cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Impact of Data Quality on the Performance Evaluation of Large-Scale PV Plants
Creators: name: Luchetta Martins, G.
name: Koumpli, E.
name: Southern, S.
name: Panoui, A.
name: Muller, J.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1311-1315
description: Quality assurance is essential to achieve reliable performance analysis on large-scale PV monitoring data. In this paper, two novel methods are demonstrated for the quality control (QC) of irradiance data. QCs are applied on four large-scale PV power plants ( >30MWpeak), both tracker and fixed tilt types. Faults distribution and energy impact are shown to depend highly on-site type and location, with tracker stows and deviations by nearby reflections and dew being the most common issues for tracker and fixed tilt sites, respectively. A comparative analysis between raw and QC Performance Ratio (PR) is performed. The impact of data quality can be major, on both performance analysis and PR calculations. Daily PR deviations can go up to -12.5%, strongly affecting the performance analysis of the power plant, carried out on a daily basis. Significant monthly deviations of up to -3.3% are also found, with the potential of causing contractual liabilities and affecting stakeholders’ expectations.
Auf dem Weg zu einem nicht-öffentlichrechtlichen Deliktenrecht?
Creators: name: Bianchi, Herman
Publisher: name: Concilium
Year: 1970

description: Concilium, Bd. 11 Nr. 8/9 (1975): Concilium: Internationale Zeitschrift für Theologie, Band 11, Heft 8/9
Estimating Global Horizontal Irradiance at the Urban Level: a Sensitivity Analysis Using Different Digital Surface Models
Creators: name: Amaro E Silva, R.
name: Blanc, P.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1316-1319
description: Digital Surface Models are key for integrating urban-level shadowing in PV modelling. Despite the increasing number of such products and their diversity in terms of acquisition method and post-processing, current state-of-the-art research on solar resource and PV modelling in urban environments consider only a single DSM and disregard the uncertainty associated to the choice of such product. Here, seven different DSMs, with different levels of detail and accuracy were used to calculate the incident global horizontal irradiance with 15-min resolution for the city of Nantes, France. First, an exploratory analysis across three DSMs is done to illustrate the visual and practical differences between products. The root-mean-squared deviation between DSM pairs was also quantified regarding the surface altitude (0.6 to 3 m) and incident solar irradiance (32 to 70%, relative to the annual mean daytime value). Lastly, the uncertainty for annual irradiance is estimated to be 1.0-24.9% for rooftops and 5.8-44.8% for ground level surfaces, while it is highlighted that uncertainty can be considerably higher for given short time periods with clear-sky conditions.
Family protection orders in the Pacific region - Report from a symposium held in December 2021
Creators: name: (:Unkn) Unknown
Publisher: name: Canberra, ACT: Dept. of Pacific Affairs, Coral Bell School of Asia Pacific Affairs, The Australian National University
Year: 2023
Subjects: Gender
Domestic Violence
Family Protection Orders
Violence against women and Children
Papua New Guinea
Solomon Islands
Vanuatu
Tonga
Pacific
Samoa
Fiji

description: On 9 December 2021, the Pacific Community (SPC) and The Australian National University (ANU) co-convened a virtual ‘Symposium on family protection orders in the Pacific region’. The symposium brought together expertise from across the region, including from the Cook Islands, Fiji, Samoa, Palau, Papua New Guinea (PNG), Solomon Islands, Timor Leste, Tonga, Tuvalu and Vanuatu. The chapters of this publication are based on the presentations that were given at the event, and provide insightful accounts of how family protection orders and domestic and family violence (DFV) response systems are working across the Pacific. The speakers contributed a rich array of expert perspectives and included lawyers, judicial officers, academics, police officers, government officials, and representatives from specialist DFV services, regional bodies and aid projects.
Short-Term Solar Irradiance Forecasting Based on the Integration of Numeric Weather Prediction and Deep Learning
Creators: name: Navid, S.
name: Fuzhan, N.
name: Ramanunni, M.
name: Eicker, U.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1320-1324
description: Accurate short-term solar irradiance forecasts would prove valuable for optimal management and effective operational control of microgrids integrated with the conventional power grid. Because of the intermittent characteristics of renewable energy resources, predicting global solar irradiance is a challenging task. The current forecasting models mainly use historical data, while the unexpected behavior of other environmental indicators, such as cloud movement, is not considered. Therefore, over a short period of time, the present-day forecast results are found to be unreliable, especially for control purposes requiring higher accuracy. To tackle this issue, the article proposes an integrated model based on the hybridization of the numeric weather prediction (NWP) model along with long shortterm memory (LSTM) in the day-ahead (24 hours) horizon. Downward shortwave and longwave solar radiation features are selected from the NWP forecast output to be integrated with the LSTM model. The results show that hybridizing models could significantly improve the forecasting accuracy in overcast and scattered climate conditions by reducing the root mean squared error of the single LSTM model's prediction results from 197.19 and 192.81 to 62.96 and 72.01, respectively.
Probing the effects of a thermonuclear X-ray burst on the neutron star accretion flow with NuSTAR
Creators: name: Degenaar, N.
name: Koljonen, K. I. I.
name: Chakrabarty, D.
name: Kara, E.
name: Altamirano, D.
name: Miller, J. M.
name: Fabian, A. C.
Publisher: name: arXiv
Year: 2016
Subjects: subject: High Energy Astrophysical Phenomena (astro-ph.HE)
subject: FOS: Physical sciences

