Working Path Research Articles

Analysis of the Implementation Path of Civic Education Work in institution of higher education under the Background of Internet+

Abstract In this work, the ideology and political characteristics are iteratively calculated using Cuckoo Search Algorithms and the Extreme Learning Machine. The ideology and political objective function are then obtained using CS-ELM. A CS-ELM-based index framework for ideology and political education effect in educational institutions is developed, all of the bird’s nest objective function values are calculated, as well as the bird’s nest position with the highest objective function value is retained in order to accurately and effectively evaluate the current state of ideology and political education effect in educational institutions. The experimental data set is an evaluation of the ideology and political education effects of colleges and universities from 2013 to 2022. Research and analysis are conducted on the evaluation of ideology and political education in institution of higher education in order to remove the quantitative definition of the collected raw data, and mixing is used to process the raw data to make it into a dimensionless one. The hierarchy of higher education has an impact on the establishment of high-quality economies. The CS-ELM model is the best way to assess ideology and political teaching effectiveness in higher education institutions, as per the results. This is because, when looking at the evaluation from an overall perspective, the RMSE value is 0.007, and the R-value is 0.995. This study enhances the quality of instruction in the classroom, promotes a positive environment and attitude, and motivates students to be actively involved in their education.

Illuminating policy for health: insights from a decade of researching urban and regional planning

Abstract Background Public health focussed policy analysis focusses on policy making practice and the conditions under which policies are made. The field has great promise for interrogating and creating ‘healthy’ public policy. Engaging with the complex realities of policy with a critical lens using established knowledge from other disciplines, especially political science, is crucial. Objectives This presentation presents a comprehensive framework for public health focussed policy analysis, informed by deep engagement with political science especially new institutionalism. The presentation of the framework is supported by insights from its application to urban and infrastructure policy-making over the past decade. Methods A priori application of theory from political science was mixed with deductive and inductive data collection and critical policy analysis of case studies of urban planning practices and systems in Australia from 2011 to 2020, including 250 policy documents and 92 semi-structured interviews. Results The final framework from the research is presented as a ‘cube’ made up of Institutions (actors, structures, ideas), Action and Evaluation (processes, decisions and choices, and outcomes and events), Governance (constitutive, directive and operational), Power and Time. Essentially the research demonstrated the power of institutional silos and historical ways of working (path dependencies) that are challenging to shift and are underpinned by often unexplored normative values promoting market and economic growth and excluding risks to health and health equity such as climate change and social protections. Change however comes about by creating and ensuring health focussed representation and voices in the governance regimes that define, create and sustain policy-making. Conclusions This comprehensive decade long research demonstrates how to investigate and interrogate healthy public policy that accepts and illuminates complexity to critically unpack policymaking. Key messages • Research that interrogates policy-making as its main object is important in an era of increasing health inequities and the climate emergency. • This presentation demonstrates how to do such research with practical examples and insights from investigating urban and infrastructure policy systems.

Optimization of Personnel Work Paths During Decommissioning of Nuclear Facilities

During the decommissioning process of nuclear facilities, workers are exposed to radiation and face the risk of exceeding safe dose limits. Ensuring the safety of personnel requires not only enhancing radiation protection measures but also optimizing work paths to minimize exposure time and avoid high-radiation areas. This paper proposes a nested optimization algorithm that combines an ant colony optimization (ACO) with an improved A* algorithm for the decommissioning of a nonradiation source. The algorithm aims to minimize the total radiation dose and transforms the original path optimization problem into an equivalent traveling salesperson problem. The improved A* algorithm is employed in the inner layer to calculate the path with the lowest radiation dose for any given sales order. The ACO operates in the outer layer to determine a set of optimal working paths that traverse all target points. The provided solution example demonstrates that the proposed path optimization algorithm effectively integrates the radiation field and obstacles. It successfully identifies a sequence for dismantling with the lowest dose and corresponding optimal work path while ensuring the completion of the dismantling task. These findings are expected to offer valuable insights for optimizing personnel work paths during the subsequent decommissioning process of nuclear facilities.

