Miracle-dz/UniFAR-FTUs huggingface dataset:
MODELLING OF 250WP PHOTOVOLTAIC MODULE AND ITS PERFORMANCE ANALYSIS USING MATLAB /SIMULINK

Interlinking of photovoltaic (PV) power to grid is one of the major interests. Design, study and analysis of key components in a photovoltaic power system starting from generation of power to interlinking to main grid are very crucial. Photovoltaic module is one of the main components of a photovoltaic power system. Also the PV power is dependent on a source of energy that can fluctuate daily, hourly and over even shorter periods hence it is important to build an accurate photovoltaic module and analyze characteristics of the PV module under various conditions. Further, for the design of an efficient MPPT algorithm the range of maximum power to be tracked is necessary. This paper presents an efficient PV module based on single diode equivalent circuit model using MATLAB/Simulink. And compared the simulated model results with manufacturer’s specifications like peak current, peak voltage, open circuit voltage and short circuit current . Also the performance of the module under variation of series resistance, ideality factor, irradiation, and temperature are analyzed. Model evaluation is presented using a WEBEL SOLAR W2300 250W Monocrystalline module. The simulated results matches with the manufacturer specification and analysis of module provides a range of peak power during various conditions which helps in designing an accurate PV system. KeywordsIrradiation, MATLAB/Simulink, PV module, Temperature. Nomenclature Used: Icell– output current of a cell Im – output current of a module Isc– Short circuit current of the cell at reference temperature Ish –current through shunt resistor Is –reverse saturation current at reference temperature Imp–current at Maximum power condition V– terminal voltage of the cell/module Voc– open circuit voltage at reference temperature. Vmp– voltage at Maximum power condition Vt– thermal voltage of cell/module at reference temperature Rsh– shunt resistance Rs – series resistance K –Boltzmann's constant =1.3806503 × 10 J/k q– electron charge 1.60217646 × 10C N– diode ideality factor Ir–irradiation in W/m P–output power of the cell/module –Efficiency of the cell/module. Pm –maximum power Ac= area of the cell/module (m). E–Input light energy (W/m) or Ambient Irradiation Ki–short circuit current co-efficient in A/C Tref–reference temperature in Kelvin T –Temperature of cell/module in Kelvin Eg–band gap energy in electron volt
Digital Modulation

In the following, we will first introduce the concept of signal space, which is a vector space with waveform as vectors. With the concept of signal space in mind, we then develop the basic principles of converting sequences to waveforms and vice versa, using orthogonal expansions and projections. Then, we introduce a standard way of converting symbol sequences to waveforms, called Pulse Amplitude Modulation (PAM), where the key component is pulse shaping. In pulse shaping, in order to be able to reconstruct the symbols from waveforms at the receiver, certain condition needs to be satisfied for the waveform. Nyquist Criterion is a sufficient condition that is simple to evaluate. Next, we switch gear to baseband-passband conversion and introduce a standard way called Quadrature Amplitude Modulation (QAM). With QAM, we then derive the equivalent complex baseband representation. Finally, the design of symbol mapping is discussed, and a prevalent way called Gray Mapping is introduced. The design of constellation set is also covered, and several standard constellation sets including PSK, PAM, and QAM are introduced.
Potentials and Challenges of Existing Plastic Pollutant Biodegradation Using Bacteria in Jakarta Bay

