Difficulties In Application Research Articles

Мінімізація кредитного ризику та підвищення якості кредитного портфеля банку

The article considers the main factors that form credit risk and determines the role of credit risk in the process of formation of the credit portfolio of a commercial bank. It is determined that bank lending involves the functioning of a complex mechanism that includes certain actions aimed at attracting cheap funds and their use in accordance with the terms of the established lending policy, taking into account the minimum risk and maximum profit. As you know, the main source of income of banks is the profit from lending. In this regard, the main problem facing the bank’s management today is the effective management of the bank’s loan portfolio. Against the background of the negative impact of the global financial crisis, the formation of an optimal loan portfolio of the bank is of particular importance in order to increase the efficiency of its activities through the appropriate credit policy. Improving the quality of lending and optimizing the structure of banks’ loan portfolios are traditionally relevant in research, as lending has always been and will remain the main economic function of banks. The article describes each stage of credit activity, which consists of sequential actions. The definition of "credit portfolio quality" as a complex concept that characterizes the efficiency of credit portfolio formation in order to determine its profitability and the degree of credit risk is considered. The development of measures to optimize credit risk is one of the ways to improve the credit process and the entire system of managing the financial flows of the bank as a whole, not just banking risks. The factors influencing the formation of credit risk are analyzed. The main approaches to credit portfolio management in a commercial bank are characterized. It is proved that most of the constructed and implemented models for optimizing the loan portfolio are based on the criterion of risk-return (rather than profitability-risk) and have certain limitations and difficulties in practical application. The quality of the loan portfolio determines the bank’s capabilities in its functioning in the market of credit products, which affects the level of its lending activity and the possibility of restoring positions in the credit market. The process associated with lending is determined by the quality of credit work in banks. Statistics on the functioning of commercial domestic and foreign banks indicates that a well-organized credit process, a well-formed loan portfolio and credit policy will ensure the bank’s prosperity in the future

Ultrahigh-power supercapacitors from commercial activated carbon enabled by compositing with carbon nanomaterials

Ultrahigh power is needed beyond the state-of-the-art supercapacitors for emerging technologies. Towards this goal, nanostructured carbon materials have been extensively studied but unfortunately encountered with the difficulty in practical applications, which is largely due to their limited packing densities. In this work, we utilize a highly dense commercial activated carbon to develop high-rate nanocomposite electrodes and ultrahigh-power supercapacitors by compositing activated carbon with carbon nanomaterials, including zero-dimensional carbon black, one-dimensional carbon nanotube, and two-dimensional graphene. Enabled by the mixed packing (forming a unique point-to-line-to-plane contact morphology), diverse electrical conduction (forming a well-interconnected three-dimensional electrical conduction network), and varied porosity (forming a well-defined hierarchical porous structure) from these multiple constituents, the optimized quaternary nanocomposite electrode possesses a good combination of facilitated electron transport and enhanced ion diffusion and thus a twofold higher rate capability (capacitance retention: 83.3% vs. 28.9% at 80 A g−1 vs. 0.5 A g−1), twofold higher power density (84.1 kW kg−1 vs. 41.9 kW kg−1), and superior high-rate cycling stability (capacitance retention: 80.2% vs. 65.9% after charge/discharge at 10 A g−1 for 30,000 cycles) than its conventional activated carbon counterpart, while its high volumetric power density (50.5 kW L−1) strengthens its practical usefulness. Our research represents a novel approach to fabricate commercially available materials into practically useful ultrahigh-power supercapacitors at low cost, which may also be employed as a universal strategy to develop high-performance nanocomposites to benefit a wider range of application technologies.

Physical parameters identification for full‐scale ten‐story reinforced concrete building with degrading tri‐linear model by modal iterative error correction method

AbstractTo assess the post‐earthquake seismic safety of buildings, it is crucial to predict seismic response, and it is necessary to set the appropriate physical parameters of the response analysis model. Numerous methods have been proposed to identify physical parameters. However, most of them are limited to linear systems, and previous researches on nonlinear systems have difficulties in practical applications. In this paper, a nonlinear response analysis model is identified for a full‐scale ten‐story reinforced concrete building with the degrading tri‐linear stiffness model by the modal iterative error correction (MIEC) method, and the accuracy of this technique is discussed by comparing with the shaking table test.