Countermeasures and Suggestions on the Reform of Physical Education in Higher Vocational Colleges from the Perspective of Lifelong Physical Education

With the rapid development of economy and science and technology, we media, as a technological product in the new era, is widely used in various fields in China, and is also full of people's daily life. College students are about to enter the society to participate in work, their ideological and political will inevitably be affected in the environment of we media, so how to maintain the noble moral character of college students is the task that educators in Colleges and universities should pay attention to. This paper first expounds the concept and characteristics of we media and the challenges that we media brings to the ideological and political work in Colleges and universities, and then discusses the innovation path of Ideological and political work in Colleges and Universities under the environment of we media, and puts forward personal opinions. Under the promotion of the national fitness policy in China, higher vocational college physical education also put forward relevant requirements, which requires students to master some sports knowledge and skills, but also to pay attention to their sports consciousness. Therefore, when carrying out efficient education reform, it is necessary to create teaching content based on students' lifelong sports development to lay a good foundation for their future life. When setting teaching objectives, we need to design from a long-term plan. For example, in track and field, they should make them form a good habit of jogging after supper or running in the morning every day. In this way, students can form a good habit of exercise from school, and they will not forget to exercise after graduation. In addition, after integrating the concept of lifelong sports into the physical education reform in higher vocational colleges, we should pay attention to the problem from the students' interest and acceptance, and then to the content of education, we should consider whether the students' physical and psychological development is helpful when they exercise.

The Paths of Social Work in Youth Health Education

In the context of the continuous development of society and the popu-larization of the Internet, social work should help young people to ex-pand access to sex education with professional knowledge combined with their specific conditions. The intervention of youth health through social work helps to cultivate young peoples personal ability and establish correct youth health values and sexual morality. Under the existing social environment and objective conditions, it mainly relies on the professional knowledge of social work to provide professional and targeted help from the perspective of family, school and community, peer education. Furthermore, group work and new media resources can be employed to improve adoles-cents cognition of youth health knowledge and realize the self-teaching and self-discipline of youth health knowledge education. The paper seeks to promote the social importance of college students health education, to bet-ter understand the necessity of home and school adolescent physical and psychological health education, and to explore to provide some effective im-plementation of the path so that to carry out related projects smoothly later.

Collaborative path planning and task allocation for multiple agricultural machines

Path planning and task allocation are critical concerns in multi-machine collaborative operations for unmanned farms. Nevertheless, several problems remain in the operation of agricultural machinery, such as the slow path planning algorithm, the omission of the working area, and the unreasonable scheduling of machines, resulting in low efficiency and wasted resources. Collaborative and complete coverage path planning was achieved to solve the problems of slow path planning algorithms and the omission of working areas. The farm’s electronic map was constructed using the topological map method. The improved Dijkstra algorithm based on priority queues was combined with three different complete coverage methods: the nested method, the reciprocating method, and the combination of nested and internal spiral path methods. The simulation results show that the improved Dijkstra method based on priority queues can effectively minimize the running time of the algorithm. The reciprocating method has a higher coverage index than the other two methods, with an average coverage rate of 94.73 %. To solve the problem of illogical scheduling of the same type of agricultural machines, an improved ant colony method was presented based on the whole working path to minimize the path cost. The simulation results show that the proposed method can allocate the task properly, and the path cost is reduced by 14 %–33 %. By combining the proposed path planning and task allocation methods, the whole-process path planning of a single agricultural machine and multiple agricultural machines of the same type was achieved, providing a technical solution for promoting the construction of unmanned farms.

Creativity, agency, and stability: Perceptions of Canadian musicians working across the cultural domains.

This research study aims to illuminate Canadian musicians' portfolio careers across the cultural domains. Previous research has highlighted the career paths of music graduates directly after graduation, and other research has highlighted the experiences of well-known performers or pedagogues. However, little is known about music graduates who persist and establish careers in music. We interviewed twelve musicians working in a variety of Canadian cultural domains to understand their work and career paths. Their stories elucidate how artists balance income stability, artistic agency, creativity, and professional challenges to create impressive and fulfilling portfolios that enable them to use their music-based knowledge and skills in various ways. Findings from this study provide a more nuanced understanding of the scope and nature of music-related work in Canada and how artists integrate artistic and creative abilities with community needs and economic stability. These findings offer insights for emerging musicians and music graduates and have implications for educating and supporting artists who wish (or indeed need) to work across cultural domains.

