Emotional State Prediction from Online Handwriting and Signiture Biometrics / (Kayıt no. 281785)
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| 000 -BAŞLIK | |
|---|---|
| Sabit Uzunluktaki Kontrol Alanı | 03799nam a22002897a 4500 |
| 003 - KONTROL NUMARASI KİMLİĞİ | |
| Kontrol Alanı | KOHA_MİRAKIL |
| 005 - EN SON İŞLEM TARİHİ ve ZAMANI | |
| Kontrol Alanı | 20210330154150.0 |
| 008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ | |
| Sabit Alan | 210326d2021 cy ||||| m||| 00| 0 eng d |
| 040 ## - KATALOGLAMA KAYNAĞI | |
| Özgün Kataloglama Kurumu | CY-NiCIU |
| Kataloglama Dili | eng |
| Çeviri Kurumu | CY-NiCIU |
| Açıklama Kuralları | rda |
| 041 ## - DİL KODU | |
| Metin ya da ses kaydının dil kodu | eng |
| 090 ## - Yerel Tasnif No | |
| tasnif no | D 231 |
| Cutter no | B29 2021 |
| 100 1# - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Bay, Yasemin |
| 245 10 - ESER ADI BİLDİRİMİ | |
| Başlık | Emotional State Prediction from Online Handwriting and Signiture Biometrics / |
| Sorumluluk Bildirimi | Yasemin BAY; Supervisor: Assoc. Prof. Dr. Erbuğ ÇELEBİ |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2021 |
| 300 ## - FİZİKSEL TANIMLAMA | |
| Sayfa, Cilt vb. | 115 sheets; |
| Boyutları | 30 cm. |
| 336 ## - CONTENT TYPE | |
| Source | rdacontent |
| Content type term | text |
| Content type code | txt |
| 337 ## - MEDIA TYPE | |
| Source | rdamedia |
| Media type term | unmediated |
| Media type code | n |
| 338 ## - CARRIER TYPE | |
| Source | rdacarrier |
| Carrier type term | volume |
| Carrier type code | nc |
| 502 ## - TEZ NOTU | |
| Tez Notu | Thesis (Ph.D) - Cyprus International University. Institute of Graduate Studies and Research Management Information Systems Department |
| 504 ## - BİBLİYOGRAFİ NOTU | |
| Bibliyografi Notu | Includes bibliography (sheets 95-111) |
| 520 ## - ÖZET NOTU | |
| Özet notu | ABSTRACT<br/>It has long been known that handwriting reveals many information for an individual's<br/>identification. For the last century, investigators first tried to predict the owner of the<br/>handwriting then recognized that it reveals more information such as the characteristics<br/>of the owner therefore shifted most of their attention to personal characteristics<br/>estimation, such as emotional state, However, to be able to evaluate and investigate the<br/>emotional state of an individual there is a need of a database with correctly labelled data<br/>with the relevant ground truth information. Yet, for researchers to be able to evaluate<br/>one's emotional state fairly is to work on a database providing the basic requirements<br/>which are, including contributors' demographic labels (age, gender, ethnicity etc.) or<br/>emotional status in addition to their identification labels. Unfortunately, there are almost<br/>no database, neither public nor commercial, providing this useful information.<br/>This dissertation will first propose a novel and rigorous handwriting and signature<br/>biometric database both in offline and online form and then predict one’s emotional state.<br/>To achieve this goal wide range of ground truths (i.e. identity labels, demographic labels<br/>as well as emotional state labels) will be used which are not contemplated by any other<br/>publicly or commercially available biometric handwriting and signature databases in the<br/>literature. Therefore, making this novel database available will shed a light to the<br/>biometric research community once again and researchers can actively work on it to<br/>contribute to science.<br/>The proposed database comprised total of 134 volunteers with handwriting and signature<br/>biometric data acquired using a digitizing tablet and a stylus pen. The process consisted<br/>of four different steps, each with aiming to extract different emotional states Task 1 -<br/>natural, Task 2 - happy, Task 3 - sad and Task 4 - stress. The database presented also<br/>includes individuals’ demographic information such as age, gender, handedness,<br/>education level and nationality. Database in total consists of 804 handwriting and 8040<br/>signature biometric samples.<br/>To be able to achieve the goal of this dissertation there have been 3 different experiments<br/>carried out to predict emotional state from handwriting and signature biometrics and the<br/>iii<br/>results obtained were encouraging with slightly high recognition rates and proves that<br/>both handwriting and signature biometrics contain valuable information regarding one’s<br/>emotional state. Out of 42 features 11 of them were selected after the feature selection<br/>method for classification purpose. |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Biometric identification |
| Alt başlık biçimi | Dissertation, Academic |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Emotions |
| Alt başlık biçimi | Dissertation, Academic |
| Genel Alt Konu | Prediction theory |
| 700 1# - EK GİRİŞ - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Çelebi, Erbuğ |
| İlişkili Terim | supervisor |
| 9 (RLIN) | 1665 |
| 942 ## - EK GİRİŞ ÖGELERİ (KOHA) | |
| Sınıflama Kaynağı | Dewey Onlu Sınıflama Sistemi |
| Materyal Türü | Thesis |
| Geri Çekilme Durumu | Kayıp Durumu | Sınıflandırma Kaynağı | Kredi için değil | Koleksiyon Kodu | Kalıcı Konum | Mevcut Konum | Raf Yeri | Kayıt Tarih | Source of acquisition | Yer Numarası | Demirbaş Numarası | Son Görülme Tarihi | Fatura Tarihi | Materyal Türü | Genel / Bağış Notu |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Tez Koleksiyonu | 26.03.2021 | Bağış | D 231 B29 2021 | T2157 | 26.03.2021 | 26.03.2021 | Thesis | Management Information Systems Department | |||
| Dewey Onlu Sınıflama Sistemi | CIU LIBRARY | CIU LIBRARY | Görsel İşitsel | 26.03.2021 | Bağış | D 231 B29 2021 | CDT2157 | 26.03.2021 | 26.03.2021 | Suppl. CD | Management Information Systems Department |