High-quality method names are very significant for us to understand programs and maintain software efficiently. Giving concise and consistent method names can help developers understand such programs well, especially ...
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High-quality method names are very significant for us to understand programs and maintain software efficiently. Giving concise and consistent method names can help developers understand such programs well, especially for inexperienced participants. The importance of the naming strategy to software engineering (SE) has attracted researchers from all around the world who are seeking approaches to enhance the quality of method names. We solve this challenge by using a unique two-phase framework that enables us to recommend precise method names. The first phase involves gathering almost 8,000,000 java methods from Github as three assessment datasets. We also offer a quick and easy classifier for classifying different categories of methods to improve the searching efficiency. Then, we use heuristic rules to recommend method names for simple method names prefixed with i.e., get-, set-, and is-. In the second phase, we take advantage of the deep learning network to recommend suitable method names for complex method bodies. The experimental findings show that our framework greatly outperforms well-known approaches. The precision of our framework reaches 62%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document}, outperforming traditional approaches by 2%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} to 13%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document}.
The capture of sharks in the Southern Indian Ocean of java waters in Indonesia has become increasingly prevalent in recent years, posing risks of overfishing and potential extinction. Information regarding shark fishe...
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The capture of sharks in the Southern Indian Ocean of java waters in Indonesia has become increasingly prevalent in recent years, posing risks of overfishing and potential extinction. Information regarding shark fisheries resources in the Indian Ocean Region in the coming years remains uncertain. This research assessed the condition of shark fisheries resources, considering utilization status and estimating production uncertainty of shark resources in the Indian Ocean, landed at the Samudra Fisheries Port (PPS) in Cilacap. The data collected consist of time-series production and fishing effort data from 2010 to 2020, which were landed at PPS Cilacap, as well as the composition of the types of captured fish. The data analysis employed in this study includes trend analysis of Catch Per Unit Effort (CPUE), utilization rate using the Schaefer surplus production model, and production uncertainty estimation using Monte Carlo simulations. Based on the utilization status, shark fisheries in the South java Sea of the Indian Ocean fall within the optimal category, with an average utilization rate of 80.5%. This is evident from the decreasing trend in CPUE values with increasing fishing effort (f). Additionally, the high production uncertainty of shark resources, as indicated by Monte Carlo simulation forecasting patterns with an average annual production of 160.81 ton and a standard deviation of 790.92 kg, underscores the need for stringent monitoring and supervision of shark fishing activities in the South java Sea of the Indian Ocean to prevent overfishing. Regulations regarding shark fishing in the Southern Sea of Jawa of the Indian Ocean, Indonesia by local communities and local governments do not yet exist. However, shark fishery management is already in place at the national level through several regulations issued by the Ministry of Marine Affairs and Fisheries.
Indonesia, one of the most earthquake-prone countries in the world, is currently developing an Earthquake Early Warning (EEW) system. A key component of this system, the Regional EEW, relies on Ground Motion Predictio...
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Indonesia, one of the most earthquake-prone countries in the world, is currently developing an Earthquake Early Warning (EEW) system. A key component of this system, the Regional EEW, relies on Ground Motion Prediction models (GMPMs) to issue end-user alerts. However, in West java, one of the pilot regions for this project, there is a lack of region-specific GMPMs essential for accurate early warnings. Traditionally, GMPMs are developed using linear regression based on complex, predefined mathematical equations and coefficients. However, Machine learning offers the advantages of bypassing the need for predefined equations and effectively capturing the nonlinear behavior present in ground motion data. To address this gap, we evaluated three machine learning algorithms (i.e. Artificial Neural Network [ANN], Gradient Boosting [GB], and Random Forest [RF]) to develop GMPMs for three tectonic categories: shallow-crustal, interface, and intraslab. These models were used to predict Peak Ground Acceleration (PGA) in West java, utilizing 3116 strong ground motion records from 365 earthquakes with moment magnitude ranging from 2.4 to 7 and epicentral distance between 5.5 and 867 km, recorded since 2010. Our results show that The Gradient Boosting model outperformed the others across all three tectonic categories, with the lowest Mean Squared Error values (0.94, 0.60, 0.65), and Standard Deviation of Residuals (0.97, 0.77, 0.80), as well as the highest Pearson correlation coefficient-value (0.83, 0.88, 0.90) for shallowcrustal, interface, and intraslab events, respectively, demonstrating strong accuracy in predicting PGA. The model was further validated with recent earthquake data and from 2024 showing good agreement and confirming its robustness. Epicentral Distance and Moment Magnitude were the most influential in predicting PGA among the six explanatory variables used in this study. These findings highlight the potential of machine learning models to improve the accuracy of
BackgroundFAO/WHO introduced food-based dietary guidelines (FBDG) to promote healthy dietary habits. To translate the FBDG, optimized food-based recommendations (FBR) can be developed using linear programming (LP) to ...
