Artifact Categories Research Articles

Transcranial Direct Current Stimulation Effects on the Neural Substrate of Conceptual Representations.

The aim of this study was to shed light on the neural substrate of conceptual representations starting from the construct of higher-order convergence zones and trying to evaluate the unitary or non-unitary nature of this construct. We used the 'Thematic and Taxonomic Semantic (TTS) task' to investigate (a) the neural substrate of stimuli belonging to biological and artifact categories, (b) the format of stimuli presentation, i.e., verbal or pictorial, and (c) the relation between stimuli, i.e., categorial or contextual. We administered anodal transcranial direct current stimulation (tDCS) to different brain structures during the execution of the TTS task. Twenty healthy participants were enrolled and divided into two groups, one investigating the role of the anterior temporal lobes (ATL) and the other the temporo-parietal junctions (TPJ). Each participant underwent three sessions of stimulation to facilitate a control condition and to investigate the role of both hemispheres. Results showed that ATL stimulation influenced all conceptual representations in relation to the format of presentation (i.e., left-verbal and right-pictorial). Moreover, ATL stimulation modulated living categories and taxonomic relations specifically, whereas TPJ stimulation did not influence semantic task performances.

Unraveling Early Holocene occupation patterns at El Arenal de la Virgen (Alicante, Spain) open-air site: an integrated palimpsest analysis

Palimpsests are ubiquitous in the open-air archaeological record. Yet, integrated intra-site research strategies of palimpsest dissection to infer occupational histories, spatial behavioural patterns and site formation processes remain scarce in the postglacial archaeology. In this work, we apply an integrated protocol of palimpsest analysis to the Mesolithic Unit IV of El Arenal de la Virgen site, radiocarbon dated in two different occupation phases (9.3–9.1 k and 8.6–8.3 k cal BP). While the archaeostratigraphic analysis identified the absence of sterile layers between both phases, the lithic refits confirmed the good preservation of the spatial properties of the assemblage. Using different point pattern analysis and geostatistical techniques, we further investigate the overall distribution pattern, the spatial correlation between lithic remains and occupation features according to different artefact categories, and the variability of spatial autocorrelation in the frequency of burnt microdebris. Our results suggest a behavioural pattern of different, and spatially recurrent, short-term camp occupation episodes. Built on explicit quantitative and reproducible standards, our research approach can be applied to other open-air sites to conduct comparative studies on open-air occupation patterns. This study underscores the importance of considering the palimpsest as an analytical unit and the need for assessing assemblage integrity and site formation processes through multidisciplinary approaches, to better characterise site occupation dynamics.

Harnessing digital community mapping for the development of primary and secondary students’ civic competences: a case study

In this study, we examine a pedagogical activity centered around the collaborative construction of a digital community map, involving students from 4th to 7th grade. Our primary focus is to explore how engaging students in meaningful activities related to their local environment can facilitate the development of civic and social competences. Furthermore, we propose a methodology for analyzing the digital artifacts created by students, with the goal of examining the connection between the discursive actions carried out through the artifacts and different types of social and civic competences. The analysis enables us to discuss four distinct categories of artifacts: Task-oriented, Reflexive/descriptive, Critical/problematizing, and Transformative/agentic. Each category encompasses artifacts that embody a specific set of discursive actions and corresponds to different competences. We claim that identifying the discursive actions that the students perform by means of the artifacts can help teachers to assess the students’ competences during this type of pedagogical activities.

