Rozprawy doktorskie na temat „REVERSIBLE MULTIPLIER”

Programmable reversible logic is emerging as a prospective logic design style for implementation in modern nanotechnology and quantum computing with minimal impact on circuit heat generation. Recent advances in reversible logic using and quantum computer algorithms allow for improved computer architecture and arithmetic logic unit designs. In this paper, a 2*2 Swap gate which is a reduced implementation in terms of quantum cost and delay to the previous Swap gate is presented. Next, a novel 3*3 programmable UPG gate capable of calculating the fundamental logic calculations is presented and verified, and its advantages over the Toffoli and Peres gates are discussed. The UPG is then implemented in a reduced design for calculating n-bit AND, n-bit OR and n-bit ZERO calculations. Then, two 3*3 RMUX gates capable of multiplexing two input values with reduced quantum cost and delay compared to the previously existing Fredkin gate is presented and verified. Next, 4*4 reversible gate is presented and verified which is capable of producing the calculations necessary for two-bit comparisons. The UPG and RC are implemented in the design of novel sequential and tree-based comparators. Then, two novel 4*4 reversible logic gates (MRG and PAOG) are proposed with minimal delay, and may be configured to produce a variety of logical calculations on fixed output lines based on programmable select input lines. A 5*5 structure (MG) is proposed that extends the capabilities of both the MRG and PAOG. The comparator designs are verified and its advantages to previous designs are discussed. Then, reversible implementations of ripple-carry, carry-select and Kogge-Stone carry look-ahead adders are analyzed and compared. Next, implementations of the Kogge-Stone adder with sparsity-4, 8 and 16 were designed, verified and compared. The enhanced sparsity-4 Kogge-Stone adder with ripple-carry adders was selected as the best design, and its implemented in the design of a 32-bit arithmetic logic unit is demonstrated. The proposed ALU design is verified and its advantages over the only existing ALU design are quantitatively analyzed.

Nous avons étudié expérimentalement les fluctuations de micro-particules browniennes piégées à l'aide de pinces optiques dans un réseau de puits de potentiels voisins. Nous donnons un descriptif général du montage expérimental, puis détaillons quatre utilisations différentes du système. Nous avons d'abord utilisé une unique particule dans un double puits de potentiel pour modéliser un système mémoire à deux niveaux, avec lequel nous avons vérifié le principe de Landauer sur le coût minimal en énergie pour l'effacement d'un bit d'information. Nous avons également appliqué une version détaillée d'un théorème de fluctuation à la procédure d'effacement de l'information pour retrouver la limite énergétique attendue. Nous avons ensuite étudié l'interaction hydrodynamique entre deux particules dont l'une est soumise à une température effective. Nous avons montré qu'il n'y a pas de fluctuations anormales lors de la transition sol-gel de la gélatine, contrairement à ce qui avait été observé précédemment, et que ce système ne pouvait donc pas être utilisé pour étudier des températures effectives. En revanche, nous avons montré que l'ajout d'un forçage aléatoire bien choisi sur la position d'un piège créait une température effective. Nous avons montré que le forçage d'une des particules résultait en une corrélation instantanée entre les mouvements des deux particules, et s'accompagnait d'un échange de chaleur de la particule virtuellement chaude à la particule froide en équilibre avec le bain thermique. Nous avons obtenu un bon accord entre les données expérimentales et les prédictions d'un modèle de couplage hydrodynamique. Enfin, nous décrivons l'utilisation de canaux micro-fluidiques pour réaliser un écoulement cisaillé à l'échelle micrométrique, et nous discutons de la possibilité d'interpréter un cisaillement en terme de température effective en testant une relation de fluctuation-dissipation
We experimentally study the fluctuations of Brownian micro-particles trapped with optical tweezers arranged in various spatial configurations. We give a general description of the set-up and detail four different experiments we conducted. We first use a single particle in a double-well potential to model a two-state memory system. We verify the Landauer principle on the minimal energetic cost to erase one bit of information, and we use a detailed version of a fluctuation theorem to retrieve the expected energetic bound. We then use two particles in two different traps to study the hydrodynamic interactions between two systems kept at different effective temperatures. Contrary to what was previously observed, we show that the sol-gel transition of gelatine does not provide any anomalous fluctuations for the trapped particle when the sample is quenched below gelification temperature. However, we show that an effective temperature is created when a well chosen random noise is added on one trap position. We demonstrate that the random forcing on one particle induces an instantaneous correlation between the two particles motions, and an energy exchange from the virtually hot particle to the cold one, which is in equilibrium with the thermal bath. We show a good agreement between the experimental data and the predictions from an hydrodynamic coupling model. Finally, we describe the use of micro-fluidic channels to create a shear flow at the micron size, and we discuss the possibility to interpret the force due to the shear-flow in terms of an effective temperature by testing a fluctuation-dissipation relation

