IoT-Based Tracking System of Transceiver Location

Object mapping based on location tracking methods has been widely used in various types of applications. Most tracking systems recently use existing technology and infrastructure such as satellite, cellular and wireless (RF) technology. These existing technologies are high-cost technology that needs authorized permission to be integrated to the novel technology. This research proposed a cheap point to point device technology to track a location of a transceiver using GPS in a portable infrastructure using Line of sight radio communication. The tracking system design is connected to the IoT system in order to be more accessible. The proposed system using GPS as an identifier of the transceiver coordinate location and 433MHz radio module as media communication between transmitter and receiver. The use of a 433MHz radio frequency module which is free-license adds value to the system so that it will be easily accessed. The design of portable and internet-based devices also gives a positive value in which the system does not have to depend on existing infrastructure and the system can also be reached even if it is placed in remote areas. The system test results show that the system can be well accessed up to a distance of 6.8 km.

Moving beyond "nouns in the lab": Using naturalistic data to understand why infants' first words include uh-oh and hi

Why do infants learn some words earlier than others? To explain how and when words are learned, existing theories of word learning prioritize visual information and draw mainly on lab-based studies of noun-to-object mapping. However, words that are more abstract than object nouns, such as uh-oh, hi, more, up, and all-gone, are typically among the first to appear in infants' vocabularies. We combined a behavioral experiment with naturalistic observational research to explore how infants learn and represent this understudied category of high-frequency, routine-based non-nouns, which we term ‘everyday words’. In Study 1, we found that conventional eye-tracking measures of comprehension were insufficient to capture 10- to 16-month-old infants' emerging understanding of everyday words. In Study 2, we analyzed the visual and social scenes surrounding caregivers' and infants' use of everyday words in a naturalistic video corpus. This ecologically-motivated research revealed that everyday words rarely co-occurred with consistent visual referents, making their early learnability difficult to reconcile with dominant word learning theories. Our findings instead point to complex patterns in the types of situations associated with everyday words that could contribute to their early representation in infants’ vocabularies. By leveraging both experimental and observational methods, this investigation underscores the value of using naturalistic data to broaden theories of early learning.

Functoriality of the Schmidt Construction

After proving, in a purely categorial way, that the inclusion functor InAlg(Σ) from Alg(Σ), the category of many-sorted Σ-algebras, to PAlg(Σ), the category of many-sorted partial Σ-algebras, has a left adjoint FΣ, the (absolutely) free completion functor, we recall, in connection with the functor FΣ, the generalized recursion theorem of Schmidt, which we will also call the Schmidt construction. Next we define a category Cmpl(Σ), of Σ-completions, and prove that FΣ, labeled with its domain category and the unit of the adjunction of which it is a part, is a weakly initial object in it. Following this we associate to an ordered pair (α,f), where α=(K,γ,α) is a morphism of Σ-completions from F=(C,F,η) to G=(D,G,ρ) and f a homomorphism in D from the partial Σ-algebra A to the partial Σ-algebra B, a homomorphism ΥαG,0(f):Schα(f)B. We then prove that there exists an endofunctor, ΥαG,0, of Mortw(D), the twisted morphism category of D, thus showing the naturalness of the previous construction. Afterwards we prove that, for every Σ-completion G=(D,G,ρ), there exists a functor ΥG from the comma category (Cmpl(Σ)↓G) to End(Mortw(D)), the category of endofunctors of Mortw(D), such that ΥG,0, the object mapping of ΥG, sends a morphism of Σ-completion in Cmpl(Σ) with codomain G, to the endofunctor ΥαG,0.

Do the Eyes Have It? A Systematic Review on the Role of Eye Gaze in Infant Language Development

