bluuebunny/crossref_metadata_2025 huggingface dataset:
Commentary on: Increased stiffness of omental arteries from late pregnant women at advanced maternal age
Authors: Stanhewicz Anna E. , Schwartz Kelsey S. , Lee Ruda
Published: November 2023

Worldwide, pregnancy at age 35 or older, termed ‘advanced maternal age (AMA)’, is increasing exponentially. As the incidence of pregnancy at AMA has increased, a growing body of evidence has suggested that AMA is also associated with increased risk for adverse maternal and fetal outcomes outside of genetic anomalies. Importantly, despite the mounting evidence and the increased global risk of adverse perinatal outcomes observed, few studies have examined the potential mechanisms underlying this elevated risk in pregnant people ≥35 years of age. Wooldridge and colleagues begin to address this gap in the literature. In their recent report, they examine vessel stiffness in omental resistance vessels obtained from pregnant individuals ≥35 years of age compared with pregnant individuals <35 years of age. Omental arteries were isolated and assessed via pressure myography (mechanical properties) and histological analysis for collagen and elastin content. Overall, the findings from this investigation report that maternal resistance arteries collected from women of AMA were less compliant and had less elastin than arteries obtained from women <35 years of age, suggesting that maternal resistance vessel stiffening in AMA may contribute to increased risk of adverse pregnancy outcomes. The authors should be commended for completing these studies in human resistance vessels, which now open new avenues for investigation and provoke a cascade of questions related to maternal cardiovascular adaptations to pregnancy in women ≥35 years of age.
Endosphere microbial communities and plant nutrient acquisition toward sustainable agriculture
Authors: Babalola Olubukola Oluranti , Adedayo Afeez Adesina
Published: November 2023

Endophytic microbial communities have essential information for scientists based on their biological contribution to agricultural practices. In the external plant environment, biotic and abiotic factors affect microbial populations before getting into plant tissues. Endophytes are involved in mutualistic and antagonistic activities with the host plant. Microbial communities inhabiting the internal tissues of plant roots depend on their ability to live and contend with other plant microflora. The advantageous ones contribute to soil health and plant growth either directly or indirectly. The microbial communities move via soil–root environment into the endosphere of plants promoting plant growth features like antibiosis, induced systemic resistance, phytohormone synthesis, and bioremediation. Therefore, the existence of these microorganisms contributes to plant genomes, nutrient availability in the soil, the presence of pathogens, and abiotic factors. This review aims at how endophytic microorganisms have displayed great interest in contributing to abundant crop production and phytopathogen inhibition.
Scene context‐aware graph convolutional network for skeleton‐based action recognition
Authors: Zhang Wenxian
Published: November 2023

Skeleton‐based action recognition methods commonly employ graph neural networks to learn different aspects of skeleton topology information However, these methods often struggle to capture contextual information beyond the skeleton topology. To address this issue, a Scene Context‐aware Graph Convolutional Network (SCA‐GCN) that leverages potential contextual information in the scene is proposed. Specifically, SCA‐GCN learns the co‐occurrence probabilities of actions in specific scenarios from a common knowledge base and fuses these probabilities into the original skeleton topology decoder, producing more robust results. To demonstrate the effectiveness of SCA‐GCN, extensive experiments on four widely used datasets, that is, SBU, N‐UCLA, NTU RGB + D, and NTU RGB + D 120 are conducted. The experimental results show that SCA‐GCN surpasses existing methods, and its core idea can be extended to other methods with only some concatenation operations that consume less computational complexity.
Dynamic multi‐agent dc‐bus reconfiguration in modular motor drives with a stacked polyphase bridge converter
Authors: Verkroost Lynn , Vande Ghinste Alexander , da Rocha Lorrana Faria , De Kooning Jeroen D. M. , De Belie Frederik , Sergeant Peter , Olsen Pål Keim , Vansompel Hendrik
Published: November 2023

A stacked polyphase bridge converter consists of multiple standard, three‐phase two‐level voltage source inverters connected in series to the same dc voltage source. The authors present a decentralised and dynamic dc‐bus reconfiguration strategy for this type of converter. The innovation of the proposed strategy lies in its ability to isolate or reactivate one of the inverters in the series connection online, even in motoring mode, enabling increased fault tolerance and an extended speed range. Both the required hardware alterations and the multi‐agent control strategy are addressed. Its major benefits compared to the state‐of‐the‐art are that only two additional active, unidirectional semiconductor switches are required per inverter, and that the control is based on local computations, local measurements and neighbour‐to‐neighbour communication only. Hence, the scalability and reliability of the hardware are extended towards the control. Simulations and experimental results on a 4 kW modular axial‐flux PMSM prove the feasibility of the concept, and validate that the dc‐bus can be reconfigured in 100 ms, without torque interruption.
Hosting capacity of distribution networks for controlled and uncontrolled residential EV charging with static and dynamic thermal ratings of network components
Authors: Zakaria As’ad , Duan Chengyan , Djokic Sasa Z.
Published: November 2023

