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31,456 Article Results

Systematic review of artificial intelligence with near-infrared in blueberries

10.11591/ijai.v13.i4.pp3761-3771
Liset Cayhualla Amaro , Sebastian Rau Reyes , María Acuña Meléndez , Christian Ovalle
The fruit quality has a direct impact on how the fruit looks and how tasty the fruit is. The correct use of tools to determine fruit quality is essential to offer the best product for the final consumer. This study has used the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. The study objective was elaborate a systematic literature review (SLR) about research of the application of techniques based on artificial intelligence to analyze indicators obtained by near infrared spectroscopy (NIRS) and chemometrics to determine the quality of fruits, including blueberries. The most frequently addressed indicator is the soluble solids concentration (SSC) which was used in several studies with techniques such as support vector machines (SVM) and convolutional neural networks (CNN). According to the results obtained, it is possible to use these techniques to predict blueberry quality indicators. There was an acceptable performance and high accuracy of these models. However, future research could cover other techniques and help to provide better quality control of products in food industries.
Volume: 13
Issue: 4
Page: 3761-3771
Publish at: 2024-12-01

Plant disease classification using novel integration of deep learning CNN and graph convolutional networks

10.11591/ijeecs.v36.i3.pp1721-1730
Saka Uma Maheswara Rao , Keshetti Sreekala , Pulluri Srinivas Rao , Nalla Shirisha , Gunnam Srinivas , Erry Sreedevi
Plant diseases present substantial challenges to global agriculture, significantly affecting crop yields and jeopardizing food security. Accurate and timely detection of these diseases is paramount for mitigating their adverse effects. This paper proposes a novel approach for plant disease classification by integrating convolutional neural networks (CNNs) and graph convolutional networks (GCNs). The model aims to enhance classification accuracy by leveraging both visual features extracted by CNNs and relational information captured by GCNs. Using a Kaggle dataset containing images of diseased and healthy plant leaves from 31 classes, including apple, corn, grape, peach, pepper bell, potato, strawberry, and tomato. Standalone CNN models were trained on image data from each plant type, while standalone GCN models utilized graph-structured data representing plant relationships within each subset. The proposed integrated CNN-GCN model capitalizes on the complementary strengths of CNNs and GCNs to achieve improved classification performance. Through rigorous experimentation and comparative analysis, the effectiveness of the integrated CNN-GCN approach was evaluated alongside standalone CNN and GCN models across all plant types. Results demonstrated the superiority of the integrated model, highlighting its potential for enhancing plant disease classification accuracy.
Volume: 36
Issue: 3
Page: 1721-1730
Publish at: 2024-12-01

Development of a primary reference material for the analysis of BTEX and chlorobenzenes in environmental samples

10.11591/ijaas.v13.i4.pp985-990
Ibrahim F Tahoun , Mohamed Adly Gab-Allah
Benzene, toluene, ethylbenzene, and xylene (BTEX) and chlorobenzenes are measured in all environments as part of world official pollution control programs. The health impact of these analytes increased the relevance of the validity and comparability of the measurement results. Therefore, equipment performance, implementation of test methods, and accuracy of results need to be verified through internal and external quality control programs. Herein, a new certified reference material (CRM) for benzene, toluene, chlorobenzene, ethylbenzene, o-xylene, 1,2-dichlorobenzene, 1,3-dichlorobenzene and 1,4-dichlorobenzene, and m, p-xylene has been produced and characterized by an approach that is metrologically valid and complies with ISO 17034:2016 and ISO 33405:2024 standards. The reference material was prepared gravimetrically and certified values were calculated based on masses of pure components. Homogeneity results proved that the between-ampule heterogeneity was negligible in comparison with the method precision. The stability of the material was evaluated for both long-term storage and dispatch and no measurable loss of analytes was observed within one year period. The developed certified reference material with small uncertainties values will support regulatory bodies, environmental protection agencies, and testing laboratories in their efforts to improve the quality of motoring results and compliance with regulations.
Volume: 13
Issue: 4
Page: 985-990
Publish at: 2024-12-01

