A Descriptive Analysis of Performance Models’ Intonation in a Recorded Excerpt from Suzuki Violin School Volume I

Objective: Too much reliance is being laid on applications of AI in finding solution to various problems being faced by human kinds. The recent outbreak of COVID 19 is comparable to outbreak of any other havoc on the mankind including war, due to similar characteristics of three Vs i.e. Velocity; Volume and Veracity. The objective of study is to draw out lessons from AI applications and success achieved during pandemic spread for the application of AI in future wars. Method : The study has been done in two parts first part consist of descriptive analysis of performance of AI in predicting, diagnosing and finding the resolution to current pandemic. The second part consists of working out the way forward for application of AI during future warfare. The methodology used for working out expected Ai performance during future warfare has been survey and interaction with the experts in the field. Findings :The findings of the study have been that AI has been quite a success story during prediction and diagnosis stage of Pandemic but the actual performance in finding solution to the problem has been questionable. As a result the countries world over have suffered huge losses and had to resort to various preventions measures. Novelty : The novelty of the study is derived from the fact that various study in the AI field have been specific to a particular field and no work was done on learning the lessons from one domain to its application to other field of similar nature. The question of “How much reliance should be laid upon AI during a future war.” has largely remained unanswered. With reference to ethical and legal issues related to AI in employment of Killer Robots the study recommends future course of action. We need to ensure that no rogue application of AI takes place in a sector where the very existence of humanity is at stake.

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Extracting Response Times from Fluid Analysis of Performance Models

Performance Evaluation: Metrics, Models and Benchmarks - Lecture Notes in Computer Science ◽

10.1007/978-3-540-69814-2_4 ◽

2008 ◽

pp. 29-43 ◽

Cited By ~ 4

Author(s):

Jeremy T. Bradley ◽

Richard Hayden ◽

William J. Knottenbelt ◽

Tamas Suto

Keyword(s):

Response Times ◽

Performance Models ◽

Fluid Analysis ◽

Analysis Of Performance

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The Elicited Language Analysis Procedure

Language Speech and Hearing Services in Schools ◽

10.1044/0161-1461.1301.37 ◽

1982 ◽

Vol 13 (1) ◽

pp. 37-41

Author(s):

Larry J. Mattes

Keyword(s):

Diagnostic Tool ◽

Descriptive Analysis ◽

Quality Measures ◽

Analysis Procedure ◽

Elicited Imitation ◽

Response Quality ◽

Semantic Relationships ◽

Language Analysis

Elicited imitation tasks are frequently used as a diagnostic tool in evaluating children with communication handicaps. This article presents a scoring procedure that can be used to obtain an in-depth descriptive analysis of responses produced on elicited imitation tasks. The Elicited Language Analysis Procedure makes it possible to systematically evaluate responses in terms of both their syntactic and semantic relationships to the stimulus sentences presented by the examiner. Response quality measures are also included in the analysis procedure.

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Perceptions of Adjunctive Mindfulness-Based Cognitive Therapy to Prevent Suicidal Behavior Among High Suicide-Risk Outpatient Participants

Crisis ◽

10.1027/0227-5910/a000519 ◽

2018 ◽

Vol 39 (6) ◽

pp. 451-460 ◽

Cited By ~ 2

Author(s):

Megan S. Chesin ◽

Beth S. Brodsky ◽

Brandon Beeler ◽

Christopher A. Benjamin-Phillips ◽

Ida Taghavi ◽

...

Keyword(s):

Cognitive Therapy ◽

Suicidal Behavior ◽

Group Treatment ◽

Suicide Risk ◽

Qualitative Data ◽

Descriptive Analysis ◽

Treatment Engagement ◽

Suicidal Thinking ◽

Prevention Interventions ◽

Risk Patients

Abstract. Background: Few investigations of patient perceptions of suicide prevention interventions exist, limiting our understanding of the processes and components of treatment that may be engaging and effective for high suicide-risk patients. Aims: Building on promising quantitative data that showed that adjunct mindfulness-based cognitive therapy to prevent suicidal behavior (MBCT-S) reduced suicidal thinking and depression among high suicide-risk patients, we subjected MBCT-S to qualitative inspection by patient participants. Method: Data were provided by 15 patients who completed MBCT-S during a focus group and/or via a survey. Qualitative data were coded using thematic analysis. Themes were summarized using descriptive analysis. Results: Most patients viewed the intervention as acceptable and feasible. Patients attributed MBCT-S treatment engagement and clinical improvement to improved emotion regulation. A minority of patients indicated that factors related to the group treatment modality were helpful. A small percentage of patients found that aspects of the treatment increased emotional distress and triggered suicidal thinking. These experiences, however, were described as fleeting and were not linked to suicidal behavior. Limitations: The sample size was small. Conclusion: Information gathered from this study may assist in refining MBCT-S and treatments to prevent suicidal behavior among high suicide-risk patients generally.

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