Relevant bibliographies by topics / RLS-90 MODEL

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Academic literature on the topic 'RLS-90 MODEL'

Author: Grafiati
Published: 11 September 2023
Last updated: 19 July 2025

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Journal articles on the topic "RLS-90 MODEL"

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Nurmutiazifah, A., and Aisyah Fitri Yuniasih. "PENERAPAN MODEL REGRESI DATA PANEL : DETERMINAN KETIMPANGAN CAPAIAN PENDIDIKAN DI KAWASAN TIMUR INDONESIA (KTI) 2015-2019." Seminar Nasional Official Statistics 2020, no. 1 (2021): 1294–304. http://dx.doi.org/10.34123/semnasoffstat.v2020i1.705.

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Pendidikan menjadi faktor penting dalam pembentukan modal manusia. Pendidikan yang berkualitas dan merata akan meningkatkan modal manusia, memperluas kesempatan kerja dan meningkatkan kesejahteraan masyarakat. Salah satu indikator yang dapat digunakan untuk menilai kualitas pendidikan yakni rata-rata lama sekolah (RLS). Indonesia dalam Human Development Report 2019 berada di peringkat terendah di antara negara anggota ASEAN 5 untuk RLS. Jika dikaji lebih lanjut berdasarkan kawasan maka KTI memiliki RLS yang lebih rendah dari RLS KBI dan RLS nasional. Jika masalah kualitas pendidikan dan tidak meratanya pendidikan di Indonesia khususnya di KTI tidak segera diatasi, maka 90 persen masyarakat miskin yang bertempat tinggal di Indonesia (bersama Filipina) khususnya di KTI akan terus terjerat dalam lingkaran kemiskinan karena tidak mampu meningkatkan kesejahteraan hidupnya.Metode yang digunakan dalam penelitian ini adalah analisis regresi panel untuk menjelaskan determinan ketimpangan capaian pendidikan di KTI. Jenis data yang digunakan berupa data panel dengan cross-section sebanyak 17 provinsi dari tahun 2015-2019. Berdasarkan hasil regresi dengan metode estimasi FGLS/SUR diperoleh bahwa investasi, distribusi guru dan akses pendidikan berpengaruh negatif signifikan, sedangkan remaja menikah muda dan ketimpangan distribusi pendapatan berpengaruh positif signifikan terhadap ketimpangan capaian pendidikan.
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Deng, Huan, Zhenhau Lu, Binrui Wang, and Yisheng Pan. "Abstract 4524: The independent prognostic nomogram models for primary and recurrent retroperitoneal liposarcoma: A population-based cohort study." Cancer Research 85, no. 8_Supplement_1 (2025): 4524. https://doi.org/10.1158/1538-7445.am2025-4524.

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Abstract Purpose: The aim of this study was to establish independent prognostic models for primary and recurrent retroperitoneal liposarcoma (RLS). Experimental design: A total of 2429 patients confirmed to have RLS were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The 245 patients collected from the same period at First Medical Center, Chinese People Liberation Army General Hospital (CPLAGH), were used for external validations. Nomogram were built on the basis of clinical practicability, univariate and multivariate Cox analyses. Results: The simplified predictive models for primary RLS was mainly based on tumor size (median size, 162 mm [range, 90-230], P < 0.001) and pathological subtypes (WDL vs DDL, hazard ratio[HR]=2.11; 95% confidence interval [CI]=1.71-2.61; P < 0.001), which can be acquired in the outpatient clinics. However, TNM stage (Stage 1 vs Stage 2, HR=2.18; 95% CI=1.49-3.20; P < 0.001) as an extremely important postoperative indicator was enrolled in the model for recurrent RLS. The area under the time-dependent receiver operating characteristic curve (time-dependent AUC) and concordance index (C-index) of models almost approach 0.75 in the training and validation cohorts. These results indicated favourable discrimination of the models. The calibration curves of the model illustrated good consistency between the predicted and observed survival probabilities in both the training and two validation cohorts. Furthermore, decision curve analysis (DCA) revealed that the nomogram models were clinically useful and had considerable practicability. Conclusion: Efficient and independent models for primary and recurrent RLS will providing clinical guidance for both prognostication and individualized therapeutic decision-making. Citation Format: Huan Deng, Zhenhau Lu, Binrui Wang, Yisheng Pan. v [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4524.
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Soleman, Riky. "KONTRIBUSI ISLAMIC BANKING FINANCING AND VARIABLES MACRO ECONOMIC TERHADAP TINGKAT KEMISKINAN DI INDONESIA." Izdihar: Jurnal Ekonomi Syariah 4, no. 01 (2024): 21–33. http://dx.doi.org/10.32764/izdihar.v3i02.3856.

