Active Learning with Expert Advice

Conventional learning with expert advice methods assumes a learner is always receiving the outcome (e.g., class labels) of every incoming training instance at the end of each trial. In real applications, acquiring the outcome from oracle can be costly or time consuming. In this paper, we address a new problem of active learning with expert advice, where the outcome of an instance is disclosed only when it is requested by the online learner. Our goal is to learn an accurate prediction model by asking the oracle the number of questions as small as possible. To address this challenge, we propose a framework of active forecasters for online active learning with expert advice, which attempts to extend two regular forecasters, i.e., Exponentially Weighted Average Forecaster and Greedy Forecaster, to tackle the task of active learning with expert advice. We prove that the proposed algorithms satisfy the Hannan consistency under some proper assumptions, and validate the efficacy of our technique by an extensive set of experiments.Comment: Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013

Ioonsetel vedelikel põhinevate elektrolüütide elektrokeemilised omadused Bi(hkl) ja mikro-mesopoorsetel süsinik elektroodidel

Väitekirja elektrooniline versioon ei sisalda publikatsiooneTänapäeva tehnoloogias ja teaduses on olulisel kohal moodsad energia muundamise ja salvestamise seadmed. Ioonsed vedelikud omavad olulist tehnoloogilist potentsiaali antud seadmetes tänu nende kõrgele keemilisele stabiilsusele, laiale variatsioonile ning rakendatavusele nii elektrolüüdi kui solvendina. Selleks, et disainida effektiivsemaid ja kõrgema erienergiaga energiasalvesteid on oluline mõista mehhanisme, mis mõjutavad energia salvestamist ioonseid vedelikke rakendavates süsteemides, nagu näiteks super- ja hübriidkondensaatorites. Elektrilise kaksikkihi (EKK) tekke ja dünaamika ning lisandite mõju, nagu näiteks halogeniid ja leelismetalli ioonid, vesi ja orgaanilised solvendid, uurimine võimaldab meil teadlikult disainida paremaid elektrokeemilisi seadmeid. Antud töös uuriti nii mudelelektrood-süsteeme, et näidata lisandite mõju EKK tekkele vismuti monokristalli eri tahkudel, kui ka superkondensaatori test-rakke, et kontrollida, kuivõrd fundamentaaluuringutest saadavad teadmised on rakendatavad ka reaalsetes seadmetes. Antud töös kasutati elektrokeemilise impedantsspektroskoopia, skaneeriva tunnelmikroskoopia ja alalisvoolu elektrokeemilisi meetodeid, et iseloomustada erinevate ioonsete vedelike mahtuvuslikke, takistuslisi ja adsorptsioonilisi omadusi vismuti monokristallide ja mikro-mesopoorse süsinikmaterjali piirpinnal. Lisaks vaadeldi erinevate pindaktiivsete lisandite mõju vastavate süsteemide omadustele. Tulemustest nähtub, et kõige olulisemat mõju vastavate süsteemide elektrood│elektrolüüt piirpinnale omavad ioonse vedeliku anioonid ning lahustunud molekulid mis omavad tugevat vastastikmõju anioonidega. Näidati, et anioonide varieerimine muudab oluliselt piirpinna mahtuvust, eriti polariseeritavamate anioonide nagu näiteks halogeniid-ioonide puhul. Skaneeriva tunnelmikroskoopia tulemustest võib järeldada, et mahtuvuse muutus on tingitud kõrgelt struktureeritud tiheda adsorptisoonilise kihi tekkest vismuti monokristallide piirpinnale. Samuti uuriti vee kui lisandi mõju Bi│ioonne vedelik süsteemile. Kõrge hügroskoopsuse tõttu on väike vee lisand levinud paljudes uuritavates süsteemides, ning vastava mõju hindamine omab olulist väärtust rakendustele. Ka siin leiti, et kõige olulisem muutus puudutab ioonse vedeliku anioone, mis veemolekulide olemasolu korral on võimelised moodustama hüdrateeritud komplekse, mis omavad olulist mõju vismutelektroodi mahtuvuslikele omadustele, eriti positiivse pinnalaengu korral. Samuti on vee-lisandil arvestatav mõju takistuslikele parameetritele, kuna vesi on elektrokeemiliselt ioonsetest vedelikest vähem stabiilsem. Ioonsete lisandite mõju superkondensaatorites uurimiseks võrreldi puhast ioonset vedelikku kui elektrolüüti sisaldavat süsteemi ning lisati nendele nii halogeniid kui ka leelismetalli ioone. Vastavad lisandid olid kasutusel abrosbeerituna mikro-mesopoorses süsinikmaterjalis, milles oluline osa poorsusest on suurematele ioonse vedeliku anioonidele ja katioonidele suletud. Seega võis eeldada, et väikesemad lisandi-ioonid on peamiselt kontsentreerunud materjali mikropooridesse. Näidati, et kuigi leelis-metallide ioonid ei oma olulist mõju superkondensaatori mahtuvusele, siis halogeniidioonid aitavad parendada