Work Platform Research Articles

Experimental Investigation on Axial Ultrasonic Vibration Assisted Milling of Cr12MoV

The conventional milling process is difficult due to the high strength and hardness of Cr12MoV, which can cause the rapid tool wear, premature failure,and poor milling quality of work platform. The ultrasonic vibration machining technology has been founded to be effective in the milling process of hard-to-cut materials like die tool steel and nickel alloys. The ultrasonic vibration assisted milling (UVM) technology is carried out the axial milling of Cr12MoV in this paper, and the average impact force Fi is influenced by the vibration amplitude A, the vibration frequency f, and equivalent mass of the vibrating part M. The mean value of cutting force Fx, Fy, and Fz decreases by 25%, 15.04%, and 17.46%, respectively. With the increase of vibration amplitudes, the value of surface roughness firstly decrease and then increase, and it is obviously lower than conventional milling. The experimental results demonstrated that the UVM technology is a feasible method for the low cutting force and high quality process of cutting Cr12MoV.

Remote Work Opportunities for the Persons with Disabilities

This research represents one of the first literature reviews of remote work opportunities for persons with disabilities. Given the fact that persons with disabilities represent almost 15% of the total world population and that this category of people is facing huge challenges in terms of employment inclusion and risk of poverty, it is obvious that remote work arrangements provide excellent employment opportunities for persons with disabilities. This argument in combination with enormous growth of the remote work platforms and digital entrepreneurship, represents a key reason for the rising interest of the research community in this topic. The aim of this research was to identify the current state of the academic literature in the area of remote work opportunities and persons with disabilities and to identify gaps in our current understanding of this field, as a basis for some future research recommendations. Insight, critique and transformative redefinition of the current academic literature on remote work and persons with disabilities was applied to analyze and synthesize the literature. In total, around 80 articles were analyzed by theoretical focus, methodology, time, and geography. Google Scholar search was conducted during December 2022 using a comprehensive search strategy built around the following major topics: 1. persons with disabilities in the labor market, 2. remote work and the persons with disabilities, and 3. remote work capacity of the persons with disabilities. The results of this research show that the research on remote work capacity of the persons with disabilities is fragmented and that more studies, covering different aspects of remote work opportunities for persons with disabilities are needed, especially those which will be quantitative in their nature and more integrative. This research has contributed towards better understanding of the literature gaps in regards to remote work opportunities for the persons with disabilities and pointing to some future research directions such as skills and competences of the persons with disabilities for remote work, the challenges of remote work for persons with disabilities, and the requirements of the remote work platforms and other remote work opportunities.

Exploration of the development path of university thinking and political education in the background of Internet

Abstract The effective development of Civic Education work in colleges and universities can promote the cultivation of high-quality talents. Starting from Internet information technology, this paper constructs a digital platform for Civic Education work, in which Shannon’s theory and balanced power allocation are used to optimize channel transmission and enhance the loading speed of Civic Education resources. The XGBoost algorithm is used to effectively cluster students’ learning behaviors as a way to help Civic Education workers understand students’ learning behaviors in Civic Education. The results show that the average response time is 0.327s, and the maximum throughput is 11849.478 bytes/sec. The prediction accuracy of the XGBoost algorithm for student learning behavior is 4.65%, 9.79%, and 21.79% higher than that of LR, RF, GBM, and Stacking classification models, respectively. 9.79%, 21.41%, and 13.5%, respectively. This shows that the university’s thinking and political education work can be developed through the direction of the digital Internet platform, which in turn provides a new research path for the reform and innovation of thinking and political education work.

A hybrid DMO-RERNN based UPFC controller for transient stability analysis in grid connected wind-diesel-PV hybrid system

AbstractIn this paper, a novel hybrid technique is proposed for transient stability analysis on grid connected Wind-Diesel-PV hybrid system. The proposed hybrid methodology is combination of the dwarf mongoose optimization algorithm (DMO) and the recalling enhanced recurrent neural network (RERNN) named DMO-RERNN. The main purpose of this work is to consider various elements on hybrid system for the analysis of transient stability according to different conditions. The voltage profile of hybrid system is enhanced using the proposed unified power flow controller (UPFC), which also has higher performance improving transient performance compared to the conventional ANN, PI and fuzzy-sliding mode controller. Considering the proposed technique, DMO is used to find the optimal global solution for the fault predicted by the RERNN approach. The proposed system is executed on MATLAB work platform; its performance with existing systems is analyzed. The result proves that the proposed hybrid technique based UPFC controller provides better results compared with other existing technique. The efficiency of the PI is 82.136, ANN is 77, Fuzzy Sliding Mode is 65.097% and proposed technique is 97.99038%.

