bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perancangan Sistem Informasi Pemesanan Berbasis Web di Restoran Pawon Jinawi
Authors: Primanda Aldyan Gilang , Fajri Ika Nur 
Published: December 2024

<p><strong>Abstrak:</strong></p><p>Pawon Jinawi merupakan sebuah usaha restoran yang bergerak dalam bidang penjualan makanan dan minuman. Restoran ini menyajikan berbagai menu rumahan khas Jawa. Namun, sistem pemesanan dan pengelolaan data di restoran ini masih dilakukan secara manual, yang menimbulkan masalah seperti lambatnya pelayanan dan risiko kehilangan catatan pesanan. Penelitian ini bertujuan untuk mengembangkan sistem informasi berbasis web yang memudahkan pelanggan dalam melakukan pemesanan secara <em>online</em>. Sistem ini juga dirancang untuk membantu karyawan dalam pengelolaan data pesanan dan pembayaran secara lebih terstruktur. Metode pengembangan yang digunakan adalah <em>waterfall</em>, sebuah metode pengembangan perangkat lunak yang berjalan secara berurutan dan sistematis. Setiap tahap diselesaikan secara menyeluruh sebelum melanjutkan ke tahap berikutnya, untuk tahapannya mencakup lima tahap <em>Requirement, Design, Implementation, Verification, dan Maintenance</em>. Pengujian sistem dilakukan menggunakan metode<em> Black box</em>. Hasil penelitian ini yaitu sebuah sistem informasi pemesanan berbasis web<em>.</em> Setelah implementasi sistem akan meningkatkan efisiensi operasional restoran, dengan waktu pemrosesan pesanan yang berkurang sebesar 45%, serta peningkatan kepuasan pelanggan dalam hal kecepatan dan kemudahan proses pemesanan. Penelitian ini didukung oleh beberapa penelitian terdahulu yang menunjukkan manfaat dari penerapan sistem informasi untuk pengelolaan pemesanan di restoran</p><p>==================================================</p><p><strong>Abstract:</strong></p><p><em>Pawon Jinawi is a restaurant business engaged in the sale of food and beverages. This restaurant serves a variety of Javanese home-style menus. However, the ordering system and data management in this restaurant are still done manually, which causes problems such as slow service and the risk of losing order records. This study aims to develop a web-based information system that makes it easier for customers to place orders online. This system is also designed to help employees manage order and payment data in a more structured way. The development method used is waterfall, a software development method that runs sequentially and systematically. Each stage is completed thoroughly before proceeding to the next stage, for the stages include five stages of Requirement, Design, Implementation, Verification, and Maintenance. System testing is carried out using the Black box method. The results of this study are a web-based ordering information system. After the implementation of the system will increase the operational efficiency of the restaurant, with order processing time reduced by 45%, as well as increased customer satisfaction in terms of speed and ease of the ordering process. This research is supported by several previous studies that show the benefits of implementing an information system for managing orders in restaurants</em></p>
Pengembangan dan Uji Usability Sistem Informasi Presensi Berbasis Web di Institusi Pendidikan
Authors: Pratisto Eko Harry , Athifah Daffa Mudia , Purnomo Fendi Aji 
Published: December 2024

