Human Resource Costs Research Articles

Development of automated system for receiving and analysing telemetry data from small spacecrafts

The system presented in the study is designed to increase the share of automation in the process of interaction with small spacecraft (SSС) at all stages of operation. Automatic operation of the system will reduce the cost of human resources, the number of errors in management, and increase the time of uninterrupted and continuous operation. The system independently calculates the time of all possible sessions of a group of small spacecrafts with a ground station; forms on its basis a schedule for the operation of a ground station, taking into account historical and future calculation sessions; implements control of the rotary antenna according to the compiled session schedule; decodes telemetry data, writes it to the database, carries out preprocessing and visualization. The system was developed taking into account possible scaling to several receiving stations.

ПРАКТИЧЕСКИЕ АСПЕКТЫ ПРИМЕНЕНИЯ СЕГМЕНТАРНОГО ИИ-ПОДХОДА ОЦЕНКИ ЭФФЕКТИВНОСТИ ДЕЯТЕЛЬНОСТИ ИНТЕГРИРОВАННЫХ СТРУКТУР

In the scientific context, despite the presence of views from the standpoint of socio-economic knowledge on the interaction of integrated business structures and artificial intelligence, a number of issues related to the peculiarities of their sustainable functioning require study. In the conditions of competition associated with the globalization of the global economic crisis, the priority of using artificial intelligence technologies in the activities of integrated agribusiness structures is growing, in particular, to assess the effectiveness of the functioning of the agricultural holding, which significantly reduces or eliminates the risk of inaccurate calculations. Therefore, the use of a segmented AI approach will ensure the holding’s competitive advantage by reducing human resource costs and improving the quality of decisions made.

Picking scheduling for single picker to multi-workstations of the part-to-picker order fulfilment system

To reduce human resource costs, the part-to-picker order fulfilment systems may have a single picker in charge of multiple workstations. And the picking speed of the picker becomes faster as the picking number increases due to the learning effect in the picking operation. In this paper, the scheduling problem to optimizing picking sequence of the picker is presented to minimize the maximum picking time, where one picker is responsible for multiple workstations. The learning effect and travel time between workstations are taken into account to improve scheduling accuracy. Two mixed integer programming (MIP) models are proposed to solve the problem, namely the rank-based model and disjunctive model. The performance of the two Mixed Integer Programming (MIP) models has been evaluated, and it has been found that they are only capable of solving small-scale problems. The rank-based model is limited to solving problems with up to 9 groups, whereas the disjunctive model can handle up to 20 groups. Therefore, the disjunctive model outperforms the rank-based model. Moreover, this paper proposes Interval Insertion NEH (IINEH) and iterative greedy (IG) algorithm to solve the large-scale problem. Numerical experiments demonstrate the effectiveness of the two methods to solve the problem, where IINEH operates faster while IG gives better results. Therefore, when faced with a large-scale problem, IINEH is recommended if a quick solution is needed. If better optimization results are needed, the decision maker can choose IG.

Research on the Regulation of Intelligent Elderly Service Laws in the Age of Artificial Intelligence

Abstract The artificial intelligence senior care model brings about work efficiency improvement and human resource cost saving to old care service enterprises and government departments. Taking Maslow’s hierarchy of needs theory as an entry point, the article systematically combs through the needs, legal source relations, and potential risks of intelligent senior care services. To accurately assess the relevant influencing factors of the legal regulation of innovative senior care services, linear regression and seemingly uncorrelated regression models are introduced. The model parameters are estimated by Bayesian estimation method, and the empirical analysis is conducted based on the baseline regression and seemingly uncorrelated regression models. When the local government pension policy decreases by every 1 percentage point, the degree of legal regulation of innovative pension services will decrease by 0.598 percentage points. In addition, in the likelihood uncorrelated regression model, the influence coefficient of education level is −0.372, which is 38.81% lower than the benchmark regression model. To better guide the standardized development of innovative senior care services, the central and local governments must actively introduce relevant policies to help the public better understand and accept the advantages of intelligent senior care services.

Where do we invest money to implement active learning on caries detection? An economic evaluation.