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

In this thesis a number of statistical methods have been developed and applied to habitat suitability modelling for rare and threatened species. Data available on these species are typically limited. Therefore, developing these models from these data can be problematic and may produce prediction biases. To address these problems there are three aims of this thesis. The _rst aim is to develop and implement frequentist and Bayesian statistical modelling approaches for these types of data. The second aim is develop and implement expert elicitation methods. The third aim is to apply these novel approaches to Australian rare and threatened species case studies with the intention of habitat suitability modelling. The _rst aim is ful_lled by investigating two innovative approaches for habitat suitability modelling and sensitivity analysis of the second approach to priors. The _rst approach is a new multilevel framework developed to model the species distribution at multiple scales and identify excess zeros (absences outside the species range). Applying a statistical modelling approach to the identi_cation of excess zeros has not previously been conducted. The second approach is an extension and application of Bayesian classi_cation trees to modelling the habitat suitability of a threatened species. This is the _rst `real' application of this approach in ecology. Lastly, sensitivity analysis of the priors in Bayesian classi_cation trees are examined for a real case study. Previously, sensitivity analysis of this approach to priors has not been examined. To address the second aim, expert elicitation methods are developed, extended and compared in this thesis. In particular, one elicitation approach is extended from previous research, there is a comparison of three elicitation methods, and one new elicitation approach is proposed. These approaches are illustrated for habitat suitability modelling of a rare species and the opinions of one or two experts are elicited. The _rst approach utilises a simple questionnaire, in which expert opinion is elicited on whether increasing values of a covariate either increases, decreases or does not substantively impact on a response. This approach is extended to express this information as a mixture of three normally distributed prior distributions, which are then combined with available presence/absence data in a logistic regression. This is one of the _rst elicitation approaches within the habitat suitability modelling literature that is appropriate for experts with limited statistical knowledge and can be used to elicit information from single or multiple experts. Three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression are compared, one of which is the questionnaire approach. Included in this comparison of three elicitation methods are a summary of the advantages and disadvantages of these three methods, the results from elicitations and comparison of the prior and posterior distributions. An expert elicitation approach is developed for classi_cation trees, in which the size and structure of the tree is elicited. There have been numerous elicitation approaches proposed for logistic regression, however no approaches have been suggested for classi_cation trees. The last aim of this thesis is addressed in all chapters, since the statistical approaches proposed and extended in this thesis have been applied to real case studies. Two case studies have been examined in this thesis. The _rst is the rare native Australian thistle (Stemmacantha australis), in which the dataset contains a large number of absences distributed over the majority of Queensland, and a small number of presence sites that are only within South-East Queensland. This case study motivated the multilevel modelling framework. The second case study is the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The application and sensitivity analysis of Bayesian classi_cation trees, and all expert elicitation approaches investigated in this thesis are applied to this case study. This work has several implications for conservation and management of rare and threatened species. Novel statistical approaches addressing the _rst aim provide extensions to currently existing methods, or propose a new approach, for identi _cation of current and potential habitat. We demonstrate that better model predictions can be achieved using each method, compared to standard techniques. Elicitation approaches addressing the second aim ensure expert knowledge in various forms can be harnessed for habitat modelling, a particular bene_t for rare and threatened species which typically have limited data. Throughout, innovations in statistical methodology are both motivated and illustrated via habitat modelling for two rare and threatened species: the native thistle Stemmacantha australis and the brush-tailed rock wallaby Petrogale penicillata.