Identifying Critical Factors and Trends Leading to Fatal Accidents in Small-Scale Construction Sites in Korea

Small-scale construction sites in South Korea account for about 91.5% of all construction workplaces and contribute to 72.3% of the total accidents and fatalities. Safety measures at these sites are often underestimated, and proper safety education is lacking. In particular, the fatality rate is about 4.43 times higher compared to medium-/large-scale construction sites. In this study, a systematic analysis was conducted to examine the causes and trends of industrial accidents in small-scale construction sites to address these issues. This study analyzed industrial accidents in small-scale construction sites using statistical analysis, LDA topic modeling, and network analysis based on data from the Korea Occupational Safety and Health Agency (KOSHA) from 2018 to 2022. The analysis revealed that the most critical cause of accidents in small-scale construction sites is ‘Scaffolding and working platforms’, with accidents primarily involving ‘Fall’. Furthermore, various risk factors and accident trends were identified in apartment construction, new building projects, and mobile scaffolding usage. This study systematically analyzed the causes and trends of industrial accidents at small-scale construction sites, providing important evidence to enhance safety management and preventive measures. The results are expected to play a crucial role in establishing a safety culture at construction sites and ensuring the wellbeing of construction workers.

BEELINE: BilevEl dEcomposition aLgorithm for synthesis of Industrial eNergy systEms

Energy transition to a more sustainable basis is the most significant and complex challenge facing industry. On most industrial sites, the largest single energy user is the utility system that produces the heat and power necessary for the site. The heavy reliance of current utility systems on fossil fuels and the requirement of strategic measures to ensure a sustainable future has prompted researchers to explore different energy sources, technologies and pathways for evolving existing systems to a sustainable basis for future utility systems. Whether based on renewable or non-renewable energy sources, it is essential to minimize energy demand and mitigate emissions. The present work focuses on developing cost-effective solutions for the synthesis of process utility systems, considering site-wide energy integration. This will provide a platform in future work for the efficient introduction of renewable energy sources in the transition to sustainable systems. Utility system performance is generally determined by system configuration and operational load. Steam mains selection, in terms of pressures and superheating have a critical role in the utility system performance and site energy integration. Therefore, the synthesis of energy-efficient utility systems involves optimizing the configuration of utility components and number and operating conditions of steam mains simultaneously. Due to nonlinearities and non-convexities from underlying physics and binary decisions involved, the resulting Mixed-Integer Non-Linear Problem (MINLP) presents challenges for advanced state-of-art solvers to solve real-world problems. In past work, a number of important practical issues have been oversimplified in order to make the solution tractable. However, the oversimplifications also lead to misleading results. In this research, a mathematical formulation for simultaneous optimization of comprehensive utility system configurations and operating conditions is for the first time combined with more realistic steam system configurations and operating conditions to represent the utility systems. Its framework is constructed via a bilevel decomposition algorithm based on piecewise MILP relaxation, McCormick relaxation, and linearization of steam properties. In addition, the solution pool feature of the CPLEX solver is incorporated to enhance the performance and convergence of the algorithm. This work presents the fundamental problem formulation that has not been sufficiently addressed previously. Indeed, this methodology sets out the basis for synthesizing energy-efficient utility systems for the future and allows for many energy conversion technologies and sources to be added to the framework that have previously not been possible to include.

Urinary peptidome analysis in CKD and IgA nephropathy.

Chronic kidney disease (CKD) has emerged as a significant challenge to human health and economic stability in aging societies worldwide. Current clinical practice strategies remain insufficient for the early identification of kidney dysfunction, and the differential diagnosis of immunoglobulin A nephropathy (IgAN) predominantly relies on invasive kidney biopsy procedures. First, we assessed a case-control cohort to obtain urine samples from healthy controls and biopsy-confirmed CKD patients. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) was applied to detect urinary peptide and then these urinary peptide profiles were used to construct diagnostic models to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. Furthermore, we assessed the robustness of the diagnostic models and their reproducibility by applying different algorithms. A rapid and accurate working platform for detecting CKD and its IgAN subtype based on urinary peptide pattern detected by MALDI-TOF MS was established. Naturally occurring urinary peptide profiles were used to construct a diagnostic model to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. The performance of several algorithms was assessed and demonstrated that the robustness of the diagnostic models as well as their reproducibility were satisfactory. The present findings suggest that the CKD-related and IgAN-specific urinary peptides discovered facilitate precise identification of CKD and its IgAN subtype, offering a dependable framework for screening conditions linked to renal dysfunction. This will aid in comprehending the pathogenesis of nephropathy and identifying potential protein targets for the clinical management of nephropathy.

