bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategic Priorities for Employees Deviate from the Widely-employed Pareto’s Law
Authors: de Poll Dr. Jan van , Chen Li
Published: June 2022

During an organizational transformation, improvements must be dosed. Usually, an organization cannot change in lockstep: some teams and employees go faster than others. A more diverse and tailor-made target setting enables managers and employees to sufficiently transform while doing their day job and keeping their sanity. When it comes to where to focus management attention on the topics and employees most behind the target, Pareto's 80-20 rule is the usual answer: Only 20% of X is responsible for 80% of Y. Although Pareto seems a very general approach, some studies in the literature claim that the idea that only 20% of employees matter can be more harmful than beneficial. Moreover, it still doesn't tell where to focus, only that there is an unequal relationship between input and output. In this study, to verify whether Pareto's 80-20 rule applies to organizational transformation, we conducted extensive surveys during 320 different transformation projects covering almost 2,500 teams and more than 100,000 employees. We found that we had to adjust Pareto's 80-20 rule to a "50-20" rule-of-thumb. Approx. 20% of questions and 20% of respondents covered approximately 50% of the improvement target. Additionally, the underlying visualizations developed in this study yielded benefits in transformation planning and knowledge sharing.
Effect of Increase in Community Resources on Poverty Alleviation through Kredit Usaha Rakyat (KUR)
Authors: Armoyu Mohammad , Azizah Nurul
Published: June 2022

The Indonesian government's strategy to overcome poverty is the People's Business Credit (K.U.R.) program. Through qualitative methods, this study examined the empowerment of the poor through K.U.R. at the Branch Office of the Indonesian People's Bank Situbondo East Java. As for the formulation of the problem that will be analyzed, first, How is the People's Business Credit (K.U.R.) program of Bank Rakyat Indonesia Situbondo Branch realizing the empowerment of the poor?; secondly, For Which Bank Rakyat Indonesia Situbondo branch office conducts coaching and assistance to K.U.R. Credit Recipient Customers. This study shows that the People's Business Credit program of Bank Rakyat Indonesia in Situbondo Regency, East Java, can realize the empowerment of the poor. The results showed that the People's Business Credit program of Bank Rakyat Indonesia in Situbondo Regency, East Java, could realize the empowerment of the poor. Therefore, the recommendations offered are the development and assistance of [Bank Rakyat Indonesia (B.R.I.)] Situbondo Regency Government empowers the poor through K.U.R. in situbondo regencies. Furthermore, this paper advises the management of Bank Rakyat Indonesia to improve facility services to realize the empowerment of the poor through K.U.R. And always conduct regular coaching and supervision to customers so that the business is more advanced it can increase human resources
Financial Performance and Prediction of Financial Distress in Food and Beverage Companies Listed on the Indonesia Stock Exchange
Authors: Muttia Elsya Ega , Sutrisno
Published: June 2022

Bankruptcy risk is a risk that is avoided by all companies because it can have an impact on the liquidation of company. This study examines several factors that are thought to affect financial distress. Financial distress is measured by the Z-Score from Altman, while the factors that are thought to influence are liquidity as measured by the current ratio (CR), profitability as measured by net profit margin (NPM), leverage as measured by debt to total assets (DTA), and company growth is measured by sales growth. The population of this research are companies in the food and beverage sector on the Indonesia Stock Exchange as many as 32 companies with a sample of 27 companies using purposive sampling technique. Test the hypothesis using multiple regression analysis with a significance level of 0.05. The results show that liquidity and profitability have a significant effect on financial distress, while leverage and company growth have no effect on financial distress.
Dapagliflozin for Chronic Kidney Disease
Authors: Khangura Sara D. , Severn Melissa
Published: June 2022

Recent, large, high-quality trials have demonstrated some benefits of dapagliflozin for the treatment of chronic kidney disease (most often in patients with Type II diabetes) as compared to placebo.

Data describing the clinical effectiveness of dapagliflozin has identified both relative benefits and no differences compared to placebo in various measures of renal and cardiovascular health and function, as well as health care utilization, mortality and adverse events.

A large proportion of the available data has been generated from the same randomized controlled trial that has recently been reported in multiple publications describing various patient subgroups and outcomes.

No evidence was identified describing the cost-effectiveness of dapagliflozin for the treatment of patients with chronic kidney disease.
New insights on the prevalence of drizzle in marine stratocumulus clouds based on a machine learning algorithm applied to radar Doppler spectra
Authors: Zhu Zeen , Kollias Pavlos , Luke Edward , Yang Fan
Published: June 2022

Abstract. The detection of the early growth of drizzle particles in marine
stratocumulus clouds is important for studying the transition from cloud
water to rainwater. Radar reflectivity is commonly used to detect drizzle;
however, its utility is limited to larger drizzle particles. Alternatively,
radar Doppler spectrum skewness has proven to be a more sensitive quantity
for the detection of drizzle embryos. Here, a machine learning (ML)-based
technique that uses radar reflectivity and skewness for detecting small
drizzle particles is presented. Aircraft in situ measurements are used to
develop and validate the ML algorithm. The drizzle detection algorithm is
applied to three Atmospheric Radiation Measurement (ARM) observational
campaigns to investigate the drizzle occurrence in marine boundary layer
clouds. It is found that drizzle is far more ubiquitous than previously
thought; the traditional radar-reflectivity-based approach significantly
underestimates the drizzle occurrence, especially in thin clouds with liquid water paths lower than 50 g m−2. Furthermore, the
drizzle occurrence in marine boundary layer clouds differs among the three ARM
campaigns, indicating that the drizzle formation, which is controlled by the
microphysical process, is regime dependent. A complete understanding of the
drizzle distribution climatology in marine stratocumulus clouds calls for
more observational campaigns and continuing investigations.
Performance characterization of low-cost air quality sensors for off-grid deployment in rural Malawi
Authors: Bittner Ashley S. , Cross Eben S. , Hagan David H. , Malings Carl , Lipsky Eric , Grieshop Andrew P.
Published: June 2022