description: Observational evidence has been accumulating that thermonuclear X-ray bursts ignited on the surface of neutron stars influence the surrounding accretion flow. Here, we exploit the excellent sensitivity of NuSTAR up to 79 keV to analyze the impact of an X-ray burst on the accretion emission of the neutron star LMXB 4U 1608-52. The ~200 s long X-ray burst occurred during a hard X-ray spectral state, and had a peak intensity of ~30-50 per cent of the Eddington limit with no signs of photospheric radius expansion. Spectral analysis suggests that the accretion emission was enhanced up to a factor of ~5 during the X-ray burst. We also applied a linear unsupervised decomposition method, namely non-negative matrix factorization (NMF), to study this X-ray burst. We find that the NMF performs well in characterizing the evolution of the burst emission and is a promising technique to study changes in the underlying accretion emission in more detail than is possible through conventional spectral fitting. For the burst of 4U 1608-52, the NMF suggests a possible softening of the accretion spectrum during the X-ray burst, which could potentially be ascribed to cooling of a corona. Finally, we report a small (~3 per cent) but significant rise in the accretion emission ~0.5 h before the X-ray burst, although it is unclear whether this was related to the X-ray burst ignition.
description: 10 pages, 10 figures, 1 table, to appear in MNRAS
The Influence of Service Quality on Customer Satisfaction: the case of ATM Service in Commercial Bank of Ethiopia, Addis Ababa
Creators: name: Yidnekachew, Girma
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2019

description: Service offering channels in banking sector has emerged on scene with a variety of forms such as internet banking, mobile banking, and ATM. Mature competition and global finance system has been forced to investigate the significance of customer satisfaction. This study was set to assess customers' satisfaction in ATM service the case of Commercial Bank of Ethiopia using SERVPERF model. A self-administered questionnaire was used to collect primary data from 385 valid respondents who are customers of CBE, using convenient sampling technique. Data was analyzed using SPSS's for frequencies, percentages, mean scores, Cronbach alpha, Pearson's linear correlation, and regression analysis. The study was based on the objective to assess on Automated Teller Machines service quality and customer satisfaction in Commercial Bank of Ethiopia. The finding revealed that all the service quality dimensions are significantly and positively associated with the overall customer satisfaction. Besides, tangibility, reliability, responsiveness, empathy and assurance are highlighted as significant predictors and key factors in determining the customer satisfaction. But reliability was found as the most influential predictor of customer satisfaction. The researcher recommended that in order to ensure customer satisfaction CBE should maintain the performance on all the dimensions of ATM service quality.
Strong-Field Resonant Dynamics in Semiconductors
Creators: name: Wismer, Michael S.
name: Kruchinin, Stanislav Yu.
name: Ciappina, Marcelo
name: Stockman, Mark I.
name: Yakovlev, Vladislav S.
Publisher: name: arXiv
Year: 2015
Subjects: subject: Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
subject: Other Condensed Matter (cond-mat.other)
subject: FOS: Physical sciences

description: We predict that a direct bandgap semiconductor (GaAs) resonantly excited by a strong ultrashort laser pulse exhibits a novel regime: kicked anharmonic Rabi oscillations (KARO). In this regime, Rabi oscillations are strongly coupled to intraband motion, and interband transitions mainly take place during short times when electrons pass near the Brillouin zone center where electron populations undergo very rapid changes. Asymmetry of the residual population distribution induces an electric current controlled by the carrier-envelope phase. The predicted effects are experimentally observable using photoemission and terahertz spectroscopies.
Geometrically induced complex tunnelings for ultracold atoms carrying orbital angular momentum
Creators: name: Polo, J.
name: Mompart, J.
name: Ahufinger, V.
Publisher: name: arXiv
Year: 2016
Subjects: subject: Quantum Gases (cond-mat.quant-gas)
subject: FOS: Physical sciences