A Unified Meshfree Path to Arbitrary Order Hermite Finite Elements for Euler-Bernoulli Beams

The fourth-order governing equation of Euler-Bernoulli beams necessitates the employment of C1 Hermite shape functions in finite element analysis. However, unlike the C0 finite element shape functions that can be easily formulated as Lagrangian polynomials in a unified manner, the Hermite shape functions of Euler-Bernoulli beam elements are usually constructed case by case. In this work, a simple and unified meshfree path is proposed to develop arbitrary order Hermite shape functions of Euler-Bernoulli beam elements. This approach is realized by proving that the Hermite reproducing kernel meshfree shape functions degenerate to the interpolatory Hermite finite element shape functions under a proper choice of support sizes. The proposed approach provides an explicit formalism for Hermite finite element shape functions, which enables an easy construction of arbitrary order Hermite beam elements. Accordingly, in addition to the conventional cubic Hermite beam elements, explicit shape functions, mass and stiffness matrices for quintic and septic Hermite beam elements are presented. Meanwhile, the frequency errors and general higher order mass matrix formulation for these Hermite beam elements are elaborated as well. These theoretical results are consistently demonstrated by numerical examples with respect to both static and free vibration analysis.

Жизнь и деятельность Моисея Иосифовича Леви и его вклад в профилактическую дезинфекцию (к 100-летию со дня рождения)

The biography of the famous domestic disinfectionist, doctor of medical sciences, professor Moisey Iosifovich Levi is given. Keywords: distinguishing features of a scientist, study, work path, scientific developments, contribution to preventive disinfection, improvement of the quality of work of the Moscow desstation to ensure sanitary and epidemiological relief in the city.

Minimum-Weight Link-Disjoint Paths With a Bounded Number of Shared Nodes

Network protection has drawn a certain interest in network optimization. One of the most effective and widely used methods to protect networks from failures is to establish backup paths for working paths. For example, we find k node-disjoint paths between a source and a sink with one working path and k-1 backup paths. However, the demand for full protection of a network is somewhat too restrictive and there may not exist k node-disjoint paths in the network due to the limitation of geographical environments. On the other hand, the occurrence probability of node failures is usually much less than that of link failures in real-world models. To save network resources, we turn to establish link-disjoint paths allowing a few shared nodes. We study the problem of finding k link-disjoint paths between a source and a sink under the constraint that the number of nodes shared by at least r paths is at most δ, minimizing the total link weight. First, we systematically study the computational complexity of the problem with respect to three parameters k, r, and δ. Then, we build an integer linear programming for the general model and design a polynomial-time algorithm for the case that k=r by using the techniques of augmenting paths and splitting nodes. Finally, we carry out experimentations on synthetic and real networks that show the effectiveness of our algorithms in practice.

Bioinspired dry-state polylactic acid adhesives-based wearable sensor with reversible adhesive performance in harsh environments via building hierarchical liquid metal bead structure

Dry-state self-adhesive wearable sensors show great application in various fields. However, the poor adhesive performance, unsatisfied reversible performance, and low sensitivity in a harsh environment still limit its broad applications. Mimicking the biological design for strong adhesive has given promise for realizing reversible adhesive and high-performance sensor capacity. Drawing inspiration from the biomimetic mechanism of mussels and the mechanical interlocking adhesion mechanism, we have devised a multi-level micro/nano adhesion strategy. This innovative approach aims to create polylactic acid (PLA)-Liquid metal (LM) 3D beaded structured adhesives, with the ultimate goal of achieving significantly enhanced adhesive strength, improved water resistance, and superior mold resistance. The bioinspired PLA-based adhesives exhibit bond shear adhesion strength of 2.7625 MPa and adhesion peel strength of 290 kPa, which is higher than that of reports. Importantly, the new concept of sunlight harvesting function was introduced into the system. The adhesives show enhanced shear strength (10.77% increment) under solar irradiation due to the photothermal capacity of EGaIn. For the concept of proof, a self-adhesive LM-based wearable sensor can be assembled to detect the electrical signals triggered by strain. This work paths the way for developing multifunctional bioinspired dry-state adhesives for wearable electronics.

A new way of measuring effects of financial crisis on contagion in currency markets

Contagion is an extremely important topic in finance. Contagion is at the core of most major financial crises, in particular the global financial crisis that started in 2007. Although various approaches to quantifying contagion have been proposed, many of them lack a causal interpretation. We will present a new measure for contagion among individual currencies within the Foreign exchange market and show how the paths of contagion work within the Forex market using causal inference. This approach will allow us to pinpoint sources of contagion and to find which currencies offer good options for diversification and which are more susceptible to systemic risk, ultimately resulting in feedback on the level of global systemic risk. In particular, we will focus on the effects of the Covid-19 global pandemic.