Working platforms and bearing capacity assessments of sand overlying clay using finite element limit analysis

The bearing capacity of shallow foundations on layered soils is typically based on empirical models assuming a strip footing. Shape factors are then applied to the strip footing solution to account for the specific geometry of the foundation being considered. A common practical application of this methodology is when the ultimate bearing capacity of a granular working platform constructed over a clay subgrade is estimated using the Working Platforms for Tracked Plant BRE-470 guideline. Previous studies using finite element limit analysis have been undertaken to examine a strip footing on a layered soil and how the resulting bearing capacity compares to that derived from BRE-470. This paper presents an extension of previous work by the authors using finite element limit analysis to investigate the three-dimensional influence on the bearing capacity of square and rectangular footings on sand over clay. The finite element limit analysis solutions are used to produce charts to assist designers with estimating the ultimate bearing capacity of granular working platforms overlying clay. The paper also aims to highlight some important considerations when adopting the BRE-470 guideline to design granular working platforms overlying clay.

A Finite Element Analysis of the Effects of Anchorage Reaction Forces and Moments on Structural Stability of Mast Climbing Work Platforms

Mast climbing work platforms (MCWPs) have been increasingly used for construction projects, whereas their safety remains an important issue. As the mast in the Mast climbing work platform (MCWP) system is “slender” structurally, its anchorages must play an important role in maintaining its stability. Therefore, the anchorages and their attachments to a construction structure are likely among the most critical components for the MCWPs. This study developed finite element models of a representative MCWP and applied them to analyze the characteristics of the reaction forces at the anchorages when the work platform operates at different heights and under different loading conditions and to simulate the mast structure responses to the failure of one of the three anchorages. The results of this study indicate that the anchorage reaction forces are sensitive to the loading and operational conditions of the MCWP. The responses of the anchorage reaction forces may reflect the stability status or risk potential of the mast structure of the MCWP to collapse. The characteristics of the anchorage forces identified in this study can be used to help develop a structural safety monitoring system, to minimize the risk of catastrophic failures of MCWPs. The knowledge obtained in the study would help improve MCWP safety management at construction sites and help MCWP manufacturers to improve anchorage design and installation procedures to reduce the risk of the mast structure’s instability or collapse.

Stratified pathways into platform work: Migration trajectories and skills in Berlin’s gig economy

Platform labour scholars have noted the prevalence of migrant workers in the gig economy. This paper builds on this research but interrogates the broad concept of ‘migrant labour’. The study draws on biographical interviews with platform workers in grocery delivery and domestic work platforms in Berlin, Germany as well as expert interviews with union representatives, migrant organisations and white-collar platform company employees. Through an examination of the mobility strategies of platform workers in this subset of the platform economy, the study reveals a stratification of migrant trajectories and of skills needed to engage in platform work across different types of labour platforms. The study finds that platform companies draw on a workforce that consists of recently arrived young migrants with comparatively high education, language skills and digital literacy. Through close analysis of an understudied section of the gig economy, the paper contributes to the ongoing theorisation of the nexus of migration regimes and platform-mediated labour regimes. The findings complicate the notion of ‘accessibility’ of platform work and call for the inclusion of visa regimes, immigration categories and particular skill sets in future research on platform labour.

Algorithmic management on digital labour platforms: A systematic literature review

This study aims to understand algorithmic management in digital work platforms. To this end, a systematic literature review was conducted in the main databases of the Administration field. Initially, 912 studies were surveyed that went through inclusion and exclusion criteria, resulting in a corpus of 39 articles. The results produced demonstrated the existing research perspectives, definitions and conceptualizations, their similarities and discrepancies, assisting the development of future research and leading researchers in the area. The contribution of this study consists in making the conceptualization process of algorithmic management more understandable and systematic, guiding towards a uniform direction instead of scattered perspectives.