süsteemi elektrokeemilisi omadusi olulisel määral. Seega on ka antud süsteemides aniooni mõju elektrokeemilistele omadustele ja EKK tekkele määrava tähtsusega. Täpsem impedants-spektrite analüüs võimaldas lahtutada vastava mõju nii mahtuvuslikuks kui ka laengu-ülekande komponentideks, aidates mõista halogeniidioonide mõju hübriidkondensaatorile.Recently, the energy crisis has become more and more serious. Thus, it is important to accelerate energy upgrading and establish the growth of new energy economics. As one of the carriers of global energy transformation, the development of electric vehicles may contribute to establishing the electrification of society and the transformation of industrial structure. However, the rapid development of electric vehicles still represents several challenges and limitations, such as the charging capacity of power sources involving batteries and supercapacitors. With the continuous iteration in the technological progress of battery and supercapacitor materials, efforts have been made to develop high-performance electrochemical energy storage devices. The electrochemical energy storage process, in principle, occurs at the electrode-electrolyte interface. It is of great significance to study the electrochemical behavior at the interface. Therefore, the electrochemical behavior and energy storage characteristics of the electrode-electrolyte interfaces were studied in this work, aiming to achieve high capacitance performance. Ionic liquids (ILs) composed of anions and cations can show high thermal, chemical and electrochemical stability. This work focused on the electrochemical characteristics of the pure IL and IL salt mixtures. Regarding electrode materials, Bi(hkl) and micro- and mesoporous carbon electrodes were studied. As an excellent alternative electrode material for traditional mercury electrodes, bismuth electrode with low toxicity has been widely studied in the Department of Physical Chemistry, University of Tartu. The capacitance-potential curves of pure IL and IL salt mixtures at the Bi(111) electrode were discussed in this work, mainly conducted by the cyclic voltammetry and electrochemical impedance spectroscopy methods. The capacitance peaks of capacitance-potential curves suggest that the specifically adsorbed anions (i.e., I‾ and Br‾) can increase the capacitance. Additionally, electrochemical characteristics of water-contained ILs at Bi(hkl) electrodes were studied. The capacitance-potential curves have seen anomalous capacitance peaks due to the specific interaction between water and anions. Interestingly, small amounts of adsorbed water molecules do not affect the electrochemical stability potential range of the base electrolyte but contribute to the increase of capacitance. According to the equivalent circuit modeling fit of experimental impedance data, the kinetics of surface processes (mass transfer and faradaic characteristics) were shown in the resistance-potential curves. To characterize the surface structure of the interface in a nanoscale, in situ scanning tunneling microscopy measurement was applied to image the surface structure of electrodes in IL within the potential range applied. Results found that the highly ordered structures on Bi(111) and Bi(011 ̅) planes were recorded relating to the strongly adsorbed anions consistent with electrochemical results. Since the specifically adsorbed halide ions (Br‾, I‾) at the Bi(111) electrode can increase the capacitance at the interface, it is assumed that such halide ions could help improve the capacitance performance of supercapacitors. The pure IL, IL salts mixture containing halide ions and IL salts mixture containing alkali ions were applied to impregnate the micro- and mesoporous carbon electrodes of supercapacitors. Compared to the pure IL treated supercapacitor, supercapacitors treated with halide salt mixtures showed higher capacitance. In contrast, alkali salt mixtures did not improve the capacitance performance of the supercapacitor. Moreover, supercapacitors treated with halide (positive electrode) and alkali (negative electrode) salt mixtures showed consistently high capacitance, suggesting an effective doping methodology by symmetrically stabilizing both electrodes. According to the equivalent circuit modeling fit of experimental impedance data, the enhanced capacitances are attributed to the pseudocapacitive effect originating in the specifically adsorbed and redox-active halide ions within and near the carbon pores.https://www.ester.ee/record=b550050

Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification

Multiple kernel learning (MKL) method is generally believed to perform better than single kernel method. However, some empirical studies show that this is not always true: the combination of multiple kernels may even yield an even worse performance than using a single kernel. There are two possible reasons for the failure: (i) most existing MKL methods assume that the optimal kernel is a linear combination of base kernels, which may not hold true; and (ii) some kernel weights are inappropriately assigned due to noises and carelessly designed algorithms. In this paper, we propose a novel MKL framework by following two intuitive assumptions: (i) each kernel is a perturbation of the consensus kernel; and (ii) the kernel that is close to the consensus kernel should be assigned a large weight. Impressively, the proposed method can automatically assign an appropriate weight to each kernel without introducing additional parameters, as existing methods do. The proposed framework is integrated into a unified framework for graph-based clustering and semi-supervised classification. We have conducted experiments on multiple benchmark datasets and our empirical results verify the superiority of the proposed framework.Comment: Accepted by IJCAI 2018, Code is availabl

Genetic Structure of Mongolian Wheatgrass (\u3cem\u3eAgroypron Mongolicum\u3c/em\u3e Keng) In Inner Mongolia of China

Mongolia wheatgrass (Agroypron mongolicum) is a cross-pollinated, long-lived, cool-season and drought-resistant perennial bunchgrass, which plays an important role in arid and semi-arid grasslands of Inner Mongolia. Collections of A. mongolicum from different areas of Inner Mongolia are valuable sources of useful genes for its breeding. The genetic diversity of 8 accessions of A. mongolicum were examined in this study. A dendrogram was constructed to obtain information on the relationship between cultivated and wild A. mongolicum genotypes, which is basic information to explore the possibility of its use in intra- and inter-specific breeding programs

Investigation On Premature Failure Of the Self-lubricated Piston Rings in Oil-free Compressor

Abstract: This paper presents the numerical simulation and experimental investigation on impact factors on premature failure of the self-lubricated piston rings in oil-free compressor. In this paper, the finite element method (FEM) was applied to study the non-uniform pressure distributions among the piston rings and the friction process between the self-lubricating piston rings and the cylinder wall, which influence the failure of the self-lubricated piston rings most. In order to verify the mathematic model, a test rig was built to measure the dynamic pressure distributions and temperature field between the piston rings. Both the theoretical and experimental results showed that the first piston ring afford more than 75% of the total pressure difference which was the main reason for the non-uniform wear and thus lead to early invalidation. The friction heat produced between the first piston ring and the cylinder was far more than the rest, which cannot be diffused rapidly through the low conductivity self-lubricating plastics and led to thermal failure of the self-lubricating piston rings. The results provide the theoretical basis to determine the design parameters and the thermal performance of piston rings reasonably

Framework Design of Emergency Management Information System for Cloud Computing in Chemical Park

Collaborative emergency management mode provides a new idea for further reducing system safety risk in the chemical park. In this paper, the cloud computing and the expert system were used for the framework design of the emergency management information system to enhance emergency response capability of collaborative emergency managementmechanisms. The use of middleware integrated with multi-source data achieved the unified data manipulation interface. Intelligent delivery of information system was provided. Using agent-middleware technology to build decision layer could make massive data analysis, data mining and decision from the “cloud computing” platform access for every user. It can provide the necessary theoretical and technical support for enterprises in the chemical park, to give full play to the collaborative emergency management capability.</p

State estimation for one-dimensional agro-hydrological processes with model mismatch

The importance of accurate soil moisture data for the development of modern closed-loop irrigation systems cannot be overstated. Due to the diversity of soil, it is difficult to obtain an accurate model for agro-hydrological system. In this study, soil moisture estimation in 1D agro-hydrological systems with model mismatch is the focus. To address the problem of model mismatch, a nonlinear state-space model derived from the Richards equation is utilized, along with additive unknown inputs. The determination of the number of sensors required is achieved through sensitivity analysis and the orthogonalization projection method. To estimate states and unknown inputs in real-time, a recursive expectation maximization (EM) algorithm derived from the conventional EM algorithm is employed. During the E-step, the extended Kalman filter (EKF) is used to compute states and covariance in the recursive Q-function, while in the M-step, unknown inputs are updated by locally maximizing the recursive Q-function. The estimation performance is evaluated using comprehensive simulations. Through this method, accurate soil moisture estimation can be obtained, even in the presence of model mismatch