Traditional Problems Research Articles

Kim and the Pairing Problem for Dualism

The philosophical history of metaphysics of mind can be narrowed into two problems: Mind and body causation and issues of the self or persons. Due to the rise of the scientific revolution the nature of mental states and its possessors has been reduced to brain and cognitive functioning or eliminated instead of the ontological basic substance of a soul. The other criticism of soul identity or substance dualism is the problem of mental causation. In The Blackwell Companion to Substance Dualism (2018), Jaegwon Kim argues against the intelligibility of Cartesian dualism and further extends that argument to any form of substance dualism by raising the question of mental causation or the traditional mind-body problem. His main attack comes from the essence of mind and the causal closure of the physical, together these provide an argument against the non-physical view of persons. The question, “can mental events cause physical events?” Is a problem for the dualist which he calls “the pairing problem.” Since causation requires a spatiotemporal relation between two bodies, and mind and body are distinct substances or properties, there’s no cause-and-effect pairing relation between minds and physical objects or bodies. Thus, according to Kim, the essence of an immaterial thinking substance, such as a soul, is unintelligible and should be rejected since it fails to answer the pairing problem. However, Kim has a misunderstanding of substance dualist views of the independent ontological status of a substantial self or soul. Further, Kim’s challenge does not take into account a causal powers ontology in which primitive is the free agentive causal subject. I’ll argue that a soul, though embodied, is a non-material primitive substance that has basic faculties to exemplify mental properties. One of the faculties of the soul is the instantiation of active agency. Further, the postulation of Gods existence, having a metaphysical internal structure and powers, is grounds for the existence of a soul with its own metaphysical, unified structure in which the dispositional properties of consciousness are located and exemplified. I conclude that mental causation is a coherent notion especially in light of the active powers of agent causation. Thus, Kim’s problem of mental causation becomes no problem at all.

A selectively calibrated derivation technique and generalized fuzzy TOPSIS for semiconductor supply chain localization assessment

There is a localization wave in the semiconductor industry for pushing wafer foundries to transfer their production capacity to where chip designers are located. The main reasons for the localization of semiconductor supply chains include the US–China trade war, geopolitics, COVID-19, the Ukraine–Russia war, and rising environmental awareness. However, this is a challenging task since some of the issues considered in traditional facility location selection problems are no longer decisive factors. To overcome this challenge, this study proposes the selectively calibrated derivation technique (SCDT)-generalized fuzzy technique for order preference by similarity to ideal solution (GFTOPSIS) approach to help wafer foundries select suitable facility locations for customer-required capacity localization. The proposed SCDT-GFTOPSIS approach has been applied to a real case to validate its effectiveness. According to the experimental results, SCDT effectively improved the accuracy of approximating the fuzzy priorities of criteria by reducing the mean absolute deviation (MAD) by 81%. In addition, the most suitable location for the facility was in Singapore, where the support of the local government was higher, while requiring less total investment and subject to less political and war risk. However, the final selection was subject to further negotiations.

Multi-Label Classification of Chinese Rural Poverty Governance Texts Based on XLNet and Bi-LSTM Fused Hierarchical Attention Mechanism

Hierarchical multi-label text classification (HMTC) is a highly relevant and widely discussed topic in the era of big data, particularly for efficiently classifying extensive amounts of text data. This study proposes the HTMC-PGT framework for poverty governance’s single-path hierarchical multi-label classification problem. The framework simplifies the HMTC problem into training and combination problems of multi-class classifiers in the classifier tree. Each independent classifier in this framework uses an XLNet pretrained model to extract char-level semantic embeddings of text and employs a hierarchical attention mechanism integrated with Bi-LSTM (BiLSTM + HA) to extract semantic embeddings at the document level for classification purposes. Simultaneously, this study proposes that the structure uses transfer learning (TL) between classifiers in the classifier tree. The experimental results show that the proposed XLNet + BiLSTM + HA + FC + TL model achieves micro-P, micro-R, and micro-F1 values of 96.1%, which is 7.5~38.1% higher than those of other baseline models. The HTMC-PGT framework based on XLNet, BiLSTM + HA, and transfer learning (TL) between classifier tree nodes proposed in this study solves the hierarchical multi-label classification problem of poverty governance text (PGT). It provides a new idea for solving the traditional HMTC problem.

