Classes Of Artifacts Research Articles

OCCMNet: Occlusion-Aware Class Characteristic Mining Network for multi-class artifacts detection in endoscopy.

Multi-class endoscope artifacts detection is crucial for eliminating interference caused by artifacts during clinical examinations and reducing the rate of misdiagnosis and missed diagnoses by physicians. However, this task remains challenging such as data imbalance, similarity, and occlusion among artifacts. To overcome these challenges, we propose an Occlusion-Aware Class Characteristic Mining Network (OCCMNet) to detect eight classes of artifacts in endoscope simultaneously. The OCCMNet comprises the following: (1) A Dual-Branch Class Rebalancing Module (DCRM) rebalances the impact of various classes by fully exploiting the benefits of two complementary data distributions, sampling and detecting from the majority and minority classes respectively. (2) A Class Discrimination Enhancement Module (CDEM) effectively enhances the discrepancy of inter-class by enhance important information and introduce nuance information nonlinearly. (3) A Global Occlusion-Aware Module (GOAM) infers the obscured part of the artifacts by capturing the global information to initially identify the obscured artifacts and combining local details to sense the overall structure of the artifacts. Our OCCMNet has been validated on a public dataset (EndoCV2020). Compared to the latest methods in both medical and computer vision detection, our approach demonstrated 3.5-6.5% improvement in mAP50. The results proved the superiority of our OCCMNet in multi-class endoscopic artifact detection and demonstrated its great potential in reducing clinical interference.

The Multifaceted Possibilities of Small Objects: Notes of the Potential of Southern Levantine Signet Rings

Signet rings constitute a class of materials whose study lies at the intersection of ancient jewelry and glyptic. Traditional approaches to the study of this artifact class have focused almost exclusively on issues related to typology, iconographical apparatus, and art historical analyses, with little consideration to the cultural and social interconnections. Signet rings may constitute a case study in their fundamental importance for a more complete picture of the trade networks, people and material movements and interconnections between peoples, cultures, and societies in the world of the Southern Levant within the context of the Eastern Mediterranean basin.

Diamonds in the rough - reconsidering the scientific and heritage value of heat-altered stones in prehistoric archaeology through a systematic literature review.

Heat-altered stones (HAS) are commonly reported in prehistoric sites across several continents, yet they continue to be generally overlooked and systematic studies on them are scarce. We performed a systematic literature review which consisted of searching journal articles, book chapters and books published in English, in Scopus and Web of Science. We collected information on their geographic distribution, chronology, composition, technological aspects and subsistence contexts from 73 records. Our aims were to assess the challenges and opportunities of analysing HAS, while highlighting that this class of artefacts is still largely an untapped source of information on prehistoric human activities. HAS have been documented since the Pleistocene, attesting that culinary and non-culinary activities using heating stones emerged among foraging groups subsisting on hunting, fishing and gathering. The high frequency of HAS during the middle and late Holocene testifies to the continuation of some practices over long time periods, amid the emergence of new food systems, and the introduction of new resources and technologies, such as domesticated plants and animals, and ceramic containers. A considerable lack of studies on HAS from Africa, Oceania, Asia, and South America was noted, all of which are key geographic areas for assessing the role of heating stones in human evolution, geographic dispersal, early cuisine and diet, and cultural transmission across the globe. Our results highlight the persistent challenges archaeologists face in establishing fundamental definitions and diagnostic criteria for identifying HAS, while emphasizing the importance of HAS as essential elements for studying ancient foodways and cultural heritage. We call on archaeologists and cultural heritage managers to reconsider the heritage value of HAS and include them in specialised research agendas before significant knowledge of our past is lost.

Directed Lobish-based explainable feature engineering model with TTPat and CWINCA for EEG artifact classification

Directed Lobish-based explainable feature engineering model with TTPat and CWINCA for EEG artifact classification

Method of automated knowledge base construction for вusiness process management information systems

The object of research is the process of automated construction and enrichment of a knowledge base. An approach has been defined to address the problem of automated knowledge base construction in information system development projects. Research has been conducted on models and methods for the automatic construction of a knowledge base for process management information systems. It has been determined that finite predicates, as well as predicate models describing IT project artifacts, are suitable as the mathematical apparatus. The method for automated construction and enrichment of a knowledge base for process management information systems has been improved based on modified predicate models. The modification involves adding new predicates and aligning event logs with classes of artifacts and their properties. The feasibility of applying the proposed method in decision support tasks under intrusion detection conditions for processes in computer systems has been verified. The architecture and description of the main characteristics of the automated knowledge base construction system for decision-making tasks in IT enterprises, are provided. The proposed solutions have been tested during the automated construction of a knowledge base in an IT project. Advantages and disadvantages of the method were identified during the automated construction of a production knowledge base. Further development of the modified method may involve analyzing the success of predictions made using the knowledge base and adjusting the initial set of predicates based on the results of this analysis.

