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The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA.

The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance.

The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations.

The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.

This paper aims to identify an inhibitor to protect rebar corrosion in concrete.

The authors use the simple method of polarization and calculate the change in open-circuit potential and corrosion current density.

Sodium molybdate is an efficient inhibitor compared with sodium tungstate for rebar corrosion in concrete.

This paper has limitation of 0.0001 M concentration of inhibitors for 400 days of exposure in 3.5 per cent sodium chloride solution.

The research focused on the concentration of both inhibitors in the range from 0.1 to 0.0001 M, which resulted in greater structural protection from corrosion in adverse conditions, such as coastal areas.

The big challenge in apparel recommendation system research is not the exploration of machine learning technologies in fashion, but to really understand clothes, fashion and people, and know what to learn. The purpose of this paper is to explore an advanced apparel style learning and recommendation system that can recognise deep design-associated features of clothes and learn the connotative meanings conveyed by these features relating to style and the body so that it can make recommendations as a skilled human expert.

This study first proposes a type of new clothes style training data. Second, it designs three intelligent apparel-learning models based on newly proposed training data including ATTRIBUTE, MEANING and the raw image data, and compares the models’ performances in order to identify the best learning model. For deep learning, two models are introduced to train the prediction model, one is a convolutional neural network joint with the baseline classifier support vector machine and the other is with a newly proposed classifier later kernel fusion.

The results show that the most accurate model (with average prediction rate of 88.1 per cent) is the third model that is designed with two steps, one is to predict apparel ATTRIBUTEs through the apparel images, and the other is to further predict apparel MEANINGs based on predicted ATTRIBUTEs. The results indicate that adding the proposed ATTRIBUTE data that captures the deep features of clothes design does improve the model performances (e.g. from 73.5 per cent, Model B to 86 per cent, Model C), and the new concept of apparel recommendation based on style meanings is technically applicable.

The apparel data and the design of three training models are originally introduced in this study. The proposed methodology can evaluate the pros and cons of different clothes feature extraction approaches through either images or design attributes and balance different machine learning technologies between the latest CNN and traditional SVM.

This paper aims to formulate a new metal working fluid (MWF) composition including some eco-friendly emulsifiers, corrosion inhibitor, biocide, and non- edible vegetable oil (castor oil) as the base oil. To achieve this aim, five MWFs with different hydrophilic–lipophilic balance (HLB) value as 10, 9.5, 9, 8.5 and 8 were prepared to identify the optimum HLB value that gives a highly stable oil-in-water emulsion. The performance of castor oil based MWF was evaluated using tool chip tribometer and drill dynamometer. The surface morphology of steel disc and friction pin was performed using scanning electron microscope (SEM) and 3D profilometer. The results revealed that the use of the prepared cutting fluid (E1) caused the cutting force to decrease from 500 N for dry high-speed steel sample to 280N, while the same value for a commercial cutting fluid (COM) was recorded as 340 N at drilling speed and cutting feed force as 1120 rpm and 4 mm/min., respectively.

A castor oil-based metalworking fluid was prepared using nonionic surfactants. The composition of the metalworking fluid was further optimized by adding performance-enhancing additives. The performance of castor oil based MWF was analyzed using Tool chip tribometer and Drill dynamometer. The surface morphology of steel ball and a disc was done using 3D profilometer and SEM.

Studies revealed that castor oil-based MWF having Monoethanolamine (MEA) as corrosion inhibitor was found to be highly stable. The drilling dynamometer and tool chip tribometer studies showed that castor oil-based MWF performance was comparable to that of commercial MWF.

This study aims to explore the performance of the castor oil based metalworking fluid (MWF) using tool chip tribometer and drill dynamometer.

The conventional MWFs are petroleum derives and are unsustainable. Use of non-edible plant-based oils for preparing the MWF will not only be conserved environment but also add value addition to agricultural crops.

The social Implications is aiming to decrease the environmental impact that results from the using of mineral cutting fluids.

The originality of this work is to replace the mineral oil and synthetic oil based cutting fluids with more eco-friendly alternatives one. In addition, the investigation will focus on developing functional additives required for cutting fluids which are environmentally benign.

This paper aims to propose an optimized overview of firefly algorithm (FA) over physical-natural impression of fireflies and its application in mobile robot navigation under the natural intelligence mechanism.