Abstract. Low-cost gas and particulate matter sensor packages offer a compact,
lightweight, and easily transportable solution to address global gaps in air
quality (AQ) observations. However, regions that would benefit most from
widespread deployment of low-cost AQ monitors often lack the reference-grade
equipment required to reliably calibrate and validate them. In this study,
we explore approaches to calibrating and validating three integrated sensor
packages before a 1-year deployment to rural Malawi using colocation data
collected at a regulatory site in North Carolina, USA. We compare the
performance of five computational modeling approaches to calibrate the
electrochemical gas sensors: k-nearest neighbors (kNN) hybrid, random forest
(RF) hybrid, high-dimensional model representation (HDMR), multilinear
regression (MLR), and quadratic regression (QR). For the CO, Ox, NO,
and NO2 sensors, we found that kNN hybrid models returned the highest
coefficients of determination and lowest error metrics when validated.
Hybrid models were also the most transferable approach when applied to
deployment data collected in Malawi. We compared kNN hybrid calibrated CO
observations from two regions in Malawi to remote sensing data and found
qualitative agreement in spatial and annual trends. However, ARISense
monthly mean surface observations were 2 to 4 times higher than the remote
sensing data, partly due to proximity to residential biomass combustion activity
not resolved by satellite imaging. We also compared the performance of the
integrated Alphasense OPC-N2 optical particle counter to a filter-corrected
nephelometer using colocation data collected at one of our deployment sites
in Malawi. We found the performance of the OPC-N2 varied widely with
environmental conditions, with the worst performance associated with high
relative humidity (RH >70 %) conditions and influence from
emissions from nearby residential biomass combustion. We did not find
obvious evidence of systematic sensor performance decay after the 1-year
deployment to Malawi. Data recovery (30 %–80 %) varied by sensor and season
and was limited by insufficient power and access to resources at the remote
deployment sites. Future low-cost sensor deployments to rural, low-income settings would benefit from adaptable power systems, standardized sensor
calibration methodologies, and increased regional regulatory-grade
monitoring infrastructure.
A novel method for objective identification of 3-D potential vorticity anomalies
Authors: Fischer Christoph , Fink Andreas H. , Schömer Elmar , van der Linden Roderick , Maier-Gerber Michael , Rautenhaus Marc , Riemer Michael
Published: June 2022

Abstract. Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics and in particular in studying the life cycle of weather
systems. The three-dimensional (3-D) structure and temporal evolution of the associated PV features, however, are not yet fully understood. An
automated technique to objectively identify 3-D PV features can help to shed light on 3-D atmospheric dynamics in specific case studies as well as
facilitate statistical evaluations within climatological studies. Such a technique to identify PV features fully in 3-D, however, does not yet
exist. This study presents a novel algorithm for the objective identification of PV anomalies along the dynamical tropopause in gridded data, as
commonly output by numerical simulation models. The algorithm is inspired by morphological image processing techniques and can be applied to both
two-dimensional (2-D) and 3-D fields on vertically isentropic levels. The method maps input data to a horizontally stereographic projection and
relies on an efficient computation of horizontal distances within the projected field. Candidates for PV anomaly features are filtered according to
heuristic criteria, and feature description vectors are obtained for further analysis. The generated feature descriptions are well suited for
subsequent case studies of 3-D atmospheric dynamics as represented by the underlying numerical simulation. We evaluate our approach by comparison
with an existing 2-D technique and demonstrate the full 3-D perspective by means of a case study of an extreme precipitation event that was
dynamically linked to a prominent subtropical PV anomaly. The case study demonstrates variations in the 3-D structure of the detected PV anomalies
that would not have been captured by a 2-D method. We discuss further advantages of using a 3-D approach, including elimination of temporal
inconsistencies in the detected features due to 3-D structural variation and elimination of the need to manually select a specific isentropic level
on which the anomalies are assumed to be best captured. These advantages, as well as the suitability of the implementation to process big data sets,
also open applications for climatological analyses. The method is made available as open-source for straightforward use by the atmospheric
community.
Droughts in Germany: Performance of Regional Climate Models in Reproducing Observed Characteristics
Authors: Petrovic Dragan , Fersch Benjamin , Kunstmann Harald
Published: June 2022

