Real-world Items Research Articles

A far ultraviolet-C light technology is effective for decontamination of items in proximity to sinks and is enhanced by a far UV-C reflective surface.

Dispersal of gram-negative bacilli from sink drains has been implicated as a source of transmission in multiple outbreaks. In an acute care hospital, we assessed how often patient care supplies and other frequently touched items were within 1 meter of sink drains. We tested the efficacy of a ceiling-mounted far ultraviolet-C (UV-C) light technology for decontamination of sink bowls and surfaces near sinks with and without a wall-mounted film that reflects far UV-C light. Of 190 sinks assessed, 55 (29%) had patient care supplies or other frequently touched items within 1 meter of the drain. The far UV-C technology reduced Pseudomonas aeruginosa, Enterobacter cloacae and Candida auris on steel disk carriers by ≥1.5 log10 colony-forming units (CFU) in 45 minutes. On inoculated real-world items, ≥1.9 log10 CFU reductions in P. aeruginosa were achieved on sites in line with the light source versus 0.4-1.8 log10 CFU reductions on shaded surfaces. The addition of the reflective surface significantly enhanced efficacy in shaded sites (P < 0.01). In a hospital setting, patient care supplies and other frequently touched items were often in proximity to sinks. The far UV-C light technology could potentially be useful for sink decontamination in high-risk areas.

Semantic meaning enhances feature-binding but not quantity or precision of locations in visual working memory

Recent studies showed that real-world items are better remembered in visual working memory (VWM) than visually similar stimuli that are stripped of their semantic meaning. However, the exact nature of this advantage remains unclear. We used meaningful and meaningless stimuli in a location-reproduction VWM task. Employing a mixture-modeling analysis, we examined whether semantic meaning enables more item locations to be remembered, whether it improves the precision of the locations stored in memory, or whether it improves binding between the specific items and their locations. Participants were presented with streams of four (Experiments 1 & 2) or six (Experiment 3) real-world items, or their scrambled, meaningless counterparts. Each item was presented at a unique location, and the task was to reproduce one item’s location. Overall, location memory was consistently better for real-world items compared with their scrambled counterparts. Furthermore, the results revealed that participants were less likely to make swap errors for the meaningful items, but there was no effect of conceptual meaning on the guess rate or the precision of the report. In line with previous findings, these results indicate that conceptual meaning enhances VWM for arbitrary stimulus properties such as item location, and this improvement is primarily due to a more efficient identity-location binding rather than an increase in the quantity or quality (precision) of the locations held in memory.

Augmented Reality Application for Optical Character Recognition

Augmented Reality (AR) technology has become popular for improving user experiences by superimposing virtual features on the real world. OCR is another recent method for extracting text from photos or real-world items. AR and OCR are combined in a new software that provides an immersive and engaging experience. The proposed AR-based OCR system uses Firebase as a backend. Users can point their smartphones at papers, signs, or other textual material to use AR, which will automatically recognizeand extract the content. This extracted content can be translated, converted to text-to-speech, or shared on social media. Storage and management of recognizedtext data is reliable and scalable with the Firebase database connector. The Firebase Realtime Database can immediately sync extracted text across several devices for user collaboration and sharing. Firebase Authentication can authenticate and authorizeusers for safe OCR access. The programuses image processing for text extraction, OCR models for accurate recognition, and AR frameworks like ARCore (Android) and ARKit (iOS). The application will be linked to the Firebase backend using SDKs and APIs for real-time data synchronizationand safe data storage. The AR-based OCR application has great promise in education, logistics, retail, and other industries. It can extract text from physical documents, increase accessibility for visually challenged people, and translate foreign languagetext in real time. Firebase's backend database solution meets the application's needs for scalability, dependability, and data security

Integration of Digital Twins Technologies in Education for Experiential learning: Benefits and Challenges

In order to provide an immersive and engaging learning environment, digital twins in education are virtual representations of real-world items, settings, or people. From elementary to secondary school to higher education establishments, digital twins can be employed in a variety of educational contexts. For instance, students can imitate scientific experiments that would be hard to execute in the classroom owing to safety issues or a lack of resources, by using digital twins to create virtual versions of the investigations. With the help of digital twins, educators may even plan virtual field trips that let learners travel the globe without ever leaving the classroom. For instance, students might be able to study history, tour of Taj Mahal in Agra in-depth, and even engage with historical personalities through a digital duplicate of the wall. Students can communicate with lecturers or subject matter experts virtually by using digital duplicates to build virtual versions of them. In remote learning environments, where students do not have access to actual classrooms or in-person instructors, this can be especially helpful. This research study discusses the advantages of using digital twin technologies extensively in the educational system, as well as the technological, social, and ethical constraints.

