International Journal of Advances in Applied Sciences
Not a member yet
668 research outputs found
Sort by
Design and implementation of an internet of things-based automatic waste sorting system
Get PDFThis paper presents the design and development of an internet of things (IoT)-based automatic waste sorting system that classifies waste into four categories: organic, non-organic, metal, and others. The system integrates an Arduino Mega for control, multiple proximity sensors (inductive, capacitive, and infrared), and ultrasonic sensors for level detection, and a NodeMCU ESP8266 for real-time monitoring via the Blynk platform. A total of 100 tests (25 per bin) were conducted. Classification success rates were 92% (metal), 80% (inorganic), 84% (organic), and 100% (others), resulting in an overall accuracy of 89%. The main contribution is a combined automatic sorting and IoT monitoring framework suitable for campus-scale deployment
Quantum-inspired magnetic resonance imaging sequence optimization for detecting neurological diseases
Get PDFAccording to a research study by the National Institutes of Health, India, a magnetic resonance imaging (MRI) holds 89% diagnostic accuracy for acute stroke, while a computed tomography (CT) holds only 54%. Means there is still 11% area of improvement for accuracy measures required and there is 84% specific in identifying nerve enlargement. The possible solution is to use quantum computing; this is new era of technology in advanced design and implementation for computing techniques as compared with that of classical computers. With the goal of improving patient care, this is the area-of research using quantum technology to solve the neurological disorders. MRI and Microsoft’s quantum-inspired algorithms to enhance approach to detecting neurological disorders. To improve accuracy of MRI results in less time, an approach called magnetic resonance fingerprinting (MRF) was explored. This paper mainly focused on optimizing the sequence using Microsoft azure simulator. By generating an optimized pulse sequence and map to the accurate predefined patterns, able to create a solution that improves the diagnostic capability of MRI. Conventional computers will take long time to predict, but accuracy may alter. The proposed quantum-inspired optimization improved MRI diagnostic accuracy up to 92%, with faster sequence optimization compared to classical methods. This simulation-based proof of concept demonstrates potential for enhanced neurological disease detection while acknowledging current limitations such as simulator dependency and limited datasets
Test rig development for load test of pipe saddle support
Get PDFPipe saddle support is a structure commonly used to support horizontal steel pipe. It prevents direct contact between the pipe and the support. Pipe saddle support can experience displacement due to pipe movement and insufficient stress analysis. Given these concerns, conducting a load test is essential to determine the stress on pipe saddle supports. However, a universal testing machine (UTM) is not suitable for this purpose due to the size limitation. Therefore, this study proposed a test rig setup for the pipe saddle support load test. The test rig consists of a portal frame secured by an underground locking system featuring a strong floor. Additionally, an actual pipe is utilized to replicate actual loading conditions on the pipe saddle support. The applied load is measured using a load cell, with a custom-designed bracket to ensure precise load transfer. Finally, the pipe saddle support specimen is bolted to a base support to maintain stability during the load test. Stress analysis using finite element analysis (FEA) demonstrated that the test rig is suitable for conducting load tests on the specimens with a maximum force of 80 kN. FEA confirmed that the test rig operates within a safety factor of 1.3
A method classifying the domestic tourist destination base similarity measuring
Get PDFThe classification problem is crucial in business, providing an effective method for supporting search activities in areas such as e-commerce, education, and marketing. This has become especially important in the wake of the COVID-19 pandemic, which has increased the need to promote and stimulate domestic tourism. This research focuses on recommending tourist destinations based on historical search data related to domestic tourism. The study uses techniques like term frequency-inverse document frequency (TF-IDF) weight vector analysis and similarity measures to calculate recommendation scores. Data was collected from various tourism websites, covering destinations across all 63 provinces and cities in Vietnam. Experiments were conducted using three approaches: cosine similarity, the brute force algorithm, and long short-term memory (LSTM) for long-text processing. The results indicate that similarity-based methods produce recommendations that closely match user preferences. For full-sentence queries, the brute force algorithm delivers more accurate results, while LSTM provides faster processing times. These findings offer businesses multiple strategies for improving recommender systems in practical applications
Eco-friendly durable asphalt using maleic-modified rosin ester
Get PDFAsphalt, a crucial component of transportation infrastructure, particularly in regions with high traffic loads and extreme climates, often lacks the necessary elasticity, strength, and durability. Various asphalt modifiers have been explored, but many struggle with cost, thermal stability, and environmental impact. This study, however, investigates maleic-modified rosin ester, a gum rosin derivative, as a sustainable and cost-effective asphalt modifier. The base asphalt was heated to 150-190 °C, sheared at 100 rpm, and combined with 4-20% maleic rosin ester and sulfur. The modified asphalt was subjected to tests, including penetration, softening point, ductility, density, kinematic viscosity, Fourier transform infrared (FTIR), and dynamic shear rheometer (DSR) tests. The results are promising, showing that maleic rosin ester enhances penetration resistance and softening points while maintaining ductility and viscosity within acceptable limits. Chemical analysis confirmed improved adhesion, crosslinking, and thermal stability, making the modified asphalt more deformation-resistant. This suggests that maleic-modified rosin ester is a viable alternative to synthetic polymers, offering improved durability and sustainability. The enhanced durability of the modified asphalt provides confidence in its long-term performance, making it a reliable choice for transportation infrastructure