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Multiplier is one of the important block in almost all the arithmetic logic units. These multipliers are mostly used in the fields of the Digital Signal Processing (DSP), Fast Fourier Transform, convolution, filtering and microprocessor applications. A system's performance is generally determined by the performance of the multiplier, because the multiplier is generally the slowest element in the system. Furthermore, it is generally the most area consuming. Hence, optimizing the speed and area of the multiplier is a major design issue. Since multiplier is the main component and hence a high speed and area efficient multiplier can be achieve by using Vedic mathematics. In this work we have implemented the Vedic multiplier using Chinese Abacus Adder with and without using Reversible logic gates. Reversible logic is one of the promising fields for future low power design technologies. Since one of the requirements of all DSP processors and other embedded devices is to minimize power dissipation multipliers with high speed and lower dissipations are critical. This work is devoted to the design of a high speed Vedic multiplier using reversible logic gates. For arithmetic multiplication, various Vedic multiplication techniques like Urdhva Tiryakbhyam, Nikhilam and Anurupye have been thoroughly discussed. It has been found that Urdhva Tiryakbhyam Sutra is the most efficient Sutra (Algorithm), giving minimum delay for multiplication of all types of numbers, either small or large. Further, the Verilog HDL coding of Urdhva Tiryakbhyam Sutra for 32x32 bits and 64x64 bits multiplication and their FPGA implementation by Xilinx Synthesis Tool on Spartan 3E kit have been done. The synthesis results show that the computation time for calculating the product of 4x4 multiplication is less as compared with other conventional multipliers.

碩士
國立臺灣大學
數學研究所
107
Chen and Hwang, 2013 proposed to improve a reversible Markov chain by adding an antisymmetric perturbation on a cycle. Since the perturbed Markov chain is no longer reversible, one can not iteratively apply this antisymmetric perturbation method on different cycles. Chen and Hwang, 2013 also showed that the method works on disjoint cycles. In this paper, we further investigate the case of two cycles sharing the same vertex. We will show that the method can work on two cycles under some additional conditions. In addition to the theory, we implement the antisymmetric perturbation method on the Ising model.

碩士
國立雲林科技大學
資訊工程系
103
This thesis proposes a novel reversible data hiding technique based on multiple diffusion. To achieve a better distribution of pixel values, we first use the Torus automorphism permutation scheme and the modified EMD scheme to change pixel’s location and value. Then, encrypt the resultant image by the selected encryption scheme. This thesis proposed two encryption schemes to analyze. The secret messages are embedded by the dual image reversible data hiding scheme; With the encrypted image and different sets of keys, the receiver can extract the following different informations: (1) the secret messages only; (2) an inferior quality of the image; (3) the secret message and the original image. In this thesis, we also researched irreversible data hiding and encryption scheme on images which are not require high quality. Using the GMEMD scheme to embed the secret messages, and encrypt it by the proposed scheme. In the extraction phase, with the feature of the GMEMD scheme we can directly extract the secret messages without any processing. But we cannot recover the original image after decryption. Experimental results show that the proposed schemes has a lower correlation between two adjacent pixels and a better uniform distribution of pixel values compared to other schemes. Thus, it can effectively resist histogram attack. In addition, we are able to decide the quality of the extracted image and whether can extract the secret messages or not by giving the receiver different sets of keys.

