In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. ...Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces.
In the present study, a new computational model which incorporates the effect of transverse shear and normal deformation is presented for the thermal analysis of laminated composite and sandwich ...plates. The present theory involves nine unknowns and uses a polynomial function in terms of thickness coordinates which is expanded up to fifth-order. In the present fifth-order shear and normal deformation theory (FOSNDT), the governing equations are variationally consistent and obtained by using the principle of virtual work. Plates are analyzed for simply supported boundary conditions using Navier's solution technique. Numerical results obtained by using the present theory are compared with three-dimensional elasticity solution and other higher-order theories available in the literature. It is found that the present theory is accurately predicting the thermal response of laminated composite and sandwich plates compared to any other theory available in the literature.
Triple-negative breast cancer (TNBC) is a metastatic disease and a formidable treatment challenge as it does not respond to existing therapies. Epigenetic regulators play a crucial role in the ...progression and metastasis by modulating the expression of anti-apoptotic, pro-apoptotic markers and related miRNAs in TNBC cells. We have investigated the anti-TNBC potential of dietary flavonoid 'Apigenin' and its combination with Vorinostat on MDA-MB-231 cells. At Apigenin generated ROS, inhibited cell migration, arrested the cell cycle at subG0/G1 phases, and induced apoptotic-mediated cell death. Apigenin reduced the expression of the class-I HDACs at the transcriptomic and proteomic levels. In the immunoblotting study, Apigenin has upregulated pro-apoptotic markers and downregulated anti-apoptotic proteins. Apigenin inhibited the enzymatic activity of HDAC/DNMT and increased HAT activity. Apigenin has manifested its effect on miRNA expression by upregulating the tumor-suppressor miR-200b and downregulation oncomiR-21. Combination study reduced the growth of TNBC cells synergistically by modulating the expression of epigenetic and apoptotic regulators. Molecular docking and MD simulations explored the mechanism of catalytic inhibition of HDAC1 and HDAC3 and supported the in-vitro studies. The overall studies demonstrated an anti-TNBC potential of Apigenin and may help to design an effective strategy to treat metastatic phenotype of TNBC.
Alzheimer’s disease (AD) is the most prevalent type of dementia caused by the accumulation of amyloid beta (Aβ) peptides. The extracellular deposition of Aβ peptides in human AD brain causes neuronal ...death. Therefore, it has been found that Aβ peptide degradation is a possible therapeutic target for AD. CathD has been known to breakdown amyloid beta peptides. However, the structural role of CathD is not yet clear. Hence, for the purpose of gaining a deeper comprehension of the structure of CathD, the present computational investigation was performed using virtual screening technique to predict CathD's active site residues and substrate binding mode. Ligand-based virtual screening was implemented on small molecules from ZINC database against crystal structure of CathD. Further, molecular docking was utilised to investigate the binding mechanism of CathD with substrates and virtually screened inhibitors. Localised compounds obtained through screening performed by PyRx and AutoDock 4.2 with CathD receptor and the compounds having highest binding affinities were picked as; ZINC00601317, ZINC04214975 and ZINCC12500925 as our top choices. The hydrophobic residues Viz
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Gly35, Val31, Thr34, Gly128, Ile124 and Ala13 help stabilising the CathD-ligand complexes, which in turn emphasises substrate and inhibitor selectivity. Further, MM-GBSA approach has been used to calculate binding free energy between CathD and selected compounds. Therefore, it would be beneficial to understand the active site pocket of CathD with the assistance of these discoveries. Thus, the present study would be helpful to identify active site pocket of CathD, which could be beneficial to develop novel therapeutic strategies for the AD.
Abstract
In this study, a new fifth order shear deformation theory is developed considering the effect of thickness stretching for the free vibration analysis of laminated composite beam. To account ...the effect of shear in transverse direction and normal de-formations, displacement field uses polynomial shape function in terms of thick-ness co-ordinate expanded up to order five. The virtual work equation is used to have the equations in terms of the unknowns and corresponding boundary conditions. The analytical solution for a laminated composite beam with simple sup-ports is developed using Navier’s solution. To assess the validity of the theory developed, dimension less natural frequencies for laminated composite beam determined by the present model are compared with previously published results.
