5 research outputs found

    ์žก์Œํ‚ค๋ฅผ ๊ฐ€์ง€๋Š” ์‹ ์›๊ธฐ๋ฐ˜ ๋™ํ˜•์•”ํ˜ธ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ์ˆ˜๋ฆฌ๊ณผํ•™๋ถ€,2020. 2. ์ฒœ์ •ํฌ.ํด๋ผ์šฐ๋“œ ์ƒ์˜ ๋ฐ์ดํ„ฐ ๋ถ„์„ ์œ„์ž„ ์‹œ๋‚˜๋ฆฌ์˜ค๋Š” ๋™ํ˜•์•”ํ˜ธ์˜ ๊ฐ€์žฅ ํšจ๊ณผ์ ์ธ ์‘์šฉ ์‹œ๋‚˜๋ฆฌ์˜ค ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ๋‹ค์–‘ํ•œ ๋ฐ์ดํ„ฐ ์ œ๊ณต์ž์™€ ๋ถ„์„๊ฒฐ๊ณผ ์š”๊ตฌ์ž๊ฐ€ ์กด์žฌํ•˜๋Š” ์‹ค์ œ ํ˜„์‹ค์˜ ๋ชจ๋ธ์—์„œ๋Š” ๊ธฐ๋ณธ์ ์ธ ์•”๋ณตํ˜ธํ™”์™€ ๋™ํ˜• ์—ฐ์‚ฐ ์™ธ์—๋„ ์—ฌ์ „ํžˆ ํ•ด๊ฒฐํ•ด์•ผ ํ•  ๊ณผ์ œ๋“ค์ด ๋‚จ์•„์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” ์ด๋Ÿฌํ•œ ๋ชจ๋ธ์—์„œ ํ•„์š”ํ•œ ์—ฌ๋Ÿฌ ์š”๊ตฌ์‚ฌํ•ญ๋“ค์„ ํฌ์ฐฉํ•˜๊ณ , ์ด์— ๋Œ€ํ•œ ํ•ด๊ฒฐ๋ฐฉ์•ˆ์„ ๋…ผํ•˜์˜€๋‹ค. ๋จผ์ €, ๊ธฐ์กด์˜ ์•Œ๋ ค์ง„ ๋™ํ˜• ๋ฐ์ดํ„ฐ ๋ถ„์„ ์†”๋ฃจ์…˜๋“ค์€ ๋ฐ์ดํ„ฐ ๊ฐ„์˜ ์ธต์œ„๋‚˜ ์ˆ˜์ค€์„ ๊ณ ๋ คํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ์ ์— ์ฐฉ์•ˆํ•˜์—ฌ, ์‹ ์›๊ธฐ๋ฐ˜ ์•”ํ˜ธ์™€ ๋™ํ˜•์•”ํ˜ธ๋ฅผ ๊ฒฐํ•ฉํ•˜์—ฌ ๋ฐ์ดํ„ฐ ์‚ฌ์ด์— ์ ‘๊ทผ ๊ถŒํ•œ์„ ์„ค์ •ํ•˜์—ฌ ํ•ด๋‹น ๋ฐ์ดํ„ฐ ์‚ฌ์ด์˜ ์—ฐ์‚ฐ์„ ํ—ˆ์šฉํ•˜๋Š” ๋ชจ๋ธ์„ ์ƒ๊ฐํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ด ๋ชจ๋ธ์˜ ํšจ์œจ์ ์ธ ๋™์ž‘์„ ์œ„ํ•ด์„œ ๋™ํ˜•์•”ํ˜ธ ์นœํ™”์ ์ธ ์‹ ์›๊ธฐ๋ฐ˜ ์•”ํ˜ธ์— ๋Œ€ํ•˜์—ฌ ์—ฐ๊ตฌํ•˜์˜€๊ณ , ๊ธฐ์กด์— ์•Œ๋ ค์ง„ NTRU ๊ธฐ๋ฐ˜์˜ ์•”ํ˜ธ๋ฅผ ํ™•์žฅํ•˜์—ฌ module-NTRU ๋ฌธ์ œ๋ฅผ ์ •์˜ํ•˜๊ณ  ์ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์‹ ์›๊ธฐ๋ฐ˜ ์•”ํ˜ธ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋‘˜์งธ๋กœ, ๋™ํ˜•์•”ํ˜ธ์˜ ๋ณตํ˜ธํ™” ๊ณผ์ •์—๋Š” ์—ฌ์ „ํžˆ ๋น„๋ฐ€ํ‚ค๊ฐ€ ๊ด€์—ฌํ•˜๊ณ  ์žˆ๊ณ , ๋”ฐ๋ผ์„œ ๋น„๋ฐ€ํ‚ค ๊ด€๋ฆฌ ๋ฌธ์ œ๊ฐ€ ๋‚จ์•„์žˆ๋‹ค๋Š” ์ ์„ ํฌ์ฐฉํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ์ ์—์„œ ์ƒ์ฒด์ •๋ณด๋ฅผ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋ณตํ˜ธํ™” ๊ณผ์ •์„ ๊ฐœ๋ฐœํ•˜์—ฌ ํ•ด๋‹น ๊ณผ์ •์„ ๋™ํ˜•์•”ํ˜ธ ๋ณตํ˜ธํ™”์— ์ ์šฉํ•˜์˜€๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์•”๋ณตํ˜ธํ™”์™€ ๋™ํ˜• ์—ฐ์‚ฐ์˜ ์ „ ๊ณผ์ •์„ ์–ด๋Š ๊ณณ์—๋„ ํ‚ค๊ฐ€ ์ €์žฅ๋˜์ง€ ์•Š์€ ์ƒํƒœ๋กœ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ์•”ํ˜ธ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๋™ํ˜•์•”ํ˜ธ์˜ ๊ตฌ์ฒด์ ์ธ ์•ˆ์ „์„ฑ ํ‰๊ฐ€ ๋ฐฉ๋ฒ•์„ ๊ณ ๋ คํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋™ํ˜•์•”ํ˜ธ๊ฐ€ ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ๋Š” ์ด๋ฅธ๋ฐ” Learning With Errors (LWE) ๋ฌธ์ œ์˜ ์‹ค์ œ์ ์ธ ๋‚œํ•ด์„ฑ์„ ๋ฉด๋ฐ€ํžˆ ๋ถ„์„ํ•˜์˜€๊ณ , ๊ทธ ๊ฒฐ๊ณผ ๊ธฐ์กด์˜ ๊ณต๊ฒฉ ์•Œ๊ณ ๋ฆฌ์ฆ˜๋ณด๋‹ค ํ‰๊ท ์ ์œผ๋กœ 1000๋ฐฐ ์ด์ƒ ๋น ๋ฅธ ๊ณต๊ฒฉ ์•Œ๊ณ ๋ฆฌ์ฆ˜๋“ค์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ํ˜„์žฌ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋Š” ๋™ํ˜•์•”ํ˜ธ ํŒŒ๋ผ๋ฏธํ„ฐ๊ฐ€ ์•ˆ์ „ํ•˜์ง€ ์•Š์Œ์„ ๋ณด์˜€๊ณ , ์ƒˆ๋กœ์šด ๊ณต๊ฒฉ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ†ตํ•œ ํŒŒ๋ผ๋ฏธํ„ฐ ์„ค์ • ๋ฐฉ๋ฒ•์— ๋Œ€ํ•ด์„œ ๋…ผํ•˜์˜€๋‹ค.Secure data analysis delegation on cloud is one of the most powerful application that homomorphic encryption (HE) can bring. As the technical level of HE arrive at practical regime, this model is also being considered to be a more serious and realistic paradigm. In this regard, this increasing attention requires more versatile and secure model to deal with much complicated real world problems. First, as real world modeling involves a number of data owners and clients, an authorized control to data