Miracle-dz/UniFAR-FTUs huggingface dataset:
STUDI POTENSI PEMBANGKIT LISTRIK TENAGA SAMPAH (PLTSa) PADA TEMPAT PEMBUANGAN AKHIR (TPA) MAKBON KOTA SORONG

TPA mengemisikan Landfill Gas (LFG) yang mengandung paling banyak metana dan karbondioksida. Metana memiliki efek pemanasan beberapa kali lebih kuat dalam menyebabkan pemanasan bumi dibandingkan dengan CO2. Oleh karena itu pemanfaatan metana TPA sebagai bahan bakar pembangkit listrik telah menjadi target negara-negara berkembang untuk mengurangi green house gas emissions (GHGs). Sebelum membangun Pembangkit Listrik Tenaga Sampah (PLTSa) di sebuah TPA dibutuhkan serangkaian studi untuk menentukan apakah PLTSa layak dibangun di TPA tersebut, salah satunya adalah mengetahui jumlah LFG dari TPA untuk menghitung potensi energi listrik yang dapat dihasilkan. Tujuan dari penelitian ini adalah mengetahui jumlah LFG yang dihasilkan oleh TPA Makbon Kota Sorong dan selanjutnya menghitung potensi PLTSa berdasarkan kandungan metana dalam LFG. Tahapan penelitian dimulai dari pengumpulan data kuantitatif berupa jumlah ton sampah yang masuk ke TPA setiap tahun, ukuran TPA, dan jumlah penduduk. Untuk estimasi LFG digunakan LandGEM-v302 yang diunduh dari website US EPA. Sedangkan untuk estimasi potensi energi listrik digunakan rumus. Dari hasil penelitian, TPA Makbon Kota Sorong model sanitary landfill menghasilkan emisi maksimal metana sebesar 7,321 x 105 m3 pada tahun 2035 jika diasumsikan tahun 2020 mulai menerima sampah. Berdasarkan hasil penghitungan dengan menggunakan rumus diperoleh potensi energi listrik maksimal yang dihasilkan 1,685 x 106 kWh.
Polarimetric SAR Signatures for Characterizing Geological Units in the Canadian Arctic

This study investigates the polarimetric radar signatures of geological units in the Canadian Arctic to characterize their physical surface properties. It focuses on the Tunnunik and Haughton meteorite impact structures using RADARSAT-2 quad polarimetric synthetic aperture radar (SAR) data. The geological units show different three-dimensional (3-D) polarimetric SAR signature plots (i.e., radar backscattering responses according to the orientation and the ellipticity of a polarization state). We analyzed the quantitative relationship between the polarimetric SAR signatures of the geological units and their surface roughness. The pedestal height and the standard deviation of linear copolarization responses (SDLP) were calculated from the 3-D copolarization power signature plot, and then compared to in situ surface roughness measurements derived from LiDAR scanned high-resolution surface topography. The results show that the pedestal height has a positive correlation coefficient of ∼0.6 with surface roughness, while the SDLP has a negative correlation coefficient of ∼0.8 with surface roughness. The variation between the different polarization responses is highly dependent on the surface roughness of the geological units. The SDLP is thus suggested as a promising parameter to characterize surface roughness, in addition to the pedestal height that has been commonly used.
Implementasi Metode Triple Exponential Smoothing Untuk Perkiraan Stok Barang

Market analysis is one of the fundamental things in company decision making, including inventory or stock of goods and sales data trends. Several studies have discussed this method, but in this study, it was tested on inventory data on rental business. Based on this, the question in this study is how is the implementation of the exponential smoothing method used in forecasting and analyzing inventory? Data was collected based on observations for 6 months, between January-June. And what will be calculated is the estimated stock of goods in July. The result is for the supply of certain goods produced number 35. This means that for certain brands of goods must inventory as many as 35 pieces so that in July does not run out of stock. Keywords: Triple Exponential Smoothing, Estimation, Stock
Potential impact of mid-frequency active sonar on whales from passive acoustic monitoring data