Research conducted by Research Center for Marine and Fisheries Product Processing and Biotechnology in the three different locations namely Tarakan, Tanjung Balai Asahan, and Jakarta Bay, has identified that Jakarta Bay had the highest plastic debris concentration among the others. Jakarta Bay is directly connected to Thousand Island National Park sea waters, in which large parts of it are marine conservation area. Thus, plastic pollutants potentially threat Jakarta Bay and Thousand Island National Park abundant biodiversity and underwater marine ecotourism. The tools such as garbage transport barges owned by Special Region of the Capital Jakarta Province are not enough to overcome the existing plastic debris. 21 tons waste end up to Jakarta Bay every day. There should be further research about solving existing plastic waste with other technology than using machine. This literature study aims to review and investigate the potentials and challenges of utilizing bacteria to combat existing marine plastic pollution in Jakarta Bay. Established researches showed that some bacteria strains isolated from plastic debris in some sea waters and sediments around the world are capable of degrading polyethylene (PE), polypropylene (PP), and possibly polystyrene (PS). Unfortunately, reports involving plastic degrading ability of bacteria isolated from plastic wastes in Indonesian sea waters, let alone Jakarta Bay, are hard to find if any. There were only researches about isolated bacterias from Jakarta Bay, which were capable of degrading oil spill. Further research about isolated bacteria from plastic debris of Jakarta Bay, should be established. It can be used to identify bacteria strains or consortia that are able to degrade plastic debris with environmentally friendly byproducts. There will be possibilities that oil spill degrading bacteria isolated from Jakarta Bay can also degrade plastics, as both oil spill and plastics are made up from hydrocarbon chains. A recently published research has revealed that Alvoranicus borkumensis isolated from marine plastic debris in Mediterranean Sea was able to degrade PE, while previously other study has isolated it from Thousand Islands sea waters and found it able to degrade marine oil spill. The expression possibility of DNA (deoxyribonucleic acid) sequence coding extracted from wax worm Galleria mellonella into widespread indigeneous Jakarta Bay bacteria and bacteria isolated from plastic debris in Jakarta Bay, can also be taken into account.
Physics-Informed Generative Adversarial Networks for Virtual Mechanical Testing

Physics-informed generative adversarial networks (PI-GANs) are used to learn the underlying probability distributions of spatiallyvarying material properties (e.g., microstructure variability in a polycrystalline material). While standard GANs rely solely on data for training, PI-GANs encode physics in the form of stochastic differential equations using autodifferentiation. The goal here is to show that experimental data from a limited number of material tests can be used with PI-GANs to enable unlimited virtual testing for aerospace applications. Preliminary results using synthetically generated data are provided to demonstrate the proposed framework. Deep learning and autodifferentiation capabilities in Tensorflow were implemented on Nvidia Volta V100 GPUs.
Psychological Ownership: Journey of Past towards a Promising Future..

Article History Published Online: 07 August 2018 Psychological ownership (PO), a relatively new construct in the domain of positive psychology, is still in its nascent stage. A clearer understanding of what is known about PO and what still needs to be explored, would provide a more focussed direction for future research initiatives in this direction. This study reviews papers published between 2001 and 2017 that fulfilled the criteria of being qualitative and/or quantitative studies on PO. An inductive review of the studies helped the researchers to unravel a model of (a) antecedents to PO which describes the factors affecting PO, (b) intervening role played by PO, (c) an outcome of PO, and d) distinguishing nature of PO making it stand apart from other related constructs. Towards the end, based on the review, directions for future research have been proposed for a greater understanding of the relationship between PO and other constructs, especially in the organizational context can be attained. Specifically, the present work presents a platform for the expansion of an inclusive theory of PO and concrete underpinning for empirical testing. This systematic review would help in understanding how organizations can benefit from psychological ownership since such a feeling would inculcate responsibility and stewardship amongst employees.
Association between jump asymmetry and reduced performance in the change of direction tests of youth soccer players

