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Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks.

In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle.

To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission.

The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.

The user interest in content searching in the web will be changed over by time.

The system is in need to find the content of user over the temporal aspects.

So, predicting the user interest over the time by analyzing the fluctuations of their search keyword is important.

So, predicting the user interest over the time by analyzing the fluctuations of their search keyword is important.

In this work, fuzzy neural network techniques are used to predict the user interest fluctuation in different times in different scenarios.

In this proposed work, both the long-term and short-term interest are evaluated using the specialized user interface designed to retrieve the user interest based on the user searching activities.

This work also categorizes the future needs of users using this proposed system.

Inclusion of mobile nodes (MNs) in Internet of Things (IoT) further increases the challenges such as frequent network disconnection and intermittent connectivity because of high mobility rate of nodes. This paper aims to propose a proactive mobility and congestion aware route prediction mechanism (PMCAR) to find the congestion free route from leaf to destination oriented directed acyclic graph root (DODAG-ROOT) which considers number of MNs connected to a static node. This paper compares the proposed technique (PMCAR) with RPL (OF0) which considers the HOP-COUNT to determine the path from leaf to DODAG-ROOT. The authors performed a simulation with the proposed technique in MATLAB to present the benefits in terms of packet loss and energy consumption.

In this pandemic situation, mobile and IoT play major role in predicting and preventing the CoronaVirus Disease of 2019 (COVID-19). Huge amount of computations is happening with the data generated in this pandemic with the help of mobile devices. To route the data to remote locations through the network, it is necessary to have proper routing mechanism without congestion. In this paper, PMCAR mechanism is introduced to achieve the same. Internet of mobile Things (IoMT) is an extension of IoT that consists of static embedded devices and sensors. IoMT includes MNs which sense data and transfer it to the DODAG-ROOT. The nodes in the IoMT are characterised by low power, low memory, low computing power and low bandwidth support. Several challenges are encountered by routing protocols defined for IPV6 over low power wireless personal area networks to ensure reduced packet loss, less delay, less energy consumption and guaranteed quality of service.

The results obtained shows a significant improvement compared to the existing approach such as RPL (OF0). The proposed route prediction mechanism can be applied largely to medical applications which are delay sensitive, particularly in pandemic situations where the number of patients involved and the data gathered from them flows towards a central root for analysis. Support of data transmission from the patients to the doctors without much delay and packet loss will make the response or decisions available more quickly which is a vital part of medical applications.

The computational technologies in this COVID-19 pandemic situation needs timely data for computation without delay. IoMT is enabled with various devices such as mobile, sensors and wearable devices. These devices are dedicated for collecting the data from the patients or any objects from different geographical location based on the predetermined time intervals. Timely delivery of data is essential for accurate computation. So, it is necessary to have a routing mechanism without delay and congestion to handle this pandemic situation. The proposed PMCAR mechanism ensures the reliable delivery of data for immediate computation which can be used to make decisions in preventing and prediction.

Multimedia applications such as digital audio and video have stringent quality of service (QoS) requirement in mobile ad hoc network. To support wide range of QoS, complex routing protocols with multiple QoS constraints are necessary. In QoS routing, the basic problem is to find a path that satisfies multiple QoS constraints. Moreover, mobility, congestion and packet loss in dynamic topology of network also leads to QoS performance degradation of protocol.

In this paper, the authors proposed a multi-path selection scheme for QoS aware routing in mobile ad hoc network based on fractional cuckoo search algorithm (FCS-MQARP). Here, multiple QoS constraints energy, link life time, distance and delay are considered for path selection.

The experimentation of proposed FCS-MQARP is performed over existing QoS aware routing protocols AOMDV, MMQARP, CS-MQARP using measures such as normalized delay, energy and throughput. The extensive simulation study of the proposed FCS-based multipath selection shows that the proposed QoS aware routing protocol performs better than the existing routing protocol with maximal energy of 99.1501 and minimal delay of 0.0554.

This paper presents a hybrid optimization algorithm called the FCS algorithm for the multi-path selection. Also, a new fitness function is developed by considering the QoS constraints such as energy, link life time, distance and delay.

The purpose of this paper is to fabricate the scaffolds with different pore architectures using additive manufacturing and analyze its mechanical and biological properties for bone tissue engineering applications.