The ongoing electrification of road transportation sector, which is expected to continue to strongly increase over the next years, will result in the connection of a significant number of electric vehicle (EV) chargers in LV and MV distribution networks, particularly in residential applications with on‐board (“slow”) EV chargers. In order to evaluate loading limits of existing distribution networks for the maximum number of EV chargers that can be safely connected (commonly denoted as a network EV “hosting capacity”, HC), this paper introduces a general approach to determine one commonly used network design parameter (after‐diversity maximum demand, ADMD) and one new parameter (maximum daily energy demand, MDED), which are both obtained from the load profiles of maximum per‐hour demands for uncontrolled residential EV charging. The presented approach uses actual EV charging data from the UK as the inputs in Monte Carlo simulations to generate daily EV charging profiles for arbitrary numbers of EVs, enabling to identify related ADMD, MDED and per‐hour maximum demand values, as well as their seasonal variations. The assessed ADMD, MDED and hourly maximum EV charging demands for uncontrolled EV charging are then combined with available UK residential daily load profiles before the EVs are connected (“pre‐EV demands”), where their combined coincidental and noncoincidental maximum demands are evaluated against the static thermal rating (STR) and dynamic thermal rating (DTR) loading limits of network components (transformers and overhead lines), taking into account relevant weather/ambient conditions. This is denoted as a network HC for uncontrolled EV charging. Finally, evaluating the resulting per‐hour maximum demand values against the STR and DTR loading limits and MDED values allows to select one particular scheduling method for controlled EV charging, which gives the absolute maximum number of EVs that can be safely connected in the considered network, that is, maximum network HC for fully controlled EV charging. The presented approach is illustrated on the example of the IEEE 33‐bus test network (modelled using typical UK network components), for the pre‐EV residential demands taken from the recordings at a UK MV substation, and for ambient data taken from a UK Met Office weather station. Obtained results allow to evaluate the range of network EV HC values for uncontrolled and controlled EV charging, that is, lower and upper HC limits, which can be correlated with the commonly used allocations of the firm and non‐firm network HC, respectively.
Synthetic populations of protoplanetary disks: Impact of magnetic fields and radiative transfer
Authors: Lebreuilly U. , Hennebelle P. , Colman T. , Maury A. , Tung N. D. , Testi L. , Klessen R. , Molinari S. , Commerçon B. , González M. , Pacetti E. , Somigliana A. , Rosotti G.
Published: November 2023

Context. Protostellar disks are the product of angular momentum conservation during protostellar collapse. Understanding their formation is crucial because they are the birthplace of planets and their formation is also tightly related to star formation. Unfortunately, the initial properties of Class 0 disks and their evolution are still poorly constrained both theoretically and observationally.

Aims. We aim to better understand the mechanisms that set the statistics of disk properties as well as to study their formation in massive protostellar clumps. We also want to provide the community with synthetic disk populations to better interpret young disk observations.

Methods. We used the ramses code to model star and disk formation in massive protostellar clumps with magnetohydrodynamics, including the effect of ambipolar diffusion and radiative transfer as well as stellar radiative feedback. Those simulations, resolved up to the astronomical unit scale, have allowed us to investigate the formation of disk populations.

Results. Magnetic fields play a crucial role in disk formation. A weaker initial field leads to larger and massive disks and weakens the stellar radiative feedback by increasing fragmentation. We find that ambipolar diffusion impacts disk and star formation and leads to very different disk magnetic properties. The stellar radiative feedback also have a strong influence, increasing the temperature and reducing fragmentation. Comparing our disk populations with observations reveals that our models with a mass-to-flux ratio of 10 seems to better reproduce observed disk sizes. This also sheds light on a tension between models and observations for the disk masses.

Conclusions. The clump properties and physical modeling significantly impact disk populations. It is critical to for the tension, with respect to disk mass estimates, between observations and models to be solved with synthetic observations. This is particularly important in the context of understanding planet formation.
Analytic description of the gas flow around planets embedded in protoplanetary disks
Authors: Kuwahara Ayumu , Kurokawa Hiroyuki
Published: November 2023

Context. A growing planet embedded in a protoplanetary disk induces three-dimensional gas flow, which exhibits a midplane outflow that can suppress dust accretion onto the planet and form global dust substructures (rings and gaps).

Aims. Because analytic formulae for the planet-induced outflow are useful for modeling its influences on local and global dust surface densities and planet accretion, we derived analytic formulae that describe the morphology and velocity of the planet-induced outflow.

Methods. We first performed three-dimensional, nonisothermal hydrodynamical simulations of the gas flow past a planet, which enabled us to introduce a fitting formula that describes the morphology of the outflow. We then derived an analytic formula for the outflow speed using Bernoulli’s theorem.

