Reference Object Research Articles

Inheritance design of residence based on Huizhou traditional dwellings

ABSTRACT Huizhou traditional dwellings have distinctive features such as climate adaptability and white walls and gray tiles. However, the building opening’s size is small and poor insulation performance lead to non-uniformity of indoor illumination, wet and cold winters. This study aims to design a new Huizhou dwelling, taking the typical Huizhou traditional dwelling, Yuqing Hall, as the prototype, new Huizhou dwelling is designed to meet occupants’ living needs and planning functional spaces while inheriting New Huizhou dwelling to the greatest extent. Then using DesignBuilder to simulate, and process the envelopes improvement scheme for indoor lighting and thermal environment that don’t meet the standards. The results showed: There is a gap between the indoor lighting and thermal environment of the preliminary design and the standards, while introduces the light from the stairs into the living room or changes the window size to make the indoor light meet the standards, the wall material of the new Huizhou dwelling uses KPI porous bricks, the roof with air layer and insulation layer and add attic can improve the indoor thermal environment. The results of this study can be used as a reference object when renovating traditional dwellings and designing occupants’ dwellings.

Safety as a synthetic scientific category

This paper the main concepts (schools) of security presented in the literature were analyzed, and it is shown that within their framework a different understanding of the term “security” was formed. It is noted that the monoreference model of B. Buzen and the binary security system of the state and society of O. Waver are being replaced by an understanding of the triad of security organized from the state to the person through society. Thus, the rethought concept of security takes into account not only States and their respective relationships, but also the relationship between the individual, society and the State and their overlapping perceptions of threats, which have become diverse and multidirectional. The combination of these approaches enriches our understanding of security, leads to the conclusion that security is now a complex (synthetic) scientific category, which is the theoretical and methodological basis for cognition and identification of a number of generic concepts: “national”, “public”, “environmental” and other security. According to the position of the authors, it is necessary to conceptualize the concept of “security” and consider it as a system of rational management of fears and threats (through various measures specifically defined in regulatory legal acts for each sector and reference object, consistently implemented by state and non-state actors.

Developmental trajectories of picture-based object representations during the first year of life.

Experience with an object's photograph changes 9-month-olds' preference for the referent object, confirming they can represent objects from pictures. However, picture-based representations appear weaker than object-based representations. The current study's first objective was to investigate age differences in object recognition memory after familiarization with objects' pictures. The second objective was to test whether age differences in object permanence sensitivity with picture-based representations match those found with object-based representations, whereby 7-month-olds search more for familiar hidden objects but 11-month-olds search more for novel ones. Six- and 11-month-olds were familiarized with an object's photo and tested on their representation of the real object by comparing their reaching for it versus a novel object. Objects were visible under conditions testing recognition memory and hidden under conditions testing object permanence. Like 9-month-olds, 6- and 11-month-olds preferred novelty with visible objects, showing early object recognition after picture familiarization, as well as developmental continuity. Unlike 9-month-olds, who switched to preferring familiarity with hidden objects, 6- and 11-month-olds switched to null preference. This pattern fails to match 7- and 11-month-olds' hidden-object preferences after familiarization with real objects, revealing discontinuity in sensitivity to object permanence after picture familiarization, and suggesting that picture-based representations are weaker than object-based ones.

A Method for Calculating the Leaf Area of Pak Choi Based on an Improved Mask R-CNN

The leaf area of pak choi is a critical indicator of growth rate, nutrient absorption, and photosynthetic efficiency, and it is required to be precisely measured for an optimal agricultural output. Traditional methods often fail to deliver the necessary accuracy and efficiency. We propose a method for calculating the leaf area of pak choi based on an improved Mask R-CNN. We have enhanced Mask R-CNN by integrating an advanced attention mechanism and a two-layer fully convolutional network (FCN) into its segmentation branch. This integration significantly improves the model’s ability to detect and segment leaf edges with increased precision. By extracting the contours of reference objects, the conversion coefficient between the pixel area and the actual area is calculated. Using the mask segmentation output from the model, the area of each leaf is calculated. Experimental results demonstrate that the improved model achieves mean average precision (mAP) scores of 0.9136 and 0.9132 in detection and segmentation tasks, respectively, representing improvements of 1.01% and 1.02% over the original Mask R-CNN. The model demonstrates excellent recognition and segmentation capabilities for pak choi leaves. The error between the calculation result of the segmented leaf area and the actual measured area is less than 4.47%. These results indicate that the proposed method provides a reliable segmentation and prediction performance. It eliminates the need for detached leaf measurements, making it suitable for real-life leaf area measurement scenarios and providing valuable support for automated production technologies in plant factories.

