Versions Of Objects Research Articles

Accountingization of the pandemic multiple: enactments of perceived completeness in accounting representations

PurposeThe aim of this paper is to add to knowledge regarding the role of accounting in managing a crisis, specifically to show the emergence of multiple and contesting accountings and their roles in governing crises.Design/methodology/approachThe empirical case concerns management of the COVID-19 pandemic in Turkey. The analysis is qualitative and based on documents.FindingsThe analysis reveals different enactments of the pandemic multiple: scientific, business, political, patient and household. Within these, accounting representations were used in contention with each other. On the one hand, efforts were made to control the pandemic by testing, quarantines, curfews and other restrictions, supported by the accounts of managerial, political and economic calculations. On the other hand, these accounts were challenged by counter accounts using medical professional calculations.Originality/valueThis study adds new knowledge about the role of calculations in crises by elaborating on the emergence, persistence, transformation and proliferation of accounts that enabled accountingization of the crisis. By understanding the pandemic as an object multiple, I unpack the multiplicity of accounting representations in different enactments. The study also provides new insights into discussions regarding the (in)completeness of accounting. More specifically, different enactments of the pandemic multiple were supported by the perception of completeness among the actors in their accounting representations. The study explored how accounting sustains different versions of objects that existed before accounting while simultaneously trying to relate the different versions: there were both flows and closures between the different enactments of pandemic. In contrast to the argument that the relative completeness of accounting can resolve multiple tensions and that absences trigger innovation, I observed differing interactions among accounting representations while perceived completeness became the source of managing and coordinating the object multiple. That is, accounting is not only used for coordination but also for maintaining the closeness of each enactment of the pandemic.

New objective Liutex vector based on an optimization procedure

The objectivity of a vortex identification method, which is critical in capturing vortices in rotating machineries, requires that the visualized vortical structures are independent of the movement of the observer. However, the common methodology to objectivize an Eulerian vortex identification method with relative/net vorticity or relative/net velocity gradient suffers from the issues of requirement to select a spatial volume to do vorticity average and inconsistency with the non-objective counterpart in an inertial reference frame. In this regard, a new objective Liutex vector method to visualize vortices is developed in the current study, which is based on the observed intermittency of Liutex represented vortices in turbulence. The intermittency indicates that a large volume fraction of the considered domain is void of Liutex, and the rotating motion of the observer is very likely to decrease this volume fraction. Therefore, an optimization procedure is proposed to approximate the rotating angular velocity of the observer by maximizing the zero Liutex volume percentage. With the known angular velocity to offset the rotational effects of the observer’s reference frame, objective version of Eulerian vortex identification methods can be introduced. As an example, the new objective Liutex method has been applied to turbulent channel flow at Reτ=180 in arbitrarily rotating coordinate systems, and the results show that the new method is both objective, i.e. independent of observer’s motion including translation and rotation and consistent with the original Liutex method in an inertial reference frame.

FLAME: A Small Language Model for Spreadsheet Formulas

Spreadsheets are a vital tool for end-user data management. Using large language models for formula authoring assistance in these environments can be difficult, as these models are expensive to train and challenging to deploy due to their size (up to billions of parameters). We present FLAME, a transformer-based model trained exclusively on Excel formulas that leverages domain insights to achieve competitive performance while being substantially smaller (60M parameters) and training on two orders of magnitude less data. We curate a training dataset using sketch deduplication, introduce an Excel-specific formula tokenizer, and use domain-specific versions of masked span prediction and noisy auto-encoding as pre-training objectives. We evaluate FLAME on formula repair, formula completion, and similarity-based formula retrieval. FLAME can outperform much larger models, such as the Davinci (175B) and Cushman (12B) variants of Codex and CodeT5 (220M), in 10 of 14 evaluation settings for the repair and completion tasks. For formula retrieval, FLAME outperforms CodeT5, CodeBERT, and GraphCodeBERT.

Die Wiederentdeckung dreier Mörserkanonen (Bombarden) aus der Waffenkammer der Stadt Hermannstadt (16. Jh.)

The invention of gunpowder in the 9th century can be seen like mankind being gifted fire for a second time. In the centuries to follow it had many practical applications, but the first ballistic usage of gunpowder is mentioned in the 13th century. Shortly after, in the 14th century, the first cannons were created. These empiric versions of artillery objects were bulky and cumbersome metal cannons called bombards. They were cast out of copper alloy such as bronze, or they were made out of iron. The focus of this paper lies on the latter and for that reason a short understanding of metallurgy was necessary. Period documents show that, in the Transylvanian city of Sibiu, there were active workshops for casting cannons since the late 14th century. Geopolitical turmoil in the 15th century forces Transylvanian cities to amass a great deal of fire weapons and arms. Further inquiry showed that in Sibiu, in the 16th century, amongst the weapons being made and kept in the city's arsenal were three mortar canons. Since a great number of the original arsenal is still in existence in the history museum of Sibiu but the collection lacks artillery pieces such as cannons, bombards or mortars, such weapons were considered to be lost throughout history. This paper aims to remediate these by giving back to the city's community its three cast iron mortar cannons.

