Object Files Research Articles

Algorithm for intelligent procesing of text information

The purpose of research. The goal of the research is to develop an intellectual processing algorithm for classifying text information. As the amount of information grows every day, it is necessary to quickly and efficiently separate significant from unimportant content. Therefore, the development of an intellectual processing algorithm for classifying text information is an urgent task.Methods. A method is proposed for classifying text information presented in one or more natural languages. It is based on 5 key stages: entering a task, accumulating a queue of tasks, processing the task, generating the result of processing the task, outputting the result. The input task is presented in the form of an http request, the body of which contains a file object. If the intensity of the input stream is greater than the processing speed, then an accumulation of tasks occurs. After selecting the active task (using the FIFO principle), it is processed. As a result of the transformations, the received data is decoded into a string using UTF-8 encoding. Processing refers to the process of categorization, when a search for patterns occurs in a line. Upon completion of rubrication, the result for the selected task is generated. From the accumulated result, a response to the original http request is formed, the body of which contains a list of found categories.Results. A method and algorithm for processing text data has been developed to determine the topics that are present in the input data set. The algorithm, implemented in software, allows you to work with text data in various languages.Conclusion. The software development of the text data classification algorithm was carried out in the C++ programming language using the Qt libraries version 5.11. This implementation showed a throughput of 1-5 MB per second (on a homogeneous input text data set). The algorithm allows you to correctly process damaged file formats.

D-Linker: Debloating Shared Libraries by Relinking From Object Files

D-Linker: Debloating Shared Libraries by Relinking From Object Files

Spatio-Temporal Hierarchical Data Structure Based on Sparse Voxel Octrees for Representation of the Geometry of Time-Variable Three-Dimensional Scenes

Abstract The paper deals with the problematics of representation of the geometry of three-dimensional scenes in computer graphics using domain-specific hierarchical data structures based on octant trees or directed acyclic graphs as the means of space saving binary representation of this information. Several hierarchical data structures were introduced in this field in past decades. In this paper we are moving this problematic to the field of the representation of three-dimensional scenes which are rather dynamic in time, so their geometry is changing on the regular basis. We are investigating the influence of this time-variability on the size of the related hierarchical data structure on binary level. We are comparing the approach in which each time step is considered as the stand-alone static three-dimensional scene and therefore is represented by its own hierarchical data structure with the approach when this time-variable scene is considered as the four dimensional space and spatio-temporal sparse voxel octree hierarchical data structure is used for the representation of the geometry of this scene. We tested both approaches on three different scenes which were obtained by voxelization into two different resolutions of polygonal surface models represented originally as the mesh of triangles in Wavefront Object file format. Results of the tests show that spatio-temporal sparse voxel octree is better solution, when we obtained from 1.73 to 2.08 more compact binary representation, in comparison to the solution when time frames were encoded separately as the set of sparse voxel octrees.

Fixation offset decreases manual inhibition of return (IOR) in detection and discrimination tasks.

Attention can be covertly shifted to peripheral stimuli to improve their processing. However, attention is also then inhibited against returning to the previously attended location; thus, both detection and discrimination of a stimulus presented at that location decrease (the inhibition of return [IOR] effect). The after-effect of the covert orienting hypothesis postulates a close link between attention shifting, IOR, and oculomotor control. The fixation offset, which improves the generation of saccades, decreases IOR in detection tasks, suggesting a close link between IOR and oculomotor control. However, according to some alternative views (e.g., the input-based IOR hypothesis and the object files segregation/integration hypothesis), IOR may be related to some sensory rather than motor processes. Some studies support that view and show that IOR may occur differently in detection and discrimination tasks and that oculomotor processes do not affect IOR in tasks where manual responses are required and eye movements are suppressed. Two experiments presented in this article show that removing the fixation point decreases manual IOR in detection and discrimination tasks. The results are discussed in terms of various theoretical approaches.