A 3D printed plant model for accurate and reliable 3D plant phenotyping.

This study addresses the importance of precise referencing in 3-dimensional (3D) plant phenotyping, which is crucial for advancing plant breeding and improving crop production. Traditionally, reference data in plant phenotyping rely on invasive methods. Recent advancements in 3D sensing technologies offer the possibility to collect parameters that cannot be referenced by manual measurements. This work focuses on evaluating a 3D printed sugar beet plant model as a referencing tool. Fused deposition modeling has turned out to be a suitable 3D printing technique for creating reference objects in 3D plant phenotyping. Production deviations of the created reference model were in a low and acceptable range. We were able to achieve deviations ranging from -10 mm to +5 mm. In parallel, we demonstrated a high-dimensional stability of the reference model, reaching only ±4 mm deformation over the course of 1 year. Detailed print files, assembly descriptions, and benchmark parameters are provided, facilitating replication and benefiting the research community. Consumer-grade 3D printing was utilized to create a stable and reproducible 3D reference model of a sugar beet plant, addressing challenges in referencing morphological parameters in 3D plant phenotyping. The reference model is applicable in 3 demonstrated use cases: evaluating and comparing 3D sensor systems, investigating the potential accuracy of parameter extraction algorithms, and continuously monitoring these algorithms in practical experiments in greenhouse and field experiments. Using this approach, it is possible to monitor the extraction of a nonverifiable parameter and create reference data. The process serves as a model for developing reference models for other agricultural crops.

ЭКСПЕРИМЕНТАЛЬНАЯ ОЦЕНКА ТОЧНОСТИ ПРОСТРАНСТВЕННОЙ СТАБИЛИЗАЦИИ КВАДРОКОПТЕРА DJI AIR 2S*

The paper proposes a method for assessing the actual accuracy of spatial stabilization of a DJI Air 2S quadcopter using its video camera and processing the resulting video sequences with a developed software package in the mode of hovering over a reference object. The software package was implemented using the OpenCV library in Python. To register deviations of stabilization systems from a given position, it is proposed to use a reference field with known geometric parameters, information about which is entered into the processing algorithm. The main task of the software package is to identify the boundaries of the reference field and measure the geometric sides in pixels which allows you to determine the center of the field and measure its deviation relative to the center of the image as well as determine the height of the unmanned aerial vehicle flight. In the work the height measurement algorithm was tested. This technique is used to evaluate the accuracy of quadcopter stabilization with various combinations of navigation sensors used for this purpose. A statistical analysis of the obtained results was carried out and conclusions were drawn about compliance with the characteristics of positioning accuracy declared by the manufacturer using optical obstacle avoidance systems and satellite navigation systems.

Construction of a pillar[5]arene-based supramolecular chiral polymer linked to aminophosphine salt for chiral recognition of enantiomers of mandelic acid.

In recent years, supramolecular chirality has been greatly developed in asymmetric synthesis, chiral sensing and other research fields, but its application in molecular chiral recognition has not been extensively studied. In this paper, L-Boc-tyrosine methoxyester and phosphorus chloride salts were introduced into the framework of pillar[n]arene, and a pillar[5]arene-based supramolecular chiral polymer L-TPP-P was constructed. The supramolecular polymer had stable supramolecular chiral properties and could be used as a chiral solvation reagent for chiral recognition of mandelic acid MA. The molar ratio method and Scatchard plot showed that the complexation ratio of L-TPP-P (pillar[5]arene monomer as the reference object) and MA was 1 : 1, and the complexation constants of L-TPP-P with R-MA and S-MA were 4.51 × 105 M-1 and 6.5 × 104 M-1, respectively. The significant affinity difference of L-TPP-P for different enantiomers of MA showed the excellent chiral recognition and stereoselectivity of pillar[5]arene-based supramolecular polymers for MA. This study provides a new idea for a novel supramolecular polymer chiral recognition reagent or chiral recognition method.