A General Approach to Sylvester-Polynomial-Conjugate Matrix Equations

Sylvester-polynomial-conjugate matrix equations unify many well-known versions and generalizations of the Sylvester matrix equation AX−XB=C which have a wide range of applications. In this paper, we present a general approach to Sylvester-polynomial-conjugate matrix equations via groupoids, vector spaces, and matrices over skew polynomial rings. The obtained results are applied to Sylvester-polynomial-conjugate matrix equations over complex numbers and quaternions. The main role in our approach is played by skew polynomial rings, which are well-known tools in algebra to provide examples of asymmetry between left-sided and right-sided versions of many ring objects.

Miniaturization as a relevant variable in determining cuteness

The question of what, exactly, makes a child “cute” began with paper, wherein he postulated a number of craniophysical traits which rendered a child “cute” with the resulting appeal and caretaking behavior on the observer. These facial traits became the focus of research. However, there is another trait that renders someone (or something) as “cute” and it is size. Children are essentially miniature adults. A total of 36 Ss of ages 5–86 were recruited to judge whether they considered inanimate objects to be “cute”. It was found in this study that if an inanimate object is a miniature version of another larger object, it was judged to be “cute”.

AeonG: An Efficient Built-in Temporal Support in Graph Databases

Real-world graphs are often dynamic and evolve over time. It is crucial for storing and querying a graph's evolution in graph databases. However, existing works either suffer from high storage overhead or lack efficient temporal query support, or both. In this paper, we propose AeonG, a new graph database with built-in temporal support. AeonG is based on a novel temporal graph model. To fit this model, we design a storage engine and a query engine. Our storage engine is hybrid, with one current storage to manage the most recent versions of graph objects, and another historical storage to manage the previous versions of graph objects. This separation makes the performance degradation of querying the most recent graph object versions as slight as possible. To reduce the historical storage overhead, we propose a novel anchor+delta strategy, in which we periodically create a complete version (namely anchor) of a graph object, and maintain every change (namely delta) between two adjacent anchors of the same object. To boost temporal query processing, we propose an anchor-based version retrieval technique in the query engine to skip unnecessary historical version traversals. Extensive experiments are conducted on both real and synthetic datasets. The results show that AeonG achieves up to 5.73× lower storage consumption and 2.57× lower temporal query latency against state-of-the-art approaches, while introducing only 9.74% performance degradation for supporting temporal features.

SOFTWARE TESTING USING THE CODE REVIEW TECHNIQUE: AN EXPLORATORY STUDY

This paper presents an exploratory study with Belbin roles, in particular role types, in an individual activity consisting of code review. The objective is to identify if, in addition to any of the three types of roles, the position of the fault and the gender of the subject influence the activity of detecting faults in the code. To create an experimental context for the review process, during a work session the subjects, who were software engineering students, used a code with injected faults for their review. With respect to the types of roles, the results of the experiment do not show significant differences either in the efficiency index obtained by the subjects in the testing process, or with the confusion index of failures. On the other hand, regarding the position of the fault, the results show significant differences between the faults detected in the first half of the code with respect to the remaining second half. Regarding the gender of the subject, the experiment does not show a significant difference between the detected errors. At the end of this report, researchers should perform a short-term analysis of the errors introduced in the code to obtain a better version of the experimental object, allowing them to perform a second controlled experiment under less restrictive conditions.

Q-system completion of 2-functors

A Q-system is a unitary version of a separable Frobenius algebra object in a C*-tensor category or a C*-2-category. We prove that, for C*-2-categories [Formula: see text] and [Formula: see text], the C*-2-category [Formula: see text] of ∗-[Formula: see text]-functors, ∗-[Formula: see text]-transformations and ∗-[Formula: see text]-modifications is Q-system complete, whenever [Formula: see text] is Q-system complete. We use this result to provide a characterization of Q-system complete categories in terms of ∗-[Formula: see text]-functors and to prove that the [Formula: see text]-category of actions of a unitary fusion category [Formula: see text] on C*-algebras is Q-system complete.