Behavioral response studies of tagged whales have documented an adverse reaction to mid-frequency active sonar (MFAS). The relationship between MFAS and the acoustic behavior of whales is complex and requires accounting for natural variability in species presence. We examine the acoustic response of Cuvier’s beaked whales (Ziphius cavirostris) and blue whales (Balaenoptera musculus) from long-term acoustic recordings at three sites in Southern California waters from 2009 to 2015. Presence and absence were marked in 1-min bins for all signal types. Generalized estimating equations (GEEs) were used to model relationships between species acoustic detection and temporal and sonar covariates while accounting for residual temporal autocorrelation. Both species showed considerable temporal variability in calling. Modeling at one site showed decreased detections of beaked whale echolocation clicks when sonar signals had higher received levels at the recorders and when the proportion of bins containing sonar increased. On cessation of sonar signals, beaked whale detection increased over periods of up to about a week. Analyses of blue whale response and a comparison of multiple sites will also be presented. This work represents substantial progress in our understanding of the impact of MFAS on cetaceans, which is crucial for effective context-dependent management of anthropogenic activities.
DESIGN OF DUAL-MODE BAND-PASS FILTER WITH NOVEL PERTURBATION ELEMENTS

A compact square patch band-pass filter is proposed in this paper. The dual-mode filter is designed based on a square patch resonator with a complementary split ring resonator (CSRR) split to be used as a perturbation element. The CSRR split is properly embedded in the square patch resonator to perturb electric current distribution on this patch and thus to simultaneously excite a pair of degenerate modes. Using the proposed CSRR elements, the band-pass filter is designed with miniaturized size, and two transmission zeros in stopbands are achieved to improve the selectivity of the filter. The influence of the CSRR elements on the band-pass filter is analyzed in detail. The proposed dual-mode filter is then fabricated and measured. Good agreement over a wide frequency range is achieved between the simulated and measured results. Moreover, in order to further investigate the characteristic of the dualmode patch filters with CSRR perturbation, a dual-mode filter with a rectangular ring slot is presented for comparative study.
Theory Of Reflectance And Emittance Spectroscopy

Thank you very much for reading theory of reflectance and emittance spectroscopy. Maybe you have knowledge that, people have search numerous times for their chosen readings like this theory of reflectance and emittance spectroscopy, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some malicious virus inside their computer.
Observer-Based Adaptive Finite-Time Quantized Tracking Control of Nonstrict-Feedback Nonlinear Systems With Asymmetric Actuator Saturation

This paper investigates the output feedback adaptive finite-time quantized tracking problem for a class of uncertain nonstrict-feedback nonlinear systems with asymmetric actuator saturation, where signals including the measurable output and the control input are quantized by the sector-bounded quantizers. In order to overcome the technical difficulties arising from asymmetric actuator saturation and sector-bounded quantization errors, the combination of some novel techniques, the Gaussian error function-based smooth model, and fuzzy logic system approximation-based method are utilized. Moreover, an observer involving the quantized output signal and the saturated input signal is designed to reconstruct the unknown states. Then an adaptive output feedback tracking control strategy is developed for this class of systems, so that the system output follows satisfactorily a desired reference signal in finite time while all signals in the closed-loop systems are semi-global practical finite-time stable. Finally, two illustrative simulation examples are provided to validate the effectiveness and applicability of the proposed design.
Uma proposta para predição de risco de evasão de estudantes em um curso técnico em informática

O alto ı́ndice de evasão em cursos de tecnologia é um desafio enfrentado por muitas instituições de ensino. Por isso, identificar os estudantes em situação de risco de evasão é relevante para que possam ser realizadas ações de incentivo à permanência e êxito. Este trabalho apresenta uma proposta para predição de evasão considerando informações acadêmicas e socioeconômicas de estudantes. Em particular, uma das etapas da proposta engloba a aplicação de algoritmos de Aprendizagem de Máquina. Um estudo de caso é apresentado considerando uma base de dados de 8 anos de um curso Técnico em Informática do IFCE. Os resultados demonstram a eficácia da proposta, alcançando 97,97% de taxa de acerto na previsão da situação dos estudantes.
Inertial confinement fusion

