bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efisiensi Penggunaan Teknik Hybrid Terhadap Pembuatan Roti Sourdough
Authors: Budiman Yulius , Jayendra Putu Sabda 
Published: May 2023

Tujuan dilakukannya penelitian ini adalah untuk mengetahui perbandingan hasil akhir dan karakteristik dari penerapan teknik hybrid dan yang menggunakan teknik konvensional terhadap pembuatan roti sourdough, dan pendapat dari responden, terhadap hasil roti Sour dough yang menggunakan tekik hybrid, dan yang mengguakan metode konvensional. Pendekatan yang digunakan dalam penelitian ini adalah kuantitatif dan kualitatif. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah eksperimen, wawancara, kuisioner. Teknik analisis yang digunakan dalam penelitian ini adalah analisis terapan, analisis deskriptif kuantitatif, dan analisis deskriptif kualitatif. Dari hasil eksperimen didapati bahwa karakteristik yang dihasilkan dari roti sourdough yang menggunakan teknik hybrid mendekati karakteristik dari roti sourdough yang menggunakan teknik konvensional, namun terdapat sedikit kekurangan yaitu rasa dan aroma khas dari roti sourdough yang kurang maksimal.

The purpose of this study was to compare the final results and characteristics of the application of hybrid techniques and those using conventional techniques to sourdough bread making, and the opinions of respondents, on the results of sourdough bread using hybrid techniques, and those using conventional methods. The approach used in this research is quantitative and qualitative. Data collection techniques used in this study were experiments, interviews, and questionnaires. The analytical techniques used in this research are applied analysis, quantitative descriptive analysis, and qualitative descriptive analysis. From the experimental results, it was found that the characteristics produced from sourdough bread using a hybrid technique were close to the characteristics of sourdough bread using conventional techniques, but there were a few drawbacks, namely the taste and distinctive aroma of sourdough bread that were less than optimal.
Data assimilation experiments inform monitoring needs for near-term ecological forecasts in a eutrophic reservoir
Authors: Wander Heather L , Thomas R. Quinn , Moore Tadhg N , Lofton Mary E. , Breef-Pilz Adrienne , Carey Cayelan 
Published: May 2023

Ecosystems around the globe are experiencing increased variability due
to land use and climate change. In response, ecologists are increasingly
using near-term, iterative ecological forecasts to predict how
ecosystems will change in the future. To date, many near-term, iterative
forecasting systems have been developed using high temporal frequency
(minute to hourly resolution) data streams for assimilation. However,
this approach may be cost-prohibitive or impossible for forecasting
ecological variables that lack high-frequency sensors or have high data
latency (i.e., a delay before data are available for modeling after
collection). To explore the effects of data assimilation frequency on
forecast skill, we developed water temperature forecasts for a eutrophic
drinking water reservoir and conducted data assimilation experiments by
selectively withholding observations to examine the effect of data
availability on forecast accuracy. We used in-situ sensors, manually
collected data, and a calibrated water quality ecosystem model driven by
forecasted weather data to generate future water temperature forecasts
using FLARE (Forecasting Lake And Reservoir Ecosystems), an open-source
water quality forecasting system. We tested the effect of daily, weekly,
fortnightly, and monthly data assimilation on the skill of 1 to
35-day-ahead water temperature forecasts. We found that forecast skill
varied depending on the season, forecast horizon, depth, and data
assimilation frequency, but overall forecast performance was high, with
a mean 1-day-ahead forecast root mean square error (RMSE) of 0.94°C,
mean 7-day RMSE of 1.33°C, and mean 35-day RMSE of 2.15°C. Aggregated
across the year, daily data assimilation yielded the most skillful
forecasts at 1-7-day-ahead horizons, weekly data assimilation resulted
in the most skillful forecasts at 8-35-day-ahead horizons. Within a
year, daily to fortnightly data assimilation substantially outperformed
monthly data assimilation in the stratified summer period, whereas all
data assimilation frequencies resulted in skillful forecasts across
depths in the mixed spring/autumn periods for shorter forecast horizons.
Our results suggest that lower-frequency data (i.e., weekly) may be
adequate for developing accurate forecasts in some applications, further
enabling the development of forecasts broadly across ecosystems and
ecological variables without high-frequency sensor data.
Statistical-Topographical Mapping of Rainfall Over Mountainous Terrain Using Beta Scaling
Authors: Wienhöfer Jan , Alcamo Lucas , Bondy Jan , Zehe Erwin 
Published: May 2023

