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International Journal of Advances in Applied Sciences
ISSN : 22528814     EISSN : 27222594     DOI : http://doi.org/10.11591/ijaas
International Journal of Advances in Applied Sciences (IJAAS) is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of applied and theoretical sciences. The journal is designed to serve researchers, developers, professionals, graduate students and others interested in state-of-the art research activities in applied science areas, which cover topics including: chemistry, physics, materials, nanoscience and nanotechnology, mathematics, statistics, geology and earth sciences.
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Articles 20 Documents
Search results for , issue "Vol 13, No 1: March 2024" : 20 Documents clear
Mamdani fuzzy-based water quality monitoring and control system in vannamei shrimp farming using the internet of things Muhammad Qomaruddin; Andi Riansyah; Hildan Mulyo Hermawan
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp180-187

Abstract

Indonesia's vast ocean expanse, spanning two-thirds of its land, is a treasure trove of marine resources, with shrimp being a vital commodity in the country's fisheries exports. To ensure successful shrimp production, maintaining optimal water conditions is paramount, necessitating extensive, large-scale monitoring. Enter our innovative prototype an internet of things (IoT) system designed for comprehensive pond water quality oversight. This smart system monitors crucial parameters like pH, turbidity, temperature, and dissolved solids in vannamei shrimp cultivation. The Mamdani fuzzy approach dynamically adjusts operations in response to changing weather conditions, fine-tuning both pump and windmill speeds. This adaptive methodology significantly improves water quality control, enhancing overall efficiency. Our IoT infrastructure ensures real-time monitoring and control, creating an ideal environment for shrimp cultivation. The Mamdani fuzzy technique’s effectiveness shines in adapting to dynamic environmental shifts. Noteworthy findings underscore the system's ability to automate and elevate pond water quality, promising increased shrimp production. This technology has the potential to revolutionize traditional shrimp farming, particularly in regions like Rembang, by promoting sustainable aquaculture practices.
Enrichment of microscopic photographs by utilizing CNN regarding soil-transmitted helminths identification Rio Andika Malik; Marta Riri Frimadani; Dwipa Junika Putra
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp46-53

Abstract

Soil-transmitted helminth (STH) infection remains a significant global health challenge, affecting millions of people, particularly in developing countries. A convolutional neural network (CNN) approach to optimize the detection of STH infections in microscopic images. The study aims to assess the effectiveness of the CNN model in identifying and classifying STH worm eggs accurately. The research employs MATLAB as the primary tool for conducting experiments and validation tests. By implementing image preprocessing techniques to enhance image quality and applying precise segmentation methods, the CNN model is trained on a dataset of microscopic images to learn and classify STH infections effectively. The validation test results demonstrate that the CNN model achieved a high accuracy rate of 92.31% in classifying STH infections. This accuracy surpasses traditional methods, which are time-consuming and susceptible to human errors. This study underscores the importance of integrating artificial intelligence, particularly CNN, into the healthcare domain to support detecting and diagnosing diseases requiring specialized expertise, such as STH infections. The findings of this research can serve as a valuable reference for researchers, medical practitioners, and data scientists in leveraging artificial intelligence to enhance the quality of healthcare services, leading to positive impacts on society worldwide.
TherapyBot: a chatbot for mental well-being using transformers Deepak Dharrao; Shilpa Gite
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp1-12

Abstract

The field of natural language processing (NLP) and conversational artificial intelligence (AI) has one ingenious application in the psychological space. Depression and anxiety are two major issues that the world is facing, with close to 41% of adults reporting these symptoms in the United States alone, as of December 2020. It has also been observed that most of the people are not open about it. As a result, it is critical to address this issue on a global scale. Developed countries reportedly have 9 psychiatrists per 100,000 people. One way to mitigate this is the use of chatbots. We propose a transformer-based methodology to build a therapy bot that has been trained on a combination of open-domain conversations from a publicly available dataset and therapist-client conversations from a self-constructed dataset. This end-to-end data-driven model shows quality performance in conversations and adds value by aiding in the case of mental health issues. The proposed architecture is proven to be effective in its usability in the psychological space for both single-turn and multi-turn dialogue. The performance of the proposed system shows loss is 0.29 and perplexity is 1.34, both metrics keeps gradually decreasing and it means an improvement in performance of chatbots system.
Business enterprise architecture in fitness center using the open group architecture framework Eric Jonathan; Johanes Fernandes Andry
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp160-167