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Poverty is a global issue faced by many countries in the world, including Indonesia. The purpose of this study is to examine the level of poverty in Indonesia by measuring the financing of Islamic banking, education, health, TPAK and inflation against the level of poverty in Indonesia. The data source used is panel data obtained from the Central Bureau of Statistics (BPS) for the 2010-2020 period. Data analysis used panel data regression with Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM) Approach processed with E-Views 10. The results of this study indicate that the estimated model chosen in this study is Fixed The Effect Model shows the results of the Islamic Banking Financing, RLS, UHH, TPAK and Inflation variables that have a significant effect in a negative direction on the level of poverty for the RLS variable that has a simultaneous effect on the mission level while UHH has a significant effect in a negative direction. This means that if there are independent variables simultaneously, then the level of poverty in Indonesia is increasingly leading to change. Whereas in the simultaneous test the prob value of the F-Statistic is 0.000000 <0.05, which means that the five independent variables simultaneously influence the level of poverty in Indonesia. And the Adjusted R-Square value is 0.987540 which means that 90% of the Islamic Banking Financing, RLS, UHH, TPAK and Inflation variables in this study are able to explain the poverty rate variable in Indonesia. While the remaining 10% is explained by other variables outside the model.
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Sonaviya, Dipeshkumar R., and Bhaven N. Tandel. "Integrated road traffic noise mapping in urban Indian context." Noise Mapping 7, no. 1 (2020): 99–113. http://dx.doi.org/10.1515/noise-2020-0009.

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AbstractRoad traffic noise has been recognized as a serious issue that affects the urban regions. Due to urbanization and industrialization, transportation in urban areas has increased. Traffic noise characteristics in cities belonging to a developing country like India are highly varied compared to developed nations because of its heterogeneous conditions. The objective of the research study is to assess noise pollution due to heterogeneous traffic conditions and the impact of horn honking due to un-authorized parked vehicles on the main roadside. Noise mapping has been done using the computer simulation model by taking various noise sources and noise propagation to the receiver point. Traffic volume, vehicular speed, noise levels, road geometry, un-authorized parking, and horn honking were measured on tier-II city roads in Surat, India. The study showed not so significant correlation between traffic volume, road geometry, vehicular speed and equivalent noise due to heterogeneous road traffic conditions. Further, analysis of traffic noise showed that horn honking due to un-authorized parked vehicles contributed an additional up to 11 dB (A), which is quite significant. The prediction models such as U.K’s CoRTN, U.S’s TNM, Germany’s RLS-90 and their modified versions have limited applicability for heterogeneity. Hence, the noise prediction models, which can be used for homogeneous road traffic conditions are not successfully applicable in heterogeneous road traffic conditions. In this research, a new horn honking correction factor is introduced with respect to unauthorized parked vehicles. The horn honking correction values can be integrated into noise model RLS-90, while assessing heterogeneous traffic conditions.
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Dai, Benlin, Yulong He, Jiming Xu, Ning Xu, Zhen Wu, and Yuanfang Deng. "Applying the RLS 90 to Develop an Inland Waterway Traffic Noise Prediction Model in China That Considers Water Surface Influence." Journal of Low Frequency Noise, Vibration and Active Control 34, no. 1 (2015): 73–85. http://dx.doi.org/10.1260/0263-0923.34.1.73.

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Muslim, Muhammad Aziz, Goegoes Dwi Nusantoro, and Dion Putra Pribadi. "Identifikasi Motor DC dengan Metode Recursive Least Square." Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) 15, no. 2 (2022): 73–78. http://dx.doi.org/10.21776/jeeccis.v15i2.1547.