Results. We successfully derived a fitting formula for the midplane outflow morphology (the shape of the streamline), which is valid when the dimensionless thermal mass falls below m ≲ 0.6. The obtained analytic formulae for the outflow, such as the maximum outflow speed and the velocity distributions of the outflow in the radial and vertical directions to the disk, show good agreement with the numerical results. We find the following trends: (1) the maximum outflow speed increases with the planetary mass and has a peak of ~30–40% of the sound speed when the dimensionless thermal mass is m ~ 0.3, corresponding to a super-Earth mass planet at 1 au for the typical steady accretion disk model, and (2) the presence of the headwind (namely, the global pressure force acting in the positive radial direction of the disk) enhances (reduces) the outflow toward the outside (inside) of the planetary orbit.

Conclusions. The planet-induced outflow of the gas affects the dust motion when the dimensionless stopping time of dust falls below St ≲ min(10 m2, 0.1), which can be used to model the dust velocity influenced by the outflow.
A case study of an early galaxy cluster with the Athena X-IFU
Authors: Castellani F. , Clerc N. , Pointecouteau E. , Bahé Y. M. , Schaye J. , Pajot F.
Published: November 2023

Context.Observations of the hot gas in distant clusters of galaxies, though challenging, are key to understanding the role of intense galaxy activity, supermassive black hole feedback, and chemical enrichment in the process of massive halo assembly.

Aims.Using X-ray hyperspectral data alone, we assess the feasibility of retrieving the thermodynamical hot gas properties and chemical abundances of az = 2 galaxy cluster of massM500 = 7 × 1013 M⊙, extracted from the Hydrangea hydrodynamical simulations.

Methods.We created mock X-ray observations of the future X-ray Integral Field Unit (X-IFU) on board the Athena mission. By forward-modelling the measured 0.4 − 1 keV surface brightness, the projected gas temperature and abundance profiles, we reconstructed the three-dimensional distribution for the gas density, pressure, temperature, and entropy.

Results.Thanks to its large field of view, high throughput, and exquisite spectral resolution, one X-IFU exposure lasting 100 ks enabled the reconstruction of density and pressure profiles with 20% precision out to a characteristic radius ofR500, accounting for each quantity’s intrinsic dispersion in the Hydrangea simulations. Reconstruction of abundance profiles requires both higher signal-to-noise ratios and specific binning schemes. We assess the enhancement brought by longer exposures and by observing the same object at later evolutionary stages (atz = 1 and 1.5).

Conclusions.Our analysis highlights the importance of scatter in the radially binned gas properties, which induces significant effects on the observed projected quantities. The fidelity of the reconstruction of gas profiles is sensitive to the degree of mixing of the gas components along the line of sight. Future analyses should aim to involve dedicated hyper-spectral models and fitting methods that are able to grasp the complexity of such three-dimensional, multi-phase, diffuse gas structures.
Determining the Factors Can Influence the Firm Value: To Create Good Corporate Governance
Authors: Rosia Rina , Wafa Dinar Rifatul , Novita Yeyen , Mujibatun Siti , Ghofur Abdul
Published: November 2023

This study aims to analyze the influence of earnings management, capital structure, and accounting conservatism with managerial ownership as a moderating variable. Earnings management is measured using the modified Jones model, the capital structure is proxied by the Dept to Equity Ratio (DER), accounting conservatism is calculated by the difference between the company's net profit and operating cash flow divided by total assets. Company value is proxied by the Tobin's ratio, and managerial ownership is calculated by the total management shareholding divided by the number of outstanding shares. This research is a quantitative study with a population of 159 companies and the number of samples used is 90 samples from 30 company data obtained through purposive sampling method. Methods of data analysis using panel data regression techniques with Eviews software version 8. The result is that earnings management, capital structure, and accounting conservatism have no effect on firm value. Managerial ownership is not able to moderate the effect of earnings management, capital structure, and accounting conservatism on firm value
Correlation of Structural and Behavioral Factors to Dropout Status of Childhood Immunization
Authors: Sriatmi Ayun , Martini Martini , Patriajati Sutopo , Budiyono Budiyono , Handayani Novia , Kusumawati Aditya , Armunanto Armunanto
Published: November 2023

