise components in monitoring signal of rotating machinery and extract more useful low-frequency fault information for downstream task. Furthermore, a novel MFCNN is designed to enrich the high-level features after each convolution operation by using multiple activation functions, so as to improve the quality of the obtained fault features. Meanwhile, a new parallel MFCNN is constructed by using a defined structural ensemble operation to improve its diagnostic performance in different noise environments. Two typical bearing and gearbox failure datasets are applied to evaluate the performance of the proposed fault diagnosis method. The experimental results indicate that the proposed parallel MFCNN has the better diagnostic performance than other methods. • A MFCC-based feature extraction method is designed to obtain more useful fault features. • A novel MFCNN is created to enhance its feature extraction capability without increasing network parameters. • A parallel MFCNN is proposed to improve the diagnostic performance under different noise environments. [ABSTRACT FROM AUTHOR]

The purpose of the study is to perform appropriate calculations of the values of the total slip coefficients alternately on the sides of a vehicle, depending on the angles of rotation of its axles, using the single slip coefficients of its individual wheels directly when turning. The basis of the methodological approach in this study is a combination of system analysis of the principles of calculating the slip coefficients of a mechanical wheeled vehicle with an analytical investigation of problematic aspects of developing a model for calculating the slip coefficients of a vehicle with two steering axles. The results obtained indicate the presence of a persistent relationship between the slipping coefficients of a mechanical wheeled vehicle and the rotation angles of its two steering axles, including a number of other parameters that are important from the standpoint of traffic safety. [ABSTRACT FROM AUTHOR]

In this article, we prove existence of weak solutions of a general class of diffusive shallow medium type equations. We truncate the coefficients from above and below. Then we prove existence to the problems associated with the truncated vector fields. At last, we show that the approximating solutions converge to the solution of the initial value problem. [ABSTRACT FROM AUTHOR]

This research investigated an alternate method for establishing the complex coefficients used in an electric vehicle’s mathematical energy consumption model. While other methods for creating electric vehicle energy models exist, it would be beneficial to have a rapid and inexpensive technique that remains accurate. Producing a mathematical energy model for such a vehicle has the challenge of determining its aerodynamic drag and rolling resistance coefficients. Currently and most often, expensive and tedious (time-consuming) methods are used to find these coefficients. Computational fluid dynamics (CFD), wind tunnel testing, and extensive mathematics make this objective challenging. For this work, a solar-powered electric vehicle provided the source data to derive its coefficients cost-effectively and efficiently. Data were collected during a road test of the solar electric vehicle from South Africa to Namibia stretching over 2000 km, in which all required energy variables were recorded. The collected data were used in an optimisation routine to establish the two coefficients by minimising the actual and modelled energy consumption error and controlling the driving speed. The outcome of the optimisation routine produced accurate coefficients with a final error value of less than 5% when applied to a validation data set not used during optimisation. With minor modifications, this method may be integrated into any electric vehicle computer system to autonomously identify its two hard-to-find coefficients while driving, which can be used to provide an accurate and realistic driving range estimation to the driver.

Response surface methodology (RSM) is used in this study to optimize the thermal characteristics of single graphene nanoplatelets and hybrid nanofluids utilizing the miscellaneous design model. The nanofluids comprise graphene nanoplatelets and graphene nanoplatelets/cellulose nanocrystal nanoparticles in the base fluid of ethylene glycol and water (60:40). Using response surface methodology (RSM) based on central composite design (CCD) and mini tab 20 standard statistical software, the impact of temperature, volume concentration, and type of nanofluid is used to construct an empirical mathematical formula. Analysis of variance (ANOVA) is applied to determine that the developed empirical mathematical analysis is relevant. For the purpose of developing the equations, 32 experiments are conducted for second-order polynomial to the specified outputs such as thermal conductivity and viscosity. Predicted estimates and the experimental data are found to be in reasonable arrangement. In additional words, the models could expect more than 85% of thermal conductivity and viscosity fluctuations of the nanofluid, indicating that the model is accurate. Optimal thermal conductivity and viscosity values are 0.4962 W/m-K and 2.6191 cP, respectively, from the results of the optimization plot. The critical parameters are 50 °C, 0.0254%, and the category factorial is GNP/CNC, and the relevant parameters are volume concentration, temperature, and kind of nanofluid. From the results plot, the composite is 0.8371. The validation results of the model during testing indicate the capability of predicting the optimal experimental conditions.

The modeling of tilting-pad journal and thrust bearings presents a level of complexity beyond that of bearings with a fixed-arc geometry, particularly with regard to their dynamic influences. With tilting-pad bearings, the theory surrounding their fluid film must be complemented with the representative modeling of the pad dynamics. What has been recognized in recent decades is the significance of the pad support, in particular the flexibility of the pivot region of the pad. The typical model for including the stiffness of the pivot is based on the Hertzian contact theory. Some researchers have noted that the Hertzian theory does not permit sufficient flexibility in the pivot region. It has been suggested that the contact mechanics at the pivot would be better represented as a pairing of rough surfaces. The modeling used here is based on a statistical asperity micro-contact theory for rough surface line contact that has been extended to include contact stiffness. This model has been applied to the determination of the effective dynamic properties of tilting-pad bearings. The results show that pivot stiffness can be as low as one third of the stiffness determined by the Hertzian theory. A comparison to published experimental results confirms the significance of the rough surface modeling, particularly for the line contacts associated with rocker-back tilting pads.