Eye gaze is a ubiquitous cue in child–caregiver interactions, and infants are highly attentive to eye gaze from very early on. However, the question of why infants show gaze-sensitive behavior, and what role this sensitivity to gaze plays in their language development, is not yet well-understood. To gain a better understanding of the role of eye gaze in infants' language learning, we conducted a broad systematic review of the developmental literature for all studies that investigate the role of eye gaze in infants' language development. Across 77 peer-reviewed articles containing data from typically developing human infants (0–24 months) in the domain of language development, we identified two broad themes. The first tracked the effect of eye gaze on four developmental domains: (1) vocabulary development, (2) word–object mapping, (3) object processing, and (4) speech processing. Overall, there is considerable evidence that infants learn more about objects and are more likely to form word–object mappings in the presence of eye gaze cues, both of which are necessary for learning words. In addition, there is good evidence for longitudinal relationships between infants' gaze following abilities and later receptive and expressive vocabulary. However, many domains (e.g., speech processing) are understudied; further work is needed to decide whether gaze effects are specific to tasks, such as word–object mapping or whether they reflect a general learning enhancement mechanism. The second theme explored the reasons why eye gaze might be facilitative for learning, addressing the question of whether eye gaze is treated by infants as a specialized socio-cognitive cue. We concluded that the balance of evidence supports the idea that eye gaze facilitates infants' learning by enhancing their arousal, memory, and attentional capacities to a greater extent than other low-level attentional cues. However, as yet, there are too few studies that directly compare the effect of eye gaze cues and non-social, attentional cues for strong conclusions to be drawn. We also suggest that there might be a developmental effect, with eye gaze, over the course of the first 2 years of life, developing into a truly ostensive cue that enhances language learning across the board.

Intelligent Object Shape and Position Identification for Needs of Dynamic Luminance Shaping in Object Floodlighting and Projection Mapping

Innovative lighting and dynamic sound systems as well as adaptive object mapping solutions constitute a rapidly developing branch of lighting technology and multimedia technology. In order to make it possible to adjust the content to specific objects in the scene, it is necessary to correctly identify them and place them in the accepted frame of reference. Dynamic identification and tracking of objects can be carried out based on two particular types of input data: data from markers installed on objects and data from digital recording systems, founding the operation on infrared (IR), visible light (RGB) and the most advanced RGB-D (RGB and depth) analysis. Most systems used today are those that use various types of markers. This paper presents the advantages and disadvantages of such solutions as well as a target system for dynamic identification and mapping of objects and the human body based on the analysis of data from digital RGB-D cameras. Analyses of identification times, implementation of perspective transformations and 3D-to-2D transformations have been carried out in relation to a planar and cuboidal moving surface. Time analyses have been performed in relation to the resolution of registered and processed images.

Multi-View Instance Matching with Learned Geometric Soft-Constraints

We present a new approach for matching urban object instances across multiple ground-level images for the ultimate goal of city-scale mapping of objects with high positioning accuracy. What makes this task challenging is the strong change in view-point, different lighting conditions, high similarity of neighboring objects, and variability in scale. We propose to turn object instance matching into a learning task, where image-appearance and geometric relationships between views fruitfully interact. Our approach constructs a Siamese convolutional neural network that learns to match two views of the same object given many candidate image cut-outs. In addition to image features, we propose utilizing location information about the camera and the object to support image evidence via soft geometric constraints. Our method is compared to existing patch matching methods to prove its edge over state-of-the-art. This takes us one step closer to the ultimate goal of city-wide object mapping from street-level imagery to benefit city administration.

Exploration for Object Mapping Guided by Environmental Semantics using UAVs

This paper presents a strategy to autonomously explore unknown indoor environments, focusing on 3D mapping of the environment and performing grid level semantic labeling to identify all available objects. Unlike conventional exploration techniques that utilize geometric heuristics and information gain theory on an occupancy grid map, the work presented in this paper considers semantic information, such as the class of objects, in order to gear the exploration towards environmental segmentation and object labeling. The proposed approach utilizes deep learning to map 2D semantically segmented images into 3D semantic point clouds that encapsulate both occupancy and semantic annotations. A next-best-view exploration algorithm is employed to iteratively explore and label all the objects in the environment using a novel utility function that balances exploration and semantic object labeling. The proposed strategy was evaluated in a realistically simulated indoor environment, and results were benchmarked against other exploration strategies.

Potential Object Mapping of Nagari Batuhampar Religious Tourism Destination for Sustainable Development in Limapuluh Kota District

Nagari Batuhampar is a village located in Akabiluru District, Limapuluh Kota Regency. Nagari Batuhampar has physical and social potential that can be used as a tourist destination. This has been planned in the Nagari Strategic Plan which will develop tourism in the form of religious tourism. However, the problem in the field is that there is no map as a reference for regional development. The Nagari government views the importance of making this map as an aspect of regional development decision making. This research is classified as a descriptive quantitative survey research, which explains the phenomena in the field in accordance with the original situation. The purpose of this study is to map the location of the objects of religious tourism destinations in Nagari Batuhampar. This is intended so that the development of tourism-based areas is more monitored, mapped, planned, and evaluated. The result of the research states that the tourism object location points are along the road. This can be developed later to diversify attractions between tourism locations.