Spectral Efficiency Analysis for IRS-Assisted MISO Wireless Communication: A Metaverse Scenario Proposal

The metaverse is emerging as a next-generation internet paradigm that will enhance human interaction and connectivity. Digital twinning, a fundamental strategy used in the metaverse, allows for the virtualization of real-world items, people, actions, and settings. A virtual world called the metaverse is built on a variety of technologies. Wireless communication is an important part of these technologies. In particular, wireless 6G communication can be essential for the growth of the metaverse. In line with the goal of achieving higher rates in the next-generation wireless network for the metaverse, in this paper, a novel conceptualization of intelligent reflecting surface (IRS)-assisted multiple-input single output-based wireless communication in physical world environments is proposed. More specifically, this paper proposes that in the physical world, the IRS-assisted communication between a communication network and users can be reflected in the metaverse through the virtual world (such as digital avatars and the virtual environment). In the simulations, the bit-error rate and spectral efficiency of the receiver terminal were performed and calculated in the metaverse engine for future consideration.

AR (Augmented Reality) Lens

The term "Augmented Reality" (AR) refers to an interactive environment in which computer-generated perceptual data is used to enhance the appearance of real-world items. A system that combines real and virtual worlds, real-time interaction is known as Augmented Reality (AR), which helps people by providing them with virtual aids. Because it was built for an android, the software runs well. Our initiative is a next-generation learning platform that allows users to engage with the virtual environment. If we point our camera at an image of medical equipment, the camera will recognize it and offer us the best results, including the device's name, description, tutorial video, and another ideal image. Our primary goal into advance the teaching strategy or platform the project will improve the learning experience. When the Augmented Reality lens' functionality was tested, it performed successfully. The goal of the project is to have a camera recognize real- world images or items using a raspberry pi that includes the Vuforia search engine, which employs Image Segmentation to find things and provide a description of the current image.

LEARNING ENGLISH LANGUAGE AS A SECOND LANGUAGE WITH AUGMENTED REALITY

The use of augmented reality (AR) in teaching English as a second language is examined in this article. Traditional language teaching techniques sometimes fall short of engaging students and offering real-world applications, which results in boredom and slow development. Through the use of augmented reality (AR) technology, digital content can be superimposed on the actual world to create an immersive and engaging learning environment. Real-world context, quick feedback, and immersive language learning experiences are all provided through AR. This article examines a number of ways that AR may be used to teach vocabulary, pronunciation, grammar, reading, and writing in English. English labels, grammatical rules, and text may be added to real-world items using augmented reality (AR), giving students a useful and fun method to practice what they have learned. Additionally, with the help of AR, learners can practice their language abilities in a variety of simulated real-world settings. The use of augmented reality (AR) in English language instruction has the potential to improve current teaching strategies and give non-native speakers of the language an enjoyable and productive learning experience.

A Game-Theoretic Approach for Rendering Immersive Experiences in the Metaverse

The metaverse is an upcoming computing paradigm aiming towards blending reality seamlessly with the artificially generated 3D worlds of deep cyberspace. This giant interactive mesh of three-dimensional reconstructed realms has recently received tremendous attention from both an academic and commercial point of view owing to the curiosity instilled by its vast possible use cases. Every virtual world in the metaverse is controlled and maintained by a virtual service provider (VSP). Interconnected clusters of LiDAR sensors act as a feeder network to these VSPs which then process the data and reconstruct the best quality immersive environment possible. These data can then be leveraged to provide users with highly targeted virtual services by building upon the concept of digital twins (DTs) representing digital analogs of real-world items owned by parties that create and establish the communication channels connecting the DTs to their real-world counterparts. Logically, DTs represent data on servers where postprocessing can be shared easily across VSPs, giving rise to new marketplaces and economic frontiers. This paper presents a dynamic and distributed framework to enable high-quality reconstructions based on incoming data streams from sensors as well as to allow for the optimal allocation of VSPs to users. The optimal synchronization intensity control problem between the available VSPs and the feeder network is modeled using a simultaneous differential game, while the allocation of VSPs to users is modeled using a preference-based game-theoretic approach, where the users give strict preferences over the available VSPs.

Object Detection Using Machine Learning and Deep Learning

Abstract: An object detection system finds objects of the real-world present either in a digital image or an object detection system locates real-world items that are present in a digital image or a video. These objects can be any type of object, such as people, automobiles, or other objects. A model database, a feature detector, a hypothesis, and a hypothesis verifier are the four components that the system must have in order to successfully detect an item in an image or video. This paper provides an overview of the many methods for object detection, localization, classification, feature extraction, appearance information extraction, and many other tasks in photos and videos. The remarks are derived from the literature that has been analyzed, and important concerns are also noted

Design &amp; Development of A 3D Scanner based on a Distance Sensor to Scan Real-life Objects &amp; 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.