description: We investigate the dynamics of angular momentum states for a single ultracold atom trapped in two dimensional systems of sided coupled ring potentials. The symmetries of the system show that tunneling amplitudes between different ring states with variation of the winding number are complex. In particular, we demonstrate that in a triangular ring configuration the complex nature of the cross-couplings can be used to geometrically engineer spatial dark states to manipulate the transport of orbital angular momentum states via quantum interference.
Day-Ahead Photovoltaic Production Forecasting Using XGBoost and Post-Calibration Modeling
Creators: name: Theocharides, S.
name: Lopez Lorente, J.
name: Makrides, G.
name: Georghiou, G.E.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1289-1294
description: This work proposes a methodology for accurate day-ahead photovoltaic (PV) production forecasting models that utilized machine learning techniques for forecasting and clustering. Specifically, the core element of the proposed method is a power output predictive model (trained in an extreme supervised learning regime) that incorporates an output post-processing step for calibrating the forecasts against cluster-based irradiance profiles. The initial forecasting model was developed using an extreme gradient boosting (XGBoost) algorithm, while the clustering was performed using the TSClust algorithm and the post-calibration using extreme learning machines (ELM). The TSClust indicated 5 types of clusters that were used to assign the type of cluster to each daily solar irradiance profile. The ELM used as input parameters the type of cluster and the output of the XGBoost model (power forecast) to improve the quality and accuracy of the PV production forecasting. The proposed methodology demonstrated absolute improvements of up to 2% compared to forecasting without post-calibration.
ENHANCED MULTIPLE DENSE LAYER EFFICIENTNET
Creators: name: Mohan, Aswathy
Publisher: name: Purdue University Graduate School
Year: 2024
Subjects: classificationCode: 460304
subject: Computer vision
classificationCode: 461104
subject: Neural networks
classificationCode: 460306
subject: Image processing

description: In the dynamic and ever-evolving landscape of Artificial Intelligence (AI), the domain of deep learning has emerged as a pivotal force, propelling advancements across a broad spectrum of applications, notably in the intricate field of image classification. Image classification, a critical task that involves categorizing images into predefined classes, serves as the backbone for numerous cutting-edge technologies, including but not limited to, automated surveillance, facial recognition systems, and advanced diagnostics in healthcare. Despite the significant strides made in the area, the quest for models that not only excel in accuracy but also demonstrate robust generalization across varied datasets, and maintain resilience against the pitfalls of overfitting, remains a formidable challenge.EfficientNetB0, a model celebrated for its optimized balance between computational efficiency and accuracy, stands at the forefront of solutions addressing these challenges. However, the nuanced complexities of datasets such as CIFAR-10, characterized by its diverse array of images spanning ten distinct categories, call for specialized adaptations to harness the full potential of such sophisticated architectures. In response, this thesis introduces an optimized version of the EffciientNetB0 architecture, meticulously enhanced with strategic architectural modifications, including the incorporation of an additional Dense layer endowed with 512 units and the strategic use of Dropout regularization. These adjustments are designed to amplify the model's capacity for learning and interpreting complex patterns inherent in the data.Complimenting these architectural refinements, a nuanced two-phase training methodology is also adopted in the proposed model. This approach commences with the initial phase of training where the base model's pre-trained weights are frozen, thus leveraging the power of transfer learning to secure a solid foundational understanding. The subsequent phase of fine-tuning, characterized by the selective unfreezing of layers, meticulously calibrates the model to the intricacies of the CIFAR-10 dataset. This is further bolstered by the implementation of adaptive learning rate adjustments, ensuring the model’s training process is both efficient and responsive to the nuances of the learning curve.
Kirchliche Disziplin und individuelles Leben der Gläubigen
Creators: name: Anastasiu, Iōannēs E.
Publisher: name: Concilium
Year: 1970

description: Concilium, Bd. 11 Nr. 8/9 (1975): Concilium: Internationale Zeitschrift für Theologie, Band 11, Heft 8/9
Evaluation of Irradiance Decomposition and Transposition Models for a Nordic Climate
Creators: name: Martinsen, D.C.
name: Øgaard, M.B.
name: Nygård, M.M.
name: Syre Wiig, M.
name: Di Sabatino, M.
name: Marstein, E.S.
name: Riise, H.N.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1295-1303
description: Cost reductions and technological advancements continue to increase profitability of photovoltaics (PV) also in the northern parts of the world. In the planning of PV systems, estimation of accumulated energy generation throughout the system lifetime is essential for estimating levelized cost of electricity (LCOE) and the financial return for the system. Robust estimations of energy output require high quality solar resource data and accurate modeling of the irradiance in the plane of the PV modules. However, existing transposition and decomposition models for estimating the irradiance in tilted planes are not widely validated for locations at high latitude. In this work, the performance of a selection of models for decomposition and transposition of irradiance was evaluated at three locations in Norway. The impact of cloud conditions and season on model performance was also investigated. The results show large variation in model performance for the three studied locations, and the model performance was found to be affected by both season and cloud cover. The decomposition models were found to yield larger uncertainties compared to the transposition models. For the decomposition models, the rRMSD ranged from 17.9% to 71.4%, and for transposition models the range was from 6.2% to 12.6%.
CV-QKD with Gaussian and non-Gaussian Entangled States over Satellite-based Channels
Creators: name: Hosseinidehaj, Nedasadat
name: Malaney, Robert
Publisher: name: arXiv
Year: 2016
Subjects: subject: Quantum Physics (quant-ph)
subject: FOS: Physical sciences

