Miracle-dz/UniFAR-FTUs huggingface dataset:
Battery State of Charge Estimation Based on a Pure Hardware Implementable Method

In this paper, a light-weighted state of charge (SoC) estimation method is proposed. A novel proportional-integral-delta structure is proposed to improve the noise-rejection performance. Experimental results show that the proposed algorithm can achieve a 4% accuracy with the presence of 50mV voltage measurement noise, while its computational time is 90% less than that of the extended Kalman filter. Compared with the existing SoC algorithms, a distinguishing feature of the algorithm is that it is implementable using pure analog devices. This feature makes it possible to build a redundant hardware-based SoC estimator to enhance the overall reliability of the battery management system.
ROS-Enabled Framework for a Miniature Hexapod as a Mobile Robot Research Platform

The purpose of this thesis is to investigate and develop a framework for connected six-legged robots which can be used as a Robotic Operating System (ROS) based research platform. The research presented aims to purvey the necessary engineering and scientific steps needed to evolve a consumer-grade connected toy into a fully functioning and highly capable robotic system. Such a platform can be used to simulate and implement novel biologically inspired swarm research. Crawling robots have the advantage of being able to scale terrains which wheeled mobile robots may not and possess many interesting characteristics. The miniROaCH, miniature ROS-enabled and Crawling Hexapod, is a lightweight and small-scale robot which is able to navigate and traverse unknown and uneven terrain. The miniROaCH robot was designed to utilize both commercially accessible components and 3D printable parts. With a 1GHz single-core on-board processor and an 8MP high-definition camera, the platform allows for situational awareness, object avoidance and mapping capabilities. Furthermore, each miniROaCH is capable of
HYBRID RESOURCE MANAGEMENT SYSTEM FOR TELECOMMUNICATION NETWORK

The implementation of modern telecommunication technologies (SDN, NFV, SDR, CloudRAN) will lead to the full dependence of the telecommunication network performance on the information and computing environment efficiency. The purpose of the article is to develop the method for managing telecommunication network resources by choosing the optimal interval for redistributing system resources. The proposed model of load management system allows presenting the method of load forecasting, taking into account long-term accumulated data of statistics, and the latest tendencies, which are observed in the network. So it becomes possible to achieve a rational ratio of management costs and the final value of service quality. A new method of monitoring and measurement, using which it is possible to avoid overloading of network functions was developed. Conclusion. Experiments to research the proposed methods were conducted in the Mathcad system. The results showed that proposed methods could rationally distribute the system resources, especially under transient conditions of overload.
Chemosystematic studies in the genus Pseudotsuga. I. Leaf oil analysis of the coastal and Rocky Mountain varieties of the Douglas fir

The volatile leaf oils of the coastal and Rocky Mountain varieties of the Douglas fir were found to have distinctive terpene compositions. The relative amounts of l-β-pinene, sabinene, 3-carene, α- and γ-terpinene, terpinolene, l-terpinen-4-ol, citronellol, citronellyl and geranyl acetate (relatively large in the former variety); and santene, tricyclene, l-camphene, limonene, and l-bornyl acetate (relatively large in the latter variety) may serve as distinguishing features. n-Hexenal, l-α-pinene, α- and β-phellandrene, linalool, fenchyl alcohol, and l-α-terpineol were also isolated. The within-tree and within-population variation of the amounts of these terpenes as well as populational differences from Calgary through the foothills to Revelstoke were small. Intermediate compositions were encountered as far west as the Cascades and one may distinguish clearly between interior and coastal intermediate terpene patterns. Between Keremeos and Hedley the terpene pattern was essentially that of the Rocky Mountai.
Representing Unawareness on State Spaces

I study unawareness by the lack of knowledge on a generalized state space. In order to understand and contrast properties of unawareness in a non-partitional standard state space model and a partitional generalized state space model, I provide a generalized framework that accommodates both models. I ask: when and how a generalized (in particular, standard) state space model has a sensible form of unawareness; and how unawareness relates to ignorance and possibility. First, unawareness can only take two forms: an agent is ignorant of knowing that she does not know an event; and the agent is ignorant of knowing an event. In either case, unawareness is also associated with the ignorance of the possibility of knowing an event. Second, the agent, who is unaware of an event, is ignorant (but not necessarily unaware) of being unaware of it. Third, the agent, facing infinitely many objects of knowledge, may know that there is an event of which she is unaware, while she cannot know that she is unaware of any particular event. Fourth, getting more information can cause the agent to become unaware of some event. Journal of Economic Literature Classification Numbers: C70, D83 Keywords:Unawareness; Awareness; Knowledge; State Space; Ignorance; Possibility
The relationship between sphincteratomy methods and post ercp pancreatitis

