Hyper Elliptic Curve Based Certificateless Signcryption Scheme for Secure IIoT Communications

Industrial internet of things (IIoT) is the usage of internet of things (IoT) devices and applications for the purpose of sensing, processing and communicating real-time events in the industrial system to reduce the unnecessary operational cost and enhance manufacturing and other industrial-related processes to attain more profits. However, such IoT based smart industries need internet connectivity and interoperability which makes them susceptible to numerous cyber-attacks due to the scarcity of computational resources of IoT devices and communication over insecure wireless channels. Therefore, this necessitates the design of an efficient security mechanism for IIoT environment. In this paper, we propose a hyperelliptic curve cryptography (HECC) based IIoT Certificateless Signcryption (IIoT-CS) scheme, with the aim of improving security while lowering computational and communication overhead in IIoT environment. HECC with 80-bit smaller key and parameters sizes offers similar security as elliptic curve cryptography (ECC) with 160-bit long key and parameters sizes. We assessed the IIoT-CS scheme security by applying formal and informal security evaluation techniques. We used Real or Random (RoR) model and the widely used automated validation of internet security protocols and applications (AVISPA) simulation tool for formal security analysis and proved that the IIoT-CS scheme provides resistance to various attacks. Our proposed IIoT-CS scheme is relatively less expensive compared to the current state-of-the-art in terms of computational cost and communication overhead. Furthermore, the IIoT-CS scheme is 31.25% and 51.31% more efficient in computational cost and communication overhead, respectively, compared to the most recent protocol.     

New Decision-Making Technique Based on Hurwicz Criteria forFuzzyRanking

Efficient decision-making remains an open challenge in the research community, and many researchers are working to improve accuracy through the use of various computational techniques. In this case, the fuzzification and defuzzification processes can be very useful. Defuzzification is an effective process to get a single number from the output of a fuzzy set. Considering defuzzification as a center point of this research paper, to analyze and understand the effect of different types of vehicles according to their performance. In this paper, the multi-criteria decision-making (MCDM) process under uncertainty and defuzzification is discussed by using the center of the area (COA) or centroid method. Further, to find the best solution, Hurwicz criteria are used on the defuzzified data. A new decision-making technique is proposed using Hurwicz criteria for triangular and trapezoidal fuzzy numbers. The proposed technique considers all types of decision makers’ perspectives such as optimistic, neutral, and pessimistic which is crucial in solving decision-making problems. A simple case study is used to demonstrate and discuss the Centroid Method and Hurwicz Criteria for measuring risk attitudes among decision-makers. The significance of the proposed defuzzification method is demonstrated by comparing it to previous defuzzification procedures with its application.     

An Efficient Proxy Blind Signcryption Scheme for IoT

Recent years have witnessed growing scientific research interest in the Internet of Things (IoT) technologies, which supports the development of a variety of applications such as health care, Industry 4.0, agriculture, ecological data management, and other various domains. IoT utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital messages. However, due to the wide-open nature of the Internet, it is important to ensure the anonymity, untraceably, confidentiality, and unforgeability of communication with efficient computational complexity and low bandwidth. We designed a light weight and secure proxy blind signcryption for multi-digital messages based on a hyperelliptic curve (HEC). Our results outperform the available schemes in terms of computational cost and communication bandwidth. The designed scheme also has the desired authentication, unforgeability of warrants and/or plaintext, confidentiality, integrity, and blindness, respectively. Further, our scheme is more suitable for devices with low computation power such as mobiles and tablets.     

Effect of terbium doping in bismuth ferrite nanoparticles for the degradation of organic pollutant under sunlight irradiation

Journal of Materials Science: Materials in Electronics - Herein, we have studied the influence of terbium (Tb) doping in bismuth ferrite (BiFeO3/BFO) nanoparticles towards its photocatalytic...     

Kinetic and Thermodynamic Study of Calcite Marble Samples from Lesser Himalayas

A kinetic and thermodynamic study of selected calcite marble samples from Lesser Himalayas has been performed using thermogravimetric and differential thermal analyses at heating rates of \(10\,^{\circ }\mathrm{C}\,{\cdot }\min ^{-1}\) and \(30\,^{\circ }\mathrm{C}\,{\cdot }\min ^{-1}\) . The minero-petrography of calcite grains, phase analysis, chemical analysis, and minor impurities determination were carried out using thin-section polarized light microscopy, X-ray diffraction, X-ray fluorescence, and electron microprobe analysis, respectively. The calcite content of the investigated marble samples varied from 97.50 mass% to 98.70 mass%. The activation energy, \(E_\mathrm{a}\) , for the decomposition process increased from \(158.6\,\mathrm{kJ}\,{\cdot }\mathrm{mol}^{-1}\) to \(179.4\,\mathrm{kJ}\,{\cdot }\,\mathrm{mol}^{-1}\) and from \(214.1\,\mathrm{kJ}\,{\cdot }\, \mathrm{mol}^{-1}\) to \(232.8\,\mathrm{kJ}\,{\cdot }\, \mathrm{mol}^{-1}\) for heating rates of \(10\,^{\circ }\mathrm{C}\,{\cdot }\, \min ^{-1}\) and \(30\,^{\circ }\mathrm{C}\,{\cdot }\, \min ^{-1}\) , respectively, with decreasing calcite content. The activation energy values obtained in the present study were in good agreement with previous studies.     