SLAM-based Navigation Technology for Rescue Robots in Post-disaster Scenarios

In order to solve the problems of difficulty and high-risk factor in implementing rescue after disasters, this paper designs an intelligent rescue robot autonomous navigation system based on LIDAR synchronous positioning and map building, with a view to achieving autonomous navigation of robots in complex post-disaster scenarios to complete rescue tasks. Firstly, the autonomous navigation system senses the scene by LiDAR and uses gmapping algorithms to construct a map of the post-disaster environment. Secondly, adaptive Monte Carlo localization algorithm is used to achieve robot localization based on radar and odometer data. Then the robot rescue work path is planned to use the Dijkstra algorithm. And TEB local planning path algorithm is used to control the robot. Finally, to verify the reliability of the autonomous navigation system designed in this paper, the ROS system software framework is used as the basis. The SLAM map construction, global path planning, and local real-time obstacle avoidance are tested practically under the scenario to ensure that the autonomous navigation of the mobile robot meets the requirements.

RiskNet: Neural Risk Assessment in Networks of Unreliable Resources

We propose a graph neural network (GNN)-based method to predict the distribution of penalties induced by outages in communication networks, where connections are protected by resources shared between working and backup paths. The GNN-based algorithm is trained only with random graphs generated on the basis of the Barabási–Albert model. However, the results obtained show that we can accurately model the penalties in a wide range of existing topologies. We show that GNNs eliminate the need to simulate complex outage scenarios for the network topologies under study—in practice, the entire time of path placement evaluation based on the prediction is no longer than 4 ms on modern hardware. In this way, we gain up to 12 000 times in speed improvement compared to calculations based on simulations.

TF-Predictor: Transformer-Based Prerouting Path Delay Prediction Framework

Timing mismatch between different stages of physical design poses great challenges for circuit optimization to achieve the desired performance, power and area (PPA) tradeoff. The inaccurate timing estimation prior to routing may lead to over-design with unwanted power and area consumption or iterating back to cell placement at the cost of design turn-around time. Existing learning models could not predict post-routing circuit timing with satisfying accuracy and efficiency due to the limitations of the ignorance of delay correlation along the timing path and the empirical feature selection solutions. In this work, an accurate and efficient pre-routing path delay prediction framework is proposed by utilizing transformer network and residual model with an ensemble feature selection mechanism. Owing to the combined filter and wrapper methods, an ensemble feature selection mechanism is implemented to determine the optimal feature subset based on the timing and physical information at the placement stage for path delay prediction, which is extracted as feature sequences for each cell along the timing path to be trained by transformer network. With the residual model, the predicted timing mismatch between the placement and routing stages by transformer network is further calibrated to estimate the post-routing path delay. The proposed framework has been validated with ISCAS’85 and OpenCores benchmark circuits for the prediction of post-routing path delay, where the perdition error in terms of rRMSE is limited within 1.3% and 3.0% and the correlation coefficient R is higher than 0.999 and 0.995 for seen and unseen circuits respectively, indicating an error reduction by 2.3 10.6 times compared by prior learning-based models. In addition, the framework achieves average three orders of magnitude speedup compared with the commercial tools and is accelerated by a factor of 14 128 as against the competitive learning models, which is promising to be applied to guide design optimization prior to time-consuming routing stage.

Professional self-determination in the context of continuing education

In this article, the author examines the features and difficulties of decision-making related to professional implementation. Research shows that only 4 out of 10 Russians choose their profession once and stay with it forever, while the rest, after completing their education, do not go to work in their chosen specialty and are forced to think about changing their field of activity. The author is convinced that in order to minimize such selection errors, it is necessary to pay great attention to the formation of a person’s professional self-determination at each stage of its development, as well as timely professional guidance. As part of the study, the author reveals the essence and features of the process of self-determination. The author focuses on the fact that professional self-determination and personal development occurs continuously throughout a person’s life and work path and includes several stages. The study also included a comparative description of approaches to the periodization of professional self-determination and human development. According to the author, the most pressing issue of professional self-determination faces schoolchildren, because it is during their school years that students are faced with the internal need to understand their purpose in life. In this regard, the article also provided a comparative description of individual methods of vocational guidance for schoolchildren. The article emphasizes that the diagnosis of professional potential begins at the stage of personnel selection and decision-making on hiring a particular candidate. The author also focuses on the fact that after accepting an employee to the headquarters, an assessment of his potential can be carried out at any frequency established by the organization’s management. The final part of the article formulates a conclusion regarding the features of diagnosing the professional potential of an employee.