Evaluating telemedicine diabetes mellitus: a mobile health app for type-2 diabetes

10.11591/ijaas.v13.i4.pp791-799
Muhammad Zakwan Abdul Karim , Norashikin M. Thamrin , Ruhizan Liza Ahmad Shauri , Rozita Jailani , Mohd Haidzir Abd Manaf , Nurul Amirah Mustapa
Telemedicine diabetes mellitus (Tele-DM) mobile health (mHealth) tool functionality, usefulness, and user feedback were examined in this study. Data from nine distinct users of type-2 diabetes (T2D) patients, healthcare professionals (HCPs), and administrators was analyzed to determine functionality. Data retrieval times increased with database user data amount, according to the study. A 3-month program with five T2D patients reduced weight (0.98 kg) and Hemoglobin A1c (HbA1c) (0.34%). This shows that Tele-DM helps manage diabetes, but more participants are needed to confirm. Nine Tele-DM customers were satisfied with the app's reception, according to 14 online questionnaires. Overall, Tele-DM simplifies diabetic self-management in a novel way. This study shows its potential to transform diabetes management and address major healthcare issues.
Volume: 13
Issue: 4
Page: 791-799
Publish at: 2024-12-01

Quality of life among physicians in Egypy and its influencing factors: a cross-sectional study

10.11591/ijphs.v13i4.23946
Amira Ismail Abdelrahman , Nora Atef Goda , Mohamed Mahmoud Bendary
Doctors have an essential role in healthcare service, and their quality of life (QoL) is crucial for their professional satisfaction and overall well-being. This study assessed the QoL among physicians and explored the influencing factors that affect it. This cross-sectional study was carried out using a self-administered Internet survey. The survey was focused on physicians employed at various hospitals and clinics in Egypt. Data on participants' demographics, work-related factors, and QoL were collected using WHOQOL-BREF. WHOQOL-BREF questionnaire measures a participant's perception of their life quality across various domains, including general health, physical well-being, psychological health, social relationships, and the environment. The scores for each domain are calculated based on participants' responses to specific items, with higher scores indicating a better QoL. The QoL scores were 3.57±1.02 for the general health domain, 12.93±2.49 for physical domain, 12.29±2.67 for psychological domain, 12.87±3.20 for social domain, and 11.00±2.58 for environmental domain. The overall QoL score was 3.64±0.835. The findings indicate a moderate QoL among the participating physicians. The physicians' QoL domains were affected by age, sex, education level, marital status, chronic disease, smoking, speciality, working hours per week, extra working hours, and work experience.
Volume: 13
Issue: 4
Page: 1696-1703
Publish at: 2024-12-01

A neural machine translation system for Kreol Repiblik Moris and English

10.11591/ijai.v13.i4.pp4976-4987
Sameerchand Pudaruth , Sheeba Armoogum , Nirmal Kumar Betchoo , Aneerav Sukhoo , Vandanah Gooria , Abdallah Peerally , Mohammad Zafar Khodabocus
Although Google Translate is a widely used machine translation service that supports 133 languages, it does not incorporate support for the Kreol Repiblik Moris (KRM) language. Addressing this limitation, the current research focuses on enhancing the accuracy and fluency of machine translation between KRM and English through natural language processing and deep neural machine translation techniques. In this study, a machine translation system using a transformer model trained with a dataset of 50,000 parallel corpora has been developed. The model was evaluated using manual translations and the bilingual evaluation understudy (BLEU) score. A score of 31.46 for translating from KRM to English and 28.15 for translating from English to KRM was achieved. To our knowledge, these are the highest BLEU scores for translation between these two languages. This is due to utilising the largest dataset and extensive atomic words from the KRM dictionary. This successful interdisciplinary funded project led to the setting up of a free online translation service and a smartphone app for Mauritian citizens and tourists.
Volume: 13
Issue: 4
Page: 4976-4987
Publish at: 2024-12-01