Design Low Order Robust Controller for the Generator’s Rotor Angle Stabilization PSS System

The electrical system's problem stabilizes the electrical system with three primary parameters: rotor angle stability, frequency stability, and voltage stability. This paper focuses on the problem of designing a low-order stable optimal controller for the generator rotor angle (load angle) stabilization system with minor disturbances. These minor disturbances are caused by lack of damping torque, change in load, or change in a generator during operation. Using the RH∞optimal robust design method for the Power System Stabilizer (PSS) to stabilize the generator’s load angle will help the PSS system work sustainably under disturbance. However, this technique's disadvantage is that the controller often has a high order, causing many difficulties in practical application. To overcome this disadvantage, we propose to reduce the order of the higher-order optimal robust controller. There are two solutions to reduce order for high-order optimal robust controller: optimal order reduction according to the given controller structure and order reduction according to model order reduction algorithms. This study selects the order reduction of the controller according to the model order reduction algorithms. In order to choose the most suitable low-order optimal robust controller that can replace the high-order optimal robust controller, we have compared and evaluated the order-reducing controllers according to many model order reduction algorithms. Using robust low-order controllers to control the generator’s rotor angle completely meets the stabilization requirements. The research results of the paper show the correctness of the controller order reduction solution according to the model order reduction algorithms and open the possibility of application in practice. Doi: 10.28991/esj-2021-01299 Full Text: PDF

Electrostatic adsorption and removal mechanism of ochratoxin A in wine via a positively charged nano-MgO microporous ceramic membrane

Ochratoxin A (OTA) is a very important mycotoxin. However, there are few studies on the removal of OTA in wine because of the great influence on product quality and difficulty in practical application. A nano-MgO-modified diatomite ceramic membrane (MCM) with a high positive charge was prepared and applied to remove OTA in wine. The isotherm adsorption between the positively charged membrane and OTA was in accordance with the Langmuir model, with a maximum adsorption capacity of 806 ng/g at 25 °C. All of the changes in adsorption enthalpy (ΔH), adsorption free energy (ΔG) and adsorption entropy (ΔS) were negative, which indicated that the combination of nano-MgO MCM and OTA was a spontaneous exothermic and nonspecific physical adsorption process. The concentrations of OTA in adsorption-treated wines were lower than 2 μg/kg, and the removal rates exceeded 92%. After OTA removal, the composition of wines was preserved to some extent.

Cramer-Rao lower bounds of target positioning estimate in netted radar system

Netted radar system has received wide attention due to its higher target detection probability, better target localization and tracking performance than the monostatic/bistatic radar systems. According to the complexity and difficulty of practical application, netted radar system can be divided into simply netted radar system with decentralized processing, traditional netted radar system with centralized data and information fusion processing. Without taking account of the SLP among multiple nodes, the traditional netted radar system has the definite radar coverage and target localization performance after deployment, which means it is not flexible enough to configure on demand in the search phase and localization phase. To further improve performance and flexibility, a novel netted radar system, across which signal, data and information can be shared and integrated to, is considered. In the novel netted radar system, the topology architecture, transmit receiving node, transmitted signal form and other resources are selected and reconstructed according to the task to be needed. To analyze the localization performance of the novel netted radar system, the Cramer–Rao lower bounds (CRLBs) of the target positioning estimate mean square errors (MSEs) are deduced for the coherent-processing (CP), noncoherent-processing (NCP) and data-level processing (DLP) in this paper. Then, the target localization performances of the novel netted radar system with different topology architectures are compared and analyzed.