Abstract. Droughts are among the most relevant natural disasters related to climate change. We evaluated different regional climate model outputs and their ability to reproduce observed drought indices in Germany and the near surroundings between 1980–2009. Both, outputs of an ensemble of six EURO-CORDEX models of 12.5 km grid resolution and outputs from a high resolution (5 km) WRF run were employed. The latter was especially tailored for the study region regarding the physics configuration. We investigated drought related variables and derived the 3 month Standardized Precipitation Evapotranspiration Index (SPEI-3) to account for meteorological droughts. Based on that, we analyzed correlations, the 2003 event, trends and drought characteristics (frequency, duration and severity) and compared the results to E-OBS. Methods used imply Taylor diagrams, the Mann-Kendall trend test and the Spatial Efficiency (SPAEF) metric to account for spatial agreement of patterns. Averaged over the domain, meteorological droughts were found to occur approx. 16 times in the study period with an average duration of 3.1 months and average severity of 1.47 SPEI units. WRF’s resolution and setup was shown to be less important for the reproduction of the single drought event and overall drought characteristics. Depending on the specific goals of drought analyses, computation resources could therefore be saved, since a coarser resolution can provide similar results. Benefits of WRF were found in the correlation analysis. Greatest benefits were identified in the trend analysis: Only WRF was able to reproduce the observed negative SPEI trends in a fairly high spatial accuracy, while the other RCMs completely failed in this regard. This was mainly due to the WRF model settings, highlighting the importance of appropriate model configuration tailored to the target region. Our findings are especially relevant in the context of climate change studies, where the appropriate reproduction of trends is of high importance.
Hidden-state modeling of a cross-section of geoelectric time series data can provide reliable intermediate-term probabilistic earthquake forecasting in Taiwan
Authors: Wen Haoyu , Chen Hong-Jia , Chen Chien-Chih , Ciamarra Massimo Pica , Cheong Siew Ann
Published: June 2022

Abstract. Geoelectric time series (TS) have long been studied for their
potential for probabilistic earthquake forecasting, and a recent model
(GEMSTIP) directly used the skewness and kurtosis of geoelectric TS to
provide times of increased probability (TIPs) for earthquakes for several
months in the future. We followed up on this work by applying the hidden Markov
model (HMM) to the correlation, variance, skewness, and kurtosis TSs to
identify two hidden states (HSs) with different distributions of these
statistical indexes. More importantly, we tested whether these HSs could
separate time periods into times of higher/lower earthquake probabilities.
Using 0.5 Hz geoelectric TS data from 20 stations across Taiwan over 7 years, we first computed the statistical index TSs and then applied the
Baum–Welch algorithm with multiple random initializations to obtain a
well-converged HMM and its HS TS for each station. We then divided the map
of Taiwan into a 16-by-16 grid map and quantified the forecasting skill,
i.e., how well the HS TS could separate times of higher/lower earthquake
probabilities in each cell in terms of a discrimination power measure that we defined. Next, we
compare the discrimination power of empirical HS TSs against those of 400 simulated HS TSs and then
organized the statistical significance values from this cellular-level
hypothesis testing of the forecasting skill obtained into grid maps of
discrimination reliability. Having found such significance values to be high for many grid cells for
all stations, we proceeded with a statistical hypothesis test of the
forecasting skill at the global level to find high statistical significance
across large parts of the hyperparameter spaces of most stations. We
therefore concluded that geoelectric TSs indeed contain earthquake-related
information and the HMM approach is capable of extracting this
information for earthquake forecasting.
Data-assimilation-based parameter estimation of bathymetry and bottom friction coefficient to improve coastal accuracy in a global tide model
Authors: Wang Xiaohui , Verlaan Martin , Veenstra Jelmer , Lin Hai Xiang
Published: June 2022

Abstract. Global tide and surge models play a major role in forecasting coastal flooding due to extreme events or climate change. The model performance is strongly affected by parameters such as bathymetry and bottom friction. In this study, we propose a method that estimates bathymetry globally and the bottom friction coefficient in shallow waters for a global tide and surge model (GTSMv4.1). However, the estimation effect is limited by the scarcity of available tide gauges. We propose complementing sparse tide gauges with tide time series generated using FES2014. The FES2014 dataset outperforms the GTSM in most areas and is used as observations for the deep ocean and some coastal areas, such as Hudson Bay and Labrador, where tide gauges are scarce but energy dissipation is large. The experiment is performed with a computation- and memory-efficient iterative parameter estimation scheme (time–POD-based coarse incremental parameter estimation; POD: proper orthogonal decomposition) applied to the Global Tide and Surge Model (GTSMv4.1). Estimation results show that model performance is significantly improved for the deep ocean and shallow waters, especially in the European shelf, directly using the CMEMS tide gauge data in the estimation. The GTSM is also validated by comparing to tide gauges from UHSLC, CMEMS, and some Arctic stations in the year 2014.
Potential of X-band polarimetric synthetic aperture radar co-polar phase difference for arctic snow depth estimation
Authors: Voglimacci-Stephanopoli Joëlle , Wendleder Anna , Lantuit Hugues , Langlois Alexandre , Stettner Samuel , Schmitt Andreas , Dedieu Jean-Pierre , Roth Achim , Royer Alain
Published: June 2022

Abstract. Changes in snowpack associated with climatic warming has drastic
impacts on surface energy balance in the cryosphere. Yet, traditional
monitoring techniques, such as punctual measurements in the field, do not
cover the full snowpack spatial and temporal variability, which hampers
efforts to upscale measurements to the global scale. This variability is one
of the primary constraints in model development. In terms of spatial
resolution, active microwaves (synthetic aperture radar – SAR) can address
the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better
parameterization of local processes that drive the spatial variability of
snow. The overall objective of this study is to evaluate the potential of
the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD)
method for characterizing snow cover at high spatial resolution.
Consequently, we first (1) investigate SD and depth hoar fraction (DHF)
variability between different vegetation classes in the Ice Creek catchment
(Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements
collected over the course of a field campaign in 2019; (2) evaluate linkages
between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015–2019
period. SD could be extracted using the CPD when certain
conditions are met. A high incidence angle (>30∘)
with a high topographic wetness index (TWI) (>7.0) showed
correlation between SD and CPD (R2 up to 0.72). Further, future work
should address a threshold of sensitivity to TWI and incidence angle to map
snow depth in such environments and assess the potential of using
interpolation tools to fill in gaps in SD information on drier vegetation
types.
Implementasi Wireless Sensor Network untuk Komunikasi Antar PLC
Authors: Khamid Imam Abdul , Yulianto Azhari , Wiwit Kurniaga Mundi
Published: June 2022