Matching visually observed 3D model to original reference object

In the development of a visual environment simulator or a thermal imager simulator, one of the challenges encountered when assessing the external appearance of engineering structures is the need to ensure the correspondence of the developed 3D model of a reference object to the original 3D object. Since creating a complete model is currently impractical, the criterion for assessment is based on the conformity of forming specified components of the cognitive model of a human observer necessary in their professional activities. Research has shown that to address this challenge, it is advisable to choose one of the artificial intelligence methods to entrust it with the task of evaluating the developed 3D model and minimize the subjectivity in the decision-making process of “whether the external appearance of the 3D model meets the client's requirements.” The article proposes using deductive reasoning in ChatGPT to assess the conformity of the external appearance of a 3D model to a specified 3D object by representing the model as incomplete sequences and evaluating its ability to complete them in accordance with conclusions made by humans.The suggested approach involves solving the problem based on scenarios where humans formulate logical conclusions from provided information, followed by the application of ChatGPT in processing the presented sequences of conclusions. A comparative analysis is presented to determine the extent to which ChatGPT demonstrates deductive reasoning and how closely it aligns with human deductive models. This allows for the creation of a model with deductive reasoning and contributes to discussions on the competencies of artificial intelligence.

Effect of reference objects on the accuracy of digital implant impressions in partially edentulous arches

Effect of reference objects on the accuracy of digital implant impressions in partially edentulous arches

Comparison of the perception of space in virtual reality and in the real world

The subject of the study is investigation the accuracy and identify the features of spatial information perception in virtual reality. During the experiment, the subjects were asked to estimate the distances to objects and between objects in virtual environment in metric units without the presence of reference objects with known dimensions in the virtual environment. It was found that in the complete absence of metric support in the action space in the real world, subjects estimated metric distances with an error of about 2 meters at 8 meters, 3 meters at 13-15 meters, and 2 meters at 30 meters. In contrast, in a virtual environment, the subjects estimated a distance of 8 meters with an error of 4 meters, a distance of 13-15 meters with an error of 7-8 meters, and a distance of 30 meters with an error of 18 meters. Introducing metric support is likely to significantly improve the result, and abandoning the metric distance measurement scale, which is not natural for humans, will considerably increase the accuracy of spatial information perception. It should be noted that in the field of long-range vision (30 meters or more) in virtual reality, the accuracy of information perception is extremely low.

Albeshrs Habb Alhaseed: A Syntactic and Semantic Study

The act of writing, which we read in the prevalent identity discourse in the world of the self or woven by the speaking, writing ego generally, moves in two directions: one is declared and known, and the second is unknown and implied. This implied unknown is often realized in the individual's reference object in its relationship to the movement of time and history, along with the awareness of the human soul that connects the insides of the self and the outer life. This matter represents several aspects of what revolves in the sphere of the self or the ego as an existential framework whose features are explored through the process of the written act, syntactically and semantically, as required by the contexts of self-literary writing that display metaphorical images of the self as it enters the memory room, capturing the parts of the personality that reveal the development of the individual and gathering them in the narrative of the individual’s life. That is what makes this art distinctive, and by that, we mean the act of writing in written genres such as "Memoirs," "Biographies," and "Diaries." These genres are concerned with methods and techniques and are characterized by subtle differences between them in writing and weaving; they take on a special character and have particular connotations when compared to other genres classified in the category of self-writing or the system belonging to reference literature.

A Low-Cost Method and Surveying of the Historical Structures from Digital Resources

A new method using optics in non-contact photogrammetry to find the dimensions of target objects by digital archive and/or open source digital images has been presented in this paper. In the proposed method, a reference object of known dimension must be present in the field of view of a pair of images collected at any two unknown arbitrary positions along the axis of camera (z-axis) and 2D size measurement (x-y) of other target objects, and it is done successfully with the help of the proposed algorithm. The presented method is applicable to the number of images(>=2) containing the target objects and reference object which are not in the same plane and which may be shot from any camera not known to the user. Hence, the internal and external specifications of the camera are completely unknown to the user. The method has been verified successfully to show its applicability in low-cost surveys by determining the dimensions of the Washington-Monument, Christ the Redeemer (Rio de Janeiro) and the Eiffel Tower (Paris) from open source images. Further, an example case of Notre-Dame Cathedral is demonstrated to find the size of the destroyed spire from the undestroyed reference structure. The results are being compared with known standard values of structures and the relative error percentage for all the cases using the proposed algorithm and are found to be less than 1%. The method may find applications in survey or analysis by old digital video footage or images from archive/libraries where the camera specifications are not known to the user.