Brain to 3D Model (Enabling tech of 3D Printers)

This study was planned to conduct and to bring the novel approach of thoughts into 3D into reality by using AI techniques & Methods. The study was conducted on user EEG signals and processed into pre-trained tokens of NLP and EEG signals to identify the probability of the EEG signal approach. The translation of EEG and ECoG signals into NLP level and generate a better prompting to Solve the issue hidden in Tokens of Prompting. These Prompt Techniques produce Generative Art by using Stable diffusion to create an image. That 2 Dimension image has Raw data at the background which is removed by using u2net & ModNet to introduce a more refined format as a preprocess for 3-D artwork Generation. The study focused on using different model like shape-e by OpenAI to create a more general approach but our code used it to produce for specifically 3-D avatar character for Metaverse. Using PifuHD estimation model by Facebook and lightweight human pose estimation.3-D art produced a more refined artwork as 3-D object file that can later be used in terms of producing into 3-D printed stuff and enable 3-D Printers closer to User Access as an efficient way of Technology.

What is the basis of ensemble subset selection?

The visual system can rapidly calculate the ensemble statistics of a set of objects; for example, people can easily estimate an average size of apples on a tree. To accomplish this, it is not always useful to summarize all the visual information. If there are various types of objects, the visual system should select a relevant subset: only apples, not leaves and branches. Here, we ask what kind of visual information makes a "good" ensemble that can be selectively attended to provide an accurate summary estimate. We tested three candidate representations: basic features, preattentive object files, and full-fledged bound objects. In four experiments, we presented a target and several distractors' sets of differently colored objects. We found that conditions where a target ensemble had at least one unique color (basic feature) provided ensemble averaging performance comparable to the baseline displays without distractors. When the target subset was defined as a conjunction of two colors or color-shape partly shared with distractors (so that they could be differentiated only as preattentive object files), subset averaging was also possible but less accurate than in the baseline and feature conditions. Finally, performance was very poor when the target subset was defined by an exact feature relationship, such as in the spatial conjunction of two colors (spatially bound object). Overall, these results suggest that distinguishable features and, to a lesser degree, preattentive object files can serve as the representational basis of ensemble selection, while bound objects cannot.

Infants infer and predict coherent event interactions: Modeling cognitive development.

Mental representations of the environment in infants are sparse and grow richer during their development. Anticipatory eye fixation studies show that infants aged around 7 months start to predict the goal of an observed action, e.g., an object targeted by a reaching hand. Interestingly, goal-predictive gaze shifts occur at an earlier age when the hand subsequently manipulates an object and later when an action is performed by an inanimate actor, e.g., a mechanical claw. We introduce CAPRI2 (Cognitive Action PRediction and Inference in Infants), a computational model that explains this development from a functional, algorithmic perspective. It is based on the theory that infants learn object files and events as they develop a physical reasoning system. In particular, CAPRI2 learns a generative event-predictive model, which it uses to both interpret sensory information and infer goal-directed behavior. When observing object interactions, CAPRI2 (i) interprets the unfolding interactions in terms of event-segmented dynamics, (ii) maximizes the coherence of its event interpretations, updating its internal estimates and (iii) chooses gaze behavior to minimize expected uncertainty. As a result, CAPRI2 mimics the developmental pathway of infants' goal-predictive gaze behavior. Our modeling work suggests that the involved event-predictive representations, longer-term generative model learning, and shorter-term retrospective and active inference principles constitute fundamental building blocks for the effective development of goal-predictive capacities.

Development and validation of a Medaka fish voxel-based model for internal ionizing radiation dosimetry

In this paper, we present a voxel-based phantom of Medaka fish that can be used to assess the internal radiation doses that would be absorbed by different organs of this fish species if exposed to radioactive wastewater released into the ocean. The geometric model for fish was generated based on available Wavefront Object files for smooth-bodied Medaka fish organs, whereas due to the lack of Medaka fish material specification, the material model was constructed using material data appropriate to ICRP 110 adult male voxel-based phantom. Absorbed Fractions (AFs) and Specific Absorbed Fractions (SAFs) were calculated for eight organs of major interest as sources and for each organ as target at a set of discrete photon, electron, alpha and neutron energies. To validate the present model the calculated AFs in the studied organs were compared to ones obtained in similar organs in a voxel-based phantom of another teleost fish species called Limanda limanda. The results presented are consistent with the reference dosimetric data. We concluded that the Medaka model can be used in radioecology research to improve marine radiation protection.

