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  • Authors: Zaluchu, Sonny;

    The practice of religion in the media-facilitated virtual world has become a trend related to religiosity on the one hand and social life on the other. This study involves twenty-three pieces of literature in the form of journal papers and book chapters that discuss the topic of digital religion. All literature has undergone the PRISMA protocol's inclusion-exclusion criteria selection stage. The research method used was a Systematic Literature Review (SLR). Four research questions were posed to be researched using the SLR method, namely searching in the literature for the definition of digital religion, the shifts that occur in the practice of digital religion regarding sacred space, authority, identity, online worship, communion, and sacraments; theological views on digital religion; and sociological views on digital religion. It is concluded that digital religion is the implementation of religious practices online so that the offline-online boundary cannot be distinguished. Both are fused and complementary. As a result of being mediated by the internet and technology, the digitalization of religion results in a shift in form, implementation, and reconstruction in terms of new sacred space, new concepts of authority, digital identity, online worship, digital fellowship, and the performance of sacraments. Theologically, digital religion is a new way of presenting the kingdom of God beyond time and space in a networked society. Sociologically, digital religion represents not only an online religious entity but also a new culture in social devices with a social nature. This is due to the internet-based nature of digital religion, which can connect anyone in the same network to benefit the religious context. The digital world has become human daily life and needs revitalization of religiosity and human spirituality to fit the times.

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    Authors: UPIK ROSALINA WASRIN; MUCHLISIN ARIEF; SETIABUDI;

    Analyses of Landsat TM and SPOT multispectral data were performed with a very detailed description of the vegetation cover in the field to get a relevancy and consistency of digital image classification in a semi-automatic approach. Three main vegetation types, i.e. primary forest, logged-over forest and secondary forest after clear cut were analyzed and the microclimatic parameters were also measured to describe the ecological condition of the vegetation. Spectral and textural analysis of data obtained from field measurements and spectral reflectance values of the remote sensing data are the main topic of this report as one aspect of study on the Digital Method of Detection and Monitoring on Forest Ecosystem Change Using High Resolution Satellite Data funded by the Indonesian National Research Council. This study shows that spectral reflectance values alone cannot differentiate the logged-over forest from the primary forest, but it is very sharply distinguished from the secondary forest. As for the texture analysis, it is possible to distinguish the logged-over forest from the primary forest, as shown by different values of degree of Entropy, although spatially, it is still doubtful. Key words: Indonesia/Jambi/Tropical rain forests/lowland areas/Remote sensing/Vegetation Analysis/ Logged-over forests/Primary forests/Secondary forests.

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    Article . 1999
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    Biotropia: The Southeast Asian Journal of Tropical Biology
    Article . 2024 . Peer-reviewed
    License: CC BY NC ND
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      Article . 1999
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      Biotropia: The Southeast Asian Journal of Tropical Biology
      Article . 2024 . Peer-reviewed
      License: CC BY NC ND
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    Authors: DWI ANDREAS SANTOSA; SULASTRI;

    This study is aimed to get lipid producing microalgae as feedstock for biofuel production. The microalgae were isolated from 355 collected water samples which  represented many distinct ecosystems such as paddy fields, rivers, agricultural dams, ponds, swampy areas and unique ecosystem of volcano and mud-volcano craters in West- and Central Java, Indonesia. A total of  267 strains of microalgae were isolated from the samples of which  221 strains of them have capability to produce lipid. There were four promising strains that produce lipid between 14.7 – 45.7 percent dry weight in optimal condition that were identified as Chlamydomonas sp. KO-7267 and PK-7195, Chlorella sp. KS-7300 and Desmodesmus sp. BK-7291.  Keywords: microalgae, lipid, biofuel, Indonesian ecosystems

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    Biotropia: The Southeast Asian Journal of Tropical Biology
    Article . 2024 . Peer-reviewed
    License: CC BY NC ND
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      Biotropia: The Southeast Asian Journal of Tropical Biology
      Article . 2024 . Peer-reviewed
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    Authors: Vanany, Iwan; Ali, Helmi; Tan, Kim Hua; Kumar, Ajay; +1 Authors