Application of turmeric as heat stress therapy for broiler chickens
Get PDFThis study aims to analyze the productivity of broilers kept in heat-stress conditions by drinking water mixed with turmeric (Curcuma domestica). This research was conducted in the Politeknik Negeri Lampung, Indonesia cage in September 2023. This study uses the experimental method by comparing the turmeric treatment group with as much as 500 mg/kg of chicken body weight which will be compared with the group without treatment (control). The results of the research on the provision of drinking water given turmeric (Curcuma domestica) to broilers kept under heat stress, based on the results of the study it can be concluded that the provision of drinking water mixed with turmeric (Curcuma domestica) as much as 500 mg/kg body weight of chickens on the productivity of broilers reared under heat stress conditions able to increases consumption and weight gain in chickens and can reduce feed conversion in broiler chickens experiencing heat stress
Identification and antioxidant activity test of β-tocopherol from Dompu corn oil as anti-aging
Get PDFCorn is a well-cultivated food crop that is grown extensively worldwide. The used portion of corn is its seeds, which are rich in oil. The objective of this study is to separate and characterize tocopherol from corn oil in Dompu, Sumbawa by employing spectroscopic techniques such as ultraviolet (UV) spectrophotometry, ultra-performance liquid chromatography (UPLC), nuclear magnetic resonance (NMR), and liquid chromatography-mass spectrometry (LC-MS). Subsequently, the in-vitro antioxidant activity of the tocopherol was assessed. 1 kilogram of dry maize kernels subjected to 70% ethanol extraction yielded 30 grams (35 ml) of corn oil. The purified isolate obtained from the fractionated extract, using radial chromatography, demonstrated the presence of tocopherol. The isolated sample exhibited the presence of beta-tocopherol. Beta-tocopherol's anti-aging properties were assessed by conducting an in-vitro antioxidant activity test utilizing the tyrosinase enzyme. The IC50 value obtained was 83.954±2.849 ppm. The IC50 value indicates that beta-tocopherol possesses significant antioxidant activity, making it suitable for usage as a primary ingredient in cosmetics and pharmaceutical products
Content based image retrieval using visual geometric group19 with Jaccard similarity measure
Get PDFContent-based image retrieval (CBIR) is an important research area that focuses on emerging techniques for handling large image collections and enabling efficient retrieval. The main challenge of image retrieval is to extract relevant feature vectors for image description. Therefore, visual geometric group 19 (VGG19) with Jaccard is proposed in this research for CBIR. The VGG19 allows to capture of hierarchical features, and it is appropriate for texture and fine detail characteristics. It enables to production of robust and discriminative feature representations because of numerous convolutional layers. The Jaccard is utilized as a similarity measure among feature vectors by comparing the union and intersection of feature sets. It is helpful to manage sparse and higher-dimensional data that provides a fast and accurate image retrieval process. The Caltech 256 and Corel 1K datasets are considered and it is preprocessed by image resizing and normalization. The raw images are resized to ensure dataset similarity and normalized into the range of 0 and 1. The metrics such as recall, f-measure, and average precision are used to calculate the VGG19-Jaccard performance. The VGG19-Jaccard achieves average precision of 99.0 and 99.8% for Caltech 256 and Corel 1K datasets compared to the two-stage CBIR technique
Analysis of ice creams from goat milk kefir and red dragon fruit
Get PDFIce cream from goat milk kefir is lower lactose than cow milk kefir. Combining goat milk kefir with red dragon fruit in ice cream formulations can improve the quality of the product. This study aims to determine the sensory characteristics, total solid, total flavonoid, and antioxidant activity of goat kefir-based ice cream flavored red dragon fruit as quality evaluation. The study used a completely randomized design with 4 treatments and 3 replications. The treatment was the ratio of goat kefir and dragon fruit, including 40:60, 50:50, 60:40, and 70:30 in the ice cream mixture. 30 panelists participated in the organoleptic test. Total solid testing referred to SNI 01-3713-1995. Determination of total flavonoid content was carried out by forming AlCl3 complexes spectrophotometrically and assaying antioxidant activity used 2.2-diphenyl-1-picrylhydrazyl (DPPH) method. The results showed that there was no significant difference in the organoleptic test for taste, color, and texture. The results of the total solids test showed that the higher the addition of goat kefir to ice cream, the lower the total solids produced. While the addition of goat kefir increased the total flavonoids in ice cream. The antioxidant activity with the best formulation of 50:50 was categorized as moderate level, which is 136.59 ppm
Combining XGBoost and hybrid filtering algorithm in e-commerce recommendation system
Get PDFThis study proposes a hybrid filtering algorithm (HFA) that combines extreme gradient boosting (XGBoost), content-based filtering (CBF), and collaborative filtering (CF) to improve recommendation accuracy in electronic commerce (e-commerce). XGBoost first leverages demographic data (e.g., age, gender, and location) to address cold start conditions, producing an initial product prediction; CBF refines this prediction by measuring product similarities through term frequency-inverse document frequency (TF-IDF) and cosine similarity, while CF (implemented via singular value decomposition) further incorporates user interaction patterns to enhance recommendations. Experimental results across multiple datasets demonstrate that HFA consistently outperforms standalone XGBoost in key metrics, including precision, F1-score, and hit ratio (HR). HFA’s precision often exceeds 90%, indicating fewer irrelevant recommendations. Although recall levels remain modest, HFA exhibits stronger adaptability under cold start scenarios due to its reliance on demographic features and user-item interactions. These findings highlight the efficacy of combining advanced machine learning with hybrid filtering techniques, offering a more robust and context-aware solution for e-commerce recommendation systems