description: In this work we investigate the effectiveness of continuous-variable (CV) entangled states, transferred through high-loss atmospheric channels, as a means of viable quantum key distribution (QKD) between terrestrial stations and low-Earth orbit (LEO) satellites. In particular, we investigate the role played by the Gaussian CV states as compared to non-Gaussian states. We find that beam-wandering induced atmospheric losses lead to QKD performance levels that are in general quite different from those found in fixed-attenuation channels. For example, circumstances can be found where no QKD is viable at some fixed loss in fiber but is viable at the same mean loss in fading channels. We also find that, in some circumstances, the QKD relative performance of Gaussian and non-Gaussian states can in atmospheric channels be the reverse of that found in fixed-attenuation channels. These findings show that the nature of the atmospheric channel can have a large impact on the QKD performance. Our results should prove useful for emerging global quantum communications that use LEO satellites as communication relays.
description: 7 pages, 5 figures
Polit-Posse MdB Prof. Dr. E. Schuchardt: „Kann Geld Urheberrecht brechen?“
Creators: name: Schuchardt, Erika
Publisher: name: [k.A.]
Year: 2021
Subjects: subject: Dewey Decimal Classification::700 | Künste, Bildende Kunst allgemein::740 | Zeichnung, Kunsthandwerk

description: Landes-Jubiläums-Buch 50 Jahre Karika-Touren. 3 Jubiläums-Eröffnungs-Ausstellungen. BS. Land. Bund. Zu 50 Jahren Niedersachsen 1946-1996
Improving Site Shading Assessment from Digital Surface Models with Onsite LiDAR Measurements
Creators: name: Mira, D.A.
name: Bartholomäus, M.
name: Poessl, S.
name: Hass, T.K.
name: Poulsen, P.B.
name: A. Dos Reis Benatto, G.
name: Spataru, S.V.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1304-1310
description: Product integrated photovoltaic (PIPV) systems, can be severely impacted by shading in the surroundings as their collector area is typically small. To ensure the proper functioning of these devices, methodologies to estimate solar irradiance and near shading accurately and efficiently in built up locations are needed. Digital Surface Models (DSM) have proven to be a good alternative to estimate solar irradiance on building surfaces and urban areas. However, high-accuracy DSM are scarce, with limited availability and tend to show the maximum elevation of the obstructions elements disregarding their real shape. We propose a methodology with onsite LiDAR measurements to improve the accuracy to which the solar irradiance can be estimated in urban environments. This methodology produces horizon matrices which can reduce the estimated irradiance’s RMSE by 25-40% compared to fisheye sky imaging methodologies, and by 45-75% to the ones obtained with low-resolution DSMs. However, at locations with low shading profiles the differences are negligible.
Effect of intellectual capital efficiency on financial performance: Evidence from Ethiopian commercial banks
Creators: name: Henok, Tefera
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2018

description: This paper adopted Pulic (1998) model known as Value Added Intellectual Coefficient™ (VAIC™) to measure the effect of Intellectual Capital (IC) efficiency on the Ethiopian commercial banks financial performance of as measured on return on asset (ROA). Purposively sampled 15 commercial banks, which enable to answer research questions by focusing on particular characteristics of a population that are of interest, 75 observations for 5 years data from 2013 to 2017 was taken. VAIC and its three components, human capital efficiency (HCE), capital employed efficiency (CEE) and structural capital efficiency (SCE) along with the control variable firm size (SIZE), constructed from the annual financial statements. The assumptions needed to be fulfilled for OLS were tested; the residual was found homoscedastic, free of multicollinearity, free of autocorrelation and normally distributed. Regression models are used to test the hypotheses of the study where the results show that there was positive significant influence of IC as measured by VAIC on financial performance. Among the component of VAIC, the results showed that human capital efficiency (HCE) and structural capital efficiency (SCE) positively influence the financial performance of Ethiopian commercial banks while capital employed efficiency (CEE) has statistically insignificant relationship with the financial performance as measured by ROA. The study also provided evidence for existence of negative significant relationship between firm size and ROA. Based on the findings, recommended that, bank managers to establish separate department for proper record of all IC components and policy makers to take in to account human capital and structural capital while setting up policies and procedures so as not to negatively affect the financial performance.
Assessment of Health Commodities Inventory Management Practices and Challenges: the Case of Zewditu Memorial Hospital, Addis Ababa, Ethiopia
Creators: name: Semahegn, Azeb
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2017