The brightness and luminosity are the decision variables in proposed study. The paper achieves the two major goals of robot navigation; first, the optimum path generation and, second, as an obstacle avoidance by co-in-centric sphere-based geometrical technique. This technique comprises the optimum path decision to objective function and constraints to paths and obstacles as the function of algebraic-geometry co-relation. Co-in-centric sphere is the proposed technique to correlate the constraints.

It is found that the present FA based on concentric sphere is suitable for efficient navigation of mobile robots at the level of optimum significance when compared with other approaches.

The paper introduces a novel approach to implement the FA for unknown and uncertain environment.

Head and neck cancers are multi-factorial diseases that can affect many sides of people's life and are due to a lot of risk factors. According to their characteristics, the treatment can be surgical, use of radiation or chemotherapy. The use of a surgical treatment can lead to surgical infections that are a main theme in medicine. At the University hospital of Naples “Federico II”, two antibiotics were employed to tackle the issue of the infections and they are compared in this paper to find which one implies the lowest length of hospital stay (LOS) and the reduction of infections.

The Six Sigma methodology and its problem-solving strategy DMAIC (define, measure, analyse, improve, control), already employed in the healthcare sector, were used as a tool of a health technology assessment between two drugs. In this paper the DMAIC roadmap is used to compare the Ceftriaxone (administered to a group of 48 patients) and the association of Cefazolin plus Clindamycin (administered to a group of 45 patients).

The results show that the LOS of patients treated with Ceftriaxone is lower than those who were treated with the association of Cefazolin plus Clindamycin, the difference is about 41%. Moreover, a lower number of complications and infections was found in patients who received Ceftriaxone. Finally, a greater number of antibiotic shifts was needed by patients treated with Cefazolin plus Clindamycin.

While the paper enhances clearly the advantages for patients' outcomes regarding the LOS and the number of complications, it did not analyse the costs of the two antibiotics.

Employing the Ceftriaxone would allow the Department of Maxillofacial Surgery to obtain lower LOS and a limited number of complications/infections for recovered patients, consequently reducing the hospitalization costs.

There is a double value in this paper: first of all, the comparison between the two antibiotics gives an answer to one of the main issues in medicine that is the reduction of hospital-acquired infections; secondly, the Six Sigma through its DMAIC cycle can be employed also to compare two biomedical technologies as a tool of health technology assessment studies.

Solar energy applications are limited because of its intermittent and discontinuous availability with respect to time. Hence, solar energy thermal conversion systems need integration with thermal storage units (TSUs) to use solar energy in off sunshine hours. This paper aims to perform thermal analysis of a solar air heater (SAH) integrated with a phase change material (PCM)-based TSU to supply hot air during night period.

An experimental setup with TSU as main component was prepared with SAH at its upward side, food chamber at its downward side as subcomponents. In TSU, paraffin wax was used as thermal energy storage material. Mass flow rate of air considered as an input parameter in the experiment. Two different absorber plates, namely, plane and ribbed absorber plates were used for the experimentation. Each day for a fixed mass flow of air, observations were made during charging and discharging of PCM.

Nusselt number and convection heat transfer coefficients were analytically calculated by considering flow through TSU as external flow over bank of tubes in a rectangular duct. A temperature drop of around 7-8°C during charging of PCM and temperature rise of around 4-5°C during discharging of PCM was observed from the experimental results. The average practical efficiency of TSU with ribbed absorber plate SAH during charging and discharging of PCM was 22 and 6 per cent, respectively, higher than that of TSU with plane absorber plate SAH.

There are no limitations for research on SAH integrated with TSU. Different PCM including paraffin wax, Glauber’s salt, salt hydrates and water are used for thermal storage. Only limitation is lower efficiency of SAH integrated with TSU because of lower heat transfer coefficients with air as working medium. If it can improve heat transfer coefficients of air then heat transfer rates with these units will be higher.

There are no practical limitations for research on SAH integrated with TSU. Sophisticated instrumentation is needed to measure flow rates, temperatures and pressure variations of air.