Effects of nanoscale size dependent parameters on lattice thermal conductivity in Si nanowire

The effects of nanoscale size dependent parameters on lattice thermal conductivity are calculated using the Debye-Callaway model including transverse and longitudinal modes explicitly for Si nanowire with diameters of 115, 56, 37 and 22 nm. A direct method is used to calculate the group velocity for different size nanowire from their related calculated melting point. For all diameters considered, the effects of surface roughness, defects and transverse and longitudinal Gruneisen parameters are successfully used to correlate the calculated values of lattice thermal conductivity to that of the reported experimental curve. The obtained fitting value for mean Gruneisen parameter has a systematic dependence on all Si nanowire diameters changing from 0·791 for 115 nm diameter to 1·515 for the 22 nm nanowire diameter. The dependence also gave a suggested surface thickness of about 5–6 nm. The other two parameters were found to have partially systematic dependence for diameters 115, 56, and 37 nm for defects and 56, 37 and 22 nm for the roughness. When the diameters go down from 115 to 22 nm, the concentration of dislocation increased from 1·16 × 10¹⁹cm⁻³ to 5·20 × 10¹⁹cm⁻³ while the surface roughness P found to increase from 0·475 to 0·130 and the rms height deviation from the surface changes by about 1·66 in this range of diameter. The diameter dependence also indicates a strong control of surface effect in surface to bulk ratio for the 22 nm wire diameter.     

Fuzzy Time-Driven Activity-Based Costing

Abstract:

Activity-Based Costing (ABC) method is a well-known costing/accounting system. It is an alternative to traditional accounting systems in which business overheads are allocated in proportion to activity's direct costs. Kaplan and Anderson proposed the second generation of the ABC system, called “time-driven activity-based costing” (TDABC), which seeks to resolve some of its drawbacks. The TDABC approach is mainly based on the time drivers spent on cost pools; however, TDABC poses some difficulties in calculations of the assigned costs. Unavailability of accurate and reliable time drivers, variety of time drivers, difficulties of collecting and updating data through calculation procedure, and huge volume of data are some examples of the difficulties. In this article, via utilizing the triangular fuzzy number (TFN), a novel mechanism for the TDABC system is proposed. We employ fuzzy logic to estimate inputs required for TDABC, namely, the required time to perform each activity and practical capacity. Our proposed approach highlights deviations caused by deterministic estimates in TDBAC and makes our estimates more realistic. In addition, sensitivity analysis can be conducted with our proposed approach. Finally, all plausible conditions ranging from the worst case to the best case can be considered; therefore, insightful and appropriate managerial decisions can be made.     

Numerical analysis of flow behaviour,grain size prediction and experimental verification of hot rolled ultralow carbon niobium microalloyed steel

Niobium bearing ultralow carbon micro alloyed dual phase steel grade steel with chemical composition of 0.045 wt.% carbon, 0.04 wt.% niobium, 0.59 wt.% chromium, 0.9 wt.% manganese, 0.28 wt.% silicon is investigated. The design of thermomechanical treatment needs knowledge about the flow behaviour at high deformation temperatures, to be used for this steel in industrial plants. Therefore, this work aims to predict, for the investigated steel, the flow behaviour and mean flow stress. A phenomenological constitutive model is established to derive the flow stress using the hyperbolic sinusoidal Arrhenius mathematical model. The relation between stress and strain with Zener-Hollomon parameter is studied. Mean flow stress has been figured out by measurements taken from compact slab production plant log data using a constitutive model. The constitutive model is further verified by multiple hits of flat compression setup mode at BährTTS820 physical simulator. The tests were performed under specific thermochemical schedule simulating compact slab production plant. The results show good agreement between the calculated flow stress, Non-recrystallization temperature and experimentally measured values obtained from the physical simulation. Ferrite grain size is modelled and predicted then validated by experimental rolled specimens in a practical hot strip mill.     

Evaluating the Impact of Prediction Techniques: Software Reliability Perspective

Maintaining software reliability is the key idea for conducting quality research. This can be done by having less complex applications. While developers and other experts have made significant efforts in this context, the level of reliability is not the same as it should be. Therefore, further research into the most detailed mechanisms for evaluating and increasing software reliability is essential. A significant aspect of growing the degree of reliable applications is the quantitative assessment of reliability. There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software. However, none of these mechanisms are useful for all kinds of failure datasets and applications. Hence finding the most optimal model for reliability prediction is an important concern. This paper suggests a novel method to substantially pick the best model of reliability prediction. This method is the combination of analytic hierarchy method (AHP), hesitant fuzzy (HF) sets and technique for order of preference by similarity to ideal solution (TOPSIS). In addition, using the different iterations of the process, procedural sensitivity was also performed to validate the findings. The findings of the software reliability prediction models prioritization will help the developers to estimate reliability prediction based on the software type.