Abstract

Sports currently have an impact on human life, especially in the health sector. One way of exercising that is popular with many people today is by exercising at the fitness center. One of them is a fitness center located in Bandung. This research aims to obtain design results that can adapt business processes in fitness centers and can help the company's performance so that its vision and mission are achieved. The current business process is still experiencing problems because business has not yet been integrated with information technology (IT), so a business process proposal was made using the business architecture method. By conducting interviews and observations, data can be collected. From this data, it can be seen that business implementation in fitness centers is not yet optimal, so it is necessary to develop information system technology that is in line with the company's business. This technology development is based on business architecture which produces a company blueprint and is assisted by the open group architecture framework (TOGAF) which can help analyze company needs. The results of this research are in the form of recommendations which will later be proposed so that benefits for the company can be achieved more quickly.
Performance assessment of routing protocols for campus area emergency delay-tolerant network Sujan Chandra Roy; Muhammad Sajjadur Rahim; Md Ashraful Islam
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp54-62

Abstract

Handheld devices have recently become an indispensable part of our daily lives. These devices always require an end-to-end connection for proper message transmission. Message transmission will be halted if the connection fails. In this case, delay-tolerant networks (DTNs) are preferable. One of the most important applications of DTN is the transmission of emergency messages among rescue personnel in the aftermath of a disaster. Previously, we created a simulation map in the Rajshahi University (RU) campus area of Bangladesh and studied the performance of DTN routing protocols. This paper used our developed simulation map to evaluate the performance of DTN and social-based routing protocols for emergency message circulation in the RU campus area when traditional communication networks are unavailable. We conducted extensive experiments with the opportunistic network environment (ONE) simulator for evaluations. The performance analysis is based on the delivery ratio, average latency, transmission cost, and average hop count of each group when the message size and node density are changed. According to the simulation results, dLife outperforms all other routing protocols in terms of delivery ratio, while the Spray-and-Focus routing protocol outperforms all other performance metrics.
Detecting and identifying occluded and camouflaged objects in low-illumination environments Gaytri Bakshi; Alok Aggarwal
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp188-196

Abstract

One of the prevailing areas of contemporary research involves the differentiation and identification of diverse objects within a given scene through automated systems. The field of study under consideration presents a multitude of obstacles, including but not limited to issues such as diminished lighting conditions, occlusion, and camouflage. The captured image exhibits variations in illumination, resulting in uneven brightness, reduced contrast, and the presence of noise. The fundamental basis of computer vision algorithms lies in the process of extracting features from datasets and subsequently discerning these features through neural networks. The task of extracting distinct feature key points from images captured under low lighting conditions is exceedingly challenging. To address this issue, the present study seeks to employ deep learning models to implement image enhancement techniques specifically designed for low-light conditions. The primary emphasis lies in obtaining key feature points that are differentiable, thereby enabling the utilization of this annotated data for specific tasks such as object detection. The task of identifying occluded and camouflaged objects has been successfully accomplished, yielding an impressive accuracy rate of 93% in total. The mean average precision has been achieved as 85% which is reasonably high compared to many earlier works.
Taxonomic attribution of the haplic gleysols of the Azerbaijan Republic in world reference base for soil resources Sultan Huseynova Maharram; Amin Ismayilov Ismayil; Maharram Babayev Pirverdi; Ali Jafarov Musa
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp116-122

Abstract

The aim of the research was to obtain new information about the genesis, status, diagnostic features, and properties of the meadow-boggy soils of the Azerbaijan Republic and to perform the taxonomic attribution of those soils in accordance with the international soil classification system in compliance with the world reference base (WRB) for soil resources. Field experiments, physical, and chemical analyses of soil samples were carried out by standard methods. The morphological properties of the meadow-boggy soils in the Greater Caucasus and Lankaran regions of Azerbaijan have been characterized. Carbonate sediments are almost always invisible in the upper layers (13.27-17.14% (No 426); 10.46-27.39% (No 5); 0.87-1.33% (No 55)). According to the humus content, they are not highly humic (1.44-1.85% (No 426); 0.90-1.58% (No 5); 3.10-3.29% (No 55) in the upper layers). The magnitude of the reaction of the soil solution varies from 8.0 to 8.5. For the first time, an attempt is made to determine the name of meadow-boggy soils in accordance with the international soil classification in compliance with the WRB 2015. The above soils are assigned to the gleysols reference soil group (RSG) with various principal and supplementary qualifiers.
Local area network architecture design at Nurul Jalal Islamic Boarding School, North Jakarta Andri Sahata Sitanggang; R. Fenny Syafariani; Novrini Hasti; Febilita Wulan Sari; Dhara Pasya
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp123-133