Mitigating blackhole attacks in wireless body area network

10.11591/ijeecs.v36.i3.pp1555-1563
Goumidi Mohammed Abdessamad , Zigh Ehlem , Ali-Pacha Adda Belkacem
In this paper, we aimed to develop a trusted secured routing Ad-hoc on-demand distance vector (AODV) protocol to fight against blackhole attacks within the wireless body area network (WBAN). The trusted secure routing protocol incorporates a routing strategy based on trust value to detect malicious nodes based on their trust value, a routing technique based on node residual energy to select the node with the highest residual energy during the communication process, and a hybrid cryptography algorithm that merges the Affine cipher with the modified RSA cipher algorithm to secure communication against malevolent biomedical sensor attacks. Simulation outcomes demonstrate that the suggested protocol outperforms the traditional AODV routing protocol in all evaluation metrics, including data rate, energy consumption, and packet delivery ratio. Its main strength is that it considers several factors, like illegitimate medical sensor detection, efficient network energy use, and secure data transmission, unlike similar secured routing protocols. Furthermore, the hybrid cipher algorithm improves the effectiveness and increases the security level of sensitive data compared to traditional cipher algorithms such as the Affine cipher and the RSA cipher.
Volume: 36
Issue: 3
Page: 1555-1563
Publish at: 2024-12-01

The production-inventory model with imperfect, rework, and scrap items under stochastic demand

10.11591/ijaas.v13.i4.pp900-910
Dana Marsetiya Utama , Artha Bripka Putri
Inventory is crucial in maintaining a smooth production process and meeting consumer demand for manufacturing companies. This research focuses on production problems involving defects, rework, and scrap items in stochastic demand. This research aims to develop a production-availability model by minimizing the expectation of total cost (ETC). The model includes four main decision variables, namely production quantity (Q), safety factor (k), production rate (P), and rework rate (P1). This research uses the Aquila optimizer algorithm to optimize the objective function. It compares with the heuristic procedure and Harris Hawk optimization algorithm. The results showed that the Aquila optimizer algorithm successfully optimized the production-availability problem. A comparison between algorithms indicates that the Aquila optimizer algorithm performs equivalently to the Harris Hawk optimization algorithm and outperforms the heuristic procedure. Sensitivity analysis shows that increasing demand uncertainty increases ETC and k. At the same time, it can decrease Q.
Volume: 13
Issue: 4
Page: 900-910
Publish at: 2024-12-01

Disturbance detection due to lightning at ionospheric D-region over Malaysia

10.11591/ijaas.v13.i4.pp825-833
Suryadi Suryadi , Mariyam Jamilah Homam , Rohaida Mat Akir , Mardina Abdullah
Previous research on the interference of very low frequency (VLF) signals in the equator region was inadequate and largely concentrated in the middle and high latitude regions. Therefore, this research aims to determine the disruption of VLF waves in the ionospheric D-region above Malaysia, which is in the equator area. This paper presents observations of early/fast, early/slow, and lightning-induced electron precipitation (LEP) events in January 2010. Broadband and narrowband data are monitored and investigated using Japan’s JJI Ebino transmitter (32°40' N, 130°81' E) to the receiver at the Universiti Kebangsaan Malaysia (2°55' N, 101°46' E). Broadband and narrowband data are analyzed with theoretical considerations and linked to events from interference in the ionospheric D-region. Many early/fast, early/slow, and LEP events are found to originate from the lightning release activity emitted and may alter the amplitude and VLF signal phase in the lower layer ionosphere over Malaysia.
Volume: 13
Issue: 4
Page: 825-833
Publish at: 2024-12-01

Analysis of high-voltage silicon vertical multi-junction solar cells: under concentrated illumination