    This article aims to explore the supply chain (SC) resilience capabilities of firms, focusing on their ability to respond to the COVID-19 pandemic disruption. Based on two cases each in the pharmaceutical and mineral water industries, this article identifies various strategies managers mobilized to tackle SC disruptions during the COVID-19 pandemic. This article contributes to theory through a proposed double-helix framework showing the dimension of disruptions and the capabilities concept to mitigate COVID-19. In addition, an in-depth investigation of the perceived importance versus actual SC resilience capabilities deployed is discussed and validated with practitioners. The findings of this article also address a critical gap in the SC operations management literature and provide a practical approach for managers to better manage future pandemic disruptions. IEEE

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    IEEE Transactions on Engineering Management
    Article . 2024 . Peer-reviewed
    License: IEEE Copyright
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      Article . 2024 . Peer-reviewed
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    Authors: Firna Firdiani; Satria Mandala; null Adiwijaya; Abdul Hanan Abdullah;

    Water presents challenges in swiftly and accurately assessing its quality due to its intricate composition, diverse sources, and the emergence of new pollutants. Current research tends to oversimplify water quality, categorizing it as potable or not, despite its complexity. To address this, we developed a water quality prediction system (WaQuPs), a sophisticated solution tackling the intricacies of water quality assessment. WaQuPs employs advanced machine learning, including an ensemble learning model, categorizing water quality into nuanced levels: potable, lightly polluted, moderately polluted, and heavily polluted. To ensure rapid and precise dissemination of information, WaQuPs integrates an Internet of Things (IoT)-based communication protocol for the efficient delivery of detected water quality results. In its development, we utilized advanced techniques, such as random oversampling (ROS) for dataset balance. We used a correlation coefficient to select relevant features for the ensemble learning algorithm based on the Random Forest algorithm. Further enhancements were made through hyperparameter tuning to improve the prediction accuracy. WaQuPs exhibited impressive metrics, achieving an accuracy of 83%, precision of 82%, recall of 83%, and an F1-score of 82%. Comparative analysis revealed that WaQuPs with the Random Forest model outperformed both the XGBoost and CatBoost models, confirming its superiority in predicting water quality.

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    Applied Sciences
    Article . 2023
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    Applied Sciences
    Article . 2023 . Peer-reviewed
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    Authors: Andy Indradjad; Muhammad Dimyati; Yenni Vetrita; Erna Sri Adiningsih; +1 Authors

    Indonesia needs a daily monitoring system due to its frequent fires and, more importantly, to assist stakeholders in the field in taking action to mitigate disasters. Our method simplified the number of hotspots for field-based purposes and was verified by comparing the point-based (point-HS) VIIRS (Visible Infrared Imaging Radiometer Suite) 375m-derived temperature anomalies (hotspots) and clustered-based hotspots (cluster-HS, our suggested method). Using Euclidean clustering, we calculated the distance between hotspot points and applied specific criteria to reduce the number of hotspots while aligning them closely with fire incidents. We evaluated accuracy at different fire sizes, burned areas, peatlands, and distances from the reported burn center. We found that the accuracy increases at 1.5 km from the center of the fire for both point- and cluster-HS at 52% and 53%, respectively. For areas larger than 14 ha, both types of hotspots yielded superior results of 83%. Cluster-HS performs better on peatlands than non-peatlands (62% vs. 57%). Without diminishing the precision of the hotspot observation, this study indicates that our method is reliable for assisting field stakeholders in the field in taking actions. Therefore, this product could be implemented into Indonesia’s daily hotspot monitoring.