Dimensional interaction is driven by feature integration: A binding theory of garner interference.

For nearly half a century now, Garner interference has been serving as the gold standard measure of dimensional interaction and selective attention. But the mechanisms that generate Garner interference are still not well understood. The current study proposes a novel theory that ascribes the interference (and dimensional interaction in general) to episodic feature integration processes at the micro (trial-to-trial) level. The novel account builds on earlier well-established notions of "feature integration" and "object files," and is augmented by formal derivations. The sequential binding account predicts that the magnitude of Garner interference is related to the strength of feature integration along consecutive trials. Three experiments were set to test this novel binding theory. Experiment 1 and Experiment 2 tested performance with integral dimensions (chroma and value, and width and height of rectangles); whereas Experiment 3 examined performance with a pair of separable dimensions (circle's size and angle of a diameter). In addition, the time lag ensuing between consecutive trials was manipulated. The results strongly supported the predictions of the sequential binding account: (a) with integral dimensions, substantial amounts of Garner interference were correlated with large partial repetition costs (e.g., consensual markers of feature integration), but this pattern was not observed with separable dimensions, and (b) the magnitude of both Garner interference and partial repetition costs diminished as a function of the ensuing time lag between consecutive trials, pointing to a common time-dependent memory mechanism. These results adduce strong support in the predictions of the feature binding theory of Garner interference, giving currency to the idea that dimensional interaction is driven by feature integration. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Applications of hybrid structure light three‐dimensional scanning in neurodegenerative disease autopsy brain banking

AbstractBackgroundPostmortem magnetic resonance imaging (MRI) and three‐dimensional (3D) printing has been demonstrated to be a feasible approach for the creation of tissue matrices to aid in postmortem brain dissection. We aimed to extend this approach using hybrid structure light technology (visible and infrared) 3D scanning to generate brain models as a digital resource and operational tool for human neurodegenerative disease brain banks.MethodA consecutive series of 56 brains accessioned into the Glenn Biggs Institute Brain Bank were imaged using an EinScan H handheld 3D scanner. Five brains were selected for generation of tissue matrices, with infratentorial structures removed using 3D object post‐processing software tools. Matrices were printed using a Raise3D Pro2 printer and 1.75‐mm polylactic acid premium filament.ResultEach scan was approximately an hour to complete, including capture and alignment of a lateral and a medial surface scan for each brain. Raw scan files (DAT and BRAP‐PRJ) averaged 5.47 GB and 3D object files were 12,991 KB for 3MF and 18,067 KB for OBJ file types. For cases with tissue matrices, average print time was 42 hours with an average filament consumption of 338 g. Brain cutting with the tissue matrices was performed in a standardized manner, with superb control for section thickness and planar orientation compared to brains cut without a matrix.Conclusion3D scanning of postmortem autopsied brains is a simple and useful strategy to generate models with utility in guided tissue sectioning and storage (practice), surface area volumetric analysis (research) and virtual reality/augmented reality neuroanatomy training (education) for Alzheimer’s disease and related dementias.

Creation of Three-dimensional Anatomic Models in Pediatric Surgical Patients Using Cross-sectional Imaging: A Demonstration of Low-cost Methods and Applications

BackgroundPediatric surgery patients often present with complex congenital anomalies or other conditions requiring deep understanding of their intricate anatomy. Commercial applications and services exist for the conversion of cross-sectional imaging data into three-dimensional (3D) models for education and preoperative planning. However, the associated costs and lack of familiarity may discourage their use in centers with limited resources. The purpose of this report is to present a low-cost, reproducible method for generating 3D images to visualize patient anatomy. MethodsDe-identified DICOM files were obtained from the hospital PACS system in preparation for assorted pediatric surgical procedures. Using open-source visualization software, variations in anatomic structures were examined using volume rendering and segmentation techniques. Images were further refined using available editing tools or artificial intelligence-assisted software extensions. ResultsUsing the described techniques we were able to obtain excellent visualization of desired structures and associated anatomic variations. Once structures were selected and modeled in 3D (segmentation), they could be exported as one of several 3D object file formats. These could then be retained for 3D printing, visualization in virtual reality, or as an anatomic reference during the perioperative period. Models may also be imported into commercial gaming engines for rendering under optimal lighting conditions and with enhanced detail. ConclusionPediatric surgeons are frequently tasked with the treatment of patients with complex and rare anomalies. Visualization and preoperative planning can be assisted by advanced imaging software at minimal to no cost, thereby facilitating enhanced understanding of these conditions in resource-limited environments. Level of EvidenceV, Case Series, Description of Technique.