Limb asymmetries is the condition which soccer players may suffer from as they perform many actions on one limb. Furthermore, some sensitive and reliable methods to identify lower limb asymmetries are the use of isokinetic dynamometer, the back squat, the unilateral mid-thigh pull and the unilateral jump tasks. Additionally, it is not clear which is the impact of limb asymmetries on physical performance. The aims of the present study were to: 1) compare single-leg countermovement jump (SLCMJ), single-leg long jump (SLLJ), and single-leg triple jump (SLTJ) between dominant (D) and non-dominant (ND) limbs, 2) to investigate the relationship between inter-limb asymmetry from the above three unilateral jump tests and 505 test and arrowhead change of direction (COD) performance and 3) to examine the relationship of lateral trunk muscles strength asymmetry with COD performance in young soccer players. Forty-two young male soccer players were separated into two groups (Under 10 U10 and Under 15 U15) and each one of them performed a SLCMJ, SLLJ, SLTJ, 505 COD test, arrowhead COD test. In order to investigate the relationship between limb asymmetries and performance on unilateral COD tests, paired samples T-test were used and Pearson’s to compare the results of their limbs. In U10 significant differences between limbs were observed on SLCMJ (p=0.024) and on SLTJ (p=0.003). SLTJ asymmetries correlated significant with slower arrowhead test times (p=0.039). In U15 significantly differences between limbs were observed on SLCMJ (p=0.032), on arrowhead test (p=0.016) and on 505 test (p=0.018). Asymmetries during SLCMJ were associated with slower performance on 505 COD test (p=0.017). The results indicated that in these two age groups (U10 and U15) of youth soccer players’ asymmetry detection is test depended. CMJ can be used in both groups for indentify lower limb asymmetries but this study highlight that the SLTJ for the age of U10 and SLCMJ for the age of U15 appear to be the most appropriate jump tests for identifying limb asymmetries. Additionally, the correlation of asymmetries with agility performance, which is very important for player success, indicates that trainers have to check their players for asymmetries and if there is a difference of greater than 10% it should be eliminated with specific and individualized strength and power programs.
Parameter Estimation of a Single-Phase Boost PFC Converter with EMI Filter Based on an Optimization Algorithm

This paper proposes an approach to estimate the parameters of an AC–DC boost power factor corrector converter that includes an EMI filter. To this end, once the topology was known, the values of the passive elements were identified from measurements at the input and output terminals of the converter. The parameters of the converter were identified based on the trust region nonlinear least squares algorithm. The steady-state and the transient signals of the converter at the input/output terminals were acquired non-intrusively without any internal modification of the circuitry. The accuracy of the proposed parameter identification approach was determined by comparing the estimated values with those provided by the manufacturer, and by comparing the measured signals with those obtained with a simulation model that included the estimated values of the parameters. The results presented in this paper prove the accuracy of the proposed approach, which can be extended to other power converters and filters.
Sustainable Free Cash Flow Analysis: A Better Measure for Resource Equities

In today’s challenging environment for global commodity prices, conventional valuation measures may not be the most effective in selecting resource stocks. In this paper, we examine the application of sustainable Free Cash Flow analysis for companies with high capital intensity. Our proprietary model suggests that sustainable Free Cash Flow can be a more insightful investment criterion in pursuing higher returns over the benchmark compared to ratios measuring price-to-earnings, price-to-cash-flow or net asset value. Our five-year sample study found that companies generating high sustainable Free Cash Flow yield tended to outperform.
DEVELOPMENTS IN GAS HYDRATE FORMATION EVALUATION

There has been a dramatic increase in both the amount and type of geophysical well log data acquired in gas hydrate saturated rocks. Data has been acquired in both offshore and Arctic environments; its availability has shed light on the applicability of current tools and the potential usefulness of recently developed and developing technologies. Some of the more interesting areas of interest are related to the usefulness of nuclear elemental spectroscopy data, the measurement of in-situ permeability and the interpretation of electrical borehole image and borehole seismic data. A key parameter for reservoir characterization and simulation is formation permeability. A reasonable understanding of this property is key to the development of future gas hydrate production. Typical applications of borehole image data are an appreciation of a reservoir’s geological environment. In hydrate saturated reservoirs, borehole images can also be used to assist in the understanding of the gas migratory path to the hydrate bearing formation. Traditionally, the identification of bottom simulation reflections (BSR) on surface seismic surveys has been used as an indicator of hydrates. Lately, the reliability of this as an indicator has been shown to be less than ideal. Recent borehole seismic survey acquisitions have advanced the understanding of this surface seismic response. This paper presents a review of the current state of geophysical log measurements in hydrate saturated reservoirs, their benefits and limitations.
A Deep Learning Based Implementation for Self-Driving Car

