Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm

This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. The precise SOC estimation confirms the safety and reliability of EV. Nevertheless, SOC is influenced by numerous factors which cannot be measured directly. RFR is suitable for real-time SOC estimation due to its robustness to noise, overfitting issues and capacity to work with huge datasets. However, proper selection of RFR architecture and hyper-parameters combination remains a key issue to be explored. Hence, a differential search algorithm (DSA) is employed to search for the optimal values of trees and leaves in the RFR algorithm. DSA optimized RFR eliminates the utilization of the filter in data pre-processing steps and does not require a detailed understanding and knowledge about battery chemistry, rather only needs sensors to monitor battery voltage and current. The developed approach is validated at room temperature using two types of lithium-ion batteries under a pulse discharge test. In addition, the proposed model is verified under varying temperature settings under EV drive cycles. The experimental results demonstrate that the DSA optimized RFR algorithm achieves RMSE of 0.382% in the HPPC test using LiNMC battery. Besides, the proposed method obtains satisfactory outcomes in EV drive cycles, estimating MAE of 0.193% and 0.346% in DST and FUDS cycles, respectively, at 25°C.
Seed functional traits in cultivars of tall fescue (Schedonorus arundinaceus) are affected by the non-toxic fungal endophyte AR584

ABSTRACT Context. Tall fescue (Schedonorus arundinaceus) is one of the most important cultivated forage grasses in temperate regions but its association with some Epichloë fungal endophytes usually makes it unsuitable for livestock feeding due to toxic alkaloids. However, re-inoculation of plants with non-toxic endophytes can result in positive effects for livestock feeding. Aims. Assess the effects of the non-toxic AR584 endophyte on seed viability and germination in two tall fescue cultivars. Methods. The effects of AR584 endophyte (presence/absence) and tall fescue cultivar (INIA Aurora/Taita) were evaluated on seed viability and germination responses across a range of temperature and water availability regimes. Response to constant temperature and water availability was characterised by the thermal-time and hydro-time models, respectively. Key results. Under accelerated aging conditions, endophyte presence reduced seed viability in cultivar Taita. For both cultivars, endophyte-infected seeds showed a lower germination rate than endophyte-free seeds, except for INIA Aurora under low incubation temperatures. Also, endophyte-infected seeds in both cultivars displayed lower germination rates and final germination as the water potential was lowered. Conclusions. A strong cultivar-by-endophyte interaction for seed germination indicates the need to understand how specific cultivar-endophyte combinations best fit a given environmental condition, as defined by temperature and water availability. Implications. The information we present can be valuable not only for farmers who have to decide what to cultivate but also for seed companies that have to preserve seed quality.
Full-wave characterization of bi-dimensional cavities and its application to the design of waveguide filters and multiplexers

Modern communications systems impose stringent requirements on the equipment that operates at microwave frequency, especially in the case of wireless communications. The design of passive components for these applications is contingent upon the availability of accurate electromagnetic (EM) modeling tools that can efficiently handle the complex geometry of these components. Despite the widespread use of mesh-based general-purpose computer-aided engineering (CAE) tools to perform final design verifications, their application during the optimization process is limited. Optimum designs require a large number of simulations, which are computationally expensive when performed by general purpose tools. Instead, microwave designers prefer to employ faster software tools tailored to specific geometries, such as waveguide components, ferromagnetic devices, multilayer planar structures, etc. Therefore, the development of faster and more efficient specialized EM tools has a direct impact on the design of microwave components, both quantitatively and qualitatively. Increasingly complex geometries are modeled more accurately, and may be incorporated into novel designs without penalizing development time and its associated costs. By doing so, passive components become more advanced and are able to fulfill stricter requirements. At the same time, new research and development opportunities arise in order to address the challenges posed by these advanced structures. The present PhD thesis is focused on a specific type of waveguide cavity geometry: bi-dimensional structures of arbitrary shape. Most microwave components based on rectangular waveguides include these elements (bends, T-junctions, tapers, power-dividers, etc.), thus the scope of this work is wide. To characterize these structures, an efficient full-wave modal formulation is developed. Taking into account common properties of bi-dimensional structures, such as its electromagnetic symmetry, the resulting technique is very efficient and accurate. Thanks to the integration of this formulation into a CAE tool, a designer is able to solve complex systems that combine this type of element with components of vastly different shapes. The developed formulation is first applied to the analysis and design of passive components, such as filters, multiplexers and orthomode transducers. These
Comparison of Surface Energy Fluxes from Global to Local Scale