This issue of the ICF Quarterly contains seven articles that describe recent progress in Lawrence Livermore National Laboratory's ICF program. The Department of Energy recently initiated an effort to design a 1--2 MJ glass laser, the proposed National Ignition Facility (NIF). These articles span various aspects of a program which is aimed at moving forward toward such a facility by continuing to use the Nova laser to gain understanding of NIF-relevant target physics, by developing concepts for an NIF laser driver, and by envisioning a variety of applications for larger ICF facilities. This report discusses research on the following topics: Stimulated Rotational Raman Scattering in Nitrogen; A Maxwell Equation Solver in LASNEX for the Simulation of Moderately Intense Ultrashort Pulse Experiments; Measurements of Radial Heat-Wave Propagation in Laser-Produced Plasmas; Laser-Seeded Modulation Growth on Directly Driven Foils; Stimulated Raman Scattering in Large-Aperture, High-Fluence Frequency-Conversion Crystals; Fission Product Hazard Reduction Using Inertial Fusion Energy; Use of Inertial Confinement Fusion for Nuclear Weapons Effects Simulations.
Considering the Role of Adaptive Evolution in Models of the Ocean and Climate System

Numerical models have been highly successful in simulating global carbon and nutrient cycles in today's ocean, together with observed spatial and temporal patterns of chlorophyll and plankton biomass at the surface. With this success has come some confidence in projecting the century‐scale response to continuing anthropogenic warming. There is also increasing interest in using such models to understand the role of plankton ecosystems in past oceans. However, today's marine environment is the product of billions of years of continual evolution—a process that continues today. In this paper, we address the questions of whether an assumption of species invariance is sufficient, and if not, under what circumstances current model projections might break down. To do this, we first identify the key timescales and questions asked of models. We then review how current marine ecosystem models work and what alternative approaches are available to account for evolution. We argue that for timescales of climate change overlapping with evolutionary timescales, accounting for evolution may to lead to very different projected outcomes regarding the timescales of ecosystem response and associated global biogeochemical cycling. This is particularly the case for past extinction events but may also be true in the future, depending on the eventual degree of anthropogenic disruption. The discipline of building new numerical models that incorporate evolution is also hugely beneficial in itself, as it forces us to question what we know about adaptive evolution, irrespective of its quantitative role in any specific event or environmental changes.
Uniqueness of solutions for weakly degenerate cordial Volterra integral equations

We study the question of uniqueness of solutions to cordial Volterra integral equations in the sense of Vainikko (Numer. Funct. Anal. Optim. 30, 2009, pp. 1145– 1172) in the case where the kernel (or core) function K(θ) ≡ K(y/x) vanishes on the diagonal x = y. When, in addition, K is sufficiently regular, is strictly positive on (0, 1), and θ−k K′(θ) is non-increasing for some k ∈ R, we prove that the solution to the corresponding Volterra integral equation of the first kind is unique in the class of functions which are continuous on the positive real axis and locally integrable at the origin. Alternatively, we obtain uniqueness in the class of locally integrable functions with locally integrable mean. We further discuss a uniquenessof-continuation problem where the conditions on the kernel need only be satisfied in some neighborhood of the diagonal. We give examples illustrating the necessity of the conditions on the kernel and on the uniqueness class, and sketch the application of the theory in the context of a nonlinear model.
Observer-Based Asynchronous Fault Detection for Conic-Type Nonlinear Jumping Systems and its Application to Separately Excited DC Motor

This work investigates the observer-based asynchronous fault detection problem for a class of nonlinear Markov jumping systems. The conic-type nonlinearities hold such a restrictive condition that locates in a known hypersphere with an undefined centre. In order to guarantee the observer modes run synchronously with the system modes, we introduce a hidden Markov model to deal with this difficulty. Utilizing <inline-formula> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$H_\_{}$ </tex-math></inline-formula> performance index, a multi-targets strategy of asynchronous fault detection problem is formulated. Via linear matrix inequality, sufficient conditions for the presence of the asynchronous fault detection observer are derived respectively. Then an asynchronous fault detection algorithm is formulated. Finally, the application of dynamic equivalent circuit of separately excited DC motor with three cases is employed to illustrate that the devised asynchronous fault detection observer is able to detect the faults after the appearances in the absence of any incorrect alarm.
Newton-SOR Iteration for Solving Large-Scale Unconstrained Optimization Problems with an Arrowhead Hessian Matrices