description: Health commodities inventory management practices provide current information on quantities of health commodities consumed as well as enables to accurately estimate requirements for future use. A poorly functioning health commodities inventory management can lead to frequent stock outs leading to services interruptions or overstock. The objective of the study was to assess the health commodities inventory management practice of the Zewditu Memorial Hospital using primary data that was collected through a semi-structured questionnaire, observation check list & interview. Out of the 91 questionnaires that were distributed to the purposively elected employees of the hospital, 77 (84.6%) of them were collected back and used for the analysis .Besides 4 hospital stores were visited & all the required information were included in this study .Data was analyzed using descriptive statics . The study found that ZMH health commodities to be long-term agreements between the hospital and its suppliers, maintain proper store management the majority of the store managers had adequate knowledge how to store and practiced health commodities and they had also a positive attitude towards the importance of appropriate storage of commodities, obsolete, expired, or damaged inventories properly identified and segregated, inventory records reconciled to advantage reports on a regular basis and management have review the reconciliation of physical inventory counts to the inventory records applied at ZMH but ,uses automatic stock tracking and adequate detailed written inventory instructions and procedures exist, uses Enterprise Resource Planning system, maintains a data base for all suppliers, uses Just In Time stock control system and an integrated information sharing system were not applicable at ZMH. Finally from the study it can be concluded that the main challenges of the hospital in managing inventory are: lack of modern technologies, insufficient funding, lack of inventory management training, the length of bureaucratic processes in the procurement system and stock out of health commodities. In general the consequences of the above were occurred high level of stock out which might have leaded to services interruptions at ZMH health commodities. Based on these findings, the study recommends that government allocates more funds to public hospitals to be invested in modern information technologies because this will lead to increased information sharing, reduction of costs and improved quality of health services. In addition, inventory management training should be given to improve the availability and the quality of services in ZMH. Key words: Health commodities inventory management, stores, medicines, medical supplies medical equipments, laboratory commodities
Hybrid Numerical Ensemble Method and Comparative Study for Solar Irradiance Forecasting
Creators: name: Thaker, J.
name: Höller, R.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1276-1284
description: Renewable energy sources like solar energy and wind power, which are not available on-demand must be stored or used instantly. The solar irradiance is strongly dependent on unpredictable atmospheric conditions. Thus, the performance and the accuracy of solar forecasting model is highly influenced by the complex and stochastic atmospheric conditions. The forecasting challenges of solar energy augment with increasing deployment of photovoltaic (PV) system into electrical grids. As the global horizontal irradiance (GHI) is the most important key input in PV power prediction systems, increasing effort is spent on research on forecasting of GHI as a basis for corresponding power forecasts. The proposed approach in this paper is based on forecast of the global numerical weather prediction (NWP) model Global Forecast System (GFS). The proposed model uses day-type classification benchmark based on hourly vectors generated using clear sky index and hybrid numerical formulation. A novel GHI prediction system using input data from an GFS and two levels ensemble is presented and evaluated by providing day ahead forecasts with an hourly time resolution. The methodology applies various machine learning (ML) and recurrent neural network (RNN) models along with a parametric model as the basis to build an ensemble model. The focus of this paper is the comparison of the capability and performance of developed models and build a hybrid ensemble model for producing reliable day-ahead forecast horizon and an hourly resolution of GHI. The detailed study and analysis of probabilistic time series forecast is presented. The reliability and the sharpness of the forecast models is evaluated by using various skill scores of probabilistic forecasts. Results show that the hourly irradiance classification approach reduces the forecasting error by a considerable margin and the optimized hybrid ensemble model outperforms all other models. These findings also emphasize that all the models perform better than GFS.
Single-phase, Five-level Inverter with SPWM-Based Neutral Point Voltage Balancing Scheme
Creators: name: Dmytro Kondratenko
name: Arkadiusz Lewicki
name: Charles Odeh
Publisher: name: Gdańsk University of Technology
Year: 2022
Subjects: subject: CAPACITOR VOLTAGE BALANCING
subject: PULSE WIDTH MODULATION (PWM)
subject: T-TYPE INVERTER
subject: VOLTAGE SOURCE INVERTER (VSI)

