scholarly journals Editorial of Energy-Efficient and Reliable Information Processing: Computing and Storage

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 914 ◽  
Author(s):  
Yongjune Kim
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Energy Efficient ◽  
Human Performance ◽  
Reliable Information ◽  
And Storage

Recently, artificial intelligence (AI) systems have begun to approach and exceed human performance in many intelligent tasks: AlexNet [...]

Artificial intelligence-based nonlinear control of renewable energies and storage system in a DC microgrid

2021 ◽  
Author(s):  
Syeda Shafia Zehra ◽  
Aqeel Ur Rahman ◽  
Hammad Armghan ◽  
Iftikhar Ahmad ◽  
Umme Ammara
Keyword(s):  
Artificial Intelligence ◽  
Nonlinear Control ◽  
Storage System ◽  
Renewable Energies ◽  
Dc Microgrid ◽  
And Storage

Evaluation and Comparison of Artificial Intelligence Vision Aids: Orcam MyEye 1 and Seeing AI

2021 ◽  
pp. 0145482X2110274
Author(s):  
Christina Granquist ◽  
Susan Y. Sun ◽  
Sandra R. Montezuma ◽  
Tu M. Tran ◽  
Rachel Gage ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Human Performance ◽  
Visual Impairments ◽  
Light Level ◽  
Viewing Distance ◽  
Light Perception ◽  
Time To Completion ◽  
Significant Difference ◽  
Text Reading ◽  
Size Contrast

Introduction: We compared the print-to-speech properties and human performance characteristics of two artificial intelligence vision aids, Orcam MyEye 1 (a portable device) and Seeing AI (an iPhone and iPad application). Methods: There were seven participants with visual impairments who had no experience with the two reading aids. Four participants had no light perception. Two individuals with measurable acuity and one with light perception were tested while blindfolded. We also tested performance with text of varying appearance in varying viewing conditions. To evaluate human performance, we asked the participants to use the devices to attempt 12 reading tasks similar to activities of daily living. We assessed the ranges of text attributes for which reading was possible, such as print size, contrast, and light level. We also assessed if individuals could complete tasks with the devices and measured accuracy and completion time. Participants also completed a survey concerning the two aids. Results: Both aids achieved greater than 95% accuracy in text recognition for flat, plain word documents and ranged from 13 to 57% accuracy for formatted text on curved surfaces. Both aids could read print sizes as small as 0.8M (20/40 Snellen equivalent, 40 cm viewing distance). Individuals successfully completed 71% and 55% ( p = .114) of tasks while using Orcam MyEye 1 and Seeing AI, respectively. There was no significant difference in time to completion of tasks ( p = .775). Individuals believed both aids would be helpful for daily activities. Discussion: Orcam MyEye 1 and Seeing AI had similar text-reading capability and usability. Both aids were useful to users with severe visual impairments in performing reading tasks. Implications for Practitioners: Selection of a reading device or aid should be based on individual preferences and prior familiarity with the platform, since we found no clear superiority of one solution over the other.

The perception of humanness in conversational journalism: An algorithmic information-processing perspective

2021 ◽  
pp. 146144482199380
Author(s):  
Donghee Shin
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Cognitive Model ◽  
Human Beings ◽  
User Perception ◽  
User Experiences ◽  
Step Flow ◽  
Algorithmic Information ◽  
Information Processing Perspective ◽  
Practical Implications

How much do anthropomorphisms influence the perception of users about whether they are conversing with a human or an algorithm in a chatbot environment? We develop a cognitive model using the constructs of anthropomorphism and explainability to explain user experiences with conversational journalism (CJ) in the context of chatbot news. We examine how users perceive anthropomorphic and explanatory cues, and how these stimuli influence user perception of and attitudes toward CJ. Anthropomorphic explanations of why and how certain items are recommended afford users a sense of humanness, which then affects trust and emotional assurance. Perceived humanness triggers a two-step flow of interaction by defining the baseline to make a judgment about the qualities of CJ and by affording the capacity to interact with chatbots concerning their intention to interact with chatbots. We develop practical implications relevant to chatbots and ascertain the significance of humanness as a social cue in CJ. We offer a theoretical lens through which to characterize humanness as a key mechanism of human–artificial intelligence (AI) interaction, of which the eventual goal is humans perceive AI as human beings. Our results help to better understand human–chatbot interaction in CJ by illustrating how humans interact with chatbots and explaining why humans accept the way of CJ.

The 6C model for accurately capturing the patient’s medical history

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Taro Shimizu
Keyword(s):  
Artificial Intelligence ◽  
Differential Diagnosis ◽  
Patient Safety ◽  
Information Processing ◽  
Safety Concern ◽  
Data Gathering ◽  
Diagnostic Errors ◽  
Accurate Diagnosis ◽  
History Taking ◽  
Novel Approach

Abstract Diagnostic errors are an internationally recognized patient safety concern, and leading causes are faulty data gathering and faulty information processing. Obtaining a full and accurate history from the patient is the foundation for timely and accurate diagnosis. A key concept underlying ideal history acquisition is “history clarification,” meaning that the history is clarified to be depicted as clearly as a video, with the chronology being accurately reproduced. A novel approach is presented to improve history-taking, involving six dimensions: Courtesy, Control, Compassion, Curiosity, Clear mind, and Concentration, the ‘6 C’s’. We report a case that illustrates how the 6C approach can improve diagnosis, especially in relation to artificial intelligence tools that assist with differential diagnosis.

AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

Construction Research of Exercise Prescription Expert System

2013 ◽  
Vol 718-720 ◽  
pp. 2422-2426
Author(s):  
Ming Gou ◽  
Jing Yang
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Expert System ◽  
Exercise Prescription ◽  
Scientific Model ◽  
Test Database

The test database of students' health is being analyzed with the information processing tool of artificial intelligence Expert System in order to create a scientific model of students Exercise Prescription in the end. It aims at starting with studying every student to realize an optimized development for the quality potential of every student.

scholarly journals Multiple purpose spin transfer torque operated devices

2013 ◽  
Vol 26 (3) ◽  
pp. 227-238
Author(s):  
Thomas Windbacher ◽  
Hiwa Mahmoudi ◽  
Alexander Makarov ◽  
Viktor Sverdlov ◽  
Siegfried Selberherr
Keyword(s):  
Information Processing ◽  
Building Block ◽  
Energy Efficient ◽  
Spin Transfer Torque ◽  
Spin Transfer ◽  
Spin Torque ◽  
Logic Device ◽  
Flip Flop ◽  
Sequential Logic ◽  
Efficient Information

We summarize our recent work on a non-volatile logic building block required for energy-efficient information processing systems. A sequential logic device, in particular, an alternative non-volatile magnetic flip-flop has been introduced. Its properties are investigated and its extension to a very dense shift register is demonstrated. We show that the flip-flop structure inherently exhibits oscillations and discuss its spin torque nano-oscillator properties.

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