Wireless Sensor Network (WSN) merupakan sebuah perangkat jaringan nirkabel yang digunakan untuk memonitoring secara kolektif tentang data yang ditangkap maupun disebarkan pada kondisi lingkungan sekitar, seperti suhu, getaran, tekanan, gelombang elektromagnetik, dan lain-lain. Penggunaan Wireless Sensor Network (WSN) saat ini telah menjadi sebuah pembahasan yang menarik karena pengaplikasiannya yang bervariasi seperti untuk komunikasi, monitoring, tracking, dan controlling. Salah satu aplikasi spesifik dari Wireless Sensor Network adalah komunikasi antar PLC. Dalam merancang dan mengimplementasikan hardware, seluruh referensi dari datasheet dari tiap-tiap komponen sangat dibutuhkan. Komponen yang digunakan berupa modul ZIG 100, mikrokontroler ATMega 128, dan beberapa komponen pendukung lainnya
Automatic Gas Control System In The Motorcycle Braking Process With The Concept Of Non-Uniform Slowing Down Motion
Authors: Anang Suryana  , Himawan Kusumah Ilman , De Wibowo Aryo , Edwinanto  , Artiyasa Marina , Pradiftha Junfithrana Anggy , Imamulhak Yufriana , Putra Yudha
Published: June 2022

When motorcyclists have an accident, they are at high risk of suffering severe or fatal injuries. The difficulty experienced by motorcyclists and considered one of the most complicated to do in an emergency is braking because motorcycle accidents are often caused by loss of control or stability when braking as evasive action. In the braking process, a motorcycle must pay attention to distance and speed so that the deceleration during braking is by the kinematic concept to avoid the shock force during braking, in this study uses research and development methods in making automatic braking systems on motorbikes. The actuator system controls the brake pedal, and the gas pedal uses a stepper motor. The two stepper motors will move automatically if the motorbike detects an object in front of it at less than 4 meters. The angle of the stepper motor that drives the brake lever is in a span between 0 degrees to 30 degrees, while the tip of motion of the stepper motor that moves the gas pedal is in a span of 0 degrees to 70 degrees. The angle movement of the stepper motor is influenced by the distance detected by the HC-SR04 type proximity sensor and the motorbike speed detected by the KY-003 type speed sensor, which works by utilizing the hall effect principle. The results of the tests that have been carried out show that the automatic braking system created can work well with an indicator that there is no shock force during the automatic braking process
Pengenalan Gerakan Tangan Menggunakan Fuzzy-Logic dengan Algoritma Jaringan Syaraf Tiruan Backpropagation
Authors: Awaludin M Irsyad
Published: June 2022

Makalah ini menyajikan metode pengenalan urutan gerakan tangan melalui kriteria multi-fitur berdasarkan area yang telah ditentukan dalam ruang dua dimensi, keberadaan warna kulit, dan non-gerakan untuk jangka waktu tertentu menggunakan kamera web. Pengenalan gerakan tangan adalah topik aktif penelitian dan pengembangan untuk antarmuka manusia-komputer. Gerakan tangan secara alami terdiri dari gerakan dan gerakan berhenti. Teknik ini berfokus pada fitur non-gerak dari gerakan tangan. Mudah bagi manusia untuk mengenali arti dari gerakan tangan yang umum, tetapi sulit bagi komputer untuk menyelesaikan tugas yang sama. Sebuah metode sistematis dikembangkan untuk membedakan gerakan berhenti dari gerakan tangan sehingga teknik pengenalan pola dapat digunakan secara efektif untuk menginterpretasikan gerakan tersebut. Kami telah membandingkan hasil pengenalan gerakan menggunakan dua algoritma - algoritma feedforward backpropagation dan algoritma neuro-fuzzy
Pengenalan Ekspresi Wajah Menggunakan Teknik Filter Wavelet Gabor
Authors: Sidik Aryo De Wibowo Muhammad , Suryana Anang , Edwinanto  , Artiyasa Marina , Pradiftha Junfithrana Anggy , Himawan Kusumah Ilman , Imamulhak Yufriana
Published: June 2022