Structural damage identification using strain mode differences by the iFEM based on the convolutional neural network (CNN)

Structural damage identification is the key problem of structural health monitoring (SHM), which has been widely used in many fields. Traditional damage detection methods usually require complete measured data and modal information before and after damage, resulting in difficulty in practical applications. Strain-based damage indicators have attracted widespread attention due to their high sensitivity to local damage. In this paper, using the inverse finite element method (iFEM), a damage identification method based on strain mode differences is proposed. The global strain data can be performed only by the limited strain measuring points, which will greatly improve the efficiency of direct use of strain data to achieve damage detection, and it can identify and locate the damage just using the post-damage strain modal data. It is noteworthy that this paper investigates the application of the convolutional neural network (CNN) training with input data contaminated by random noises in structural damage estimation. The results show that the CNN-based damage detection method using strain mode differences as the inputs has a high accuracy under different damage conditions, i.e., the proposed method not only has a significant damage localization ability, but also has a relatively high damage quantification prediction accuracy, which provides a new research approach for the structural health monitoring system.

High-performance CdSe/CdS@ZnO quantum dots enabled by ZnO sol as surface ligands: A novel strategy for improved optical properties and stability

Colloidal semiconductor quantum dots (QDs) have attracted great attention in field of optoelectronic devices. However, the surface organic ligands of QDs involving in optical instability and limited passivation remain challenging, thus bringing additional difficulties in practical application. Here, the high-performance CdSe/CdS@ZnO QDs were successfully prepared by ZnO sol as surface ligands. Importantly, this kind of CdSe/CdS@ZnO QDs maintained the typical advantages of conventional QDs, such as superior monodispersity and long-term storage stability in solution. Because of the effective surface passivation provided by inorganic sol ligands and the deionization effect that electron transferring from surface state of QDs to ZnO acceptor, CdSe/CdS@ZnO QDs showed the remarkably enhanced photostability and biexciton lifetime, as well as further suppressed Auger process and PL blinking. Meanwhile, the CdSe/CdS@ZnO QDs demonstrated PL thermal stability much higher than that of pristine CdSe/CdS QDs under heating to 100 °C, which was efficiently improved 3 times that from ~20% to ~63% of their initial emission intensity. Moreover, a stable amplified spontaneous emission process was observed in CdSe/CdS@ZnO QDs film and still retained a lower ASE threshold (~28 μJ cm−2). Finally, we successfully fabricated a high-performance vertical cavity surface-emitting laser based on CdSe/CdS@ZnO QDs, which presented spatially directional single-mode lasing output with an ultralow threshold of ~3.3 μJ cm−2. We believe that this work could not only enrich the family of surface ligands passivated semiconductor QDs but also provide a novel strategy towards constructing stable and functionalized colloidal nanomaterials for all-inorganic optoelectronic devices.

Analytical and experimental study on Van der Pol-type and Rayleigh-type equations for modeling nonlinear aeroelastic instabilities

An empirical modeling of nonlinear aerodynamic force during aeroelastic instabilities, that is, vortex-induced vibration (VIV), galloping and flutter, is necessary in the estimation of vibration responses. Previous works on single-degree-of-freedom (SDOF) models suggest that nonlinear forms (Van der Pol or Rayleigh types) differ from section to section, which causes difficulty in practical application. Analytical evidences in this study have clarified that Van der Pol-type and Rayleigh-type models are equivalent in the amplitude-dependent aerodynamic damping; their difference lies in the higher-order harmonic responses. An identification algorithm of aerodynamic parameters is proposed to improve the robustness of aerodynamic parameters and guarantee the equivalence of both model types. Wind-tunnel tests of typical aeroelastic instabilities indicate that higher-order harmonic responses are small for VIV, galloping, and early-stage flutter instability when compared with the fundamental components due to weak nonlinearity. Van der Pol-type and Rayleigh-type models are both applicable until the flutter amplitude grows excessively large. It is clear that both model types are suitable for any section shape when use the proposed method of aerodynamic identification, and thus can be treated as a universal model for estimating the vibration amplitudes of nonlinear aeroelastic instabilities.

