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End-to-end latency in network affects the overall performance in number of ways. It is one of the major tasks to minimize the end-to-end latency in cognitive radio ad hoc networks (CRAHN), as the transmission of packets passes through every hop of the routing path. This paper aims to propose a new reactive multicast routing protocol, namely, improved frog leap inspired protocol (IFLIP) to reduce the overall end-to-end latency in CRAHN.

It is difficult to solve the problems that emerge in optimization. Routing is the procedure for choosing the best network path. This paper proposes a novel algorithm by improving the FLIP to use an ideal route, which progressively reduces the congestion level on various routing path by considering the spectrum accessibility and the service rate of each hop in CRAHN.

Result of this research work concludes that IFLIP significantly outperforms other baseline schemes (namely, TIGHT and Greedy TIGHT) in minimizing the end-to-end latency in CRAHN.

It is proved that IFLIP gives a better ratio of packet delivery under varying primary users and secondary users. IFLIP results in increased packet deliver ratio, reduced end-to-end latency and better throughput.

In the context of fire incidents within buildings, efficient scene perception by firefighting robots is particularly crucial. Although individual sensors can provide specific types of data, achieving deep data correlation among multiple sensors poses challenges. To address this issue, this study aims to explore a fusion approach integrating thermal imaging cameras and LiDAR sensors to enhance the perception capabilities of firefighting robots in fire environments.

Prior to sensor fusion, accurate calibration of the sensors is essential. This paper proposes an extrinsic calibration method based on rigid body transformation. The collected data is optimized using the Ceres optimization algorithm to obtain precise calibration parameters. Building upon this calibration, a sensor fusion method based on coordinate projection transformation is proposed, enabling real-time mapping between images and point clouds. In addition, the effectiveness of the proposed fusion device data collection is validated in experimental smoke-filled fire environments.

The average reprojection error obtained by the extrinsic calibration method based on rigid body transformation is 1.02 pixels, indicating good accuracy. The fused data combines the advantages of thermal imaging cameras and LiDAR, overcoming the limitations of individual sensors.

This paper introduces an extrinsic calibration method based on rigid body transformation, along with a sensor fusion approach based on coordinate projection transformation. The effectiveness of this fusion strategy is validated in simulated fire environments.

Seeking online bilingual scientific information is a key aspect of bilingual scientific Web literacy – abilities to engage critically with science on the Web using two languages. This study aims to determine whether factors such as age, education major, gender and type of school attended at secondary level (monolingual, bilingual, trilingual) influence undergraduates’ ability to search online Spanish-English bilingual scientific information.

The participants in this study were 60 students (43 females and 17 males, 18–25 years old) enrolled in a university bilingual science course at a high-ranked Colombian university. They were asked to complete two tasks in which they had to seek online scientific information in Spanish and in English and post their responses on the Web application, Padlet^® (padlet.com).

Results indicate that students’ gender and age influence their academic performance in both tasks and level of originality in using information obtained via the Web, respectively. Moreover, the “scientific journal” was the top source of online information from which participants sought most information to complete both tasks.

People are becoming increasingly accustomed to seeking and sharing online scientific information to support points of view and make decisions. However, it is not known which factors influence students’ ability to seek online first language-English bilingual scientific information in countries where English is the second or foreign language.

This final chapter draws together the key findings presented in the preceding pages and considers emergent conclusions and implications for mental health and wellbeing in schools. The author draws upon the evidence presented by the book’s eclectic range of contributors and the health promoting schools’ (HPSs) framework to provide a road map of what an effective whole school approach (WSA) might look like moving forward. Crucially, lessons from recent crises in education, including COVID-19-driven changes in pathways to support, are highlighted as pivotal factors in a future vision which sees schools as an effective and sustainable frontline force to help tackle the global burden of child and adolescent mental health through a proactive, preventive stance. With this future focus in mind, next steps are considered in terms of developing effective and sustainable mental health and wellbeing support for all within healthy school settings.