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    Fire
    Article . 2023 . Peer-reviewed
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    Fire
    Article . 2023
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      Fire
      Article . 2023 . Peer-reviewed
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      Article . 2023
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    Authors: Pierre-François Blin; Trias Aditya; Purnama Budi Santosa; Christophe Claramunt;

    Cybersecurity risk management in land administration systems is crucial for maintaining the integrity of spatial cadastral data, which faces increasing threats owing to the digital transformation of LAS. This research validates the findings of this preliminary step in the form of a cyber risk management methodology that combines BPMN 2.0 with model business processes implemented by a compliance-based approach using EBIOS Risk Manager. A practical case of land parcel subdivision in Indonesia is analysed to serve as a proof of concept for our proposed methodology. Vulnerabilities are identified and are characterised by a concentration of manual tasks and the absence of systematic controls, resulting in significant risks to data integrity. These findings underscore the urgent need for a proactive approach to strengthen the cyber resilience of LAS. This study attempts to develop a fit-for-purpose reference methodology for cyber risk management specifically tailored to LAS to identify and treat vulnerabilities, threats, risks, and impacts.

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    Land
    Article . 2023
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    Land
    Article . 2023 . Peer-reviewed
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      Article . 2023
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      Land
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Alvin Muhammad Savero; Jong-Ho Kim; Byantara Darsan Purusatama; Denni Prasetia; +5 Authors

    The macroscopic and microscopic anatomical characteristics of wood impact its utilization. This study investigated and compared the anatomical characteristics of six Korean oak wood species: Quercus variabilis, Quercus serrata, Quercus mongolica, Quercus dentata, Quercus aliena, and Quercus acutissima. Microscopic anatomical characteristics were evaluated according to the International Association of Wood Anatomists’ list for hardwood identification. Q. variabilis had a corky bark texture, with a color similar to that of Q. serrata. Flat ridges and shallow-fissured barks were observed in Q. serrata and Q. mongolica. The heartwood color was darker than that of sapwood in all species, with color variations. Q. variabilis had heartwood–sapwood colors similar to those of Q. acutissima, while Q. mongolica and Q. aliena presented similar heartwood–sapwood colors. Concerning microscopic features, Q. variabilis and Q. acutissima exhibited similar latewood vessel arrangements, featuring diagonal and/or radial patterns. In contrast, dendritic-to-diagonal patterns of vessels with angular outlines were observed in Q. serrata, Q. mongolica, Q. dentata, and Q. aliena. Additionally, Q. variabilis and Q. acutissima had vasicentric, confluent, and unilateral paratracheal axial parenchyma in the latewood. In summary, bark morphology, bark color, wood color, and latewood vessel characteristics can be used as identification keys for Korean oak species.

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    Forests
    Article . 2023
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    Forests
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      Forests
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Andri Cahyo Kumoro; Dyah H. Wardhani; Tutuk D. Kusworo; Mohamad Djaeni; +3 Authors

    AbstractFish protein concentrate (FPC) is considered as a promising alternative to overcome the world’s shortage of affordable animal-based protein. Snakehead fish (Channa striata) offers a large potential as a raw material for FPC manufacture. This work aims to investigate the influence of solvent types (ethanol, n-hexane, and an azeotrope mixture of ethanol + n-hexane), extraction time (0, 10, 15, 20, 25, and 30 minutes), temperature (30, 40, 50, and 60°C), liquid solvent volume to solid feed fish flesh mass ratio (LSSFR) (1, 2, 3, 4, 5, 6, and 7 mL/g), and ultrasonic power (100, 200, 300, and 400 W) on the ultrasound-assisted extraction (UAE) to manufacture high-quality FPC from snakehead fish. After being subjected to UAE, the fish flesh was filtered and dried under reduced pressure at 55°C. The optimum UAE conditions for the manufacture of FPC from snakehead fish flesh were using ethanol as solvent, LSSFR (6 mL/g), temperature (40°C), ultrasonic power (200 W), and extraction time (25 minutes). The resulted FPC can be categorized as type A, which contains protein (73.17%) and fat (0.73%). An SDS-PAGE electrophoresis evaluation proved that the FPC contained 12 types of peptides having molecular weight (MW) ranging from 4.00 to 174.00 kDa with the major fractions being those with MWs ranged from 4.00 to 11.00 kDa and the minor fractions with MWs between 71.70 to 174.00 kDa. Indeed, the presence of both low and high MW peptides in the FPC indicates its potential applications in the development of nutritious food products.