Гарантии защиты прав адвокатов при проведении обыска в жилых и служебных помещениях: проблемы законодательного регулирования и практического применения

The article is dedicated to the problem of effectiveness of the guarantees ensuring professional rights of advocates during investigative actions in their residential and office premises. The authors analyze standards developed by the European Court of Human Rights for the protection of the advocates’ right to private and family life and assess the conformity of domestic legal regulations with these standards. Reviewing the provisions of Article 450.1 of the Russian Code of Criminal Procedure, the authors come to the conclusion that the difficulties in practical application of the mentioned guarantees in the Russian law are caused by the imperfection of legislation under consideration, including by unclear conditions for the application of relevant provisions, insufficient detailing of the powers of representatives of lawyers’ associations taking part in the investigative actions, etc. Furthermore, it appears that the shortcomings of regulation governing the sphere in question condone violations not only by the investigative authorities but also by the advocates themselves. Hence, the authors maintain that the legal provisions under consideration require further amendments, including those proposed in this article.

Parameter identification for nonlinear structural model using modal iterative error correction method

In seismic response analysis of buildings against strong earthquakes, it is very important to appropriately set the model parameters of the building. Numerous methods have been proposed to identify these parameters. However, most are based on only linear analysis; some studies using nonlinear analysis noted difficulty in practical application. In the present study, the Modal Iterative Error Correction (MIEC) method is proposed to identify the nonlinear seismic parameters of buildings. The accuracy of this technique is evaluated based on shaking table test results.

Research on Face Recognition Algorithm Based on HOG Feature

As a common biometric recognition technology, face recognition is also an important research direction in the field of computer. Although compared with the initial research, the current research has made great progress, but there are still many difficulties in practical application. In this paper, by extracting HOG features, after introducing the detailed steps of PCA and LDA subspace feature extraction methods, dimensionality reduction feature extraction method combing PCA with LDA is applied to extract face features. This method first uses PCA to reduce the dimension of face features, and then uses LDA for linear discriminant analysis. Finally, the feature extraction methods based on PCA and LDA are tested and compared in FERET standard face database and CAS-PEAL database of Chinese Academy of Sciences

Circumstances Excluding Criminality of an Act in the Light of the General Theory of Law

The paper is devoted to an actual problem of the legal theory and practice, namely: the institution of circumstances excluding criminal nature (criminality) of an act (Chapter 8 of the Russian Criminal Code). As a manifestation of criminal and legal compromise steadily strengthening its position in domestic criminal legislation, this legal phenomenon is intended to encourage citizens to commit actions that contribute to localization or minimization of threats to the interests of the individual, society and the state protected by the law. At the same time, despite seemingly clear legislative enactment, the institution of circumstances precluding the criminal nature of an act evokes hot scientific debates. Among forensic scientists there is no uniform opinion concerning the legal nature of the criminal law institution as a whole and some of the individual types of circumstances constituting the institution under consideration, in particular. The legal literature substantiates the idea of the need to expand the legislative list of such circumstances. Investigators and judges often face difficulties in practical application of the rules enshrined in articles of Chapter 8 of the Criminal Code (especially provisions concerning necessary defense, extreme necessity, reasonable risk). The reasons for theoretical and practical problems related to the circumstances excluding the criminal nature of the act are largely preconditioned by the insufficient research of the institution under consideration in the general theory of law. This fundamental theoretical legal science lacks general legal equivalents of the criminal law concepts “criminality of the act”, “circumstances excluding criminality of the act.” It is proposed to introduce into scientific circulation the general legal equivalent of the concept “criminality of the act” — “delinquency of the act”, representing the set of such features of the offense as public harm, wrongfulness, culpability and punishability. This new legal design will allow us to investigate the phenomenon of circumstances excluding criminality of the act in the light of a general theory of law, to determine the possibility and limits of their subsidiary application in various branches of law. Thus, categories of circumstances excluding criminal, administrative, civil. disciplinary delinquency of acts will acquire the right to exist in differnt legal sciences and relevant branches of law. This, in turn, will contribute to improving the effectiveness of protection of rights, freedoms and legitimate interests of the individual, ensuring the interests of the society and the state.