This trial-based economic evaluation aimed to estimate the incremental cost of implementing an active learning strategy (theoretical-practical workshop) to substitute the didactic lecture as the sole method for students training in caries detection. We also provided a budget impact analysis and explored the composition of costs related to the activity. Data from the coordinating centre of a multicentre randomized and controlled study (IuSTC01) was analyzed as the first part of our main economic analysis plan. The perspective of the educational provider (the institution implementing the activity) was considered, and an immediate time horizon was adopted. All used resources were valued in Brazilian Real by adopting a microcosting strategy. Costs for each strategy were estimated and converted into international dollars. The incremental Cost per student and the total cost of implementing the complete teaching strategy for 80 students were calculated. Monte Carlo simulations were used to estimate the uncertainties. The incremental Cost estimated for the workshop implementation would be $7.93 per student (interquartile range (IQR): $7.8-8.1), and the total cost of the teaching activity would be $684 (IQR:672-696). The laboratory training comprised more than 50% of the total amount spent, and a higher percentage of this value was related to human resources costs (72%). Saving 40% of the costs could be expected for the next rounds of activities in the institution, assuming no need for additional preparation of didactic materials and tutor training. A modest incremental cost per student and an acceptable organizational budget impact should be expected for the institution when including active learning training in caries detection for undergraduate students, mainly related to the human resources involved.

The Main Scientific and Practical Directions and Priorities of Management and Development of the Digital Economy at the Enterprises of Modern Shipbuilding

Theoretical reference: The article outlines some of the main theoretical and empirical aspects of studying the process of digitalization and human capital management of industrial economic entities, including considering the main structural elements of human capital formation/functioning, and the synergistic effect of various structural elements of human capital. Method: The article discusses some main analytical methods for assessing the effectiveness of digitalization processes, including the market capitalization method, a method for assessing intellectual capital based on average annual return on assets (ROA), and a method for estimating the cost of human resources based on computational and analytical indicator of information productivity. Results and Conclusion: The article discusses results around trends in digital transformation for shipbuilding companies and conclusions that the digital economy determines the new role of human resources and capital and that people remain a key success factor for digital enterprises. Implications of research: The research helps outline the main directions and priorities of human resource management and digital economy development at modern shipbuilding enterprises. Originality and value: The research provides a comparative analysis of theoretical and empirical aspects of digitalization and human capital management in the context of the shipbuilding industry, examining computational methods for evaluation. This contributes new perspectives and analysis specific to this industry context.

The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.

This manuscript will be of interest to most Clinical and Translational Science Awards (CTSA) as they retool for the increasing emphasis on translational science from translational research. This effort is an extension of the EDW4R work that most CTSAs have done to deploy infrastructure and tools for researchers to access clinical data. The Iowa Health Data Resource (IHDR) is a strategic investment made by the University of Iowa to improve access to real-world health data. The goals of IHDR are to improve the speed of translational health research, to boost interdisciplinary collaboration, and to improve literacy about health data. The first objective toward this larger goal was to address gaps in data access, data literacy, lack of computational environments for processing Personal Health Information (PHI) and the lack of processes and expertise for creating transformative datasets. A three-pronged approach was taken to address the objective. The approach involves integration of an intercollegiate team of non-informatics faculty and staff, a data enclave for secure patient data analyses, and novel comprehensive datasets. To date, all five of the health science colleges (dentistry, medicine, nursing, pharmacy, and public health) have had at least one staff and one faculty member complete the two-month experiential learning curriculum. Over the first two years of this project, nine cohorts totaling 36 data liaisons have been trained, including 18 faculty and 18 staff. IHDR data enclave eliminated the need to duplicate computational infrastructure inside the hospital firewall which reduced infrastructure, hardware and human resource costs while leveraging the existing expertise embedded in the university research computing team. The creation of a process to develop and implement transformative datasets has resulted in the creation of seven domain specific datasets to date. The combination of people, process, and technology facilitates collaboration and interdisciplinary research in a secure environment using curated data sets. While other organizations have implemented individual components to address EDW4R operational demands, the IHDR combines multiple resources into a novel, comprehensive ecosystem IHDR enables scientists to use analysis tools with electronic patient data to accelerate time to science.

APPROACHES TO INCREASE THE EFFICIENCY OF TRAINING AND TESTING BY CREATING A UNIFORM INFORMATION AND REFERENCE SYSTEM AND AUTOMATING THE ACTIVITIES OF THE INSTITUTE’S SCIENTISTS

