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The use of Carica papaya seeds as bio coagulant for laundry wastewater treatment

Journal of engineering and Applied Science 2024年第1期71卷 99页

作者： Vezar, Siti Alfinna Naulita Belinda, Zeriyatina Tri Rendana, Muhammad Agustina, Tuty Emilia Nasir, Subriyer Hanum, Laila Andarini, Desheila Undergraduate Student of Chemical Engineering Program Faculty of Engineering Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Chemical Engineering Program Faculty of Engineering Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Biology Department Faculty of Mathematics and Natural Sciences Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Public Health Program Study Faculty of Public Health Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia

The study aims to analyze the effectiveness of wastewater treatment by using Carica papaya seeds as bio coagulants to diminish total suspended solids (TSS) and excess phosphate. This method has some advantages because it does not use chemical materials, is simple to apply, and is safe for the environment and human health. The wastewater samples were taken from an active laundry site in Palembang City, South Sumatra Province of Indonesia. The study found that the best dosage of coagulant was 3 g for the wastewater samples. The pH and BOD parameters showed slight changes after treatment, with pH 7.63–7.19 and 33–27 mg/L values, respectively. The TSS removal efficiency ranged from 9.3 to 15.6%, while the COD and phosphate removals were obtained from 11.7 to 39.3% and 56.3 to 68.4%, respectively. The treated TSS, COD, and phosphate concentrations have met the Indonesian domestic wastewater quality standard and environmental protection organization (EPO) guidelines. In addition, the statistical analysis and t-test showed significant differences (p © The Author(s) 2024.

关键词： Wastewater treatment

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Adaptive governance in the water-energy-food-ecosystem nexus for sustainable community sanitation

World Development Sustainability

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World Development Sustainability 2025年 6卷

作者： Sofiyah, Evi Siti Sianipar, Imelda Masni Juniaty Rahman, Ari Caesarina, Naila Putri Suhardono, Sapta Suryawan, I Wayan Koko Lee, Chun-Hung Department of Environmental Engineering Faculty of Infrastructure Planning Universitas Pertamina Jalan Sinabung II Terusan Simprug Jakarta 12220 Indonesia Department of International Relations Faculty of Social Science and Political Science Universitas Kristen Indonesia Jakarta 13630 Indonesia Environmental Sciences Study Program Faculty of Mathematics and Natural Sciences Universitas Sebelas Maret Surakarta 57126 Indonesia Department of Natural Resources and Environmental Studies College of Environmental Studies and Oceanography National Dong Hwa University Hualien 97401 Taiwan Center for Environmental Solution (CVISION) Universitas Pertamina Jalan Sinabung II Terusan Simprug Jakarta 12220 Indonesia Center for Interdisciplinary Research on Ecology and Sustainability College of Environmental Studies and Oceanography National Dong Hwa University Hualien 97401 Taiwan

As the intensity of global environmental challenges increases, so does the need to understand and strengthen the resilience of interconnected systems. This research underscores the crucial role of adaptive governance in navigating the complexities of the Water-Energy-Food-Ecosystem nexus, particularly under the pressures of changing climatic conditions. The study conducts an in-depth analysis of adaptive capacities by identifying critical components such as assets, flexibility, organization, learning, and agency as fundamental elements of adaptive governance in sanitation practices. Data were collected through structured questionnaires and analyzed using binary probit and logit models to examine how these attributes influence community engagement in sanitation. Descriptive analysis was also used to summarize respondent characteristics and attribute distributions. © 2025 The Author(s)

关键词： Adaptive governance Community engagement Environmental sustainability Sanitation resilience Water-energy-food-ecosystem nexus

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The effect of lard concentration and ozonation on changes in polarization angle of olive oil 10

The effect of lard concentration and ozonation on changes in...

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10th International Seminar on New Paradigm and Innovation of Natural Sciences and itsApplication, ISNPINSA 2020

作者： Saputra, F.A. Azam, M. Arianto, F. Sofjan, K.F. Sugito, H. Alkian, I. Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang50275 Indonesia Study Program of Automation Engineering Technology Vocational School Diponegoro University Indonesia

This research aims to analyze the effect of ozone exposure time and lard mixture on the polarization angle of transmission of olive oil. The study uses a transmission polarization method with a laser (λ = 532 nm) as a light source. The research sample in the form of olive oil mixed with lard at a concentration of 10, 20, 40, and 80%, with an ozone exposure time of 0-30 minutes. The sample is subjected to external electric fields with variations from 0-4.5 x 102 kV/m to increase the change's polarization angle. The results showed that the change in polarization angle would change linearly with the increase in lard concentration with olive oil. Olive oil with a low concentration of lard (10%) experienced an increase in the change in polarization angle with a value of 0.31 due to the effect of 90 minutes of ozone exposure. In general, the results of the study showed that increased concentrations of lard, ozone exposure time, electric field strengths caused an increase in changes in the polarization angle in a mixture of olive oil and lard. © Published under licence by IOP Publishing Ltd.