博士
臺灣大學
電子工程學研究所
98
Reversible circuits have applications in many areas such as digital signal processing, low power design, and quantum computing. If a circuit is reversible, it can reduce the energy consumption caused by information loss. The Karnaugh map method is faster and easier to apply than other simplification methods for combination logic circuits. But the classical Karnaugh map is not directly applicable to reversible circuits because the basic logic gates, except the NOT gate, are not reversible gates. In this dissertation, we propose a method to solve the problem so that the Karnaugh map can be applied to the reversible circuit synthesis. Our algorithm provides a systematic method for simplifying the reversible circuit. This can generate the resulting expression in exclusive-sum form and transform it into a final reversible circuit with lower quantum cost. Moreover, we can realize permutations to be reversible circuits with lower quantum cost and without unnecessary garbage bits. We can also convert irreversible circuits by adding qubits to make the circuits reversible. The experimental results show that the average saving in quantum cost is 15.82% compared with previous approaches. So far there are no synthesis algorithms that can find all the optimal reversible circuits except an exhaustive algorithm. We propose a method based on the divide and conquer approach which can significantly improve the performance of the existing synthesis algorithms to synthesize reversible circuits. A reversible circuit is first divided into two subcircuits. The smaller subcircuit will input all possible combinations of m gates, except for those combinations with the same functionality only the one with fewest gates is selected for input. The other subcircuit can be synthesized with an existing algorithm. The two subcircuits are then combined to form all the possible results and from these results we can choose the most simplified one. According to the experimental results on all the 3-variable reversible functions, we can see that the performance of the existing algorithms can be significantly improved by using our method. Therefore the synthesized reversible circuits are much more simplified than previous results. Moreover, in order to efficiently represent a quantum operation, we propose X-decomposition Quantum Decision Diagram (XQDD) which can easily perform matrix operations. XQDD can be used to verify quantum and reversible circuits even if the reversible circuits have different number of garbage qubits. It is more efficient in terms of space and time. We extend the binary-valued XQDD to multiple-valued quantum logic. The extended XQDD can represent a multiple-valued quantum operation and perform matrix operations. It can be applied to verify the equivalence of two multiple-valued quantum or reversible circuits which are synthesized by different approaches. According to the simulation results, it is much better than multiple-valued QuIDD and very close to QMDD in terms of time. Besides, we show that the space in multiple-valued XQDD is less than other representations. Finally, previous quantum secure direct communication (QSDC) protocols usually consume one Einstein-Podolsky-Rosen (EPR) pair to transmit a single qubit. If Alice wants to transmit an n-bit message, she needs at least n/2 EPR pairs when dense coding scheme is used. We propose a new QSDC protocol based on EPR pairs. If both Alice and Bob pre-share 2c+1 EPR pairs with the trusted server where c is a constant, Alice can transmit arbitrary number of qubits to Bob. The 2c EPR pairs are used by Alice and Bob to authenticate each other and the remaining EPR pair is used to encode and decode the message qubit. Thus the total number of EPR pairs used for one communication is a constant no matter how many bits will be transmitted. It does not need to transmit EPR pairs before transmitting the secret message except the pre-shared constant number of EPR pairs. It reduces both the utilization of the quantum channel and the risk. In addition, after the authentication, the server is not involved in the message transmission. Thus we can prevent the server from knowing the message.

碩士
逢甲大學
通訊工程所
99
Data hiding technique is mainly embedding the secret messages using a meaningful digital media as a cover, that other people cannot detect the existence of the secret messages. The technology of reversible data hiding has many typical applications, such as related fields of medical and military. The technology of reversible data hiding using multiple steganographic can be used to achieve a hidden secret communication behavior of secret sharing techniques. In 2009, Lee et al. proposed a novel reversible data hiding based on dual steganographic images. Their main idea is to disperse the secret messages hiding in two identical cover images and to produce two different stego-images. Thus the people must also have two stego-images who can extract the secret messages completely. According to Lee et al.’s embedding algorithm, there is 0 bit, 2 bits or 4 bits embedded into four pixels. The average of capacity is about 0.75 bpp and PSNR is about 52.3 dB. In this paper, we propose a method to improve the algorithm proposed by Lee et al. In our proposed method, not only using three identical cover images to produce three different stego-images, but also ensure that can embed 4 secret bits into three pixels without overflow. Thus our method not only obtains higher capacity (about 1.333 bpp) but also preserves pretty good image quality (about 49.77 dB).