Ethnic and Cultural Affiliation of the Xichaogou Burial Ground Based on Materials of the Xiongnu Culture Belt Plaques

Purpose of the work is to determine the ethnic and cultural affiliation of the population that left the Xichaogou burial ground. Xichaogou is an expressive archaeological complex located in the Liaoning region of China. The uniqueness of this necropolis lies in the fact that several hundred burials of varying degrees of preservation have been recorded in it. Inventory complexes of burials include ceramics, objects made of bronze, iron and stone. The materials of the site demonstrate the features of various cultures – Xiongnu, Buyeo, Han, Xianbi and etc. Since the burial inventory of the Xichaogou burial site demonstrates multicultural features, the question of the ethnic and cultural affiliation of the population that created this site is debatable.Materials and methods. In previous works, the problem of ethnic identification of the Xichaogou burial ground was solved on the basis of certain categories of grave artefacts. In this paper, the questions of the ethnic and cultural affiliation of the Xichaogou sie are considered on the material of the belt plaques decorated in the animal style. The main reason for this choice of material is that the shape and ornament of belt plaques reflect the ethnic and cultural identity of an individual or group in nomadic cultures. 17 belt plaques were found at the Xichaogou site. The entire amount of material is divided into 3 types according to such features as shape, rim ornament (teardrop-shaped, dotted, herringbone), manufacturing technique (presence of through openwork holes), method of fastening (presence of eyelets on the back side), function as part of a belt set (presence peg). A search for analogies to the groups of belt plaques in the Xiongnu culture, identified in the materials of the Sichagou site, has been undertaken.Result. It has been established that belt plaques from the materials of the Xichaogou burial ground find analogies in the vast territory of the Xiongnu culture in Northern Eurasia.Conclusion. It can be concluded that the population that created the Xichaogou site does not belong to the Xiongnu by ethnic origin, but was strongly influenced by this culture. The population of Xichaogou was formed on the basis of the local culture of the previous period. Various and diverse cultures of the eastern part of the Liaoning and the western part of the Jilin regions also contributed to its formation. At the current stage it is possible to identify the Xiongnu and Buyeo cultural components.

Composition analysis and identification of Chinese glass artifacts

Ancient glass is susceptible to weathering by the burial environment, so it is important to promote the study of weathering and erosion of artifacts so as to make targeted conservation measures. In this paper, the chemical composition of ancient glass artifacts, based on logistic regression to obtain statistical patterns of chemical composition of different types of glass artifacts, and the use of hierarchical clustering method to identify unknown types of glass artifacts. Finding the chemical composition patterns of different categories of glass artifacts is an important reference for studying their raw material sources and facilitating comparative studies of artifacts.

Observations Regarding the Terracotta Pipes from the Orăștie Mountains

The following paper brings forth a less studied category of artefacts discovered in the Orăștie Mountains area. The terracotta pipes found in the area since the 19th c. are mentioned in different historical sources, archaeological reports and publications, but they have rarely been treated as the object of particular studies. As such, based on information obtained during my doctoral research that focused on the water management systems of pre-Roman Dacia, I will present some observations regarding the terracotta pipes discovered in the Orăștie Mountains. Before that, I will try to discuss the information and interpretations proposed for this type of artefacts during the last two centuries, in parallel to the general interpretation of the archaeological sites from the Orăștie Mountains and Grădiștea de Munte in particular. All of this is done in order to determine if this category of objects can be related to a certain period and cultural material expression.

Subclass classification of ancient glassware based on K-Means and GMM

This paper focuses on the composition analysis and type identification of ancient glass objects. This paper establishes a judgment model based on the surface characteristics of cultural relics samples, and analyzes the classification laws of high-potassium glass and lead-barium glass; then, the samples of the same category are classified into subclasses according to K-Means method, Gaussian mixture method (GMM) and Mini-Batch K-Means method, and according to each evaluation method, the K-Means method is chosen comprehensively to establish The K-Means method was used to establish a clustering model for glass samples, and the results of subclass classification under each category were obtained. Based on the composition and surface characteristics of the samples, descriptive statistics, scatter plots, S-W test and Pearson correlation coefficient were used to analyze the correlations of chemical compositions among samples of different categories; then, based on the subclass classification made in Problem 2, the differences of the correlations among samples of different categories of artifacts were analyzed using the methods of correlation analysis and difference analysis based on different ranges of data sets.