Opportunistic Digital Twin: an Edge Intelligence enabler for Smart City

Although Digital Twins (DTs) became very popular in industry, nowadays they represent a pre-requisite of many systems across different domains, by taking advantage of the disrupting digital technologies such as Artificial Intelligence (AI), Edge Computing and Internet of Things (IoT). In this paper we present our “opportunistic” interpretation, which advances the traditional DT concept and provides a valid support for enabling next-generation solutions in dynamic, distributed and large scale scenarios as smart cities. Indeed, by collecting simple data from the environment and by opportunistically elaborating them through AI techniques directly at the network edge (also referred to as Edge Intelligence), a digital version of a physical object can be built from the bottom up as well as dynamically manipulated and operated in a data-driven manner, thus enabling prompt responses to external stimuli and effective command actuation. To demonstrate the viability of our Opportunistic Digital Twin (ODT) a real use case focused on a traffic prediction task has been incrementally developed and presented, showing improved inference performance and reduced network latency, bandwidth and power consumption.

Cogency, Seriousness, Cohesion, and Importance: Assessing the Strasbourg Case-Law on Religion or Belief

Abstract In Campbell and Cosans v the United Kingdom (1982), the European Court of Human Rights (ECtHR) determined that a view must ‘attain a certain level of cogency, seriousness, cohesion and importance’ to be considered a religion or belief under Article 9 of the Convention. The Court has seemed hesitant to provide much guidance beyond the words quoted. This article’s first aim is to attempt a comprehensive interpretation of these requirements by examining clues as to their meaning and scope in the case law of the last 40 years. This includes well-known cases like Pretty and Gough, as well as recent cases like Vavřička and De Wilde. The second aim is to evaluate these standards in light of liberal egalitarian principles, specifically, the principle of ‘integrity’ developed by Cécile Laborde. Integrity refers to the value of living in accordance with one’s profound beliefs, which are distinguished from mere preferences and inclinations. The argument presented is that the objective versions of cogency, cohesion, and importance endorsed by the ECtHR are incompatible with the subjectivist value of integrity. Conversely, depending on which of three possible interpretations of seriousness one finds most plausible, the ECtHR’s version of seriousness may align with the integrity view.

Feasible Technology for Augmented Reality in Fashion Retail by Implementing a Virtual Fitting Room

Augmented Reality has become a bridge from the virtual to the real world. This technology has been an implementable choice for fashion companies to provide more information and customization for their user's shopping experience. From the COVID-19 pandemic alongside technological globalization, fashion industries have to find a new way for customers to purchase products. All things considered, AR helped fashion industries keep customers attracted and satisfied. This paper is conducted in a Systematic Literature Review manner to review and compare the AR technologies used by fashion industries. Furthermore, the result would be a proposition of which Augmented Reality technology or platform option is feasible and implementable for the fashion industry. After comparing the technologies used in past papers and their technical and economic feasibility, we propose a 3-term plan. The short-term plan with zero cost and mobile platform-focused application, the medium-term plan with an upgraded version of the garment object from 2D images to 3D objects, and the long-term plan changing the platform used from mobile to a new device. We also conclude that artificial intelligence can also support and improve the augmented reality experience for customers in the fashion retail industry by implementing an AI-powered virtual assistant.

Ergodic Limits, Relaxations, and Geometric Properties of Random Walk Node Embeddings

Random walk-based node embedding algorithms learn vector representations of nodes by optimizing an objective function of embedding vectors and skip-bigram statistics computed from random walks on the network. They have demonstrated state-of-the-art performance in many supervised learning problems such as link prediction and node classification. Yet, their properties remain poorly understood. This paper studies properties of random walk based node embeddings in the unsupervised setting of discovering latent network block structure, i.e., learning node representations whose cluster structure in Euclidean space reflects node adjacencies within the network. We characterize the ergodic limits of the embedding objective, its generalization, and related convex relaxations to derive corresponding non-randomized versions of the node embedding objectives. We also characterize the optimal node embedding Grammians of the non-randomized objectives for the expected graph of a two-community Stochastic Block Model (SBM). We prove that the solution Grammian has rank 1 for a suitable nuclear norm relaxation of the non-randomized objective. Comprehensive experimental results on SBM random networks reveal that our non-randomized ergodic objectives yield node embeddings whose distribution is Gaussian-like, centered at the node embeddings of the expected network within each community, and concentrate in the linear degree-scaling regime as the number of nodes increases.