VINet: A Visually Interpretable Image Diagnosis Network

Recently, due to the black box characteristics of deep learning techniques, the deep network-based computer-aided diagnosis (CADx) systems have encountered many difficulties in practical applications. The crux of the problem is that these models should be explainable the model should give doctors rationales that can explain the diagnosis. In this paper, we propose a visually interpretable network (VINet) which can generate diagnostic visual interpretations while making accurate diagnoses. VINet is an end-to-end model consisting of an importance estimation network and a classification network. The former produces a diagnostic visual interpretation for each case, and the classifier diagnoses the case. In the classifier, by exploring the information in the diagnostic visual interpretation, the irrelevant information in the feature maps is eliminated by our proposed feature destruction process. This allows the classification network to concentrate on the important features and use them as the primary references for classification. Through a joint optimization of higher classification accuracy and eliminating as many irrelevant features as possible, a precise, fine-grained diagnostic visual interpretation, along with an accurate diagnosis, can be produced by our proposed network simultaneously. Based on a computed tomography image dataset (LUNA16) on pulmonary nodule, extensive experiments have been conducted, demonstrating that the proposed VINet can produce state-of-the-art diagnostic visual interpretations compared with all baseline methods.

Pupil function engineering for surface plasmon microscopic interferometry

Interferometric surface plasmon microscopy (SPM) measures plasmonic properties of nano-materials using the so-called V(z) curves. However, experimentally acquired V(z) curves suffer from extremely poor magnitude of interference signals, severe disturbing oscillations and background noises, which show difficulties in practical applications and could not be properly explained by the conventionally ray-model-based principle. The situation is more severe when operating confocal surface plasmon interferometry. This work revisits the conventional principle of interferometric SPM and investigates the fundamental reasons that cause the disagreements between expected V(z) effect and actually acquired V(z) curves. A modified ray model is presented to properly interpret the principle of confocal SPM. We demonstrate how the pupil function engineering can effectively suppress both the systematically disturbing oscillations and severe background noises. The experimental setup is established. Experimental verification and related analysis are also demonstrated.

A simple protocol for measuring device independent quantum key distribution based on hybrid encoding

Quantum key distribution technology refers to a method to share keys between communication parties by transmitting quantum states in public channels. Although unconditional security is the main advantage of QKD, its application prospect has been controversial in practical implementation due to the potential security risks caused by device imperfections. Fortunately, the measurement device independent quantum key distribution protocol removes the vulnerability of all measurement devices and greatly improves the practical security of the quantum key distribution system. However, the security key rate of this protocol is still lower than that of other quantum key distribution protocols. At present, using high-dimensional coding to improve the performance of the quantum key distribution protocol has been proved in theory and experiment, and recently, it has been proposed to use high-dimensional coding to improve the performance of measurement device independent quantum key distribution protocol, but because these protocols have higher requirements for the laboratory equipment performance, that the high-dimensional encoding is applied to the aforementioned protocol still has many difficulties in practical application. In this paper, we propose a hybrid coding based on the polarization and two-degree phase of freedom measurement device independent quantum key distribution protocol. In the first place in an ideal case, we introduce in detail the protocol decoding rules, then introduce 4intensity decoy-state method to solve the problem of actual light source multiphoton, in addition we also consider the statistical fluctuation effect under the condition of limited code length, channel loss, actual dark count of single photon detector and detection efficiency problem. Finally, the optimal security code rate and its corresponding optimal parameters are obtained by full parameter optimization method, And the numerical simulation results show that the security key rate of this protocol is increased by 50% by considering the practical implementation. We point out that compared with other measurement device independent quantum key distribution protocol, the proposed agreement requires local users only to have a phase encoding device and a polarization coding device, and 4 single photon detectors for detecting side. The proposed device can use the existing experimental condition, beyond that, compared with the time encoding based high dimensional measurement device independent quantum key distribution protocol, the proposed protocol possesses the advantage that the rate of system security key can be increased without increasing the repetition frequency of users. It is proved that this protocol has great application value in the future field of quantum communication, especially, in the field of quantum network communication.