Discrimination in labor relations: economic approach and labor law

The problem of discrimination in labor relations is a traditional problem not only for jurisprudence, but also for economic science. This article gives the author’s analysis of the views on discrimination of modern classics of legal science, as well as economists, Nobel Prize winners in economics G. Becker, D. Akerlof, A. Sen, J. Stiglitz. The conclusion is made about the significance of these views in determining the labor and legal policy of the state in the field of ensuring, equality and prohibition of discrimination in labor relations.

Explanatory efficiency: A framework for analyzing the dynamic properties of explanatory games

In this paper I will discuss the problem of evaluating dynamic properties of the procedural rules that govern science. I will propose a novel framework for evaluating dynamic properties of such rules. This framework is based upon an analogy from New Institutional Economics. I will argue that the concept of ‘adaptive efficiency’, as it has been developed by Douglass North, solves a problem in economics that is analogous to the problem of evaluating dynamic properties of the procedural rules that govern science. I will propose to apply the main ideas underlying this concept to Chrysostomos Mantzavinos’s theory of Explanatory Games. Based on these ideas, I will develop the concept of ‘explanatory efficiency’. This concept is meant to provide the means to evaluate the dynamic properties of Explanatory Games. I will argue that the proposed analogy also motivates more general applications of New Institutional Economics to traditional problems of philosophy of science.

Culture — the brdge that could not be blown up

Not so long ago one of the main and traditional problems of Russia has been that culture was not considered to be a subject of political life. Before the bill "About Culture” each region in the country used to live in different cultural context and to understand aspects of culture in different manners. At the edges of 20th–21st cc. the understanding of the problems of Russia-Caucasian social and cultural communication actualized. North Caucasian region is a complicated system of very many cultures. It was a contact zone and at the same time a kind of a barrier among civilizations and empires in The Mediteranian region, South-Western Asia and Eastern Europe. The today culture of North Caucasian region has been formed as a result of the dialogue among Caucasian mountain, Islam and Russian civilizations and cultures, and also the processes of modernization during 20th-21-st centuries. The problem of preserving of cultural traditions is a central one in "ases of state culturally politics" (2014). Cultural bridges among the peoples and countries should be kept even in times of war conflicts and military actions.

Unsupervised Financial Fraud Detection Using Low-rank Recovery

Many outlier detection methods have been studied and applied to financial fraud detection problems in recent years. These traditional financial fraud detection problems (such as classification-based methods) often suffer performance degradation caused by imbalanced data. Even worse, the frauds often destroy the low dimensional structure of the sub-space on which the intrinsic samples are distributed, and the traditional financial fraud detection methods fail to study the low rankness prior in the intrinsic samples when outliers emerge. We give an effective unsupervised financial fraud detection algorithm based on a low-rank recovery method to solve these issues. Our work has several folds: (1) We adopt the Outlier Pursuit (OP) algorithm and its non-convex variants, which can study the low rankness within the intrinsic samples and detect the outliers without supervision. (2) We solve OP and its non-convex variants by combining Alternating Direction Method Of Multipliers (ADMM) with Generalized Accelerating Iterative Algorithm (GAI). (3) We evaluate the effectiveness of the OP-based methods and compare methods on three data sets, including the German Credit Data, Insurance Company (TIC) Benchmark, and IEEE-CIS fraud Detection data set. The related code is available at https://github.com/jzheng20/FinancialFraudDetectionViaOP.git.

Location First Non-Maximum Suppression for Uncovered Muck Truck Detection

Uncovered muck truck detection aims to detect the muck truck and distinguish whether it is covered or not by dust-proof net to trace the source of pollution. Unlike traditional detection problem, recalling all uncovered trucks is more important than accurate locating for pollution traceability. When two objects are very close in an image, the occluded object may not be recalled because the non-maximum suppression (NMS) algorithm can remove the overlapped proposal. To address this issue, we propose a Location First NMS method to match the ground truth boxes and predicted boxes by position rather than class identifier (ID) in the training stage. Firstly, a box matching method is introduced to re-assign the predicted box ID using the closest ground truth one, which can avoid object missing when the IoU of two proposals is greater than the threshold. Secondly, we design a loss function to adapt the proposed algorithm. Thirdly, a uncovered muck truck detection system is designed using the method in a real scene. Experiment results show the effectiveness of the proposed method.

