Modes Of Usage Research Articles

Optimizing video feedback for snatch technical error correction in young weightlifters: Comparing the effectiveness of different video playback speeds

Researchers are actively recommending optimal modes of usage for techno-pedagogical tools to ensure that athletes reap the benefits of technology in their training. In this study, we investigated the most effective video feedback viewing speed among normal-speed (NS), half-speed (HS), and quarter-speed (QS), for technical error correction in young weightlifters during the snatch movement. A total of 37 weightlifters (25 boys and 12 girls), aged 11–12 years, were randomly divided into three groups, namely the normal-speed (control group), the half-speed, and the quarter-speed group. Participants completed a pretest (T0), a seven-week snatch learning unit, and a posttest (T1), as well as a retention test one week later (T2). Video-mediated technical analysis of the snatch movement was conducted using the Kinovea motion analysis software. The main results showed that weightlifters who viewed their feedback videos at a quarter of the normal speed (QS) achieved significantly greater improvements in the displacement of the bar in the first pull Dx2 (T1 vs. T0: 27.41 ± 26.10%, Hedges’ g = 0.87, p < 0.05; T2 vs. T0: 24.34 ± 27.11%, Hedges’ g = 1.07, p < 0.05) and the vertical displacement VTR (T1 vs. T0: 22.89 ± 14.16%, Hedges’ g = 1.16, p < 0.05) compared to those who viewed the videos at NS or HS. These findings suggest that slowing down video feedback playback to a quarter of the normal speed can be an effective strategy for enhancing technical error correction in young weightlifters.

Appropriation and usage of management control tools: An imperious reconsideration of the behavioral representations of actors in a public organization

Nowadays, public organizations are in a state of perpetual change. They are part of the need to improve performance supported by the New Public Management (NPM) trend (El Oussa & Fasly, 2023). In this sense, adherence to this movement is materialized by the insertion of management control tools, which are straddled between the instrumental aspect based on a technicality in relation to specific ends (Martineau, 2014) and the behavioral aspect is the real responsible for the fate of these tools. This paper aims to understand how users use appropriate management control tools, by determining the factors behind their usage behaviors. For this purpose, we have applied an interpretivist epistemology by conducting an exploratory qualitative study in a Moroccan public institution, we carried out semi-structured interviews with 10 members of the audit and management control department. Our results show that there are several modes of usage (solid, fragile, rejection) differing from one actor to another. This divergence in behavior is due to institutional factors, factors linked to the tool’s attributes and socio-psychological factors linked to the user. Our results contribute to enriching the literature by deducing the different usages and modes of appropriation supported by the factors that promote or hinder the implementation of management control tools.

Razlike u primeni Kaizena između zemalja i tipova industrije u multinacionalnom lancu snabdevanja

Previous research shows that Kaizen's benefits are multiple and evident, but its practices in the supply chain have been sufficiently examined now. Conversely, we are witnessing numerous issues in contemporary global supply networks. In this survey, after conducting a literature review, three research questions regarding Kaizen modes of usage were formulated and tested on the sample of 195 enterprises that are part of the global supply chain, located in 31 countries, and active in two different types of industries - aircraft, and transportation. A combined approach containing descriptive statistics, reliability, factor analysis, and statistical hypothesis testing by Kruskal-Wallis one-way ANOVA and Mann-Whitney U tests were used. Results show significant differences between Kaizen practices applied in countries such as Italy, the United Kingdom, Canada, the USA, Japan, and China, where national and corporate cultures differ. Kaizen implementation significantly differs between companies operating in the aircraft and transportation sectors, which is unsurprising since aircraft industry has a higher formalization level. The goal to determine the differences in Kaizen practices around the globe was fulfilled since statistically significant differences indicate the importance of the contextual factors and connect adverse and Kaizen events.

“Spotify for News”? User Perception of Subscription-Based Content Platforms for News Media

Subscription-based news platforms (such as “Apple News+” or “Readly”) that bundle content from different publishers into one comprehensive package and offer it to media users at a fixed monthly rate are a new way of accessing and consuming digital journalism. These services have received little attention in journalism studies, although they differ greatly from traditional media products and distribution channels. This article empirically investigates the perception of journalism platforms based on eight qualitative focus group discussions with 55 German news consumers. Results show that the central characteristics these platforms should fulfill in order to attract users are strikingly similar to the characteristics of media platforms from the music and video industries, in particular regarding price points, contract features, and modes of usage. Against this background, the potential and perspectives of a subscription-based news platform for journalism’s societal role are discussed.