Post (ERCP) pancreatitis (PEP) is the most commonly seen complication after endoscopic retrograde cholangio-pancreaticography (ERCP). It is associated with pancreatic hyperamylasemia and persistent abdominal pain. It can be classified as mild, moderate and severe. During ERCP, bile ducts or pancreatic duct can be cannulated using standard sphincteratomy or needle-tipped sphincteratomy methods and contrast material is injected in order to view these ducts. In this study, we aimed to examine whether the use of sphincterotomy methods and pancreatic canal interventions poses a risk in the development of PEP, which is the most common complication after ERCP. Of the 445 patients who underwent ERCP, 270 had standard sphincterotomy and 175 had Needle-knife sphincterotomy (NKS). Patients who were cannulated with pancreatic duct and injected with contrast agent during the procedure and patients who were diagnosed with PEP according to the revised Atlanta criteria, were included in the study. Of 445 patients, 187 were male (39.7%) and 258 were female (60.3%). After successful sphincterotomy, stone extraction basket and / or balloon procedure was applied to all patients. Of the 270 patients, 13(2.9%) patients developed PEP and 9 of these patients had pancreatic duct cannulation and contrast agent injection during the procedure. PEP development was statistically significant in patients with pancreatic duct cannulation (p
RayBooster : An efﬁcient, robust, generic and easy to use basic component for high performance radiative simulations

Latest environment concerns and bioclimatic issues are essential in modern building performance simulations. Among those concerns, most of simulations require radiative propagation computation to estimate solar incomes, daylighting, solar panel efﬁciency, etc. Ray Tracing based methods are a robust approach to radiative simulation. However, a common wisdom is to associate them to slow performances or high demanding computation power. Based on the acquired expertise of HPC-SA in terms of research, industrialization and integration of Ray Tracing technologies over the last decade, we introduce a ray tracer named RayBooster. It helps to reduce signiﬁcantly the per ray cost of simulations. In fact, this innovative basic component allows both to increase the quality of results for the same amount of time, and to shift off-line simulations, which need a lot of time computations, toward a real-time world. In this paper, we brieﬂy describe the RayBooster ray tracer and its advantages in terms of genericity and performances. We then measure its efﬁciency on practical benchmarks before illustrating its ease of use by providing a RayBooster 4 powered version of the widely used light simulation toolchain named Radiance (Ward 1994). We show that this integration is not only straightforward but also drastically improves both the robustness and the efﬁciency of this well-tried codebase.
Integrating User Profiles from Academic and Professional Web Data Sources

—Semantic Web concepts and technologies have been considered as a way for enhancing integration of datasets on the Web. Based on that, this work applies a semantic Extract-Transform-Load approach to integrate user profiles from academic and professional web data sources. Considering a given application, which needs those integrated user profiles, we take into account the application data requirements in order to refine the proposed approach and to easy the data integration tasks. In this paper, we present the principles underlying our approach and some obtained results in the light of a scenario including some real web academic and professional data sources.
Preference Learning for Real-World Multi-Objective Decision Making

In experimentation at Internet firms, it is common to make product decisions based on multiple competing or complementary objectives where the experimenter needs to select the most “favorable” option with the highest utility. However, despite the prevalence of this decision problem, such multi-objective decisions are often made in arguably sub-optimal ways. In this paper, we propose a framework that enables us to suggest the configuration in a potentially large action space that is expected to maximize the experimenter’s utility function. We demonstrate the efficacy of preference learning and our proposed framework with two user studies conducted at a large Internet firm. We show how the learned preference models can accurately recover machine learning engineers’ preferences in the user study and are most useful when trained on near-optimal regions where real-world tradeoffs are expected to happen the most.
Designing the Attitude toward Advertising Model through Mobile Social Networks

The aim of this research is to help advance a better understanding of digital advertising innovation adoption, consumer acceptance of customized advertising, and the influence of customized advertising on product purchase intent via a mobile social network. To this end, two types of questionnaires, including an open questionnaire filled up by 16 experts and university professors was designed to identify the indicators and sub-indicators of advertising acceptance determinants through mobile-based cyberspace networks. The other questionnaire was a 5-point Likert questionnaire designed based on the identified indicators of the open questionnaire, which was filled by 234 cyber-space users who were chosen using simple random sampling method in order to verify the identified factors. The results of the study led to the identification of seven main indicators namely revenue generating, legalization, Awareness at social levels, Family and friends, Advertiser owners, monitoring and Advertising quality and the identification of 44 sub-indicators for seven three main determinants.
EFFECT OF AIR VELOCITY ON THE LENGTH OF FLAME IN TURBULENT NON-PREMIXED FLAMES