<p><strong>Abstrak:</strong></p><p>Penelitian ini bertujuan mengembangkan sistem informasi presensi berbasis website untuk meningkatkan efisiensi dan akurasi pencatatan data kehadiran di sektor pendidikan. Sistem ini mendukung pencatatan kehadiran secara real-time yang dapat diakses dari berbagai perangkat yang terhubung ke internet, memudahkan pengguna seperti guru, siswa, dan pihak administrasi. Melalui pendekatan perancangan sistem berbasis Agile, penelitian ini melibatkan analisis kebutuhan, desain sistem menggunakan Entity-Relationship Diagram (ERD) dan Unified Modeling Language (UML), pengembangan, serta pengujian menggunakan metode usability testing. Hasil uji SUS menunjukkan nilai 82, 5 yang dapat diartikan sistem ini memiliki tingkat kemudahan penggunaan dan efisiensi yang baik, serta meningkatkan transparansi dan akuntabilitas pengelolaan kehadiran. </p><p>=====================================================</p><p><strong>Abstract:</strong></p><p><em>This study aims to develop a web-based attendance information system to enhance the efficiency and accuracy of attendance data recording in the education sector. The system supports real-time attendance recording accessible from various internet-connected devices, facilitating users such as teachers, students, and administrative staff. Using an Agile system design approach, this study involves requirements analysis, system design utilizing Entity-Relationship Diagram (ERD) and Unified Modeling Language (UML), development, and testing through usability testing methods. The test result show 82,5 for SUS score which demonstrate that the system offers a high level of ease of use and efficiency while improving transparency and accountability in attendance management.</em><br /><em>The implementation of this system also shows a reduction in data input errors and an increase in the speed of attendance recapitulation compared to manual methods. However, challenges such as data security and technological infrastructure limitations in certain areas require attention. The web-based system is vulnerable to cyber threats, thus necessitating data security enhancements and infrastructure development to ensure its effectiveness.</em></p><p> </p>
Adding Nativity, Citizenship, and Immigration Status to Health Monitoring and Survey Data
Authors: Marouf Fatma E. , Perreira Krista M. , Pham Huyen 
Published: December 2024

Immigration status and related policies have a significant impact on health outcomes. Yet major national health surveys currently provide little or no information about immigration status, rendering subgroups of noncitizens largely invisible. Even measures of citizenship, nativity, country of birth, and years in the United States, which provide critical information about immigration history, are not consistently included in national data sets. The main objections to asking directly about immigration status are that (1) such questions are too stigmatizing, risking lower response rates and inaccurate responses; and (2) answering the questions may expose respondents to possible immigration or criminal consequences. Our analysis shows that these objections are unfounded or can be mitigated. National health surveys have evolved over the past decades to include questions about mental health, substance use, sexual orientation, and gender identity—topics once assumed to be too stigmatizing to ask about, with possible negative legal consequences. We argue that the time has come to obtain more detailed information about immigration status as well as to consistently include the measures of immigration history mentioned so that we can better evaluate the health consequences of immigrant-related policy choices. ( Am J Public Health. 2025;115(1):75–82. https://doi.org/10.2105/AJPH.2024.307867 )
EmoMBTI-Net: Introducing and Leveraging a Novel Emoji Dataset for Personality Profiling with Large Language Models
Authors: Kumar Akshi , Jain Dipika 
Published: December 2024

Abstract

Emojis, integral to digital communication, often encapsulate complex emotional layers that enhance text beyond mere words. This research leverages the expressive power of emojis to predict Myers-Briggs Type Indicator (MBTI) personalities, diverging from conventional text-based approaches. We developed a unique dataset, EmoMBTI, by mapping emojis to specific MBTI traits using diverse posts scraped from Reddit. This dataset enabled the integration of Natural Language Processing (NLP) techniques tailored for emoji analysis. Large Language Models (LLMs) such as FlanT5, BART, and Pegasus were trained to generate contextual linkages between text and emojis, further correlating these emojis with MBTI personalities. Following the creation of this dataset, these LLMs were applied to understand the context conveyed by emojis and were subsequently fine-tuned. Additionally, transformer models like Roberta, DeBERTa, and BART were specifically fine-tuned to predict MBTI personalities based on emoji mappings from MBTI dataset posts. Our methodology significantly enhances the capability of personality assessments, with the fine-tuned BART model achieving an impressive accuracy of 0.875 in predicting MBTI types, which notably exceeds the performances of Roberta and DeBERTa, at 0.82 and 0.84 respectively. By leveraging the nuanced communication potential of emojis, this approach not only advances personality profiling techniques but also deepens insights into digital behaviour, highlighting the substantial impact of emotive icons in online interactions.
Evaluation of fatigue-induced changes in swimming technique using a tri-axial accelerometer in high performance adolescent swimmers
Authors: Skorulski Maciej , Stachowicz Małgorzata , Kuliś Szymon , Gajewski Jan 
Published: December 2024