Extreme Convective Gusts in the Contiguous USA

Most damage to buildings across the contiguous United States of America (USA) is caused by gusts in convective events associated with thunderstorms. Design rules for structures to resist these events rely on the integrity of meteorological observations and the methods of assessment. These issues were addressed for the US Automated Surface Observation System (ASOS) in six preliminary studies published in 2022 and 2023, allowing this present study to focus on the analysis and reporting of gust events observed between 2000 and 2023 at 642 well-exposed ASOS stations distributed across the contiguous USA. It has been recently recognized that the response of buildings to convective gusts, which are non-stationary transient events, differs in character from the response to the locally stationary atmospheric boundary gusts, requiring gust events to be classified and assessed by type. This study sorts the mixture of all observed gust events exceeding 20 kn, but excluding contributions from hurricanes and tropical storms, into five classes of valid meteorological types and two classes of invalid artefacts. The valid classes are individually fitted to optimal sub-asymptotic models through extreme value analysis. Classes are recombined into a joint mixture model and compared with current design rules.

A Strategic Approach to Stone Tool Economy: An Example from Southwest Germany

ABSTRACT The acquisition and use of stone raw materials by prehistoric groups requires many strategic decisions that affect various costs and benefits. These decisions entail consideration of a number of characteristics of the available materials themselves, including quality, nodule size, source location, spatial distribution and abundance. In addition, they must take into account the intended uses – the types and requirements of the different tools to be made. An example using assemblages of Late Paleolithic and Early Mesolithic artifacts from southwestern Germany explores the nature of such decisions. Aspects of blank production and use of different materials for different classes of artifacts are explored.

Will Artificial Intelligence Affect How Cultural Heritage Will Be Managed in the Future? Responses Generated by Four genAI Models

Generative artificial intelligence (genAI) language models have become firmly embedded in public consciousness. Their abilities to extract and summarise information from a wide range of sources in their training data have attracted the attention of many scholars. This paper examines how four genAI large language models (ChatGPT, GPT4, DeepAI, and Google Bard) responded to prompts, asking (i) whether artificial intelligence would affect how cultural heritage will be managed in the future (with examples requested) and (ii) what dangers might emerge when relying heavily on genAI to guide cultural heritage professionals in their actions. The genAI systems provided a range of examples, commonly drawing on and extending the status quo. Without a doubt, AI tools will revolutionise the execution of repetitive and mundane tasks, such as the classification of some classes of artifacts, or allow for the predictive modelling of the decay of objects. Important examples were used to assess the purported power of genAI tools to extract, aggregate, and synthesize large volumes of data from multiple sources, as well as their ability to recognise patterns and connections that people may miss. An inherent risk in the ‘results’ presented by genAI systems is that the presented connections are ‘artifacts’ of the system rather than being genuine. Since present genAI tools are unable to purposively generate creative or innovative thoughts, it is left to the reader to determine whether any text that is provided by genAI that is out of the ordinary is meaningful or nonsensical. Additional risks identified by the genAI systems were that some cultural heritage professionals might use AI systems without the required level of AI literacy and that overreliance on genAI systems might lead to a deskilling of general heritage practitioners.

Objectionable Commemorations: Ethical and Political Issues

AbstractThe term, "objectionable commemorations”, refers to a broad category of public artefacts – such as, and especially, memorials, monuments and statues – that are regarded as morally problematic in virtue of what or whom they honour. In this regard, they are a special class of public artefacts that are subject to public contestation. In this paper, we survey the general ethical and political issues on this topic. First, we categorise the arguments on offer in the literature, concerning the objectionable nature of such commemorations. Second, we review common political responses to objectionable commemorations. Finally, we identify fruitful areas for further philosophical inquiry on this topic.

Towards an archaeology of everyday life in British Ionian Islands: the cultural itineraries of the Kythera Gin Bottles

SUMMARY During the course of the nineteenth century the island of Kythera, Southwest Greece, was part of the United States of Ionian Islands, under the control of the British empire. This paper explores the materiality of colonialism in local contexts, through the object itineraries of a group of stoneware bottles—a class of artefacts that continues to be represented in domestic assemblages locally today. We examine the diverse ways the vessels became entangled with the lives of individuals, colonialist agendas, and collective perceptions of identity, seeking to identify how the meanings associated with the objects and their relational connections shifted across time and space.