Coupling dynamic stiffness identification of mechanical assembly with linear and planar connection by the indirect scheme of inverse substructuring analysis

Mechanical assembly is an important process in manufacturing electromechanical products and it directly affects the dynamic quality of a whole product. The traditional inspection and analysis of mechanical assembly quality mainly focuses on the “static quality”, such as the shape accuracy and dimensional coordination, while ignoring its “dynamic quality”, which is incomplete estimation on the assembly quality. Meanwhile, the assembly coupling dynamic stiffness is a key determinant of the dynamic quality of mechanical assembly. To overcome test operation difficulties in practical application which is caused by the direct scheme of inverse substructuring of the mechanical assembly coupling dynamic stiffness, it needs to discrete the non-ideal mechanical assembly connection interface including linear and planar connection interface so as to apply two kinds of indirect method of inverse substructuring analysis based on frequency response function (FRF) spectrum to recognize its coupling dynamic stiffness. The experimental models of mechanical assembly for the more practical linear and planar connections are designed, and the practicability of applying these two methods to recognize the dynamic stiffness after assembly coupled is verified.

Crop Organ Segmentation and Disease Identification Based on Weakly Supervised Deep Neural Network

Object segmentation and classification using the deep convolutional neural network (DCNN) has been widely researched in recent years. On the one hand, DCNN requires large data training sets and precise labeling, which bring about great difficulties in practical application. On the other hand, it consumes a large amount of computing resources, so it is difficult to apply it to low-cost terminal equipment. This paper proposes a method of crop organ segmentation and disease recognition that is based on weakly supervised DCNN and lightweight model. While considering the actual situation in the greenhouse, we adopt a two-step strategy to reduce the interference of complex background. Firstly, we use generic instance segmentation architecture—Mask R-CNN to realize the instance segmentation of tomato organs based on weakly supervised learning, and then the disease recognition of tomato leaves is realized by depth separable multi-scale convolution. Instance segmentation algorithms usually require accurate pixel-level supervised labels, which are difficult to collect, so we propose a weakly supervised instance segmentation assignment to solve this problem. The lightweight model uses multi-scale convolution to expand the network width, which makes the extracted features richer, and depth separable convolution is adopted to reduce model parameters. The experimental results showed that our method reached higher recognition accuracy when compared with other methods, at the same time occupied less memory space, which can realize the real-time recognition of tomato diseases on low-performance terminals, and can be applied to the recognition of crop diseases in other similar application scenarios.

Ellipsoidal Approximation of Distributions and Its Applications

Analytical methods of the mathematical statistics of random vectors and matrices based on the parametrization of the distributions are widely used. These methods permit to design practically simple software when it is possible to have the definite information about analytical properties of the distributions under research. The main difficulty in practical applications of the methods based on the parametrization of the distributions is the rapid increase of the number of equations for the moments, the semiinvariants or the coefficients of the truncated orthogonal expansions of the dimension or the state vector (extended in the general case) and the maximal order of the moments involved. The number of equations for the parameters becomes exceedingly large in such cases. For structural parametrization and/or approximation of the probability densities of the random vectors we shall apply the ellipsoidal densities, i.e. the densities whose planes of the levels of equal probability are similar concentric ellipsoids (the ellipses for two-dimensional vectors, the ellipsoids for three-dimensional vectors, the hyperellipsoids for the vectors of the dimension more than three). In particular, a normal distribution in any finite-dimensional space has an ellipsoidal structure. The distinctive characteristics of such distributions consists in the fact that their probability densities are the functions of positively determined quadratic form where is an expectation of the random vector is some positively determined matrix. Ellipsoidal approximation method (EAM) cardinally reduces the number of parameters till ( ) where being the number of probabilistic moments. While using ellipsoidal linearization method (ELM) we get Basic EAM and ELM foundations and applications to problems of mathematical statistics and ellipsoidal distributions with invariant measure in populational Volterra differential stochastic nonlinear systems are considered.

A literature survey on kinship verification through facial images

Kinship verification is an emerging task in computer vision which aims at finding out whether there is a kin relation between given identities through their facial images. Applications of kinship verification include image annotation, children adoption, and social media analysis, etc. However, kinship verification through facial images is challenging because facial images usually contain high intra-variances, which vary from genetic, age and gender difference. Over the past decade, more and more effective methods have emerged. This paper aims at categorizing and evaluating these methods systematically. We attach great importance to the difficulties in practical applications of kinship verification, and review the prominent algorithms from the perspective of learning more efficient models with more diverse kin relations. Then we further show how to develop an efficient and robust kinship verification system. Finally we present several potential directions for future research.