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Motor DC Minertia tipe UGTMEM-03STC25 merupakan salah satu alat di Laboratorium Sistem Kontrol Universitas Brawijaya Malang. Dengan menggunakan metode RLS motor DC Minertia tipe UGTMEM-03STC25 diperoleh model terbaik adalah orde 4 dengan parameter a1 = -0.405, a2 = -0.01, a3 = -0.0123, a4 = -0.0138, b1 = 0.0095, b2 = 0.0169, b3 = 0.9036, dan b4 = -0.3521. Setelah dilakukan uji validitas data percobaan dengan whiteness test, akaike's FPE, dan Fitness test Motor DC Minertia tipe UGTMEM-03STC25 didapatkan hasil nilai PRBS dengan batas bawah 50 dan batas atas 70 mendapatkan nilai Best Fits sebesar 83.3973% dan nilai FPE 0.1041, dan ketika nilai PRBS dengan batas bawah 60 dan batas atas 90 mendapatkan nilai Best Fits 90.4838% dan nilai FPE 0.1891 dan nilai PRBS dengan batas bawah 50 dan batas atas 90 mendapatkan nilai Best Fits 92.2456% dan nilai FPE 0.1065. Angka keakurasian ini dinyatakan dalam persentase, dimana semakin besar nilainya (maksimal 100%) dapat diartikan keluaran model sudah mendekati keluaran sistem yang sesungguhnya. dan nilai FPE pada data-data tersebut sudah sangat mendekati nol semakin kecil nilai FPE yang didapat, maka model tersebut semakin mewakili system yang telah dimodelkan.
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Yoon, Jewon, Chulhwan Kim, Woongyong Lee, Hyejin Kang, and Jooweon Lee. "Parameter analysis and Reliability Evaluation of Road Traffic Noise Prediction Model for Highway Traffic Noise Evaluation." Journal of Korean Society of Environmental Engineers 44, no. 8 (2022): 267–75. http://dx.doi.org/10.4491/ksee.2022.44.8.267.

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The purpose of this study is to evaluate the reliability of prediction models(KHTN, RLS-90, CRTN, NMPB-08) that are widely used in road traffic noise analysis. For this purpose, the accuracy and difference values of the prediction model were analyzed by comparing the measurement values performed at the total of 21 highway sites, reflecting various conditions such as road structure, road pavement type, and noise barrier installation. In addition, the correlation between commercial programs(SoundPlan, CadnaA) was compared and reviewed for each of the same prediction models. First of all, as a result of analyzing the accuracy of each prediction model, KHTN is rated as 92.8% the most accurate based on ±3 dB error range. And CRTN is rated as 74.0~76.8% the most accurate among prediction models inherent in commercial programs. And, as a result of analyzing the correlation between commercial programs for prediction models, CRTN is 100% highly correlated and NMPB has the lowest correlation by 69.6%.
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Hustim, Muralia, Muhammad Isran Ramli, Rasdiana Zakaria, and Zulfiani AR. "The Effect of Speed Factors and Horn Sound to The RLS 90 Model Reliability on The Visum Program in Predicting Noise of Heterogeneous Traffic." International Journal of Integrated Engineering 10, no. 2 (2018): 77–81. http://dx.doi.org/10.30880/ijie.2018.10.02.015.

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Melo, Andrélia Maciel, Nilton Vivacqua-Gomes, Ricardo Affonso Bernardes, Rodrigo Ricci Vivan, Marco Antônio Húngaro Duarte, and Bruno Carvalho de Vasconcelos. "Influence of Different Coronal Preflaring Protocols on Electronic Foramen Locators Precision." Brazilian Dental Journal 31, no. 4 (2020): 404–8. http://dx.doi.org/10.1590/0103-6440202003282.

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Abstract: The aim of this study was to evaluate the influence of different coronal preflaring protocols (absent, conservative and conventional) on the accuracy of Root ZX II, Raypex 6, and RomiApex A-15 electronic foramen locators (EFLs). Twenty mandibular molars with Vertucci’s type IV mesial roots were subjected to endodontic exploration and foraminal patency confirmation. Under 16x magnification, its real lengths (RL) were measured and registered (RL1). The canals were then irrigated with 2.5% sodium hypochlorite and electronically measured (EM1) employing the alginate model; all measurements were performed in triplicate by a blind operator using adjusted endodontic hand-files introduced until the apex foramen. Coronal preflaring procedures were sequentially performed with #25/.06 (conservative) and #25/.12 (conventional) instruments; new RLs extents were performed after each coronal preparation protocol (RL2/RL3), as same as electronic measurements (EM2/EM3). The devices error (mm) was evaluated considering the difference between RLs and EMs at each preparation stage; their precision was stablished adopting ±0.5 mm as tolerance margin. The EFLs error significantly reduced after conventional coronal preflaring protocol (p<0.05), which not occur after the conservative one. The best precisions values were noted after conventional preparation as 90% (Root ZX II), 97.5% (Raypex 6), and 92.5% (RomiApex A-15). No significant differences were found in EFLs comparisons, regardless of the coronal protocol tested (p>0.05). Under the conditions tested it can be concluded that the EFLs evaluated were precise. Moreover, the preflaring protocols influences its accuracy’s, where the less conservative one produced the best results.
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AR, Zulfiani. "Prediksi Kebisingan Lalu Lintas Heterogen Menggunakan Aplikasi Visum." Jurnal Teknik Sipil MACCA 6, no. 2 (2021): 126–34. http://dx.doi.org/10.33096/jtsm.v6i2.337.