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    Cogent Food & Agriculture
    Article . 2024
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    Cogent Food & Agriculture
    Article . 2023 . Peer-reviewed
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      Cogent Food & Agriculture
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    Authors: See Ven Lim; Mohd Asyraf Zulkifley; Azlan Saleh; Adhi Harmoko Saputro; +1 Authors

    Deforestation remains one of the key concerning activities around the world due to commodity-driven extraction, agricultural land expansion, and urbanization. The effective and efficient monitoring of national forests using remote sensing technology is important for the early detection and mitigation of deforestation activities. Deep learning techniques have been vastly researched and applied to various remote sensing tasks, whereby fully convolutional neural networks have been commonly studied with various input band combinations for satellite imagery applications, but very little research has focused on deep networks with high-resolution representations, such as HRNet. In this study, an optimal semantic segmentation architecture based on high-resolution feature maps and an attention mechanism is proposed to label each pixel of the satellite imagery input for forest identification. The selected study areas are located in Malaysian rainforests, sampled from 2016, 2018, and 2020, downloaded using Google Earth Pro. Only a two-class problem is considered for this study, which is to classify each pixel either as forest or non-forest. HRNet is chosen as the baseline architecture, in which the hyperparameters are optimized before being embedded with an attention mechanism to help the model to focus on more critical features that are related to the forest. Several variants of the proposed methods are validated on 6120 sliced images, whereby the best performance reaches 85.58% for the mean intersection over union and 92.24% for accuracy. The benchmarking analysis also reveals that the attention-embedded high-resolution architecture outperforms U-Net, SegNet, and FC-DenseNet for both performance metrics. A qualitative analysis between the baseline and attention-based models also shows that fewer false classifications and cleaner prediction outputs can be observed in identifying the forest areas.

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    Forests
    Article . 2023
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    Forests
    Article . 2023 . Peer-reviewed
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  • Authors: Zaluchu, Sonny;

    The practice of religion in the media-facilitated virtual world has become a trend related to religiosity on the one hand and social life on the other. This study involves twenty-three pieces of literature in the form of journal papers and book chapters that discuss the topic of digital religion. All literature has undergone the PRISMA protocol's inclusion-exclusion criteria selection stage. The research method used was a Systematic Literature Review (SLR). Four research questions were posed to be researched using the SLR method, namely searching in the literature for the definition of digital religion, the shifts that occur in the practice of digital religion regarding sacred space, authority, identity, online worship, communion, and sacraments; theological views on digital religion; and sociological views on digital religion. It is concluded that digital religion is the implementation of religious practices online so that the offline-online boundary cannot be distinguished. Both are fused and complementary. As a result of being mediated by the internet and technology, the digitalization of religion results in a shift in form, implementation, and reconstruction in terms of new sacred space, new concepts of authority, digital identity, online worship, digital fellowship, and the performance of sacraments. Theologically, digital religion is a new way of presenting the kingdom of God beyond time and space in a networked society. Sociologically, digital religion represents not only an online religious entity but also a new culture in social devices with a social nature. This is due to the internet-based nature of digital religion, which can connect anyone in the same network to benefit the religious context. The digital world has become human daily life and needs revitalization of religiosity and human spirituality to fit the times.

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    Authors: UPIK ROSALINA WASRIN; MUCHLISIN ARIEF; SETIABUDI;

    Analyses of Landsat TM and SPOT multispectral data were performed with a very detailed description of the vegetation cover in the field to get a relevancy and consistency of digital image classification in a semi-automatic approach. Three main vegetation types, i.e. primary forest, logged-over forest and secondary forest after clear cut were analyzed and the microclimatic parameters were also measured to describe the ecological condition of the vegetation. Spectral and textural analysis of data obtained from field measurements and spectral reflectance values of the remote sensing data are the main topic of this report as one aspect of study on the Digital Method of Detection and Monitoring on Forest Ecosystem Change Using High Resolution Satellite Data funded by the Indonesian National Research Council. This study shows that spectral reflectance values alone cannot differentiate the logged-over forest from the primary forest, but it is very sharply distinguished from the secondary forest. As for the texture analysis, it is possible to distinguish the logged-over forest from the primary forest, as shown by different values of degree of Entropy, although spatially, it is still doubtful. Key words: Indonesia/Jambi/Tropical rain forests/lowland areas/Remote sensing/Vegetation Analysis/ Logged-over forests/Primary forests/Secondary forests.

