Explore the vast range of titles available.

Malaria is a pressing medical issue in tropical and subtropical regions. Currently, the manual microscopic examination remains the gold standard malaria diagnosis method. Nevertheless, this procedure required highly skilled lab technicians to prepare and examine the slides. Therefore, a framework encompassing image processing and machine learning is proposed due to inconsistencies in manual inspection, counting, and staging. Here, a standardized segmentation framework utilizing thresholding and clustering is developed to segment parasites’ stages of P. falciparum and P. vivax species. Moreover, a multi-stage classifier is designed for recognizing parasite species and staging in both species. Experimental results indicate the effectiveness of segmenting thick smear images based on Phansalkar thresholding garnered an accuracy of 99.86%. The employment of variance and new transferring process for the clustered members, enhanced k-means (EKM) clustering has successfully segmented all malaria stages with accuracy and an F1-score of 99.20% and 0.9033, respectively. In addition, the accuracies of parasite detection, species recognition, and staging obtained through a random forest (RF) accounted for 86.89%, 98.82%, and 90.78%, respectively, simultaneously. The proposed framework enables versatile malaria parasite detection and staging with an interactive result, paving the path for future improvements by utilizing the proposed framework on all others malaria species.

[...]frames are to be extracted from the input video [4]. Face detection Emotions are featured mainly from the face. [...]it is crucial to detect the face to obtain facial features for further processing and recognition. [...]resizing is very important to shorten the processing time. [...]better resizing techniques should be used to preserve image attributes after resizing [8]. The accuracy of the classification depends on whether the features are well representing the expression or not. [...]the optimization of the selected features will automatically improve classification accuracy [9].

Background: Infectious illnesses are a serious health concern in Indonesia. Widespread use of self-medication by the community increases the risk of developing multi-drug resistant (MDR) bacteria. This study assessed the potential of sappan wood as an inhibitor of extendedspectrum beta-lactamase (ESBL) encoded by blaSHV, blaTEM and blaCTX-M genes. Method: In silico testing was conducted to develop an effective and economical starting strategy. Thereby, this study significantly advances the development of novel treatments to combat antibiotic resistance. Using clavulanic acid as the benchmark medicine, the potency of the betalactamase inhibitor brazilein was predicted. Using the Molegro Virtual Docker computer tool, docking was performed to estimate the chemical and physical properties of the compounds, as well as the biological activity of brazilein toward the required receptor. The receptors used were SHV1 beta-lactamase, PDB code: 2H0T; TEM-1 beta-lactamase, PDB code: 4OQG and CTX-M-14 betalactamase, PDB code: 6VHS. Data analysis was performed by comparing the binding energies of the docking results between the ligands and the target receptor. The more stable the bond that formed between the ligand and the target receptor, the lower the bond energy. Results: The in silico test results on the blaSHV gene were as follows: binding energy of ligand MA4_400[A] = −100.699, brazilein = −82.206, clavulanic acid = −79.3704; in the blaTEM gene: ligand bond energy 2UL_301[B] = −107.681, brazilein = −82.0296, clavulanic acid = −103.3; in the blaCTX-M gene: X57_301[A] ligand bond energy = −86.6197, and brazilein = −88.1586, clavulanic acid = −101.933. Conclusion: The findings of this study demonstrate the significant potential of brazilein sappan wood to block the beta-lactamase activity of blaCTX-M.

Augmented Reality (AR) is a technology that combines 2 dimensions with 3 dimensions in realtime. Augmented reality can be applied in various things, one of them is in the field of education. In the world of augmented reality technology education can be used as a means of introduction of aquatic animals. Augmented reality serves to display 3-dimensional objects and their information by scanning markers. Markers made as scanning objects are carried out by the smartphone camera and will display objects in 3 dimensions. Based on testing the distance measurement of the camera against the marker, the optimal distance obtained from the camera can read the marker at a distance of 8 - 77 cm. This augmented reality application has been running well on smartphones and has featured 3-dimensional objects along with its information. Applications that have been made to facilitate the introduction of aquatic animals.

Threshold secret sharing is one of the cryptographic techniques to secure a confidential data by dividing or distributing the data into several parts called shares, each part of the data does not provide any information about the secret in question if it is not combined with other parts. In general, thescheme is secret sharing divided into three namely Threshold, Prevention and Disenrollment schemes. The scheme applied to this application is the threshold secret sharing. Threshold secret sharing, has a concept that allows n people participated to hold fractional(share) different generated from s. Meanwhile, to reconstruct the data, it is necessary to have different pieces ofshare, each of which is held by a different participant. The security system that will be created using one of the platforms commonly used today is Visual Basic.NET

This research discusses encryption and security description of files in images with hill cipher cryptography and steganogography using the lsb + 1 method, testing the results of cryptographic and stegano data security applications that are equipped with cryptography, then from the results the trial was done with the hill cipher method, by displaying data in the form of files that want to do the data security. The results of the DIPA trial with a file size of 17.2 MB after being encrypted into RNPF with a file size of 17.2 MB.

Background Indonesia's hospital‐based Severe Acute Respiratory Infection (SARI) surveillance system, Surveilans Infeksi Saluran Pernafasan Akut Berat Indonesia (SIBI), was established in 2013. While respiratory illnesses such as SARI pose a significant problem, there are limited incidence‐based data on influenza disease burden in Indonesia. This study aimed to estimate the incidence of influenza‐associated SARI in Indonesia during 2013‐2016 at three existing SIBI surveillance sites. Methods From May 2013 to April 2016, inpatients from sentinel hospitals in three districts of Indonesia (Gunung Kidul, Balikpapan, Deli Serdang) were screened for SARI. Respiratory specimens were collected from eligible inpatients and screened for influenza viruses. Annual incidence rates were calculated using these SIBI‐enrolled influenza‐positive SARI cases as a numerator, with a denominator catchment population defined through hospital admission survey (HAS) to identify respiratory‐coded admissions by age to hospitals in the sentinel site districts. Results From May 2013 to April 2016, there were 1527 SARI cases enrolled, of whom 1392 (91%) had specimens tested and 199 (14%) were influenza‐positive. The overall estimated annual incidence of influenza‐associated SARI ranged from 13 to 19 per 100 000 population. Incidence was highest in children aged 0‐4 years (82‐114 per 100 000 population), followed by children 5‐14 years (22‐36 per 100 000 population). Conclusions Incidence rates of influenza‐associated SARI in these districts indicate a substantial burden of influenza hospitalizations in young children in Indonesia. Further studies are needed to examine the influenza burden in other potential risk groups such as pregnant women and the elderly.

The Parigi Formation has been a significant gas exploration in West Java Basin. This is due to their abundance, and they occur at shallow depths (800-1000 m). The main objective of this study was to focus on the characteristics and distribution patterns of the shallow carbonate to be used for gas storage. The case will be focused on Parigi Formation as a reservoir carbonate in the depleted oil and gas field in West Java Basin. These build-ups are better developed in onshore West Java Basin, where they exhibit coral reef frameworks and reach over 450 m in thickness. Moreover, Parigi Formation carbonate is well exposed in Palimanan, West of Cirebon City, and it is divided into four types of lithofacies. Preservation conditions, storage capacity, effective injection, and production are important factors in underground gas storage. In the geological site, factors that need to be evaluated are as follows: a reservoir, trap sealing, and tectonic activities in the surrounding area. However, in the USA and Europe, the porous reservoir formations such as sandstone or carbonate at depths of 500 - 1800 meters are common in storing natural gas in large volumes size. Ultimately, according to this case study, it has been found out that the most influential parameters for storing natural gas are porosity and permeability (petrophysical properties).