Classification and Identification of Ancient Glass Objects based on K-means++ and Fisher Discriminant

The significance of this study is to classify and identify the types of ancient glass products according to their chemical composition. The data were selected from the proportion of chemical compositions that have been analyzed for ancient glass, and the best number of clusters (k) for the division was roughly determined using the elbow rule for the five chemical compositions of high potassium and lead barium, respectively, and brought into the k-means++ algorithm for cluster analysis, and then the final determination of k and the evaluation of the rationality of clustering were performed using the contour coefficient, and finally the Fisher discriminant analysis method based on variable meritocracy combined with eigenvalues, Wilke Lambda, and classification function coefficients to identify unknown categories of glass artifacts. The model used was analyzed and evaluated with good results, and the model is applicable to the classification of ancient glass artifacts and identification of the type to which they belong.

Glass Classification and Identification based on K-means++ Clustering Analysis and BP Neural Network Method

The weathering caused by the burial environment will cause the ancient glass to exchange material with the environment, and the weathering layer produced by the material exchange will have an impact on the class judgment of ancient glass. In this paper, we analyze the classification rules of high potassium glass and lead-barium glass; select the appropriate chemical composition for subclass division and establish the classification model of glass. After this, a binary classification (high potassium/lead-barium) model is established by BP neural network training, and the subclassified main components of each type of glass derived from the classification model are used as adjustment variables to analyze the chemical composition of unknown categories of glass artifacts and identify the types to which they belong by controlling a single variable.

Glass Classification and Identification based on Decision Tree and Random Forest Classification Models

Glass artifacts are weathered due to age and improper preservation, etc. This paper analyzes the classification laws of high potassium glass and lead-barium glass based on the data; for each category, suitable chemical compositions are selected to classify them into subcategories, and firstly, a decision tree classification model is used to analyze the classification laws of the two categories of glass by substituting the data set for machine learning, and specific classification methods and classification results are given. And the chemical composition of the unknown category of glass artifacts is analyzed, and the random forest classification model is used to predict the training set and test set by.

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Composition analysis and identification of ancient glass products based on population forest-KNN algorithm

This paper is based on the KNN and Random Forest algorithms in machine learning to analyze the differences and correlations in the compositions of ancient glass objects, determine their classification and identify the unknown categories of artifacts. The classification rules of different types of glass are analyzed; for each category, appropriate sub-classification processes are performed according to their chemical composition, specific classification methods and processing results are given, and sensitivity and rationality analyses are performed on the results. The chemical composition of glass artifacts of unknown categories is analyzed, and then their categories are identified and sensitivity analysis is performed on their classification results. Samples of glass artifacts from different categories and analyze the relationships between their chemical compositions, and compare the differences that exist in the relationships between the chemical compositions of different categories.

Analysis of the chemical composition of ancient glass products and identification of the types to which they belong

The Silk Road is a land artery connecting China and the West, an important passage for East-West trade, and glass products are one of the treasures of early exchanges. Due to different production techniques, the composition and performance of Eastern and Western glass are often very different, but the identification of glass has always been a problem in ancient times. Aiming at the analysis of the composition and source of ancient glass products, this paper designs a mathematical model to avoid duplication of work. Based on the data, this paper calculates the classification rules of the main components of high potassium glass, lead-barium glass; and by selecting the appropriate chemical components as the subcomponents for each category, the specific division methods and division results are given, and the rationality and sensitivity of the classification results are analyzed. And the chemical composition of the unknown category of glass artifacts is identified by the model to identify the type they belong to, and the sensitivity of the classification results is analyzed.