Virtual Aquascape for Users Utilizing Augmented Reality

Aquascape is the art of arranging plants in water. The large number of complaints from aquascape buyers were not up to expectations, causing sellers to have difficulty in setting an example of an orderable aquascape, so researches created an aquascape application system to increase their promotional activities with augmented reality technology accessible through smartphone. One uses the methode MDLC (Multimedia Development Life Cycle). As a result, the application can implement a markless augmented reality to display 3D objects in real time with the help of a camera on a smartphone or a trilib feature by importing 3D object files found on file managers on a smartphone. User can easily provide the desired aquascape example of the aquascape application.

µFuncCache: A User-Side Lightweight Cache System for Public FaaS Platforms

Building cloud-native applications based on public “Function as a Service” (FaaS) platforms has become an attractive way to improve business roll-out speed and elasticity, as well as reduce cloud usage costs. Applications based on FaaS are usually designed with multiple different cloud functions based on their functionality, and there will be call relationships between cloud functions. At the same time, each cloud function may depend on other services provided by cloud providers, such as object storage services, database services, and file storage services. When there is a call relationship between cloud functions, or between cloud functions and other services, a certain delay will occur, and the delay will increase with the length of the call chain, thereby affecting the quality of application services and user experience. Therefore, we introduce μFuncCache, a user-side lightweight caching mechanism to speed up data access for public FaaS services, fully utilizing the container delay destruction mechanism and over-booked memory commonly found in public FaaS platforms, to reduce function call latency without the need to perceive and modify the internal architecture of public clouds. Experiments in different application scenarios have shown that μFuncCache can effectively improve the performance of FaaS applications by consuming only a small amount of additional resources, while achieving a maximum reduction of 97% in latency.

Imagined object files: Visual imagery produces partial repetition costs where perception does not.

The present study explored whether object (or event) files can be formed that integrate color imagery and perceptual location features. To assess this issue, a cue-target procedure was used whereby color imagery was cued to be generated at a particular location in space, which was then followed by a perceptual color discrimination task. Partial repetition costs (PRCs) were then measured by varying the overlap of the color and location features of the cue and target to evaluate whether an object/event file was formed. Robust PRCs were observed when imagery was generated at a location, supporting the idea that imagery and perception can be incorporated into a common event file. It was also revealed that the PRC effects for perceptual color cues were tenuous-they did not reach significance in the present study. Overall, the present study indicates that imagery can produce stronger binding effects than perception, offering important insights into the role that active engagement plays in the formation of object/event files.

Quantity discrimination by kittens of the domestic cat (Felis silvestris catus)

Quantitative abilities are well described in many species and in diverse life situations, including in the adult domestic cat. However, such abilities have been much less studied during ontogeny. In the present study we examined spontaneous quantity discrimination by pre-weaning age kittens in two-way food choice experiments. In Experiment 1, 26 kittens performed 12 trials with different ratios between the number of same-size food items. In Experiment 2, 24 other kittens performed eight trials with different ratios between the size of two food items. We found, in general, that the kittens discriminated between the different amounts of food and spontaneously chose the larger one, but that their choice was influenced by the ratio of difference. The kittens in Experiment 1 chose the larger number of same-size food items if the ratio was smaller than 0.4 and in Experiment 2 they chose the larger pieces of food if the ratio between the items was smaller than 0.5. Because the kittens’ choice was not influenced by the absolute number of food items or the numerical difference between them in Experiment 1, it suggests that their cognitive performance relied on an analog magnitude system rather than on an object file system during the quantity discrimination tasks. We discuss our results considering the ecological and social background of cats and compare it with the performance of previously studied species.

