scholarly journals Evaluation of whole-water churn splitters for suspended-sediment sample collection and analysis

2018 ◽  
Author(s):  
Miya N. Barr
Keyword(s):  
Suspended Sediment ◽  
Sediment Sample ◽  
Sample Collection ◽  
Whole Water

scholarly journals Hubungan Pengendapan Suspended Sedimen dengan Kerapatan Mangrove pada Perairan Romokalisari, Surabaya

2019 ◽  
Vol 8 (4) ◽  
pp. 355-360
Author(s):  
Muhammad Yusuf Arifin ◽  
Nirwani Soenardjo ◽  
Chrisna Adhi Suryono
Keyword(s):  
Data Analysis ◽  
Suspended Sediment ◽  
Deposition Rate ◽  
Sediment Sample ◽  
Sedimentation Rates ◽  
Sediment Samples ◽  
Mangrove Area ◽  
A Value ◽  
One Way Anova

ABSTRAK: Romokalisari merupakan bagian hilir dari sungai Lamong, dimana daerah tersebut merupakan daerah pasang surut dan rawan terhadap banjir. Romokalisari banyak ditumbuhi oleh mangrove yang sangat rapat. Tujuan penelitian ini adalah untuk mengetahui pengaruh kerapatan mangrove terhadap laju pengendapan suspended sedimen pada perairan Romokalisari, Surabaya. Sampel sedimen diambil dari 8 stasiun yang terbagi dalam wilayah muara, mangrove dan laut, dimana masing-masing stasiun diulang 4 kali dengan periode setiap minggu. Analisis sampel sedimen menggunakan metode hydrometer dan analisis data menggunakan One Way Anova. Hasil penelitian menunjukkan bahwa ada perbedaan laju pengendapan suspended sedimen antara muara, mangrove dan laut, dengan nilai p = 0,046 < 0,05. Laju pengendapan suspended tertinggi terdapat pada stasiun 1 di wilayah muara dengan nilai sebesar 86,97 g/cm2/minggu dan laju pengendapan suspended terendah terdapat pada stasiun 2 di wilayah mangrove dengan nilai sebesar14,36g/cm2/minggu. ABSTRACT: Romokalisari is downstream part of the Lamong River, where the area is tidal and prone to flooding. Romokalisari is overgrown by very dense mangroves. The aim of this study was to determine the effect of mangrove density on suspended sediment rate in Romokalisari, Surabaya. Sediment sample were taken from 8 statios divided into estuaries, mangroves, and sea areas, each station was repeated 4 times with periods each week. Analysis of sediment samples using a hydrometer and data analysis using One Way Anova. The results showed that there were differences in suspended sedimentation rates between estuaries, mangroves and seas, with a value of p = 0,046 < 0,05. The highest suspended deposition rate is at station 1 in the estuary area with a value of 86.97 g/cm2/week and the lowest suspended deposition rate is at station 2 in the mangrove area with a value of 14.36 g/cm2/week.

A Standard-Reference Water-Suspended Sediment Sample for Total Recoverable Metals

1984 ◽  
Vol 12 (3) ◽  
pp. 182
Author(s):  
R Horstman ◽  
KA Peters ◽  
S Gebremedhin ◽  
RL Meltzer ◽  
MB Vieth ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
Sediment Sample

Evaluation of Acoustic Analyses of Voice in Nonoptimized Conditions

2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung
Keyword(s):  
Repeated Measures ◽  
Voice Quality ◽  
Data Sets ◽  
Acoustic Measurements ◽  
Sample Collection ◽  
Experimental Conditions ◽  
Environment Analysis ◽  
Acoustic Measures ◽  
Recording Conditions ◽  
Cepstral Peak Prominence

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.

Issues in Language Sample Collection and Analysis With Children Using AAC

2014 ◽  
Vol 23 (2) ◽  
pp. 65-74 ◽  
Author(s):  
Gail Van Tatenhove
Keyword(s):  
Clinical Practice ◽  
Augmentative And Alternative Communication ◽  
Language Production ◽  
Expressive Language ◽  
Sample Analysis ◽  
Alternative Communication ◽  
Sample Collection ◽  
Speech Language Pathologists ◽  
Language Sample Analysis ◽  
Language Sample

Language sample analysis is considered one of the best methods of evaluating expressive language production in speaking children. However, the practice of language sample collection and analysis is complicated for speech-language pathologists working with children who use augmentative and alternative communication (AAC) devices. This article identifies six issues regarding use of language sample collection and analysis in clinical practice with children who use AAC devices. The purpose of this article is to encourage speech-language pathologists practicing in the area of AAC to utilize language sample collection and analysis as part of ongoing AAC assessment.

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