In poultry farms during night, chicks cannot survive at cold climatic conditions. Hence, hot air should be supplied to poultry farms whenever the atmospheric temperature drops. It is proposed that, in combination with TSUs, heat produced by SAH is stored in day time in the form of either sensible or latent heat and is retrieved to provide hot air in the night times. This will reduce total operating costs in poultry farms.

Conventionally, people are producing hot air by combusting coal in poultry forms. This cost around Rs. 75,000 per month for a batch of 225 to 250 chicks in a poultry form. Hot air could be produced economically during off sunshine hours from SAH integrated with TSU compared to the conventional method of coal burning. Present experimental investigations conducted to fill the literature gap in this area of research and to design a SAH integrated with TSU to produce hot air for poultry forms.

It is an important style classification way to sort out suits according to the button arrangement. However, since the different dressing ways of suit cause the buttons to be easily occluded, the traditional identification methods are difficult to identify the details of suits, and the recognition accuracy is not ideal. The purpose of this paper is to solve the problem of fine-grained classification of suit by button arrangement. Taking men's suits as an example, a method of coordinate position discrimination algorithm combined faster region-based convolutional neural network (R-CNN) algorithm is proposed to achieve accurate batch classification of suit styles under different dressing modes.

The detection algorithm of suit buttons proposed in this paper includes faster R-CNN algorithm and coordinate position discrimination algorithm. Firstly, a small sample base was established, which includes six suit styles in different dressing states. Secondly, buttons and buttonholes in the image were marked, and the image features were extracted by the residual network to identify the object. The anchors regression coordinates in the sample were obtained through convolution, pooling and other operations. Finally, the position coordinate relation of buttons and buttonholes was used to accurately judge and distinguish suit styles under different dressing ways, so as to eliminate the wrong results of direct classification by the network and achieve accurate classification.

The experimental results show that this method could be used to accurately classify suits based on small samples. The recognition accuracy rate reaches 95.42%. It can effectively solve the problem of machine misjudgment of suit style due to the cover of buttons, which provides an effective method for the fine-grained classification of suit style.

A method combining coordinate position discrimination algorithm with convolutional neural network was proposed for the first time to realize the fine-grained classification of suit style. It solves the problem of machine misreading, which is easily caused by buttons occluded in different suits.

The development of robust control algorithms for the position, velocity and trajectory control of unmanned underwater vehicles (UUVs) depends on the accuracy of their mathematical models. Accuracy of the model is determined by precise estimation of the UUV hydrodynamic parameters. The purpose of this study is to determine the hydrodynamic forces and moments acting on an underwater vehicle with complex body geometry and moving at low speeds and to achieve the accurate coefficients associated with them.

A three-dimensional (3D) computer-aided design (CAD) model of UUV is designed with one-to-one dimensions. 3D fluid flow simulations are conducted using computational fluid dynamics (CFD) software programme in the solution of Navier Stokes equations for laminar and turbulent flow analysis. The coefficients depending on the hydrodynamic forces and moments are determined by the external flow analysis using the CFD programme. The Flow Simulation k-ε turbulence model is used for the transition from laminar flow to turbulent flow. Hydrodynamic properties such as lift and drag coefficients and roll and yaw moment coefficients are calculated. The parameters are compared with the coefficient values found by experimental methods.

Although the modular type UUV has a complex body geometry, the comparative results of the experiments and simulations confirm that the defined model parameters are accurate and close to the actual experimental values. In the proposed k-ε method, the percentage error in the estimation of drag and lifting coefficients is decreased to 4.2% and 8.39%, respectively.

The model coefficients determined in this study can be used in high-level control simulations which leads to the development of robust real-time controllers for complex-shaped modular UUVs.

The Lucky Fin UUV with 4 degrees of freedom is a specific design and its CAD model is first extracted. Verification of simulation results by experiments is generally less referenced in studies. However, it provides more precise parameter identification of the model. Proposed study offers a simple and low-cost experimental measurement method for verification of the hydrodynamic parameters. The extracted model and coefficients are worthwhile references for the analysis of modular type UUVs.

The free vibration analysis of cyclic symmetric structures is considered as a Hermitian eigenvalue problem in semi‐complex domain using subspace iteration method is presented. The trial vectors are selected using a modified Ritz vector scheme. A modified convergence criterion which gives true error estimates which is suited for clustered eigenvalue problems is presented. Also the effect of purification of trial vectors on convergence is considered.