Analysing Different Dimensions of the Lexical Meaning of "Xian Sheng" from the Textual Corpus of the Republic of China

Vocabulary is a reflection of social thought. As an appellation, the Chinese word "Xian Sheng" expresses the social relationship between people in different social states. The Republic of China period was a special era from 1912 to 1949; the feudal imperial system had just disappeared, so the referential object of "Xian Sheng" was then generalised. This paper focuses on the meaning of "Xian Sheng" in the textual corpus of the Republic of China period. It discusses the inheritance of the old meaning, the similarities and differences between the Chinese and Japanese meanings, and the emergence of the new meaning by applying comprehensive analysis and inductive comparison. It is concluded that while feudalism remains and democratic and scientific thinking prevails, interpersonal relations in the Republic of China tend to be equalised, and the status of women has been improved to a certain extent. This study of interpersonal relationships in China during the Republic of China will be conducted by analysing this vocabulary. At the same time, it will consider whether the term "Xian Sheng" still applies to women today.

Towards Unsupervised Referring Expression Comprehension with Visual Semantic Parsing

Referring Expression Comprehension (REC) is a task that involves grounding a specific object in an image based on a given referring query in the form of bounding boxes. Existing fully-supervised or weakly-supervised REC methods rely on either manually annotated regional coordinates or query texts. In this paper, we propose an unsupervised training paradigm for the REC task that does not require any manual annotated data. Specifically, we introduce a Visual-Semantic-Parsing-based Unsupervised Referring Expression Comprehension framework (VUREC), which leverages a Visual Semantic Parser (VSP) as its core module to recognize the rich semantic information in images and construct pseudo-region-query pairs as the training supervision for REC. The VSP comprises a Scene Graph Parser (SGP) and a Visual Concept Detector (VCD) that can detect the locations, categories, attributes of objects, and visual relationships among them in images. Furthermore, we present a Referring Expression Reasoning (RER) model that utilizes a Multi-Modal Cascade Attention Decoder (MCAD) for fine-grained multi-modality fusion and regresses the four coordinates of the referential object directly. The experimental results on three benchmark datasets of Refcoco, Refcoco+ and Refcocog demonstrate the effectiveness of our proposed method.

THE SEMIOTIC EXPLORING OF THE JAMBI MALAY CUCI KAMPUNG TRADITION

There is a change in the cuci kampung tradition of the Jambi Malay community in Indonesia. This change is based on reinterpreting the sign attached to the tradition in question. This research is aimed at looking at this reinterpretation process. This research uses a descriptive-analytical qualitative method with a field and literature study as a background. Data was collected through interviews, observation, archiving and FGD. Apart from that, reading was also carried out on several related literatures. The collected data was analyzed using Charles Sanders Peirce's semiotic theory. This research produced several findings. First, the sign that is a reference in the cuci kampung tradition is the act of adultery which is sanctioned by stoning. Second, this sign is a reference for objects in the form of the cuci kampung tradition where the Jambi Malay community gave birth to this tradition with a traditional fine in the form of a goat or buffalo. Third, through reinterpreting the sign, the Jambi Malay community made changes to the cuci kampung tradition, both the procession and the traditional fines. The form of the procession became simpler, while the traditional fine changed into money

BUILDING A HUMAN REFERENCE ATLAS

Abstract The Human Reference Atlas (HRA, https://humanatlas.io) is a comprehensive, high-resolution, three-dimensional atlas of all the cells in the healthy human body. The HRA provides standard terminologies and data structures for describing specimens, biological structures, and spatial positions linked to existing ontologies. In this talk, we will present a high-level overview of the major components of the HRA--including 67 anatomically correct 3D Reference Objects for 29 organs and 31 Anatomical Structure, Cell Types, and Biomarker (ASCT+B) Tables--and the tools to explore, use, author, and review the HRA--including the Registration User Interface, the Exploration User Interface, the ASCT+B Reporter, and the HRA Organ Gallery in virtual reality. We welcome experts and practitioners to join the monthly WG meetings (sign up at https://iu.co1.qualtrics.com/jfe/form/SV_bpaBhIr8XfdiNRH), to explore and contribute to this effort, and to provide feedback on the evolving HRA from diverse perspectives.

