AI SearchAdvancing in-situ microplastic detection using electrical sensing zone empowered by machine learning and deep learning approaches (Record no. 2564)
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| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260817161747.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
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| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | .b12507891 |
| 099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Classification number | AIT Thesis no.EV-26-06 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Laraib |
| 245 10 - TITLE STATEMENT | |
| Title | Advancing in-situ microplastic detection using electrical sensing zone empowered by machine learning and deep learning approaches |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Pathum Thani, Thailand : |
| Name of publisher, distributor, etc. | Asian Institute of Technology, |
| Date of publication, distribution, etc. | 2026 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 118 leaves : |
| Other physical details | ill.+ |
| Accompanying material | 1 online resource |
| 490 1# - SERIES STATEMENT | |
| Series statement | Thesis ; |
| Volume/sequential designation | no. EV-26-06 |
| 500 ## - GENERAL NOTE | |
| General note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Environmental Engineering and Management |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M. Sc.) - Asian Institute of Technology, 2026 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | The problem of pollution with microplastic debris has become one of the most pressing ones because of the resistance of plastics to biodegradation and existing challenges of the classical approach to their rapid detection in aquatic ecosystems. This work studied the potential for applying the method of Electrical Sensing Zone (ESZ) combined with machine learning and deep learning techniques for classifying particles. The chosen classes include three types of microplastics: polyethylene terephthalate (PET), polypropylene (PP), and polystyrene (PS); two classes of inorganic particles: silicon dioxide (SiO₂) and calcium carbonate (CaCO₃); and Chlorella algae as a class of biological particles.The raw signals have been generated under laboratory conditions as voltage-time waveforms. Further preprocessing comprised denoising, baseline correction, peak detection, and pulse extraction. The signal of Chlorella algae particles was close to the baseline. Thus, the main classification analysis involved microplastic particles and inorganic particles' signals. Pulse signals have been encoded both as engineered feature vectors for feature-based machine learning and as fixed-length segments (windows) for CNN classification. The strategies considered included the following: five-class machine learning, binary machine learning, binary CNN classification, flat three-particle CNN classification, step-wise hierarchical three-particle CNN classification, and PET/PS/PP subtype CNN classification.The performance of five-class feature-based machine learning models proved low since the best results were obtained by Random Forest with a baseline test accuracy of 44.13%, followed by Boosting (42.76%) and SVM (38.43%). For the binary machine learning classifier, which could classify microplastics against inorganic particles, the performance was not taken into account here. CNN models demonstrated stronger classification capabilities: binary CNN yielded 91.98% of test accuracy; flat three-particle CNN {u2013} 58.13%; step-wise hierarchical three-particle CNN {u2013} 74.47%; PET/PS/PP subtypes CNN {u2013} 51.05%. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Coulter principle |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Microplastics |
| General subdivision | Dection |
| -- | Technique |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Xue, Wenchao, |
| Relator term | Chairperson |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ghimire, Anish, |
| Relator term | Examination Committee |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Attaphongse Taparugssanagorn, |
| Relator term | Examination Committee |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | PMU-KPCIP-AIT Scholarship, |
| Relator term | Scholarship Donor |
| 810 2# - SERIES ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | Asian Institute of Technology. |
| Title of a work | Thesis ; |
| Volume/sequential designation | no. EV-26-06 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Materials specified | Full-Text |
| Uniform Resource Identifier | <a href="http://203.159.5.9/ait-thesis/detail.php?q=B24442">http://203.159.5.9/ait-thesis/detail.php?q=B24442</a> |
| 907 ## - LOCAL DATA ELEMENT G, LDG (RLIN) | |
| a | .b12507891 |
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| c | a |
| 902 ## - LOCAL DATA ELEMENT B, LDB (RLIN) | |
| a | 260622 |
| 998 ## - LOCAL CONTROL INFORMATION (RLIN) | |
| Operator's initials, OID (RLIN) | 0 |
| Cataloger's initials, CIN (RLIN) | 260617 |
| First date, FD (RLIN) | m |
| -- | h |
| -- | a |
| -- | 0 |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 945 ## - LOCAL PROCESSING INFORMATION (OCLC) | |
| l | mnarc |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 67-Electronic Resource |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | 40-Archives |
| 909 ## - LOCAL ITEMS USED | |
| Barcode | Barcode : - |
| CREATED | CREATED : 2026-06-16 |
| RECORD Id | RECORD # : i13605148 |
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| Barcode | Barcode : 30050120421044 |
| CREATED | CREATED : 2026-06-17 |
| RECORD Id | RECORD # : i13605872 |
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| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Copy number | Price effective from | Koha item type | Barcode |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.EV-26-06 | 17/08/2026 | 1 | 17/08/2026 | 67-Electronic Resource | |||||
| Available for Loans | Asian Institute of Technology Library | Asian Institute of Technology Library | Archives | 17/08/2026 | AIT Thesis no.EV-26-06 | 17/08/2026 | 1 | 17/08/2026 | 40-Archives | 30050120421044 |