An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training

Large medical imaging data sets are becoming increasingly available. A common challenge in these data sets is to ensure that each sample meets minimum quality requirements devoid of significant artefacts. Despite a wide range of existing automatic methods having been developed to identify imperfections and artefacts in medical imaging, they mostly rely on data-hungry methods. In particular, the scarcity of artefact-containing scans available for training has been a major obstacle in the development and implementation of machine learning in clinical research. To tackle this problem, we propose a novel framework having four main components: (1) a set of artefact generators inspired by magnetic resonance physics to corrupt brain MRI scans and augment a training dataset, (2) a set of abstract and engineered features to represent images compactly, (3) a feature selection process that depends on the class of artefact to improve classification performance, and (4) a set of Support Vector Machine (SVM) classifiers trained to identify artefacts. Our novel contributions are threefold: first, we use the novel physics-based artefact generators to generate synthetic brain MRI scans with controlled artefacts as a data augmentation technique. This will avoid the labour-intensive collection and labelling process of scans with rare artefacts. Second, we propose a large pool of abstract and engineered image features developed to identify 9 different artefacts for structural MRI. Finally, we use an artefact-based feature selection block that, for each class of artefacts, finds the set of features that provide the best classification performance. We performed validation experiments on a large data set of scans with artificially-generated artefacts, and in a multiple sclerosis clinical trial where real artefacts were identified by experts, showing that the proposed pipeline outperforms traditional methods. In particular, our data augmentation increases performance by up to 12.5 percentage points on the accuracy, F1, F2, precision and recall. At the same time, the computation cost of our pipeline remains low –less than a second to process a single scan– with the potential for real-time deployment. Our artefact simulators obtained using adversarial learning enable the training of a quality control system for brain MRI that otherwise would have required a much larger number of scans in both supervised and unsupervised settings. We believe that systems for quality control will enable a wide range of high-throughput clinical applications based on the use of automatic image-processing pipelines.

On the Status of the Boar Tooth Artifact from the Backdirt of Vogelherd

During the course of the excavations in the backdirt of Vogelherd in 2008, the crew recovered a tusk of a boar preserving clear signs of anthropogenic modification. In addition to the polishing that regularly occurs on tusks during the life of the animal, this specimen, showed signs of cut- ting, scraping and polish subsequent to the animal’s death. This artifact superficially resembles a Magdalenian female figurine with a triangular buttock and a stick-like torso, which led to the hypothesis that the find may be of Paleolithic origin and may be an artwork. Alternatively, the find was hypothesized to be an artifact of unknown function from the Holocene, based on the rarity of faunal remains of boar from the Paleolithic of the Swabian Jura. While the excavator always stressed the uncertainty related to the interpretation of the find, some colleagues ac- cepted the hypothesis that the find represented a Magdalenian female figurine. Thirteen years after its recovery, we have reexamined this artifact and conducted comparative studies that support the hypothesis that the find is of Holocene age. Based on similar finds, we conclude that, although the function of this class of artifact is not yet certain, this artifact is a Neolithic or Mesolithic tool with clear parallels in Germany, France and Switzerland. This class of artifact is rare in Central Europe, but our survey of Neolithic and Mesolithic publications allows us to reject the hypothesis, that this find represents a Magdalenian female figurine. This artifact, however, enriches the record of Holocene organic technology in southwestern Germany.

Reassessing the terminal ballistic performance of trilobate and quadrilobate arrow points on Iron Age battlefields.

In the Eurasian Iron Age arrow points comprise a prominent class of artifact. Projectile experiments are useful for studying the ballistic performance of ancient arrow points and implications of arrow point innovations in warfare and shifting socio politics in Eurasia. However, when projectile experiments are not representative of past weapon use, they can lead to misinterpretations of the archaeological record. Notable problems arise when homogeneous target simulants used in controlled experiments are not representative of the targets past weapons were designed to encounter. This article explores the relationship between arrow point morphology and design choices in the Iron Age using different target media. Shooting arrow points into pottery clay leads to the conclusion that more blades reduced penetrating performance on ancient battlefields, but a very different result obtains by shooting the same points into thick tooling leather as a simulant for leather body armor. The results help explain patterns observed in the Eurasian archaeological record, where trilobate arrow points-initially developed by lightly armored horse archers on the Eurasian steppe-were increasingly adopted by a wide range of societies across Eurasia throughout the Iron Age.

