Review of Intentional Electromagnetic Interference on UAV Sensor Modules and Experimental Study.

With the advancement of technology, Unmanned Aerial Vehicles (UAVs), also known as drones, are being used in numerous applications. However, the illegal use of UAVs, such as in terrorism and spycams, has also increased, which has led to active research on anti-drone methods. Various anti-drone methods have been proposed over time; however, the most representative method is to apply intentional electromagnetic interference to drones, especially to their sensor modules. In this paper, we review various studies on the effect of intentional electromagnetic interference (IEMI) on the sensor modules. Various studies on IEMI sources are reviewed and classified on the basis of the power level, information needed, and frequency. To demonstrate the application of drone-sensor modules, major sensor modules used in drones are briefly introduced, and the setup and results of the IEMI experiment performed on them are described. Finally, we discuss the effectiveness and limitations of the proposed methods and present perspectives for further research necessary for the actual application of anti-drone technology.

Estimation of K-WAIS-IV Premorbid Intelligence in South Korea: Development of the KPIE-IV.

OBJECTIVE: The accurate estimation of premorbid intellectual functioning in patients with known or suspected cognitive impairment is crucial for clinicians. However, there is no reliable method for estimating premorbid intelligence in South Korea. The purpose of this study was to develop the Korea Premorbid Intelligence Estimate (KPIE) as an estimate of the premorbid intellectual functioning. METHOD: Data from the Korean WAIS-IV standardization sample were used to generate several Full Scale Intelligence Quotient (FSIQ) estimation formulas using demographic variables and current WAIS-IV subtest performance. The standardization sample (N = 1216) was randomly divided into two groups: the first group was used to develop the formulas and the second group was used to validate the prediction equations. Age, education, gender, region of the country, and select subtest raw scores (Vocabulary, Information, Matrix Reasoning, and Visual Puzzle) were used as predictor variables. RESULTS: Five KPIE-4 equations were generated. Estimated FSIQ derived from the KPIE-4 equation is highly correlated with K-WAIS-IV FSIQ. CONCLUSIONS: The resulting formulas for estimating premorbid FSIQ were highly significant and precise in predicting FSIQ scores of participants in the K-WAIS-IV normative sample. These equations provide a means for clinicians to estimate intellectual functioning in adults, and can be utilized as a method of estimating individuals premorbid functioning.