Composition analysis and identification of ancient glass objects based on LightGBM

In this paper, for a batch of existing data related to ancient glass objects in China, by analyzing the relationship between the basic information of cultural relics and the information of chemical composition detected by cultural relics, a prediction model that can predict the chemical composition data before weathering by the chemical composition data after weathering is established, a classification model based on the existing data is built to simulate the original classification law, and the model is used to identify the type of unclassified cultural relics, and then by The importance of the feature selects barium oxide as a criterion for subcategory classification. The proportion of chemical composition of the classified glass artifacts was determined by feature engineering to determine whether the 0 in the detection data was filled in artificially, and it was used as a new feature to reduce the impact of extreme data 0 on the model. The data were then used for model training to obtain the LightGBM classification model. The mean value of the chemical components with the highest feature importance in the model was selected as the criterion for subclass classification, and the values in each class were divided into 2 subclasses. The chemical components with the top 3 feature importance were subjected to sensitivity analysis, and sensitivity judgments were made by the indicators of the model. After first performing feature engineering on the data information of the unknown category of artifacts, the type identification output results were performed using the classification model built in Problem 2. The top 3 chemical components of importance in the model were selected to let their values fluctuate up and down by 5%, and the model indicator curves were plotted for sensitivity analysis.

Subjectivity and social constitution: Contrasting conceptions of institutions, artifacts, and animals.

We systematically compared beliefs about animal (e.g., lion), artifactual (e.g., hammer), and institutional (e.g., police officer) categories, aiming to identify whether people draw different inferences about which categories are subjective and which are socially constituted. We conducted two studies with 270 American children, ages 4 through 10: 140 girls, 129 boys, one not reported; 59% White, 3% Black, 10% Asian, one Native American, 17% multiracial or another race, 11% unreported. We also conducted two studies with 360 American adults recruited from Amazon mechanical Turk. In all four studies we found that children and adults judged institutional categories as more socially constituted than artifactual categories (in all studies) but as less subjective (in three of four studies). Whereas younger and older children's beliefs about subjectivity were similar, younger and older children expressed different beliefs about social constitution. Young children judged none of the category domains as socially constituted; older children differentiated between the three domains. These results support the conceptual independence of subjectivity and social constitution and suggest that concepts of institutions and artifacts differ. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Research on the Prediction of Ancient Glass Artifact Types based on XGBoost and Random Forest Algorithm

Ancient Chinese glass is susceptible to weathering by environmental influences, and its chemical composition has changed considerably thus affecting the category judgment. The classification of ancient glass is mainly divided into two types: high potassium and lead-barium. In this paper, in order to determine the type of ancient glass according to its chemical composition, the multicollinearity phenomenon of many chemical compositions is reduced by using LDA model and then the parameters of XGBoost and RF models are optimized by using GA algorithm and the five-fold cross-validation of existing data sets, and then the weights of XGBoost and RF are optimized by GA algorithm, and finally the GA - XGBoost - RF dual optimization model. The predicted categories can be derived by bringing the chemical composition content of unknown categories of artifacts into the well-trained model, which provides more accurate and faster categorization guidance for ancient glass artifact types to a certain extent.

Inductive Empiricism, Theory Specialization and Scientific Idealization in IS Theory Building

This paper distinguishes and discusses three strategies for theory building in Information Systems (IS) - inductive empiricism, theory specialization, and scientific idealization - and contrasts them in terms of three desiderata of theories - realism, generality, and precision - and the tradeoffs between them. Inductive empiricism, emphasizing realism and generality, represents the received view with the classic Grounded Theory Methodology as a prime example. This paper argues for openness to theory specialization in practical disciplines such as IS. Theory specialization implies sacrificing a generality of theories for their realism and precision. The distinctive attention of the paper lies in scientific idealization, sacrificing the realism of theories for their precision and generality. It has almost been completely omitted in the literature on IS theory building. The special focus of this paper lies in IT applications as a category of IT artifacts and in design-oriented theories that provide knowledge of how to design “better” IT applications. This paper illustrates its points using TAM/UTAUT research.