We present a robust approach for quantitative precipitation estimation
(QPE) for water resources management in mountainous catchments, where
rainfall sums and variability are correlated with orographic elevation,
but density of rain gauges does not allow for advanced geostatistical
interpolation of rainfall fields.
Key of the method is modelling rainfall at unobserved locations by their
elevation-dependent expected daily mean, and a daily fluctuation which
is determined by spatial interpolation of the residuals of neighbouring
rain gauges, scaled according to the elevation difference. The scaling
factor is defined as the ratio of covariance and variance, in analogy to
the “beta” used in economics.
The approach is parameterized and illustrated for the Chirilu catchments
(Chillón, Rímac, Lurín) in the Andes near Lima, Peru. The results are
compared to conventional IDW (inverse-distance weighting) interpolation
and a merged national rainfall product. The method results in QPE that
are better matching with observed discharges. The combination of
inverse-distance weighting with β-scaling thus provides a robust and
flexible means to estimate rainfall input to mesoscale mountainous
catchments.
王水照：《北宋三大文人集團》
Authors: 麥 嘉倩 
Published: May 2023

LANGUAGE NOTE | Document text in Chinese only.
從問學者到治學者，手握疆繩，駕著“授課，研究，撰稿”的三駕馬車獨自前行，篳路藍縷以求心中所志之道。如此積蓄數十年，不斷打磨成型的《北宋三大文人集團》，即爲王水照先生在這條漫漫長路上登覽觀眺、隨足力所到揮灑而成的遊記。(撮要取自內文首段)
Thermal stress influence on the productive and economic effectiveness of Holstein-Friesian dairy cows in temperate climate
Authors: Sowula-Skrzyńska Elżbieta , Borecka Anna , Pawłowska Joanna , Kaczor Andrzej 
Published: May 2023

Abstract
The aim of this study was to evaluate the heat stress influence on milk production from primiparous and multiparous Holstein-Friesian cows and to estimate economic losses associated with the decrease in the farm’s milk yield. The cows selected for the study were in the middle phase of the 1st, 2nd, and 3rd lactation and were characterized by similar daily milk production. Additionally, the animals were kept in the same conditions and fed with the same feeds throughout the season. The analysis covered two 30-day periods – “cold” (April), in which no days with THI >70 were noted, and “hot” (July), in which THI was above 70 for 90% of the days (74.4 on average). The average daily drop in milk production noted in the hot period was 1.25 kg/cow for multiparous cows and 2.78 kg/cow for primiparous cows. The average daily financial loss resulting from a drop in milk production was €0.55/day/cow in primiparous and €0.46/day/cow in multiparous animals. The calculated daily loss in the profit on production of 1 kg of milk was €0.27/day/kg for primiparous and €0.24/day/kg for multiparous animals. Based on test results, economic losses were simulated depending on the daily milk yield and the size of the primary cattle herd. For the multiparous cows, the estimated losses ranged from €6.07/day (farm sizes 25 cows and average daily milk yield 25 kg) to nearly €219/day (900 cows/25 kg). In larger facilities (900 cows) with an average daily milk yield of 55 kg, the daily loss will be about €481. The obtained results confirmed the assumptions made that with a change in microclimate conditions in the barn, a decrease in the daily production and changes in the milk chemical composition were noted, and the economic efficiency of the studied activity decreased.
From Animal Personality to Animal Individuality in Farm Animals – A Review
Authors: Adamczyk Krzysztof , Nowicki Jacek , Wróblewski Zbigniew , Dutkowska Anna 
Published: May 2023