access is still required even for HE scenario. Second, we note that although homomorphic operation requires no secret key, the decryption requires the secret key. That is, the secret key management concern still remains even for HE. Last, in a rather fundamental view, we thoroughly analyze the concrete hardness of the base problem of HE, so-called Learning With Errors (LWE). In fact, for the sake of efficiency, HE exploits a weaker variant of LWE whose security is believed not fully understood. For the data encryption phase efficiency, we improve the previously suggested NTRU-lattice ID-based encryption by generalizing the NTRU concept into module-NTRU lattice. Moreover, we design a novel method that decrypts the resulting ciphertext with a noisy key. This enables the decryptor to use its own noisy source, in particular biometric, and hence fundamentally solves the key management problem. Finally, by considering further improvement on existing LWE solving algorithms, we propose new algorithms that shows much faster performance. Consequently, we argue that the HE parameter choice should be updated regarding our attacks in order to maintain the currently claimed security level.1 Introduction 1 1.1 Access Control based on Identity 2 1.2 Biometric Key Management 3 1.3 Concrete Security of HE 3 1.4 List of Papers 4 2 Background 6 2.1 Notation 6 2.2 Lattices 7 2.2.1 Lattice Reduction Algorithm 7 2.2.2 BKZ cost model 8 2.2.3 Geometric Series Assumption (GSA) 8 2.2.4 The Nearest Plane Algorithm 9 2.3 Gaussian Measures 9 2.3.1 Kullback-Leibler Divergence 11 2.4 Lattice-based Hard Problems 12 2.4.1 The Learning With Errors Problem 12 2.4.2 NTRU Problem 13 2.5 One-way and Pseudo-random Functions 14 3 ID-based Data Access Control 16 3.1 Module-NTRU Lattices 16 3.1.1 Construction of MNTRU lattice and trapdoor 17 3.1.2 Minimize the Gram-Schmidt norm 22 3.2 IBE-Scheme from Module-NTRU 24 3.2.1 Scheme Construction 24 3.2.2 Security Analysis by Attack Algorithms 29 3.2.3 Parameter Selections 31 3.3 Application to Signature 33 4 Noisy Key Cryptosystem 36 4.1 Reusable Fuzzy Extractors 37 4.2 Local Functions 40 4.2.1 Hardness over Non-uniform Sources 40 4.2.2 Flipping local functions 43 4.2.3 Noise stability of predicate functions: Xor-Maj 44 4.3 From Pseudorandom Local Functions 47 4.3.1 Basic Construction: One-bit Fuzzy Extractor 48 4.3.2 Expansion to multi-bit Fuzzy Extractor 50 4.3.3 Indistinguishable Reusability 52 4.3.4 One-way Reusability 56 4.4 From Local One-way Functions 59 5 Concrete Security of Homomorphic Encryption 63 5.1 Albrecht's Improved Dual Attack 64 5.1.1 Simple Dual Lattice Attack 64 5.1.2 Improved Dual Attack 66 5.2 Meet-in-the-Middle Attack on LWE 69 5.2.1 Noisy Collision Search 70 5.2.2 Noisy Meet-in-the-middle Attack on LWE 74 5.3 The Hybrid-Dual Attack 76 5.3.1 Dimension-error Trade-o of LWE 77 5.3.2 Our Hybrid Attack 79 5.4 The Hybrid-Primal Attack 82 5.4.1 The Primal Attack on LWE 83 5.4.2 The Hybrid Attack for SVP 86 5.4.3 The Hybrid-Primal attack for LWE 93 5.4.4 Complexity Analysis 96 5.5 Bit-security estimation 102 5.5.1 Estimations 104 5.5.2 Application to PKE 105 6 Conclusion 108 Abstract (in Korean) 120Docto