Today, self-driving cars are a part of our life. It has received much attention in recent years. Many big companies and developers have invested a lot in this area and developed their own autonomous driving car platforms. The intriguing area of self-driving car motivates us to build a self-driving platform. This paper proposes the self-driving car's architecture and its software components that have been solved in FPT's contest. Lane detection in different environmental conditions, dodging obstacles, and detecting traffic signs. In this competition, the vehicle is equipped with limited hardware such as a single low-cost camera, an Nvidia Jetson TX2 board. We analyze the results obtained in the game in the simulator. We see that our method has overcome limited hardware but still achieved good results in complex problems. The final product has been used to compete in the Digital Race competition 2020 - a competition held annually by FPT Corporation.
Automated Discovery of Secure Website Domains

Since the large-scale surveillance programs of intelligence agencies like the NSA became known, privacy concerns got in focus of the general public. Many websites support encryption via the HTTPS protocol securing the data transmitted between browsers and webservers by using TLS. Unfortunately, there is no reliable possibility to find out whether a website is available via HTTPS as well. Therefore, the Electronic Frontier Foundation (EFF) developed the browser extension HTTPS Everywhere that automates upgrading HTTP connections to secured HTTPS connections if this is supported by the corresponding server. The extension uses manually created and maintained URLrewriting rules that are shipped with the extension. This diploma thesis investigates the possibilities of automatic rule set generation. For this purpose, a software that checks a large set of domains on HTTPS support and generates the corresponding rules has been implemented. The websites reachable via HTTPS get compared to the versions available via HTTP in order to ensure their equality and correct rewriting rules. Therefore, we implemented and evaluated 15 different similarity matching methods. The large-scale crawl of the Alexa top million websites allowed the generation of about 190,000 single rules for nearly 129,000 different domains.
The Political Complexity of Coastal Flood Risk Reduction: Lessons for Climate Adaptation Public Works in the U.S.

Coastal climate adaptation public works, such as storm surge barriers and levees, are central elements of several current proposals to limit damages from coastal storms and sea‐level rise in the United States. Academic analysis of these public works projects is dominated by technocratic and engineering‐driven frameworks. However, social conflict, laws, political incentives, governance structures, and other political factors have played pivotal roles in determining the fate of government‐led coastal flood risk reduction efforts. Here, we review the ways in which politics has enabled or hindered the conception, design, and implementation of coastal risk reduction projects in the U.S. We draw from the literature in natural hazards, infrastructure, political science, and climate adaptation and give supporting examples. Overall, we find that (1) multiple floods are often needed to elicit earnest planning; (2) strong and continuous leadership from elected officials is necessary to advance projects; (3) stakeholder participation during the design stage has improved outcomes; (4) legal challenges to procedural and substantive shortcomings under environmental protection statutes present an enduring obstacle to implementing megastructure proposals.
Dataset of Georeferenced Dams in South America (DDSA)