A Reputation Model of OSM Contributor Based on Semantic Similarity of Ontology Concepts

Due to their status as non-professionals, the reputations of Volunteered Geographic Information (VGI) contributors have a very important impact on data quality. In the process of contributor reputation evaluation in OpenStreetMap (OSM), it is very difficult to calculate the semantic similarity between object versions contributed by volunteers. Aimed at this issue, this paper proposes a model of contributor’s reputation based on semantic similarity of ontology concepts. Firstly, contributors are classified into three categories based on an improved WPCA and classification method. Then, an initial reputation is set for every OSM user in each class according to these categories and related research. Secondly, the related concept ontology is constructed for OSM entities; then, the semantic similarity of the object version is calculated according to the similarity of concept attributes and the semantic distance of concept. The contributor’s evaluation reputation is computed by synthesizing the semantic similarity, geometric similarity, and topological similarity of object versions. Thirdly, the contributor’s evaluation reputation and the initial reputation is aggregated to obtain the contributor’s reputation; finally, the OSM data of Rutland, England, is used as an example to verify the validity of our model. The experimental results show that the proposed model can obtain a more comprehensive contributor’s evaluation by fusing with the semantic similarity of ontology concept. The evaluation bias caused only by the semantic change between versions can be eliminated. Moreover, the obtained user’s reputation is positively correlated with the data quality. The contributor’s reputation evaluation method proposed in this paper is an effective method for evaluating the contributor’s reputation in OSM-like systems.

Evaluating Instability in Degenerative Lumbar Spondylolisthesis: Objective Variables Versus Surgeon Impressions.

In this multicenter cohort study, we prospectively enrolled 408 consecutive adult patients who received surgery for symptomatic DLS. Surgeons prospectively categorized preoperative instability using the existing S-DSIC system. Subsequently, an O-DSIC system was created. Variables selected for inclusion were assigned point values based on previously determined evidence quality. DSIC types were derived by point summation: 0 to 2 points was considered stable, Type I); 3 points, potentially unstable, Type II; and 4 to 5 points, unstable, Type III. Surgeons' subjective perceptions of instability (S-DSIC) were retrospectively compared with O-DSIC types. The O-DSIC system includes 5 variables: presence of facet effusion, disc height preservation (≥6.5 mm), translation (≥4 mm), a kyphotic or neutral disc angle in flexion, and low back pain (≥5 of 10 intensity). Type I (n = 176, 57.0%) and Type II (n = 164, 53.0%) were the most common DSIC types according to the O-DSIC and S-DSIC systems, respectively. Surgeons categorized higher degrees of instability with the S-DSIC than the O-DSIC system in 130 patients (42%) (p < 0.001). The assignment of DSIC types was not influenced by demographic variables with either system. The O-DSIC system facilitates objective assessment of preoperative instability related to DLS. Surgeons assigned higher degrees of instability with the S-DSIC than the O-DSIC system in 42% of cases. Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Blockchain supported BIM data provenance for construction projects

The management of construction projects requires adequate techniques to support the continual exchange of information across disciplines. Recent advances in Building Information Modelling (BIM) have exposed new ways for process and data integration with open data formats, process mapping, and terminology. In construction projects where multiple disciplines produce and share BIM data, mechanisms for defining information priority, provenance and suitability become necessary in order to have consistent and traceable use of data. This includes objects or collection of attributes for data objects that are associated with a discipline or organisation including clear identification of the transaction that has introduced the information. Blockchain can be used to record metadata of BIM objects such as the issuing discipline, object version and responsibility/ liability associated with the data. Blockchain can offer the capability to apply levels of “trust” to individual BIM objects and a more secured framework of collaboration across stakeholders.This paper proposes a Blockchain-based BIM data provenance model to support information exchange in construction projects. By testing the solution in a real-world bridge construction scenario, it has been shown that the approach can recognise the levels of competence and can improve the process of BIM implementation. The proposed approach gives stakeholders more confidence when sharing their BIM data, reduces costs, and improves risk contingencies in construction projects. The paper provides a cost analysis to evidence the implications of using Blockchain for BIM data provenance through an experimental framework supported by an Ethereum public test network. A front-end web page has also been created to facilitate interaction with smart contracts and to monitor the BIM data provenance process.

Digital transit ports for the illicit trade in antiquities: the case of the ‘Afghan Genizah’

AbstractIn this article, we present the idea of a digital transit port, an online space that illicit cultural objects pass through in digital format while on a pathway to public legitimization. These virtual transit ports connect virtual illicit and illegally trafficked cultural objects with virtual consumers under the aegis of promoting access and preservation, while simultaneously normalizing the presence of these objects in market and academic spaces. Digital transit ports, then, make virtual versions of illicit cultural objects openly consumable, much like physical transit ports launder physical cultural objects. They may also legitimize use of the physical objects, infringing on legislative efforts at curbing the illicit trade. To explore the idea of the digital transit port, we will consider the case of the so-called ‘Afghan Genizah’ collection, a disarticulated group of historical documents from northern Afghanistan that have appeared on the international market most likely after being looted and trafficked illicitly outside their country of origin.