Blockchain and Machine Learning-Based Hybrid IDS to Protect Smart Networks and Preserve Privacy

The cyberspace is a convenient platform for creative, intellectual, and accessible works that provide a medium for expression and communication. Malware, phishing, ransomware, and distributed denial-of-service attacks pose a threat to individuals and organisations. To detect and predict cyber threats effectively and accurately, an intelligent system must be developed. Cybercriminals can exploit Internet of Things devices and endpoints because they are not intelligent and have limited resources. A hybrid decision tree method (HIDT) is proposed in this article that integrates machine learning with blockchain concepts for anomaly detection. In all datasets, the proposed system (HIDT) predicts attacks in the shortest amount of time and has the highest attack detection accuracy (99.95% for the KD99 dataset and 99.72% for the UNBS-NB 15 dataset). To ensure validity, the binary classification test results are compared to those of earlier studies. The HIDT’s confusion matrix contrasts with previous models by having low FP/FN rates and high TP/TN rates. By detecting malicious nodes instantly, the proposed system reduces routing overhead and has a lower end-to-end delay. Malicious nodes are detected instantly in the network within a short period. Increasing the number of nodes leads to a higher throughput, with the highest throughput measured at 50 nodes. The proposed system performed well in terms of the packet delivery ratio, end-to-end delay, robustness, and scalability, demonstrating the effectiveness of the proposed system. Data can be protected from malicious threats with this system, which can be used by governments and businesses to improve security and resilience.

How Platform Economic Dependence Leads to Long Working Time: The Role of Work Pressure and Platform HRM Practices

Drawing upon the conservation of resources (COR) theory, this paper discusses the effect of platform economic dependence on working time and the mediating role of work pressure, as well as the boundary role of platform human resource management practices, with a survey of 9576 takeaway riders. The results suggest that the greater the economic dependence of takeaway riders on the platform organization, the longer they work; work pressure plays a mediating role between platform economic dependence and working time; the amount of platform rewards has no effect on the positive relationship between platform economic dependence and working time, whereas the difficulty of obtaining platform rewards strengthens the positive relationship between platform economic dependence and working time. This paper contributes to the literature on gig work by providing a micro-individual perspective and to the literature on COR theory by enriching the studies of resource caravan passageways.

Sustainable transformation of bio-waste into bio-compatible carbon dots for highly specific and sensitive detection of monosodium glutamate in food products

In this work, a simple and convenient sensory platform based on the fluorescence quenching and paper-based probe has been developed using carbon dots (CQDs). The CQDs prepared from waste rice straw (RS@CQDs) as a precursor source. Significantly, low value of detection (1.33 nM) and a wide linear response (5 nM to 80 μM), as well as good stability and repeatability endowed them to be highly sensitive and efficient probe for the quantitative analysis of monosodium glutamate (MSG) ions. Interferences from various biological compounds were also investigated for the developed sensor. Further, the RS@CQDs-based sensor efficiently detected MSG ions in real food samples. The portable and highly sensory podium for the visual detection of MSG in aqueous samples with LOD as low as 1 nm has also been prepared.

Multi-objective Evolutionary Algorithm Supported Construction of Architectural Window Design Model Based on Visual Comfort - A Case Study of Office Buildings in Cold Regions

Abstract With the accelerated advancement of big data Internet development, people gradually realize the urgency and importance of energy saving, so the multi-objective optimization research for the performance of office buildings in cold regions is significant, and this paper focuses on the construction of a building window design model based on visual comfort supported by multi-objective evolutionary algorithm- taking office buildings in cold regions as an example, firstly, by reviewing the literature to understand the principle, algorithm, and concept of multi-objective evolution, construct the building window design model based on visual comfort according to the objective function and extract the standard model of inner corridor slab space building in office buildings in cold regions of Harbin and Shenyang. The optimized design of building window parameters was carried out using the established joint simulation and optimization work platform. The results show that for Harbin, as the window heat transfer coefficient increases, the heating energy consumption increases, the cooling energy consumption increases more slowly, and the total energy consumption increases linearly. An increase in window heat transfer coefficient by 0.1W/ (m 2 ∙K) Increases are cooling energy consumption by 0.18%, heating energy consumption by 0.78%, and total energy consumption by 0.46%. For Shenyang, as the window heat transfer coefficient increases, the heating energy consumption increases, the cooling energy consumption increases more slowly, and the total energy consumption increases linearly. If the heat transfer coefficient of the window increases by 0.1W/ (m 2 ∙K), cooling energy consumption increases by 0.18%, heating energy consumption increases by 0.78%, and total energy consumption increases by 0.46%. This study provides a theoretical basis for extracting standard models for other building types while making the results more generalizable and improving the efficiency of sustainable office building design.