Solving unconstrained optimization problems using Newton method requires calculating Newton’s direction, which involves inverse Hessian matrices. Once the order of Hessian matrices is large, it may be impossible to store the inverse of the Hessian matrices using the direct method. To overcome this problem, we used a point iterative method as an inner iteration in finding Newton direction. Therefore in this paper, we proposed a combination between Newton method and successive overrelaxation (SOR) point iterative method for solving large scale unconstrained optimization problems in which the Hessian of the Newton direction is arrowhead matrices. To calculate and validate the performance of the proposed method, we used a combination of Newton method with Gauss-Seidel point iteration and Jacobi point iteration scheme as a reference method. The proposed method provides results that are more efficient compared to the reference methods in terms of execution time and a number of iteration.
High-resolution mapping of protected agriculture in Mexico, through remote sensing data cloud geoprocessing

ABSTRACT In recent years, plasticulture, which is broadly defined as the use of plastics in agriculture, including greenhouse, tunnels and plastic mulch has become a fast-growing production system. While in the 1970s, the system was used on 2.8 M ha worldwide, the area had grown to 38 M ha in 1996/97 and is still increasing at a rapid rate: In Asia and Africa, the use of plastic greenhouses is growing by 15-30% per year. Therefore, plasticulture is expected to rise in many agrarian countries such as Mexico. Nonetheless, there are negative effects of plasticulture, that need to be correctly addressed in order to have responsible rural landscape management. Ergo our study attempts, through cloud geoprocessing of Sentinel-2 imagery, to rapidly provide a reliable and updated high-resolution map of protected agriculture that employs plastics (mostly tunnels and greenhouses). This map can be used as a basis for a protected agriculture monitoring system in Mexico, and eventually help to effectively plan the upcoming rural development, e.g. by providing input for territorial planning, showing the municipal rural practice trends, and monitoring the markets and its economic impacts.
Direct Torque Control Based on Shoot-Through States of an Induction Motor Fed by a Z-Source Three-Level Neutral Point Clamped Inverter

This paper deals with an adaptive direct torque control of an induction motor fed by a Z-source three-level NPC (Neutral Point Clamped) inverter. The proposed control ensures simultaneously the buck-boost operation mode and the induction motor control. Indeed, a switching table, taking into account the Z-source structure, is developed for the direct torque control. In this context, shoot-through states of the Z-source three-level NPC inverter is applied in each sampling time of the direct torque control. The proposed system can be used as promising solution in event of sags voltage, improve power factor, and reduce harmonics. Experimental tests, carried out on digital development board, clearly demonstrate the feasibility and effectiveness of the proposed control.
Identification of jet aircraft model based on frequency characteristics of noise by convolutional neural network

: We have been developing an aircraft model identiﬁcation system that uses a convolutional neural network (CNN). The assumption is that this identiﬁcation system would be used to estimate the number of ﬂights to create noise maps. In our previous study, we used the CNN model to classify ﬁve aircraft comprising three rotorcraft, one turboprop, and one jet aircraft, and the accuracy reached 99%. In the present study, to examine whether this method is also eﬀective for identifying the sound sources of jet aircraft, we conducted two case studies using frequency characteristics of aircraft noise obtained from ﬁeld measurements around Osaka International Airport and Narita International Airport. Targeting 7 and 18 types of sound source at Osaka and Narita, respectively, an identiﬁcation rate of 98% was obtained in both cases. This suggests that the present system can estimate the number of jet aircraft ﬂights for each engine type or each aircraft model with very high accuracy.
Design of pitch angle controller for wind turbine based on pi neurofuzzy model