    1-Piece Implant

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    Prosthodontic treatment using implants has many advantages in comparison with conventional treatment. However, it is reported that there are several complications associated with implants. They are divided into mechanical, biological, and esthetic aspects in prosthodontics. To overcome them, there have been numerous attempts such as a connection type of abutment-fixture, microthread, crestal module design, and abutment profile. Recently, one of the methods involves the development of a 1-piece implant. A 1-piece implant has many advantages in comparison with previous 2-piece implant. It is free of mechanical complications such as screw looseness, screw fracture, and fixture fracture. Also, in a biological aspect, absence of microgap, micromovement, and dis/reconnection of abutment leads to the stable maintenance of soft and hard tissue. However, 1-piece implants have limited indications. Selection of abutment is very strict and correction of the path is difficult after the installation of the fixture. Also, bone quality and primary stability are very important factors in 1-piece implants because it is based on immediate provisionalization. Although there are not many kinds of available 1-piece implants, one of the most well-known 1-piece implants is NobelDirectยฎ (Nobel Biocare). However, clinical results of NobelDirectยฎ are controversial and improvement is necessary. In most studies, it is reported that long term studies and improvements of implant design are required. Therefore, this research focuses on the advantages, design, clinical application and practical result of 1-piece implants.ope

    (The) influence of internal gap and type of cement on retention of zirconia coping