Immunization dropout (DO) occurs when a child does not receive follow-up immunization according to the set schedule. High dropout status has potential increasing the risk of contracting dangerous diseases because the body immunity is not optimal. Resistance, hesitate and distrust of vaccines lead to delays and refusal of immunization. The study aims to analyze the incidence of immunization dropout from structural and behavioral dimensions. This is a quantitative study with a cross-sectional approach. The population was all children aged 12-23 months in Central Java province with totally sample of 685 people. Data were collected through interviews using structured questionnaire instruments and observations using the MCH Book. The dropout rate for DPT/HB/HiB_1 to DPT/HB/HiB_3 immunization was 6.2%, and to Meales/Rubella was 10.4%. A total of 14.4% of children have a dropout immunization status. For structural dimension, there is a correlation between information sources and family income with dropout status. For behavioral dimension, variables of knowledge, perception of adverse events and perception of booster correlated with immunization dropout status. The involvement of all stakeholders is needed to provide correct information about vaccines and immunization, as well as the use of attractive communication media. Responsive and adequate surveillance and anticipation of adverse immunization reports should be strengthened.
Assessment of Safety Behavior and Hazard Communication Knowledge Amongst Tangerang-Merak Toll Road Users
Authors: Varina Eka Lailita Eti , Mahachandra Manik
Published: November 2023

A hazard prevention symbol is an essential safety communication tool in helping to indicate the various hazards present. The hazard prevention symbol warns against caution, providing needed safety information and instructions. This study aims to determine the understanding of symbols of danger and driving behavior on toll roads, especially the Tangerang-Merak toll road. The sampling method was carried out using a random sampling sample. Safety behavior will be assessed using the Driver Behavior Questionnaire (DBQ). The results obtained by car drivers on toll roads, on average, understand the symbol of hazard communication in horizontal alignment conditions, vertical alignment, and dangerous road warnings. However, many drivers need help understanding the communication hazard symbol on the lane separator construction. Based on the Driver Behavior Questionnaire, sequentially, the deviant behavior of car drivers on the Tangerang-Merak toll road, namely violations, lapses, and errors.
Blockchain-Based Web Certification uses Descriptive Analytics to standardize Data
Authors: Bahrudin Muhammad Joko Umbaran Haris , Isnanto R. Rizal , Gernowo Rahmat
Published: November 2023

Certification is an important component for a cryptocurrency project in terms of data security, networks and tokens or coins in the cryptocurrency network to attract investors to invest in a blockchain project. This is what encourages this research to conduct data analysis trials based on descriptive analysis for cryptocurrency project certification. In the data analysis used, the data analysis process includes using a pilot test to test the questionnaire so that the data obtained for testing the Abrar LMS system is maintained and its validity is continued. Pilot test is a test of the reliability and validity of research equipment. Before the survey was distributed to actual respondents, the survey was first tested on students and heads of university study programs. The validity of a test or a series of procedures indicates how well it measures what it is designed to measure. This interest can be proven by the results of respondents who have been analyzed using SPSS to conduct pilot tests, validity tests, and reliability tests. Testing the system on respondents using alpha to test the functionality of the system so that valid results are obtained from the combination of respondent data analysis.
Data Visualization and Forecasting Domestic Component Level (TKDN) Indonesian Ministry of Industry Using Power Business Intelligence
Authors: Fikri Moh. Ali , Darsih Darsih , Amalia Dita Rizki
Published: November 2023

The government is optimizing the Domestic Component Level (TKDN) for strategic projects funded by the State. Domestic products that must be used must have a TKDN value of at least 25%. According to the Head of LKPP, the target for procurement of government goods/services for domestic products (PDN) in 2023 is 90%. Ironically, products that have TKDN certificates are not comparable to the needs of government agencies. This is of particular concern, whether the targets declared in 2023 will be met or not. Therefore, a touch of technology is needed to be able to analyze TKDN data quickly and precisely. Power Business Intelligent is one of the tools that can be used to analyze data easily understood. Data is taken on the official website of TKDN Kemenperin which has a Microsoft excel file extension. The indicators observed are the trend of TKDN certificates per year, the trend of certificates per month, the trend of goods categories, regional demographic trends in Indonesia and forecasting TKDN certificates for the next 5 years. The overall results of TKDN certified products in 2019-2022 were 33,554. The average number of TKDN products is 49.15% with the highest content of 99.99%. On average, the Ministry of Industry issues TKDN certificates every day as many as 43 products. The number of products certified TKDN with the LKPP e-catalog website is not comparable. The results of the analysis showed that the number of new TKDN certified products was 34.6% and 65.94% had not been certified.
Development of application for sustainable tourism index calculation
Authors: Purwaningsih Ratna , Arvianto Ary , Fitria Rizqi Fauzul , Putri Ade Aisyah Arifna
Published: November 2023

The lack of a reliable application to automate the assessment process has led to surveyors performing manual calculations, which increases the risk of human errors during data processing. Therefore, this research aims to develop a composite index calculation application designed using Macro VBA in Excel, focusing on user-friendliness and customized functionalities based on user needs. The proposed application assesses sustainable cultural tourism across four dimensions: environmental, economic, government, and socio-cultural. The development process follows the Rapid Application Development (RAD) method, consisting of three stages: requirements planning, workshop design, and implementation. The application's validity is assessed by comparing its output with manual calculations. The application was tested through functionality, maintainability, and usability testing. Application usability was evaluated using the Computer System Usability Questionnaire (CSUQ) method. The research outcome is a reliable composite index calculation application, enhancing the efficiency and accuracy of sustainable tourism assessments.
Designing Online English Test: View from Natural Environmental Preservation
Authors: Alfarisy Fitri , Nur Patria Aditya
Published: November 2023