10.11591/ijpeds.v15.i4.pp2019-2026
Mohamed Khalis , Rachid Masrour
We analyze the J-V characteristics of silicon vertical multi-junction solar cells. The J-V characteristic data includes J0, RS, Rsh, n, and Jph, representing saturation current density, series resistance, shunt resistance, ideality factor, and photocurrent density, respectively, and are utilized to extract the parameters of these multi-junction solar cells. These parameters were recently acquired in a previous investigation. In our research, we developed a MATLAB code to investigate the efficiency variation with concentration using the nonlinear least-squares method, following a similar approach as the previous study. Our findings reveal that the algorithm effectively utilizes electrical parameters obtained through the nonlinear least-squares method, ensuring stable convergence and faithful replication of experimental J-V characteristics. Our findings indicate that an increase in light concentration from 1 to 100 suns leads to an efficiency improvement from 19.4 to 26.2%. However, beyond 100 suns, the efficiency declines from 26.2 to 17.3%. The most influential parameter in determining solar cell efficiency is the open-circuit voltage, Voc. Our experiments have shown an increase in this voltage with light concentration. For instance, its value changes from around 19.147 V at 1 sun to approximately 25.491 V at 500 suns.
Volume: 15
Issue: 4
Page: 2019-2026
Publish at: 2024-12-01

Insights into pour point depressants: a brief review of their impact on the behavior of waxy crude oil

10.11591/ijaas.v13.i4.pp920-935
Gaurav Himanta Khaklari , Prasenjit Talukdar
A persistent challenge in the petroleum industry involves paraffin wax deposition from crude oils during low-temperature conditions, complicating pipeline flow assurance due to the intricate rheological behaviors exhibited by waxy crude oil gels. These behaviors include viscoelasticity, yield stress, and thixotropy, contributing to issues like flow reduction and pipeline obstruction, adversely affecting overall pipeline performance. Mitigating this problem requires a combination of mechanical and chemical processes, with pour point depressants (PPDs) emerging as an effective chemical solution. PPDs operate by interacting with wax crystals in the oil, disrupting their formation into a continuous network and preventing flow blockage at lower temperatures. The performance of PPDs depends on factors such as base oil type, PPD concentration, and application temperature. Recent advancements in PPDs focus on developing new polymers with enhanced performance and reduced environmental impact, including those derived from renewable resources, biodegradable PPDs, nano-structured PPDs, or hybrid PPDs. Polymeric additives, such as crystalline-amorphous copolymers, ethylene-vinyl acetate copolymers, comb polymers, and nanohybrids, are employed to modify wax crystallization behavior. Understanding the molecular structure of these additives, fluid composition, and pipeline conditions is crucial for optimizing formulations tailored to specific petroleum fluid compositions and transport conditions, ensuring effective wax deposition mitigation.
Volume: 13
Issue: 4
Page: 920-935
Publish at: 2024-12-01

Enhanced driving assistance: automated day and night vehicle detection system utilizing convolutional neural networks

10.11591/ijeecs.v36.i3.pp1532-1542
Abdelmoghit Zaarane , Ibtissam Slimani , Mourad Elhabchi , Issam Atouf
This paper presents an enhanced real-time vehicle detection system using convolutional neural networks (CNNs) for both daytime and night-time conditions. Initially, the system determines the time of capture by analyzing the upper part of input images. For daytime detection, it uses normalized cross-correlation and two-dimensional discrete wavelet transform (2D-DWT) techniques. Night-time detection involves identifying vehicle lamps through color thresholding and connected component techniques, followed by symmetry analysis and CNN classification. The dataset for training includes images from the Caltech Cars, AOLP, KITTI Vision, and night-time vehicle detection datasets, ensuring robust performance across various lighting conditions. Experiments demonstrate the system's high accuracy, achieving 99.2% during the day and 98.27% at night, meeting real-time requirements and enhancing driving assistance systems' reliability.
Volume: 36
Issue: 3
Page: 1532-1542
Publish at: 2024-12-01

Exploring fertility differentials between tea and ex-tea garden laborers of Assam