关键词： Mixtures

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The Application of ANN-Linear Perceptron in the Development of DSS for a Fishery Industry

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Procedia Computer Science 2015年 72卷 67-77页

作者： Asep Sholahuddin Agung Pre Ramadhan Asep K. Supriatna Informatics Engineering Study Program Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Jalan Raya Bandung Sumedang Km. 21 Jatinangor-45363 Indonesia Mathematics Study Program Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Jalan Raya Bandung Sumedang Km. 21 Jatinangor-45363 Indonesia

Overfishing is a global environmental problem that risks fisheries since many of the fish stock of the fisheries have already reduced to below a tolerable level. One of solutions that often implemented in the fishery management is by calculating the value of Maximum Sustainable Yield (MSY) as the maximum tolerable harvest that can be taken out from the natural stock without harming the population over an indefinite period of time. A proper tool used for computing the MSY is needed to support the fishery manager in solving this decision making problem. In this paper we propose a software development of Decision Support System (DSS) to address such fishery industry problem. The DSS is developed to compute the MSY from the annual yield-effort data of the fishery. We use two sigmoid growth equations, Logistic and Gompertz equations, as the underlying population models, which then are approximated by their discrete forms for computing several growth parameters. Most known methods of growth parameter estimation use a Multiple Linear Regression with Ordinary Least Square method (MLR-OLS). Here we propose the application of Artificial Neural Network with Linear Perceptron method (ANN-LP). A case study in this paper shows that the effectiveness of the proposed ANN-LP is as good as the MLR-OLS in estimating both the growth parameters and the MSY of the fishery in the case study needed in the computation of its MSY by using Artificial Neural Network (ANN) Linear Perceptron.

关键词： DSS MSY Logistic Gompertz ANN Linear Perceptron

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An Evaluation of Number of Pixels Change Rate (NPCR) in Symetric Cryptography Based on Data Encryption Standard (DES)

An Evaluation of Number of Pixels Change Rate (NPCR) in Syme...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Naufal, Muhammad Rizky Sari, Christy Atika Rachmawanto, Eko Hari Handoko, Lekso Budi Isinkaye, Folasade Olubusola Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Ekiti State University Department of Computer Science Ekiti Nigeria Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Data Encryption Standard (DES) is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. In addition, the cipher text will be hidden inside an image using Stepic. DES Encryption use symmetric encryption to encrypt and decryption to decrypt. It will secure the symmetric encryption and maintain the speed of the encryption and decryption. The result of this study is the lowest error that we got as the Mean Square Error (MSE) is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche with 79.36% and 34.91% in order that is not stable for result of Avalanche Effect (AVA). Inversely proportional to the length of the text that is hidden in the image, the longest text that is hidden, the more changes that we get in the image with the highest Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) with the biggest image size with 43.47% for UACI and 99.87% for the NPCR. © 2023 IEEE.

关键词： Pixels

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Machine Learning-based Modulation Format Identification and Optical Performance Monitoring Techniques Implementation

Machine Learning-based Modulation Format Identification and ...

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2021 Advanced Communication Technologies and Signal Processing, ACTS 2021

作者： Devi, Pukhrambam Puspa Vincent Simatupang, Joni Welman National Institute of Technology Silchar Department of Electronics and Communication Engineering Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung40132 Indonesia President University Study Program of Electrical Engineering Bekasi17530 Indonesia

ISBN: (纸本)9781665423373

In this paper, machine learning-based techniques are used to solve and analyze the modulation format recognition problem. The combination of intelligent software and high-performance hardware provides a large scope for innovation in optical networking. Machine learning algorithms can use a large amount of data available from the network monitors to learn and make the network more robust. This is a problem in optical communication that consists of defining the type of digital modulation process in which an electrical signal should be sent. A dataset to represent realistic transmission behaviors was generated using a simulator based on a Gaussian noise model. A multi-layer perceptron was used and tested with different architectures to show that a high level of accuracy is achievable with machine learning. An analysis of the input features was made by using the select K best features method. Finally, an attempt to visualize the data in 2-dimension was made using the Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE) methods to reduce the dimensionality of the input features and see their relationships. © 2021 IEEE.