Singular Optimal Linear Quadratic Regulator of Switched Systems

In this paper, we will investigate the singular linear quadratic regulator (LQR) problem of switched linear system in finite time horizon. The proposed method is transforming into a switched LQR problem by adopting linear transformation. Next, we adopt an embedding transformation method to convert the switched LQR problem to a traditional optimal control problem, so the bang-bang-type solution of the embedded optimal control problem in finite time is the optimal solution to the switched LQR problem. The switching sequence of modes and the switching instants can be calculated by solving a closed-form optimal switching condition. The optimal state feedback control law is determined simultaneously. Then, by solving a sequence of Riccati equation, we find some conditions that ensure switched LQR problem can be convert to the singular LQR problem. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed method.

The capacitated location problem of precast concrete component factory

The location and capacity of precast concrete component factories (PC component factories) are not only the key factors for manufacturers to gain competitive advantage, but also the important factors affecting the operational efficiency of the prefabricated construction supply chain. This paper takes the capacitated location problem of PC component factories as the research object. Drawing on the model of traditional capacitated plant location problem, the model of capacitated location problem of PC component factories is constructed by setting the optional production scale by stages. According to the characteristics of this model, the optimal strategy of location is determined by using the Tabu search algorithm. Taking the location problem of PC component factory in the Beijing-Tianjin-Hebei region as the object, the calculation example is designed, in which the influence of the distance parameters on the results of location problem is analyzed. The results can make the configuration of regional PC component factories more reasonable and balanced.

A Cooperative Localization Method for Leader–Follower Multiple UAVs Using Continuous Relative Ranging Information

Cooperative localization (CL) utilizing multiple unmanned aerial vehicles (UAVs) has become the current development trend and research hotspot. The traditional distance-based CL method typically uses principle of the spherical intersection to achieve UAV high-precision positioning. However, this distance-based CL strategy requires several leader UAVs at the known positions. Thus, a cooperative localization method for leader–follower multiple UAVs using continuous relative ranging information is proposed in this paper. Aiming at the UAV formation consists of a leader UAV node with the known position and at least a follower UAV that needs to be located. Using the Inertial short-time high-precision relative position constraint and the continuous relative distance constraints with the leader UAV nodes, the closed-form solution of follower UAV’s three-dimensional position can be obtained using spherical intersection principle. On this basis, we derive and construct follower UAV’s position observation equation. The developed strategy requires a single known position leader UAV node to realize high-precision CL, which can effectively solve the traditional distance-based collaborative location problem in case the number of leader UAVs is small. The simulation and experimental results demonstrate that the proposed method significantly improves follower UAV’s positioning accuracy, and neglects the limitation of the traditional distance-based CL method on the number of leader UAV nodes at known positions.

Доверие современной российской молодежи политическим институтам в условиях кризисных потрясений

Introduction. The article is devoted to the analysis of the interaction between government and society in modern Russia, expressed in the phenomenon of trust. The focus of the authors’ attention is directed to the study of the impact of crisis upheavals (the COVID-19 pandemic and the implementation of the Special Military Operation in Ukraine) on the change in the trust of the population of the Russian Federation in the main political institutions. The relevance of the study is determined by the need to fix the existing forms of interaction between the authorities and society as well as identify the prospects for changing these practices in the perspective of society’s transition to a post-crisis state. Methods and materials. The methodological basis of the study was the neo-institutional approach, which made it possible to present trust because of the activity of political institutions in building and observing the “rules of the game.” The empirical basis of the study is public opinion polls conducted by the largest Russian sociological centers. Analysis and results. Trust in political institutions is presented as an important phenomenon of civilized societies, characterizing the importance of rules rather than specific personalities. The study revealed that in Russia, crisis situations, which are institutionally determined trajectories caused by external shocks that change the “rules of the game” that have developed in society and forms of communication with the authorities, are a condition for an exponential growth of trust (both generalized and institutional). At the same time, during crises, an increase in the level of trust is observed even for institutions that are traditionally criticized by most of society (such as the government and the State Duma). The youth, being reactionary and variable in their political behavior, show increased trust in political institutions. However, if adult trust is based on emotional hope for the future, youth trust is usually based on rational grounds. Yet a sharp increase in trust in the main political institutions during crises can be replaced by the same rapid decline in the conditions of “normality” when the traditional problems of socio-economic development again come to the fore on the agenda formed by society. Authors’ contributions. S.I. Morozov carried out an analysis of studies on institutional trust in modern Russia, chose and substantiated the theoretical and methodological framework of the work, and also formed the general concept of the study. K.M. Makarenko summarized and analyzed empirical data on the research topic, substantiated the role and impact of crisis shocks on institutional trust in the Russian Federation, and formulated the main conclusions of the work.

