Predictive Monitoring of Wirebond Ultrasonic Signal on Electrical Test Result Using Machine Learning

Background. New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome. Methods. We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis. Results. A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase. Conclusions. Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.

Download Full-text

Ultrasonic signal enhancement for coarse grain materials by machine learning analysis

Ultrasonics ◽

10.1016/j.ultras.2021.106550 ◽

2021 ◽

pp. 106550

Author(s):

Wanli Xu ◽

Xiaohong Li ◽

Jun Zhang ◽

Zhixiang Xue ◽

Jiancheng Cao

Keyword(s):

Machine Learning ◽

Ultrasonic Signal ◽

Signal Enhancement ◽

Coarse Grain ◽

Learning Analysis

Download Full-text

PENGARUH MEDIA PEMBELAJARAN BERBASIS ENGINE STAND TERHADAP HASIL BELAJAR MESIN KONVERSI ENERGI SISWA KELAS X JURUSAN TEKNIK KENDARAAN RINGAN DI SMK NEGERI 3 SINGARAJA

Jurnal Pendidikan Teknik Mesin Undiksha ◽

10.23887/jptm.v7i2.26501 ◽

2019 ◽

Vol 7 (2) ◽

pp. 79

Author(s):

M Syahrul Utama ◽

L.J.E. Dewi ◽

I.N Pasek Nugraha

Keyword(s):

Machine Learning ◽

Statistical Analysis ◽

Energy Conversion ◽

Learning Outcomes ◽

Average Energy ◽

Student Learning Outcomes ◽

Vocational School ◽

Vehicle Engineering ◽

Light Vehicle ◽

Test Result

Penelitian ini bertujuan untuk mengetahui pengaruh penggunaan media pembelajaran berbasis engine stand terhadap hasil belajar mesin konversi energi siswa kelas X Teknik Kendaraan Ringan (TKR). Penelitian ini dilakukan di SMK Negeri 3 Singraja, pada kelas X TKR yang berjumlah 66 orang yang terbagi menjadi dua kelas. Kelas X TKR 3 (kelas eksperimen) dan kelas X TKR 2 (kelas kontrol). Instrumen yang digunakan dalam penelitian ini berupa tes hasil belajar tipe pilihan ganda sebanyak 30 butir dengan lima pilihan. Data hasil tes dianalisis dengan uji analisis statistik berbantuan SPSS 16.0 for windows berupa uji kesamaan rata-rata nilai pretest dan posttest kedua kelas. Hasil penelitian menyimpulkan bahwa media pembelajaran berbasis engine stand menunjukkan pengaruh terhadap hasil belajar mesin konversi energi pada siswa. Hal ini berdasarkan output pair 2 diperoleh nilai Sig. (2-tailed) sebesar 0,000 < 0,05, maka dapat disimpulkan ada perbedaan rata-rata hasil belajar mesin konversi energi siswa kelas X TKR untuk pretest kelas kontrol dengan posttest kelas kontrol. Hal ini terlihat dari rata-rata hasil belajar mesin konversi energi pada siswa yang menggunakan media pembelajaran berbasis engine stand sebesar 83.42, sedangkan rata-rata hasil belajar siswa mesin konversi energi tanpa media pembelajaran berbasis engine stand sebesar 60.88 dengan selisih 22.54. Kata-kata kunci: media pembelajaran berbasis engine stand, hasil belajar siswa. This study aims to determine the effect of the use of engine stand based learning media on the learning outcomes of energy conversion machine students in Class X Light Vehicle Engineering (TKR). This research was conducted at Singraja State Vocational School 3, in class X TKR totaling 66 people divided into two classes. Class X TKR 3 (experimental class) and class X TKR 2 (control class). The instrument used in this study was in the form of a 30 choice multiple choice type of learning outcomes test with five choices. The test result data were analyzed with SPSS 16.0 for windows statistical analysis test in the form of a similarity test of the pretest and posttest scores of the two classes. The results of the study concluded that engine stand based learning media showed an influence on learning outcomes of energy conversion machine on students. This is based on the results of the SPSS 16.0 t-test for Windows, the value based on pair 2 the Sig value is obtained. (2-tailed) of 0,000 <0.05, it can be concluded that there are differences in the average learning outcomes of machine energy conversion of class X TKR students for the control class pretest and the control class posttest. This can be seen from the average energy conversion machine learning outcomes of students who use engine stand based learning media at 83.42, while the average learning outcomes of energy conversion machine students without engine stand based learning media is at 60.88 with a difference of 22.54. Key words: engine stand based learning media, student learning outcomes.

Download Full-text

Mind wandering as data augmentation: How mental travel supports abstraction

Behavioral and Brain Sciences ◽

10.1017/s0140525x1900311x ◽

2020 ◽

Vol 43 ◽

Author(s):

Myrthe Faber

Keyword(s):

Machine Learning ◽

Data Augmentation ◽

Mental Content ◽

Mind Wandering ◽

Theoretical Framework ◽

Important Addition

Abstract Gilead et al. state that abstraction supports mental travel, and that mental travel critically relies on abstraction. I propose an important addition to this theoretical framework, namely that mental travel might also support abstraction. Specifically, I argue that spontaneous mental travel (mind wandering), much like data augmentation in machine learning, provides variability in mental content and context necessary for abstraction.

Download Full-text

Item Context and /s/ Phone Articulation Test Results

Journal of Speech and Hearing Research ◽

10.1044/jshr.1504.852 ◽

1972 ◽

Vol 15 (4) ◽

pp. 852-860 ◽

Cited By ~ 8

Author(s):

Zoe Zehel ◽

Ralph L. Shelton ◽

William B. Arndt ◽

Virginia Wright ◽

Mary Elbert

Keyword(s):

Test Score ◽

Sound Production ◽

Broad Context ◽

Test Results ◽

Production Task ◽

Test Result

Fourteen children who misarticulated some phones of the /s/ phoneme were tape recorded articulating several lists of items involving /s/. The lists included the Mc-Donald Deep Test for /s/, three lists similar to McDonald’s but altered in broad context, and an /s/ sound production task. Scores from lists were correlated, compared for differences in means, or both. Item sets determined by immediate context were also compared for differences between means. All lists were found to be significantly correlated. The comparison of means indicated that both broad and immediate context were related to test result. The estimated “omega square” statistic was used to evaluate the percentage of test score variance attributable to context.

Download Full-text