Aerodynamic torque of wind turbine is adjusted by controlling the pitch angle of the blades of the turbine when the wind speed is higher than rated wind speed. So that, in the recent research in this field, the pitch angle controller becomes dominated controller type for extracting the electrical power from the wind energy. Three types of the pitch angle control systems are designed to construct the speed controller: conventional PI controller, Neurofuzzy controller and modified PI-Neurofuzzy controller. The results are shown that the modified PI-Neurofuzzy controller is more efficient than the others because the rotation speed of generator is kept almost constant. It means that the generated output power has remained constant at maximum power limited even the wind speed rises up the rated wind speed.
Simulasi Dan Analisis Sistem Smart Traffic Light Berbasis Pengolahan Citra Digital Dengan Metode Deteksi Tepi Dan Segmentasi

Sistem lampu lalu lintas saat ini belum cukup efektif untuk mengurai kemacetan karena sistemnya masih menggunakan fixed time traffic signal dimana sistem ini bekerja dengan waktu yang telah ditentukan. Hal ini menyebabkan terjadinya banyak kemacetan dibeberapa ruas jalan. Pada penulisan tugas akhir ini dikembangkan sitem lampu lalu lintas yang bisa mendeteksi ruas mana yang memiliki antrian paling panjang pada persimpangan jalan. Cara kerja detektor ini merekam video pada masing-masing ruas jalan dan frame didetik ke 40 diambil untuk diproses menggunakan metode deteksi tepi dan segmentasi. Perhitungan centroid dan thresholding dilakukan agar sistem dapat membedakan warna aspal dengan kendaraan. Pengambilan video ini dilakukan di 3(tiga) kondisi yaitu pagi hari(cerah), siang hari(cerah), dan sore hari(berawan). Hasil yang diperoleh dari penelitian ini adalah sebuah sistem yang mampu menentukan ruas mana yang memiliki antrian paling panjang dengan menghitung panjang centroid-centroid pada masing-masing ruas jalan. Setelah dilakukan pengujian terhadap sistem, dapat diambil kesimpulan bahwa sistem bekerja secara optimal di pagi dan sore hari dengan tingkat akurasi sebesar 82,85%. Sedangkan sistem bekerja kurang optimal di siang hari dengan tingkat akurasi sebesar 77,14%. Dengan demikian rata-rata tingkat akurasi sistem sebesar 80,93%. Kata kunci : Lampu lalu lintas, citra, antrian, deteksi tepi, segmentasi
Extraction of snow cover from high-resolution remote sensing imagery using deep learning on a small dataset

ABSTRACT Snow cover is of great significance for many applications. However, automatic extraction of snow cover from high spatial resolution remote sensing (HSRRS) imagery remains challenging, owing to its multiscale characteristics, similarities to clouds, and occlusion by the shadows of mountains and clouds. Deep convolutional neural networks for semantic segmentation are the most popular approach to automatic map generation, but they require huge computing time and resources, as well as a large dataset of pixel-wise annotated HSRRS images, which precludes the application of many superior models. In this study, these limitations are overcome by using a sequence of transfer learning steps. The method starts with a modified aligned ‘Xception’ model pre-trained for object classification on ImageNet. Subsequently, a ‘DeepLab version three plus’ (DeepLabv3+) model is trained using a large dataset of Landsat images and corresponding snow cover products. Finally, a second transfer learning step is employed to fine-tune the model on the small dataset of GaoFen-2, the highest resolution HSRRS satellite in China. Experiments demonstrate the feasibility and effectiveness of this framework for automatic snow cover extraction.
Understanding the Impact of Individual Users' Rating Characteristics on the Predictive Accuracy of Recommender Systems

In this study, we investigate how individual users’ rating characteristics affect the user-level performance of recommendation algorithms. We measure users’ rating characteristics from three perspectives: rating value, rating structure, and neighborhood network embeddedness. We study how these three categories of measures influence the predictive accuracy of popular recommendation algorithms for each user. Our experiments use five real-world data sets with varying characteristics. For each individual user, we estimate the predictive accuracy of three recommendation algorithms. We then apply regression-based models to uncover the relationships between rating characteristics and recommendation performance at the individual user level. Our experimental results show consistent and significant effects of several rating measures on recommendation accuracy. Understanding how rating characteristics affect the recommendation performance at the individual user level has practical implications for the design of recommender systems.