description: Multilevel inverter topologies provide several advantages over two-level inverter configuration. These benefits are the reason for the growing interest in multilevel topologies among research society. One of the most popular topological concepts (diode and active switch clamping) requires neutral-point potential balancing due to series-connected capacitor banks across the input dc link in such derived inverter configurations. This paper presents a Sinusoidal PWM (SPWM) scheme that ensures balanced and reduced input capacitor voltages' variations in single-phase T-type inverter. Comparison analyses with existing carrier-based pulse-width modulation methods are provided. Simulation results are provided which showcase the effectiveness of the control approach. Experimental validation of these results was provided with a five-level single-phase T-type VSI; that supplies single-phase RL load.
How Does the Use of Satellite-Derived Insolation Data Impact the Accuracy of Performance Ratio Estimates?
Creators: name: Ozkalay, E.
name: Virtuani, A.
name: Fairbrother, A.
name: Skoczek, A.
name: Friesen, G.
name: Ballif, C.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1285-1288
description: PV systems' short- and long-term performances are often analyzed using satellite-derived insolation data. Despite the fact that higher uncertainties are associated with satellite-derived insolation data, no studies have been conducted to quantify the impact on the assessment of the PV plant's performance ratio (PR), used to judge the overall health status of a plant. In order to evaluate the performance of a PV system accurately, the uncertainty contribution needs to be carefully computed. In this work, we quantify: (1) the accuracy of two satellite-derived insolation data-set (opensource and paid service) with respect to the irradiance ground measurement obtained by properly maintained sensors; and (2) their effect on the uncertainty of the plant’s PR computed using satellite-derived insolation with different temporal resolutions. The uncertainty of PR computed using insolation data from a well-maintained and regularly recalibrated pyranometer computed as 3.6% (k=2), and it assumed constant for all temporal resolutions (daily, monthly and yearly) as a conservative assumption. The statistical evaluation shows that monthly and yearly PR values, which have an uncertainty of less than 5%, can be obtained using satellite-derived insolation data without having to deal with regular calibration and maintenance of an on-site pyranometer. We showed that depending on the quality of satellite-derived data and temporal resolution, uncertainty of PR differs. The PR computed using paid-service satellite-derived data has approximately a 1.7% lower uncertainty (k=2) than the PR computed using open-source satellite-derived data for the temporal resolutions considered (day and month), with the exception of the yearly resolution (for which this value is 0.6% lower).
The dust content of the most metal-poor star-forming galaxies
Creators: name: Schneider, Raffaella
name: Hunt, Leslie
name: Valiante, Rosa
Publisher: name: arXiv
Year: 2016
Subjects: subject: Astrophysics of Galaxies (astro-ph.GA)
subject: FOS: Physical sciences

description: Although dust content is usually assumed to depend uniquely on metallicity, recent observations of two extremely metal-poor dwarf galaxies have suggested that this may not always be true. At a similar oxygen abundance of ~ 3% Zsun, the dust-to-gas and dust-to-stellar mass ratios in SBS 0335-052 and IZw 18 differ by a factor 40-70 according to including molecular gas or excluding it. Here we investigate a possible reason for this dramatic difference through models based on a semi-analytical formulation of chemical evolution including dust. Results suggest that the greater dust mass in SBS 0335-052 is due to the more efficient grain growth allowed by the high density in the cold interstellar medium (ISM), observationally inferred to be almost 20 times higher than in IZw 18. Our models are able to explain the difference in dust masses, suggesting that efficient dust formation and dust content in galaxies, including those with the highest measured redshifts, depend sensitively on the ISM density, rather than only on metallicity.
description: 10 pages, 5 figures, to appear in MNRAS
Improved Models for Nowcasting Sunshine Number
Creators: name: Paulescu, M.
name: Stefu, N.
name: Dughir, C.
name: Sabadus, A.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1264-1267
description: This study deals with the performance in intra-hour forecasting of the relative position of the Sun and clouds. Sunshine number SSN, a binary quantifier showing if the Sun shines or not, is used as a measure for the Sun position with respect to clouds. The quality of SSN forecasts issued by statistical, (ARIMA modeling of various radiometric time-series) and physics-based models (sky-imagery analysis) is assessed. Irrespective the forecasting procedure, the overall results show a low percentage of SSN forecasts misclassified. Total misclassification increases with increasing the forecast horizon and with the increase in variability of the state-of-the-sky. At the transition from a state to another, the different statistical models experience a different inertia. The level of accuracy in the SSN forecasting by sky-imagery is strongly dependent on the procedure applied for cloud displacement estimation.
A Computationally Light Data-driven Alternative to Cloud-Motion Prediction for PV Forecasting
Creators: name: Carrillo Rangel, R.E.
name: Alet, P.J.
name: Müller, S.
name: Remund, J.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1268-1271
description: In this paper we compare a state-of-the-art cloud-motion tracking solution against a data-driven solution for photovoltaic (PV) power production to provide insights into their performance drivers. The solutions are MeteoTest’s CloudMove, based on cloud-motion tracking from satellite images, and CSEM’s data-driven solution based on graph machine learning forecasting models that use only past PV production data from a network of PV systems. The study compared the two approaches in terms of accuracy in different scenarios for a forecasting horizon of up to six hours ahead, with a resolution of 15 minutes, on a dataset of 21 days and 18 locations in Switzerland. The days and locations were selected as a representative sample of the whole range of different conditions in terms of seasons, weather conditions, terrain, and distance to other instrumented sites. Over the whole benchmarking set, CSEM’s data-driven technique yields a lower normalized root-mean-square error than the cloud-motion tracking method for forecasting horizons above one hour, though the error spread is larger with CSEM’s data-driven solution. Regarding computational load, the data-driven methods can accelerate the computation of forecasts by a factor 100, after an initial training, thus offering a viable alternative to satellite-based cloud-tracking methods.
Spin-Orbital Entangled Excitonic Insulators in $(t_{2g})^4$ Correlated Electron Systems
Creators: name: Sato, Toshihiro
name: Shirakawa, Tomonori
name: Yunoki, Seiji
Publisher: name: arXiv
Year: 2016
Subjects: subject: Strongly Correlated Electrons (cond-mat.str-el)
subject: FOS: Physical sciences