Pengenalan Emosi Wajah telah lama menjadi topik hangat dalam penelitian identifikasi pola komputer, dan saat ini tidak ada metode pengenalan ekspresi wajah yang memiliki tingkat pengenalan 100%. Jadi, meningkatkan tingkat pengenalan memerlukan pra-pemrosesan set data yang lebih baik, meningkatkan pendekatan ekstraksi fitur, dan memanfaatkan pengklasifikasi terbaik untuk pengenalan wajah. Penelitian ini bertujuan untuk meningkatkan pendekatan ekstraksi ciri untuk meningkatkan tingkat pengenalan sistem pengenalan ekspresi wajah. Fase penting dalam pengenalan gerakan wajah adalah ekstraksi fitur, yang menentukan tingkat pengenalan. Fitur harus diekstraksi dengan cara atau proyeksi yang berbeda untuk meningkatkan tingkat pengenalan, tetapi ada risiko mengembangkan redundansi, yang akan menurunkan tingkat pengenalan. Sementara Gabor memiliki varian fitur yang maksimal, ia memiliki kesulitan dengan dimensi dan redundansi yang tinggi. Beberapa strategi harus digunakan untuk mengurangi ukuran dan redundansi. Filtering adalah teknik pengurangan dimensi yang digunakan oleh Gabor. Oleh karena itu seluruh proses dikenal sebagai filter Gabor. Pengambilan sampel, pemfilteran rata-rata, dan teknik pemfilteran lainnya adalah contohnya. Fitur-fitur Gabor difilter menggunakan transformasi wavelet dan mendapatkan komponen optimal dari dataset wajah dalam teknik ekstraksi fitur Gabor yang diusulkan, memberikan tingkat pengenalan yang lebih tinggi daripada teknik ekstraksi fitur Gabor rata-rata dan teknik ekstraksi fitur penyaringan Gabor sampling pengenalan ekspresi wajah.
Pengenalan Wajah Berbasis Template menggunakan Gambar Asli
Authors: Rizal Muhamad
Published: June 2022

Algoritma pengenalan wajah berdasarkan pendekatan pemerataan histogram diusulkan dalam penelitian ini. Pengenalan wajah menggunakan pemerataan Histogram dan eigenfaces memberikan hasil yang lebih unggul daripada teknik lama, seperti LDA dan PCA, dengan menormalkan iluminasi wajah dan menghilangkan perbedaan untuk ekstraksi fitur yang berbeda. Prosedur ini menghasilkan hasil yang lebih akurat dan dapat diandalkan. Setelah penelitian, ROC dan hasilnya dikontraskan. Algoritma diuji dan diverifikasi pada database ORL dan foto-foto yang dikumpulkan di luar database. Ini adalah pertama kalinya strategi ini digunakan, dan menghasilkan hasil yang lebih cocok bahkan ketika gambar diperoleh di luar database (ORL)
Teknik Data Mining untuk Prediksi Kanker Payudara yang Efisien
Authors: Solikin Irfan
Published: June 2022

Salah satu keganasan paling umum pada wanita, kanker payudara, juga merupakan salah satu penyebab utama kematian. Menurut Organisasi Kesehatan Dunia, kanker payudara sekarang menjadi keganasan paling umum di antara wanita di seluruh dunia. Untuk menyelamatkan nyawa, identifikasi dini kanker payudara sangat penting. Akurasi klasifikasi dari database Wisconsin Breast Cancer (WBC) digunakan untuk membandingkan berbagai pengklasifikasi Data Mining dalam penelitian ini. Bertujuan untuk akurasi prediksi yang tinggi, pekerjaan ini bermaksud untuk mengembangkan model klasifikasi akurat untuk prediksi kanker payudara yang sepenuhnya menggunakan informasi berharga yang ditemukan dalam data klinis. Berdasarkan data WBC, kami telah menjalankan uji coba. Ini dibagi menjadi dua set: set latihan 499 pasien dan set tes dunia nyata 200. Menggunakan perangkat lunak Weka, eksperimen ini menganalisis enam strategi kategorisasi dan menemukan bahwa Support Vector Machine (SVM) lebih akurat dalam memprediksi masa depan daripada teknik lain yang diuji. Keakuratan beberapa teknologi deteksi kanker payudara sedang diselidiki dan dibandingkan. SVM lebih cocok untuk menangani kesulitan klasifikasi seperti prediksi kanker payudara. Jadi kami menyarankan untuk menerapkan temuan ini pada masalah klasifikasi lainnya juga
Fluid Volume Detector on a Horizontal Tube Using an Ultrasonic-based Water Level Sensor
Authors: Suryana Anang , Paikun  , Ali Setyo Yudono Muchtar
Published: June 2022

Measurement of the volume of liquid in a vertical cylinder can be done by multiplying the area of ​​the circle with the length of the cylinder. Likewise, measuring the volume of liquid in a horizontal pipe can also be done by multiplying the area by the length of the cylinder. There is a difference between the two measurements of the volume of liquid in the cylinder. In a horizontal cylinder, the measurement of area used is a measurement of the segment of the circle that is exposed to the liquid. To get the value of the circle area segment that is with geometric analysis. In this study, in measuring the volume of liquid in a horizontal cylinder using the multiplication between the circle area segment and the horizontal pipe length. The variables used in measuring the volume of liquid in a horizontal cylinder are, cylinder diameter 2r, liquid level H, and cylinder length L. So that in making this measuring instrument the volume of liquid in a horizontal cylinder has two variables, namely fixed and variable variables. free. For the fixed variables, namely the diameter and length of the cylinder, and for the independent variables, namely the level of the liquid level in the H pipe. In measuring the independent variables, a proximity sensor Type HC-SR04 is used. Installation of a volume measuring device on a horizontal cylinder using a PVC pipe connection type equal tee which is connected to other pipes with the same diameter with a predetermined total length. The fixed variable that has been determined is the cylinder diameter of 10.16 cm with a length of 100 cm.
Bitcoin USD Closing Price (BTC-USD) Comparison Using Simple Moving Average And Radial Basis Function Neural Network Methods
Authors: Yudono Muchtar Ali Setyo , Sidik Aryo De Wibowo Muhammad , Kusumah Ilman Himawan , Suryana Anang , Junfithrana Anggy Pradiftha , Nugraha Adi , Artiyasa Marina , Edwinanto Edwinanto , Imamulhak Yufriana
Published: June 2022

