Enhancement to the patient's health care image encryption system, using several layers of DNA computing and AES (MLAESDNA)

Keeping patient health data private has been a big issue for decades, and this issue will not go away anytime soon. As an integral part of many developing technologies, cryptographic Internet communications ICs (e.g. fog computing and cloud computing) are a main focus of IoT research. Just keep trying all the potential keys until you find the correct one. New and future technologies must have a model of DNA cryptography in order to assure the efficient flow of these technologies. Public-key cryptography is also required to make DNA sequence testing devices for the Internet of Things interoperable. This method employs DNA layers and AES in such a way that it may be easier to design a trustworthy hybrid encryption algorithm that uses DNA layers and AES. In order to guard against brute-force decryption attacks, DNA sequences are encrypted using three keys: (I) the main key, which is the key to the AES encryption algorithm; (II) the rule 1 key, which is the base DNA structure; and (III) the rule 2 key, which is the DNA helical structure binding probability. This key was created with increased security in mind. multi-layered AES encryption and DNA computing were applied to "Covid 19" images in this research (MLAESDNA). With cloud computing, the MLAESDNA team was able to show that IoT signals could be enhanced with encrypted data

Experimental and Numerical Investigation of Heat Transfer Augmentation Using Al2o3-Ethylene Glycol Nanofluids Under Turbulent Flows in a Flat Tube

A study of computational fluid dynamics has been conducted to study the characteristics of the heat transfer and friction factor of Al2O3/Ethylene glycol-water nanofluid flowing inside flat tube. The three dimensional realizable k?e turbulent model with an enhanced wall treatment was utilized. The evaluation of the overall performance of the tested tube was predicated on the thermo-hydrodynamic performance index. The obtained results showed that the difference in behaviour depending on the parameter that has been selected to compare the nanofluid with the base fluid. In addition, the friction factor and the heat transfer coefficient increases with an increase of the nanoparticles volume concentration at the same Reynolds number. The penalty of pressure drop is negligible with an increase of the volume concentration of nanoparticles. Conventional correlations that have been used in turbulent flow regime to predict average heat transfer and friction factor are Dittus-Boelter and Blasius correlations, for tubes are also valid for the tested nanofluids which consider that the nanofluids have a homogeneous fluid behaviour

Nanoparticle sensor for label free detection of swine DNA in mixed biological samples

We used 40 ± 5 nm gold nanoparticles (GNPs) as colorimetric sensor to visually detect swine-specific conserved sequence and nucleotide mismatch in PCR-amplified and non-amplified mitochondrial DNA mixtures to authenticate species. Colloidal GNPs changed color from pinkish-red to gray-purple in 2 mM PBS. Visually observed results were clearly reflected by the dramatic reduction of surface plasmon resonance peak at 530 nm and the appearance of new features in the 620–800 nm regions in their absorption spectra. The particles were stabilized against salt-induced aggregation upon the adsorption of single-stranded DNA. The PCR products, without any additional processing, were hybridized with a 17-base probe prior to exposure to GNPs. At a critical annealing temperature (55 °C) that differentiated matched and mismatched base pairing, the probe was hybridized to pig PCR product and dehybridized from the deer product. The dehybridized probe stuck to GNPs to prevent them from salt-induced aggregation and retained their characteristic red color. Hybridization of a 27-nucleotide probe to swine mitochondrial DNA identified them in pork–venison, pork–shad and venison–shad binary admixtures, eliminating the need of PCR amplification. Thus the assay was applied to authenticate species both in PCR-amplified and non-amplified heterogeneous biological samples. The results were determined visually and validated by absorption spectroscopy. The entire assay (hybridization plus visual detection) was performed in less than 10 min. The LOD (for genomic DNA) of the assay was 6 µg ml − 1 swine DNA in mixed meat samples. We believe the assay can be applied for species assignment in food analysis, mismatch detection in genetic screening and homology studies between closely related species

Characterisation of calcium carbonate and its polymorphs from cockle shells (Anadara granosa)

Calcium carbonate and its polymorphs from cockle shells (Anadara granosa) and commercial calcium carbonate were characterised using a variable pressure scanning electron microscopes (VPSEM), a transmission electron microscope (TEM), an energy dispersive X- ray analyser (EDX), X-ray diffraction (XRD) and Fourier transmission infrared spectroscopy (FT-IR). Cubic-like calcite crystals of commercial calcium carbonate and rod-like aragonite crystals of cockle shell powders were observed by both SEM and TEM. The EDX results showed that the cockle shells contained more calcium and carbon than the commercial calcium carbonate, whereas the commercial calcium carbonate contained more oxygen than the cockle shells. FT-IR analyses revealed the presence of carbonate groups in both the cockle shells and the commercial calcium carbonate. FT-IR analyses also showed the presence of aragonite in the cockle shells and calcite in the commercial calcium carbonate. XRD analyses showed that the cockle shells powder contained aragonite, whereas the commercial calcium carbonate contained calcite. The cockle shells powder was formed with good quality calcium carbonate and contained calcium carbonate in the aragonite phase

