Design of an Integrated Microfluidic Paper-Based Chip and Inspection Machine for the Detection of Mercury in Food with Silver Nanoparticles

For most of the fast screening test papers for detecting Hg2+, the obtained results are qualitative. This study developed an operation for the μPAD and combined it with the chemical colorimetric method. Silver nanoparticle (AgNP) colloids were adopted as the reactive color reagent to combine and react with the Hg standards on the paper-based chip. Then, the RGB values for the color change were used to establish the standard curve (R2 > 0.99). Subsequently, this detection system was employed for the detection tests of actual samples, and the detected RGB values of the samples were substituted back to the formula to calculate the Hg2+ contents in the food. In this study, the Hg2+ content and recovery rate in commercially available packaged water and edible salts were measured. The research results indicate that a swift, economical, and simple detection method for Hg2+ content in food has been successfully developed.

Least Significant Bit (LSB) Modification Analysis With Alternate Insertion Message Technique On Image Media

One aspect of success in data communication is security. Data security can be done by using steganography. Steganography is a way to hide messages in the media in such a way that other people do not realize there is a message in the media. Many of the algorithms used in steganography one of which is the Least Significant Bit. In this research, the authors modify Least Significant Bit algorithms with Alternate Insertion method. Modification is doing of embedding and extracting messages process by changing the RGB values ??at each pixel of image data with confidential file by inserting message alternately and insertionly until the all message inserted. This steganography applications have input password that is used as the key of a message can't be opened in addition to the addressee so that the data will be kept confidential. The parameters used to measure the performance of the Least Significant Bit and Alternate Insertion are using runtime program and analysist algorithms of Big . The message insertion applications built by using C# (C Sharp) programming language. From the results of research that extracting process messages work faster than the embedding process. More larger of image in used it will be spend longer time to process the inserting message. Time complexity of algorithms (Big ) embedding and extracting processes obtained in testing the system is T (n) = (xy). From the results of research that extracting process messages work faster than the embedding process. More larger of image in used it will be spend longer time to process the inserting message. Time complexity of algorithms (Big ) embedding and extracting processes obtained in testing the system is T (n) = (xy). From the results of research that extracting process messages work faster than the embedding process. More larger of image in used it will be spend longer time to process the inserting message. Time complexity of algorithms (Big ) embedding and extracting processes obtained in testing the system is T (n) = (xy).

Prediction of nanosilver and dye content on silk fabric using a scanner-based artificial intelligence technique

Purpose This paper aims to investigate using scanner-based adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANNs) and polynomial regression methods for prediction of silver nanoparticles (AgNPs) and dye concentrations on AgNP-treated silk fabrics. Design/methodology/approach For estimation of the dye and AgNPs concentration using image processing, the silk fabrics were scanned under the condition of 200 pixels per inch. The red green blue (RGB) values of scanned images were obtained after applying the median filter. Then, the relationship between scanner RGB values and dye and AgNPs concentrations were obtained by using artificial intelligence methods such as ANFIS and ANNs. Findings The best result was achieved by the ANFIS system for calculation concentration of dye with 0.07% error and concentration of AgNPs with 0.008 (gr/l) error. The obtained results indicate that the performance of the ANFIS system method is better than the other methods. Originality/value Using a scanner-based artificial intelligence technique for prediction of nanosilver and dye content on silk fabric.

Characteristics of skin coat as well as the physiological status of F1 crossing Bali (Bos Sondaicus) x Angus (Bos Taurus) for early identification of adaptability in tropical environment

Characteristics of skin and hair color in cattle, as well as the number of skin follicles, have an essential role in the process of adapting to the ambient temperature and humidity. Bali cattle (Bos Sondaicus) is an indigenous Indonesian cattle that is a tropical climate, has the characteristics of the light hair color crossing with Black Angus (Bos Taurus) from different species, subtropical climate. Objective: To know the changes in the skin and hair color characteristics of F1 crossing of Bos Sondaicus with Angus (Bos Taurus), and whether it affects its adaptability to the tropical environment. Methods: Twenty of F1 Angus x Bali cross cattle were studied for their characteristics of skin and hair color, a number of skin follicles as well as physiological status for early identification of adaptability in a tropical environment. Hair and skin color measured by the value of the RGB (Red, Green, Blue) method. Completely Randomized Design (CRD) was done to distinguish RGB values and the physiological status between crossed compare to local breed. Results: The results showed that the RGB values of crossed were significantly lower (P<0.05), had meant that darker and had fewer hair follicles (P<0.05) (15.18±2.24 vs. 21.38±4.33/mm2) which caused the skin surface temperature was higher (P<0.05)(35.41±1.14 vs. 34.31±2.27˚C). Although during the day, they had a higher physiological status (P<0.05) but still in the normal range. Conclusion: It concluded that although the skin and hair color became markedly darker, they still can adapt to the tropical environment, shown from body temperature, respiration rate, and pulses, as the gold standard for measures cattle's tolerance to environmental conditions.