Abstract
As a result of the domestication process and systematic breeding, livestock species have been shaped as donors of animal goods for humans. The animals’ role so defined, which has remained unchanged for millennia, now faces criticism from intellectuals (posthumanism), pro-animal activists, and increasingly often, postmodern societies. The core aspect of this growing conflict can be described at the level relationship between the personality/individuality of farm animals, animals as persons/nonpersons, and animals as moral subjects/agents. This review aims to discuss these relationships in the context of the current state of ethical reflection and knowledge, and in relation to the future of livestock production. It presents problems of definition and research methodology in the field of animal personality, with particular reference to farm animals, characterises the dilemmas of the moral status of animals in the personality/individuality of farm animals – animals as persons/nonpersons – animals as moral subjects/agents, and discusses the relationship between farm animal personality and animal individuality; moreover, it undertakes to analyse the possibilities of individualised treatment of farm animals at the level of future livestock production. It concludes, among other things, that the concept of “animal personality” in relation to farm animals remains undefined in both research and social spaces. While livestock animals remain moral subjects, some ethical concepts attribute to them a wider range of rights intended for personal moral agents. At the same time, it was noted that an individualised approach to animals appears to be one of the most important aspects in the sourcing food of animal origin in the future, in line with a systematically increasing level of animal welfare.
A Review of Virtual Surgical Object Modeling Technology Based on Force Feedback
Authors: Liu Yu , Liu Baolong 
Published: May 2023

Abstract
The early virtual surgical system was only developed on the computer software, and users could only interact with the surgical model through the mouse. The disadvantage of this way was that users could not get tactile feelings. Therefore, with the development and progress of virtual reality technology, force feedback equipment has been introduced into virtual surgery, and has become a research hotspot in this field, in order to make efforts to feedback equipment in the research institute and higher and higher utilization rate. Researchers, teachers and students used force feedback devices to improve the immersion of virtual surgical system. This article mainly introduced the virtual modeling method in the operation, including geometric modeling and physical modeling, the geometric modeling of the two models are introduced, and summarizes their advantages and disadvantages, the physical modeling of soft tissue deformation modeling of three models are analyzed and compared, and the feedback force calculation model are introduced, finally, expounds some problems faced by modeling technology, virtual surgery The future development is also prospected.
3D Face Feature Processing and Recognition Technology
Authors: Wu Hejing 
Published: May 2023

Abstract
Nowadays, we frequently use a lot of biometric identification technology means, such as: iris recognition, voice recognition and face recognition, but compared with other human biometric features, face information is easier to collect and more easily accepted by the public. According to the survey, in interpersonal contact, most people get information based on the first impression, even if there are changes in external conditions such as age, expression, makeup, etc., but the brain can still recognize these information, this phenomenon shows that face does have more feature information. From the information of a person's facial features, we can effectively distinguish each person. Face recognition is a technology that analyzes the face data and then uses it as an authentication mechanism. Generally, cameras are used to track and collect human faces, model theory and then analyze the collected binary data stream to extract relevant feature data. The research of human face recognition technology began in the middle of 1960s. After 1980s, due to the development of computer technology and the improvement of optical image processing technology, it gradually matured. The real use stage of face recognition is in the late 1990s, with Germany, Japan and the United States as the main technologies.
Score Level Fusion for Iris and Periocular Biometrics Recogniton Based on Deep Learning
Authors: Wang Yufei , Lei Songze , Li Yonggang , Liu Bo , Zuo Huan 
Published: May 2023

Abstract
Traditional iris recognition has high recognition accuracy and low misrecognition rate. However, in the case of mobile terminal or distance, the image resolution and image quality decrease, and the recognition rate also decreases. To solve the above problems, this article is based on deep learning technology, on the basis of single mode state recognition, from different levels of multimodal integration, the iris and the eyes in the score level fusion recognition research, put forward the adaptive dynamic weighted score fusion method, to determine the weighing values can adaptive algorithm of the modal, without artificial specified, dynamic weighting algorithm more flexible, stronger applicability. Experimental results of casIA-Iris-LAMP and CasIA-Iris-Distance Iris database in Chinese Academy of Sciences show that the proposed fusion algorithm has higher recognition accuracy and better recognition performance than the single mode recognition algorithm and the traditional fractional fusion method, which proves the effectiveness of the algorithm.
Research on Static Gesture Recognition Based on Deep Learning
Authors: Zhang Min , Liu Pingping 
Published: May 2023