The article is devoted to ways of solving certain problematic aspects of the preparation and conducting of tests, caused by the lack of a centralized approach to the creation, replenishment and access of scientists of the institute to the regulatory and legal framework and other materials necessary for the development of organizational and methodical documents for conducting tests. This causes long-term, not always high-quality preparation and testing of weapons, military, special equipment, ammunition, software and other types of experimental samples.
 The authors of the article outline approaches to increase the efficiency, automation, and quality of preparation and testing. For this purpose, it is proposed to create a single information and reference system at the institute, built on the basis of global (cloud environment) and local (local computer network) data exchange systems.
 The proposed approaches provide for the implementation of advanced information technologies that ensure the accumulation, search, access and use by scientists of the State Research Institute of Testing and Certification of Weapons and Military Equipment of the necessary regulatory and legal acts, organizational and methodological documents, reporting materials and other reference data at the stages preparation and testing of weapons, military, special equipment, ammunition, software and other types of prototypes.
 The introduction of the proposed approaches will reduce the cost of human resources for the preparation for the tests, will ensure the improvement of the quality of working out the organizational and methodical documents, which will ensure the proper conduct of the tests by the test team.

A Novel Fuzzy Unsupervised Quadratic Surface Support Vector Machine Based on DC Programming: An Application to Credit Risk Management

Unsupervised classification is used in credit risk assessment to reduce human resource costs and make informed decisions in the shortest possible time. Although several studies show that support vector machine-based methods have better performance in unlabeled datasets, several factors still negatively affect these models, such as unstable results due to random initialization, reduced effectiveness due to kernel dependencies, and noise points and outliers. This paper introduces an unsupervised classification method based on a fuzzy unsupervised quadratic surface support vector machine without a kernel to avoid selecting related kernel parameters for credit risk assessment. In addition, we propose an innovative fuzzy membership function for reducing noise points and outliers in line with the direction of sample density variation. Fuzzy Unsupervised QSSVM (FUS-QSSVM) outperforms well-known SVM-based methods based on numerical tests on public benchmark credit data. In some real-world applications, the proposed method has significant potential as well as being effective, efficient, and robust. The algorithm can therefore increase the number of potential customers of financial institutions as well as increase profitability.

АВТОНОМНІ НАДВОДНІ ДОПОМІЖНІ СУДНА: ПЕРЕВАГИ ТА ПРОБЛЕМИ

With the continuous progress of modern science and technology and the increasing requirements for marine transport in various fields, the intelligence and automation of ships has become a general trend. Autonomous unmanned surface vessel (UASV) control generally includes UASV trajectory planning, path tracking control, and autonomous collision avoidance control. Due to their low cost, small size, fast action, reconnaissance capabilities and other advantages, BPNS play a very important role in everyday life, emergency response and scientific research. UASV, as a rule, consist of a platform and a payload system. But in the whole process of UASV navigation, autonomous mooring is also an important part. And there are fewer studies on the automatic mooring algorithm of UASV. The advanced technology of autonomous mooring of BPNS can effectively reduce the cost of human, material and financial resources, while reducing the accident rate in a reasonable and safe manner. Therefore, it is very important to comprehensively promote the development of autonomous navigation and mooring technology of UASV. Keywords: Autonomous unmanned surface vessel (UASV), autonomous mooring.

Analysis of Temporary Works Interest Protection by Negotiation

According to some experts, temporary workers are becoming less willing to speak out when they have made a loss as previously they were. Nonetheless, when their benefits are being infringed, temporary workers will bargain with the employer to safeguard their own interests. However, there is no unified explanation for the reasons behind the formation and solutions. Therefore, this paper collects data on temporary workers employed by some companies and analyzes the correlation between the data and the case of "temporary workers employed by Meituan Takeaway" to investigate the topic of how temporary workers should negotiate with companies to protect their own interests. The study found that there are two reasons why temporary workers are not valued by the company, including the low skill level of temporary workers and the high risk of quitting; the company hires temporary workers not only because it can save human resources costs, but also shows higher motivation for temporary workers. The company should insist on "equal pay for equal work", which is beneficial to the development of the company and establish a good corporate image. In view of the above findings, this paper proposes that the company should actively cooperate with the negotiation process and the temporary workers should use such negotiation skills to communicate with the company.

A BIM-based development method for digital drawing review system in the construction sector

ABSTRACT This paper proposes a digital review method based on BIM (Building Information Modeling). The C# language is used to structure and compile architectural design standards into computer identifiable discriminant conditions, match and judge BIM model information, and return the review results. Encapsulate the digital review system’s core code into an executable program by Microsoft’s NET framework. The program includes Login, Model Review, Result Display, and Result Export functions. As a case study, the paper uses the fire control review of construction drawings for a newly constructed student dormitory to implement the process of a digital drawing examination system. The results show that compared with the traditional manual review, the digital review reduces the cost of high-quality human resources, simplifies the workflow of construction drawing review, and shortens the drawing review cycle. It plays an active role in promoting the whole process of digital achievement delivery and application of construction engineering.