FISH SKIN FRESHNESS LEVEL BY INTEGRATED RGB COLOUR IMAGE AND QUALITY INDEX METHOD (QIM) ASSESSMENT

The colour of the fish skin is one of the important factors to determine the freshness of a fish. There are potential to use the fish images as an alternative to determining the fish freshness. However, the freshness relationship of the fish skin image to the Red, Green, Blue (RGB) colour channel needs to be elucidated to achieve an accurate interpretation of fish freshness. The objective of this study is to determine the freshness of the fish samples using QIM assessment and to extract the RGB colour value from fish skin images. Finally, to establish the relationship between the QIM scores ranging from 1 (fresh) to 3 (spoiled) and RGB value for freshness indicator using fish images. The effects of temperature, environment, and storage method have been shown to play an important role in determining the rate of deterioration towards the quality and freshness level in fish. From this study, a freshness indicator based on the Quality Index Method (QIM) and RGB value for Queenfish and Threadfin were created. Based on the QIM score, Threadfin was easier to deteriorate as compared to Queenfish from its leaner body type properties. Different fish would reflect different freshness reading as Threadfin is in a fresh state when it possesses a QIM score of 1 with RGB values to range between of 143 to 172. As deterioration progresses, the QIM score is at 3 and the RGB values are ranging from 132 to 161. While Queenfish is found to be in a fresh state when it acquires QIM score of 1 and the RGB values are in the range of 148 to 170. It starts to spoil when the QIM score is at 3 and the RGB values are ranging from 154 to 184.

Application Notes - APD LAMP Diagnostic App: Automated Colorimetric Analysis and Documentation

Amidst rapid diagnostic kits, reverse transcription loop-mediated isothermal amplification (RT-LAMP) has emerged as a rapid point-of-care testing (POCT) method during the COVID-19 pandemic. While many POCT kits rely on plate readers or visual classifications, these processes require experienced staff, and with the use of plate readers, the need for peripheral equipment and infrastructure as well. To address the gap and ensure objectivity in colorimetric POCT kits, the Automated Product Determination (APD) LAMP Diagnostic App was developed for automatic colorimetric analysis of single to multiple LAMP samples. Leveraging on the smartphone camera, barcode-based documentation feature, and a colour distance formula, the app algorithm calculates RGB values, labelling samples as “positive” when yellow, “negative” when pink, and “unknown” when orange. The APD Lamp diagnostic app for Android hereby demonstrates the integration of smartphone apps in POCT kits and ways the smartphone revolution changes laboratory processes to be timely and on-the-go.

Targetless Coregistration of Terrestrial Laser Scanning Point Clouds Using a Multi Surrounding Scan Image-Based Technique

The coregistration of terrestrial laser point clouds is widely investigated where different techniques are presented to solve this problem. The techniques are divided either as target-based or targetless approaches for coarse and fine coregistration. The targetless approach is more challenging since no physical reference targets are placed in the field during the scanning. Mainly, targetless methods are image-based and they are applied through projecting the point clouds back to the scanning stations. The projected 360 point cloud images are normally in the form of panoramic images utilizing either intensity or RGB values, and an image matching is followed to align the scan stations together. However, the point cloud coregistration is still a challenge since ICP like methods are applicable for fine registration. Furthermore, image-based approaches are restricted when there is: a limited overlap between point clouds, no RGB data accompanied to intensity values, and unstructured scanned objects in the point clouds. Therefore, we present in this paper the concept of a multi surrounding scan MSS image-based approach to overcome the difficulty to register point clouds in challenging cases. The multi surrounding scan approach means to create multi-perspective images per laser scan point cloud. These multi-perspective images will offer different viewpoints per scan station to overcome the viewpoint distortion that causes the failure of the image matching in challenging situations. Two experimental tests are applied using point clouds collected in Enschede city and the published 3D toolkit data set in Bremen city. The experiments showed a successful coregistration approach even in challenging settings with different constellations.

Encryption and Decryption Application on Images with Hybrid Algorithm Vigenere and RSA

Digital image is digital pictures on a two-dimensional plane which consists of pixels, where every pixels has Red, Green, Blue (RGB) with varying intensity depending on the image. In this thesis digital image is encrypted using hybrid algorithm Vigenere and RSA. Vigenere algorithm is a symmetric key algorithm which is a variety from Caesar algorithm where the similarity is in both of them are based on shifting the index of alphabet letters. RSA algorithm are based on the difficulty of factorizing large numbers that have 2 and only 2 factors (Prime numbers). The encryption process starts with getting the RGB intensity of each pixels from the image, then the RGB values are encrypted using Vigenere algorithm, after that RSA Algorithm encrypt those values, the values of RSA Algorithm encryption are limited so the value can be within the intervals of RGB values and the after limitation the values after being limited become the RGB values in the encrypted image. The decryption process is the inverse of encryption process, which enables the encrypted image to become the initial image before encryption. The program for encrypting and decrypting image are made using Java programming language with Netbeans IDE 8.2 software. The result of this implementation on image file donbass.jpg with the length of Vigenere key of 5 those are k1=144, k2=166 , k3=38 , k4=204 , k5=98, and RSA Algorithm keys are n=2201, e=1139, d=59, the results from the encrypted image is a visually very different image from the initial image. While in the decryption process, the encrypted image is able to be decrypted back to the initial image.