10.11591/ijphs.v13i4.24364
Lipika Kalita , Hari K. Choudhury
Addressing the issue of high fertility rates among tea garden laborers in Assam is critical due to its adverse effects on the health of both mothers and children, diminished investment in human capital, stunted economic growth, and exacerbated environmental challenges. To effectively tackle this challenge, we need to delve into two key questions: What perpetuates high fertility rates, and how can we mitigate them? The solution lies in a comprehensive analysis of the immediate and underlying factors influencing fertility. Fertility is a multifaceted demographic phenomenon influenced by both direct and indirect determinants. In this study, we investigate the impact of various proximate and distant factors on fertility among two groups: The tea garden labor community in Assam and the ex-tea garden labor community, comprising individuals who have transitioned to other forms of employment. Our research identifies significant factors such as wife's age at marriage, breastfeeding duration, educational attainment, family size, duration of married life, child mortality, respondent category, and wife's occupational status that affect fertility levels in Assam's tea garden community. The study's findings indicate the need for implementing targeted family planning and reproductive health education programs within tea garden communities. These programs should offer comprehensive information and resources to assist individuals in making informed decisions regarding family size and reproductive health.
Volume: 13
Issue: 4
Page: 1855-1863
Publish at: 2024-12-01

Impedance network-based ultra sparse matrix converter with enhanced voltage gain

10.11591/ijpeds.v15.i4.pp2262-2274
Zahid Hassan , M. A. Khan , Md. Rabiul Islam
The matrix converter is devised to achieve sinusoidal input current and output voltage, and high power density. The typical matrix converter gives voltage gain less than unity using a significantly large number of switches. To reduce the number of switches an ultra sparse matrix converter (USMC) is introduced whose voltage gain is still less than unity. Researchers also introduced many modified versions of these matrix converters including quasi-Z-source, series Zsource, switched inductor, and switched capacitor USMCs. Although all of these matrix converters have their relative advantages and disadvantages in terms of the number of switches and passive elements, the voltage gain is still marginal. This paper focused on achieving higher voltage gain using minimal switches and passive elements. We proposed a doubler boost impedance network based ultra sparse matrix converter (DB-USMC). The doubler boost impedance network consists of a boost stage and doubler stage where the boost stage enhances the voltage and the doubler stage makes it double. The voltage gain of the proposed DB-USMC converter is 4.00 at a 50% duty cycle. The obtained results of the proposed DB-USMC converter show a path to get superior voltage gain using minimal switches and passive elements in a cost-effective manner.
Volume: 15
Issue: 4
Page: 2262-2274
Publish at: 2024-12-01

Enhancing power quality: An Adaline algorithm for direct resonance current extraction in shunt active power filter

10.11591/ijpeds.v15.i4.pp2470-2479
Nor Farahaida Abdul Rahman , Muhammad Ammirrul Atiqi Mohd Zainuri , Naeem M. S. Hannoon , Muhamad Nabil Hidayat , Rahimi Baharom , Wan Noraishah Wan Abdul Munim
This paper presents an adaptive linear neuron (Adaline) algorithm designed to extract resonance current from the supply current directly. It aims to reduce the computation burden while upholding efficacy in the extraction process. The approach involves establishing the primary power system, evaluating harmonic and resonance current impacts, formulating efficient extraction strategies based on current waveform characteristics, employing the Adaline algorithm for extraction, and constructing a single-phase shunt active power filter (SAPF) to address harmonic currents and parallel resonance effects. Comparative analysis demonstrates the Adaline algorithm’s precision in extracting current amplitudes pre- and post-SAPF implementation. However, observed disparities in extracted resonance current amplitude may stem from the algorithm’s limitations in capturing low-amplitude signals. While a gain adjustment effectively boosts amplitude. However, it introduces considerable ripple and inconsistency, likely linked to parallel resonance effects. Notably, the SAPF exhibits simultaneous harmonic compensation and resonance damping capabilities. Results affirm the SAPF’s effectiveness in reducing harmonic components across all frequencies, including resonance frequency. Furthermore, resonance damping is crucial for further improving SAPF performance and reducing resonance current. This results in significantly improved waveform quality and reduced total harmonic distortion (THD) and individual harmonic distortion (THDi) values of compensated supply current.
Volume: 15
Issue: 4
Page: 2470-2479
Publish at: 2024-12-01
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