碩士
國立宜蘭大學
化學工程與材料工程學系碩士班
107
In this work we prepared peroxide crosslinked OBC/PCL blends with different ratios of olefin block copolymer (OBC) and polycaprolactone (PCL). The gel contents of blends were above 98 % after adding 2 phr peroxide, and this strong polymer network is beneficial for shape memory. The 2DXRD (Two-dimensional X-Ray Diffractometer) patterns revealed the stress-induced orientation of crystalline regions in the two-way shape memory with applied load. In the one-way shape memory results, the fixing ratios of the blends were above 95 %, and the recovery ratios of the blends were above 96 %. The samples had the reversible two-way shape memory effect under external force. Additionally, the blends demonstrated the triple-shape reversible shape memory behavior because OBC and PCL had two distinct melting/crystallization temperatures. They also had the reversible shape memory behavior under stress-free condition after programming. The optimized blend of OBC/PCL D2 40/60 with the absolute reversible strain change of 7.7 % and the relative reversible strain change of 17.5 % was prepared after 300 kPa programming. These blends achieved the effect by partially melting the crystals of PCL to improve the narrow range of melting temperature in the respective neat resin. In chemo-induced shape memory effect, we discovered that the deformed samples had the reversible shape change owing to the solvent-induced inhomogeneous swelling/crystallization, which was different from those previous reported literature work requiring additional pre-soaking treatment. The results showed that the higher content of PCL to increase the reversible angle was more significant in both THF and acetone vapor environment, and these phenomena showed a similar tendency in solvent uptake. Furthermore, the addition of multi-walled carbon nanotube (CNT) in blends showed the reversible shape memory behavior by near-infrared laser irradiation.

Modern technologies have eased the way for adversaries to bypass the conventional identity authentication and identification processes; hence security systems have been developed to a great extent for protection of privacy and security of identities in different applications. The focus of this thesis is digital watermarking, security and privacy, as well as the ability to employ electrocardiogram as a method to enhance the security and privacy level. A high capacity reversible multiple watermarking scheme is introduced to mainly target the medical images. Furthermore, the use of ECG biometric signals in the form of the embedded watermark is studied. Experimental results indicate that the reversible data hiding scheme outperforms other approaches in the literature in terms of payload capacity and marked image quality. Results from the ECG mark embedding also show that no major degradation in performance is noticeable compared to the case where no watermarking is needed.

碩士
玄奘大學
資訊管理學系碩士班
101
We proposed an application for reversible information hiding in multiple secret images sharing based on Shamir’s method. Many researchers develop secret image sharing method with Shamir’s scheme in one image. We mixed the multiples secret images with one host image and employ the modified Shamir’s method to share the participants. Lagrange method is applied with enough numbers of the shadow images in the retrieval step. The experiment results demonstrate our method can retrieve secret images lossless.

碩士
國立屏東教育大學
資訊科學系碩士班
102
Reversible data hiding based on prediction methods is a good technique that can hide secret bits into cover images efficiently. In this study, we propose a reversible data hiding method based on multiple prediction methods and local complexity. In our proposed method, before we embed the secret message in one level, we evaluate four prediction methods by two ways to decide which prediction method will be used. First, if we want to achieve high-capacity, the prediction methods’ capacities are calculated. Second, if we want to achieve high-quality, the prediction methods’ efficiency ratios are calculated. When the selected prediction method is applied, a threshold based on local complexity is used to determine which pixel should join the shifting and embedding process. If the local complexity is smaller than the threshold, the pixel will be taken for message hiding or pixel shifting; otherwise, the pixel will quit joining the process of data concealing and pixel shifting. Therefore, more pixels will avoid executing the process of pixel shifting. It results to the stego-images with lower distortion. The experimental results show that our embedding capacity and quality are superior to other approaches.