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Big data capability and supply chain performance: the mediating effect of supply chain resilience and the moderating effecting of environmental uncertainty
No full textDevelopmental and personality theory
No full textHow do human beings come to be the people they are? More specifically, why do some people come to experience the psychological difficulties that they do? These are the questions that developmental and personality theorists in the counseling and psychotherapy field have asked, and this chapter looks at person-centred attempts to answer these questions. The principal focus of this chapter is on developments from childhood to adulthood. Discussed in this chapter is the historical development of theories of personality and growth in the person-centred field; Rogers' classic model of human development; evidence in support of the classical model; contemporary critiques and developments of Rogers' classical model; and the relevance of developmental and personality theory to person-centred practice
TerraMontes [Screendance]
No full textTerraMontes is a meditative site-specific screendance which explores an embodied sense of healing with the environment. As with the two previous works from the WECreate Productions’ Terra series, (HinterTerra, and UrbáTerra), the dancers and camera explore the poetics of place through improvisation.In a matter of hours, The Lower North Fork Fire blazed through more than four thousand acres of pristine forest. Thousands were displaced, the fire destroyed almost thirty homes and resulted in three fatalities. The fire began on March 26, 2012 when firefighters lost control of a planned burn in Foxton, Colorado. Some of the fire was classified as high intensity, making the recovery of the land a very long process or impossible in some cases.Filmed in the Colorado Foothills, United States, 2024Direction: Ana Baer & Heike SalzerChoreography and Dance: Michelle Nance, Kim Olson, Heike SalzerOriginal composition: Joaquin Lopez ChasMusic Design and Music Mixing: Richard D. HallCostume design: Shay IsshiCinematography: Ana Baer Editing: Ana Baer Production: WECreate ProductionsLength: 5.55 minUS Premiere, at Opening Doors Dance Theatre, "Leaving the light on" Celebrating 40 years [Oct 24-26, 2024] Patti Strickel Harrison Theatre, Texas State University, San Marcos, TX, US.<br/
EFT for Three: Working with Polyamorous Relationships
No full textThis article proposes an adaptation of Emotionally Focused Therapy (EFT) for couples to serve nonmonogamous clients. This article also discusses the risks of failing to adapt therapeutic models to consider individuals who practice polyamory and research to date on attachment styles and polyamory. The authors suggest EFT as an efficacious approach to working with polyamorous individuals seeking therapy and provide a case illustration of a three-person polyamorous group, or triad
An introduction to acoustic location Template-based positioning model
No full textIndoor location information, which is an indispensable label for linking the vast amount of data circulating in the world of IoT, 5G, and AI, is essential. This paper proposes a novel template pattern matching-based acoustic positioning method, Location Template-based Positioning Model, for indoor acoustic source localisation. This innovative technology, similar to the passive SONAR systems on submarines, uses audible acoustic waves to locate acoustic sources in complex indoor environments. The proposed LTPM is a statistical model, and it calculates the coordinates of acoustic sources by matching input acoustic signals with template acoustic signals that are pre-collected from preset locations. A comprehensive overview of the principles and implementations of LTPM is provided, and its feasibility is verified through preliminary positioning tests in this paper. It is hoped to provide research references for the advancement of pattern matching-based acoustic indoor positioning technologies
Motor imagery drives the effects of combined action observation and motor imagery on corticospinal excitability for coordinative lower-limb actions
No full textCombined action observation and motor imagery (AOMI) facilitates corticospinal excitability (CSE) and may potentially induce plastic-like changes in the brain in a similar manner to physical practice. This study used transcranial magnetic stimulation (TMS) to explore changes in CSE for AOMI of coordinative lower-limb actions. Twenty-four healthy adults completed two baseline (BL , BL ) and three AOMI conditions, where they observed a knee extension while simultaneously imagining the same action (AOMI ), plantarflexion (AOMI ), or dorsiflexion (AOMI ). Motor evoked potential (MEP) amplitudes were recorded as a marker of CSE for all conditions from two knee extensor, one dorsi flexor, and two plantar flexor muscles following TMS to the right leg representation of the left primary motor cortex. A main effect for experimental condition was reported for all three muscle groups. MEP amplitudes were significantly greater in the AOMI condition compared to the BL condition (p = .04) for the knee extensors, AOMI condition compared to the BL condition (p = .03) for the plantar flexors, and AOMI condition compared to the two baseline conditions for the dorsi flexors (ps ≤ .01). The study findings support the notion that changes in CSE are driven by the imagined actions during coordinative AOMI. [Abstract copyright: © 2024. The Author(s).
Ontology-Based Deep Learning Model for Object Detection and Image Classification in Smart City Concepts
Get PDFObject detection in remotely sensed (RS) satellite imagery has gained significance in smart city concepts, which include urban planning, disaster management, and environmental monitoring. Deep learning techniques have shown promising outcomes in object detection and scene classification from RS satellite images, surpassing traditional methods that are reliant on hand-crafted features. However, these techniques lack the ability to provide in-depth comprehension of RS images and enhanced interpretation for analyzing intricate urban objects with functional structures and environmental contexts. To address this limitation, this study proposes a framework that integrates a deep learning-based object detection algorithm with ontology models for effective knowledge representation and analysis. The framework can automatically and accurately detect objects and classify scenes in remotely sensed satellite images and also perform semantic description and analysis of the classified scenes. The framework combines a knowledge-guided ontology reasoning module into a YOLOv8 objects detection model. This study demonstrates that the proposed framework can detect objects in varying environmental contexts captured using a remote sensing satellite device and incorporate efficient knowledge representation and inferences with a less-complex ontology model