Vision based smart sorting machine

In this paper, a research on improved image processing method and a prototype of a vision based sorting machine have been developed to segregate objects based on color, shape and size. In today’s world, image processing is becoming popular technology and it grabs great attentions due to its capabilities of doing various applications in many field. The existing sorting system in industrial environment has to be improved by implementing the image processing method in the system. In some light industries, sorting process will be carried out by manually using human labour. However, this traditional method has brought some disadvantages such as human mistake, slow in work speed, inaccuracy and high cost due to the manpower. A vision based smart sorting machine is proposed to solve the aforementioned problems by segregating the workpieces based on their color, shape and size. It will be operated by a singleboard mini-computer called Raspberry Pi to perform the operation. In the proposed system, Raspberry Pi camera is used to capture the image/stream video of the incoming workpieces through the conveyor. The image/video stream of the incoming workpiece will be captured and implemented with pre- processing that consists of image enhancement to reduce the effect of non-uniform illumination which results from the surrounding llumination. To detect the color of the workpiece, the pre-enhanced image will be decomposed into its respective channels and the dominant color channel will be regarded as the object color. The result will be then matched with the database which is pre- installed in the raspberry storage through features matching method. The results from the features matching will turn on the servo motor and separates the workpieces’ color. For the purpose of shape segregation, the captured image will be first converted into black and white image before it is matched with the database based on certain coverage object properties. While for size segregation, the coverage object pixel area of the pre-processing image is extracted and matched with the databased in the system. Tested results indicate that vision based automatic segregation system improves the accuracy and efficiency of the works and thus the production rate of the industr

Preventive maintenance for effective operation of boilers in Kuwait industry

In this research study, preventive maintenance technique for improving the boiler efficiency is analysed with help of specific methodology. High efficiency can be achieved with the help of an optimal approach of the preventive method. In Kuwait. Among (80) participants, 62.5% of the participants were technical while 37.5% were engineers, the highest group 51.3% were 45 to 55 years old, 51% had master’s degree, 42.5% had more than 10 years as experience and 28.8% working in steel industry. The participants' responses towards the preventive maintenance for efficient operation of boilers had high level with mean score > (3.57) out of (5) according to Likert scale; indicate a high level of agreements. The first rank was (It is required to clean the water side surfaces under preventive maintenance) with the highest mean score 3.9250, indicate that 78.5% of the total participants agreed about it. Last rank is observed (It is required to check the efficiency of boiler routinely by inspecting all major components) with the lowest mean score 3.2500, indicating that only 65% of the total participants agreed about it. Result show that there is a significant difference in the degree of responds towards the preventive maintenance for efficient operation of boilers according to job in favor of engineers group. There is a significant association between job and the following issues which concerned preventive maintenance for efficient operation of boilers, the higher the job as an engineer, the higher the approval score in the following issues: Preventive maintenance is more useful than other maintenance program. It is required to purpose an efficient plan/ schedule for preventive maintenance of boile

A novel catalytic method for the synthesis of spherical aragonite nanoparticles from cockle shells

For the first time, we report here a novel top down catalytic approach for the synthesis of aragonite nanoparticles with spherical morphology from cockleshells. Cockle shell is a natural reservoir of aragonite which is a biogenic polymorph of calcium carbonate. Aragonite polymorph is widely used in the repair of fractured bone, development of advanced drug delivery systems, and tissue scaffolds. The method involves an easily performable and low-cost mechanical stirring of the micron-sized cockle shell powders in presence of a nontoxic biomineralization catalyst, dodecyl dimethyl betaine (BS-12). It produces spherical shaped aragonite nanoparticles of 35 ± 5 nm in diameter with a good reproducibility and without any additional impurities at room temperature. The findings were verified with a variable pressure scanning electron microscopy (VPSEM), energy dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM),Fourier transmission infrared spectroscopy (FT-IR), X-ray diffractometer (XRD), and thermogravimetric analyzer (TGA).The reproducibility, low-cost and simplicity of the method suggested its potential applications in large scale synthesis of aragonite nanoparticles with spherical morphology in an industrial set up

A novel method for the synthesis of calcium carbonate (aragonite) nanoparticles from cockle shells

We report a simple, novel and low-cost method for the synthesis of aragonite nanoparticles from cockle shells. Aragonite is one of the least abundant biogenic polymorphs of calcium carbonate and is widely used as a biomaterial for the repair of fractured bone, development of advanced drug delivery systems, and tissue scaffolds. The method involves a simple mechanical grinding of the micron-sized cockle shell powders in the presence of a non-toxic and non-hazardous biomineralization catalyst, dodecyl dimethyl betaine (BS-12). The method produces rod-shaped aragonite particles with a diameter of 20 ± 5 nm with good reproducibility and without any additional impurities. This was confirmed by a combined analysis of variable pressure scanning electron microscopy (VPSEM), transmission electron microscopy (TEM), Fourier transmission infrared spectroscopy (FTIR), thermogravimetric analyzer (TGA), X-ray diffraction spectroscopy (XRD) and energy dispersive X-ray analyser (EDX). The method should find potential applications in industry for the large scale synthesis of aragonite nanoparticles from a low cost but abundant natural resource such as cockle shells