The polylactic acid (PLA)/composite filament were fabricated through single screw extrusion and scaffolds were printed with four different pore architectures, i.e. circle, square, triangle and parallelogram with fused deposition modelling. Afterwards, scaffolds were coated with hydroxyapatite (HA) using dip coating technique. Various physical and thermo-mechanical tests have been conducted to confirm the feasibility. Furthermore, the biological tests were conducted with MG63 fibroblast cell lines to investigate the biocompatibility of the developed scaffolds.

The scaffolds were successfully printed with different pore architectures. The pore size of the scaffolds was found to be nearly 1,500 µm, and porosity varied between 53% and 63%. The fabricated circular pore architecture resulted in highest average compression strength of 13.7 MPa and modulus of 525 MPa. The characterizations showed the fidelity of the work. After seven days of cell culture, it was observed that the developed composites were non-toxic and supported cellular activities. The coating of HA made the scaffolds bioactive, showing higher wettability, degradation and high cellular responses.

The research attempts highlight the development of novel biodegradable and biocompatible polymer (PLA)/bioactive ceramic (Al₂O₃) composite for additive manufacturing with application in the tissue engineering field.

This paper aims to study the various developments taking place in the field of gas sensors made from polyaniline (PANI) nanocomposites, which leads to the development of high-performance electrical and gas sensing materials operating at room temperature.

PANI/ferrite nanocomposites exhibit good electrical properties with lower dielectric losses. There are numerous reports on PANI and ferrite nanomaterial-based gas sensors which have good sensing response, feasible to operate at room temperature, requires less power and cost-effective.

This paper provides an overview of electrical and gas sensing properties of PANI/ferrite nanocomposites having improved selectivity, long-term stability and other sensing performance of sensors at room temperature.

The main purpose of this review paper is to focus on PANI/ferrite nanocomposite-based gas sensors operating at room temperature.

The purpose of this study is to explore the potential of Cordyline Australis fibers as an alternate raw material for textile.

The water retting method was used to extract the fiber. Cordyline Australis fibers were characterized in terms of the morphology of fibers (fiber cross-sectional and longitudinal), fiber chemical functional groups, tensile strength and elongation, fineness, fiber length, moisture regain and friction coefficient.

Cordyline Australis fiber strands consist of several individual fibers. At the longitudinal section, the fiber cells appeared as long cylindrical tubes with a rough surface. The cross-section of the Cordyline Australis fibers was irregular but some were oval. The key components in the fibers were cellulose, hemicellulose and lignin. The tensile strength of the fiber per bundle was 2.5 gf/den. The elongation of fibers was 13.15%. The fineness of fiber was 8.35 Tex. The average length of the fibers was 54.72 cm. Moisture Regain for fiber was 8.59%. The friction coefficient of fibers was 0.16. The properties of the fiber showed that the Cordyline Australis fiber has the potential to be produced into yarn.

To the best of the author's knowledge, there is no scientific article focused on the Cordyline Australis fibers. Natural fibers from the leaves of the Cordyline Australis plant could be used as an alternate material for textile.

This study aims to prevent mild steel (MS) against corrosion in 0.5 M HCl solution, 2-amino-4-methoxy-6-methyl-1,3,5-triazine was used. The effectiveness of the compound as a corrosion inhibitor was studied via electrochemical, surface and theoretical calculation techniques.

For concentrations ranging from 0.5 to 10.0 mM, almost similar polarization resistances were obtained from electrochemical impedance spectroscopy (EIS) and linear polarization resistance tests. It also investigated inhibitive activity of 2-amino-4-methoxy-6-methyl-1,3,5-triazine on the steel surface using scanning electron and atomic force microscope instruments. Langmuir adsorption is the best matched isotherm for the adsorption of the inhibitor to the steel surface.

EIS method was used to determine inhibition efficiency, which was determined to be 95.7% for 10.0 mM inhibitor containing acid solution. Density functional theory’s predictions for quantum chemistry agreed well with the other experimental results.

The methods used in this study are effective and applicable; the used organic inhibitor is 2-amino-4-methoxy-6-methyl-1,3,5-triazine; and protective effectiveness is important, which is crucial for the task of MS corrosion prevention.

Steady-state mixed convection boundary layer flow, heat and mass transfer characteristics of Buongiorno's model nanofluid over an inclined porous vertical plate with thermal radiation and chemical reaction are presented in this analysis.

The governing nonlinear partial differential equations represent the flow model that can be converted into system of nonlinear ordinary differential equations using the similarity variables and are solved numerically using finite element method.

The rates of nondimensional temperature and concentration are both decelerate with the higher values of thermophoresis parameter (N_t).

The work carried out in this paper is original.