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Kebisingan merupakan salah satu permasalahan yang berpengaruh pada keselamatan lalu lintas. Kebisingan yang terjadi berasal dari berbagai macam aktivitas lalu lintas di jalan, baik yang bersumber dari kendaraan umum maupun kendaraan pribadi. Indonesia sebagai negara berkembang juga tak lepas dari masalah kebisingan lalu lintas. Kendaraan yang bergerak di jalan akan mengeluarkan suara baik itu mesin maupun klakson kendaraan. Penelitian ini bertujuan memprediksi kebisingan yang dihasilkan lalu lintas heterogen menggunakan program Visum. Titik pengamatan dilakukan pada 37 titik pada ruas jalan Kota Makassar. Waktu pengamatan dilakukan pada pukul 06.00 – 18.00 dan 06.00 – 21.00 dengan objek penelitian sepeda motor (Motorcycle), kendaraan ringan (Light Vehicle) dan kendaraan berat (Heavy Vehicle). Data yang diamati adalah volume lalu lintas, kecepatan kendaraan, jumlah klakson dan kebisingan dengan menggunakan alat Sound Level Meter Tenmars TM-103. Hasil menunjukkan bahwa tingkat kebisingan hasil prediksi menggunakan program Visum dengan model prediksi RLS 90 menghasilkan nilai tingkat kebisingan rata-rata 69,3 dB dengan korelasi pearson dan RMSE sebesar 0,71 dan 9,97.
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Dissertations / Theses on the topic "RLS-90 MODEL"

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SINGH, AMIT. "MONITORING AND PREDICTION OF NOISE LEVEL IN URBAN AREA USING RLS-90 MODEL." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16056.

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Noise pollution is the major environmental problem in developing countries as well as in developed country. Rapid industrialization, vehicle growth, urbanization and change in lifestyle of people has increased the noise level above the prescribed standard level. Traffic noise contribution in the total noise pollution is approximately 75%. Delhi is the fourth noisiest city in the world and third noisiest city of the India. During this study, by keeping in mind the significance of the noise pollution in Delhi, ten locations have been selected to monitor the ambient noise level. These locations have been identified on the basis of different kind of land use pattern like residential, commercial and silence zone. The monitoring has been conducted during morning peak hour, off peak hour and evening peak hour. Sound level meter (Cesva SC 260) type two instrument has been used to monitor the ambient noise level at selected location. Worldwide, various traffic noise model like FHWA, CORTN, Stop and Go and RLS -90 are available for the prediction of traffic noise in different condition. In this study RLS-90 Model has been used to predict the noise level at all the selected location. At the same time, this model used to forecast the traffic noise for the year of 2022, 2027 and 2032. After data analysis, it was observed that the measured ambient noise level at all the locations were violated the permissible limits prescribed by CPCB. During monitoring, highest traffic noise level was observed at Ashram Chowk. This may be due to higher traffic volume as well as high traffic congestion at the particular location. The parentage error between monitored traffic noise level and predicted traffic noise level was found within the range of 0.5 % to 5.75% which indicates the suitability and applicability of the model in city like Delhi.
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Conference papers on the topic "RLS-90 MODEL"

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Alam, Pervez, Kafeel Ahmad, S. S. Afsar, and Nasim Akhtar. "Validation of the Road Traffic Noise Prediction Model RLS-90 in an Urban Area." In 2020 3rd International Conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things (ICETCE). IEEE, 2020. http://dx.doi.org/10.1109/icetce48199.2020.9091759.

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