Detectability and accuracy of computational measurements of in-silico and physical representations of enlarged perivascular spaces from magnetic resonance images

BackgroundMagnetic Resonance Imaging (MRI) visible perivascular spaces (PVS) have been associated with age, decline in cognitive abilities, interrupted sleep, and markers of small vessel disease. But the limits of validity of their quantification have not been established. New methodWe use a purpose-built digital reference object to construct an in-silico phantom for addressing this need, and validate it using a physical phantom. We use cylinders of different sizes as models for PVS. We also evaluate the influence of ‘PVS’ orientation, and different sets of parameters of the two vesselness filters that have been used for enhancing tubular structures, namely Frangi and RORPO filters, in the measurements’ accuracy. ResultsPVS measurements in MRI are only a proxy of their true dimensions, as the boundaries of their representation are consistently overestimated. The success in the use of the Frangi filter relies on a careful tuning of several parameters. Alpha= 0.5, beta= 0.5 and c= 500 yielded the best results. RORPO does not have these requirements and allows detecting smaller cylinders in their entirety more consistently in the absence of noise and confounding artefacts. The Frangi filter seems to be best suited for voxel sizes equal or larger than 0.4 mm-isotropic and cylinders larger than 1 mm diameter and 2 mm length. ‘PVS’ orientation did not affect measurements in data with isotropic voxels. Comparison with existent methodsDoes not apply. ConclusionsThe in-silico and physical phantoms presented are useful for establishing the validity of quantification methods of tubular small structures.

Comparison of LASSO and random forest models for predicting the risk of premature coronary artery disease

PurposeWith the change of lifestyle, the occurrence of coronary artery disease presents a younger trend, increasing the medical and economic burden on the family and society. To reduce the burden caused by this disease, this study applied LASSO Logistic Regression and Random Forest to establish a risk prediction model for premature coronary artery disease(PCAD) separately and compared the predictive performance of the two models.MethodsThe data are obtained from 1004 patients with coronary artery disease admitted to a third-class hospital in Liaoning Province from September 2019 to December 2021. The data from 797 patients were ultimately evaluated. The dataset of 797 patients was randomly divided into the training set (569 persons) and the validation set (228 persons) scale by 7:3. The risk prediction model was established and compared by LASSO Logistic and Random Forest.ResultThe two models in this study showed that hyperuricemia, chronic renal disease, carotid artery atherosclerosis were important predictors of premature coronary artery disease. A result of the AUC between the two models showed statistical difference (Z = 3.47, P < 0.05).ConclusionsRandom Forest has better prediction performance for PCAD and is suitable for clinical practice. It can provide an objective reference for the early screening and diagnosis of premature coronary artery disease, guide clinical decision-making and promote disease prevention.

EVALUATION OF INTEL REALSENSE D455 CAMERA DEPTH ESTIMATION FOR INDOOR SLAM APPLICATIONS

Abstract. The aim of this study is to propose evaluation methodology for the quality assessment of depth cameras for indoor mapping applications. Specifically, we evaluate the RGBD sensor Intel Realsense D455 w.r.t. measurement accuracy and noise while investigating their dependence on two central parameters characterizing the measurement scenario simultaneously: measurement distance and inclination of observed surfaces. The evaluation results are presented two-dimensionally as a function of both parameters. To this aim, two evaluation studies are conducted. First, a checkerboard pattern is used as reference object in a controlled setting. Secondly, actual indoor mapping data resulting from the deployment of the evaluated sensor in the context of an RGBD-SLAM application is used to conduct a similar evaluation in representative conditions for the intended usage scenario of indoor mapping. In this case, a TLS scan of the respective indoor environment is used as reference for evaluation.

A Formation Control and Obstacle Avoidance Method for Multiple Unmanned Surface Vehicles

This study introduces a method for formation control and obstacle avoidance for multiple unmanned surface vehicles (USVs) by combining an artificial potential field with the virtual structure method. The approach involves a leader–follower formation structure, where the leader autonomously avoids collisions using an artificial potential field based on the target’s position as a reference. It also determines the ideal position of each follower in the formation based on its own position, heading angle, and the formation structure. To effectively avoid obstacles and maintain formation, the follower selects the position of the target or its ideal position as a reference during movement, depending on whether it is being repelled by obstacles. Additionally, this paper modifies the attractive force model of the traditional artificial potential field method to restrict the maximum magnitude of the attractive force when encountering repulsive forces, thus expediting departure from obstacle areas. The dynamic characteristics of USVs are taken into account by constraining the maximum linear speed and angular speed. Formation stability is ensured by maintaining a constant speed for the leader, while the linear speed of the follower varies based on the distance to the reference object during movement. Simulation experiments demonstrated that this method can effectively avoid obstacles and maintain formation.