A honeypot is a concealed security system that functions as a decoy to entice cyberattackers to reveal their information. Therefore, it is essential to disguise its identity to ensure its successful ...operation. Nonetheless, cyberattackers frequently attempt to uncover these honeypots; one of the most effective techniques for revealing their identity is a fingerprinting attack. Once identified, a honeypot can be exploited as a zombie by an attacker to attack others. Several effective techniques are available to prevent a fingerprinting attack, however, that would be contrary to the purpose of a honeypot, which is designed to interact with attackers to attempt to discover information relating to them. A technique to discover any attempted fingerprinting attack is highly desirable, for honeypots, while interacting with cyberattackers. Unfortunately, no specific method is available to detect and predict an attempted fingerprinting attack in real-time due to the difficulty of isolating it from other attacks. This paper presents a computational intelligence enabled honeypot that is capable of discovering and predicting an attempted fingerprinting attack by using a Principal components analysis and Fuzzy inference system. This proposed system is successfully tested against the five popular fingerprinting tools Nmap, Xprobe2, NetScanTools Pro, SinFP3 and Nessus.
Electronic Government (e-Government) systems constantly provide greater services to people, businesses, organisations, and societies by offering more information, opportunities, and platforms with ...the support of advances in information and communications technologies. This usually results in increased system complexity and sensitivity, necessitating stricter security and privacy-protection measures. The majority of the existing e-Government systems are centralised, making them vulnerable to privacy and security threats, in addition to suffering from a single point of failure. This study proposes a decentralised e-Government framework with integrated threat detection features to address the aforementioned challenges. In particular, the privacy and security of the proposed e-Government system are realised by the encryption, validation, and immutable mechanisms provided by Blockchain. The insider and external threats associated with blockchain transactions are minimised by the employment of an artificial immune system, which effectively protects the integrity of the Blockchain. The proposed e-Government system was validated and evaluated by using the framework of Ethereum Visualisations of Interactive, Blockchain, Extended Simulations (i.e. eVIBES simulator) with two publicly available datasets. The experimental results show the efficacy of the proposed framework in that it can mitigate insider and external threats in e-Government systems whilst simultaneously preserving the privacy of information.
The YARA rules technique is used in cybersecurity to scan for malware, often in its default form, where rules are created either manually or automatically. Creating YARA rules that enable analysts to ...label files as suspected malware is a highly technical skill, requiring expertise in cybersecurity. Therefore, in cases where rules are either created manually or automatically, it is desirable to improve both the performance and detection outcomes of the process. In this paper, two methods are proposed utilising the techniques of fuzzy hashing and fuzzy rules, to increase the effectiveness of YARA rules without escalating the complexity and overheads associated with YARA rules. The first proposed method utilises fuzzy hashing referred to as enhanced YARA rules in this paper, where if existing YARA rules fails to detect the inspected file as malware, then it is subjected to fuzzy hashing to assess whether this technique would identify it as malware. The second proposed technique called embedded YARA rules utilises fuzzy hashing and fuzzy rules to improve the outcomes further. Fuzzy rules countenance circumstances where data are imprecise or uncertain, generating a probabilistic outcome indicating the likelihood of whether a file is malware or not. The paper discusses the success of the proposed enhanced YARA rules and embedded YARA rules through several experiments on the collected malware and goodware corpus and their comparative evaluation against YARA rules.
The standard and real-time communication technology is an unalloyed inevitability for the development of Internet of Things (IoT) applications. However, the selection of a standard and effective ...messaging protocol is a challenging and daunting task for any organisation because it depends on the nature of the IoT system and its messaging requirements. Copious messaging protocols have been developed and employed by various organisations based on their requirements in the last two decades. Though, none of them is able to support all messaging requirements of all types of IoT systems. Messaging protocol is an ongoing dilemma for the IoT industry; consequently, it is important to understand the pros and cons of the widely accepted and emerging messaging protocols for IoT systems to determine their best-fit scenarios. Therefore, this paper presents an evaluation of the four established messaging protocols MQTT, CoAP, AMQP and HTTP for IoT systems. Firstly, it presents the broad comparison among these messaging protocols to introduce their characteristics comparatively. Afterwards, it performs a further in-depth and relative analysis based on some interrelated criteria to gain insight into their strengths and limitations. Thus, based on this detailed evaluation, the user can decide their appropriate usage in various IoT systems according to their requirements and suitability.
Innovation in learning and teaching is an everyday requirement in contemporary higher education (HE), especially in challenging subjects such as mathematics. Teaching mathematics to students with ...limited experience of formal mathematical instruction is a good example of a demanding pedagogical undertaking where innovatory practice can help HE teachers rise to the challenge. This paper presents an innovative game-based learning approach to the teaching of basic mathematics in HE through the example of a first-year mathematics module of the BSc Computer Science course offered by the Aberystwyth University (UK). Excellent examination results and positive student feedback concerning the learning experience point to the value-addedness of this approach in HE and it is, therefore, offered here as an example of good teaching practice to be disseminated more widely in the sector.
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