Technology Usage and Impacts by COVID-19 among Patients in a Radiation Oncology Clinic

Purpose/Objective(s)Mobile devices provide platforms for consistent and real time symptom tracking for cancer patients, allowing for better symptom reporting and more timely interventions. There is limited research investigating barriers to adoption within the oncology setting and COVID-19 impacts on patent willingness to use health technology. Understanding these issues is key to successful development and implementation. We designed a survey to assess patient willingness and barriers to using mobile devices to report/track symptoms (e-report).Materials/MethodsTwo cohorts of adult patients completed a 21-question anonymized survey. The survey was administered to clinic patients before (PRE) and 18mo after (POST) the start of the COVID pandemic. Three additional questions were added to POST survey to investigate impacts from COVID. Demographics, technology usage, willingness to report data, barriers to utilization, and changes due to COVID were evaluated using descriptive statistics. Predictors of willingness to e-report, barriers to use, and changes due to the COVID-19 pandemic were analyzed using univariate and multivariate logistic regression (MVA).Results318 patients completed the survey (PRE= 144 patients; POST= 174 patients) with mean age 65y, 75% Caucasian, 55% male. Altogether, 75% used a smart phone (PRE=66.7%; POST=81.3%; p 0.003), 90% reported home internet access (PRE=87.5%; POST=91.4%; p 0.259), 86% used a computer (PRE=79.2%; POST=90.8%; p 0.004), and 26% used a wearable health tracker (PRE 25.7%; POST 26.4%; p 0.881). On MVA, age>65 (OR 0.32; p 0.001), annual income>50K (OR 2.16; p 0.032), smart phone ownership (OR 4.07; p 0.000), and new/current patient status (OR 2.15; p 0.020) were all significant factors impacting willingness to e- report. Limited tech literacy (p 0.024) and time commitment (p 0.048) were the only significant barriers. Privacy as a barrier was greater in PRE vs POST cohort (OR 2.3 vs OR 1.1) trending toward significance. Nearly all modes of tech usage were greater in POST vs PRE cohort. POST cohort was significantly more willing to e- report (81.1% vs 69.1%; OR 1.91; p 0.016). This remained significant on MVA after adjusting for age, concern for privacy, tech literacy, and patient status (OR 1.88; p 0.026). Furthermore, 51% of POST cohort reported the pandemic directly influenced their willingness to e-report (40% more, 11% less).ConclusionRadiation oncology patients are willing to use mobile technology to report symptoms. Willingness increases with decreasing age, increasing annual income, smartphone ownership, and new/current patient status. Significant barriers include tech literacy and time commitment. Post-pandemic patients are more willing to e-report and list fewer barriers. The COVID-19 pandemic appears to have had a positive impact on technology usage by patients. Efforts to develop and test mobile applications for this population are justified.

Cellphone-distracted crashes of novice teen drivers: Understanding associations of contributing factors for crash severity levels and cellphone usage types

Objective As novice teen drivers are uniquely susceptible to the harmful effects of secondary activities on cellphones, 38 states and Washington D.C. have banned all types of cellphone usage for drivers younger than 18 years or in the learner/intermediate phase of driving. Despite the prevalence of such cellphone prohibitions, several surveillance studies have highlighted the persistent engagement of teenagers in cellphone-distracted driving, which increases the related crash risk. Most of the prior studies broadly consider cellphone usage as a general distraction instead of investigating different distraction-related tasks associated with cellphone use. This study analyzed the cellphone crashes of novice teenagers (aged 15–17 years) to discover the grouping of contributing factors by crash severity levels and cellphone usage types. Methods The current study collected five years (2015–2019) of related crash data from the Louisiana Department of Transportation and Development. A manual effort was carried out to recognize the type of cellphone tasks before collision by reading the narratives of police-investigated crash reports. Association rule mining was applied to explore the associations between numerous crash attributes in multiple circumstances without relying on any predetermined hypotheses. Results The cumulative effect of cellphone distraction and no seatbelt usage is frequently visible in confirmed injury crash scenarios. Cellphone crashes of novice teenagers at intersections are strongly associated with talking/listening rather than texting/browsing/dialing and reaching for/answering/locating. The associations among environmental factors and modes of cellphone usage significantly influence the manner of collisions. Single-vehicle crashes are associated with cellphone manipulation while driving on weekends in cloudy weather, whereas sideswipe collisions are frequent in evening hours during reaching for/answering/locating the cellphones. In relation to texting/browsing/dialing, novice teenagers operating vans/SUVs are strongly associated with traffic control violations. Conclusions The findings are expected to be beneficial for policymakers and other safety officials to develop strategic planning and implementable countermeasures when dealing with cellphone-distracted novice teenagers. The association of factors identified from the analysis exhibits real-world crash scenarios critical to strengthening driver education programs to mitigate teen driver crashes. Moreover, cellphone crashes and related casualties can be reduced by eliminating or improving one of the attributes involved in the crash patterns.