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BackgroundFAO/WHO introduced food-based dietary guidelines (FBDG) to promote healthy dietary habits. To translate the FBDG, optimized food-based recommendations (FBR) can be developed using linear programming (LP) to address problem nutrients. Despite the importance of local-specific FBR for anemia prevention, no study has reported the effect of nutrition education which promoted FBR in adolescent girls. Therefore, this study aimed to investigate the effect of optimized FBR in adolescent girls in improving dietary and nutrient intakes, hemoglobin levels, and memory *** intervention study was carried out in Malang District, Indonesia amongst 14-18 year adolescent girls. The study's Indonesian slogan was Remaja which meant Active, Healthy, Smart, and Creative adolescents. The optimized FBR was developed using LP and translated into six key messages. Twenty-week nutrition education was integrated into the weekly school's *** 20 weeks, a significant increase in dietary practices (animal protein, liver, plant protein, vegetables), nutrient intakes (protein, fat, iron), and memory performance (digit span forward and backward) were found in the intervention group. In contrast, there was decreases in the control group's intakes of animal and plant *** finding shows that nutrition education with optimized FBR increased intakes of nutrient-dense food, protein, fat, iron, and memory performance (concentration). Nutrition education with optimized FBR should be integrated into the school system together with weekly iron supplementation for anemia prevention among these adolescent *** registrationThe study was registered on *** (ID No: NCT03946475).
This study examines the local dynamics of the 1965-1966 communist massacres in Indonesia through a micro-historical analysis of the Gunung Kidul region, a mountainous area southeast of Yogyakarta that constituted a si...
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This study examines the local dynamics of the 1965-1966 communist massacres in Indonesia through a micro-historical analysis of the Gunung Kidul region, a mountainous area southeast of Yogyakarta that constituted a significant communist stronghold. Drawing on ethnographic fieldwork and oral narratives collected between 2019 and 2022, this research enhances our understanding of these events by exploring how village social structures and relationships contributed to both the dynamics of repression and the emergence of forms of resistance. The study makes three main contributions. First, it illustrates how the Indonesian Communist Party (PKI) established itself in rural areas by adapting its ideology to javanese sociocultural frameworks and leveraging existing village networks. Second, it reveals how violence, although primarily stemming from military operations, intensified according to pre-existing rivalries and inter-village political dynamics - its intensity varying with local social dynamics and geographical accessibility. Third, it documents forms of resistance rooted in javanese ritual (kejawen) and initiatory (kanuragan) practices. This 'bottom-up' approach, combining microhistory and anthropology, highlights how villagers reappropriated state repression logics and developed avoidance strategies. It reveals how they interpreted these events through local socio-ritual categories and developed modes of action that shaped a particular memory. This perspective enriches our understanding of how national political violence was mediated through local frameworks, thus contributing to debates on state formation, political margins, and collective memory in contemporary Indonesia. Studi ini mengkaji dinamika lokal pembantaian komunis 1965-1966 di Indonesia melalui analisis sehjarah mikro wilayah Gunung Kidul, kawasan pegunungan tenggara Yogyakarta yang merupakan basis komunis yang signifikan. Berdasarkan penelitian etnografis dan narasi lisan yang dikumpulkan antara 2019
We present CPA-Daemon, a microservice for continuous software verification of C code. CPA-Daemon provides full access to the verifier CPAchecker, but adds a clear network interface based on gRPC that abstracts from th...
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ISBN:
(纸本)9783031787492;9783031787508
We present CPA-Daemon, a microservice for continuous software verification of C code. CPA-Daemon provides full access to the verifier CPAchecker, but adds a clear network interface based on gRPC that abstracts from three different modes of execution: (1) running CPAchecker in a separate JVM, (2) running CPAchecker as a native executable compiled with GraalVM, and (3) running CPAchecker in a shared, continuously-running JVM. The last two are novel execution modes that greatly improve the response time of verification in different verification scenarios and enable the seamless integration of CPAchecker as an engine in other verification tooling. Our comparative evaluation shows that CPA-Daemon reduces the response time on small verification tasks down to 17 %, and that it can reduce the response time of existing cooperative verification techniques down to 70 %. While our implementation focuses on CPAchecker, the conceptual ideas are of general nature and can serve as a solution for other verification tools that face similar JVM-specific issues. CPA-Daemon is open source and available at https://***/sosy- lab/software/cpadaemon.