Bitcoin is a decentralized electronic money that is not controlled nor insured by a central authority. Because it is still a young system, the price of Bitcoin is extremely unpredictable, making Bitcoin users and investors uneasy. A typical difficulty for investors and traders is predicting the future movement of the value of Bitcoin electronic money based on historical data. Because investors and traders only notice swings in global currency prices and make Bitcoin buy/sell decisions instinctively, they frequently make the erroneous buy/sell decisions. Many investors and traders suffered significant losses as a result of this error. Losses can be reduced by employing an algorithm that predicts the movement of the value of Bitcoin electronic money. Using a comparison of two methodologies, the Simple Moving Average and RBFNN, we will anticipate the closing price of Bitcoin USD (BTC-USD) from January 1, 2021 to January 31, 2021. The results obtained using the simple moving average method MSE = 0.01 percent and MAPE = 36.67 percent, and the results obtained using the RBFNN method MSE = 9.97 x 10-7 and MAPE = 9.97 x 10-5, indicating that the RBFNN method with an accuracy rate of 99.9995 percent is better than the simple moving average method in forecasting the closing price of bitcoin.
Kriptanalisis DES menggunakan Jaringan Syaraf Tiruan
Authors: Kurniaga Mundi Wiwit , Yulianto Azhari , Setya Aji Kumoro Tri
Published: June 2022

Selama dua dekade sebelumnya, Kriptanalisis block ciphers telah mengalami banyak perubahan, dengan banyak teknik Kriptanalisis baru yang diperkenalkan. Di sisi lain, karena aplikasinya tersebar di beberapa bidang, Jaringan Syaraf Tiruan telah menunjukkan keandalan dan penerapan yang tinggi. Selain itu, metode efektif untuk mengimplementasikan perangkat keras dan perangkat lunaknya dibuat lebih cepat dan lebih mudah. Algoritma genetik untuk meningkatkan jaringan saraf telah terbukti menjadi cara yang menjanjikan untuk menghasilkan lebih baik dan lebih mudah untuk melatih jaringan saraf. Makalah ini memperkenalkan teknik Kriptanalisis baru berdasarkan jaringan saraf yang dihasilkan menggunakan algoritma genetika. Jenis kriptanalisis ini disebut sebagai serangan teks biasa yang diketahui. Metode yang diusulkan dimasukkan ke dalam perangkat lunak dan diuji terhadap Data Encryption Standard (DES). DES adalah block cipher yang canggih dengan ukuran blok 64-bit. Dalam hal waktu, kemampuan pemrosesan, dan jumlah pasangan ciphertext-plaintext yang diperlukan untuk Kriptanalisis, implementasi perangkat lunak sistem yang disarankan telah menunjukkan keuntungan yang signifikan dibandingkan sistem Kriptanalisis yang ada. Kemampuan pembelajaran jaringan syaraf tiruan dan aplikasinya dalam kriptanalisis menjadi pokok bahasan penelitian ini
Yabancı Dil Olarak Türkçe Temel Dil Becerilerinin Öğretiminde Öğrenci Motivasyonun Sağlanmasında Kullanılan Yöntemler
Authors: KARİMOV Samir , ARSLAN Mustafa
Published: June 2022

In this study, the methods used to provide student motivation in the development of four basic language skills in teaching Turkish as a foreign language were examined. In the research, a short scientific explanation about motivation was given and it was associated with the subject. The importance of using various motivational methods in Turkish education for foreign students and its effect on the teaching process are highlighted. In the study, different sources and data related to the subject were used. The purpose and methods of using motivation were questioned from the perspective of students and teachers. In the study, different ideas about the differences between intrinsic and extrinsic motivation and which one is more efficient in the educational process were carried out. Case study, one of the qualitative patterns, was used in the research. Data were collected through document review and evaluated with content analysis. According to the findings, if internal and external motivation is used correctly and appropriately, it is understood that what is taught is used more quickly and for a long time by students. According to the results of the research, the contribution of motivation to foreign language education, the use of different types of motivation in second language teaching and which one is more efficient are scientifically explained. In addition, the importance of using different motivation methods in foreign language lessons and making new knowledge permanent thanks to it was emphasized. Keywords: Foreign language, Turkish teaching, student motivation, methods
Development and evaluation of pneumatic trap cum electric swatter for the control of whitefly in cotton crop
Authors: . Gagandeep
Published: June 2022

The insecticides that are used to protect the crop from insects and pests not only pose a financial burden on the farmer but also affect human health and the environment. In this study, a prototype is developed and evaluated in the cotton crop to see the effect of various speeds and different locations of airstream in respect of the plant to control the population of adult whitefly. The percentage reduction in the population of the whitefly was found to be increased from 38% to 42% with the increase in the blower speed from 1800 to 4050 rpm. The field efficiency was found to be decreased from 87.90% to 74.92% with an increase in the forward speed from 1.74 to 4.19 km.h-1. The damage to the crop in the form of damage to branches and damage of flowers/bolls was found to be increased from 4.44% to 5.30% and 1.04% to 2.02% respectively, with the increase in the blower speed from 1800 to 4050 rpm.
Post-harvest management – a strategy for climate resilient agriculture
Authors: Dhingra Devinder
Published: June 2022