Residential Water Tanks with IoT: A Solution for Household Water Consumption Monitoring

Wasting water has been a big problem in human society throughout the world. It can happen either in developed or developing countries. They tend to waste the water without knowing it. Moreover, people's awareness of the importance of using water wisely is still low. While they think the source of water is limitless, in fact, it is not. In contrast, the availability of freshwater in the world is limited. Furthermore, if the water is overused without reservation, it can trigger the phenomenon of water scarcity. However, the problem of wasting water can be reduced by using the water wisely and efficiently. With the growth of Internet of Things technology, it can help people use water efficiently by monitoring their water consumption. The Internet of Things (IoT) is a network of real-world items that may communicate with other electronic devices and systems via the internet by using sensors, software, and other technologies. IoT devices can be used for the purpose of household or the industrial. This paper focuses on designing and implementing a residential water tank system embedded with the Internet of Things technology for monitoring the water consumption in a household. The system will measure the water consumption from the residential water tank and send the data to a cloud server. Users will then be able to monitor it using a mobile device. With the data, users could change their habits of using water and start to use it wisely. Thus, the water shortage can be prevented.

Handheld Augmented Reality Application for 3D Fruits Learning

The purpose of this study is to look into the use of augmented reality (AR) technology in education materials for fruits and the nutrition. Augmented Reality (AR) is the primary technology for this proposed application project. AR is a real-world interactive experience in which real-world items are augmented with computer-generated perceptual information. The idea of this project is to use AR to complement the traditional method of learning with flashcards. Because schools are closed during this outbreak, traditional learning is unavailable. This study proposes the use of 3D animation in Augmented Reality (AR) to illustrate each of the fruits to overcome and improve traditional learning among students. The use of 3D animation with the Augmented Reality (AR) method on fruits and nutrition learning content outperforms the 2D illustration method in terms of student understanding. Furthermore, case studies on the application of AR technology to fruit learning content revealed that the proposed algorithm could be used as an alternative to determine the best way to teach and learn about fruits and nutrition. With this AR application, it can complement the traditional methods. To achieve the objectives of this project there are 4 main phases that need to be carried in developing this project. The first phase in developing this project is to study the data and learning interaction of fruits and the nutrition in handheld augmented reality. The second phase is designing process along with the development of the project. The third phase is to integrate the AR application. The final phase is to evaluate the user learning experience in fruits using the AR application. The project's expected outcome is evaluated using data collection and analysis from the users through the final phase.

3D Campus Map Towards Sustainable Development and Infrastructure Management In UPNM

Abstract 3D technology is used in GIS maps to create descriptive graphics that accurately depict the size of real-world items. In a wide variety of various areas, 3D models aid in appearance and survey. For example, 3D maps may depict the height of a building or a mountain in addition to its location. 3D tools must be utilized in conjunction with 2D GIS and then visualized in a 3D environment. The current UPNM campus map accessible to students and staff is not sufficiently helpful and hardly identified its whereabouts. This project was undertaken to develop a web-based 3D campus map and analyze specifically the campus’s area zoning. This study uses a personal computer with Esri CityEngine software to develop the 3D campus map and ArcGIS Online to publish the web-based 3D campus map. The data was acquired by downloading the base map of UPNM from OpenStreetMap (OSM). Completion of data processing results in a web-based 3D UPNM campus map with area zoning. The finding shows that the 3D map, using the Geographical Information System (GIS) platform, is more informative and attractive than the 2D map due to the attribute and spatial data. In addition, the capabilities of the 3D map to visualize and show the campus area and area zoning in the map can be managed according to the structural information. All in all, it can be concluded that this web-based 3D map contributes towards the sustainability of the UPNM infrastructure and campus while facilitating campus maintenance and rehabilitation.

Different features of real-world objects are represented in a dependent manner in long-term memory.

In the present study, we examined how real-world objects are represented in long-term memory. Two contrasting views exist with regard to this question: one argues that real-world objects are represented as a set of independent features, and the other argues that they form bound integrate representations. In 5 experiments, we tested the different predictions of each view, namely whether the different features of real-world items are remembered and forgotten independently from each other, in a feature-based manner, or conversely are stored and lost in an object-based manner, with all features depending upon each other. Across various stimuli, learning tasks (incidental or explicit), experimental setups (within- or between-subjects design), feature-dimensions, and encoding times, we consistently found that information is forgotten in an object-based manner. When an object ceases to be fully remembered, all of its features are lost, instead of only some of the object's features being lost whereas other features are still remembered. Furthermore, we found support for a strong form of dependency among the different features, namely a hierarchical structure. We conclude that visual long-term memory is object-based, challenging previous findings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Efficacy of a multi-purpose high level disinfection cabinet against Candida auris and other health care-associated pathogen

Portable equipment and other small devices used in health care are a potential source for dissemination of pathogens. We demonstrated that a high-level disinfection cabinet using ultrasonic submicron droplets of peracetic acid and hydrogen peroxide was effective against methicillin-resistant Staphylococcus aureus, Clostridiodes difficile spores, the nonenveloped virus bacteriophage MS2, and Candida auris on steel disk carriers. The device also eliminated Candida auris inoculated on real-world items of portable equipment.