This study uses the ECMWF Reanalysis 5 and observationally constrained top-of-the-atmosphere radiative fluxes to infer net surface energy fluxes covering 1985–2018, which can be further adjusted to match the observed mean land heat uptake. Various diagnostics are applied to provide error estimates of inferred fluxes on different spatial scales. For this purpose, adjusted as well as unadjusted inferred surface fluxes are compared with other commonly used flux products. On regional scale, the oceanic energy budget of the North Atlantic between RAPID array at 26.5°N and moorings located further north, e.g. at the Greenland-Scotland ridge, is evaluated. On station-scale, a comprehensive comparison of inferred and buoy-based fluxes is presented. Results indicate that global land and ocean averages of unadjusted inferred surface fluxes agree with the observed heat uptake to within 1 W m−2, while satellite-derived and model-based fluxes show large global mean biases. Furthermore, the oceanic energy budget of the North Atlantic is closed to within 2.7 (−0.2) W m−2 for the period 2005–2009 when unadjusted (adjusted) inferred surface fluxes are employed. Indirect estimates of the 2004–16 mean oceanic heat transport at 26.5°N are 1.09 PW (1.17 PW with adjusted fluxes), which agrees well with observed RAPID transports. On station-scale, inferred fluxes exhibit a mean bias of −20.1 W m−2 when using buoy-based fluxes as reference, which confirms expectations that biases increase from global to local scales. However, buoy-based fluxes as reference are debatable, and are likely positively biased, suggesting that the station-scale bias of inferred fluxes is more likely on the order of −10 W m−2.
AUTOMATED DESIGN OF INDUCTIVELY COUPLED RECTANGULAR WAVEGUIDE FILTERS USING SPACE MAPPING OPTIMIZATION

In this paper, an efficient and full-automated design procedure for waveguide filters based on the aggressive space mapping technique is described. A novel procedure for the optimum choice of the starting point is proposed. The method implemented for the parameter extraction phase of the space mapping procedure is also detailed. The design technique is successfully applied to inductively coupled rectangular waveguide filters with and without tuning elements. A CPU comparative study is also included, thus confirming the efficiency of the new method proposed.
Development of MATLAB Based Software for the Analysis of the Impedance Data Obtained from in-House Developed Bio-Impedance Analyzer

Biological samples are sensitive to physical changes, mechanical as well as electrical. When any force is applied or temperature of the environment is increased or any torsion given to the system or electricity flows through it then it shows some changes behaviorally which in some distinguishable into eyes and is predictable. But there are two types of observations present which is taken into consideration. One is qualitative and other one is quantitative. Qualitative way is meant just to detect whether changes happening. But when it comes to comparison at that time one needs proof in which case this qualitative study fails. Again as biological samples are very sensitive to changes and different sample have different properties ,so they act differently in different time duration to the changes. Some changes such as due to electrical flow the changes in the behavior of the sample might not be visible but it can be predicted by the proposed method in quantitative approach. This study shows an easy approach to show the changes due to electrical current flow through the system. This quantitative approach also help in finding the stability as well as the utility of the model both in estimated and predicted cases. Here the well-known impulse response, Nyquist plot and Bode plot and the location of poles and zeros were used for detail analysis of the model behavior. Here hydrogel is taken as the dummy model for all the studies. This approach can be proposed in industrial way for samples stability prediction, its utility in required conditions and the productivity of the designed sample
Bayesian discovery sampling in financial auditing: a hierarchical prior model for substantive test sample sizes