Abstract

A computer network is a telecommunications network that allows computers to communicate with each other by exchanging data. At Nurul Jalal Islamic Boarding School, they have taken advantage of advances in computer network technology, but have not been fully connected properly. Therefore, in this research, a local area network (LAN) architecture that is connected to speedy internet will be built and developed. The design of this network architecture includes designing a connection to the internet speedy network and designing a computer lab architecture that is connected to the network at the Nurul Jalal Islamic Boarding School. This study aims to design the existing technology with the system and add technologies and systems that do not yet exist so that they can be integrated into a computer network connected to the speedy internet network. It is hoped that this research will help teachers and students of Nurul Jalal Islamic Boarding School in exploring information so that it can help effective and efficient learning.
A novel reduced-switch multi-level inverter based multi-device universal power-quality conditioner for PQ enhancement Naarisetti Srinivasa Rao; Pulipaka Venkata Ramana Rao
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp168-179

Abstract

The reduced-switch multilevel inverter (RSMLI) has garnered significant attention across various industries as a viable alternative to conventional multilevel inverter (MLI) topologies. In the realm of medium voltage high-power applications, the topologies of resonant switched MLIs are regarded as advanced due to their development with a reduced number of switching elements. The primary emphasis of the customizable multi-device universal power-quality conditioner (MD-UPQC) device is on the design and development of a significant RSMLI topology to improve power-quality (PQ) features. This study presents the development of a novel 5-level RSMLI-based MD-UPQC device, designed specifically for addressing power-quality concerns in multi-feeder distribution networks. The device facilitates uninterrupted power flow between the feeders, thereby mitigating power-quality issues. The 5-level RSMLI topology possesses the capability to decrease the necessity for a larger quantity of gate-drive circuits by implementing a switching-logic design utilizing the reduced-carrier-based pulse width modulation (PWM) technique. The 5-level RSMLI-MDUPQC device incorporates a unified voltage-current reference (UVCR) control scheme to ensure efficient operation. The functionality and efficacy of the proposed RSMLI-MDUPQC device have been assessed using the MATLAB/Simulink software tool, with the evaluation conducted under different PQ conditions. The simulation outcomes are presented for analysis and interpretation.
Artificial intelligence assisted insights into Bali’s destination image: sentiment and thematic analyses of TripAdvisor reviews Putu Chris Susanto; Putu Wida Gunawan; I Gde Dhika Widarnandana
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp63-72

Abstract

This study applies sentiment and thematic content analyses based on natural language processing (NLP) to gain valuable insights into the perceived image of Bali as a tourist destination. This study addresses the gap in how to realize the benefits of big data analytics in applied research, by using more approachable tools for researchers with limited programming skills and coding experience. A total of 6,800 TripAdvisor reviews of Bali’s top 12 tourist attractions between May 2019 and April 2023 were scrapped. The authors used Bardeen.ai for data mining and Atlas.ti for qualitative data analyses. Sentiment analysis revealed an overwhelmingly positive sentiment (70.4%) towards Bali’s tourist attractions, indicating a positive destination image. Post-pandemic tourists tend to express more positive sentiments in their reviews compared to pre-pandemic. Thematic content analysis indicated that positive sentiments are strongly related to satisfaction, positive experiences, enjoyment, and excitement, while environmental concerns and dissatisfaction are potentially harmful to Bali’s destination image. The study provides valuable insights into tourists’ emotional sentiments, perceptions, and thematic patterns of behavior, which can inform tourism marketers and destination strategists, and contribute to the larger discussion of utilizing big data analytics in tourism marketing research.

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