AbstractWith the continuous development and progress of the times, the ways of human-computer interaction have become more and more diverse. In order to reduce the spread of the new crown virus, gesture recognition has become a hot topic in the field of human-computer interaction in recent years. Traditional gesture recognition is affected by the environment and database, etc., with poor robustness and low accuracy. In order to improve the recognition rate of static gestures, this paper proposes to establish a deep learning model using CNN convolutional neural network, and a static gesture recognition method based on template matching. By establishing a palm template diagram, the gesture image to be recognized is matched with the template diagram based on the feature point, and the image is rotated after matching, and the template based on the grayscale value is matched again, so as to extract the gesture part. Through experimental proof, the algorithm can effectively improve the gesture recognition rate, the recognition accuracy rate reached 93.17%, and the recognition speed is faster.
Super-resolution Image Reconstruction Based on Double Regression Network Model
Authors: Lv Jieyi , Wang Zhongsheng 
Published: May 2023

Abstract
By learning nonlinear mapping functions from low resolution (LR) images to high resolution (HR) images, deep neural networks show good performance in image super-resolution (SR). However, the existing SR approach has two potential limitations. First, learning the mapping function from LR to HR images is usually an ill-conditioned problem, since there exist an infinite number of HR images that can be down-sampled to the same LR image. Thus, the space of possible functions can be very large, making it difficult to find a good solution. Second, paired LR-HR data may not be available in real-world applications, and the underlying degradation method is often unknown. For this more general case, existing SR models tend to generate adaptive problems and produce poor performance. To solve the above problem, we propose a dual regression scheme that reduces the space of possible functions by introducing additional constraints on LR data.
Research on Gaze Estimation Method Combined with Head Motion Changes
Authors: Zhan Xiangyi , Wang Changyuan 
Published: May 2023

Abstract
The line of sight reflects the focus of human attention. Gaze estimation technology has a wide range of application prospects in human-computer interaction, human emotion analysis, commercial advertising, and so on. Gaze estimation needs to be jointly determined by eye movement and head movement because the human gaze is often with the head movement. In this paper, a gaze estimation system with head movement is implemented by a monocular camera, using eye movement features and head movement posture changes to estimate the gaze point. A camera is used as the information acquisition device to extract the eye movement feature information, and the offset of head movement is estimated at the same time. The final fixation point position coordinates are obtained by compensating the fixation point position in the case of head movement, and then the fixation point position coordinates are estimated. For the compensated gaze drop point, the average pixel error on the X-axis is estimated to be 118 pixels, and the average pixel error on the Y-axis is estimated to be 136 pixels.
Direksi Asing, Ukuran Perusahaan dan Penghindaran Pajak dengan Direktur Wanita Sebagai Variabel Pemoderasi
Authors: Setiadi Nyimas Belinda Thania , Widaningsih Desti Sri , Erlita Winda , Hatta Hambali Atika Jauharia 
Published: May 2023

Tax avoidance will result in reduced state revenues which can hinder national development. This study aims to determine the effect of foreign directors and company size on tax avoidance with female directors as a moderating variable. The nature of women who prefer to avoid risks and comply with regulations can influence decision making related to company policies. The research sample was obtained from the annual reports of manufacturing companies listed on the Indonesia Stock Exchange for the period 2015 - 2019 totaling 172 companies. The sampling technique was carried out by purposive sampling. By using panel data regression and moderated regression analysis, the result is that foreign directors have a negative effect on tax evasion, while firm size has a positive effect on tax evasion. In addition, female directors are not proven to be able to strengthen the influence of foreign directors and weaken the effect of company size on tax evasion. Thus, the number of female directors does not influence the decision to avoid tax.
Keywords: Foreign Directors; Firm Size; Female Directors; Tax Avoidance
Desentralisasi dan Ketidakpastian Lingkungan sebagai Pemoderasi Pengaruh Sistem Akuntansi Manajemen Terhadap Kinerja Manajerial
Authors: Bawanti Ida Ayu Gede Weda Satya , Krisnadewi Komang Ayu 
Published: May 2023