Agriculture, animal husbandry and fisheries depend largely on the climate of the region. Global warming, changes in rain patterns, droughts, floods, cyclones, storms, etc., have become a challenge for the food production systems. Various strategies being explored to counter negative impact of climate change on agriculture and allied activities. Promising crop genotypes and livestock breeds tolerant to climatic stress are looked into through strategic research. Also it is important to develop infrastructure and train the manpower to reduce post-harvest losses. Post-harvest losses among selected fruits and vegetables were observed to be in the range of 6.70 - 15.88% during the year 2014. Post-harvest losses among cereals, pulses and oilseeds were also observed to be in the range of 3.08 – 9.96%. Post-harvest management of agricultural produce and setting-up of custom hiring centres in rural areas have the potential to reduce post-harvest losses, create rural employment opportunities, enhance farmers income and counter the negative impact of climate change. This paper describes the post-harvest losses of selected commodities along the value chain in India and the strategies to reduce post-harvest losses.
Application uniformity assessment of deep fertilizer placement machine for urea briquettes
Authors: Choudhary Swapnil
Published: June 2022

Deep placement of fertilizer has not only a positive agronomic and socioeconomic impact, but also an environmental benefit. A Deep Fertilizer Placement Machine was evaluated for uniformity of fertilizer application at different level of urea briquette in fertilizer box. Various physical and engineering properties of urea briquette viz. size, shape, bulk density, briquette weight, angle of repose and coefficient of friction were measured for design and selection of machine components. The calibration of machine was done at three peripheral speed of ground wheel (3.5, 4.5 and 5.5 km h-1) and four different level of fill (full, 3/4th, half and 1/4th) of fertilizer box. The performance of machine was best at 4.5 km h-1 peripheral speed of ground wheel and fertilizer box filled up to 3/4th level. The field evaluation data revel that approximately 51 number of urea briquette per row were dropped in 15 m distance with average spacing of 301.4 mm with standard deviation of 90 mm among the spacing of dropped urea briquette. The observed miss index, multiple index, quality feed index and precision index of machine was 0.06, 0.06, 0.89 and 0.11 respectively. The effective field capacity of machine was 0.71 ha h-1 with average working width of 1.94 m. The fertilizer application rate, average draft requirement, field efficiency and fuel consumption during field evaluation of machine was observed as 186 kg ha-1, 656 kg, 80.75 % and 2.9 l h-1 respectively.
SPORTS PROFILE OF ELITE ATHLETES IN RHYTHMIC GYMNASTICS
Authors: Ivanova Ivanova Vesela
Published: June 2022

Elite athletes are competitors who combine in themselves exceptional talent, many years of hard work and distinctive psychological qualities. Highly qualified rhythmic gymnasts do not differ from this definition, as their sports profile includes all these characteristics. The aim of this study is to develop a methodology to create the sports profile of elite competitors in rhythmic gymnastics on the basis of current competitors from the USA, Singapore and Taiwan and to compare the obtained results. This could help us assess the current habits of these gymnasts, the positive or negative impact of those habits on their performance, and the necessary changes that need to be made to optimize the training process. The results of the current study and the statistical data processing from the conducted experiment showed that the three studied teams of elite athletes (total of 63 gymnasts) demonstrated strong commitment and engagement in the training process. Generally, the Singaporean and Taiwanese athletes had difficulties in communication with their coach and lagged behind in the development of technical qualities and mental skills for effective adaptation compared to their colleagues from the United States. At the same time, however, they showed a higher degree of self-awareness for improvement. On the other hand, the athletes from the US demonstrated shortcomings in Consistency in training. The numerical values also showed that some of the US athletes demonstrated limitations in the development of physical qualities which could affect their professional sports development in the future.
DUKUNGAN PEKERJA SOSIAL PADA MASYARAKAT SELAMA MASA PANDEMI COVID-19
Authors: Sholikah Ratna Junyekawati
Published: June 2022

Munculnya pandemi covid-19 menjadi fokus pembahasan terutama dengan hal-hal yang berkaitan dengan permasalahan sosial yang ditimbulkan. Kerentanan dan ketimpangan sosial yang ditimbulkan dalam situasi pandemi covid-19 ini memerlukan dukungan baik dalam individu, kelompok, maupun lingkup masyarakat. Hal tersebut juga untuk mengembalikan keberfungsian sosial yang dalam hal ini merupakan profesi pertolongan yang dilakukan oleh pekerja sosial. Tulisan ini mendeskripsikan terkait dengan dukungan yang dilakukan pekerja sosial dalam situasi pandemi covid-19 terhadap individu, kelompok, maupun masyarakat, baik yang mengalami kerentanan ataupun yang terdampak dalam situasi pandemi ini. Metode yang digunakan dalam penyusunan tulisan ini menggunakan studi literatur yang berkaitan.Kata Kunci : Pandemi Covid-19, dukungan, pekerja sosial
Epidemiological profile of patients with malignant Brain tumors in Rio Grande do Sul state - Brazil
Authors: De Moraes Rêgo Soares Pedro , Pastorello Julia , Lando Emanuela , Rottenfusser Robson , Mesquita Filho Paulo Moacir
Published: June 2022