Ureido Hyperbranched Polymer Modified Urea-Formaldehyde Resin as High-Performance Particleboard Adhesive.

The performance of urea-formaldehyde (UF) resin and its formaldehyde emission is a natural contradiction. High molar ratio UF resin performance is very good, but its formaldehyde release is high; low molar ratio UF resin formaldehyde release is reduced, but the resin itself performance becomes very bad. In order to solve this traditional problem, an excellent strategy of UF resin modified by hyperbranched polyurea is proposed. In this work, hyperbranched polyurea (UPA6N) is first synthesized by a simple method without any solvent. UPA6N is then added into industrial UF resin in different proportions as additives to manufacture particleboard and test its related properties. UF resin with a low molar ratio has a crystalline lamellar structure, and UF-UPA6N resin has an amorphous structure and rough surface. The results show that internal bonding strength increased by 58.5%, modulus of rupture increased by 24.4%, 24 h thickness swelling rate (%) decreased by 54.4%, and formaldehyde emission decreased by 34.6% compared with the unmodified UF particleboard. This may be ascribed to the polycondensation between UF and UPA6N, while UF-UPA6N resin forms more dense three-dimensional network structures. Finally, the application of UF-UPA6N resin adhesives to bond particleboard significantly improves the adhesive strength and water resistance and reduces formaldehyde emission, suggesting that the adhesive can be used as a green and eco-friendly adhesive resource for the wood industry.

ELECTRIC VEHICLE ROUTING PROBLEM USING ADAPTIVE SIMULATED ANNEALING

Road transport is a major CO2 emission contributor globally. To tackle the challenge of reducing world carbon emissions, alternative technologies for the automobile industry are widely researched. The automotive industry has started to shift from Internal combustion engine (ICE) vehicles to electric vehicles (EVs), where EVs are the future of the automotive industry in terms of reducing greenhouse gas emissions and air pollution. EV manufacturers are continuously looking for opportunities to optimize the supply chain processes, aiming for supply chain resilience. In this study, we present an Electric Vehicle Routing Problem (EVRP) to achieve the best decision, which is an extension of the traditional Vehicle routing problem (VRP) which in particular finding the shortest route for electric vehicles. The objective function is to find the best travel route that minimizes travel distance. Each route serves a set of customer nodes that starts and ends at a given depot node. We take battery capacity and charging stations as the constraints. In addition, the use of homogenous fleets and single depot are considered in this paper. A hybrid metaheuristic approach is used to find the best solution with the Adaptive Simulated Annealing algorithm. The use of adaptive in simulated annealing generates a higher probability of finding the best operators, which results in better solutions. A comparison of results from various metaheuristic methods is also presented in this paper to get the best method for the EVRP based on a benchmark dataset. This paper ends with recommendations for creating a routing plan that is resilient to disruptions to distribution.

Low-cost Fermentation of Polyhydroxyfatty Acid Esters

With the depletion of traditional fossil energy and environmental problems, there is an urgent need for alternative materials. Biosynthesis not only achieves low-carbon green economy, but also reduces energy consumption. Polyhydroxyfatty acid ester is a kind of material with excellent performance, but the production cost is high, mainly due to the high cost of fermentation carbon source, fermentation process and other factors. Using waste as substrate not only reduces fermentation costs but also solves environmental problems. On the other hand, mixed strains can be used simultaneously to reduce the cost of fermentation.