This paper is concerned with non-fragile robust H_∞ control problems for nonlinear networked control systems (NCSs) with time-varying delay and unknown actuator failures. The paper aims to discuss these issues.

The system parameters are allowed to have time-varying uncertainties and the actuator faults are unknown but whose upper and lower bounds are known. By using some lemmas, uncertainties can be replaces with the known values. By taking the exogenous disturbance and network transmission delay into consideration, a delay nonlinear system model is constructed.

Based on Lyapunov stability theory, linear matrix inequalities (LMIs) and free weighting matrix methods, the sufficient conditions for the existence of the non-fragile robust H_∞ controller gain are derived and which can obtained by solving the LMIs. Finally, a numerical example is provided to illustrate the effectiveness of the proposed methods.

The introduced approach is interesting for NCSs with time-varying delay and unknown actuator failures.

The purpose of this paper is to test the pricing performance of Black-Scholes (B-S) model, with the volatility of the underlying estimated with the two-scale realised volatility measure (TSRV) proposed by Zhang et al. (2005).

The ex post TSRV is used as the volatility estimator to ensure efficient volatility estimation, without forecasting error. The B-S option prices, thus obtained, are compared with the market prices using four performance measures, for the options on NIFTY index, and three of its constituent stocks. The tick-by-tick data are used in this study for price comparisons.

The B-S model shows significantly negative pricing bias for all the options, which is dependent on the moneyness of the option and the volatility of the underlying.

The negative pricing bias of B-S model, despite the use of the more efficient TSRV estimate, and post facto volatility values, confirms its inadequacy. It also points towards the possible existence of volatility risk premium in the Indian options market.

The use of tick-by-tick data obviates the nonsynchronous error. TSRV, used for estimating the volatility, is a significantly improved estimate (in terms of efficiency and bias), as compared to the estimates based on closing data. The use of ex post realised volatility ensures that the forecasting error does not vitiate the test results. The sample is selected to be large and varied to ensure the robustness of the results.

The purpose of this study is to present a systematic literature review of academic peer-reviewed articles in English published between 2005 and 2021. The articles were reviewed based on the following features: research topic, conceptual and theoretical characterization, artificial intelligence (AI) methods and techniques.

This study examines the extent to which AI features within academic research in retail industry and aims to consolidate existing knowledge, analyse the development on this topic, clarify key trends and highlight gaps in the scientific literature concerning the role of AI in retail.

The findings of this study indicate an increase in AI literature within the field of retailing in the past five years. However, this research field is fairly fragmented in scope and limited in methodologies, and it has several gaps. On the basis of a structured topic allocation, a total of eight priority topics were identified and highlighted that (1) optimizing the retail value chain and (2) improving customer expectations with the help of AI are key topics in published research in this field.

This study is based on academic peer-reviewed articles published before July 2021; hence, scientific outputs published after the moment of writing have not been included.

This study contributes to the in-depth and systematic exploration of the extent to which retail scholars are aware of and working on AI. To the best of the author’s knowledge, this study is the first systematic literature review within retailing research dealing with AI technology.

The purpose of this paper was to analyse the present status of the information available on rice bean [Vigna umbellata (Thunb.)] cultivars with respect to its nutritional and functional characteristics. It is one of the non-conventional and under-utilized beans of South and Southeast Asia. In northeastern regions of India, it is an important crop for shifting cultivation or kitchen garden which is consumed as vegetable (tender pod) and pulse. The information gaps filling could be useful for several work proposals and for consumers and cultivators to know the nutritional strength and varied usability of the grain which in-turn can help in its commercialization.

The approach to information collection was emphasized on nutritional strength of the grain compared to other beans of Vigna family and the varied usability among the rice bean varieties of the Himalayan Belt.

