Special Issue Editors Note

This special issue consists of some selective papers submitted to the 5th International Conference on Natural Science and Technology (ICNST’18). The papers were accepted by our peer review process. ICNST is organized by Science and Math Program of Asian University for Women (AUW) each year since 2014. The main aim of the conference is to bring forward the latest research advances in natural sciences and technology by the scientific and research communities, and provide a forum for the exchange of latest technical information, the dissemination of the high-quality research results on the issues, the presentation of the new developments in these areas, and the debate and shaping of future directions. The conference has maintained its uniqueness and yet evolved gradually to add extra dimension like the session on “Women in Science”, increased overall number of sessions and has gone international for the first time this year.  It is a multi-disciplinary conference on the topics of Biosciences and Bioinformatics, Environmental Sciences, Information and communication technologies, and Public Health.   Papers on related topics were solicited from all relevant disciplinary areas, ranging from current problems, projections, new concepts, modeling, experiments and measurements, to simulations. The ICNST’18 received extraordinary international attention over the world. It included plenary sessions, keynote lectures, and several specialized sessions on different topics including “women in science”. The Women in Science session has been an integral part of the ICNST conference since 2014. The purpose of arranging this session is to create a platform for women researchers and scientists from STEM to share their journey and viewpoints on the contributions made by women in this field.   As we are all aware, the efforts required in organizing and holding this kind of Conference are extensive. We would like to take this opportunity to convey our heartfelt appreciation to some key individuals, all the members of the Organizing Committee, especially the students, who are the driving force behind this conference. We would also like to thank all the sponsors, attendees, presenters, reviewers, chairs of session and keynote & invited speakers from Bangladesh and abroad for their contributions in making this conference a success

Robot sensors process based on generalized Fermatean normal different aggregation operators framework

Novel methods for multiple attribute decision-making problems are presented in this paper using Type-Ⅱ Fermatean normal numbers. Type-Ⅱ Fermatean fuzzy sets are developed by further generalizing Fermatean fuzzy sets and neutrosophic sets. The Type-Ⅱ Fermatean fuzzy sets with basic aggregation operators are constructed. The concept of a Type-Ⅱ Fermatean normal number is compatible with both commutative and associative rules. This article presents a new proposal for Type-Ⅱ Fermatean normal weighted averaging, Type-Ⅱ Fermatean normal weighted geometric averaging, Type-Ⅱ generalized Fermatean normal weighted averaging, and Type-Ⅱ generalized Fermatean normal weighted geometric averaging. Furthermore, these operators can be used to develop an algorithm that solves MADM problems. Applications for the Euclidean distance and Hamming distances are discussed. Finally, the sets that arise as a result of their connection to algebraic operations are emphasized in our discourse. Examples of real-world applications of enhanced Hamming distances are presented. A sensor robot's most important components are computer science and machine tool technology. Four factors can be used to evaluate the quality of a robotics system: resolution, sensitivity, error and environment. The best alternative can be determined by comparing expert opinions with the criteria. As a result, the proposed models' outcomes are more precise and closer to integer number $\delta$. To demonstrate the applicability and validity of the models under consideration, several existing models are compared with the ones that have been proposed

Recent advances in the solar thermochemical splitting of carbon dioxide into synthetic fuels

Recent years have seen a sharp rise in CO2 emissions into the atmosphere, which has contributed to the issue of global warming. In response to this several technologies have been developed to convert CO2 into fuel. It is discovered that the employment of a solar-driven thermochemical process (S-DTCP) that transforms CO2 into fuels can increase the efficiency of the production of sustainable fuels. The process involves the reduction of metal oxide (MO) and oxidizing it with CO2 in a two-step process using concentrated solar power (CSP) at higher and lower temperatures, respectively. This study summarizes current advancements in CO2 conversion methods based on MO thermochemical cycles (ThCy), including their operating parameters, types of cycles, and working principles. It was revealed that the efficiency of the solar conversion of CO2 to fuel is not only influenced by the composition of the MO, but also by its morphology as well as the available surface area for solid/gas reactions and the diffusion length. The conversion mechanism is governed by surface reaction, which is influenced by these two parameters (diffusion length and specific surface area). Solar energy contributes to the reduction and oxidation steps by promoting reaction kinetics and heat and mass transport in the material. The information on recent advances in metal oxide-based carbon dioxide conversion into fuels will be beneficial to both the industrial and academic sectors of the economy.Scopu