Alternative metrics, traditional problems? Assessing gender dynamics in the altmetrics of political science

Altmetrics are an emerging form of bibliometric measurement that capture the online dimension of scholarly exchange. Against the backdrop of both a higher education landscape increasingly focused on quantifying research productivity and impact, as well as literature emphasising the need to address gender bias in the discipline, we consider whether and how altmetrics (re)produce gendered dynamics in political science. Using a novel dataset on the Altmetric Attention Scores (AAS) of political science research, we investigate two questions: Do AAS vary by gender? And how do AAS relate to gendered social media dynamics? We find that AAS reproduce gendered dynamics found in disciplinary publication and citation practices. For example, journal articles authored exclusively by female scholars score 27% lower on average than exclusively male-authored outputs. However, men are also more likely to write articles with an AAS of zero. These patterns are shaped by the presence of high-scoring male “superstars” whose research attracts much online attention. Complementing existing scholarship, we show that the AAS closely overlaps with virality dynamics on Twitter. We suggest that these gendered dynamics may be hidden behind the seemingly neutral, technical character of altmetrics, which is worrisome where they are used to evaluate scholarship.

Real-time Spread Burst Detection in Data Streaming.

Data streaming has many applications in network monitoring, web services, e-commerce, stock trading, social networks, and distributed sensing. This paper introduces a new problem of real-time burst detection in flow spread, which differs from the traditional problem of burst detection in flow size. It is practically significant with potential applications in cybersecurity, network engineering, and trend identification on the Internet. It is a challenging problem because estimating flow spread requires us to remember all past data items and detecting bursts in real time requires us to minimize spread estimation overhead, which was not the priority in most prior work. This paper provides the first efficient, real-time solution for spread burst detection. It is designed based on a new real-time super spreader identifier, which outperforms the state of the art in terms of both accuracy and processing overhead. The super spreader identifier is in turn based on a new sketch design for real-time spread estimation, which outperforms the best existing sketches.

An intervention study of VR sports games on the perceptual and motor abilities of children with incomplete intellectual development

Abstract Childhood is a critical stage for the development of perceptual and motor abilities, and strengthening the training of children with incomplete mental development at this stage will affect the development of motor skills during their growth. In this paper, we take VR technology as a starting point to build a perceptual model and introduce a convolutional sparse representation algorithm. First, a sparse representation with few non-zero elements is found to optimize a function consisting of a data fidelity term and a sparse induced penalty function. Then, the sum of the convolution of the filter and the convolution sparse feature map, i.e., the convolution operation, is computed to generate the translation invariants. Then the convolutional sparse coding method is introduced to the traditional unsupervised problem by calculating the minimization objective function and solving it in an iterative manner alternatively. Finally, the constituents of the signal are analyzed and the discrete equivalence of the convolution is derived based on the Fourier transform to derive the intervening variables. The experimental results showed that the mean value of the post-test of motor ability compared with the pre-test increased by 4.6 through an eight-week VR sports game training intervention study test on different children with incomplete mental development. Therefore, it is of great theoretical and practical significance to understand the characteristics of perceptual and motor abilities of children with incomplete intellectual development and to develop corresponding programs for VR sports game training according to their characteristics.

A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids

As fossil energy is increasingly depleted, promoting the integration of renewable energy into the grid and improving its utilization rate has become an irresistible development trend in China’s power industry. However, the volatility of wind power increases the difficulty of economic dispatch in power systems. With the rising participation of wind power in the system, the complexity of traditional microgrid dynamic scheduling problems has increased, transforming into a dynamic economic scheduling problem for wind power thermal power hybrid microgrids. Starting from the concept and research significance of economic dispatch, this article analyzes the current research status of microgrid economic dispatch as well as the impact and influencing factors of wind energy grid connection on it. It summarizes the research performed by scholars in two aspects: scheduling models and solving algorithms in static dispatch, as well as how to deal with wind power randomness in dynamic dispatch and how to balance environmental protection while ensuring economic maximization. Finally, the existing problems in current research were summarized and future development directions were prospected. This research has important application prospects in improving the economy of the system and protecting the ecological environment.

The Trolley Problem in the Ethics of Autonomous Vehicles

Abstract In 2021, Germany passed the first law worldwide that regulates dilemma situations with autonomous cars. Against this background, this article investigates the permissibility of trade-offs between human lives in the context of self-driving cars. It does so by drawing on the debate about the traditional trolley problem. In contrast to most authors in the relevant literature, it argues that the debate about the trolley problem is both directly and indirectly relevant for the ethics of crashes with self-driving cars. Drawing on its direct normative relevance, the article shows that trade-offs are permissible in situations with self-driving cars that are similar to paradigmatic trolley cases. In scenarios that are unlike paradigmatic trolley cases, the debate about the trolley problem can have indirect normative relevance because it provides reasons against the use of moral theories and principles that cannot account for the trolley problem.