Abstract

The present study analyzed the technique and kinematic changes under fatigue in highly trained adolescent swimmers during a 50-meter swim at maximum crawl speed. Twenty-four girls and fourteen boys aged 12–13 participated in the study. The movement of the hip rim was analyzed using a specialized inertial device equipped with a triaxial gyroscope and accelerometer to measure changes in angular velocity and acceleration. Between the first and second lengths of the pool, the following were observed: a significant (F1.36 = 63.6; p < 0.0001; η²=0.64) increase (34%) in maximum pelvic angle, significant (F1,36 = 6.0; p = 0.0193; η²= 0.14;) increase (12.10%) in angular velocity in rotational motion around a vertical axis, and a significant (F1,36 = 11.29; p = 0.0018; η²= 0.24) increase (6.86%) in angular velocity in yaw rotation motion around the sagittal axis. Significant (F1,36 = 13.96; p = 0.0006; η²=0.28) differences in maximum pelvic angle were observed for lap and side. Repeated high-intensity, high-volume repetitions in adolescent athletes can lead to the perpetuation of a faulty movement pattern. Taking this into account, coaches should limit maximum-speed swimming in adolescent athletes to short distances and an appropriate interval and use training methods to reduce asymmetric work such as training snorkels.
A multi-spectral and hyperspectral image dataset for evaluating the health status of avocado, olive and vineyard
Authors: Estrada Juan Sebastian , Demarco Rodrigo , Johnson Ciarán Miceal , Zañartu Matías , Fuentes Andres , Cheein Fernando Auat 
Published: December 2024

Abstract

Assessing the health status of vegetation is of vital importance for all stakeholders. Multi-spectral and hyper-spectral imaging systems are tools for evaluating the health of crops across large areas, particularly when deployed on robotic platforms such as unmanned aerial vehicles (UAVs). However, the literature lacks benchmark datasets to test algorithms for predicting plant health status, with most researchers creating tailored datasets. This work presents a dataset composed of multi-spectral images, hyper-spectral reflectance values, and measurements of weight, chlorophyll, and nitrogen content of leaves at five different drying stages, from avocado, olive, and vineyard trees, which are common crops in the Valparaíso region of Chile. This dataset is a valuable asset for developing tools in the field of precision agriculture and assessing the general health status of vegetation.
Study on the mechanical behavior and penetration performance of composite tungsten alloy penetrator
Authors: Long Fengying , Li Weibing , Li Jun-bao , Zou Bin 
Published: December 2024

Abstract

To improve the penetration performance of armor-piercing projectile, a composite tungsten alloy penetrator was designed, and mechanical property tests, LS-DYNA simulations and ballistic gun tests were conducted to investigate the mechanical behavior and penetration performance differences between composite tungsten alloy penetrator and homogeneous tungsten penetrator. The local microstructure of the residual penetrator tipwas obtained, and the penetration mechanism of the penetrator was deeply analyzed. The results show that the deformation and failure of composite tungsten alloy penetrator exhibit localized characteristics, and the composite structure of the penetrator can reduce the number of cracks and avoid the phenomenon of large cracks cutting off the penetrator. It can better ensure the integrity of the penetrator tip and the durability of penetration power, and has an increasing trend of " tip-form self-sharpening" ability, which has better penetration performance than homogeneous tungsten penetrator. It can provide theoretical reference for further structural optimization and performance improvement of armor-piercing projectile.
Spent lithium-ion battery recycling: multi-stage synergistic deep removal of impurities and lithium extraction
Authors: Lou Wenbo , Liu Dong-yan , WANG Yun , ZHAO Da , SUN Zi-cheng , ZOU Yi , WANG Sheng-yan , CHENG Quan-guo , LI Jian-zhong , LIU Hong-hui 
Published: December 2024