Using machine learning to identify patient characteristics to predict mortality of in-patients with COVID-19 in south Florida.

The SARS-CoV-2 (COVID-19) pandemic has created substantial health and economic burdens in the US and worldwide. As new variants continuously emerge, predicting critical clinical events in the context of relevant individual risks is a promising option for reducing the overall burden of COVID-19. This study aims to train an AI-driven decision support system that helps build a model to understand the most important features that predict the "mortality" of patients hospitalized with COVID-19. We conducted a retrospective analysis of "5,371" patients hospitalized for COVID-19-related symptoms from the South Florida Memorial Health Care System between March 14th, 2020, and January 16th, 2021. A data set comprising patients' sociodemographic characteristics, pre-existing health information, and medication was analyzed. We trained Random Forest classifier to predict "mortality" for patients hospitalized with COVID-19. Based on the interpretability of the model, age emerged as the primary predictor of "mortality", followed by diarrhea, diabetes, hypertension, BMI, early stages of kidney disease, smoking status, sex, pneumonia, and race in descending order of importance. Notably, individuals aged over 65 years (referred to as "older adults"), males, Whites, Hispanics, and current smokers were identified as being at higher risk of death. Additionally, BMI, specifically in the overweight and obese categories, significantly predicted "mortality". These findings indicated that the model effectively learned from various categories, such as patients' sociodemographic characteristics, pre-hospital comorbidities, and medications, with a predominant focus on characterizing pre-hospital comorbidities. Consequently, the model demonstrated the ability to predict "mortality" with transparency and reliability. AI can potentially provide healthcare workers with the ability to stratify patients and streamline optimal care solutions when time is of the essence and resources are limited. This work sets the platform for future work that forecasts patient responses to treatments at various levels of disease severity and assesses health disparities and patient conditions that promote improved health care in a broader context. This study contributed to one of the first predictive analyses applying AI/ML techniques to COVID-19 data using a vast sample from South Florida.

Technology-Assisted Hip and Knee Arthroplasty in Orthopaedic Residency Training: A National Survey.

The adoption of technology-assisted total joint arthroplasty (TA-TJA) is increasing; however, the extent to which TA-TJA is used among orthopaedic trainees is unknown. The purpose of this study was to assess the current use of TA total knee arthroplasty (TKA) and total hip arthroplasty (THA) by orthopaedic residents and to evaluate resident perceptions toward TA-TJA in their surgical training. In this cross-sectional study, an anonymous electronic survey was sent to all Accreditation Council for Graduate Medical Education-accredited orthopaedic surgery residency program coordinators to distribute to their PGY-2 to PGY-5 residents. The survey consisted of 24 questions, including resident demographics, utilization of TA-TJA in their training, and perceptions regarding TA-TJA. A total of 103 orthopaedic residents completed the survey, of whom 68.0% reported using TA-TJA at their institution. Of the residents using TA-TJA, 28.6% used TA for total TKA only, 71.4% used TA for both TKA and THA, and none used TA solely for THA. One-third of residents (33.3%) use TA for more than half of all TKAs conducted, whereas 57.0% use TA for <10% of all THAs conducted. Approximately half of all residents (49.5%) thought that training in TA-TJA should be required during residency, with no significant differences between junior and senior level residents ( P = 0.24). Most (82.0%) thought that trainees should be required to learn conventional TJA before learning TA-TJA. 63.0% thought that technology had a positive effect on their primary TJA training experience; however, 26.0% reported concern that their training conducting conventional TJA may be inadequate. This study demonstrates that most orthopaedic residents currently conduct TA-TJA and highlights notable differences in TJA training experiences. These results provide a platform for future work aimed at further optimizing TJA training in residency, particularly as technology continues to rapidly evolve and utilization of TA-TJA is projected to grow exponentially. N/A, survey-based study.