Case study on optimal design and operation of detached house energy system: Solar, battery, and ground source heat pump

Government policy impacts the level of sustainability for which houseowners design and operate their energy system. Consequently, there is a need to consider the sustainability level resulting from different policies, assuming optimal design and operation. The present work focuses on detached residential houses, where the energy system consists of photovoltaic systems for energy generation and batteries and optional ground-source heat pump systems for energy storage. A mixed-integer linear programming model is presented, which takes policies and other constraints into account when optimizing system size and operation. The results allow overall sustainability validation through parameters like self-sufficiency and self-sustainability, as well as a detailed drill-down of the optimal operation. From the analysis, two modes of ground-source heat pump usage are seen. With a feed-in tariff present, its main use is as an energy source, while without this tariff the optimal use is for seasonal energy storage. It is also found that ground-source heat pump systems contribute to increased sustainability, but they may not be economically beneficial for single-family homes having low or medium heating requirements. Demands for heating and cooling change with time and place, as do available area for photovoltaic energy generation and externally available energy sources. Therefore, a detailed analysis of the kind presented here is recommended before new energy policies are implemented. For each specific house or project, this kind of analysis will also be useful to evaluate the sensitivity of an energy system’s performance towards changing policies.

Therapeutic Claims in Cannabidiol (CBD) Marketing Messages on Twitter.

Although the U.S. FDA has only approved exactly one cannabidiol (CBD) drug product (specifically to treat seizures), CBD products are proliferating rapidly through different modes of usage including food products, cosmetics, vaping pods, and supplements (typically, oils). Despite the FDA clearly warning consumers about unproven health claims made by manufacturers selling CBD products over the counter, the CBD market share was nearly 3 billion USD in 2020 and is expected to top 55 billion USD in 2028. In this context, it is important to assess the presence of health claims being made on social media, especially claims that are part of marketing messages. To this end, we collected over two million English tweets discussing CBD themes. We created a hand-labeled dataset and built machine learned classifiers to identify marketing tweets from regular tweets that may be generated by consumers. The best classifier achieved 85% precision, 83% recall, and 84% F-score. Our analyses showed that pain, anxiety disorders, sleep disorders, and stress are the four main therapeutic claims made constituting 31.67%, 27.11%, 13.77%, and 10.37% of all medical claims made on Twitter, respectively. Also, more than 93% of advertised CBD products are edibles or oil/tinctures. Our effort is the first to demonstrate the feasibility of surveillance of marketing claims for CBD products. We believe this could pave way for more explorations into this indispensable task in the current landscape of social media driven health (mis)information and communication.

Amphipathic environments for determining the structure of membrane proteins by single-particle electron cryo-microscopy.

Over the past decade, the structural biology of membrane proteins (MPs) has taken a new turn thanks to epoch-making technical progress in single-particle electron cryo-microscopy (cryo-EM) as well as to improvements in sample preparation. The present analysis provides an overview of the extent and modes of usage of the various types of surfactants for cryo-EM studies. Digitonin, dodecylmaltoside, protein-based nanodiscs, lauryl maltoside-neopentyl glycol, glyco-diosgenin, and amphipols (APols) are the most popular surfactants at the vitrification step. Surfactant exchange is frequently used between MP purification and grid preparation, requiring extensive optimization each time the study of a new MP is undertaken. The variety of both the surfactants and experimental approaches used over the past few years bears witness to the need to continue developing innovative surfactants and optimizing conditions for sample preparation. The possibilities offered by novel APols for EM applications are discussed.