Unveiling the frontiers of deep learning: innovations shaping diverse domains

Deep learning (DL) enables the development of computer models that are capable of learning, visualizing, optimizing, refining, and predicting data. In recent years, DL has been applied in a range of fields, including audio-visual data processing, agriculture, transportation prediction, natural language, biomedicine, disaster management, bioinformatics, drug design, genomics, face recognition, and ecology. To explore the current state of deep learning, it is necessary to investigate the latest developments and applications of deep learning in these disciplines. However, the literature is lacking in exploring the applications of deep learning in all potential sectors. This paper thus extensively investigates the potential applications of deep learning across all major fields of study as well as the associated benefits and challenges. As evidenced in the literature, DL exhibits accuracy in prediction and analysis, makes it a powerful computational tool, and has the ability to articulate itself and optimize, making it effective in processing data with no prior training. Given its independence from training data, deep learning necessitates massive amounts of data for effective analysis and processing, much like data volume. To handle the challenge of compiling huge amounts of medical, scientific, healthcare, and environmental data for use in deep learning, gated architectures like LSTMs and GRUs can be utilized. For multimodal learning, shared neurons in the neural network for all activities and specialized neurons for particular tasks are necessary.Comment: 64 pages, 3 figures, 3 table

Techno-economical evaluation of bio-oil production via biomass fast pyrolysis process: a review

Biomass pyrolysis is one of the beneficial sources of the production of sustainable bio-oil. Currently, marketable bio-oil plants are scarce because of the complex operations and lower profits. Therefore, it is necessary to comprehend the relationship between technological parameters and economic practicality. This review outlines the technical and economical routine to produce bio-oils from various biomass by fast pyrolysis. Explicit pointers were compared, such as production cost, capacity, and biomass type for bio-oil production. The bio-oil production cost is crucial for evaluating the market compatibility with other biofuels available. Different pretreatments, upgrades and recycling processes influenced production costs. Using an energy integration strategy, it is possible to produce bio-oil from biomass pyrolysis. The findings of this study might lead to bio-oil industry-related research aimed at commercializing the product

Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future

Given the exponential expansion of the internet, the possibilities of security attacks and cybercrimes have increased accordingly. However, poorly implemented security mechanisms in the Internet of Things (IoT) devices make them susceptible to cyberattacks, which can directly affect users. IoT forensics is thus needed for investigating and mitigating such attacks. While many works have examined IoT applications and challenges, only a few have focused on both the forensic and security issues in IoT. Therefore, this paper reviews forensic and security issues associated with IoT in different fields. Future prospects and challenges in IoT research and development are also highlighted. As demonstrated in the literature, most IoT devices are vulnerable to attacks due to a lack of standardized security measures. Unauthorized users could get access, compromise data, and even benefit from control of critical infrastructure. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system by designing a FLIP-based system that is highly scalable and adaptable. Utilizing a blockchain-based authentication mechanism with a multi-chain structure can provide additional security protection between different trust domains. Deep learning can be utilized to develop a network forensics framework with a high-performing system for detecting and tracking cyberattack incidents. Moreover, researchers should consider limiting the amount of data created and delivered when using big data to develop IoT-based smart systems. The findings of this review will stimulate academics to seek potential solutions for the identified issues, thereby advancing the IoT field.Comment: 77 pages, 5 figures, 5 table

A Framework of Building and Locational Characteristics Ranking for Purpose-built Offices in Malaysia