In this study, the turbulent non-promixed methane-air flame is simulated to determine the effect of air velocity on the length of flame. The computational fluid dynamics (CFD) technique is used to perform this simulation. To solve the turbulence flow, k-ε model is used. In this study, contrary of some of the past works, the material properties are considered variable in each of the simulations and obtained results are compared with them. Finally, it is achieved that at a certain flow rate of fuel, increasing the air velocity, as expected, like when the properties were considered constant, causes an increase on the flame temperature, leads to a thinner flame.
Modelling the behaviour of swelling clays in a Geological Disposal Facility (GDF) La modélisation du comportement des argiles gonflantes dans les structures pour le stockage géologique profond

This paper discusses the numerical modelling of the buffer material in a Geological Disposal Facility (GDF), by simulating the FEBEX in-situ experiment. The test was conducted over 18 years at the Grimsel site in Switzerland, under the conditions of a real GDF, with compacted bentonite blocks used as the buffer material and a heater replacing the nuclear waste canister. Particular emphasis in the paper is given to the constitutive modelling of the FEBEX bentonite, highlighting the importance of accounting in the model for the double porosity structure of the compacted bentonite. Furthermore, the coupled thermo-hydro-mechanical (THM) finite element analysis also emphasises the importance of realistic modelling of the evolution of the hydraulic permeability of the bentonite with the changing suctions. The analysis results demonstrate substantial agreement between numerical predictions and FEBEX field measurements in terms of the buffer’s THM evolution. The area of the host formation affected by the test is also defined and investigated in order to provide useful information for the design of a GDF. RÉSUMÉ: Cet article discute de la modélisation numérique du comportement du bouchon de bentonite en simulant le test FEBEX. Ce test a eu lieu pendant 18 ans au Grimsel en Suisse : les conditions d’une vraie structures pour le stockage géologique profond ont été reproduites, avec un bouchon fait par des blocs compactés de bentonite et les déchets simulés par des appareils de chauffage. Une attention particulaire est portée à la modélisation constitutive du bouchon de FEBEX bentonite : le rôle de la double structure dans la bentonite compactée est très important. En outre l’analyse numérique thermo-hydro-mécanique (THM) aux éléments finis souligne l’importance de prendre en compte le changement de la perméabilité de la bentonite avec la succion. Les résultats de l’analyse numérique sur l’évolution thermo-hydro-mécanique du bouchon sont en accord avec les mesures prises par les capteurs situés dans la bentonite. La région de la roche dans laquelle la structure pour le stockage géologique profond est creusée est étudiée afin de définir les contours de la partie la plus influencée par le test FEBEX et de fournir des indications utiles en phase d’étude.
EXPERIMENTAL AND NUMERICAL INVESTIGATION OF A CONDENSATION REPELLENT RADIANT COOLING PANEL SYSTEM

Radiant cooling panels (RCP) use controlled-temperature surfaces to provide heat transfer mainly by radiation. In this study, the performance of RCP system is investigated using experimental measurements and numerical calculations. In the experimental study, a radiant cooling panel system equipped with cooling coils was examined in a vacant room. The power consumption, condensation rate and thermal comfort were studied experimentally. A numerical model was also employed to study flow pattern inside the room and to predict temperature distributions. The flow field was obtained by solving the flow governing equations namely continuity, momentum and energy equations. The turbulent flow was solved by using Re-Normalization Group RNG k-ε turbulence model. Heat transfer by radiation was modeled using Discrete Ordinates DO radiation model. The effect of the radiant panel surface temperature and exit air temperature from the panel were studied. The results showed that the used numerical technique could predict temperature distribution in the room with reasonable accuracy. It was found through this study that RCP provide thermal comfort and is energy efficient.
Off-policy Policy Evaluation Under Unobserved Confounding

When observed decisions depend only on observed features, off-policy policy evaluation (OPE) methods for sequential decision making problems allow evaluating the performance of evaluation policies before deploying them. This assumption is often violated due to the presence of unobserved confounders, variables that impact both the decisions and their outcomes. We assess the robustness of OPE methods by developing worst-case bounds on the performance of a evaluation policy under different models of confounding. When unobserved confounders can affect every decision in an episode, we demonstrate that even small amounts of per-decision confounding can heavily bias OPE methods. Fortunately, in a number of important settings found in healthcare, policy-making, operations, and technology, unobserved confounders may primarily affect only one of the many decisions made. Under this less pessimistic model of one-decision confounding, we propose an efficient loss-minimization-based procedure for computing worst-case bounds on OPE estimates, and prove its statistical consistency. On simulated healthcare examples, we demonstrate that our method allows reliable off-policy evaluation by invalidating non-robust results, and providing certificates of robustness.
Detecting Botnets Communicating with Command and Control Servers with DNS and NetFlow Data