description: We employ the multi-orbital dynamical mean-field theory to examine the ground state of a three-orbital Hubbard model with a relativistic spin-orbit coupling (SOC) at four electrons per site. We demonstrate that the interplay between the strong electron correlations and the SOC induces a Van Vleck-type nonmagnetic insulator and its magnetic exciton condensation. We also find in the moderate electron correlation regime that the SOC induces another type of a nonmagnetic excitonic insulator, in addition to a relativistic band insulator. The characteristic features among these insulators are manifested in the momentum resolved single-particle excitations, thus accessible by angle-resolved photoemission spectroscopy experiments.
description: 5 pages, 3 figures
Relative Equilibria in the Spherical, Finite Density 3-Body Problem
Creators: name: Scheeres, D. J.
Publisher: name: arXiv
Year: 2016
Subjects: subject: Dynamical Systems (math.DS)
subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: Classical Physics (physics.class-ph)
subject: FOS: Mathematics
subject: FOS: Physical sciences

description: The relative equilibria for the spherical, finite density 3 body problem are identified. Specifically, there are 28 distinct relative equilibria in this problem which include the classical 5 relative equilibria for the point-mass 3-body problem. None of the identified relative equilibria exist or are stable over all values of angular momentum. The stability and bifurcation pathways of these relative equilibria are mapped out as the angular momentum of the system is increased. This is done under the assumption that they have equal and constant densities and that the entire system rotates about its maximum moment of inertia. The transition to finite density greatly increases the number of relative equilibria in the 3-body problem and ensures that minimum energy configurations exist for all values of angular momentum.
description: Accepted for publication in the Journal of Nonlinear Science
PV Very Short-Term Power Forecasting Method Based on Cloud Monitoring Data
Creators: name: Esteves, J.
name: Pestana, R.
name: Cao, Y.
name: Pinho Da Silva, N.
name: Wang, Z.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1272-1275
description: In the wake of climate change, more attention is being focused on green energy production. Renewable energy resources play an important role in the goal of reducing greenhouse gas emissions as they allow the reduction of fossil fuel use. One method to produce energy in a sustainable way is to make use of photovoltaic (PV) panels, which convert the solar energy directly into electricity. Even though the deployment of solar energy production contributes to the decarbonisation of the energy system, it also has its obstacles. The power that can be generated by PV units is proportional to the amount of irradiation reaching the PV panels, which introduces high levels of uncertainty and volatility. In this work, a PV power forecast method based on cloud monitoring data is presented to tackle the very short-term forecast horizon (up to two hours-ahead). The developed methodology uses an all-sky imager (ASI) installed in a solar PV power plant located in the South of Portugal.
Assessment of pharmaceuticals Distribution System: the Case of Pharmaceuticals Fund and Supply Agency (PFSA)
Creators: name: Teketel, Adimasu
Publisher: name: National Academic Digital Repository of Ethiopia
Year: 2017

description: Government of Ethiopia is focusing to avail pharmaceuticals at an affordable price,accessible to all citizens through pharmaceuticals fund and Supply agency.However the Ethiopian pharmaceuticals distribution system is constrained by weak distribution practices and weak fleet management. The objective of this studywas to assess the pharmaceuticals supply chain distribution system practices at PFSA.The study employed both quantitative and qualitative study approaches. Quantitative data was collected from 41 employees using self-administeredquestionnaires, whereas, interview questions were also used to collect qualitative data from the two directors and 31 Drivers.Descriptive data analysis method through the use of Statistical packages for social science (SPSS) version 20 software was used to analyze the data. Findings of the study showed that most of the employees perceived the following;warehousing and storage are moderately practiced however computerized system for inventory control to pick products was not fully implemented in the warehouses, availability of mechanical machines is very low. Location of some warehouses was not comfortable to load pharmaceuticals. They also agreed that fleet management of the agency has the following problems: global positioning system (GPS) was not in place, volume of the vehicles is not known,there is lowcoordination withreceiving health facilities. During transportation, pharmaceuticals were managed by drivers. Delivery document prepared as soon as they comes from hubs and health facilities, however there is limitations in that documents were not prepared considering to pick all products from a single warehouse. The study recommends that agency shall fully implement computerized system and use of mechanical machines in the warehouses. To control vehicles, PFSA shall apply GPS andperform volume determination for each vehicle. It is also recommended pharmacy professional shall handle when transporting pharmaceuticals. Over all, the entire agency is expected to work coordinatelywith receiving health facilities. Key words; distribution practices' ' warehousing and storage ' 'fleet management' Communication system
Is the “average Pigouvian tax” robust to the size of the group of polluters?
Creators: name: Sarr, Hamet
name: Bchir, Mohamed Ali
name: Cochard, François
name: Rozan, Anne
name: Sarr, Hamet
name: Bchir, Mohamed Ali
name: Cochard, François
name: Rozan, Anne
Publisher: name: Unknown
Year: 2021
Subjects: subject: Environmental Economics and Policy
subject: Nonpoint source pollution
subject: Ambient-based taxes
subject: Cooperation
subject: Size effect
subject: sucker’s payoff