Component Analysis and Identification of Glass Products Based on Support Vector Machine Comprehensive Classification Model

It is of great significance to study the ancient Silk Road to analyze and identify the types and components of glass products. In this paper, support vector machine (SVM) method is used to study the statistical rule and internal relation between different chemical components of ancient glass products and how to classify ancient glass products. Firstly, the high-potassium glass and lead-barium glass were further divided into subclasses, and then the K-means cluster analysis was carried out. After many fitting repeats, the optimal number of classes was obtained as 5, and the chemical composition characteristics of the classified types were quantitatively analyzed and their ranges were divided. Finally, the five glass types were named as PbO- BaO- SiO2, PbO (~)- BaO- SiO2, K2O- SiO2- Al2O3, PbO- BaO (~)- SiO2- CuO and K2O- SiO2 (~).Then the classification criteria of each category are given on the basis of K-means clustering, and then combined with the support vector machine model, the unknown categories of glass artifacts are classified by machine learning, and finally the final results are obtained by fitting the five ancient glass artifact subcategories based on multiple chemical compositions. And the result probability is predicted from the 5 subclasses, and the maximum probability is taken as the final predicted category.

К ПОСТАНОВКЕ ПРОБЛЕМЫ МАРКЕРОВ КАМЕННЫХ ИНДУСТРИЙ ЭПОХИ ЭНЕОЛИТА И БРОНЗЫ ГОРНО-ЛЕСНОГО ЗАУРАЛЬЯ

The authors propose to discuss the methodology of searching for the defi nitive indicators of flaking techniques of the Eneolithic — Bronze Age in the mountain-forest Trans-Urals. The methodology is based on a step-by-step cross-referencing analysis of raw materials, technological and morphological characteristics of stone artifacts. The multilayer settlement Shaitanskoe 4–6 stone tools assemblage (the Kirovgrad district, Sverdlovsk Oblast) served as the main resource for the analysis. Main stages of the site’s populating correlated with the Eneolithic and the Bronze Age (Cherkaskul culture). Arrowheads were chosen as the key category of artifacts. This choice was based on both the large number of these artifacts (more than 100 items) and their fairly reliable cultural and chronological verification by the well-known interments and single-layer sites of the Urals and the adjacent territories. The Eneolithic flaking technique demonstrated a pronounced variability of tools. Pressure flaking technique used for obtaining blanks of a certain type (blades, microblades, and flakes of preset shapes and sizes) formed the lithic industry basis. During the Bronze Age, the emphasis shifted towards biface-production-oriented striking and counter striking knapping techniques. One of the Bronze Age lithic industry markers was a significant amount of characteristic waste, defected and good blanks as opposed to a small group of two-sided retouched tools with a high level of standardization and manufacturing quality (arrowheads, knives of an asymmetrical triangular shape with an arc-shaped side blade, scrapers of geometric shapes, etc.). The Eneolithic population preferred siliceous and clay shales, high-quality homogeneous jaspers, some types of chalcedony of gray and yellow, homogeneous flint of greenish and greenish-gray shades, and rhyolites of similar colors. During the Bronze Age, most popular materials were mottled flint of mediocre quality, siliceous shales of dark shades, siliceous quartz and chalcedony of light tones, and some varieties of jasper.

The Artifact Problem: A Category and Its Vicissitudes

There is increasing interest in artifacts among philosophers. The leading edge is the metaphysics of artifacts and artifact kinds. However, an important question has been neglected. What is the ontological status of the category ‘artifact’ itself? Dan Sperber (2007) argues against its theoretical integrity for the purposes of naturalistic social sciences. In Section 2, I lay out Sperber’s argument, which is based on the observed continuum between natural objects and artifacts. I also review the implicit support for this continuum argument in the philosophical literature on artifacts. In Section 3, I diagnose the fatal weakness affecting continuum-based arguments about categories. They fail to take into account recent thinking about classification in philosophy of science, which has been forced to accommodate continua in biology. In Section 4, I focus specifically on the species problem in philosophy of biology, and on pluralism about species concepts as a response to it. I then identify an analogous artifact problem, and argue that pluralism about artifact concepts is an appropriate and defensible response here as well. Finally, in Section 5, I show that just as species pluralism leads to skepticism about the species category, so artifact pluralism leads to skepticism about the artifact category. I thus arrive at Sperber’s conclusion by an alternate route that does not run afoul of the weakness affecting continuum-based arguments about categories.