This research focuses on designing an online English language test that prioritizes environmental preservation. As advancements in technology revolutionize the field of language testing, it is essential to ensure that these innovations align with sustainable practices. By incorporating eco-friendly principles into test development, administration, and data management, language testing programs can contribute to environmental conservation while maintaining the validity and reliability of language assessments. The research explores various strategies and considerations for developing an online language test that minimizes paper usage, reduces energy consumption, and mitigates transportation emissions. Sustainable item formats, digital resources, and energy-efficient infrastructure are emphasized, along with secure test administration practices and responsible waste management. The benefits of such an online language test include reduced environmental impact through paper reduction, energy efficiency, and decreased transportation emissions. Additionally, it promotes accessibility, reach, and inclusivity by enabling remote test-taking and flexible scheduling options. Collaboration, research, and awareness play critical roles in advancing sustainable language testing practices. By integrating environmental considerations into language testing, we can contribute to the broader objective of sustainable education practices and inspire a greener future.
Deep Learning on Medical Imaging in Identifying Kidney Stones: Review Paper
Authors: Sulaksono Nanang , Adi Kusworo , Isnanto dan Rizal
Published: November 2023

Medical imaging is currently using artificial intelligence-based technologies to aid evaluate diagnostic information images, particularly in enforcing kidney stones. Artificial intelligence technology continues to develop, many studies show that deep learning is more widely used compared to traditional machine learning, so an Artificial intelligence system is needed to assist the accuracy of health diagnoses, thus helping in the field of radiology health. The aim of the research is to use artificial intelligence with deep learning models to help detect abnormalities in the kidneys. This research method is a literature review of Scopus data related to deep learning in medical imaging in detecting kidney stones. The results of using Artificial Intelligence in medical imaging can be used in diagnosing diseases including detecting Covid-19, musculoskeletal, calcium scores on Cardiac CT, liver tumors, urinary tract lesions, examination of the abdomen and kidney stones. Utilization of Artificial Intelligence in detecting kidney stones can be done with various classification models including XResNet-50, ExDark19, CystoNet, CNN, ANN. Using the right model and having a high accuracy value can help radiologists to accurately detect kidney stones.
A Systematic Literature Review On Missing Values: Research Trends, Datasets, Methods and Frameworks
Authors: Setiawan Ismail , Gernowo Rahmat , Warsito Budi
Published: November 2023

Handling of missing values in data analysis is the focus of attention in various research fields. Imputation is one method that is commonly used to overcome this problem of missing data. This systematic literature review research aims to present a comprehensive summary of the relevant scientific literature that describes the use of the imputation method in overcoming missing values. The literature search method is carried out using various academic databases and reliable sources of information. Relevant keywords are used to find articles that match the research question. After selection and evaluation, 40 relevant articles were included in this study. The findings of this study reveal a variety of imputation approaches and methods used in various research fields, such as social sciences, medicine, economics, and others. Commonly used imputation methods include single imputation, multivariate imputation, and model-based imputation methods. In addition, several studies also describe a combination of imputation methods to deal with more complex situations. The advantage of the imputation method is that it allows researchers to maintain sample sizes and minimize bias in data analysis. However, the research results also show that the imputation method must be applied with caution, because inappropriate imputation decisions can lead to biased results and can affect the accuracy of the research conclusions. In order to increase the validity and reliability of research results, researchers are expected to transparently report the imputation method used and describe the considerations made in the imputation decision-making process. This systematic review of the literature review provides an in-depth view of the use of the imputation method in handling missing values. In the face of the challenge of missing data, an understanding of the various imputation methods and the context in which they are applied will be key to generating meaningful findings in various research fields.
Comparison of Optimizers for Drone Signal Detection Using Convolutional Neural Networks (CNN)
Authors: Taqiyuddin Muhammad , Adi Kusworo , Dwi Nurhayati Oky , Ochi Hiroshi
Published: November 2023

Convolutional Neural Networks (CNNs) have emerged as a promising approach for drone signal detection from radio frequency (RF) data. The choice of optimizer significantly affects the performance of CNNs, as it influences the network's ability to learn complex patterns. In this paper, we conduct a comprehensive comparison of popular optimizers, including SGD, Adam, RMSprop, and Adagrad, and their variants, for drone signal detection using CNNs on an RF dataset. The results demonstrated that RMSprop outperformed other optimizers, particularly for larger datasets, maintaining consistently high accuracy with increased test data. Adam, Adamax, and AdamW also achieved impressive accuracy levels above 95%, with the exception of the Adadelta optimized model, which showed lower accuracy due to suboptimal performance during training. In conclusion, the RMSprop optimizer is the most suitable for drone signal detection using a CNN model, although other optimizers such as Adam, Adamax, and AdamW can also provide satisfactory results.
Analysis Of The Relevance Of Meeting Activities To The Number Of Scientific Publications Using Invitation Management System Data
Authors: Kusdiantoro  , Selo  , Widyawan
Published: November 2023