Abstract

Nowadays, the recycling of spent lithium-ion batteries is a key concern in the energy field. Among them, for the purification of Li-containing mother liquor, the targeted multi-means coupling impurity removal methods are mostly employed, which however, inevitably lead to a Li loss of 3~5%, and high costs. In this study, a multi-stage hydrolysis method, combining with the residual P and Al, Mg, Cu, Zn, Ni, Fe, forming hydroxide-phosphate co-precipitation for the synergistic impurity separation, was adopted. Thermodynamic calculations show that Li+ and Mg2+ are insensitive to pH when pH <10, and Al, Cu, Zn, Ni, Fe behave similarly in nature. Impurities should be precipitated as: Fe3+＞Al3+＞Cu2+＞Ni2+＞Zn2+＞Mg2+, with phosphate precipitating first, followed by converting into hydroxide as pH rising. Actual results showed that the order was P＞Fe & Al & Cu & Ni & Zn＞Mg, and the process was divided into three steps, with separation points at pH = 2.37, 8.66, and 11.00, respectively. All the impurity removal efficiencies were close to 100%, the loss of Li was 1.74%. The optimal conditions for Li2CO3 precipitation were determined: an Na2CO3 addition of 1.5 times the theoretical amount, a temperature of 90 oC, a reaction time of 4 hours, and a one-time addition of dosing method. Li precipitation efficiency reaches 90.10%, with a 99.95% purity. The results effectively reduced Li losses and provided a practically feasible basis for the industrial purification of Li-containing mother liquor.
Large scale burning of the upstream catchment results in greater and longer lasting effects on stream macroinvertebrate communities than local site scale burning.
Authors: Shenton Mark D , Thompson Ross M , Kefford Ben J 
Published: December 2024

Abstract

Background
The increasing frequency, severity and intensity of wildfire globally is generally recognised as a significant threat to freshwater biodiversity. Fires impact streams through a range of mechanisms including geomorphological change, altered resource availability and direct impacts on biota. The magnitude and duration of fire impacts on stream ecosystems vary widely. Reasons for this variation are hypothesised to include the effects of fire can be from upstream catchment disturbance, disturbance at the site, or both. Additionally, many studies have sub-optimal designs as they are poorly replicated, short term, lack before data, and/or lack unburnt controls, which may further contribute to this variations in impacts. Here, we use a before-after-control-impact (BACI) design in sub-alpine woodlands in south-eastern Australia with 7 years of before data and 8 years of after data, to determine the effects of landscape-scale fires on stream macroinvertebrate community structure at local and landscape scales.
Results
Catchment scale disturbance had greater impacts for a longer duration (up to 4 years) on macroinvertebrate communities than local site scale disturbance (up to 1 year). Fire-induced changes in in-stream habitat and resources (e.g., substrate composition) were associated with the greatest changes in macroinvertebrate communities. Macroinvertebrate diversity was lower post fire at burnt sites and catchment burnt sites because of both reduced taxa richness and increased evenness. Differences between burnt and unburnt sites were predominantly a consequence of changes to the abundances of Coleoptera and Diptera taxa. Recovery in macroinvertebrate communities, including those downstream of fire, was associated with recovery of riparian vegetation cover at burnt sites.
Conclusions
Larger scale disturbance to the upstream catchment was more important for the macroinvertebrate community than local site scale disturbance. Post-fire management to minimise and ameliorate fire effects on stream macroinvertebrates should focus on limiting the downstream effects of fire on in-stream habitat caused by sediment movement and geomorphic changes.
A lightweight network-based automatic modulation recognition method for resource constrained edge devices
Authors: Sun Long , Li Tantan , Shao Hui , Meng Fanyu 
Published: December 2024

Abstract

With the rapid development of intelligent communication technology, modulation recognition of signals has become a crucial research topic in multiple domains such as radar, communications, and electronic warfare. Currently, deep learning-based modulation recognition methods leverage their powerful feature learning capabilities to effectively improve recognition accuracy in low signal-to-noise ratio environments. However, these methods often suffer from complex network structures, high computational requirements, and demanding hardware platforms. Addressing these issues, this paper proposes an automatic modulation recognition method based on lightweight networks applicable under edge conditions. Firstly, the original I/Q data undergo wavelet threshold denoising to mitigate the impact of noise on signal modulation recognition. Subsequently, by incorporating a phase estimator and an enhanced channel attention mechanism into the model, this approach accurately captures signal features affected by noise and interference, while endowing the network with the ability to learn and focus on key information. Importantly, it replaces complex and redundant network structures by utilizing only three one-dimensional convolutional layers for feature extraction, thereby achieving simplification and optimization of the network architecture.After validation on the public dataset RadioML 2016.10a, the number of parameters of this model is only 0.06M, but the average recognition rate reaches 62.32%.
Multi-directional shearing synchronous polarization phase- shifting interferometer and its interferometry system experimental verification
Authors: zhu Yahui , tian Ailing , wang Hongjun , liu Bingcai , wang Kai 
Published: December 2024