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    DOAJ
    Article . 1999
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    Biotropia: The Southeast Asian Journal of Tropical Biology
    Article . 2024 . Peer-reviewed
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      Article . 1999
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      Biotropia: The Southeast Asian Journal of Tropical Biology
      Article . 2024 . Peer-reviewed
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    Authors: DWI ANDREAS SANTOSA; SULASTRI;

    This study is aimed to get lipid producing microalgae as feedstock for biofuel production. The microalgae were isolated from 355 collected water samples which  represented many distinct ecosystems such as paddy fields, rivers, agricultural dams, ponds, swampy areas and unique ecosystem of volcano and mud-volcano craters in West- and Central Java, Indonesia. A total of  267 strains of microalgae were isolated from the samples of which  221 strains of them have capability to produce lipid. There were four promising strains that produce lipid between 14.7 – 45.7 percent dry weight in optimal condition that were identified as Chlamydomonas sp. KO-7267 and PK-7195, Chlorella sp. KS-7300 and Desmodesmus sp. BK-7291.  Keywords: microalgae, lipid, biofuel, Indonesian ecosystems

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    Biotropia: The Southeast Asian Journal of Tropical Biology
    Article . 2024 . Peer-reviewed
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      Biotropia: The Southeast Asian Journal of Tropical Biology
      Article . 2024 . Peer-reviewed
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    Authors: Vanany, Iwan; Ali, Helmi; Tan, Kim Hua; Kumar, Ajay; +1 Authors

    This article aims to explore the supply chain (SC) resilience capabilities of firms, focusing on their ability to respond to the COVID-19 pandemic disruption. Based on two cases each in the pharmaceutical and mineral water industries, this article identifies various strategies managers mobilized to tackle SC disruptions during the COVID-19 pandemic. This article contributes to theory through a proposed double-helix framework showing the dimension of disruptions and the capabilities concept to mitigate COVID-19. In addition, an in-depth investigation of the perceived importance versus actual SC resilience capabilities deployed is discussed and validated with practitioners. The findings of this article also address a critical gap in the SC operations management literature and provide a practical approach for managers to better manage future pandemic disruptions. IEEE

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    IEEE Transactions on Engineering Management
    Article . 2024 . Peer-reviewed
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      IEEE Transactions on Engineering Management
      Article . 2024 . Peer-reviewed
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    Authors: Firna Firdiani; Satria Mandala; null Adiwijaya; Abdul Hanan Abdullah;

    Water presents challenges in swiftly and accurately assessing its quality due to its intricate composition, diverse sources, and the emergence of new pollutants. Current research tends to oversimplify water quality, categorizing it as potable or not, despite its complexity. To address this, we developed a water quality prediction system (WaQuPs), a sophisticated solution tackling the intricacies of water quality assessment. WaQuPs employs advanced machine learning, including an ensemble learning model, categorizing water quality into nuanced levels: potable, lightly polluted, moderately polluted, and heavily polluted. To ensure rapid and precise dissemination of information, WaQuPs integrates an Internet of Things (IoT)-based communication protocol for the efficient delivery of detected water quality results. In its development, we utilized advanced techniques, such as random oversampling (ROS) for dataset balance. We used a correlation coefficient to select relevant features for the ensemble learning algorithm based on the Random Forest algorithm. Further enhancements were made through hyperparameter tuning to improve the prediction accuracy. WaQuPs exhibited impressive metrics, achieving an accuracy of 83%, precision of 82%, recall of 83%, and an F1-score of 82%. Comparative analysis revealed that WaQuPs with the Random Forest model outperformed both the XGBoost and CatBoost models, confirming its superiority in predicting water quality.