The invitation management system is one of the applications of the Smart Information System. One invitation management system developed by the Faculty of Engineering Gadjah Mada University (FT UGM) is the SIMADANG application. SIMADANG manages data from all meeting activities (meetings and FGDs) at FT UGM, which can be processed to determine the relevance of the meeting activities to performance achievements, one of which is the number of scientific publications. The invitation management system data is processed using panel data regression and produces several findings. From data processing it was found that the frequency and number of meeting participants had a significant effect on the effectiveness of the meeting indicated by the number of scientific publications.
Comparison of Security Performance of NTRU and ECC Algorithms For RFID Authentication
Authors: Bambang Harjito  , Muhammad Fadhli Putra Mulyana
Published: November 2023

The rapid development of the Internet of Things creates information security vulnerabilities due to the unavoidable process of exchanging data. One device that is vulnerable to data security is RFID. One way to increase its security is to embed a cryptosystem in it. The NTRU algorithm can be a solution because of its low computational power. However, ECC is widely used because its computational power requirements are lower than other traditional public key algorithms. This research proposes the implementation and performance analysis of the ECC and NTRU algorithms on RFID devices. Testing is carried out by running 100-400 RFID devices simultaneously. The key generation and ECC decryption processes were faster than NTRU. The NTRU encryption process is faster than ECC. The ECC algorithm is more efficient and suitable for RFID devices. However, ECC is vulnerable to invalid curve attacks that can attack at the recommended security level. In NTRU, there is also a vulnerability to attacks using the LLL algorithm, but these attacks cannot yet attack the recommended security level. For this reason, the NTRU algorithm is more suitable for use on RFID devices, provided that the RFID device must increase its resources for computational needs heavier than ECC.
Identifying Potential Students as College Customers Using Machine Learning: A Literature Review
Authors: Handayani Sri , Isnanto R. Rizal , Warsito Budi
Published: November 2023

College customers begin with prospective students who are important asset opportunities. Potential prospective students can be identified from academic score data while in SMA / SMK / MAN, achievement data, data on the number of siblings, and data on parents' income. After being a student, their potential can be identified from GPA scores, non-academic achievement data and length of study in college. When becoming an alumnus, college customers can be identified for their potential from the waiting time for alumni to get a job, place of work, and type of alumni work. The use of CRM (Customer Relationship Management) is expected to be able to recognize the potential of college customers to benefit universities. This article contains a systematic literature review of several research themes that have been carried out related to the utilization of machine learning for CRM using several existing machine learning algorithms, The goal of this article is to find new ideas that are better at implementing CRM in college by using machine-based learning methods. The results found turned out that there were only 5 literatures out of 50 that did machine learning method development for CRM or only 5/50 *100% = 10%.
Effectiveness of Automatic Detection of Osteoarthritis using Convolutional Neural Network (CNN) Method with DenseNet201 on Digital Images of Knee Joint Radiography
Authors: Nurfadhillah Dea , Santoso Gunawan , Fatimah  , Murti Wibowo Gatot , Darmini  , Nuryatno
Published: November 2023

The manual detection of osteoarthritis using Kellgren Lawrence system depends on experience and agreement between doctors. The study was conducted to develop DenseNet201 to assist doctors in making a diagnosis of osteoarthritis grading. This study analyzes the accuracy; sensitivity; specificity; positive predictive value (PPV) and negative predictive value (NPV) of DenseNet201 in grading osteoarthritis and compares the classification results between DenseNet201 and radiologists in detecting osteoarthritis on knee joint images. This study is an applied experiment that compares the classification results of DenseNet201 and radiology specialists. Firstly, DenseNet201 is built with the MATLAB R2021a. Tests are carried out by measuring accuracy, sensitivity, specificity, PPV and NPV of 75 images of knee joint. Lastly, the data is analyzed using the Wilcoxon statistical test. The study has shown that the performance of DenseNet201 was good in detecting osteoarthritis, with accuracy value 91.84%; sensitivity value 76.61%; specificity value 94.32%; PPV 82.60% and NPV 94.32%. There was no significant difference between classification results using DenseNet201 and radiologist with a value (p>0.05) of 0.119. DenseNet201 can be considered as an alternative diagnostic tool for osteoarthritis with the condition that verification of the diagnostic decision still refers to the confirmation and justification of the radiologist.
Analysis of Physical and Chemical Parameters as One of the Determinants of Tasi Tolu Lake Water Quality
Authors: Maia da Silva Saturnina , Hydayat Jafron Wasiq , Muhammad Fuad
Published: November 2023