Application of Machine learning techniques in environmental governance: A review

In recent years, based on the continuous improvement of computer hardware performance, machine learning (ML) technology has made rapid development. Due to the strong ability of ML methods to find complex functions between associated data and the low cost of human and material resources, they are increasingly favored by environmental governance practitioners. Current research has confirmed that the application of ML technology to the field of environmental governance is of great significance in overcoming the difficulties of analysis and practice in traditional environmental work, and can greatly promote the long-term development of such directions as air quality prediction, solid waste classification, pollutant distribution mapping, and intelligent management of water environment. Therefore, by organizing the representative literature in the past five years, this paper describes the current status of the application of ML technology in four different elements of environmental governance, namely, atmosphere, water, soil, and solid waste, and aims to summarize the possible directions of the future development of ML technology and the new development brought to the field of environmental governance by exploring the basic concepts of ML, the advantages and disadvantages of the model and the constraints and other issues.

Hotel Human Resource Management Strategy During the Pandemic---A Case Study of Hilton Hotel

As COVID-19 spreads, an increasing number of industries have become stagnant, especially the hotel industry. Considering safety hazards, lots of hotel employees tend to make a career change. Therefore, the labor shortage and rising operating costs of human resources have gradually become the major issues for the hotel industry under the pandemic. In this circumstance, it is of great significance for the human resource department to think about how to adjust the hotel business strategy, optimize the management structure and reduce labor costs. Taking the renown Hilton Hotel as an example, this paper describes how the hotel should adopt human resources strategies to effectively cope with the crisis brought by COVID-19 and seize new development opportunities in this context. Hilton Hotels is working hard to ensure guaranteed quality of service during the pandemic, lowering corporate labor costs, and earning higher profits.The specific practice is to improve employee satisfaction, launch new employment mode, use artificial intelligence and so on.

An overview of developments and challenges for unmanned surface vehicle autonomous berthing

With the continuous progress of contemporary science and technology and the increasing requirements for marine vehicles in various fields, the intelligence and automation of ships have become a general trend. The autonomous control of surface Unmanned Surface Vessel (USV) generally covers the USV path planning, path tracking control, and autonomous collision avoidance control. But in the whole navigation process of USV, autonomous berthing is also a crucial part. And the research on the algorithm of the automatic berthing process of the USV is less. Mature USV autonomous berthing technology can effectively reduce the cost of human and material resources and financial resources while reducing the accident rate reasonably and safely. Therefore, it is of great importance to comprehensively promote the development of USV autonomous berthing technology.

The Application of Text Mining Technology in Business Management—Take Hotel Management as an Example

In recent years, the development of the information industry has led to the rapid rise of data mining, and in the face of the trend of data mining development, the field of data mining has become a focal point of concern for various industries. As a very customer-focused service industry, the hospitality industry is imperative to popularize and intelligently integrate text mining into management in the context of rising human resource costs and the general intelligence of all industries. In this paper, the application of text mining technology in business management is explored, using hotel management as an example. The Porter's Five Forces model, the SWOT model are used to analyze the importance of unstructured data such as customer reviews and the great role of text analytics in the internal and external management of hotels. The recommendations for the integration of text mining and hotel management are proposed, suggesting that text mining should be commonly used in hotel management and recommending that managers adopt A small amount of manpower and a large amount of text mining to overcome the drawbacks of text mining and improve hotel operations.

Consumer Electronics Product Manufacturing Time Reduction and Optimization Using AI-Based PCB and VLSI Circuit Designing

Circuit design plays an essential role in all consumer electronics products. Printed circuit board (PCB) and very-largescale integration (VLSI) circuit designing requires optimization of the electronic components placement and wire routing to connect the components. Currently, circuit routing processes have been performed manually by experts, which greatly increases the cost of human resources and time. Such heuristic circuit designs are not optimized and may have errors, which is why automated circuit routing algorithms are important. However, it is difficult to obtain an optimal solution in circuit routing as it is an NPhard problem. In addition, poor circuit routing increases the wire length of the circuit, which causes an increase in circuit cost and weight as well as performance degradation. In order to achieve routing optimization, many technologies have been proposed, in which some have applied artificial intelligence (AI) to improve the overall performance and reduce the designing time. Accordingly, in this paper, routing problems in PCB and VLSI are explained, and proposed technologies to solve these routing problems are introduced. Especially, a detailed investigation and analysis of AI technologies grafted into circuit routing algorithms are explained, and the considerations for AI-based routing algorithms are presented.