description: We study the “average Pigouvian tax” (APT), an ambient-based policy instrument that requires polluters to cooperate to achieve the social optimum. In this paper, we are interested in the group size variation and its effect of the APT efficiency. Indeed, in the field, the implementation of the instrument will face group sizes that can vary from a few to a large number of farmers.We find that increasing the size of the group reduces cooperation among subjects, thereby reducing the efficiency of the instrument. We also show that when the sucker’s cost is lowered, the instrument can converge towards the social optimum.
Day-Ahead Forecasting of Solar Irradiance: KNN-Based Ensembles
Creators: name: Kamarianakis, Y.
name: Pantazis, Y.
name: Kalligiannaki, E.
name: Kotsovos, K.
name: Gereige, I.
name: Abdullah, M.
name: Tzavaras, A.
name: Katsaounis, T.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1248-1252
description: This work presents a novel, outlier-robust forecasting scheme, which is derived by combining two specifications. Specifically, a recently proposed time series KNN (TSKNN) ensemble procedure is combined with splinebased daily profiles (SDP), estimated via median regression. An experiment that mimics real-world implementation of an online system is performed, to evaluate day-ahead solar irradiance forecasts of the proposed method, dubbed TSKKNR0, versus TSKNN, SDP and the persistence model. Alternative specifications are evaluated with a new relative error metric which is outlier-robust. The analyzed measurements are collected at KAUST, Thuwal, Saudi Arabia for a full year, with 10-minute granularity.
Towards Understanding What Contributes to Forming an Opinion
Creators: name: Wang, Peng
name: Song, Jia
name: Huo, Jie
name: Hao, Rui
name: Wang, Xu-Ming
Publisher: name: arXiv
Year: 2016
Subjects: subject: Physics and Society (physics.soc-ph)
subject: FOS: Physical sciences

description: Opinion evolution mechanism can be captured by physics modeling approaches. In this context, a kinetic equation is established by defining a generalized displace (cognitive-level), a driving force and the related generalized potential, information quantity, altitude. It has been shown that the details of opinion evolution depends the type of the driving force, self-dominated driving or environment- dominated driving. In the former case, the participants can have their altitudes changed in the process of competition between the self-driving force and environment-driving force. In the latter case, all of the participants are pulled by the environment. Some regularity behind the dynamics of opinion is also revealed, for instance, the information entropy decays with time in a special way, etc. the results may help us to get some deep understandings to formation of a public opinion.
description: 11 gages, 15 Figures, research paper
Improved Adaptive Neuro-Fuzzy Inference Model for Photovoltaic Power Forecast
Creators: name: Habib, M.
name: Gram, A.
name: Wang, Q.
Publisher: name: WIP
Year: 2022
Subjects: PV Systems Engineering, Integrated/Applied PV
Solar Resource and Forecasting

description: 8th World Conference on Photovoltaic Energy Conversion; 1253-1260
description: Photovoltaic (PV) systems are recently the most used sustainable energy source to fit with the energy demand growth. Generally, batteries, as storage systems, are installed along with PV modules. When it comes to an optimal power management of PV/battery hybrid systems, the uncertain and intermittent behavior of PV power production can provoke some challenges, with which, the real-time operation of the hybrid system can be degraded, therefore, PV power forecast is highly needed. Datadriven models are became nowadays very efficient methods to build regression models for the purpose of PV power forecast. In this paper, Adaptive Neuro-Fuzzy Inference (ANFIS) is chosen as a data-driven technique, to build up forecasting models. Standard ANFIS, which uses only weather data, cannot avoid the confusing scenarios like PV modules covered by the snow in clear-sky days. This work proposes an improved ANFIS model taking historical generated power into account. The developed model is validated on a real case, using the PV system of the institute of energy system technologies in Offenburg. When adding the average of produced power of the last 72 hours as additional input, the model was able to follow the rapid changes in weather conditions and overcome the unexceptional situations like the problem of snow on the PV modules.