The research aims to obtain empirical facts regarding the role of decentralization and uncertainty as a moderator of the relationship between the management accounting system (SAM) and managerial performance. The research location is at the BPD Bali sub-branch office. The method of determining the sample in this study was purposive sampling and obtained 74 heads of business and operational sections who were selected to be sampled with the criteria for a minimum of one year's position. Hypothesis testing uses MRA or moderated regression analysis. The results showed that management accounting systems (MAS) did not affect managerial performance, decentralization and environmental uncertainty acted as moderators and did not moderate the effect of MAS on managerial performance.
Keywords: Managerial Performance; MAS; Decentralization; Environmental Uncertainty
Nilai Tukar, Inflasi dan Return Saham dengan Jenis Industri sebagai Variabel Pemoderasi
Authors: Nugraha Gede Made Ananda Cipta , Wirama Dewa Gede 
Published: May 2023

Stock returns are the results obtained by investors from investment activities and rewards for their courage in taking the risk of investing in stocks in the capital market. The research objective is to determine the effect of exchange rates and inflation on stock returns with the type of industry as a moderating variable. The research was conducted in all companies listed on the Indonesia Stock Exchange during the 2016-2020 period. The number of samples taken was 226 companies using proportionate stratified random sampling technique. The analysis technique used is moderation regression analysis. The results showed that the exchange rate and inflation had a negative effect on stock returns. The impact of the weakening exchange rate and rising inflation on stock returns is stronger in the financial industry.
Keywords: Exchange Rate; Inflation; Stock Return; Industry Type
Bahasa IndonesiaSelf Assessment System, Diskriminasi, dan Kemungkinan Terdeteksinya Kecurangan pada Persepsi Tax Evasion
Authors: Kumala Dewi Ni Made Ratih , Sari Maria Mediatrix Ratna 
Published: May 2023

Tax evasion is a phenomenon that occurs in Indonesia. The perception of tax evasion views that the tax money paid is not used properly. The aim of this study is to empirically examine the effect of the self-assessment system, discrimination, and the possibility of detecting fraud on the perception of tax evasion. The research was conducted at KPP Pratama West Denpasar. Purposive sampling technique was used in this study and a sample of 100 individual taxpayers (WPOP) was found. Data analysis in this research used multiple linear regression analysis techniques. The results showed that the self-assessment system and the possibility of detecting fraud had a negative effect on perceptions of tax evasion, while discrimination had a positive effect on perceptions of tax evasion. The implication of this research is to provide support for the theory of planned behavior and attribution theory related to the factors that influence the perception of taxpayers in tax evasion.
Keywords: Self Assessment System; Discrimination; Possibility Of Detecting Fraud; Perceptions In Tax Evasion
Green Banking, Kesehatan Bank dan Profitabilitas dengan Corporate Social Responsibility sebagai Variabel Moderasi
Authors: Kweeswara Corinna Octavia , Irawan Judith Felicia Pattiwael 
Published: May 2023

The 2020 - 2021 pandemic has had an impact on banking activities. The aim of the study was to find out green banking practices carried out by the core capital bank group (KBMI) 3 during the pandemic, including CSR, as well as the health conditions of the banks. The study is based on the theory of Socially Responsible Investment and the concept of bank soundness. The study sample is KBMI 3 banks listed on the IDX. The operational variable is the dependent variable ROA as a measure of profitability. Meanwhile, the independent variables are CAR, BOPO, and NPL as bank health variables, 16 Green Banking indicators and 91 CSR indicators. The data analysis technique uses multiple and simple linear regression methods. The results show that the BOPO variable has a negative effect on bank profitability. Meanwhile, other variables have no effect. Thus, the study results provide findings that during a pandemic, KBMI 3 banks focused on maintaining cost efficiency, one measure of bank health. The research results are in line with the concept of bank soundness. The research contribution is that in the conditions of Covid-19, the KBMI 3 bank supports sustainability but maintains more cost efficiency.
Keywords: Green Banking, Corporate Social Responsibility, Specific Condition, Cost Efficiency.