The immediate treatment outcomes and cost estimate for managing clinical measles in children admitted at Mulago Hospital: A retrospective cohort study.

Over the recent years, the Ministry of Health in Uganda has reported multiple measles outbreaks in various districts despite the availability of a safe cost effective vaccine. Measles, especially among the unvaccinated can lead to serious complications including death while its management heavily burdens the family and health care system. This study aims to determine the immediate treatment outcomes and estimate the cost of treating a measles case. A retrospective cohort study using records review was conducted among children 0-12 years admitted at Mulago hospital throughout 2018. Demographics, complications, vaccination status, discharge status, duration of hospital stay, type of treatment, supplies and investigations done were abstracted from the patient charts. Treatment costs were obtained from the hospital pharmacy price list while the unit cost of utilities, human resource, food and security were obtained from the hospital accounts department. Patients' characteristics were summarized descriptively. Cost information, was reported as mean with standard deviation (SD) and range, and was stratified and presented as direct health care (blood test, radiology and treatment) and direct non health care costs. Among 267 reviewed patient charts, the median age was 1.0 ((IQR 0.75-2) years. 63patients (24%) were immunised, 79 (29%) were not immunized, Median length of hospital stay was 4.0 days (IQR 3.0-7.0) with majority (n = 207, 77%) staying < 7 days. 30 patients (11%) died with mortality highest among the unimmunised (n = 13, 44%) and severe pneumonia (39.5%) was the commonest complication. 114.5 USD was estimated to treat a child with measles. Human resource (79.33USD, SD 4.63) and treatment costs (21.98USD, SD 22.77) were the largest expenses. Complications are common in majority of fatal measles cases and these carry a high cost to the healthcare system.

Portfolio instability and socially responsible investment: Experiments with financial professionals and students

Efficiency of SRI portfolios is commonly assessed based on an inconclusive risk-return ratio. We propose to approach the efficiency of portfolios with the notion of instability. Unstable portfolios are characterized by higher transaction costs and human resources costs that justify search for more stable portfolios. We examine the instability of SRI portfolios from the perspective of behavioral finance. Based on data from incentivized experiments with 153 financial professionals and 233 students, we compare a baseline treatment to a ranking treatment in which participants received feedback regarding their average investment in SRI assets. We found that SRI portfolios had significantly lower instability: portfolios with a majority of SRI shares exhibited less instability in both treatments compared to conventional portfolios. Moreover, in the ranking treatment subjects invested more in SRI assets than in the baseline. In addition, the experiment revealed the convergence of professionals’ and students’ behavioral patterns.

Estimating the Cost of Delivering Tobacco Cessation Intervention Package at Noncommunicable Disease Clinics in Two Districts of North India.

Integrated care is likely to improve outcomes in strained healthcare systems while limiting costs. NCD clinics were introduced under the "National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Disease, and Stroke" (NPCDCS) in India; however, there is limited literature on the costs of delivering tobacco cessation interventions within NPCDCS. One of the study's objectives was to estimate the cost of delivering a culturally specific patient-centric behavioral intervention package in two district-level NCD clinics in Punjab, India. Costing was undertaken using the health systems perspective. A top-down or financial costing approach and a bottom-up or activity-based approach were employed at each step of development and implementation. The opportunity cost was used to include the cost of human resources, infrastructure, and capital resources used. All infrastructure and capital costs were annualized using a 3% annual discount rate. Four additional scenarios were built up concerning three major components to reduce costs further when rolled out on a large scale. The cost of intervention package development, human resource training, and unit cost of implementation were estimated to be INR 6,47,827 (USD 8,874); INR 134,002 (USD 1810); and INR 272 (USD 3.67), respectively. Based on our sensitivity analysis results, the service delivery cost varied from INR 184 (USD 2.48) to INR 326 (USD 4.40) per patient. The development costs of the intervention package accounted for the majority proportion of the total cost. Of the total unit cost of implementation, the telephonic follow-up, human resources, and capital resources were the major contributory components. The current study aims to fill gaps by estimating the unit-level health systems cost of a culturally sensitive, disease-specific, and patient-centric tobacco cessation intervention package delivered at the outpatient settings of NCD clinics at the secondary level hospital, which represents a major link in the health care system of India. Findings from this study could be used to provide supportive evidence to policymakers and program managers for rolling out such interventions in established NCD clinics through the NPCDCS program of the Indian Government.