We Write to You About Africa curated by Laura De Becker and Ozi Uduma; Wish You Were Here: African Art and Restitution curated by Laura De Becker, Bridget Grier, Timnet Gedar, and Ozi Uduma

We Write to You About Africa curated by Laura De Becker and Ozi Uduma; Wish You Were Here: African Art and Restitution curated by Laura De Becker, Bridget Grier, Timnet Gedar, and Ozi Uduma

Module extraction and DLL hijacking detection via single or multiple memory dumps

A memory dump contains the current state of a system's physical memory at the time of its acquisition. Among other things, it contains the processes that were running at the time of acquisition. These processes can share certain functionalities provided by shared object files, which are internally represented by modules in Windows. However, each process only maps in its address space the functionalities it needs, and not the entire shared object file. In this way, the current tools for extracting modules from existing processes in a memory dump from a Windows system obtain the partial content of a shared object file instead of the entire file. In this paper we present two tools, dubbed Modex and Intermodex, which are built on top of the Volatility 3 framework. These tools allow a forensic analyst to extract a 64-bit module from one or more Windows memory dumps as completely as possible. To achieve this, they aggregate the contents of the same module loaded by multiple processes that were running in the same memory dump or in different dumps (we called it intradump and interdump, respectively). Additionally, we also show how our developed tools are useful to detect dynamic-link library (DLL) hijacking attacks, a widely used attack on Windows where attackers trick processes into loading a malicious DLL instead of the benign one.

Design & Development of A 3D Scanner based on a Distance Sensor to Scan Real-life Objects & Implementing in Digital Reality

This research aims to scan a real-world 3D object, reconstruct its digital model with internal hollow space data (volume, area), and blend it into augmented reality. When it comes to rebuilding a body, precision is a significant necessity. To scan a three-dimensional object, numerous methods are available. Most of which can only determine the outside dimensions of the entity being scanned. They barely provide any information regarding the hollow surface of the body. And to ensure accuracy, expenses may spike. To reconstruct a 3D object, the distance (e.g., Lidar, GP2Y0A41SK0F, Ultrasonic, etc.) sensor-based 3d scanner comes into play. The proposed system also includes a feature that can measure the hollow space inside the object. The distance sensor bounces laser light, infrared rays, or ultrasound to gauge distance and depth to form a 3D scan. The sensor sends that data to the microcontroller, and then the microcontroller brings that cartesian coordinate data to computer software to build the mesh. For detecting internal hollow space, gamma resonance is used. Furthermore, after scanning an object, Stereolithography or Film box files may be used for various purposes, including integrating with augmented reality, generating 3D prints, creating a video game or CGI avatars, etc. This project can create 3D scanned mesh quickly and accurately of real-world items. The 3D scan data regenerated by the proposed system can merge with augmented reality to simulate the metaverse. Scanning a three-dimensional body can be useful in our everyday lives as well as for research and experimental purposes. This proposed system provides an unbiassed novel strategy for reconstructing 3D internal hollow space with significant accuracy. This research addresses the hypothetical subject of what impact real-world objects portrayed in the digital world will have on mankind's new cyber world.

Framework architecture of a secure big data lake

This paper presents the architecture of a secure big data lake framework, the foundation of which is the Data Lake Architecture Framework (SDLAF). Security is entrusted to 2 components: Global Monitoring Tool (GMT), Check Sum Controller (CSC). The first one monitors data lake logs, automatically detecting anomalous data, the second one tracks the history of loading, processing, and unloading of file objects in the data lake. The conducted instrumental audit demonstrates both the effectiveness of the architecture and its prospects.

Enhancement of WRF Model Using CUDA

The main aim of this paper is to implement and run WRF (Weather Research and Forecasting) model on Graphical Processing Unit (GPU) with the help of NVidia’s CUDA (Compute Unified Device Architecture) in a normal machine. Without GPU, the model needs high-end systems to be executed smoothly. For this, CUDA code is executed for a particular microphysics module to create an object file which is then added to the WRF model. Later the object file is executed on the GPU with the help of CUDA.