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    ์น˜์˜ํ•™๊ณผ/์„์‚ฌ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์˜ ํฌ๊ธฐ๋ฅผ ๋‹ค๋ฅด๊ฒŒ ์ œ์ž‘ํ•œ ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ์ฝ”ํ•‘์„ ๋™์ผํ•œ ํ˜•ํƒœ๋กœ ์‚ญ์ œ๋œ ์ž์—ฐ์น˜์— 3๊ฐ€์ง€ ์‹œ๋ฉ˜ํŠธ๋กœ ํ•ฉ์ฐฉ ์‹œ ์‹œ๋ฉ˜ํŠธ์˜ ์ข…๋ฅ˜ ๋ฐ ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์˜ ํฌ๊ธฐ์— ๋”ฐ๋ฅธ ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ์ฝ”ํ•‘์˜ ์œ ์ง€๋ ฅ ์ฐจ์ด๋ฅผ ๋น„๊ตํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ์ตœ๊ทผ ๋ฐœ๊ฑฐ๋œ 48๊ฐœ์˜ ์น˜์•„๋ฅผ computer aided design and manufacturing (CAD/CAM) ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ์ˆ˜๋ ด๊ฐ 20๋„, ๋†’์ด 2.5 mm์˜ ์ง€๋Œ€์น˜ ํ˜•ํƒœ๋กœ ์‚ญ์ œํ•˜์˜€๋‹ค. ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ์ฝ”ํ•‘ ์—ญ์‹œ CAD/CAM ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์˜ ํฌ๊ธฐ๋ฅผ 40 ใŽ›์™€ 160 ใŽ› ๋‘ ๊ตฐ์œผ๋กœ ๊ฐ๊ฐ 24๊ฐœ์”ฉ ์ œ์ž‘ํ•˜์˜€๋‹ค. ์ œ์ž‘๋œ ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ์ฝ”ํ•‘์˜ ๋‚ด๋ฉด์— 50 ใŽ› alumina particle๋กœ air-abrasion์„ ์‹œํ–‰ํ•œ ํ›„ 10-methacryloyloxydecyldihydrogenphosphate (MDP)๋ฅผ ํฌํ•จํ•œ ๋ ˆ์ง„ ์‹œ๋ฉ˜ํŠธ (Panavia F), ์ž๊ฐ€ ์ ‘์ฐฉ ๋ ˆ์ง„ ์‹œ๋ฉ˜ํŠธ (RelyX Unicem), ๋ ˆ์ง„ ๊ฐ•ํ™”ํ˜• ๊ธ€๋ž˜์Šค ์•„์ด์˜ค๋…ธ๋จธ ์‹œ๋ฉ˜ํŠธ (RelyX Luting)๋ฅผ ์ด์šฉํ•˜์—ฌ ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ์ฝ”ํ•‘๊ณผ ์ž์—ฐ์น˜๋ฅผ ํ•ฉ์ฐฉํ•˜์˜€๋‹ค. ํ•ฉ์ฐฉ๋œ ๋ชจ๋“  ์‹œํŽธ์€ 37โ„ƒ์—์„œ 24์‹œ๊ฐ„ ๋ณด๊ด€ ํ›„ 5โ„ƒ์™€ 55โ„ƒ์˜ ์—ด์ˆœํ™˜๊ธฐ์—์„œ 10,000ํšŒ์˜ ์—ด์ˆœํ™˜์„ ์‹œํ–‰ํ•œ ํ›„ universal testing machine์„ ์ด์šฉํ•˜์—ฌ crosshead speed 0.5 mm/min๋กœ ์น˜์•„์˜ ์žฅ์ถ•์„ ๋”ฐ๋ผ์„œ ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ์ฝ”ํ•‘์ด ์น˜์•„์—์„œ ํƒˆ๋ฝ๋  ๋•Œ๊นŒ์ง€ pull out test๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ์ˆ˜์ง‘๋œ ์ž๋ฃŒ๋Š” one-way ANOVA test์™€ two-way ANOVA test๋ฅผ ํ†ตํ•ด ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฅผ ์–ป์—ˆ๋‹ค. 1. RelyX Unicem๊ณผ RelyX Luting์€ ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์ด ์ฆ๊ฐ€ํ•ด๋„ ์œ ์ง€๋ ฅ์˜ ์ฐจ์ด๊ฐ€ ์—†์—ˆ์ง€๋งŒ Panavia F๋Š” ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์ด ์ฆ๊ฐ€ํ•˜๋ฉด ์œ ์ง€๋ ฅ์ด ํ˜„์ €ํžˆ ๊ฐ์†Œํ•˜์˜€๋‹ค.2. ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์˜ ํฌ๊ธฐ์— ์ƒ๊ด€์—†์ด ๋ ˆ์ง„ ์‹œ๋ฉ˜ํŠธ(RelyX Unicem, Panavia F)๋Š” ๋ ˆ์ง„ ๊ฐ•ํ™”ํ˜• ๊ธ€๋ž˜์Šค ์•„์ด์˜ค๋…ธ๋จธ ์‹œ๋ฉ˜ํŠธ(RelyX Luting)๋ณด๋‹ค ๋†’์€ ์œ ์ง€๋ ฅ์„ ๋ณด์˜€๋‹ค.3. ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์˜ ํฌ๊ธฐ๊ฐ€ 40 ใŽ› ์ธ ๊ฒฝ์šฐ ์œ ์ง€๋ ฅ์˜ ํฌ๊ธฐ๋Š” Panavia F > RelyX Unicem > RelyX Luting์˜ ์ˆœ์„œ์˜€์œผ๋‚˜, ๋‚ด๋ฉด ๊ฐ„๊ฒฉ์˜ ํฌ๊ธฐ๊ฐ€ 160 ใŽ› ์ธ ๊ฒฝ์šฐ๋Š” RelyX Unicem > Panavia F > RelyX Luting์˜ ์ˆœ์„œ๋กœ ์œ ์ง€๋ ฅ์˜ ํฌ๊ธฐ๊ฐ€ ๋‚˜ํƒ€๋‚ฌ๋‹ค.ope