The Word of God in One’s Hand: Touching and Holding Pendant Koran Manuscripts

Abstract Koran manuscripts that fit comfortably within the palm of one’s hand are known as early as the 10th century CE. For the sake of convenience, all dates will be given in the common era (CE) without further mention, and not in the Islamic or Hijra calendar. Their minute and sometimes barely legible script is clearly not intended for comfortable reading. Instead, recent scholarship suggests that the manuscripts were designed to be worn on the body like pendants or fastened to military flag poles. This is corroborated by some preserved cases for these books which feature lugs to attach a cord or chain, but also their rare occurrence in contemporary textual sources. While pendant Korans in rectangular codex form exist, the majority were produced as codices in the shape of an octagonal prism, and others as scrolls that could be rolled up into a cylindrical form. Both resemble the shapes of similarly dated and pre-Islamic amulets or amulet cases. Building on recent scholarship, I will argue in this article that miniature or pendant Koran manuscripts were produced in similar forms and sizes because of comparable modes of usage, but not necessarily by a deliberate imitation of their amuletic ‘predecessors’. The manuscripts’ main functions did not require them to be read or even opened; some of their cases were in fact riveted shut. Accordingly, the haptic feedback they gave to their owners when they carried or touched them was not one of regular books but one of solid objects (like amulets) or even jewellery, which then reinforced this practice.

Whistleblowing in a time of digital (in)visibility: towards a sociology of ‘grey areas’

ABSTRACT There are currently no concerted attempts to understand the role of whistleblowers in the new social and political environment created by digital ICTs. Digital ICTs drive an accelerating visibility where elites and citizens constantly acquire new tools to track, surveil, and scrutinize each other. Moreover, these technologies make possible a new kind of invisibility. Increasingly complex modes of digital data production and usage generate grey areas that seem to escape legal jurisdiction and democratic oversight. With their privileged access inside these grey areas, conscientious employees-turned-whistleblowers are likely to become key sources for the disclosure of serious wrongdoing in the coming years. The argument is empirically illustrated through three cases that represent different types of grey areas in advanced democracies: big data surveillance (Edward Snowden), tax havens (Antoine Deltour and the Panama and Paradise Papers), and digital political profiling (Christopher Wylie).

SplineLib: A modern multi-purpose C++ spline library

This paper provides the description of a novel, multi-purpose spline library. In accordance with the increasingly diverse modes of usage of splines, it is multi-purpose in the sense that it supports geometry representation, finite element analysis, and optimization. The library features reading and writing for various file formats and a wide range of spline manipulation algorithms. Further, a new efficient and objective-oriented algorithm for B-spline basis function evaluation is included. All features are available by a spline-type independent interface. The library is written in modern C++ with CMake as build system. This enables it for usage in typical scientific applications. It is provided as open-source library.

The Tipping Point

While previous researchers have addressed motivations to join and continue using social media, this paper focuses on why users quit certain social media and change their favorite platforms, such as the current shift from Facebook to Twitter to Instagram and Snapchat. Furthermore, this exploratory study seeks to build an understanding of social media usage and motivations for switching from a cross-cultural perspective by comparing findings from Korean and U.S. users. Findings from 19 focus group sessions (n = 118) highlight influences regarding modes of usage, user control, commitment, addiction, privacy, perceived relationships, self-construals, and social/cultural trends. Findings are further analyzed and compared in light of relevant theoretical frameworks and cultural differences.

Benchmark and Parameter Sensitivity Analysis of Single-Cell RNA Sequencing Clustering Methods.

Single-cell RNA-seq (scRNAseq) is a powerful tool to study heterogeneity of cells. Recently, several clustering based methods have been proposed to identify distinct cell populations. These methods are based on different statistical models and usually require to perform several additional steps, such as preprocessing or dimension reduction, before applying the clustering algorithm. Individual steps are often controlled by method-specific parameters, permitting the method to be used in different modes on the same datasets, depending on the user choices. The large number of possibilities that these methods provide can intimidate non-expert users, since the available choices are not always clearly documented. In addition, to date, no large studies have invistigated the role and the impact that these choices can have in different experimental contexts. This work aims to provide new insights into the advantages and drawbacks of scRNAseq clustering methods and describe the ranges of possibilities that are offered to users. In particular, we provide an extensive evaluation of several methods with respect to different modes of usage and parameter settings by applying them to real and simulated datasets that vary in terms of dimensionality, number of cell populations or levels of noise. Remarkably, the results presented here show that great variability in the performance of the models is strongly attributed to the choice of the user-specific parameter settings. We describe several tendencies in the performance attributed to their modes of usage and different types of datasets, and identify which methods are strongly affected by data dimensionality in terms of computational time. Finally, we highlight some open challenges in scRNAseq data clustering, such as those related to the identification of the number of clusters.