Research on the Composition Analysis and Identification of Ancient Glass Products Based on Decision Tree and K-means Clustering Algorithm

Ancient glass is susceptible to weathering by environmental influences, resulting in changes in its chemical composition and proportions, which affects the correct judgment of its category by archaeologists. In order to correctly analyze and identify the composition of ancient glass artifacts, firstly, this paper establishes a decision tree model to derive the basis for determining the type of glass artifacts. Secondly, the aggregation coefficients of high potassium glass and lead-barium glass were plotted separately in this paper, and the K-value of clustering was determined to be 2 according to the elbow rule. After using principal component analysis to reduce the dimensionality of the chemical composition content data, the K-means clustering algorithm was used to classify the subclasses of high potassium glass and lead-barium glass respectively. Finally, the established model was used to identify the chemical composition and its type of unknown class of glass artifacts.

Exploration And Analysis of Weathering Factors of Glass Artefacts Based on Cluster Analysis and Grey Correlation Analysis

The aim of this paper is to investigate the relationship between the chemical composition of ancient glass artefacts after weathering and to construct a model for classifying and predicting the class of artefacts based on some of the characteristics of the ancient glass artefacts obtained. Cardinality tests, information entropy, cluster analysis, support vector machines and grey correlation are mainly used to conduct the study. Through chi-square test, the relationship between weathering of glass relics and glass type, glass color and glass pattern is explained. Finally, the relationship between weathering and glass type is closer. Information entropy was used to explain the relationship between the weathering of cultural relics and the content of chemical components contained in cultural relics. Among them, potassium oxide ( O) and calcium oxide (CaO) had the largest information gain. The effective information gain of lead barium is silicon dioxide (Si ), potassium oxide (PbO), copper oxide (CuO) and sodium oxide ( O). By using cluster analysis, the law analysis and corresponding subcategories of high-potassium cultural relics and lead-barium cultural relics are made, and 3-5 subcategories are formed. Support vector machine was used to judge the type of glass relics, and the final result was that A1, A6 and A7 were high potassium. A2, A3, A4, A5, A8 are lead barium; The correlation coefficient matrix was used to analyze the correlation between the chemical components in different kinds of cultural relics, and the differences were explained based on the results of grey correlation degree analysis. Finally, the conclusion was drawn: in the firing process of high-potassium glass, the substance with high potassium content as the co-solvent did not have an essential effect on the formation of high-potassium glass. However, lead barium glass is different. As lead ore (high content of lead oxide and barium oxide) is added as co-solvent in the firing process, lead barium glass produced by firing contains a large amount of lead oxide and barium oxide.

IMPACT OF OSCILLOMETRIC MEASUREMENT ARTEFACTS IN AMBULATORY BLOOD PRESSURE MONITORING ON ESTIMATES OF AVERAGE BLOOD PRESSURE AND OF ITS VARIABILITY: A PILOT STUDY

Objective: Ambulatory blood pressure monitoring (ABPM) plays an important role in the diagnosis of hypertension. However, methodological factors and the measurement conditions affect the results and may lead to incorrect classification of the patient. We performed a pilot study to evaluate the impact of oscillometric measurement artefacts on ABPM-derived variables. Methods: Four classes of artefacts have been detected: motor activity artefacts, cuff errors, cardiovascular arousals, and arrhythmias. These artefacts were identified via simultaneous recording of actigraphy, cuff pressure, and an ECG. The data consisted of uncorrected measurements (all data), corrected measurements (all artefact free data), and artefact affected data. Design and method: A total of 30 individuals (9 female / 21 male, aged between 36 and 86 years, mean: 65.5 (SD: 9.5) were included in the study. The 24h average blood pressure (BP) was higher in artefacts-affected measurements compared the artefact-free measurements both for systolic (4.6 mmHg) and diastolic (1.3 mmHg) measurements. Further, artefact-affected systolic BP (SBP) was 6.4 mmHg higher than artefact-free measurements during daytime. On average, nocturnal measurements showed no artefact-depended differences. However, individual comparisons yielded that 23% of the subjects crossed the threshold for BP classification for either 24-h, daytime or nocturnal hypertension when comparing uncorrected and artefact-free measurements. Dipping classification changed in 24% of subjects. BP variability was 21% and 12% higher for SPB and DBP, respectively, during daytime when comparing uncorrected and artefact-free measurements. These differences were even higher (27% for SBP and 21% for DPB) when focussing on night-time BP variability. Conclusions: The study reveals that measurement artefacts are frequently present during cuff-based ABPM and do relevantly affect measurement outcome. Exclusion of measurement artefacts is a promising approach to improving cuff-based ABPM accuracy.