—The threat of botnets has been growing, as the number of C&C servers nearly doubled between 2017 and 2019. To defend against this threat, botnet detectors are necessary. In this research, we built a proof of concept botnet detector using DNS and NetFlow data. We make use of two independent classiﬁcation systems to combine the two data sources in our proof of concept. One classiﬁcation system, which we have designed, makes use of DNS and WHOIS data to determine the likelihood that a domain is malicious. The other classiﬁcation system named Disclosure makes use of NetFlow data to determine if a ﬂow is likely malicious. Disclosure was proposed by Bilge et al. [1]. Our proof of concept system combines the two scores given by the two classiﬁcation systems to determine if the network trafﬁc is malicious. We have evaluated the DNS and WHOIS features used by the domain classiﬁcation system because the classiﬁcation system was designed in this study. The evaluation was done by comparing the differences between benign and malicious domains for each feature. Moreover, we have also evaluated the prediction accuracy of the two classiﬁcation systems individually. Finally, we have evaluated the accuracy of our whole proof of concept system. From our experiments, we have found that the chosen features of our designed classiﬁcation system were properly considered.
Using Active Learning for Assisted Short Answer Grading

Eﬃcient and comprehensive assessment of students knowledge is an imperative task in any learning process. Short answer grading is one of the most successful methods in assessing the knowledge of students. Many supervised learning and deep learning approaches have been used to automate the task of short answer grading in the past. We investigate why assistive grading with active learning would be the next logical step in this task as there is no absolute ground truth answer for any question and the task is very subjective in nature. We present a fast and easy method to harness the power of active learning and natural language processing in assisting the task of grading short answer questions. A web-based GUI is designed and implemented to incorporate an interactive short answer grading system. The experiments show that active learning saves the time and eﬀort of graders in assessment and reaches the performance of supervised learning with less amount of graded answers for training.
REVISION OF THE EARLY CRETACEOUS CORDICEPHALUS FROM ISRAEL AND AN ASSESSMENT OF ITS RELATIONSHIPS AMONG PIPOID FROGS

Abstract Because many fossil pipoid anurans have been described during the past 35 years from Cretaceous deposits in South America and Africa, it is appropriate to revisit some of the earlier ones to have been discovered, viz., Cordicephalus gracilis, C. longicostatus, and Thoraciliacus rostriceps from Israel. Careful examination of Cordicephalus, based on study of previously, as well as newly, prepared specimens, reveals the existence of only one species. Cordicephalus gracilis is redescribed and compared with Thoraciliacus, and the phylogenetic relationships of these genera to other living and fossil pipoid frogs are investigated in a parsimony analysis. Thoraciliacus is basal to a clade containing Cordicephalus, Palaeobatrachus, and all other living and fossil pipids; however, the placement of Cordicephalus with respect to Palaeobatrachus and Pipidae is unresolved. Both Thoraciliacus and Cordicephalus retain the primitive state for several pipid synapomorphies involving the condition of the vomers, parasphenoid, and presence of a tympanosquamosal bone. In contrast to Thoraciliacus, however, Cordicephalus is characterized by several derived characters including possession of an otic capsule modified to accommodate a Eustachian tube and depressed, fully ossified opisthocoelous vertebrae. Despite their lack of many pipid specializations, both Thoraciliaus and Cordicephalus seem to possess many morphological features that typically are associated with aquatic habits. Among these are possession of a flat skull with a short rostrum, short axial column, and relatively long metapodials.
An On-Chip Soft-Start Circuit for DC-DC Switching Regulators

A soft-start circuit based on DAC (digital-to-analog converter) control for DC-DC switching regulator is presented.Using the techniques of DAC control and soft-start voltage sense,the rush current and overshoot of the output voltage during start-up are eliminated effectively,allowing for a smooth output voltage ramp from zero to regulation.At the end of start-up,the biased current of the soft-start circuit is cut off completely. Consequently,it is power-efficient.The circuit is designed using CMOS devices without the need of any external components,so it is suitable for integration in DC-DC switching regulators.The proposed soft-start circuit has been applied to a Buck PWM controller successfully.The experimental results show that in the entire load range the output of the system can start up smoothly,the inductor current remains stable,the output voltage rises smoothly without overshot,and the soft-start time is about 1.2ms.
Multi-task Bayesian Optimization via Gaussian Process Upper Conﬁdence Bound

Bayesian optimization is a popular method for optimizing black-box functions. In this work, we consider multi-task generalization of Bayesian optimization for optimizing multiple related black-box functions simultaneously. We use multi-task Gaussian processes to model the joint distribution among all tasks and propose a simple acquisition function based on GP-UCB (Srinivas et al., 2012). Extending the notion of regret to multi-task Bayesian optimization, we provide a theoretical analysis to show that our proposed algo-rithm is no-regret under mild assumptions. We provide experimental results on a wide variety of applications, from synthetic test function optimizations to hyperparameter tuning of machine learning models and nanophotonic structure designs. Our experiments show that multi-task GP-UCB is able to achieve smaller simple regret compared to optimizing each task individually using single-task GP-UCB.