Active inspection of objects to detect possible damage and measure their volume using 3D reconstruction

Automated inspection processes offer the advantages of objectivity and efficiency for each test. For this reason, certain techniques for digital image processing and machine vision have been developed. However, it remains an open question due to the great variability in appearance and shape of the objects of study. In this work, we propose an inspection methodology that allows us to analyze objects for which we have developed an active inspection system to detect damage or malfunction. Its operation begins with the acquisition of images of the object using two cameras located in front of a rotating platform, with a controlled rotation, and projecting a laser line on the object. The following is the 3D reconstruction of a section of the object, to then make a comparison using a 3D descriptor and distance analysis between points of the 3D test model and the 3D model generated with a base version of the same object without damage, which was stored in a database. If any damage is detected, the inspection is continued until the entire damaged section is completed and its volume is calculated. The main contributions of our work are summarized as: (i) Efficient combination of machine vision algorithms for volume estimation, (ii) Active inspection in the automatic search for surface damage on objects, and (iii) Measurement of the damage volume detected in metric units , which can be subtractive or additive damage. To validate our proposal, we have applied this methodology to different objects, thus being able to estimate the volume of damage (if any). Our results are promising, as we achieved a Mean Absolute Percentage Error, MAPE=2.78%.

Clinical Frailty Assessment and Associated Outcomes Through COVID-19 Outbreak in a Long-Term Care Facility

Frailty is a syndrome characterized by decreased physiologic reserve resulting from decline across multiple physiologic systems. It is a common condition among elderly patients in nursing homes and has been linked to increased risk of adverse health outcomes. The association of frailty with health and quality of life outcomes in these living in nursing homes during the COVID-19 pandemic is not well understood. Evaluation of Frailty in nursing home residents might help provide an identification tool to recognize patients who are likely to have poor outcomes including rapid deterioration or significant functional decline. Demographics, weights, and functional measures were collected from the electronic medical records and physical therapy records of the residents at a single nursing home in West Virginia. Data was collected from prior to the first positive case at the facility and at the 6-month mark after the first case. A clinical frailty assessment was created using a modified FRAIL-NH scale. Weight loss values were chosen at 2.5% and 5% for the scale. Fatigue was measured using patients’ ability to maintain static balance in sitting and standing positions. The remaining measures were obtained using data from the Modified Barthel Index. Frailty scores were compared pre and post COVID-19 outbreak and infection status to assess risk factors for worsening of frailty status. Preliminary results showed that half of the facility met the cutoffs for frailty initially, with a quarter of the total being pre-frial and a quarter being non-frail. Using Mantel-Haenszel Chi-Square testing, Frailty was compared against sex, dementia, CHF, CVA, CAD, diabetes, asthma, COVID-19 infection, and severe COVID-19 symptoms for pre and post COVID outbreak frailty scores. Only patients with dementia met statistical significance for increased risk of frailty (P= 0.0022). Frailty scores before and after the COVID-19 outbreak at the facility did not show any significant change. COVID-19 infection and/or symptoms were not linked to worsening of or the development of frailty. Further analysis of the subset of patients who did show a decline in frailty score is currently underway. *Finalized data will be presented on the final poster. Frail elderly adults in nursing homes are at high risk for clinical decline and mortality, especially in the setting of a global pandemic. Early recognition of these patients could help identify those at risk for rapid deterioration if they acquire the virus. This study identified nursing home patients who were pre-frail and frail and followed their medical outcome to identify if they were at increased risk for a negative outcome. This objective version of the Frail-NH scale did help identify frail individuals in this facility, but it did not show any correlation between COVID-19 severity and worsening of frailty. Further investigation into those with frailty decline is ongoing to develop a better understanding of what places those patients at higher risk so a targeted intervention can be made.

Q-system completion for C⁎ 2-categories

A Q-system in a C⁎ 2-category is a unitary version of a separable Frobenius algebra object and can be viewed as a unitary version of a higher idempotent. We define a higher unitary idempotent completion for C⁎ 2-categories called Q-system completion and study its properties. We show that the C⁎ 2-category of right correspondences of unital C⁎-algebras is Q-system complete by constructing an inverse realization †-2-functor. We use this result to construct induced actions of group theoretical unitary fusion categories on continuous trace C⁎-algebras with connected spectra.