SUMMARY In financial auditing statistical sampling is often used to obtain a quantitative evaluation of a population of monetary units. Often, the auditor has already evaluated the quality of the accounting system that produced the data before testing those data. Classical statistical theory, however, does not allow the results of these evaluations and compliance tests on the accounting system to influence the sample sizes required for substantive testing. Many audit firms have investigated a methodology to determine sample sizes for substantive testing from the results of compliance testing. As a response to the evident flaws in the so-called audit assurance model, developed in the 1970s in the accounting profession, in 1989 the Netherlands member firm of Deloitte Touche Tohmatsu International launched its Bayesian discovery sampling (BDS) model by publications by van Batenburg and Kriens in the statistical literature and by Veenstra'and van Batenburg in the Dutch auditors' professional journal. This simple Bayesian model used the last year's posterior as an anchor to choose the current year's prior for the population error fraction. Essential to BDS is the ratio p*/pm between the prior maximum error rate and the stipulated posterior maximum error rate. To facilitate its elicitation by auditors, this ratio was derived by usingf, the 'stability of the accounting process', defined as a measure of the correspondence between the last year's posterior and this year's prior. The auditor's professional judgment, based on risk assessment and on the results of compliance tests, provided a value for f Although using the previous year's results as an anchor, the auditor thereby chose a prior based on this year's evaluation of the quality of the accounting system. From this model, a sample size resulted that, when no errors occur, suffices for a set posterior probability that the error fraction will not have exceeded a stipulated critical value. Since 1990, Deloitte & Touche has applied this BDS model in Dutch audit practice and in 1991 Deloitte Touche Tohmatsu International, one of the six largest world-wide audit firms, adopted this Bayesian model in their audit sampling guide. As the next step the authors, together with the University of Nottingham, have developed a hierarchical model of the auditor's legal tasks and professional goals, of error prevalence and error consequences, and of the relationship between compliance tests results and substantive tests requirements. By comparing the resulting p*/pm-ratios of this 'wholeheartedly' Bayesian discovery sampling model to the ratios set by BDS in corresponding circumstances, conclusions can be drawn about the applicability of BDS and about the validity of the prior used in this model.
Skin-on-a-Chip Technology: Microengineering Physiologically Relevant In Vitro Skin Models

The increased demand for physiologically relevant in vitro human skin models for testing pharmaceutical drugs has led to significant advancements in skin engineering. One of the most promising approaches is the use of in vitro microfluidic systems to generate advanced skin models, commonly known as skin-on-a-chip (SoC) devices. These devices allow the simulation of key mechanical, functional and structural features of the human skin, better mimicking the native microenvironment. Importantly, contrary to conventional cell culture techniques, SoC devices can perfuse the skin tissue, either by the inclusion of perfusable lumens or by the use of microfluidic channels acting as engineered vasculature. Moreover, integrating sensors on the SoC device allows real-time, non-destructive monitoring of skin function and the effect of topically and systemically applied drugs. In this Review, the major challenges and key prerequisites for the creation of physiologically relevant SoC devices for drug testing are considered. Technical (e.g., SoC fabrication and sensor integration) and biological (e.g., cell sourcing and scaffold materials) aspects are discussed. Recent advancements in SoC devices are here presented, and their main achievements and drawbacks are compared and discussed. Finally, this review highlights the current challenges that need to be overcome for the clinical translation of SoC devices.
Innovation in museums through the use of ICTs

In the last decades, museums have transformed their role from restricted high-class mausoleums to popular attractions along with other leisure activities for both local and touristic routes. Hence, they have to relate with the socio-economic environment in similar ways as for-profit organizations, concerning the sustainability of their operations, and to innovate to achieve excellence in their mission of serving the society with socio-cultural and educational purposes. While museums have many ways to innovate, the dissemination of information and communication technologies (ICTs) in this field has recently received some attention for their influence and the possibilities those tools offer to enhance innovative strategies. ICTs are found in most museums operations, both inside and outside its walls, being used by the work team, users/visitors, the market, and the environment in general. Those tools can help from internal procedures, to exhibition design, and customer relationship management. Despite recent researches, however, our understanding of the different functions played by ICTs for the innovative activities and economic performance of museum organizations is still limited. The aim of this thesis is to investigate further how museums make use of ICTs in order to execute and achieve success in their innovative projects and goals. Based on the existing literature, the thesis presents a new typology of ICTs’ use in museums dividing technologies according to their characteristics, objective, and place of use. This typology is later confronted with empirical results to investigate the impression visitors have about the relevance of ICTs in promoting innovation.
Exploring Customer Value in the Hardwood Lumber Industry

In this paper, the author investigates the role of product, service, and price-relative to competition-in determining customer value perceptions among buyers of northern hardwood lumber. Based on survey data collected in December 1999, this study examines the importance of attributes affecting purchase decisions and compares these findings with a regression approach incorporating an explicit customer value measurement. These data indicate that attributes deemed important to the purchaser are not necessarily the same attributes related to perceptions of highly valued suppliers. Results indicate that consistent availability of desired species and aesthetic qualities of shipments are the most influential attributes in the identification of suppliers providing high levels of customer value. Finally, value perceptions are examined across broad industrial buyer segments.
Creating Science Online Learning Media Using Scratch App Block Programming

