The Design of the Portable EEG Acquisition Device Based on ZigBee Wireless Protocol

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage

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Commitment in L3 relationships: Sacred vows or polyamory?

Second language Research ◽

10.1177/0267658320988045 ◽

2021 ◽

pp. 026765832098804

Author(s):

David Stringer

Keyword(s):

Second Language ◽

First Language ◽

Acquisition Process ◽

Third Language ◽

L3 Acquisition ◽

Acquisition Device ◽

Crosslinguistic Influence ◽

The Mind ◽

N Acquisition ◽

Full Copy

Westergaard (2019) presents an updated account of the Linguistic Proximity Model and the micro-cue approach to the parser as an acquisition device. The property-by-property view of transfer inherent in this approach contrasts with other influential models that assume that third language (L3) acquisition involves the creation of a full copy of only one previously existing language in the mind. In this commentary, I review Westergaard’s proposal that first language (L1), second language (L2), and L3 acquisition proceed on the basis of incremental, conservative learning and her view of the parser as the engine of the acquisition process. I then provide several arguments in support of her position that crosslinguistic influence in L n acquisition may flow from any previously acquired language.

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fNIRS Signal Classification Based on Deep Learning in Rock-Paper-Scissors Imagery Task

Applied Sciences ◽

10.3390/app11114922 ◽

2021 ◽

Vol 11 (11) ◽

pp. 4922

Author(s):

Tengfei Ma ◽

Wentian Chen ◽

Xin Li ◽

Yuting Xia ◽

Xinhua Zhu ◽

...

Keyword(s):

Deep Learning ◽

Total Duration ◽

Signal Classification ◽

Imagery Task ◽

Neural Activities ◽

Computer Interfaces ◽

Acquisition Device ◽

The Time Domain ◽

The Brain

To explore whether the brain contains pattern differences in the rock–paper–scissors (RPS) imagery task, this paper attempts to classify this task using fNIRS and deep learning. In this study, we designed an RPS task with a total duration of 25 min and 40 s, and recruited 22 volunteers for the experiment. We used the fNIRS acquisition device (FOIRE-3000) to record the cerebral neural activities of these participants in the RPS task. The time series classification (TSC) algorithm was introduced into the time-domain fNIRS signal classification. Experiments show that CNN-based TSC methods can achieve 97% accuracy in RPS classification. CNN-based TSC method is suitable for the classification of fNIRS signals in RPS motor imagery tasks, and may find new application directions for the development of brain–computer interfaces (BCI).

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A Flexible Microcontroller-Based Data Acquisition Device

Sensors ◽

10.3390/s140609755 ◽

2014 ◽

Vol 14 (6) ◽

pp. 9755-9775 ◽

Cited By ~ 10

Author(s):

Darko Hercog ◽

Bojan Gergič

Keyword(s):

Data Acquisition ◽

Acquisition Device ◽

Data Acquisition Device

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Student-Teacher: The Learning Machine as an Instructional Device

Journal of Educational Computing Research ◽

10.2190/f04u-g1n3-vb0n-qllm ◽

1988 ◽

Vol 4 (1) ◽

pp. 57-70

Author(s):

Carol Scheftic ◽

George Darlington Wood

Keyword(s):

Functional Analysis ◽

Expert System ◽

Socratic Method ◽

Educational Tool ◽

System Technology ◽

Solution Strategy ◽

Analysis Techniques ◽

Acquisition Device ◽

Learning Machine ◽

Further Development

This article presents QUERIOUS, an educational tool based on expert system technology, functional analysis techniques, and Socratic method. Using a knowledge acquisition device originally developed to allow specialists to impart their knowledge to expert systems, our tool asks students questions, leads them through functional analysis of a problem and, in effect, induces them to teach the system their solution strategy. An existing prototype is described, and a proposal for further development is presented.

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Structure of an Embedded System Software Platform for Plate Recognition System Based on Applied Mechanics

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.460.266 ◽

2012 ◽

Vol 460 ◽

pp. 266-270

Author(s):

Xing Wu Sun ◽

Yu Chen ◽

Ai Fei Wang

Keyword(s):

Embedded System ◽

Recognition System ◽

Cmos Camera ◽

Camera System ◽

New Thought ◽

Development Platform ◽

Embedded Linux System ◽

Acquisition Device ◽

The Embedded System ◽

And Control

According to the shortcomings of large volume and high cost about the plate recognition system, an embedded plate recognition system is developed based on the ARM11 processor at lower costs. Taking the embedded Linux system as the software development platform, the system uses graphical user interface to operate and control the machine. Using CMOS camera system as image acquisition device, the system adopts HSV algorithm to realize the image classification on the platform of the embedded plate recognition system. The experimental results show that the embedded system runs stably, can realize the plate classification by color, and has the advantages of small size, low power consumption, convenience for using and so on. The embedded system provides a new thought for plate recognition.

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Learning and the Evolution of Language: The Role of Cultural Variation and Learning Costs in the Baldwin Effect

Artificial Life ◽

10.1162/106454602321202408 ◽

2002 ◽

Vol 8 (4) ◽

pp. 311-339 ◽

Cited By ~ 23

Author(s):

Steve Munroe ◽

Angelo Cangelosi

Keyword(s):

Language Acquisition ◽

Structural Properties ◽

Cultural Transmission ◽

Cultural Variation ◽

Baldwin Effect ◽

Evolution Of Language ◽

Specific Language ◽

Acquisition Device ◽

The Baldwin Effect

The Baldwin effect has been explicitly used by Pinker and Bloom as an explanation of the origins of language and the evolution of a language acquisition device. This article presents new simulations of an artificial life model for the evolution of compositional languages. It specifically addresses the role of cultural variation and of learning costs in the Baldwin effect for the evolution of language. Results show that when a high cost is associated with language learning, agents gradually assimilate in their genome some explicit features (e.g., lexical properties) of the specific language they are exposed to. When the structure of the language is allowed to vary through cultural transmission, Baldwinian processes cause, instead, the assimilation of a predisposition to learn, rather than any structural properties associated with a specific language. The analysis of the mechanisms underlying such a predisposition in terms of categorical perception supports Deacon's hypothesis regarding the Baldwinian inheritance of general underlying cognitive capabilities that serve language acquisition. This is in opposition to the thesis that argues for assimilation of structural properties needed for the specification of a full-blown language acquisition device.

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