    Influence of internal-gap width and cement type on the retentive force of zirconia copings in pullout testing

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    OBJECTIVES: The purpose of this study was to evaluate the influence of internal-gap width and cement type on the retentive force of zirconia copings. METHODS: A CAD/CAM system was used to mill 48 identical abutments on extracted human molars and fabricate 48 zirconia copings. The internal-gap width for cement was set to 40 ฮผm or 160 ฮผm (n=24 each). Three cement types (Panavia F, RelyX Unicem, and RelyX Luting) were used with each internal-gap width (n=8/cement type). The intaglio surfaces of the copings were airborne-particle abraded, and each coping was cemented onto the corresponding abutment using the indicated luting agent. After 10,000 cycles of thermocycling, the retentive force was evaluated by pullout tests. Kruskal-Wallis and Wilcoxon Rank Sum tests were used for data analysis (ฮฑ=0.05). RESULTS: In the 40-ฮผm gap groups, Panavia F had the highest mean retentive force compared to RelyX Unicem and RelyX Luting (P<0.000). In 160-ฮผm gap groups, RelyX Unicem had the highest mean retentive force compared to Panavia F and RelyX Luting (P<0.000). CONCLUSIONS: With the increase in internal gap width, a resin cement with self-etching agents as a co-initiator for autopolymerization resulted in significantly decreased retentive force, whereas a resin-modified glass ionomer cement or a self-adhesive resin cement did not. Use of resin cements rather than resin-modified glass ionomer cements improved the retentive force of zirconia copings regardless of the amount of internal gap width.ope

    Accuracy of implant impressions without impression copings: a three-dimensional analysis

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    STATEMENT OF PROBLEM: Implant impressions without impression copings can be used for cement-retained implant restorations. A comparison of the accuracy of implant impressions with and without impression copings is needed. PURPOSE: The purpose of this study was to evaluate and compare the dimensional accuracy of implant definitive casts that are fabricated by implant impressions with and without impression copings. MATERIAL AND METHODS: An acrylic resin maxillary model was fabricated, and 3 implant replicas were secured in the right second premolar, first, and second molars. Two impression techniques were used to fabricate definitive casts (n=10). For the coping group (Group C), open tray impression copings were used for the final impressions. For the no-coping group (Group NC), cementable abutments were connected to the implant replicas, and final impressions were made assuming the abutments were prepared teeth. Computerized calculation of the centroids and long axes of the implant or stone abutment replicas was performed. The Mann-Whitney U test analyzed the amount of linear and rotational distortion between groups (ฮฑ =.05). RESULTS: At the first molar site, Group NC showed significantly greater linear distortion along the Y-axis, with a small difference between the groups (Group C, 7.8 ยฑ 7.4 ฮผm; Group NC, 19.5 ยฑ 12.2). At the second molar site, increased distortion was noted in Group NC for every linear and rotational variable, except for linear distortion along the Z-axis. CONCLUSIONS: Implant impression with open tray impression copings produced more accurate definitive casts than those fabricated without impression copings, especially those with greater inter-abutment distance.ope
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