Development of Path Generation and Algorithm for Autonomous Combine Harvester Using Dual GPS Antenna

Research on autonomous driving technology is actively underway to solve the facing problems in the agricultural field. Combine harvesters used in East Asian countries, including Korea, are tracked-type vehicles. The steering control system of the tracked vehicle has different characteristics from the wheeled vehicle used in the agricultural tractor. In this paper, a dual GPS antenna-based autonomous driving system and path tracking algorithm were developed for a robot combine harvester. An α-turn-type work path generation algorithm and a path tracking algorithm were developed. The developed system and algorithm were verified through experiments using actual combine harvesters. The experiment consisted of an experiment with harvesting work and an experiment without harvesting work. In the experiment without harvesting work, an error of 0.052 m occurred during working driving and 0.207 m during turning driving. In the experiment where the harvesting work was carried out, an error of 0.038 m occurred during work driving and 0.195 m during turning driving. As a result of comparing the non-work area and driving time to the results of manual driving, the self-driving experiment with harvesting work showed an efficiency of 76.7%.

Path planning in continuous adjacent farmlands and robust path-tracking control of a rice-seeding robot in paddy field

During rice seeding, paddy fields are segmented by embankments to hold water and evenly supply nutrients to the rice. Reasonable path planning from the entry to the exit of continuous adjacent sublands and accurate path tracking in harsh paddy fields are crucial for efficient and high quality work by an autonomous rice-seeding robot. In this study, four entering and exiting modes with continuous adjacent sublands are defined, and the corresponding planning paths for each mode are provided and analyzed. The optimal working path is obtained under the constraints of full coverage without overlap or skip between rows, minimum blank operation areas at the headland and minimum turns while working; The requirements for the width of standardized farmland and the number the farmland is divided into are given. A kinematic model of the rice-seeding robot embodying slip and side slip is built to achieve reliable and accurate path tracking under adverse conditions of paddy fields. The equivalent disturbances caused by slip and side slip are estimated using a nonlinear observer. Combined with a nonlinear observer, a fast terminal sliding-mode controller is designed for the path tracking of the rice-seeding robot in paddy fields. The control algorithm is validated through simulations and field tests.

The value implication and promotion path of ideological and political work in colleges and universities in the era of digital intelligence

With the advent of the era of digital intelligence, it has had a profound impact and change on the economic, political, cultural, educational and other fields of human society. As an important part of modern society, colleges and universities are also facing new opportunities and challenges brought by the era of digital intelligence. Colleges and universities need to explore the practical path that conforms to the characteristics of the times, adapts to the needs of students, and improves the effect of educating people. It is necessary to give full play to the advantages of digital technology in ideological and political education. It is necessary to continuously innovate the content, methods, methods, and evaluation of digital ideological and political education. It is necessary to continuously improve the main ability and level of digital ideological and political education, and make new contributions to the cause of moral education in colleges and universities.

A Simple Method to Calculate Positions in Pose Tracking to Verify Work Procedures

Although manufacturing processes are becoming increasingly automated, many factories still rely on manual operations. In such facilities, there is a strong need to automatically detect human errors by checking whether specified procedures are being followed. For this purpose, studies have been conducted on utilizing deep neural network (DNN) based three-dimensional (3D) human pose-tracking methods to examine work procedures. However, most of these techniques require a high-end computer equipped with a graphics processing unit (GPU). On the other hand, in this study, we adopt MediaPipe Pose, a lightweight pose estimation network provided by Google, to perform pose tracking on a low-end personal computer (PC) to enable such systems to be deployed in small factories. However, MediaPipe Pose cannot track the location of a human body because it estimates poses in a coordinate system with the waist as the origin (that is, in a root‑relative coordinate system). Therefore, in this study, we developed a method to obtain the absolute coordinates of the root with a simple calculation. The results of an experimental evaluation show that the computational load of the proposed approach is negligible, and the repeatability of the estimation sufficed to evaluate a given operator's work on a predetermined working path. Therefore, the proposed methods enables work procedures to be checked using MediaPipe Pose on a low-end PC.