The average carbohydrate, protein, fat, crude fibre and ash content of 75 genotypes of rice bean was found 59.96 ± 2.81, 20.78 ± 2.65, 1.74 ± 1.42, 5.07 ± 1.17 and 4.44 ± 1.03 per cent, respectively. It has high quality protein with all essential amino acid in balance manner. Among the minerals, it contains calcium, iron, zinc and potassium with high bio-availability of calcium (59.8 ± 0.3 per cent). The factors such as flatulence producing saccharides, trypsin inhibitors, polyphenols, phytic acid, saponin and tannins of rice bean were reported to be in the range of 3.28-5.87 per cent, 55.12-163.98 TIU/g, 0.58-1.82 1.88-8.17, 1.2-3.1 and 0.24-1.55 per cent, respectively. The toxic compounds such as hydrogen cyanide (0.09 mg/100 g) and L-3, 4-dihydroxyphenylalanine (0.36 mg/100 g) is lowest in rice bean. The nutritional advantages of rice bean over the other beans of Vigna family were required to emphasize to induce interest among the researchers, producers and consumers.

In view of the recommended daily requirements with respect of amino acids, vitamin-B and minerals, rice bean could be a major component of the diet to fulfill them. However, the scanty information available on nutritional and functional components of rice bean varieties grown in northeastern India calls for the gap filing research to explore full potential of the bean.

The information about differences among the northeastern varieties of rice bean available on nutritional functional components essentially required the updating of research data to explore full potential and utility of the bean.

This paper aims to explore the numerical study of the steady two-dimensional MHD hybrid Cu-Fe₃O₄/EG nanofluid flows over an inclined porous plate with an inclined magnetic effect. Iron oxide (Fe₃O₄) and copper (Cu) are hybrid nanoparticles, with ethylene glycol as the base fluid. The effects of several physical characteristics, such as the inclination angle, magnetic parameter, thermal radiation, viscous propagation, heat absorption and convective heat transfer, are revealed by this exploration.

Temperature and velocity descriptions, along with the skin friction coefficient and Nusselt number, are studied to see how they change depending on the parameters. Using compatible similarity transformations, the controlling equations, including those describing the momentum and energy descriptions, are turned into a set of non-linear ordinary differential equations. The streamlined mathematical model is then solved numerically by using the shooting approach and the Runge–Kutta method up to the fourth order. The numerical findings of skin friction and Nusselt number are compared and discussed with prior published data by Nur Syahirah Wahid.

The graphical representation of the velocity and temperature profiles within the frontier is exhibited and discussed. The various output values related to skin friction and the Nusselt number are shown in the table.

The new results are compared to past research and discovered to agree significantly with those authors’ published works.

The purpose of this paper is to analyze the mechanism of nanofluid enhanced heat transfer in microchannels and promote the application of nanofluids in industrial processes such as solar collectors, electronic cooling and automotive batteries.

The two-phase lattice Boltzmann method was used to calculate the flow and heat transfer characteristics of Al₂O₃ nanofluids in a microchannel at Re = 50. By comparing the simulation results of pure water, nanofluids without calculated nanoparticle-fluid interaction forces and nanofluids with calculated nanoparticle-fluid interaction forces, the effects of physical properties improvement and interaction forces on flow and heat transfer are quantified.

The findings show that the nanofluid (φ = 3%, R = 10 nm) increases the average Nusselt number by 22.40% at Re = 50. In particular, 16.16% of the improvement relates to nanoparticles optimizing the thermophysical parameters of the base fluid. The remaining 6.24% relates to the disturbance of the thermal boundary layer caused by the interaction between nanoparticles and the base fluid. Moreover, the nanoparticle has a negligible effect on the average Fanning friction factor. Ultimately, we conclude that the nanofluid is an excellent heat transfer working medium based on its performance evaluation criterion, PEC = 1.225.

To the best of the authors' knowledge, this research quantifies for the first time the contribution of nanoparticle-liquid interactions and nanofluids physical properties to enhanced heat transfer, advancing the knowledge of the nanoparticle's behavior in liquid systems.