关键词： Principal component analysis

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AlexNet Architecture Based Convolution Neural Network for Realtime Audio to Text Translator of Bisindo Hand Sign

AlexNet Architecture Based Convolution Neural Network for Re...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Sujatmiko, Dhiki Sari, Christy Atika Rachmawanto, Eko Hari Krismawan, Andi Danang Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Animation Semarang Indonesia Mosul University Presidency University of Mosul Department of Computer Science Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Deafness is a condition that results in the loss of hearing function, hindering the reception of information such as oral communication that relies on auditory senses. Consequently, individuals with hearing impairment experience communication barriers and may have limited or no ability to respond. One solution is the use of sign language. In Indonesia, there are two known sign languages: Sibi and Bisindo. Both serve the same function but differ in their style of movement and expression. Bisindo is considered more flexible as it conveys meaning based on the Indonesian language. However, the universal understanding of this language solution is still limited among many people. Therefore, a program is needed to facilitate translation between deaf individuals who use sign language and their counterparts who do not communicate through sign language. CNN (Convolutional Neural Network) is a deep learning algorithm used for training visual input data recognition by computer systems. There are various CNN-based architectures, and one of them is AlexNet. Based on the author's testing, the AlexNet architecture proves to be suitable for real-time sign language translation. The evaluation of the system involved 7,800 datasets and 520 testing instances, with an average accuracy of 468 correct translations. When averaged, the system achieved a 90% accuracy rate, representing a 100% increase in accuracy compared to previous approaches. © 2023 IEEE.

关键词： Audition

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On the maximum of cotangent sums related to the Riemann hypothesis in rational numbers in short intervals

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Moscow Journal of Combinatorics and Number Theory 2022年第4期10卷 303-313页

作者： Maier, Helmut Rassias, Michael Th. Department of Mathematics University of Ulm Ulm Germany Department of Mathematics and Engineering Sciences Hellenic Military Academy Athens Greece Moscow Institute of Physics and Technology Dolgoprudny Russian Federation Program in Interdisciplinary Studies Institute for Advanced Study Princeton NJ United States

Cotangent sums play a significant role in the Nyman–Beurling criterion for the Riemann hypothesis. Here we investigate the maximum of the values of these cotangent sums over various sets of rational numbers in short ... 详细信息

关键词： Cotangent sums Estermann’s zeta function Kloosterman sums Nyman–Beurling criterion Riemann hypothesis Riemann zeta function

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Early Detection and Classification of Melanoma Based on Android MobileNet V2 Convolutional Neural Network

Early Detection and Classification of Melanoma Based on Andr...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Prabandari, Jasmine Iswarini Dyah Sari, Christy Atika Rachmawanto, Eko Hari Irawan, Candra Altamer, Bilal R. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Mosul University Presidency University of Mosul Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Melanoma is a malignant form of cancer that affects the skin and has a particularly high mortality rate, so it requires early detection to increase the level of safety for users. Diagnosis and detection of skin cancer are usually done through manual screening and visual inspection. This process requires a long time, has high complexity, is subjective, and is prone to errors. CNN is one of the algorithms with advantages in accurate classification. In this research, early detection and classification of melanoma cancer were carried out based on two classes, namely benign and malignant using the Convolutional Neural Network method. Our proposed method yields an accuracy of 81.11% for the validation data. The accuracy results obtained can be improved by using more datasets and increasing the number of layers used. This study uses the CNN method using MobileNet V2 architecture to detect melanoma skin cancer. The class used is benign and malignant. © 2023 IEEE.

关键词： Convolutional neural networks

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RFI measurements at Bosscha observatory to prepare a new VGOS station

RFI measurements at Bosscha observatory to prepare a new VGO...

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2023 International Symposium From the Universe Back to Earth: Developing Astronomy to Meet Today's Natural Challenges

作者： Ramadhan, S. Hidayat, T. Suryana, J. Romadhoni, A. Kurniasari, M. Bosscha Observatory Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Indonesia Astronomy Study Program Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Indonesia Laboratory of Radio and Microwave Telecommunication School of Electronics and Informatics Engineering Institut Teknologi Bandung Indonesia

A new VGOS (VLBI Global Observing System) radio telescope will be constructed at Bosscha Observatory Lembang, West Java, in cooperation between Shanghai Astronomical Observatory (SHAO) and Institut Teknologi Bandung. One of the preparation steps is to conduct RFI (Radio Frequency Interference) measurements to obtain the RFI environment from the vicinity of the observatory. In this work, we report preliminary measurements of the RFIs that were done for several days in August and September 2023. Instruments used includes: A-INFOTM LB-20180 horn antenna, Wright TechnologiesTM low noise amplifier, and AaroniaTM Spectran V5 80200 OEM spectrum analyzer. The frequency range of 2.0 - 18.0 GHz is targeted referring to VGOS frequencies. Measurements in one day are carried out for about 24 hours in eight cardinal directions and two polarizations. The results and analysis are presented in spectral power flux density plots. © Published under licence by IOP Publishing Ltd.

关键词： Observatories

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