Tasi Tolu Lake is a water which has salty characteristics and has its own uniqueness and natural beauty. The potential of lake resources owned by this lake is mangrove forests, water bird species, fish, and ecotourism potential. The function of this lake is to provide economic resources for fishing activities, ecotourism potential, which has a unique nature. The purpose of this research is to analyze physical and chemical parameters as one of the determinants of Tasi Tolu Lake water quality. The method used is STORED method and accordance with class II quality standards, according to the regulation of the Minister of Environment no. 115 of 2003 concerning guidelines for controlling the status of water quality and implemented in the Republic of Indonesia government regulation no.82/2001. The results of analysis physical and chemical parameters as one of the determinants of Tasi Tolu Lake water quality is moderately polluted, with chemical parameters consisting of pH and DO values still meet the quality standard values, physical parameters in the form of temperature values that meet the quality standard values, while the turbidity and TDS values is exceeding the quality standard values.
Green Open Space Revitalization Using Citizen Science and Green Design Theory: A Case Study of Green Open Space in Bener Village, Yogyakarta
Authors: Willdan Muhamad , Cahyo Kresnanto Nindyo , Iqbal Ramadhan Raihan , Said Nur , Harisa Putri Wika
Published: November 2023

The revitalization of green open space is becoming an increasingly critical issue in cities with dense populations. The population density in big cities causes the growth of slums and insufficient public utilities, one of which is the availability of green open space. The availability of green open space is required to satisfy every need of citizens for public spaces with multifunctional uses as a highly needed public space in the middle of limited urban space. Green open space can be used by the public to enjoy fresh air, as a healthy recreation area, a gathering place for residents, and for a variety of other purposes. However, there are major obstacles facing green open space today, which are not well maintained, and this is thought to be due to the surrounding community's lack of literacy on the importance of green open space, minimal aspects of green open space functionality, and residents' carrying capacity for green open space maintenance. It is intended that by incorporating the community in the planning, management, and maintenance stages in a participatory manner, it would result in the long-term usage of green open space, benefiting both the community and the environment.
Application for waste hotspots investigation in the frozen shrimp upstream supply chain using environmental value stream mapping (E-VSM)
Authors: Krisnasari Dea Dita , Vanany Iwan
Published: November 2023

The waste that frequently results from the frozen shrimp industry includes the use of large amounts of clean water for processings, the production of large amounts of wastewater, the production of waste materials, and the utilisation of electricity from processings, all of which have an negative effect on the environment. This has indeed created improvement strategy with environmental integration as a way out to reduce waste hotspots in the frozen shrimp supply chain. The case study addresses a frozen shrimp company in Indonesia that encounters difficulties in natural resources utilization. Environmental Value Strseam Mapping (E-VSM) is used for the framework of a model to analyse upstream supply chain flows and to identify value added and non value added activities. Coagulant as a by-product from shrimp shells and seasoned shrimp powder from shrimp heads are used to potentially boost the added value of shrimp waste. Identifying and eliminating waste points in the frozen shrimp upstream supply chain will result in a 78% reduction in electricity use, a 68% reduction in water use, a 30% reduction in distribution costs, a 69.6% reduction in non-value-added activities, and a complete elimination of carbon emissions from the distribution process when compared to current conditions.
Sustainability of Rural Ecotourism
Authors: Suryani Dewi Amanatun , Purwanto Purwanto , Purnaweni Hartuti , Yuniningsih Tri
Published: November 2023

Increasing public awareness of the environment and the development of rural tourism has attracted researchers' interest in conducting studies on ecotourism in rural areas. Many tourist villages use the ecotourism concept in developing their tourism. It is hoped that the development of tourist villages will be able to encourage the realization of sustainable tourism. This research uses a literature study with bibliometric methods from data sourced from Scopus by utilizing Vos Viewer, Excel and Data wrapper to visualize the results. The findings of this research include 7 clusters based on keywords, namely: sustainable tourism, rural tourism, rural development, ecotourism, smart tourism, agritourism, and cultural tourism. The results of this research also identified authors who were cited the most, countries of origin with the largest number of articles, and links between countries that were most influential in writing on the themes of rural tourism, ecotourism, and sustainability. This article is organized into several sections, namely research objectives, methodology and data tracking, discussion analysis, and closing section. The conclusion presents future development trends for the study of rural development, entrepreneurship, and smart tourism which is increasingly of interest to researchers. This reflects a significant contribution to the development of sustainable tourism in subsequent research.
Green Court Towards Ecojustice
Authors: Putrijanti Aju , Sulistyawan Aditya Yuli
Published: November 2023