Population and industrial growth in Mexico's Bajío region demand greater electricity consumption. The production of electricity from fuel oil has severe implications on climate change and people's health due to SO2 emissions. This study describes the simulation of eight different scenarios for SO2 pollutant dispersion. It takes into account distance, geoenvironmental parameters, wind, terrain roughness, and Pasquill–Gifford–Turner atmospheric stability and categories of dispersion based on technical information about SO2 concentration from stacks and from one of the atmospheric monitoring stations in Salamanca city. Its transverse character, its usefulness for modeling, and epidemiological, meteorological, and fluid dynamics studies, as suggested by the models approved by the Environmental Protection Agency (EPA), show a maximum average concentration of 399 µg/m3, at an average distance of 1800 m. The best result comparison in the scenarios was scenery 8. Maximum nocturnal dispersion was shown at a wind speed of 8.4 m/s, and an SO2 concentration of 280 µg/m3 for stack 4, an atypical situation due to the geography of the city. From the validation process, a relative error of 14.7 % was obtained, which indicates the reliability of the applied Gaussian model. Regarding the mathematical solution of the model, this represents a reliable and low-cost tool that can help improve air quality management, the location or relocation of atmospheric monitoring stations, and migration from the use of fossil fuels to environmentally friendly fuels. [ABSTRACT FROM AUTHOR]

An investigation into the prediction method for internal solitary waves (ISWs) loads on the columns and caissons of the semi-submersible platform found on three kinds of internal solitary wave theories and the modified Morison Equation is described. The characteristics of loads exerted on the semi-submersible platform model caused by the ISWs have been observed experimentally, and the inertial and drag coefficients in Morison Equation are determined by analyzing the forces of experiments. From the results, it is of interest to find that Reynolds number, KC number and layer thickness ratio have a considerable influence on the coefficients. The direction of incoming waves, however, is almost devoid of effects on the coefficients. The drag coefficient of columns varies as an exponential function of Reynolds number, and inertia coefficient of columns is a power function related to KC number. Meanwhile, the drag coefficient of caissons is approximately constant in terms of regression analysis of experimental data. The results from different experimental conditions reveal that the inertia coefficient of caissons appears to be exponential correlated with upper layer depths. [ABSTRACT FROM AUTHOR]

Birds are excellent environmental indicators and may indicate sustainability of the ecosystem; birds may be used to provide provisioning, regulating, and supporting services. Therefore, birdlife conservation-related researches always receive centre stage. Due to the airborne nature of birds and the dense nature of the tropical forest, bird identifications through audio may be a better solution than visual identification. The goal of this study is to find the most appropriate cepstral features that can be used to classify bird sounds more accurately. Fifteen (15) endemic Bornean bird sounds have been selected and segmented using an automated energy-based algorithm. Three (3) types of cepstral features are extracted; linear prediction cepstrum coefficients (LPCC), mel frequency cepstral coefficients (MFCC), gammatone frequency cepstral coefficients (GTCC), and used separately for classification purposes using support vector machine (SVM). Through comparison between their prediction results, it has been demonstrated that model utilising GTCC features, with 93.3% accuracy, outperforms models utilising MFCC and LPCC features. This demonstrates the robustness of GTCC for bird sounds classification. The result is significant for the advancement of bird sound classification research, which has been shown to have many applications such as in eco-tourism and wildlife management. [ABSTRACT FROM AUTHOR]

A radiator is used to remove a portion of the heat generated by a vehicle engine. It is challenging to efficiently maintain the heat transfer in an automotive cooling system even though both internal and external systems need enough time to keep pace with catching up with evolving engine technology advancements. The effectiveness of a unique hybrid’s heat transfer nanofluid was investigated in this study. The hybrid nanofluid was mainly composed of graphene nanoplatelets (GnP), and cellulose nanocrystals (CNC) nanoparticles suspended in a 40:60 ratio of distilled water and ethylene glycol. A counterflow radiator equipped with a test rig setup was used to evaluate the hybrid nano fluid’s thermal performance. According to the findings, the proposed GNP/CNC hybrid nanofluid performs better in relation to improving the efficiency of heat transfer of a vehicle radiator. The suggested hybrid nanofluid enhanced convective heat transfer coefficient by 51.91%, overall heat transfer coefficient by 46.72%, and pressure drop by 34.06% with respect to distilled water base fluid. Additionally, the radiator could reach a better CHTC with 0.01% hybrid nanofluid in the optimized radiator tube by the size reduction assessment using computational fluid analysis. In addition to downsizing the radiator tube and increasing cooling capacity over typical coolants, the radiator takes up less space and helps to lower the weight of a vehicle engine. As a result, the suggested unique hybrid graphene nanoplatelets/cellulose nanocrystal-based nanofluids perform better in heat transfer enhancement in automobiles.

Let f be analytic in D = { z ∈ C : | z | < 1 } , and be given by f (z) = z + ∑ n = 2 ∞ a n z n . We give sharp bounds for the second Hankel determinant, some Toeplitz, and some Hermitian-Toeplitz determinants of functions in the class of Ozaki close-to-convex functions, together with a sharp bound for the Zalcman functional J 2 , 3 (f). [ABSTRACT FROM AUTHOR]