Abstract

This paper explores a multi-directional shearing synchronous polarization phase-shifting interferometer utilizing a birefringent crystal displacer. This design effectively mitigates nonlinear issues and environmental influences commonly encountered in synchronous phase-shifting interferometry. Additionally, it facilitates the acquisition of shear wavefront information from multiple directions. By solving for the coefficients of the measured wavefront using multi-directional differential wavefront information, this system performs fitting coefficient to reconstruct the wavefront. The characteristics of crystal birefringence beam modulation, phase grating diffraction, and polarization phase-shifting array for synchronous phase-shifting interferometry are investigated based on the specific implementation methods of multi-directional shearing and synchronous polarization phase-shifting. Subsequently, the preprocessing method for the multi-directional shearing phase-shifting interferogram was presented, followed by a detailed explanation of the spatial position registration technique for the shearing interferogram and the calculation method of the shear amount. The construction system of the interferometer was experimentally tested using a spherical optical component and was compared with the test results obtained from ZYGO to verify its correctness and testing accuracy.
The effect of plasticizers on rheological, physical and mechanical properties of low cement high alumina gunning refractories
Authors: Mobasheri Mohammad , Hadian Ali Mohammad , Mohammadi Yasaman , Azimi Behzad , Kamali Mehrnoosh 
Published: December 2024

Abstract

In this research, the effect of different plasticizers with different amounts on the properties of monolithic alumina-based refractories has been investigated. All samples were fired at 1100°C and 1550°C. In order to evaluate the desired properties, first the rheological properties of the samples were examined, and then for further investigations, loss on ignition (LOI), percentage of permanent linear changes (PLC), apparent porosity (AP), bulk density (BD) and cold crushing strength (CCS) tests were used. In addition, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffractometry (XRD) were used to characterize the samples. The results of this research showed that the sample containing 1 wt% of ball clay can be the most appropriate one due to its highest strength, highest density and lowest apparent porosity. Moreover, the sample containing 2 wt% of H19 (a commercially available binder) has the optimum properties because of its highest strength for the samples fired at 1100°C. For the mixtures fired at 1550°C, the more amount of silica has caused higher cold crushing strength due to the presence of the low melting point phases which are not desired and therefore, the mixtures with less silica can be used.
Enhancing 3D Gaussian Splatting for Low-Quality Images: Semantically Guided Training and Unsupervised Quality Assessment
Authors: Cao Zehao , Wang Zongji , Zhang Yuanben , Zeng Zhihong , Cai Weinan , Zhang Lili , Liu Junyi 
Published: December 2024

Abstract

This paper proposes CLIPGaussian, an improved training and rendering method for 3D Gaussian Splatting tailored to address the degradation of reconstruction quality under low-quality image conditions. By integrating a multi-view semantic evaluation module based on CLIP and a 3D spatial consistency loss, CLIPGaussian enhances the model's sensitivity to object-level semantics, enabling better reconstruction even with limited or blurred training images. Furthermore, we introduce an unsupervised evaluation method leveraging semantic features and explicit 3D Gaussian properties to assess reconstruction quality, providing practical guidance in scenarios where ground truth is unavailable. Experiments on the Mip-NeRF360 dataset demonstrate CLIPGaussian's superiority, particularly in low-quality image scenarios, validating both the training and evaluation approaches. This work paves the way for more robust and reliable 3D scene reconstruction from imperfect data. Our source code and pre-trained models are available at https://github.com/ZhChessOvO/CLIPGaussian.