Abstract. Dams and their reservoirs generate major impacts on society and the environment. In general, its relevance relies on facilitating the management of water resources for anthropogenic purposes. However, dams could also generate many potential adverse impacts related to safety, ecology or biodiversity. These factors, as well as the additional effects that climate change could cause in these infrastructures and their surrounding environment, highlight the importance of dams and the necessity for their continuous monitoring and study. There are several studies examining dams both at regional and global scales; however, those that include the South America region focus mainly on the most renowned basins (primarily the Amazon basin), most likely due to the lack of records on the rest of the basins of the region. For this reason, a consistent database of georeferenced dams located in South America is presented: Dataset of Georeferenced Dams in South America (DDSA). It contains 1010 entries of dams with a combined reservoir volume of 1017 km 3 , and it is presented in the form of a list describing a total of 24 attributes that include the dams' names, characteristics, purposes and georeferenced locations. Also, hydrological information on the dams' catchments is also included: catchment area, mean precipitation, mean near-surface temperature, mean potential evapotranspiration, mean runoff, catchment population, catchment equipped area for irrigation, aridity index, residence time and degree of regulation. Information was obtained from public records, governments records, existing international databases and extensive internet research. Each register was validated individually and geolocated using public-access online map browsers, and then, hydrological and additional information was derived from a hydrological model computed using the HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) dataset. With this database, we expect to contribute to the development of new research in this region. The database is publicly available at https://doi.org/10.5281/zenodo.4315647 (Paredes-Beltran et al., 2020).
Modelo Neural NARX Aplicado à Inferência Dos Sinais De Controle De Dosagem De Coagulantes Principal E Auxiliar No Processo De Tratamento De Água Por Filtração Direta

Abstract – Considering the importance of the control chemical c oagulation for the water treatment process by direc t filtration, was developed a NARX neural model for i nference of the control signals of the main coagula nt dosage and auxiliary, through of the measured values for turbidity and pH of untreated water and coagulated. This model coul d replace the instrumentation and hardware conventionally used fo r m nitoring and control of the chemical coagulatio n, contributing for the viability of projects in water treatment plants.
JEL Classification : H 2 Keywords : Wealth Taxation , Capital taxation , inequality

This paper evaluates proposals for an annual wealth tax. While a dozen OECD countries levied wealth taxes in the recent past, now only three retain them, with only Switzerland raising a comparable fraction of revenue as recent proposals for a US wealth tax. Studies of these taxes sometimes, but not always, find a substantial behavioral response, including of saving, portfolio change, avoidance, and evasion, and the impact depends crucially on design features, especially the broadness of the base and enforcement provisions. Because the US proposals are very different from any previous wealth tax, experience in other countries offers only broad lessons, but we can gain insights from closely related taxes, such as the property and the estate tax, and from optimal tax analysis of the role of wealth taxation. JEL Classification: H2
Predicting RNA-seq data using genetic algorithm and ensemble classification algorithms

Malaria parasites accept uncertain, inconsistent life span breeding through vectors of mosquitoes stratospheres. Thousands of different transcriptome parasites exist. A prevalent ribonucleic acid sequencing (RNA-seq) technique for gene expression has brought about enhanced identifications of genetical queries. Computation of RNA-seq gene expression data transcripts requires enhancements using analytical machine learning procedures. Numerous learning approaches have been adopted for analyzing and enhancing the performance of biological data and machines. In this study, a genetic algorithm dimensionality reduction technique is proposed to fetch relevant information from a huge dimensional RNA-seq dataset, and classification uses Ensemble classification algorithms. The experiment is performed using a mosquito Anopheles gambiae dataset with a classification accuracy of 81.7% and 88.3%.
Application of the Alkaline-Digestion-HPLC Method to the Rapid Determination of Polyhydroxyalkanoate in Activated Sludge

A new method for analyzing polyhydroxyalkanoate (PHA) in activated sludge based on alkaline digestion followed by high-performance liquid chromatography (HPLC) was evaluated. The effects of the concentration of NaOH, reaction time, and reaction temperature were examined using activatedsludge samples containing PHA and commercially purchased PHA. To determine PHA concentrations, 0.5 mL 2 N NaOH was added to 1 mL activated-sludge mixed liquor, and the resulting mixture was heated at 105°C in a drying oven for 1 h to convert 3-hydroxybutyrate units into 2-butenoate and 3-hydroxyvalerate units into 2-pentenoate. The mixture was then acidified with 0.5 mL of 2 N H2SO4, and the solids were removed and subsequently analyzed by HPLC. The present method gave results consistent with those obtained by the conventional method of methanolysis followed by gas chromatography. The present method can facilitate investigations of PHA in activated sludge by reducing the time and labor required for analysis and by eliminating the use of organic solvents.