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    Applied Sciences
    Article . 2023
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    Applied Sciences
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      Applied Sciences
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    Authors: Andy Indradjad; Muhammad Dimyati; Yenni Vetrita; Erna Sri Adiningsih; +1 Authors

    Indonesia needs a daily monitoring system due to its frequent fires and, more importantly, to assist stakeholders in the field in taking action to mitigate disasters. Our method simplified the number of hotspots for field-based purposes and was verified by comparing the point-based (point-HS) VIIRS (Visible Infrared Imaging Radiometer Suite) 375m-derived temperature anomalies (hotspots) and clustered-based hotspots (cluster-HS, our suggested method). Using Euclidean clustering, we calculated the distance between hotspot points and applied specific criteria to reduce the number of hotspots while aligning them closely with fire incidents. We evaluated accuracy at different fire sizes, burned areas, peatlands, and distances from the reported burn center. We found that the accuracy increases at 1.5 km from the center of the fire for both point- and cluster-HS at 52% and 53%, respectively. For areas larger than 14 ha, both types of hotspots yielded superior results of 83%. Cluster-HS performs better on peatlands than non-peatlands (62% vs. 57%). Without diminishing the precision of the hotspot observation, this study indicates that our method is reliable for assisting field stakeholders in the field in taking actions. Therefore, this product could be implemented into Indonesia’s daily hotspot monitoring.

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    Fire
    Article . 2023 . Peer-reviewed
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    Fire
    Article . 2023
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      Fire
      Article . 2023 . Peer-reviewed
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    Authors: Pierre-François Blin; Trias Aditya; Purnama Budi Santosa; Christophe Claramunt;

    Cybersecurity risk management in land administration systems is crucial for maintaining the integrity of spatial cadastral data, which faces increasing threats owing to the digital transformation of LAS. This research validates the findings of this preliminary step in the form of a cyber risk management methodology that combines BPMN 2.0 with model business processes implemented by a compliance-based approach using EBIOS Risk Manager. A practical case of land parcel subdivision in Indonesia is analysed to serve as a proof of concept for our proposed methodology. Vulnerabilities are identified and are characterised by a concentration of manual tasks and the absence of systematic controls, resulting in significant risks to data integrity. These findings underscore the urgent need for a proactive approach to strengthen the cyber resilience of LAS. This study attempts to develop a fit-for-purpose reference methodology for cyber risk management specifically tailored to LAS to identify and treat vulnerabilities, threats, risks, and impacts.

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    Land
    Article . 2023
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    Land
    Article . 2023 . Peer-reviewed
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      Land
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    Authors: Alvin Muhammad Savero; Jong-Ho Kim; Byantara Darsan Purusatama; Denni Prasetia; +5 Authors

    The macroscopic and microscopic anatomical characteristics of wood impact its utilization. This study investigated and compared the anatomical characteristics of six Korean oak wood species: Quercus variabilis, Quercus serrata, Quercus mongolica, Quercus dentata, Quercus aliena, and Quercus acutissima. Microscopic anatomical characteristics were evaluated according to the International Association of Wood Anatomists’ list for hardwood identification. Q. variabilis had a corky bark texture, with a color similar to that of Q. serrata. Flat ridges and shallow-fissured barks were observed in Q. serrata and Q. mongolica. The heartwood color was darker than that of sapwood in all species, with color variations. Q. variabilis had heartwood–sapwood colors similar to those of Q. acutissima, while Q. mongolica and Q. aliena presented similar heartwood–sapwood colors. Concerning microscopic features, Q. variabilis and Q. acutissima exhibited similar latewood vessel arrangements, featuring diagonal and/or radial patterns. In contrast, dendritic-to-diagonal patterns of vessels with angular outlines were observed in Q. serrata, Q. mongolica, Q. dentata, and Q. aliena. Additionally, Q. variabilis and Q. acutissima had vasicentric, confluent, and unilateral paratracheal axial parenchyma in the latewood. In summary, bark morphology, bark color, wood color, and latewood vessel characteristics can be used as identification keys for Korean oak species.