Accurate Estimation of Battery SOH and RUL Based on a Progressive LSTM with a Time Compensated Entropy Index

The accurate estimation of the State of Health (SOH) and Remaining Useful Life (RUL) has been a subject of keen interest due to its impact on safety and condition-based maintenance services. A number of approaches have been proposed to tackle this problem based either on a model-driven or on a data-driven framework. Due to the electro-chemical complexity involved in battery aging, they are yet to achieve the accuracy required, especially, for real-world applications. This is because of the difficulty either in identifying the time-varying nature of model parameters and in collecting the real-world training dataset from widely varying modes of battery usage.
 In this paper, we propose a method of estimating SOH and RUL simultaneously in such a way as to contribute to its real-world applicability. First, noticing that battery aging causes the time sequence of charging and discharging voltage and current in a cycle to be shortened and dispersed, we define an aging index, referred to here as the time compensated entropy, for SOH and RUL. Second, for LSTM-based RUL prediction, we optimize the number of SOH input and the RUL prediction sequences for the minimum prediction error associated with a sequence of cycles. Third, we adopt a progressive framework of LSTMs such that whatever learned from the prior predictions are transferred to the subsequent prediction, starting with learned SOH. For experimental verification, we train the proposed progressive LSTM network based on CALCE datasets and apply to various cases of charging and discharging cycles. With SOH estimated online, we achieve less than 10 cycles of accuracy in RUL prediction, moving closer to real-world applicability.

Задачі та методи аналізу великих даних (огляд)

We review tasks and methods most relevant to Big Data analysis. Emphasis is made on the conceptual and pragmatic issues of the tasks and methods (avoiding unnecessary mathematical details). We suggest that all scope of jobs with Big Data fall into four conceptual modes (types): four modes of large-scale usage of Big Data: 1) intelligent information retrieval; 2) massive (large-scale) conveyed data processing (mining); 3) model inference from data; 4) knowledge extraction from data (regularities detection and structures discovery). The essence of various tasks (clustering, regression, generative model inference, structures discovery etc.) are elucidated. We compare key methods of clustering, regression, classification, deep learning, generative model inference and causal discovery. Cluster analysis may be divided into methods based on mean distance, methods based on local distance and methods based on a model. The targeted (predictive) methods fall into two categories: methods which infer a model; "tied to data" methods which compute prediction directly from data. Common tasks of temporal data analysis are briefly overviewed. Among diverse methods of generative model inference we make focus on causal network learning because models of this class are very expressive, flexible and are able to predict effects of interventions under varying conditions. Independence-based approach to causal network inference from data is characterized. We give a few comments on specificity of task of dynamical causal network inference from timeseries. Challenges of Big Data analysis raised by data multidimensionality, heterogeneity and huge volume are presented. Some statistical issues related to the challenges are summarized. Problems in programming 2019; 3: 58-85

Perceptions of Quality and Household Water Usage: A Representative Study in Jacksonville, FL

When faced with the fear of low-quality tap water, households are motivated to seek out and use alternatives. This study investigated the role of quality perception and aesthetics on choices among three modes of household water usage: unfiltered tap water, filtered tap water, and bottled water. The data were based on a telephone survey of randomly selected households in Jacksonville, FL, conducted during March 2016. As the three modes of water usage were not mutually exclusive, a multivariate probit model was fitted and simultaneous parameter estimates were generated for each of three binary equations. The key results suggest that concerns regarding safety, contamination and sickness linked to unfiltered tap water are associated with increased bottled water usage in the home, but they have no effect on water filter usage. By contrast, complaints about foul-smelling water are associated with increased usage of water filters. In addition, the evidence implies that while water filter usage increases with household income, bottled water usage appears insensitive to changes in income. Finally, African-American households have a higher probability than other racial groups of using bottled water in the home, all else equal.