Introduction: A severe skin reaction called Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN) can cause a number of short-term and long-term problems that affect many organ systems. Objective: To desc...
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Introduction: A severe skin reaction called Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN) can cause a number of short-term and long-term problems that affect many organ systems. Objective: To describe acute complications and long-term sequelae in patients with SJS/TEN in two tertiary referral hospitals in West java. Methods: A retrospective study was conducted in patients with SJS/TEN treated from January 1st, 2022, to July 31st, 2024, at Dr. Hasan Sadikin General Hospital Bandung and Cicendo Eye Hospital Bandung. Results: The study included a total of 28 patients, 11 males and 17 females. The study diagnosed patients with SJS (33%), SJS/TEN overlap (31%), or TEN (36%). The age range of the majority of patients was 25-44 years (32%). The most commonly implicated medication was acetaminophen, accounting for 43% of the cases. The average length of hospitalization for SJS was 8 +/- 3.29 days, for SJS/TEN overlap was 15.12 +/- 18.42 days, and for TEN was 13 +/- 9.01 days. The highest SCORTEN was 4. Among SJS and SJS/TEN overlap patients, cheilitis was the most frequent complication, while hypokalemia was the most common acute complication in TEN patients (17%). Long-term skin sequelae include hypopigmentation in five patients and hyperpigmentation in eleven. The most common long-term eye sequelae, dry eye, affected 3 patients. Conclusion: Common acute complications include extensive cheilitis, hypoalbuminemia, hypocalcemia, acute conjunctivitis, and acute kidney injury. Hyperpigmentation and hypopigmentation were found as the most frequent long-term skin complications, and dry eyes were the most frequent long-term eye sequelae. Further studies on the physical sequelae of SJS/TEN are necessary to enhance our understanding of the condition and improve treatment for survivors.
Bandung is one of the major cities of Indonesia, a country that often experiences damaging earthquakes. Geologically, Bandung is located in the Bandung Basin, which has a thick sedimentary fill that likely has a signi...
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Bandung is one of the major cities of Indonesia, a country that often experiences damaging earthquakes. Geologically, Bandung is located in the Bandung Basin, which has a thick sedimentary fill that likely has a significant effect on seismic ground motion. In this study, a microtremor array experiment was conducted to estimate the near-surface S-wave velocity structure using 30 observation sites spread throughout the city, each involving a triangular array configuration. The Spatial Autocorrelation method was applied to obtain dispersion curves, before S-wave velocity structure was inverted for using a Genetic Algorithm. The results show that the engineering bedrock depth in the study area ranges between 100 and 320 m, with a gradual increase toward the south, while the time-averaged shear-wave velocity to 30 m depth (Vs30) is in the range 100-340 m/s, corresponding to site classes SE and SD. These parameters were considered in a seismic hazard analysis in order to determine the effects of site characteristics on ground motion. The results reveal a potentially strong influence, particularly on the amplification factor for the city of Bandung, both for peak ground acceleration and for response spectral acceleration at 0.2 and 1.0 s. Our findings reinforce the need for detailed imaging and analysis of near surface structure in order to produce robust seismic hazard assessments.
This research examines the application of the Conditional Generative Adversarial Network (cGAN) on historic map datasets of java, Indonesia. The procedure is divided into four stages: input, pre-processing, processing...
This research examines the application of the Conditional Generative Adversarial Network (cGAN) on historic map datasets of java, Indonesia. The procedure is divided into four stages: input, pre-processing, processing, and output. The observed data are historical maps from various years of creation from the 1500s to the 1900s. The method used is Pix2Pix which aims to translate the cartographic archives into satellite images. The map sample size has a resolution of 256 x 256 pixels. The generator adopts the U-Net architecture, while the discriminator adopts a patch-based fully convolutional network. The results of the translation are evaluated in both quantitative and qualitative, highlighting that different cartographic characteristics over time, such as map styles, geographic information, scales, and creators vary their response to built models in generator and discriminator performance. Furthermore, this research is expected to facilitate the creation of a database of translated geographic information from historical maps towards satellite imagery as well as authorising the leverage of cartographic heritage collections as part of archival resources to create sustainable cultural heritage in the future.
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