An analytical identification model for ancient glass based on support vector machine and cluster analysis

Glass artifacts are easily weathered by environmental influences during burial, and the internal chemical composition is exchanged with the external environment, resulting in changes in its composition ratio. For archaeological interrogation, it is of great significance to study the chemical composition of glass before and after weathering and related issues. In this paper, a support vector machine model is used to reasonably separate the data points of high potassium glass and lead-barium glass, and a linear classification function is derived, i.e., the classification law of the two types of glass is obtained. Then, this paper performs R-type cluster analysis on the chemical composition indexes first, and reduces the dimensionality of several indexes; then performs Q-type cluster analysis on the sample detection points, and performs a one-way ANOVA test on the classification scheme of different numbers of subclasses obtained, and finally divides them into four subclasses. On this basis, the data of the unknown class of glass artifacts are substituted into the trained support vector machine model, and the type to which they belong can be determined by calculating the value of the judgment linear classification function.

From settlement patterns to memory of place among Holocene hunter-gatherers at Sai Island, Middle Nile Valley

ABSTRACT Persistent places are the locations where people aggregate, utilise and reuse natural or built features and develop their social identities and interactions. A network of persistent places forms interconnected persistent settlement patterns, which create a humanly made or storied landscape with a shared community-based memory of place. Although it has been demonstrated that persistent settlement patterns long preceded the onset of Neolithic farming villages, the Levant has received the most attention regarding this perspective. At the same time, Africa still needs to be addressed. This paper provides an illustrative case study of persistent settlement patterns created by Holocene hunter-gatherers in the Middle Nile Valley of Sudan. It employs geostatistical patterning and visual mapping of an extensive collection of different classes of artefacts (lithic industry, hammerstones, ground stone tools and pottery) from a well-preserved Khartoum Variant site on Sai Island and correlates them to complex architectural features exposed on an archaeological surface (Level 1) at site 8-B-10C dating to the early fifth millennium cal. BC. The combination of multiple in-depth geostatistical analyses of a complex habitation system successfully documents an exceptionally preserved planned intra-site settlement organisation maintained over several generations, revealing a memory of place.

SvCapture: efficient and specific detection of very low frequency structural variant junctions by error-minimized capture sequencing.

Error-corrected sequencing of genomic targets enriched by probe-based capture has become a standard approach for detecting single-nucleotide variants (SNVs) and small insertion/deletions (indels) present at very low variant allele frequencies. Less attention has been given to comparable strategies for rare structural variant (SV) junctions, where different error mechanisms must be addressed. Working from samples with known SV properties, we demonstrate that duplex sequencing (DuplexSeq), which demands confirmation of variants on both strands of a source DNA molecule, eliminates false SV junctions arising from chimeric PCR. DuplexSeq could not address frequent intermolecular ligation artifacts that arise during Y-adapter addition prior to strand denaturation without requiring multiple source molecules. In contrast, tagmentation libraries coupled with data filtering based on strand family size greatly reduced both artifact classes and enabled efficient and specific detection of single-molecule SV junctions. The throughput of SV capture sequencing (svCapture) and base-level accuracy of DuplexSeq provided detailed views of the microhomology profile and limited occurrence of de novo SNVs near the junctions of hundreds of newly created SVs, suggesting end joining as a possible formation mechanism. The open source svCapture pipeline enables rare SV detection as a routine addition to SNVs/indels in properly prepared capture sequencing libraries.

A 2D Geometric Morphometric Assessment of Chrono-Cultural Trends in Osseous Barbed Points of the European Final Palaeolithic and Early Mesolithic

Abstract Studies on prehistoric osseous barbed points have relied heavily on typology in linking presumed types to broader techno-complexes, and for making chronological inferences. The accumulation of both new finds and of radiocarbon dates obtained directly on such artefacts, however, has revealed that (i) shape variability defies neat typological divisions, and that (ii) chronological inferences based on typology often fail. To further query these issues and to better understand the design choices and cultural evolutionary dynamics within this artefact class, we present a 2D open-outline geometric morphometric analysis of 50 directly dated Late Pleistocene and Early Holocene osseous barbed points primarily from northern and western Europe. The results indicate that (a) different components (tip, base, and barbs) of these artefacts were subject to varying design constraints and that (b) there is no clear-cut distinction between Final Palaeolithic and Mesolithic point traditions. Different techno-functional components evolved at various rates while specimens assigned to the same type and/or techno-complex are only occasionally morphologically similar. The results reflect a relatively low level of normativity for this artefact class and likely a repeated convergence on similar design elements. We propose that interpretations linked to cultural dynamics, individual craft agency, and repeated convergence on locally optimal designs may offer more satisfying avenues for thinking about the barbed points of this period.