The development of purpose-built office market in Malaysia is primarily resolved by a supplydemand market. Since the office market in Malaysia has displayed significance improvement due to increasing level of competitiveness, many characteristics of purpose-built office have appeared and become prominent during the process of assessment. These characteristics were generally used as indicators in property valuation, building performance as well as office market appraisal. Based on these characteristics, property market participants can evaluate their property proficiently based on their requirements, especially in decision making during business planning, investment or property management. Technology growth and national policy also gave contribution factors on revealing newly characteristics of purpose-built office such as green building, intelligent building and sustainable development model. The purpose of this article is to identify suitable characteristics of purpose-built office that can be used in Malaysia. Integral to achieving this objective, exploration on purpose built office characteristics in a global and local context will be reconsidered. As a result, a building and locational framework of purpose-built office’s characteristics in Malaysia will be diagnosed and verified appropriately

Selection of suitable passive cooling strategy for a subtropical climate

Background: Passive cooling system has become an attractive option to design and modify homes to achieve thermal comfort. The system provides cooling through the use of passive processes, which often use heat flow paths that do not exist in conventional or bioclimatic buildings. Methods: Six different cities namely Rockhampton, Brisbane, Mackay, Townsville, Charleville and Mount Isa in the hot and humid subtropical climatic zone in Queensland, Australia have been considered for this study. Two main climatic factors such as the temperature and the relative humidity of those cities over a period of around 50 yearshave been taken into account in order to select the appropriate passive cooling strategy for a specific location . Results: Results show that the passive cooling strategy of natural ventilation would be suitable for Rockhampton, Brisbane, Mackay and Townsville whereas high thermal mass would be appropriate for Mackay and Townsville. Conclusion: The procedure of selecting an appropriate passive cooling strategy has been developed for the residences and buildings in a hot and humid subtropical climate. It would be applicable for all buildings with internal heat gains of a hot and humid subtropical climate and will encourage the inhabitants to design the building considering their local climatic conditions

Fluid-Structure-Acoustic coupling analysis for external laminar and turbulent fluid flows

Controlling noise pollution is one of the most crucial parameters in various industries. The use of elastic plates has a substantial impact on noise pollution control and associated factors, such as transmission loss. Additionally, the transmission loss is affected by geometric variations. However, the effect of a rib and elastic plate on the acoustic properties of a channel for a wide range of Reynolds numbers has not yet been investigated, although their use could reduce noise pollution. This study thus investigates the acoustic and flow impacts of a rib and an elastic plate. The control variables for fluid-structure–acoustic coupling numerical simulations are rib height, rib angle, elastic plate length, elastic plate position, Reynolds number, and the Young module of the elastic plate. The governing equations are discretized using the Galerkin method. The results indicate that the transmission loss is 27% more at the elastic plate’s highest position. By decreasing the length of the elastic plate by 50%, the mean transmission loss is reduced by 9%. The findings of this study can be utilized by mechanical and aerospace engineers in the design of aircraft, automobiles, and cooling and heating systems, particularly fan coils

Predicting airfoil stalling dynamics using upwind numerical solutions to non-viscous equations

Over the last few decades, researchers have been focusing on determining the critical attack angle at which dynamic stall occurs. This angle is usually determined by solving the Navier-Stokes equations, which include viscosity, pressure, gravity, and acceleration terms. However, Navier-Stokes equations are quite complex to solve and consequently difficult to simulate, thus the simulation is not accurate enough. Therefore, this article predicts the critical attack angle for the first time using Euler equations devoid of viscous terms. One of the key advantages of Euler equations is their ability to capture the vortices and predict stall dynamics. The Euler equations are thus integrated and the resulting equations are discretized using the finite volume method. A first-order upwind-based method is used to calculate the convective fluxes at the cell boundaries in the finite volume approach. A NACA 0012 airfoil is chosen for this study at various attack angles with a Mach number of 0.3. Based on the justification of Crocco's theorem, the Euler equations successfully act as Navier-Stokes equations. The vortex patterns are found to behave independently of the artificial dissipation. All the vortices are successfully predicted using the inviscid governing equations. The numerical results obtained are validated by other published experimental and numerical data