Everyone has the rights to have a good and healthy environment. Through judiciary bodies is one of the ways to fulfill the rights. Research questions are how is the role of green court to implement ecojustice and access to justice to get ecojustice. The method use is normative legal research, use primary and secondary data. Datas will be analyzed in qualitative method and describe with descriptive analysis. To build green court, has to prepare the system of law which based on principle of good environmental law. The competence of green court and its formal law should be clear, judges should have environmental certified, raise the society awareness to protect the environmental. Regulations to protect the environmental defender has to be made as well as to build green court. Acess to justice to get ecojustice can be made from judiciary system. Regulations about Anti Eco SLAPP has to be made, in order to protect to environmental defender. Filling lawsuit with citizen lawsuit mechanism also has to be made, this is to give opportunity to everyone to have healthy environment. Judiciary system has to make regulations that possible to build green court as judiciary body to protect the environment and Anti Eco SLAPP, citizen lawsuit which has to be developed in future.
Industrial Noise Mapping: Literature Review, Designed for New Plant Operation
Authors: Putro Edi Karyono , Mangkoedihardjo Sarwoko , Karnaningroem Nieke , Pandabessi Ellina Sitepu , Syafei Arie Dipareza
Published: November 2023

This paper review focuses onto industrial mapping published by researchers in different industrial sectors from different countries published in past 10-year time aimed at mapping software usage and mitigation plans implemented. The review found out that ArcGIS and SurferPLAN were commonly utilized in visualizing the industry measured noise into the contour map and the noise mapping study in each specific discrete study area could be used as initial document or basis for decision maker or town city planning to plan and execute the noise mitigation measures. In the industrial expansion planning, on the other hand, it is obvious that the previous study of noise monitoring and noise mapping could be used as basis of predicting the noise level of any planned machinery installation, heavy equipment operation, or even building construction and its probability of noise propagation as well as predicted noise control measures.
The Concept of Thematic Village as A Driver of Sustainable Settlement in Semarang City
Authors: Yuliastuti Nany , Esariti Landung , Humaira Syaeful Hana , Putri Pressilia Adhista
Published: November 2023

Population growth and urbanization are global issues that the world must face. Increased pressure on the socio-economic welfare of the community, the environment, and living standards can lead to poverty. Several countries in the world, including Indonesia, are trying to overcome these challenges in line with the Sustainable Development Goals (SDGs). Semarang City is one of the cities that is committed to tackling poverty in 2016-2021 through the "Great Gate" program. One of the tangible manifestations of responding to poverty alleviation in Semarang City is the Thematic Village program, which requires a minimum of two urban villages for each sub-district in Semarang City. This paper aims to identify or assess the potential for sustainable thematic villages. A qualitative approach is used in this study. Through a case study in Batik Rejomulyo Village, several strategies were formulated using a SWOT analysis. The results show that there are several potentials that Rejomulyo Batik Village has, including a reasonably strategic location, the presence of skilled batik-making resources, a friendly community, and the opportunity for tourism integration with the Old City. Batik Village's existence can improve the community's quality of life, provide opportunities for the district to manage its environment, improve social relations and strengthen social ties through an institution. This shows that thematic villages could encourage the realization of sustainable settlements.
Comparative Study on the Structure of Plankton Community at Integrated Multi Trophic Aquaculture (IMTA) and Conventional Monoculture Net Cages at Coastal Area of Menjangan Besar, Karimunjawa Islands, Indonesia
Authors: Purnomo Putro Sapto , Saodah Rifahyanti Siti , Hariyati Riche , Adhy Satriyo
Published: November 2023

Over the last decade, a modern sustainable aquaculture has become a driving force to speed up a production capacity but still pay attention to the carrying capacity of the environment for sustainability of the farming practice. We assessed the modern farming practice using stratified double net cage – Integrated Multi Trophic Aquaculture (SDNC-IMTA) to be compared to the conventional monoculture using structure of plankton community. The study was carried out at Menjangan Besar Island, Karimunjawa, Central Java during October 2021. The purpose of this study was to compare the plankton community's structure and determine the correlation between plankton abundance and water quality. Plankton sampling was carried out using the filtration method at three locations, i.e. monoculture cages, SDNC-IMTA cages, and reference sites. The abundance of phytoplankton and zooplankton were considerably higher at IMTA sites compared to the monoculture and reference sites. In particular, the highest abundance of zooplankton was found at the IMTA of 8569 ind.L-1, while the lowest abundance of zooplankton was found at the reference location of 3098 ind.L-1. The species considered as biological indicator were Ceratium sp., Dinophysis sp., Navicula sp., Pseudonitzchia sp., Oscillatoria sp., and Rhizolenia sp. The results of the NMDS ordination of phytoplankton data obtained a tendency of grouping the stations based on the three main sampling sites, while results from the zooplankton data did not show clustering between the sampling sites. The analysis of plankton abundance using with BIO ENV (Primary V 6.1.5) showed that the most abiotic factors affecting the abundance of plankton were temperature, turbidity, and salinity (
pvalue = 0.176).