Design and optimization study of a resistance structure for an industrial storage platform supporting injection molding tools for the automotive industry

The paper offers an optimized solution for an industrial storage platform supporting injection molding tools used to produce thermoplastic components in the automotive sector. After analyzing the current situation for storing the massive tools, a work platform was proposed in order to ensure the conditions imposed by the extension of the company’s implementation of LEAN methods to streamline the production flow. The design of the resistance structure was modeled in the program Autodesk Inventor Professional 2020, taking into account realistic loads and their statistical distribution in the construction of the static and loading scheme of the main beam. The analysis of stress and strain in the main beam under the action of external loads was performed using the finite element method of the program Autodesk Inventor Nastran. The optimized solution for the main beam has been found by analyzing the optimization possibilities in three steps: structural optimization, dimensional optimization and the validation of the proposed optimization options, by verifying the safety of the structure. This paper presents in detail the choice of optimization criteria, decision variables, constraints and objective function. Based on the numerical analysis of mechanical stress and safety coefficient in operation, an optimal variant was chosen from the analyzed models: recessed articulated structure simple and with intermediate support, using laminated profiles IPE 200 and IPE 140.

MODERN METHOD OF APPLYING THE MIXTURE ON A VERTICAL SURFACE

When applying mixtures to a vertical surface, it is not always possible to use stationary equipment. This includes scaffolding, cradles, aerial work platforms, and, for small volumes, installation climbers. The mixture is usually applied with a roller, brush or spray gun. These methods lead to excessive consumption of the mixture, increased work time, and often a lack of safety precautions. Working at height is very dangerous, especially in the current environment. Therefore, both in our country and abroad, scientists are developing new alternatives to manual, semi-manual and mechanised methods. One of these mechanisms is automation and robotics. The task of the workers is to control the work processes, monitor the supply of materials and replace equipment as necessary. Such mechanisms are operated by up to three workers. Having studied all the available information, the authors proposed to use the Portal equipment to perform a range of works at height. It will allow you to perform work on slopes, terraces, and hard-to-reach places. To do this, you need to make a small terrace, level the surface, mount the rails, and install the Portal. Then, using additional mechanisms, the equipment is attached. In the first stage, augers are used to drill a well into which the reinforcement is installed, and the concreting process is carried out using various removable devices (winches, drills, etc.) that are attached to the Portal. In the second stage, the ground is excavated, and the pile is exposed by 3.6 metres. In the third stage, a wooden formwork is placed between the piles. The frame is partially attached to the pile, and the outer side of the formwork is mounted. The concreting process is carried out sequentially. First, the lower part is concreted, and then the upper part. In the fourth stage, the mixture is applied to the surface. The article presents and analyses the results of laboratory studies of the operation of the Portal equipment with a device for intensifying the injection of a flowing mixture. The following schemes were considered when choosing the technology of mixture injection: perpendicular-straight-line, perpendicular-circular and inclined-straight-line. The optimal combinations of layer thickness and the angle of inclination of the nozzle axis to the surface and technological schemes of application are given.

Social Relations of IT Professionals with Other Professional Groups: Network Modeling and Results of Empirical Analysis

Introduction. The relationship of IT specialists to representatives of other professional groups is built in different ways – from cooperation to conflicts. The important practical significance of the analysis of this problem actualizes the development of theoretical and methodological foundations for the study and diagnosis of relations between IT specialists and representatives of other socio-professional groups based on an appeal to values. This is important for a holistic understanding of the trends in the development of the social structure of modern society.Methodology and sources. The multi-paradigm platform of work is formed on the ideas of two directions. Firstly, the fundamental principles of the theory of P.A. Sorokin on the sociodynamics of values in the process of social development are used; the ideas of D.A. Leontiev on the connections of individual and group values; approaches to the construction of methodological procedures for diagnosing values, set out in the works of V.A. Yadov and N.I. Lapin. Another part of the study is formed on the provisions M. Grannoweter’s theory of the strength of weak ties. The methodological procedure of the study is based on the technologies for assessing the relevance of professions proposed by J. Holland.Results and discussion. On the basis of network models of relations between IT specialists, it is shown that interaction with professionals of various professional groups is carried out in different ways. The professional groups with which IT specialists develop tense relations are shown, which is due to the specifics of their professional competencies. The sociodynamics of changes in professional values is revealed as the status and role positions of IT specialists change.Conclusion. The conducted research shows that the attitudes of IT specialists to actors of other professional groups of external social interaction are built inconsistently and ambiguously. Relationships between IT professionals and other professions are formed more like relationships oriented towards different values and variables. In this sense, a group of IT professionals can be perceived as a special case. Unlike relationships within the group of IT professionals themselves, relationships with professionals of other specialties are predominantly situational in nature and are more likely determined by some specific conditions and circumstances, specific people and specific factors than by the unity or solidarity of professional values and interests.