A difficulty faced by science teachers in online teaching is the inability to apply science materials straight to the students. This research examined how Scratch app block programming can be used on a personal computer or tablet to create science instructional tools to be used online. It was found that the steps to do so are: (1) downloading the Scratch app and running the file; (2) creating designs for the project with e.g. backdrops, paint, costumes; (3) coding or programming the scripts while choosing blocks in block palettes for the science project; (4) dragging and dropping the blocks to the script area for setting the parameter, operator, control, motion, look, sound, sensing and motion block inputs for the program; and (5) saving and running the block code/script in the scripts area. The researchers found that the Scratch app was effective in creating an online medium for learning about science and applying science concepts in everyday life. Keywords: science learning, measurement, online learning, scratch app, block programming, computational thinking
A Proactive Statistical Model Supporting Services and Tasks Management in Pervasive Applications

The combination of the Internet of Things (IoT) and Edge Computing (EC) can support intelligent pervasive applications that meet the needs of end users. A challenge is to provide efficient inference models for supporting collaborative activities. EC nodes can interact with IoT devices and each other to conclude those activities producing knowledge. In this paper, we propose a proactive scheme to decide upon the efficient management of services and tasks present/reported at EC nodes. Services can be processing modules applied upon local data while being required for the execution of tasks. We monitor the demand for the available services and reason upon their management, i.e., for their local presence/invocation as the demand is updated by the requested processing activities. For each incoming task, an inference process is fired to proactively meet the strategic targets of the envisioned model. We propose a statistical inference process upon the demand for services and the contextual performance data of nodes combining it with a utility aware decision making model. Instead of exclusively focusing on services migration or tasks offloading as other relevant efforts do, we elaborate on the decision making for the selection of one of the aforementioned activities (the most appropriate at a specific time instance). We present our model and evaluate it through a high number of simulations to expose its pros and cons placing it in the respective literature as one of the first attempts to proactively decide the presence of services to an ecosystem of processing nodes.
The relevance of the notion for all publicity is good publicity: The influencing factors in the 21st century

In the age of technology and a competitive market within the Philippines, an adverse stance or aftereffects of a situation have a significant impact on the sensibility of the audiences and are likely to prompt either positive or negative reactions from them. However, in the marketing and advertising sectors, the belief "All Publicity is Good Publicity" is well-known, which states that any form of publicity is fine as long as it cultivates presence and visibility. To be able to determine whether the notion is still highly appropriate in the 21st century and to provide a definite difference between good and bad publicity, the researchers have used a mixed-method approach and employed the use of quasi-experiment and short Focus Group Discussion (FGD) instruments for forty (40) participants under the Generation Z demographic group in Metro Manila. The researchers have also chosen six (6) business owners, advertisers, or managers within the metro for personal interviews in order to identify the perspective of both parties. Overall, the results show that the notion is no longer very relevant. According to the four influencing factors, defiance of advertising ethics does not always result in negative press, but non-compliance with corporate social responsibility (CSR), controversial advertising and situations, and corporate scandals do. It is important to highlight that every advertising or activity must be well-planned since there is a clear difference between good and poor exposure.
helayo: Reconstructing Sanskrit texts from manuscript witnesses

For most ancient and medieval texts, the original text itself is no longer extant in a material form. Instead, we have manuscripts that are copies of copies of copies made over the course of hundreds or thousands of years, which accumulate errors and other changes each time they are transcribed by hand. To reconstruct the original text from these imperfect copies, scholars create a stemma — analogous to an evolutionary tree — to determine the relationships between manuscripts and trace those textual changes over time.
Joint Target and Ionosphere Parameter Estimation in Over-the-Horizon Radar

Target localization, especially the estimation of target altitude, is a challenging task in over-the-horizon radar (OTHR) because of the narrow signal bandwidth as well as the complexity and uncertainty involved in the ionosphere conditions. This task becomes further complicated when the height of the ionosphere layer varies over time. Therefore, it is important to jointly estimate the instantaneous height of the ionosphere and the target altitude as well as other motion parameters. In this article, we achieve these objectives by analyzing the Doppler frequencies of the target local-multipath signals and the clutter. We reveal that the change of the ionosphere height can either enhance or deteriorate the performance of target parameter estimation depending on its direction of motion relative to the target’s motion profile. In addition, it is found that the received target and clutter Doppler signatures follow the chirp signal profile at the OTHR receiver. Based on these observations, we develop a general framework that achieves joint target and ionosphere parameter estimation and accounts for the velocity and accelerations of both target and ionosphere layer. Unlike existing time-frequency-based strategies for target localization and tracking in OTHR, where the Doppler signatures only directly determine target vertical velocity and the target altitude is estimated indirectly, the proposed model enables direct estimation of target altitude and ionosphere parameters. The parameter estimation problem in the proposed strategy is analytically derived and the effectiveness is verified using extensive simulation results.