Processing of different spatial scales in the human brain.

Humans navigate across a range of spatial scales, from rooms to continents, but the brain systems underlying spatial cognition are usually investigated only in small-scale environments. Do the same brain systems represent and process larger spaces? Here we asked subjects to compare distances between real-world items at six different spatial scales (room, building, neighborhood, city, country, continent) under functional MRI. Cortical activity showed a gradual progression from small to large scale processing, along three gradients extending anteriorly from the parahippocampal place area (PPA), retrosplenial complex (RSC) and occipital place area (OPA), and along the hippocampus posterior-anterior axis. Each of the cortical gradients overlapped with the visual system posteriorly and the default-mode network (DMN) anteriorly. These results suggest a progression from concrete to abstract processing with increasing spatial scale, and offer a new organizational framework for the brain's spatial system, that may also apply to conceptual spaces beyond the spatial domain.

STDP Forms Associations between Memory Traces in Networks of Spiking Neurons.

Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. However, there is conflicting evidence regarding neural codes for associated memory traces. Some studies suggest the emergence of overlaps between assemblies during an association, while others suggest that the assemblies themselves remain largely unchanged and new assemblies emerge as neural codes for associated memory items. Here we study the emergence of neural codes for associated memory items in a generic computational model of recurrent networks of spiking neurons with a data-constrained rule for spike-timing-dependent plasticity. The model depends critically on 2 parameters, which control the excitability of neurons and the scale of initial synaptic weights. By modifying these 2 parameters, the model can reproduce both experimental data from the human brain on the fast formation of associations through emergent overlaps between assemblies, and rodent data where new neurons are recruited to encode the associated memories. Hence, our findings suggest that the brain can use both of these 2 neural codes for associations, and dynamically switch between them during consolidation.

Online Interactive Collaborative Filtering Using Multi-Armed Bandit with Dependent Arms

Online interactive recommender systems strive to promptly suggest to consumers appropriate items (e.g., movies, news articles) according to the current context including both the consumer and item content information. However, such context information is often unavailable in practice for the recommendation, where only the users' interaction data on items can be utilized. Moreover, the lack of interaction records, especially for new users and items, worsens the performance of recommendation further. To address these issues, collaborative filtering (CF), one of the recommendation techniques relying on the interaction data only, as well as the online multi-armed bandit mechanisms, capable of achieving the balance between exploitation and exploration, are adopted in the online interactive recommendation settings, by assuming independent items (i.e., arms). Nonetheless, the assumption rarely holds in reality, since the real-world items tend to be correlated with each other (e.g., two articles with similar topics). In this paper, we study online interactive collaborative filtering problems by considering the dependencies among items. We explicitly formulate the item dependencies as the clusters on arms, where the arms within a single cluster share the similar latent topics. In light of the topic modeling techniques, we come up with a generative model to generate the items from their underlying topics. Furthermore, an efficient online algorithm based on particle learning is developed for inferring both latent parameters and states of our model. Additionally, our inferred model can be naturally integrated with existing multi-armed selection strategies in the online interactive collaborating setting. Empirical studies on two real-world applications, online recommendations of movies and news, demonstrate both the effectiveness and efficiency of the proposed approach.

PREPARING WORKPLACE-READY STUDENTS WITH DIGITAL MARKETING SKILLS

Digital marketing practice continues to grow along with the need for a qualified workforce. This paper presents a course design intended to teach students how to use relevant digital marketing tools and give them an end-to-end experience and managerial control over key resources. Students leave the course with real-world skills and items for their résumé to demonstrate workplace readiness. The project lays out how students create original content, perform keyword research, implement Google Ads and social media pay-per-click campaigns, analyze results, course correct, present a final report, and become Google Ads Certified. Innovation effectiveness is tested and reported.

Does “Being There” Matter? The Impact of Web-Based and Virtual World’s Shopping Experiences on Consumer Purchase Attitudes

The use of virtual worlds as an emerging technology is already having a significant impact on business to consumer commerce and on corporate Internet retailing strategies. This research investigates consumer behavior in e-commerce retail environments, particularly with respect to consumer attitudes toward using virtual world’s shopping compared to web-based, online shopping for real-world items. We investigate two forms of presence, perceived social presence and telepresence, and their effect on attitudes toward e-commerce, attitudes that ultimately influence the consumer's intention to shop using a particular e-commerce environment. Key implications of this research for researchers and practitioners are discussed.