Аналітика великих даних: принципи, напрямки і задачі (огляд)

We review directions (avenues) of Big Data analysis and their practical meaning as well as problems and tasks in this field. Big Data Analytics appears a dominant trend in development of modern information technologies for management and planning in business. A few examples of real applications of Big Data are briefly outlined. Analysis of Big Data is aimed to extract useful sense from raw data collection. Big Data and Big Analytics have evolved as computer society’s response to the challenges raised by rapid grows in data volumes, variety, heterogeneity, velocity and veracity. Big Data Analytics may be seen as today’s phase of researches and developments known under names ‘Data Mining’, ‘Knowledge Discovery in Data’, ‘intelligent data analysis’ etc. We suggest that there exist three modes of large-scale usage of Big Data: 1) ‘intelligent information retrieval; 2) massive “intermediate” data processing (concentration, mining), which may be performed during one or two scanning; 3) model inference from data; 4) knowledge discovery in data. Stages in data analysis cycle are outlined. Because of Big Data are raw, distributed, unstructured, heterogeneous and disaggregated (vertically splitted), this data should be prepared for deep analysis. Data preparation may comprise such jobs as data retrieval, access, filtering, cleaning, aggregation, integration, dimensionality reduction, reformatting etc. There are several classes of typical data analysis problems (tasks), including: cases grouping (clustering), predictive model inference (regression, classification, recognition etc.), generative model inference, extracting structures and regularities from data. Distinction between model inference and knowledge discovery is elucidated. We give some suggestion why ‘deep learning’ (one of the most attractive topic by now) is so successive and popular. One of drawbacks of traditional models is they disability to make prediction under incomplete list of predictors (when some predictors are missed) or under augmented list of predictors. One may overcome this drawback using causal model. Causal networks are illuminated in the survey as attractive in that they appear to be expressive generative models and (simultaneously) predictive models in strict sense. This means they pretend to explain how the object at hand is acting (provided they are adequate). Being adequate, causal network facilitates predicting causal effect of local intervention on the object. Methods used in Big Data Analytics will be reviewed in the next paper.

Resource portfolio problem under relaxed resource dedication policy in multi-mode multi-project scheduling

The most common approach in the multi-project scheduling literature considers resources as a common pool shared among all projects. However, different resource management strategies may be required for different problem environments. We present the relaxed resource dedication (RRD) policy, which prevents the sharing of resources among projects but allows resource transfers when a project starts after the completion of another one. We treat the case where the available amounts of resources - namely, the capacities - are decision variables subject to a limited budget. This capacity planning problem, called the resource portfolio problem, is investigated under the RRD policy employing both renewable and non-renewable resources with multiple modes of usage. A mixed integer linear programming model to minimise total weighted tardiness is proposed. To obtain some benchmark solutions for this hard problem, the branch and cut procedure of ILOG CPLEX is modified by customised branching strategies, feasible solution generation schemes and valid inequalities.

Technology Studies and Material Culture Studies: Possibilities of Cooperation in the Case of Bone Artefacts

Bone artefacts are among the less thoroughly studied classes of archaeological material, especially in the case of particular periods and regions. The reasons behind this are not uniform. The most obvious and general are linked to the research practices of culture-historical archaeology, often neglecting bone artefacts, considering them not sufficiently attractive or informative. The most significant shift towards recognition of a set of potential information gained from bone objects was achieved in the framework of studies of prehistoric technology during the second half of 20th century, especially in the French archaeological school. This research strategy raised a number of questions concerning the acquisition of raw material, modes of production and usage of objects, whose interpretative potential gained in power, leading to the increased attention paid to faunal remains in archaeological investigations. Yet this source of information on the actual details of relations between people and material culture, opened by technology studies, has not been sufficiently explored. It may be suggested that the reasons are the narrow specialization of researchers and insufficient inclusion of the gathered information into the wider interpretive framework, various traditions and lack of cooperation among the national archaeological “schools”, language barriers etc. However, the main reason behind this state of affairs may be sought for in non-integrated theoretical perspectives and the lack of clearly articulated interpretive position of researchers seeking to apply the knowledge gained from technology studies, considering this strategy as an “objective, scientific method”, providing concrete answers clearly complying to the expectations of the dominant archaeological paradigm.
 The paper offers a critical review of a number of examples of application of technology studies in archaeology and possible directions of a more integrated and theoretically informed approach. One of the obvious solutions may be sought in the direction of another research strategy – material culture studies. The aim of the paper is thus to link these two approaches, whose theoretical foundations are not uniform today, but the history of the ideas and the mode of articulation of the basic theoretical assumptions indicate similar theoretical roots.