To determine the epidemiological profile of patients diagnosed with primary malignant brain tumors in the state of Rio Grande do Sul/RS, Brazil, from 2013 to 2019. This is a descriptive, retrospective study with a quantitative approach, carried out through analysis of secondary data collected at the Information Technology Department of the Unified Health System (DATASUS). One thousand five hundred and fifty-eight cases of malignant primary brain tumor were diagnosed. The highest prevalence of cases occurred among men (55.78%) and among individuals aged 40 to 59 years (28.34%). The macro-region with the highest incidence was the Metropolitan (45.64%). An expansion of the database is necessary, mainly in some pathological characteristics such as location of the neoplasm, histological type and morbidity and mortality and patient characteristics such as race to better predict risk factors, prevention and diagnosis.
The effect of Positions on selected Physiological parameters among Term Neonates in a selected Hospital, Kerala
Authors: K D Betty
Published: June 2022

Simple intervention like appropriate positioning of neonate is vital since it affects many physiological parameters and reduces neonatal morbidity. This study was conducted to assess the effect of positions on selected physiological parameters among term neonates in a selected hospital, Kerala. The objectives were (1) To assess the effect of supine position on selected physiological parameters among term neonates. (2) To assess the effect of lateral position on selected physiological parameters among term neonates. (3) To assess the effect of prone position on selected physiological parameters among term neonates. (4) To compare the effects of supine, lateral and prone positions on physiological parameters among term neonates. (5) To associate the effect of positions on physiological parameters among term neonates with selected variables. One group pre-test post- test design was used to collect data from a total of forty subjects, by purposive sampling method. Baseline proforma and observation chart were used to collect the data. The heart rate, respiratory rate and oxygen saturation were recorded at 5th, 15th and 30th minutes in supine, lateral and prone positions. The data was analyzed by descriptive and inferential statistics. Comparison of effect of positions revealed that the mean heart rate and mean oxygen saturation showed the highest values in supine position. Highest mean respiratory rate was same in supine and prone position. With neonatal age in days and gestational age in weeks oxygen saturation showed a positive correlation. The Fisher test revealed that there was statistical difference at 5% significant level only in heart rate and respiratory rate in supine and prone position.
A Study to assess the impact of online education during COVID-19 Pandemic on mental health among college students of selected nursing college at Kottayam district
Authors: S Thomas Amala , Das Anakha , Alexander Anet , K R Arathy , Shaji Asha , Biju Bismi , Mathew Lida , Simon Linu , Tomy Marrena , Sabu Neha , Jose Anajo , Paul Anu , SVM Sr. Joseena
Published: June 2022

COVID-19 has rapidly spread worldwide and it was officially declared as a pandemic by WHO on March 11, 2020. A descriptive study was conducted to assess the impact of online education during COVID-19 pandemic on mental health among college students of selected college at Kottayam district. Simple random sampling technique was used to select 40 samples from the population. The instrument used for the study was rating scale regarding the impact of online education on mental health. The structured tool was divided into 2 sections. The major findings of the study were among the total 40 samples, 20 samples (50%) were having severe negative impact, 13 samples (32.5%) were having moderate negative impact, 5 samples (12.5%) were having mild negative impact and 2 samples (5%) were having critical negative impact. It is found that there is significant impact on online education during COVID-19 pandemic on mental health among college students.
Prevalence and its associated factors of extracranial carotid stenosis in patients with transient ischemic or ischemic stroke in Bach Mai Hospital
Authors: Tung Bui Nguyen , Ton Mai Duy , Hung Pham Manh
Published: June 2022

Incidence of transient ischemic attack (TIA) or ischemic stroke has increased in recent years in Viet Nam due to lifestyle changes. Carotid stenosis is a common cause of TIA/ischemic stroke. The purpose of this study was to estimate current prevalence and identify risk factors of ipsilateral internal carotid artery (ICA) stenosis in patients with TIA/ischemic stroke. We recruited patients hospitalized to Bach Mai hospital in the first half of 2021 who suffered from TIA/ischemic stroke. The primary outcome is the presence of significant carotid stenosis, defined as atherosclerotic narrowing of 50 percent or greater, and confirmed by multidisciplinary team (MDT) discussion. In total, 328 consecutive patients with TIA/ischemic stroke were included in this study. Of these, 29 (8.84%, 95% confidence interval (CI): 6.0 -12.45) have 50-99% ipsilateral ICA stenosis. Patients with considerable ICA stenosis are more likely to have type 2 diabetes, ischemic heart disease (IHD) and higher creatinine serum level. On multivariate logistic regression, type 2 diabetes (OR 2.61; CI 95%: 1.14 -5.97, p = 0,034), IHD (OR 5.27; CI 95%: 1.68 - 16.56, p < 0.001), creatinine level (OR 1.15/10 mmol/l ; CI 95%: 1.01 -1.3, p = 0.031) are statistically significant risk factors for 50-99% ICA stenosis. The prevalence of extracranial ICA stenosis in TIA/ischemic stroke patient in Viet Nam is lower than Western countries but quite similar to Asia regions. Diabetes mellitus, IHD and high creatinine level are important risk factors for symptomatic ICA stenosis.
ORGANIZATION PRINCIPLES AND APPROACHES ANALYSIS TO IMPROVING THE PERSON RE-IDENTIFICATION ACCURACY IN DISTRIBUTED VIDEO SURVEILLANCE SYSTEMS
Authors: IHNATSYEVA S.
Published: June 2022

The paper presents a classification of existing re-identification systems according to such criteria as system type, requests number and type, and operating time. The general scheme is discussed, which reflects the basic operation principle of re-identification systems, and the main approaches and methods for solving this problem using convolutional neural networks are considered. The study ways existing to improve re-identification algorithms and systems accuracy has been carried out. The influence analysis hyperparameters choice in convolutional neural networks training on the efficiency and dynamics re-identification algorithm training is carried out.