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    Forests
    Article . 2023
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    Forests
    Article . 2023 . Peer-reviewed
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    Authors: Andri Cahyo Kumoro; Dyah H. Wardhani; Tutuk D. Kusworo; Mohamad Djaeni; +3 Authors

    AbstractFish protein concentrate (FPC) is considered as a promising alternative to overcome the world’s shortage of affordable animal-based protein. Snakehead fish (Channa striata) offers a large potential as a raw material for FPC manufacture. This work aims to investigate the influence of solvent types (ethanol, n-hexane, and an azeotrope mixture of ethanol + n-hexane), extraction time (0, 10, 15, 20, 25, and 30 minutes), temperature (30, 40, 50, and 60°C), liquid solvent volume to solid feed fish flesh mass ratio (LSSFR) (1, 2, 3, 4, 5, 6, and 7 mL/g), and ultrasonic power (100, 200, 300, and 400 W) on the ultrasound-assisted extraction (UAE) to manufacture high-quality FPC from snakehead fish. After being subjected to UAE, the fish flesh was filtered and dried under reduced pressure at 55°C. The optimum UAE conditions for the manufacture of FPC from snakehead fish flesh were using ethanol as solvent, LSSFR (6 mL/g), temperature (40°C), ultrasonic power (200 W), and extraction time (25 minutes). The resulted FPC can be categorized as type A, which contains protein (73.17%) and fat (0.73%). An SDS-PAGE electrophoresis evaluation proved that the FPC contained 12 types of peptides having molecular weight (MW) ranging from 4.00 to 174.00 kDa with the major fractions being those with MWs ranged from 4.00 to 11.00 kDa and the minor fractions with MWs between 71.70 to 174.00 kDa. Indeed, the presence of both low and high MW peptides in the FPC indicates its potential applications in the development of nutritious food products.

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    Cogent Food & Agriculture
    Article . 2024
    Data sources: DOAJ
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    Cogent Food & Agriculture
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Cogent Food & Ag...arrow_drop_down
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      Cogent Food & Agriculture
      Article . 2024
      Data sources: DOAJ
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      Cogent Food & Agriculture
      Article . 2023 . Peer-reviewed
      License: CC BY
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    Authors: See Ven Lim; Mohd Asyraf Zulkifley; Azlan Saleh; Adhi Harmoko Saputro; +1 Authors

    Deforestation remains one of the key concerning activities around the world due to commodity-driven extraction, agricultural land expansion, and urbanization. The effective and efficient monitoring of national forests using remote sensing technology is important for the early detection and mitigation of deforestation activities. Deep learning techniques have been vastly researched and applied to various remote sensing tasks, whereby fully convolutional neural networks have been commonly studied with various input band combinations for satellite imagery applications, but very little research has focused on deep networks with high-resolution representations, such as HRNet. In this study, an optimal semantic segmentation architecture based on high-resolution feature maps and an attention mechanism is proposed to label each pixel of the satellite imagery input for forest identification. The selected study areas are located in Malaysian rainforests, sampled from 2016, 2018, and 2020, downloaded using Google Earth Pro. Only a two-class problem is considered for this study, which is to classify each pixel either as forest or non-forest. HRNet is chosen as the baseline architecture, in which the hyperparameters are optimized before being embedded with an attention mechanism to help the model to focus on more critical features that are related to the forest. Several variants of the proposed methods are validated on 6120 sliced images, whereby the best performance reaches 85.58% for the mean intersection over union and 92.24% for accuracy. The benchmarking analysis also reveals that the attention-embedded high-resolution architecture outperforms U-Net, SegNet, and FC-DenseNet for both performance metrics. A qualitative analysis between the baseline and attention-based models also shows that fewer false classifications and cleaner prediction outputs can be observed in identifying the forest areas.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Forestsarrow_drop_down
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    Forests
    Article . 2023
    Data sources: DOAJ
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    Forests
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Forestsarrow_drop_down
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      Forests
      Article . 2023
      Data sources: DOAJ
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      Forests
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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